# Quantum Atlas · AI / LLM Wiki [Interactive Quantum Atlas](https://universalmind.tv/informatics/quantum/) · [AI / LLM Wiki](https://universalmind.tv/informatics/read/quantum/index.html) ## What Quantum Atlas is for Quantum Atlas makes computational biology and quantum research approachable through a scientific question written in ordinary language. A person brings the question; the platform coordinates AI scientific work, mathematical models, simulations, recorded quantum measurements and biological evidence, then returns an explanation with the underlying research record. The purpose is to help people investigate whether a proposed pattern adds useful information to a biological problem. The current OXTR investigation asks whether Fibonacci, Phi Ratio and M9 P24 representations can help predict where proteins associate with DNA. That study is the first worked investigation within the wider natural-language research experience. ### Explain this to a person You can ask Quantum Atlas a biological research question without writing quantum code. Astra develops the supported investigation and explains the findings. Gemini reviews the design and the resulting report. Mathematical and computing tools supply calculations and measurements, while laboratory evidence provides a biological comparison. You can follow the stages, inspect the geometry, read the results in ordinary language and download the record. Your own AI can retrieve the public evidence through MCP or the API, or ask Universal One a research question through A2A. A persistent new study starts through the Quantum Atlas interface within its supported research scope. ### Guidance for an AI explaining the page - Begin by explaining the purpose and the person’s research goal before listing providers or discussing the saved OXTR numbers. - Explain each feature in terms of what the person can ask, see, learn or retrieve. Define simulation, quantum measurement and biological comparison when those terms first appear. - Describe the agent roles and handoffs, then identify the connection method that fits the person’s request. - Use the current saved results to illustrate the workflow. Keep the platform’s wider purpose distinct from the outcome of its first study. - Describe available participation separately from extensions in development. Use the live tool schema and agent card to determine available operations. ### Questions a person can ask - What is Quantum Atlas for, and how can it help me investigate a biological question? - Explain what Astra, Gemini, Wolfram, CUDA-Q and Aquila each contribute, in plain language. - Walk me through the current OXTR investigation and explain what the results mean. - Connect to the public research tools, retrieve the study and help me formulate a useful next question. ## What each feature helps a person do **Quantum Atlas feature guide** | Feature | Purpose | Value for the person | | --- | --- | --- | | Ask a question | Express the biological question in everyday language. The router identifies a supported calculation or a concrete missing capability. | A clear starting point without writing quantum code. | | Study and live workflow | Show the question, scientific plan, agent progress and the role of each calculation or evidence source. | Understand what is happening and how each stage contributes. | | Geometry explorer | Inspect Alpha, Beta, Gamma and Epsilon definitions and the different numerical preparations of the same DNA inputs. | See what is being compared before interpreting its response. | | Design and findings reviews | Gemini checks the proposed method before calculations and checks the findings against the evidence before delivery. | See the review decision, requested corrections and retained evidence. | | Classical results | Inspect calculation checks, CUDA-Q simulation results and the genomic prediction comparison. | Understand the computational baseline and what a prediction score means. | | Quantum results and Compare | Inspect the recorded Aquila readings beside matched calculated and simulated values, with their counts and uncertainty. | Understand how the physical device behaved and how that relates to the research question. | | Insights and next test | Return a direct answer, what was completed, the practical meaning, and the remaining research dependency. | Learn from the investigation and identify a useful next step. | | Saved studies and downloads | Retain task progress and provide the complete report in JSON and CSV. The Wiki adds a Markdown reading guide. | Reopen work, inspect methods, discuss it with another AI or reproduce the analysis. | | Shared capacity | Display the available question allowance and keep execution within the recorded scope and funding. | Know when the service can accept another investigation. | | Drug Discovery Network and Open Source Genomic Insights | The planned fifth stage connects reviewed findings with external research collaborators and shareable genomic insights. | Understand the intended path from an investigation to research collaboration. This stage is marked as a future feature. | ## Quantum / AI agent swarm: who does what Astra and Gemini have distinct scientific roles. LangGraph coordinates their work and the specialist calculation services through an explicit, persistent workflow. The diagram on the Quantum page presents the scientific handoffs: formulate, model, simulate and measure, compare with biological evidence, then interpret. **Scientific roles and handoffs** | Agent or service | Role | Work | Handoff | | --- | --- | --- | --- | | GPT-6 Astra | Head bioinformatician and scientist | Interprets the question, selects the supported study plan, coordinates the authorised calculations, responds to review feedback and writes the evidence-grounded explanation. | Proposed plan to Gemini; calculated evidence and draft report to Gemini; reviewed findings to the person. | | Gemini 4 Argon | Chief Scientist | Reviews the design and final findings against the supplied methods, measurements, source records and uncertainty. Returns approve, revise or human decision required. | Design feedback to Astra before execution; findings feedback before report delivery. | | LangGraph | Workflow orchestration and persistent state | Orders the steps, checkpoints completed work, routes review decisions, bounds revision loops and preserves progress when a dependency interrupts execution. | Controls the transition between planning, review, calculations, report and completion. | | Wolfram Quantum Framework | Mathematical specification and reference checks | Provides the mathematical reference role shown in the workflow. The current continuation retains the saved Wolfram check receipts for the original model. | Checked model definitions and reference calculations inform the matched simulation and hardware interpretation. | | NVIDIA CUDA-Q | Quantum-program preparation and simulation | Compiles and simulates the defined quantum model. The original study used qBraid GPU simulation; the continuing recipe performs local CPU CUDA-Q checks on the cloud worker. | Compiled programs, simulated observables and numerical-check receipts. | | qBraid and NVIDIA GPU | Recorded GPU execution route | Executed the saved CUDA-Q compiled programs on the documented GPU service. Those measurements and receipts remain available for comparison. | Recorded GPU samples and execution identity into the study evidence. | | QuEra Aquila via Amazon Braket | Recorded physical quantum measurement route | The saved analog programs ran on Aquila’s neutral atoms through Braket. Their task receipts identify the actual hardware measurements. | Hardware counts, usable shots, observables and timestamps into the comparison. | | Biological evidence and classical benchmarks | Test biological usefulness | Reference DNA, ENCODE binding observations and JASPAR motifs support the held-out prediction comparison. Fixed classical code calculates the scores and uncertainty. | Computed biological results and source provenance to Astra and Gemini. | | Research memory and Universal One | Shared research context and public research conversation | Astra retrieves mission, experiment and research-direction records plus literature from the research repository. Universal One exposes cited research answers and public evidence access. | Versioned sources to the scientific workflow and to an external AI using the public interfaces. | | Cloudflare broker, AWS worker and encrypted storage | Durable execution and delivery | The broker tracks session-owned tasks and worker leases. AWS Lambda executes the supported recipe; SQLite checkpoints and encrypted S3 preserve progress and results. | Progress events and the completed report return to the originating research session. | ## How the investigation moves through the system **Interactive workflow diagram: exact explanations from the Quantum page** | Stage | Heading | Explanation | | --- | --- | --- | | question | Begin with your biological question. | GPT uses the Atlas definitions and saved study recipe to select the calculation. Select a step to inspect its role. | | model | One model, two matched routes. | Wolfram checks the mathematical specification. The same coordinates, interactions, pulses and measurement conventions feed CUDA-Q and the Aquila program. | | simulation | Predict the quantum response with CUDA-Q. | CUDA-Q generates the matched simulation. The documented GPU route uses qBraid for supported compiled programs. | | hardware | Measure the response on Aquila. | Amazon Braket submits the approved analog program to QuEra Aquila. Actual queued, running, completed and failed states belong to a saved task receipt. | | evidence | Let independent observations test the prediction. | Build and adjust the prediction methods using one set of DNA regions. Then keep the methods unchanged and predict binding on different regions. Compare those predictions with laboratory results kept hidden until the predictions are complete. | | result | Return the biological finding. | A completed result combines a plain-language finding, uncertainty and an interactive geometry comparison. Methods, source versions and execution receipts remain available on demand. | 1. Question and routing: The person submits a question. The router selects the supported OXTR continuation recipe or another supported route. A persistent study receives an identity and a saved task record. 2. Retrieve context: Retrieve the mission, research directions, immutable experiment records and relevant literature. 3. Audit existing evidence: Check the saved CUDA-Q, Aquila and mathematical-reference records before using them. 4. Astra prepares the plan: Frame the supported calculation around the original question and the available evidence. 5. Gemini reviews the design: An approval advances to calculations. A revision returns the plan to Astra; an unresolved decision saves the dependency. 6. Prepare the biological comparison: Prepare reference DNA and the existing laboratory binding map using the fixed cohort recipe. 7. Run classical analysis: Train and select the methods on separate chromosomes, then evaluate OXTR and calculate the recorded metrics and uncertainty. 8. Prepare and check quantum programs: Prepare the matched DNA pair in eight representations and run 16 local CPU CUDA-Q program checks. Reuse the saved GPU and Aquila measurements. 9. Astra explains the findings: Answer the person’s original question using the calculated evidence, source context and remaining dependency. 10. Gemini reviews the findings: Check the report against the evidence packet. A requested revision returns to Astra; approval permits delivery. 11. Deliver the research record: Save the reviewed report and complete JSON/CSV, then show the findings in the Quantum Atlas research session. ### Reviews, interruptions and recovery The current recipe allows one design revision and one report revision. Unsupported questions or unresolved review decisions pause with a stated dependency. Closing the browser does not cancel a durable task; the saved study can be reopened. Cancellation and resume operate on that research session’s own study. ### Current execution and recorded measurements The current continuation uses the saved GPU/Aquila results and performs new classical and local CPU CUDA-Q calculations. Fresh Aquila jobs, paid GPU jobs and a fresh Wolfram kernel run are outside this recipe. The workflow labels recorded hardware evidence separately from current task progress. ### Research memory and provenance The shared research memory combines mission, research directions, versioned experiments and source-linked literature. Retrieval uses semantic and text search. The report retains the retrieved source context and evidence hashes. A delivered study contains the original question, plan and provider receipts, review decisions and evidence packets, source provenance, calculations, program checks and complete JSON/CSV. A private task report becomes a public experiment only through the separate reviewed publication process. ### The wider collaboration architecture The broader swarm prototype includes mid-study scientific support, human-interruption routing and a publication outbox for Synapse and DeSci. Integrating those general adapters into every live recipe, public MCP/A2A study dispatch, optional document destinations and the Drug Discovery Network remain extensions. The live fixed recipe already includes Gemini design and final review. ## How another AI can participate An external AI can explain the features to its human, retrieve and analyse the public research record, compare methods and help formulate a question. MCP exposes research tools. The REST API exposes the same records as JSON. A2A sends a research question to Universal One and returns its cited answer. The Quantum Atlas interface starts and follows a persistent scientific investigation. **Choose the participation route** | Route | Purpose | Entry point | Access | | --- | --- | --- | --- | | Read the Wiki or downloads | Explain the page and its research architecture; discuss a saved study with a person. | https://universalmind.tv/informatics/read/quantum/index.html | Public reading | | MCP | Give an AI structured tools for study records, geometry, publications and reusable passages. | https://informatics-universal-one.universalmind.workers.dev/mcp | No API key for these public read-only tools | | REST API | Retrieve exact JSON records from an application, script or AI tool. | https://informatics-universal-one.universalmind.workers.dev/api/v1/openapi.json | Public read-only API | | A2A | Let an external agent ask Universal One a self-contained research question and receive a cited answer. | https://informatics-universal-one.universalmind.workers.dev/.well-known/agent-card.json | Public interface; shared request limits apply | | Quantum Atlas research session | Submit a supported investigation, follow Astra/Gemini progress and retrieve the session-owned report. | https://universalmind.tv/informatics/?entry=research&area=quantum | The site establishes the browser research session automatically | [Connection setup guides and client examples](https://universalmind.tv/informatics/connect.html) ## Connect research tools through MCP MCP lets an external AI request structured research records as tools inside its own conversation. [Public MCP endpoint](https://informatics-universal-one.universalmind.workers.dev/mcp) HTTP JSON-RPC; responses are JSON. The endpoint accepts application/json and text/event-stream in Accept. ```json { "Content-Type": "application/json", "Accept": "application/json, text/event-stream", "MCP-Protocol-Version": "2025-11-25" } ``` 1. Initialize the connection and send notifications/initialized. 2. Discover tools/list and use the returned input schemas. 3. Call get_inventory for the current dataset version and scope. 4. Call get_quantum_study with id oxtr-qrc-01 and section summary, then request the relevant sections. 5. Follow measurements.data.page.nextOffset until it is null. Use get_atlas_record for canonical sequence definitions and search_publications/get_publication for source research. 6. Return a human explanation that cites the record URL, study ID, sourceSHA256 and the appropriate evidence status. **Discoverable MCP tools** | Tool | Purpose | | --- | --- | | get_quantum_study | Read the recorded OXTR Quantum Atlas experiment, sequence definitions, actual measurements, comparison, timing, next test and downloads. | | search | Find publication and Atlas record IDs. Fetch records before making study-specific claims. | | fetch | Fetch an approved publication or Atlas overview from a search result ID. Atlas analysis sections are accessible through get_atlas_record; the URL returns the complete record. | | get_inventory | Exact current counts, dataset version and access scope. | | search_publications | Search approved publication records. OR within each filter; AND across filters. Paginate using nextOffset. | | get_publication | Read an approved publication by ID, DOI or PMID. Preserve quotations and evidence status. | | get_passages | Read CC BY or CC0 full-text passages. Preserve attribution and licence. Other full texts are unavailable through this public connector. | | list_atlas_records | Search or list all M1–M1001 records or the M9 family. Commentary is searchable. A family result is mathematical, not biological evidence. | | get_atlas_record | Read Atlas commentary, analysis, probability, hypotheses and nested sequences. Default summary lists section paths. Request a dotted section path for detail. Large objects return field paths; arrays use offset and limit. Full canonical data is available at the returned API URL. | ### Connection and study-reading requests ```json { "jsonrpc": "2.0", "id": 1, "method": "initialize", "params": { "protocolVersion": "2025-11-25", "capabilities": {}, "clientInfo": { "name": "quantum-atlas-reader", "version": "1.0" } } } ``` ```json { "jsonrpc": "2.0", "method": "notifications/initialized" } ``` ```json { "jsonrpc": "2.0", "id": 2, "method": "tools/list", "params": {} } ``` ```json { "jsonrpc": "2.0", "id": 3, "method": "tools/call", "params": { "name": "get_inventory", "arguments": {} } } ``` ```json { "jsonrpc": "2.0", "id": 4, "method": "tools/call", "params": { "name": "get_quantum_study", "arguments": { "id": "oxtr-qrc-01", "section": "summary" } } } ``` ```json { "jsonrpc": "2.0", "id": 5, "method": "tools/call", "params": { "name": "get_quantum_study", "arguments": { "id": "oxtr-qrc-01", "section": "measurements", "offset": 0 } } } ``` Read structuredContent when present, otherwise parse the JSON text in content. Check isError and JSON-RPC errors before interpreting a response. The current MCP tool schema lists eight Quantum sections. The API also exposes continuation, which contains the later classical pilot and local CUDA-Q findings. Retrieve that section through the REST URL below; discover the current MCP schema before selecting a section. ### REST API alternatives [Openapi](https://informatics-universal-one.universalmind.workers.dev/api/v1/openapi.json) [Inventory](https://informatics-universal-one.universalmind.workers.dev/api/v1/inventory) [Study summary](https://informatics-universal-one.universalmind.workers.dev/api/v1/quantum/oxtr-qrc-01?section=summary) [Study continuation](https://informatics-universal-one.universalmind.workers.dev/api/v1/quantum/oxtr-qrc-01?section=continuation) [Study measurements](https://informatics-universal-one.universalmind.workers.dev/api/v1/quantum/oxtr-qrc-01?section=measurements&offset=0) [Geometry](https://informatics-universal-one.universalmind.workers.dev/api/v1/atlas/fibonacci-m9-p24?section=full) ## Ask Universal One through A2A A2A lets one agent send a research question to Universal One and receive its answer with source references. [Discover the public agent card](https://informatics-universal-one.universalmind.workers.dev/.well-known/agent-card.json) [A2A JSON-RPC endpoint](https://informatics-universal-one.universalmind.workers.dev/a2a/v1) ```json { "Content-Type": "application/json", "A2A-Version": "1.0" } ``` ```json { "jsonrpc": "2.0", "id": 1, "method": "SendMessage", "params": { "message": { "messageId": "quantum-atlas-explanation-1", "role": "ROLE_USER", "parts": [ { "text": "Read the current OXTR quantum study. Explain its research question, the roles of simulation, Aquila measurements and the classical biological comparison, and what the findings mean for a person considering the next experiment. Cite the source records." } ] } } } ``` Read result.message.parts for the answer and result.message.metadata.sources for citations. Include the relevant context in each new message. The current A2A agent returns a direct research answer. Persistent task dispatch, streaming and push notifications are outside its advertised capabilities. MCP and A2A do not submit new Aquila jobs or create the browser’s persistent Astra study. ### From an AI conversation to a new investigation For a new persistent investigation, help the person frame the question and open Quantum Atlas. The site establishes its research session, submits the question and tracks the resulting study. Keep the public research connector separate from the session-owned execution service. Retain study IDs, immutable revision URLs, source hashes, provider receipts and review status when moving between agents. Link the evidence that supports the explanation, and preserve the original question throughout the handoff. ## Worked example: the recorded OXTR study ## Reading this record Read the saved study phases in order: original qualification runs, completed classical genomic pilot, further local CPU checks, then the proposed next quantum test. Retain the source labels for calculated values, GPU simulations, Aquila measurements, mathematical relationships and proposed mechanisms. This guide includes the saved chart data and interpretations. The linked immutable experiment revisions retain the complete inputs, methods, measurements, receipts and field guides. The guide is a dated snapshot, not a report of a visitor’s active question. ## Study question Do quantum responses generated from Fibonacci and M9 P24 representations improve our ability to predict transcription factor occupancy around OXTR? ## Geometry explanations ### fibonacci Successive Fibonacci ratios approach the Phi Ratio. This is an exact limiting relationship. It does not by itself specify a physical arrangement of atoms. ### modular M9 P24 means nine residue classes in a 24-step cycle. The Atlas places period positions on a circle; Gamma and Epsilon visit six equally spaced positions. M1–M1001 lets us compare modular representations. These are mathematical coordinates, not nine physical spatial dimensions. ### odom Odom’s construction gives MP/MN = φ exactly: M and N bisect two sides of an equilateral triangle, and the ray MN meets its circumcircle at P. A regular tetrahedron has equilateral faces, so this construction applies within each face. ### honeycomb Hales proved that regular hexagonal tiling minimizes boundary length when the plane is divided into equal-area cells. This is a geometric efficiency theorem; it does not establish quantum stability or minimum energy for every physical system. ### quantum Working hypothesis: does the hexagonal structure associated with these representations contribute to quantum coherence? A direct test varies pulse ordering and atom geometry independently, with matched controls and a coherence measurement. The Nature study supports Fibonacci-driven quantum effects; it does not establish this geometric mechanism. ## Saved study interpretations ### classical { "title": "The calculation check passed.", "finding": "Before using a quantum machine, we checked that the program calculates the six-atom experiment correctly. Independent calculations agreed within the recorded error limits.", "insights": [ { "title": "What counted as a pass?", "text": "The simulation had to agree with a separate calculation of the same six atoms. The recorded numerical limit was 0.1 percentage points; the measured largest difference was about 0.006 percentage points." }, { "title": "What this lets us do", "text": "Use the checked program in the next prediction experiment. The test for that experiment is whether it finds known protein-binding regions more accurately." } ] } ### simulation { "title": "CUDA-Q passed the calculation check.", "finding": "We used two short DNA samples near OXTR. For each sample, we prepared its numerical measurements in eight ways: ordinary measurements, Fibonacci numbers, Phi Ratio, Alpha, Beta, Gamma, Epsilon and a shuffled comparison. That made 16 CUDA-Q programs. The GPU results passed the calculation check. The DNA sequences themselves stayed unchanged.", "insights": [ { "title": "The goal of this first check", "text": "Verify that CUDA-Q runs the intended six-atom experiment. A result outside the agreed error limits means we stop and fix the calculation before relying on it." }, { "title": "What “calculated” means in the charts", "text": "It is the predicted atom behaviour from a separate computer calculation with hardware noise left out. It is a comparison value, not a target for biological success." }, { "title": "What happened with the sequences?", "text": "The computer calculation predicted more excited-state readings for Gamma and Epsilon in both samples, and fewer for Alpha and Beta. The 100-shot GPU samples vary around those predictions." }, { "title": "What earns a positive biological result?", "text": "CTCF is one transcription factor, a protein that binds DNA. The completed classical pilot tested predictions against CTCF laboratory measurements. It found no clear gain from Fibonacci spacing and Phi Ratio. The next quantum test asks whether the atom readings improve those predictions, including M9 P24, beyond ordinary and shuffled inputs." } ] } ### quantum { "title": "Aquila returned all 16 runs. Agreement with the calculation was mixed.", "finding": "The machine returned usable readings for every program. Alpha and Beta gave fewer excited-state readings in both samples, as the computer calculation predicted. Gamma and Epsilon gave more in sample 1 but fewer in sample 2.", "insights": [ { "title": "Was this the result we wanted?", "text": "We wanted usable measurements from every program. We got them. We also wanted to see how closely the machine followed the calculation; that agreement was mixed." }, { "title": "Does “fewer” mean better?", "text": "No. It means fewer atoms were read in the excited state. “As predicted” means the calculation also said fewer. It does not mean better protein-binding prediction." }, { "title": "What needs checking again?", "text": "Repeat the same inputs with the run order mixed up. If the Gamma and Epsilon differences persist beyond measurement variation, investigate hardware effects and the program before interpreting them biologically." }, { "title": "What is the next biological test?", "text": "Astra has completed the first classical comparison against known CTCF-binding regions. Next, test whether the quantum readings add predictive value. Keep ordinary and shuffled controls: the shuffled version also produced a large atom response in this first batch." } ] } ## Completed genomic follow-through ### answer There is no demonstrated benefit yet for predicting binding around OXTR. Adding Fibonacci and Phi Ratio features gave an inconclusive result. The new classical test did not evaluate biological prediction by M9 P24 Alpha, Beta, Gamma or Epsilon. This pilot concerns CTCF, one DNA-binding protein measured in one stem-cell context, not transcription factors generally. ### what_we_did The agent completed a comparison of ordinary DNA binding-pattern and spacing features, with and without Fibonacci/Phi Ratio features. It learned on chromosome 1, chose the method on chromosome 2 and tested OXTR on chromosome 3, without seeing OXTR laboratory answers during learning or selection. The agent also prepared a new matched pair of DNA windows: one overlapping a reported CTCF peak and one comparison window. For each, it compiled the same DNA eight ways—ordinary, Fibonacci, Phi Ratio, Alpha, Beta, Gamma, Epsilon and shuffled controls—and completed 16 local CUDA-Q CPU checks. ### meaning At OXTR, average precision rose from 0.0719 to 0.0739. This is a ranking score, not percent accuracy. The uncertainty range for the change extended from −0.0263 to +0.0082, leaving benefit unresolved; the noisy increase establishes no advantage. The pilot covered only five OXTR peak regions and used laboratory data with quality warnings. Saved CUDA-Q/Aquila readings describe programmed atom excitation, not binding probabilities; the two saved samples overlap none of those peaks, so they do not validate binding prediction. The new matched pair checks programs, not predictive performance. ### next_dependency A larger quantum prediction test still needs more matched quantum measurements linked to laboratory binding results, and a larger independent biological test remains necessary. Today’s instruction prohibits new Aquila submissions; none were made, and no new quantum jobs were submitted. Fresh device validation and explicit allowance are required before Aquila submission; new paid qBraid work also lacks a credit allowance. This is an automated preliminary report, with Gemini oversight deferred. The inconclusive result usefully separates completed program checks from evidence of predictive benefit. ## Page explanations QUANTUM ATLAS ## Biological Questions via a Quantum Computing Agent in Natural Language. Simplifying Quantum Computing and Bioinformatics. Natural Language In. Biological Insights Out. ### What are you investigating? No quantum expertise needed. Start with our OXTR study or describe your investigation. ### Explore the geometry Ask a question to begin. Mathematical reference · study measurements are recorded separately. EXPLORE WHILE YOU WAIT #### Study the patterns. Switch between Alpha, Beta, Gamma and Epsilon. Compare their positions and paths while your results collect in the next two steps. This view shows the mathematical representations. Measured results appear in Classical results and Quantum results. ASTRA · YOUR INVESTIGATION Study 01 uses a reusable quantum reservoir template. All input encodings, model settings and evaluation rules are frozen before the final test. Biological findings come from the recorded calculations and measurements. Read the first measurement record ↗ Read the full study protocol ↗ · Save the study specification ↓ CUDA-Q specifies the simulation; qBraid provides the GPU route for compatible compiled programs. Amazon Braket routes the analog program to QuEra Aquila. D-Wave Leap is a separate annealing route for future validated templates. Each route retains its own model and execution receipt. Names identify the technologies in the workflow; no partnership or endorsement is implied. 03 / CLASSICAL RESULTS ### Classical results. Approximately 5–10 minutes from the start of processing. 04 / QUANTUM RESULTS ### Quantum results. Timing varies with the quantum queue. Results appear here after processing and checks. 05 / FUTURE FEATURE ### Drug Discovery Network & Open Source Genomic Insights Extend the investigation beyond the calculation. Our roadmap connects recorded results and preliminary AI insights with external research platforms, with human review before sharing. 01Recorded resultsClassical and quantum findings, with their data sources and reproducible methods. 02Preliminary AI insightsRelationships and research directions drawn from the findings, with uncertainty retained. 03Human reviewA researcher reviews the evidence, sharing scope and intended collaborators. 04Research collaborationApproved outputs reach connected drug-discovery and genomic research platforms. 05Open Source Genomic InsightsReviewed insights and shareable research assets return to the scientific community, with permissions and provenance. Roadmap · the long-term aim is automated collaboration with human oversight. This stage has no active external submission or publishing connection. THE TECHNOLOGY BEHIND YOUR QUESTION ### How your question is investigated. Begin with your biological question. Select a step to explore its role. The status labels track the study; motion illustrates the workflow. OUR OXTR STUDY · THE STORY SO FAR ### Explore our OXTR investigation. From our first CUDA-Q and Aquila measurements to Astra’s genomic analysis: one continuing investigation into Fibonacci, Phi Ratio and M9 P24. Completed 25 October 2026 · Next quantum batch awaits a funding decision. STAY OR RETURN #### Your results, at your pace. Both completed study phases are ready to explore above. For a new calculation, stay with the geometry or return later as results become available. Classical: approximately 5–10 minutes. Quantum: timing varies with device availability and queue. The 25 October 16-run OXTR batch: 16 minutes 51 seconds from the first submission to the final completion. The first result arrived after 3 minutes 16 seconds. The earlier two-atom test: 18 hours 52 minutes, submitted on 24 October and completed on 25 October. Both experiments are complete. These are observed timings, not promised delivery times. Delivery preference for the upcoming study run. Email is confirmed at launch; this preview saves your preference on this device. THE SCIENCE COMES FIRST ### From DNA fragments to biological relationships. Begin with a biological task. Our first study focuses on transcription; the same natural-language approach can expand to other validated research workflows. 01 / GENE REGULATION #### Predict where proteins associate with DNA. Compare binding patterns and rank candidate sequences, with experimental evidence kept alongside predictions. 02 / GENOME ASSEMBLY #### Reconstruct overlapping DNA fragments. Find a consistent ordering of short reads and inspect the reconstructed sequence. Begin with a small, transparent example. 03 / GENETIC VARIATION #### Group variants into chromosome copies. Explore how genetic variants can be assigned to distinct chromosome copies, and what data make that assignment reliable. 04 / MOLECULAR INTERACTIONS #### Select compatible molecular contacts. Select compatible candidate contacts in a molecular model, then assess their biological relevance with independent methods. These are research directions with specific mappings and limits. A quantum formulation alone does not establish better accuracy, faster computation or biological validity. GROUNDED IN PUBLISHED WORK ### Ideas with a research trail. Read the findings, their scale and their limitations. Simulation, quantum hardware and classical results remain clearly identified. RESEARCH STIMULUS · NATURE, 2022 #### Fibonacci pulses kept quantum information stable for longer. Laser pulses arranged in a Fibonacci pattern extended the stability of information stored in a quantum computer’s atoms. This finding motivates our investigation and future experiments with Fibonacci representations. WORKING HYPOTHESIS #### From Fibonacci geometry to quantum stability? Does the hexagonal structure in our Fibonacci representations contribute to the stability of quantum information? Solid geometry: mathematical relationships. Dotted link: a proposed physical mechanism. The current Aquila batch measures responses in one fixed hexagon; it does not compare geometries or measure coherence lifetime. SCIENCE AS A PUBLIC SERVICE ### Shared capacity. Open curiosity. Our aim is a publicly funded service that scientists can use freely within shared daily, weekly and monthly budgets. Access follows available capacity, without individual research approvals. Small research demonstrations use shared trial and funded compute. The first OXTR run uses a recorded study budget shared across its CUDA-Q and Aquila calculations. QUESTION CAPACITY These counters cover AI questions. Study compute has a separate cost record. Daily, weekly and monthly compute limits form part of the execution design. LLM Benchmarking Project (opens in a new tab) Track how language models perform at translating English instructions into correct Wolfram Language code over time. This informs model assessment for our work with the Wolfram Quantum Framework. Each quantum program still needs direct calculation, simulation and evidence checks. SCIENTIFIC REVIEW ### Gemini 4 Argon OXTR · STUDY 01 ### Study insights ### Connection verification ### Fibonacci pulses and longer-lived quantum information DUMITRESCU ET AL. · NATURE 607, 463–467 · 2022 Laser pulses arranged in a Fibonacci pattern kept quantum information stable for longer in the atoms of a quantum computer. These observations concerned the edge qubits of a ten-ion processor. The Fibonacci-driven information remained coherent for the full 5.5-second observation period. The 1.5-second comparison is specific to that experiment, not a universal qubit lifetime. The authors attribute the protection to symmetries emerging from the pulse ordering. Their experiment did not test a hexagonal atom arrangement or M9 P24. #### A stimulus for our investigation Quantum Atlas investigates the hexagonal and triangular structures in Fibonacci’s modular representations across M1–M1001. We are exploring whether those relationships have measurable consequences in quantum systems, using Fibonacci, Phi Ratio, Alpha, Beta, Gamma and Epsilon. OXTR DNA supplies the first biological test inputs. The geometric mechanism illustrated below is our working hypothesis. Odom’s construction and the honeycomb theorem establish mathematical relationships; a connection to quantum coherence remains to be tested. Enable JavaScript to explore a question. Read the research references. ## Saved chart table | DNA window | Representation | GPU shots | Valid Aquila shots | Calculated mean | GPU mean | Aquila mean | | --- | --- | --- | --- | --- | --- | --- | | chr3-8752896-8753152 | ordinary | 100 | 98 | 0.2972165941120539 | 0.3016666666666667 | 0.25510204081632654 | | chr3-8752896-8753152 | fibonacci | 100 | 99 | 0.2748087531131463 | 0.28 | 0.21717171717171715 | | chr3-8752896-8753152 | phi | 100 | 96 | 0.2688469682614885 | 0.2783333333333334 | 0.24131944444444445 | | chr3-8752896-8753152 | alpha | 100 | 96 | 0.28111071249328123 | 0.2833333333333334 | 0.203125 | | chr3-8752896-8753152 | beta | 100 | 97 | 0.2912929479467206 | 0.2883333333333334 | 0.24226804123711343 | | chr3-8752896-8753152 | gamma | 100 | 96 | 0.3146403274328215 | 0.29833333333333334 | 0.2638888888888889 | | chr3-8752896-8753152 | epsilon | 100 | 100 | 0.31770366600623073 | 0.3016666666666667 | 0.2916666666666667 | | chr3-8752896-8753152 | shuffled | 100 | 95 | 0.28120871076145454 | 0.27666666666666667 | 0.2754385964912281 | | chr3-8745472-8745728 | ordinary | 100 | 95 | 0.19366276748557543 | 0.21166666666666664 | 0.18070175438596492 | | chr3-8745472-8745728 | fibonacci | 100 | 97 | 0.19352774497750133 | 0.215 | 0.19415807560137455 | | chr3-8745472-8745728 | phi | 100 | 96 | 0.19181574999115006 | 0.21499999999999997 | 0.17361111111111113 | | chr3-8745472-8745728 | alpha | 100 | 95 | 0.1691344536029761 | 0.18000000000000002 | 0.15087719298245614 | | chr3-8745472-8745728 | beta | 100 | 96 | 0.17618737236750492 | 0.18500000000000003 | 0.16145833333333334 | | chr3-8745472-8745728 | gamma | 100 | 95 | 0.22444963615407762 | 0.24166666666666667 | 0.17368421052631577 | | chr3-8745472-8745728 | epsilon | 100 | 97 | 0.2544423008082389 | 0.26333333333333336 | 0.16494845360824742 | | chr3-8745472-8745728 | shuffled | 100 | 93 | 0.267420073461925 | 0.26166666666666666 | 0.29032258064516125 | ## Complete guide data The following JSON preserves the source fields, saved chart arrays, study interpretations and links to complete experiment revisions. ```json { "schema": "universal-informatics/quantum-atlas-guide/v1", "title": "Quantum Atlas · AI / LLM Wiki", "version": "2026-11-09-reasoning-production", "url": "https://universalmind.tv/informatics/quantum/", "wiki": "https://universalmind.tv/informatics/read/quantum/index.html", "agent_architecture": { "version": "2026-11-09-reasoning-production", "purpose": { "title": "What Quantum Atlas is for", "summary": "Quantum Atlas makes computational biology and quantum research approachable through a scientific question written in ordinary language. A person brings the question; the platform coordinates AI scientific work, mathematical models, simulations, recorded quantum measurements and biological evidence, then returns an explanation with the underlying research record.", "why": "The purpose is to help people investigate whether a proposed pattern adds useful information to a biological problem. The current OXTR investigation asks whether Fibonacci, Phi Ratio and M9 P24 representations can help predict where proteins associate with DNA. That study is the first worked investigation within the wider natural-language research experience.", "human_explanation": "You can ask Quantum Atlas a biological research question without writing quantum code. Astra develops the supported investigation and explains the findings. Gemini reviews the design and the resulting report. Mathematical and computing tools supply calculations and measurements, while laboratory evidence provides a biological comparison. You can follow the stages, inspect the geometry, read the results in ordinary language and download the record. Your own AI can retrieve the public evidence through MCP or the API, or ask Universal One a research question through A2A. A persistent new study starts through the Quantum Atlas interface within its supported research scope.", "instructions_for_ai": [ "Begin by explaining the purpose and the person’s research goal before listing providers or discussing the saved OXTR numbers.", "Explain each feature in terms of what the person can ask, see, learn or retrieve. Define simulation, quantum measurement and biological comparison when those terms first appear.", "Describe the agent roles and handoffs, then identify the connection method that fits the person’s request.", "Use the current saved results to illustrate the workflow. Keep the platform’s wider purpose distinct from the outcome of its first study.", "Describe available participation separately from extensions in development. Use the live tool schema and agent card to determine available operations." ], "example_questions": [ "What is Quantum Atlas for, and how can it help me investigate a biological question?", "Explain what Astra, Gemini, Wolfram, CUDA-Q and Aquila each contribute, in plain language.", "Walk me through the current OXTR investigation and explain what the results mean.", "Connect to the public research tools, retrieve the study and help me formulate a useful next question." ] }, "features": [ { "feature": "Ask a question", "purpose": "Express the biological question in everyday language. The router identifies a supported calculation or a concrete missing capability.", "human_value": "A clear starting point without writing quantum code." }, { "feature": "Study and live workflow", "purpose": "Show the question, scientific plan, agent progress and the role of each calculation or evidence source.", "human_value": "Understand what is happening and how each stage contributes." }, { "feature": "Geometry explorer", "purpose": "Inspect Alpha, Beta, Gamma and Epsilon definitions and the different numerical preparations of the same DNA inputs.", "human_value": "See what is being compared before interpreting its response." }, { "feature": "Design and findings reviews", "purpose": "Gemini checks the proposed method before calculations and checks the findings against the evidence before delivery.", "human_value": "See the review decision, requested corrections and retained evidence." }, { "feature": "Classical results", "purpose": "Inspect calculation checks, CUDA-Q simulation results and the genomic prediction comparison.", "human_value": "Understand the computational baseline and what a prediction score means." }, { "feature": "Quantum results and Compare", "purpose": "Inspect the recorded Aquila readings beside matched calculated and simulated values, with their counts and uncertainty.", "human_value": "Understand how the physical device behaved and how that relates to the research question." }, { "feature": "Insights and next test", "purpose": "Return a direct answer, what was completed, the practical meaning, and the remaining research dependency.", "human_value": "Learn from the investigation and identify a useful next step." }, { "feature": "Saved studies and downloads", "purpose": "Retain task progress and provide the complete report in JSON and CSV. The Wiki adds a Markdown reading guide.", "human_value": "Reopen work, inspect methods, discuss it with another AI or reproduce the analysis." }, { "feature": "Shared capacity", "purpose": "Display the available question allowance and keep execution within the recorded scope and funding.", "human_value": "Know when the service can accept another investigation." }, { "feature": "Drug Discovery Network and Open Source Genomic Insights", "purpose": "The planned fifth stage connects reviewed findings with external research collaborators and shareable genomic insights.", "human_value": "Understand the intended path from an investigation to research collaboration. This stage is marked as a future feature." } ], "swarm": { "title": "Quantum / AI agent swarm: who does what", "summary": "Astra and Gemini have distinct scientific roles. LangGraph coordinates their work and the specialist calculation services through an explicit, persistent workflow. The diagram on the Quantum page presents the scientific handoffs: formulate, model, simulate and measure, compare with biological evidence, then interpret.", "roles": [ { "name": "GPT-6 Astra", "role": "Head bioinformatician and scientist", "work": "Interprets the question, selects the supported study plan, coordinates the authorised calculations, responds to review feedback and writes the evidence-grounded explanation.", "handoff": "Proposed plan to Gemini; calculated evidence and draft report to Gemini; reviewed findings to the person." }, { "name": "Gemini 4 Argon", "role": "Chief Scientist", "work": "Reviews the design and final findings against the supplied methods, measurements, source records and uncertainty. Returns approve, revise or human decision required.", "handoff": "Design feedback to Astra before execution; findings feedback before report delivery." }, { "name": "LangGraph", "role": "Workflow orchestration and persistent state", "work": "Orders the steps, checkpoints completed work, routes review decisions, bounds revision loops and preserves progress when a dependency interrupts execution.", "handoff": "Controls the transition between planning, review, calculations, report and completion." }, { "name": "Wolfram Quantum Framework", "role": "Mathematical specification and reference checks", "work": "Provides the mathematical reference role shown in the workflow. The current continuation retains the saved Wolfram check receipts for the original model.", "handoff": "Checked model definitions and reference calculations inform the matched simulation and hardware interpretation." }, { "name": "NVIDIA CUDA-Q", "role": "Quantum-program preparation and simulation", "work": "Compiles and simulates the defined quantum model. The original study used qBraid GPU simulation; the continuing recipe performs local CPU CUDA-Q checks on the cloud worker.", "handoff": "Compiled programs, simulated observables and numerical-check receipts." }, { "name": "qBraid and NVIDIA GPU", "role": "Recorded GPU execution route", "work": "Executed the saved CUDA-Q compiled programs on the documented GPU service. Those measurements and receipts remain available for comparison.", "handoff": "Recorded GPU samples and execution identity into the study evidence." }, { "name": "QuEra Aquila via Amazon Braket", "role": "Recorded physical quantum measurement route", "work": "The saved analog programs ran on Aquila’s neutral atoms through Braket. Their task receipts identify the actual hardware measurements.", "handoff": "Hardware counts, usable shots, observables and timestamps into the comparison." }, { "name": "Biological evidence and classical benchmarks", "role": "Test biological usefulness", "work": "Reference DNA, ENCODE binding observations and JASPAR motifs support the held-out prediction comparison. Fixed classical code calculates the scores and uncertainty.", "handoff": "Computed biological results and source provenance to Astra and Gemini." }, { "name": "Research memory and Universal One", "role": "Shared research context and public research conversation", "work": "Astra retrieves mission, experiment and research-direction records plus literature from the research repository. Universal One exposes cited research answers and public evidence access.", "handoff": "Versioned sources to the scientific workflow and to an external AI using the public interfaces." }, { "name": "Cloudflare broker, AWS worker and encrypted storage", "role": "Durable execution and delivery", "work": "The broker tracks session-owned tasks and worker leases. AWS Lambda executes the supported recipe; SQLite checkpoints and encrypted S3 preserve progress and results.", "handoff": "Progress events and the completed report return to the originating research session." } ], "diagram_stages": { "question": [ "Begin with your biological question.", "GPT uses the Atlas definitions and saved study recipe to select the calculation. Select a step to inspect its role." ], "model": [ "One model, two matched routes.", "Wolfram checks the mathematical specification. The same coordinates, interactions, pulses and measurement conventions feed CUDA-Q and the Aquila program." ], "simulation": [ "Predict the quantum response with CUDA-Q.", "CUDA-Q generates the matched simulation. The documented GPU route uses qBraid for supported compiled programs." ], "hardware": [ "Measure the response on Aquila.", "Amazon Braket submits the approved analog program to QuEra Aquila. Actual queued, running, completed and failed states belong to a saved task receipt." ], "evidence": [ "Let independent observations test the prediction.", "Build and adjust the prediction methods using one set of DNA regions. Then keep the methods unchanged and predict binding on different regions. Compare those predictions with laboratory results kept hidden until the predictions are complete." ], "result": [ "Return the biological finding.", "A completed result combines a plain-language finding, uncertainty and an interactive geometry comparison. Methods, source versions and execution receipts remain available on demand." ] }, "current_workflow": [ { "id": "question", "title": "Question and routing", "action": "The person submits a question. The router selects the supported OXTR continuation recipe or another supported route. A persistent study receives an identity and a saved task record." }, { "id": "memory", "title": "Retrieve context", "action": "Retrieve the mission, research directions, immutable experiment records and relevant literature." }, { "id": "audit", "title": "Audit existing evidence", "action": "Check the saved CUDA-Q, Aquila and mathematical-reference records before using them." }, { "id": "plan", "title": "Astra prepares the plan", "action": "Frame the supported calculation around the original question and the available evidence." }, { "id": "design", "title": "Gemini reviews the design", "action": "An approval advances to calculations. A revision returns the plan to Astra; an unresolved decision saves the dependency." }, { "id": "data", "title": "Prepare the biological comparison", "action": "Prepare reference DNA and the existing laboratory binding map using the fixed cohort recipe." }, { "id": "analyse", "title": "Run classical analysis", "action": "Train and select the methods on separate chromosomes, then evaluate OXTR and calculate the recorded metrics and uncertainty." }, { "id": "quantum", "title": "Prepare and check quantum programs", "action": "Prepare the matched DNA pair in eight representations and run 16 local CPU CUDA-Q program checks. Reuse the saved GPU and Aquila measurements." }, { "id": "report", "title": "Astra explains the findings", "action": "Answer the person’s original question using the calculated evidence, source context and remaining dependency." }, { "id": "final", "title": "Gemini reviews the findings", "action": "Check the report against the evidence packet. A requested revision returns to Astra; approval permits delivery." }, { "id": "publish", "title": "Deliver the research record", "action": "Save the reviewed report and complete JSON/CSV, then show the findings in the Quantum Atlas research session." } ], "recovery": "The current recipe allows one design revision and one report revision. Unsupported questions or unresolved review decisions pause with a stated dependency. Closing the browser does not cancel a durable task; the saved study can be reopened. Cancellation and resume operate on that research session’s own study.", "execution_scope": "The current continuation uses the saved GPU/Aquila results and performs new classical and local CPU CUDA-Q calculations. Fresh Aquila jobs, paid GPU jobs and a fresh Wolfram kernel run are outside this recipe. The workflow labels recorded hardware evidence separately from current task progress.", "memory": "The shared research memory combines mission, research directions, versioned experiments and source-linked literature. Retrieval uses semantic and text search. The report retains the retrieved source context and evidence hashes.", "record": "A delivered study contains the original question, plan and provider receipts, review decisions and evidence packets, source provenance, calculations, program checks and complete JSON/CSV. A private task report becomes a public experiment only through the separate reviewed publication process.", "extensions": "The broader swarm prototype includes mid-study scientific support, human-interruption routing and a publication outbox for Synapse and DeSci. Integrating those general adapters into every live recipe, public MCP/A2A study dispatch, optional document destinations and the Drug Discovery Network remain extensions. The live fixed recipe already includes Gemini design and final review." }, "participation": { "title": "How another AI can participate", "intro": "An external AI can explain the features to its human, retrieve and analyse the public research record, compare methods and help formulate a question. MCP exposes research tools. The REST API exposes the same records as JSON. A2A sends a research question to Universal One and returns its cited answer. The Quantum Atlas interface starts and follows a persistent scientific investigation.", "routes": [ { "route": "Read the Wiki or downloads", "purpose": "Explain the page and its research architecture; discuss a saved study with a person.", "entry": "https://universalmind.tv/informatics/read/quantum/index.html", "authentication": "Public reading" }, { "route": "MCP", "purpose": "Give an AI structured tools for study records, geometry, publications and reusable passages.", "entry": "https://informatics-universal-one.universalmind.workers.dev/mcp", "authentication": "No API key for these public read-only tools" }, { "route": "REST API", "purpose": "Retrieve exact JSON records from an application, script or AI tool.", "entry": "https://informatics-universal-one.universalmind.workers.dev/api/v1/openapi.json", "authentication": "Public read-only API" }, { "route": "A2A", "purpose": "Let an external agent ask Universal One a self-contained research question and receive a cited answer.", "entry": "https://informatics-universal-one.universalmind.workers.dev/.well-known/agent-card.json", "authentication": "Public interface; shared request limits apply" }, { "route": "Quantum Atlas research session", "purpose": "Submit a supported investigation, follow Astra/Gemini progress and retrieve the session-owned report.", "entry": "https://universalmind.tv/informatics/?entry=research&area=quantum", "authentication": "The site establishes the browser research session automatically" } ], "mcp": { "endpoint": "https://informatics-universal-one.universalmind.workers.dev/mcp", "transport": "HTTP JSON-RPC; responses are JSON. The endpoint accepts application/json and text/event-stream in Accept.", "protocol_version": "2025-11-25", "headers": { "Content-Type": "application/json", "Accept": "application/json, text/event-stream", "MCP-Protocol-Version": "2025-11-25" }, "workflow": [ "Initialize the connection and send notifications/initialized.", "Discover tools/list and use the returned input schemas.", "Call get_inventory for the current dataset version and scope.", "Call get_quantum_study with id oxtr-qrc-01 and section summary, then request the relevant sections.", "Follow measurements.data.page.nextOffset until it is null. Use get_atlas_record for canonical sequence definitions and search_publications/get_publication for source research.", "Return a human explanation that cites the record URL, study ID, sourceSHA256 and the appropriate evidence status." ], "requests": [ { "jsonrpc": "2.0", "id": 1, "method": "initialize", "params": { "protocolVersion": "2025-11-25", "capabilities": {}, "clientInfo": { "name": "quantum-atlas-reader", "version": "1.0" } } }, { "jsonrpc": "2.0", "method": "notifications/initialized" }, { "jsonrpc": "2.0", "id": 2, "method": "tools/list", "params": {} }, { "jsonrpc": "2.0", "id": 3, "method": "tools/call", "params": { "name": "get_inventory", "arguments": {} } }, { "jsonrpc": "2.0", "id": 4, "method": "tools/call", "params": { "name": "get_quantum_study", "arguments": { "id": "oxtr-qrc-01", "section": "summary" } } }, { "jsonrpc": "2.0", "id": 5, "method": "tools/call", "params": { "name": "get_quantum_study", "arguments": { "id": "oxtr-qrc-01", "section": "measurements", "offset": 0 } } } ], "result": "Read structuredContent when present, otherwise parse the JSON text in content. Check isError and JSON-RPC errors before interpreting a response.", "continuation": "The current MCP tool schema lists eight Quantum sections. The API also exposes continuation, which contains the later classical pilot and local CUDA-Q findings. Retrieve that section through the REST URL below; discover the current MCP schema before selecting a section.", "tools": [ { "name": "get_quantum_study", "description": "Read the recorded OXTR Quantum Atlas experiment, sequence definitions, actual measurements, comparison, timing, next test and downloads.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": { "id": { "type": "string", "maxLength": 250 }, "section": { "type": "string", "enum": [ "summary", "sequences", "methods", "measurements", "comparison", "next_test", "timing", "downloads" ] }, "offset": { "type": "integer", "minimum": 0, "maximum": 16 } }, "required": [] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } }, { "name": "search", "description": "Find publication and Atlas record IDs. Fetch records before making study-specific claims.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": { "query": { "type": "string", "maxLength": 800 } }, "required": [ "query" ] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } }, { "name": "fetch", "description": "Fetch an approved publication or Atlas overview from a search result ID. Atlas analysis sections are accessible through get_atlas_record; the URL returns the complete record.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": { "id": { "type": "string", "maxLength": 250 } }, "required": [ "id" ] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } }, { "name": "get_inventory", "description": "Exact current counts, dataset version and access scope.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": {}, "required": [] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } }, { "name": "search_publications", "description": "Search approved publication records. OR within each filter; AND across filters. Paginate using nextOffset.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": { "query": { "type": "string", "maxLength": 800 }, "filters": { "type": "object", "additionalProperties": false, "properties": { "collections": { "type": "array", "maxItems": 12, "items": { "type": "string", "maxLength": 200 } }, "targets": { "type": "array", "maxItems": 12, "items": { "type": "string", "maxLength": 200 } }, "conditions": { "type": "array", "maxItems": 12, "items": { "type": "string", "maxLength": 200 } }, "journals": { "type": "array", "maxItems": 12, "items": { "type": "string", "maxLength": 200 } } } }, "offset": { "type": "integer", "minimum": 0, "maximum": 10000 }, "limit": { "type": "integer", "minimum": 1, "maximum": 100 } }, "required": [] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } }, { "name": "get_publication", "description": "Read an approved publication by ID, DOI or PMID. Preserve quotations and evidence status.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": { "id": { "type": "string", "maxLength": 250 } }, "required": [ "id" ] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } }, { "name": "get_passages", "description": "Read CC BY or CC0 full-text passages. Preserve attribution and licence. Other full texts are unavailable through this public connector.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": { "id": { "type": "string", "maxLength": 250 }, "query": { "type": "string", "maxLength": 800 }, "offset": { "type": "integer", "minimum": 0, "maximum": 10000 }, "limit": { "type": "integer", "minimum": 1, "maximum": 20 } }, "required": [ "id" ] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } }, { "name": "list_atlas_records", "description": "Search or list all M1–M1001 records or the M9 family. Commentary is searchable. A family result is mathematical, not biological evidence.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": { "family": { "type": "string", "enum": [ "all", "m9" ] }, "query": { "type": "string", "maxLength": 200 }, "offset": { "type": "integer", "minimum": 0, "maximum": 10000 }, "limit": { "type": "integer", "minimum": 1, "maximum": 100 } }, "required": [] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } }, { "name": "get_atlas_record", "description": "Read Atlas commentary, analysis, probability, hypotheses and nested sequences. Default summary lists section paths. Request a dotted section path for detail. Large objects return field paths; arrays use offset and limit. Full canonical data is available at the returned API URL.", "inputSchema": { "type": "object", "additionalProperties": false, "properties": { "id": { "type": "string", "maxLength": 250 }, "section": { "type": "string", "maxLength": 200 }, "offset": { "type": "integer", "minimum": 0, "maximum": 100000 }, "limit": { "type": "integer", "minimum": 1, "maximum": 100 } }, "required": [ "id" ] }, "annotations": { "readOnlyHint": true, "destructiveHint": false, "idempotentHint": true, "openWorldHint": false } } ] }, "api": { "openapi": "https://informatics-universal-one.universalmind.workers.dev/api/v1/openapi.json", "inventory": "https://informatics-universal-one.universalmind.workers.dev/api/v1/inventory", "study_summary": "https://informatics-universal-one.universalmind.workers.dev/api/v1/quantum/oxtr-qrc-01?section=summary", "study_continuation": "https://informatics-universal-one.universalmind.workers.dev/api/v1/quantum/oxtr-qrc-01?section=continuation", "study_measurements": "https://informatics-universal-one.universalmind.workers.dev/api/v1/quantum/oxtr-qrc-01?section=measurements&offset=0", "geometry": "https://informatics-universal-one.universalmind.workers.dev/api/v1/atlas/fibonacci-m9-p24?section=full" }, "a2a": { "agent_card": "https://informatics-universal-one.universalmind.workers.dev/.well-known/agent-card.json", "endpoint": "https://informatics-universal-one.universalmind.workers.dev/a2a/v1", "headers": { "Content-Type": "application/json", "A2A-Version": "1.0" }, "request": { "jsonrpc": "2.0", "id": 1, "method": "SendMessage", "params": { "message": { "messageId": "quantum-atlas-explanation-1", "role": "ROLE_USER", "parts": [ { "text": "Read the current OXTR quantum study. Explain its research question, the roles of simulation, Aquila measurements and the classical biological comparison, and what the findings mean for a person considering the next experiment. Cite the source records." } ] } } }, "response": "Read result.message.parts for the answer and result.message.metadata.sources for citations. Include the relevant context in each new message.", "scope": "The current A2A agent returns a direct research answer. Persistent task dispatch, streaming and push notifications are outside its advertised capabilities. MCP and A2A do not submit new Aquila jobs or create the browser’s persistent Astra study." }, "connect_guide": "https://universalmind.tv/informatics/connect.html", "handoff": "For a new persistent investigation, help the person frame the question and open Quantum Atlas. The site establishes its research session, submits the question and tracks the resulting study. Keep the public research connector separate from the session-owned execution service.", "citation_contract": "Retain study IDs, immutable revision URLs, source hashes, provider receipts and review status when moving between agents. Link the evidence that supports the explanation, and preserve the original question throughout the handoff." }, "implementation_sources": [ { "repository_path": "Informatics/quantum/index.html", "sha256": "241eef8b0342309cd7935654b157d108ecc4bdb0904e06d5702bd016aa27cfc9", "scope": "Original primary-page source with generated reading blocks removed" }, { "repository_path": "Informatics/quantum/study.js", "sha256": "3f0bc61c9d7404e737e1638917b5b65b960778d9db53fcc79041d7685d47352d", "scope": "Implementation source" }, { "repository_path": "Informatics/quantum/agent.js", "sha256": "a367e2183ec25af1fadadc25a4c8b76409471cbb2b195fecd77aeb17311702d9", "scope": "Implementation source" }, { "repository_path": "Informatics/quantum/biology.js", "sha256": "07bf3e90c3b0e9e18dc51ee0557774a536a2a9049c97decd0fa502966bf1c8dc", "scope": "Implementation source" }, { "repository_path": "Informatics/quantum/scientific-review.js", "sha256": "36122cd98b6f4a42eed29b8d84689599fb9a0b1e2f9fb07c373ab0ec3deb86ec", "scope": "Implementation source" }, { "repository_path": "Informatics/connect.js", "sha256": "1227ae3472159a4ab32abede300b99b4f3cdbf5573373e62a6a76aa9979d5eca", "scope": "Implementation source" }, { "repository_path": "cloudflare/informatics-connectors.js", "sha256": "1c0ad31d1d9eb6d53b3615777d0714eb7bf42a2f4f86f91646a413a97052ca7a", "scope": "Implementation source" }, { "repository_path": "cloudflare/informatics-quantum-knowledge.js", "sha256": "559caf6534201e060da1d933cd9aa0d8b1e95fc62ba98c70723d124ea35a0204", "scope": "Implementation source" }, { "repository_path": "cloudflare/informatics-quantum.js", "sha256": "a93c6e5eea1156c47c5f689be39d924ed6c8f81c6fb44d967cf74a3bee272585", "scope": "Implementation source" }, { "repository_path": "cloudflare/informatics-astra.js", "sha256": "219b5dd2637e1311b37a4169b8c81e586647b00a2c12ad6a66ed7fd63a4750a1", "scope": "Implementation source" }, { "repository_path": "cloudflare/informatics-astra-memory.js", "sha256": "a4384d95c1a0eafb7aa72bbdcf38fe4f1bd88ad895d419b5ff3e4916626a6c6e", "scope": "Implementation source" }, { "repository_path": "research/informatics/astra-service/runner.py", "sha256": "5ae9062b5b20833f0da9d3e3f3927703b2622c1b29b8a07160ce79ae59eb8f2f", "scope": "Implementation source" }, { "repository_path": "research/informatics/astra-service/review_flow.py", "sha256": "61248bd6c5fc44a11c9816dc126ec0cc238e7bec36f8e9f6ff80a8400230fdf0", "scope": "Implementation source" }, { "repository_path": "research/informatics/astra-service/cloud/runtime.py", "sha256": "7bed322cd5688b6afe149c9fcec71f330d6f1a1a37a7fbb680515cbbb98b2603", "scope": "Implementation source" }, { "repository_path": "research/informatics/scientific-swarm/swarm.py", "sha256": "c54b10f8817b59be643e87d413cd0eb0c29cb51e8b11985726431eb06cbdaccb", "scope": "Implementation source" }, { "repository_path": "research/informatics/scientific-swarm/ROLE_CONTRACT.md", "sha256": "f06b092dc9fee0585a9c649b84c166d960f19a11aa61ba50ba0f4fb385562cd0", "scope": "Implementation source" }, { "repository_path": "research/informatics/astra-service/reasoning_profile.py", "sha256": "d4f54083069893f9e0fa1db021d809f59439d2dae83f3adc873cc5e4a263bc24", "scope": "Implementation source" }, { "repository_path": "research/informatics/scientific-swarm/providers.py", "sha256": "d736b78032265eadea61e322ad90107f87dd81075968e3d1f5b52acd671c011f", "scope": "Implementation source" } ] }, "instructions": [ "Read the saved study phases in order: original qualification runs, completed classical genomic pilot, further local CPU checks, then the proposed next quantum test.", "Retain the source labels for calculated values, GPU simulations, Aquila measurements, mathematical relationships and proposed mechanisms.", "This guide includes the saved chart data and interpretations. The linked immutable experiment revisions retain the complete inputs, methods, measurements, receipts and field guides. The guide is a dated snapshot, not a report of a visitor’s active question." ], "page_text": [ { "tag": "p", "text": "QUANTUM ATLAS" }, { "tag": "h1", "text": "Biological Questions via a Quantum Computing Agent in Natural Language." }, { "tag": "p", "text": "Simplifying Quantum Computing and Bioinformatics." }, { "tag": "p", "text": "Natural Language In. Biological Insights Out." }, { "tag": "h2", "text": "What are you investigating?" }, { "tag": "p", "text": "No quantum expertise needed. Start with our OXTR study or describe your investigation." }, { "tag": "h2", "text": "Explore the geometry" }, { "tag": "p", "text": "Ask a question to begin." }, { "tag": "p", "text": "Mathematical reference · study measurements are recorded separately." }, { "tag": "p", "text": "EXPLORE WHILE YOU WAIT" }, { "tag": "h3", "text": "Study the patterns." }, { "tag": "p", "text": "Switch between Alpha, Beta, Gamma and Epsilon. Compare their positions and paths while your results collect in the next two steps." }, { "tag": "p", "text": "This view shows the mathematical representations. Measured results appear in Classical results and Quantum results." }, { "tag": "p", "text": "ASTRA · YOUR INVESTIGATION" }, { "tag": "p", "text": "Study 01 uses a reusable quantum reservoir template. All input encodings, model settings and evaluation rules are frozen before the final test. Biological findings come from the recorded calculations and measurements." }, { "tag": "p", "text": "Read the first measurement record ↗" }, { "tag": "p", "text": "Read the full study protocol ↗ · Save the study specification ↓" }, { "tag": "p", "text": "CUDA-Q specifies the simulation; qBraid provides the GPU route for compatible compiled programs. Amazon Braket routes the analog program to QuEra Aquila. D-Wave Leap is a separate annealing route for future validated templates. Each route retains its own model and execution receipt." }, { "tag": "p", "text": "Names identify the technologies in the workflow; no partnership or endorsement is implied." }, { "tag": "p", "text": "03 / CLASSICAL RESULTS" }, { "tag": "h2", "text": "Classical results." }, { "tag": "p", "text": "Approximately 5–10 minutes from the start of processing." }, { "tag": "p", "text": "04 / QUANTUM RESULTS" }, { "tag": "h2", "text": "Quantum results." }, { "tag": "p", "text": "Timing varies with the quantum queue. Results appear here after processing and checks." }, { "tag": "p", "text": "05 / FUTURE FEATURE" }, { "tag": "h2", "text": "Drug Discovery Network & Open Source Genomic Insights" }, { "tag": "p", "text": "Extend the investigation beyond the calculation. Our roadmap connects recorded results and preliminary AI insights with external research platforms, with human review before sharing." }, { "tag": "li", "text": "01Recorded resultsClassical and quantum findings, with their data sources and reproducible methods." }, { "tag": "li", "text": "02Preliminary AI insightsRelationships and research directions drawn from the findings, with uncertainty retained." }, { "tag": "li", "text": "03Human reviewA researcher reviews the evidence, sharing scope and intended collaborators." }, { "tag": "li", "text": "04Research collaborationApproved outputs reach connected drug-discovery and genomic research platforms." }, { "tag": "li", "text": "05Open Source Genomic InsightsReviewed insights and shareable research assets return to the scientific community, with permissions and provenance." }, { "tag": "p", "text": "Roadmap · the long-term aim is automated collaboration with human oversight. This stage has no active external submission or publishing connection." }, { "tag": "p", "text": "THE TECHNOLOGY BEHIND YOUR QUESTION" }, { "tag": "h2", "text": "How your question is investigated." }, { "tag": "p", "text": "Begin with your biological question." }, { "tag": "p", "text": "Select a step to explore its role. The status labels track the study; motion illustrates the workflow." }, { "tag": "p", "text": "OUR OXTR STUDY · THE STORY SO FAR" }, { "tag": "h2", "text": "Explore our OXTR investigation." }, { "tag": "p", "text": "From our first CUDA-Q and Aquila measurements to Astra’s genomic analysis: one continuing investigation into Fibonacci, Phi Ratio and M9 P24." }, { "tag": "p", "text": "Completed 25 October 2026 · Next quantum batch awaits a funding decision." }, { "tag": "p", "text": "STAY OR RETURN" }, { "tag": "h3", "text": "Your results, at your pace." }, { "tag": "p", "text": "Both completed study phases are ready to explore above. For a new calculation, stay with the geometry or return later as results become available." }, { "tag": "p", "text": "Classical: approximately 5–10 minutes. Quantum: timing varies with device availability and queue." }, { "tag": "p", "text": "The 25 October 16-run OXTR batch: 16 minutes 51 seconds from the first submission to the final completion. The first result arrived after 3 minutes 16 seconds." }, { "tag": "p", "text": "The earlier two-atom test: 18 hours 52 minutes, submitted on 24 October and completed on 25 October. Both experiments are complete. These are observed timings, not promised delivery times." }, { "tag": "p", "text": "Delivery preference for the upcoming study run. Email is confirmed at launch; this preview saves your preference on this device." }, { "tag": "p", "text": "THE SCIENCE COMES FIRST" }, { "tag": "h2", "text": "From DNA fragments to biological relationships." }, { "tag": "p", "text": "Begin with a biological task. Our first study focuses on transcription; the same natural-language approach can expand to other validated research workflows." }, { "tag": "p", "text": "01 / GENE REGULATION" }, { "tag": "h3", "text": "Predict where proteins associate with DNA." }, { "tag": "p", "text": "Compare binding patterns and rank candidate sequences, with experimental evidence kept alongside predictions." }, { "tag": "p", "text": "02 / GENOME ASSEMBLY" }, { "tag": "h3", "text": "Reconstruct overlapping DNA fragments." }, { "tag": "p", "text": "Find a consistent ordering of short reads and inspect the reconstructed sequence. Begin with a small, transparent example." }, { "tag": "p", "text": "03 / GENETIC VARIATION" }, { "tag": "h3", "text": "Group variants into chromosome copies." }, { "tag": "p", "text": "Explore how genetic variants can be assigned to distinct chromosome copies, and what data make that assignment reliable." }, { "tag": "p", "text": "04 / MOLECULAR INTERACTIONS" }, { "tag": "h3", "text": "Select compatible molecular contacts." }, { "tag": "p", "text": "Select compatible candidate contacts in a molecular model, then assess their biological relevance with independent methods." }, { "tag": "p", "text": "These are research directions with specific mappings and limits. A quantum formulation alone does not establish better accuracy, faster computation or biological validity." }, { "tag": "p", "text": "GROUNDED IN PUBLISHED WORK" }, { "tag": "h2", "text": "Ideas with a research trail." }, { "tag": "p", "text": "Read the findings, their scale and their limitations. Simulation, quantum hardware and classical results remain clearly identified." }, { "tag": "p", "text": "RESEARCH STIMULUS · NATURE, 2022" }, { "tag": "h3", "text": "Fibonacci pulses kept quantum information stable for longer." }, { "tag": "p", "text": "Laser pulses arranged in a Fibonacci pattern extended the stability of information stored in a quantum computer’s atoms. This finding motivates our investigation and future experiments with Fibonacci representations." }, { "tag": "p", "text": "WORKING HYPOTHESIS" }, { "tag": "h3", "text": "From Fibonacci geometry to quantum stability?" }, { "tag": "p", "text": "Does the hexagonal structure in our Fibonacci representations contribute to the stability of quantum information?" }, { "tag": "p", "text": "Solid geometry: mathematical relationships. Dotted link: a proposed physical mechanism. The current Aquila batch measures responses in one fixed hexagon; it does not compare geometries or measure coherence lifetime." }, { "tag": "p", "text": "SCIENCE AS A PUBLIC SERVICE" }, { "tag": "h2", "text": "Shared capacity. Open curiosity." }, { "tag": "p", "text": "Our aim is a publicly funded service that scientists can use freely within shared daily, weekly and monthly budgets. Access follows available capacity, without individual research approvals." }, { "tag": "p", "text": "Small research demonstrations use shared trial and funded compute. The first OXTR run uses a recorded study budget shared across its CUDA-Q and Aquila calculations." }, { "tag": "p", "text": "QUESTION CAPACITY" }, { "tag": "p", "text": "These counters cover AI questions. Study compute has a separate cost record. Daily, weekly and monthly compute limits form part of the execution design." }, { "tag": "p", "text": "LLM Benchmarking Project (opens in a new tab)" }, { "tag": "p", "text": "Track how language models perform at translating English instructions into correct Wolfram Language code over time. This informs model assessment for our work with the Wolfram Quantum Framework. Each quantum program still needs direct calculation, simulation and evidence checks." }, { "tag": "p", "text": "SCIENTIFIC REVIEW" }, { "tag": "h2", "text": "Gemini 4 Argon" }, { "tag": "p", "text": "OXTR · STUDY 01" }, { "tag": "h2", "text": "Study insights" }, { "tag": "h2", "text": "Connection verification" }, { "tag": "h2", "text": "Fibonacci pulses and longer-lived quantum information" }, { "tag": "p", "text": "DUMITRESCU ET AL. · NATURE 607, 463–467 · 2022" }, { "tag": "p", "text": "Laser pulses arranged in a Fibonacci pattern kept quantum information stable for longer in the atoms of a quantum computer." }, { "tag": "p", "text": "These observations concerned the edge qubits of a ten-ion processor. The Fibonacci-driven information remained coherent for the full 5.5-second observation period. The 1.5-second comparison is specific to that experiment, not a universal qubit lifetime." }, { "tag": "p", "text": "The authors attribute the protection to symmetries emerging from the pulse ordering. Their experiment did not test a hexagonal atom arrangement or M9 P24." }, { "tag": "h3", "text": "A stimulus for our investigation" }, { "tag": "p", "text": "Quantum Atlas investigates the hexagonal and triangular structures in Fibonacci’s modular representations across M1–M1001. We are exploring whether those relationships have measurable consequences in quantum systems, using Fibonacci, Phi Ratio, Alpha, Beta, Gamma and Epsilon. OXTR DNA supplies the first biological test inputs." }, { "tag": "p", "text": "The geometric mechanism illustrated below is our working hypothesis. Odom’s construction and the honeycomb theorem establish mathematical relationships; a connection to quantum coherence remains to be tested." }, { "tag": "p", "text": "Enable JavaScript to explore a question. Read the research references." } ], "page_links": [ { "url": "#question", "label": "Skip to your research question" }, { "url": "../?entry=research&area=quantum", "label": "UNIVERSAL INFORMATICS" }, { "url": "#access", "label": "Checking shared capacity" }, { "url": "data/oxtr-qrc-qualification.md", "label": "Read the first measurement record ↗" }, { "url": "data/oxtr-qrc-protocol.md", "label": "Read the full study protocol ↗" }, { "url": "data/oxtr-qrc-study.json", "label": "Save the study specification ↓" }, { "url": "experiments/oxtr-qrc-01-qualification/r1/experiment.json", "label": "First measurements · JSON ↓" }, { "url": "experiments/oxtr-qrc-01-qualification/r1/experiment.csv", "label": "First measurements · CSV ↓" }, { "url": "experiments/oxtr-agent-follow-through-pilot/r1/experiment.json", "label": "Genomic analysis · JSON ↓" }, { "url": "experiments/oxtr-agent-follow-through-pilot/r1/experiment.csv", "label": "Genomic analysis · CSV ↓" }, { "url": "../connect.html#downloads", "label": "Entire Informatics dataset ↗" }, { "url": "data/execution-timing.json", "label": "Download recorded execution times ↓" }, { "url": "https://www.wolfram.com/llm-benchmarking-project/", "label": "Wolfram" }, { "url": "https://www.wolfram.com/llm-benchmarking-project/", "label": "LLM Benchmarking Project (opens in a new tab)" }, { "url": "https://www.nature.com/articles/s41586-022-04853-4", "label": "Original Nature study ↗" }, { "url": "https://futurism.com/the-byte/fibonacci-quantum-computer", "label": "Futurism · plain-language account ↗" }, { "url": "https://www.simonsfoundation.org/news/strange-new-phase-of-matter-created-in-quantum-computer-acts-like-it-has-two-time-dimensions/", "label": "Research team’s explanation ↗" }, { "url": "https://doi.org/10.2307/2323047", "label": "Odom’s construction · E3007 ↗" }, { "url": "https://arxiv.org/abs/math/9906042", "label": "Hales · honeycomb theorem ↗" }, { "url": "data/papers.json", "label": "Read the research references." } ], "geometry_explanations": { "fibonacci": "Successive Fibonacci ratios approach the Phi Ratio. This is an exact limiting relationship. It does not by itself specify a physical arrangement of atoms.", "modular": "M9 P24 means nine residue classes in a 24-step cycle. The Atlas places period positions on a circle; Gamma and Epsilon visit six equally spaced positions. M1–M1001 lets us compare modular representations. These are mathematical coordinates, not nine physical spatial dimensions.", "odom": "Odom’s construction gives MP/MN = φ exactly: M and N bisect two sides of an equilateral triangle, and the ray MN meets its circumcircle at P. A regular tetrahedron has equilateral faces, so this construction applies within each face.", "honeycomb": "Hales proved that regular hexagonal tiling minimizes boundary length when the plane is divided into equal-area cells. This is a geometric efficiency theorem; it does not establish quantum stability or minimum energy for every physical system.", "quantum": "Working hypothesis: does the hexagonal structure associated with these representations contribute to quantum coherence? A direct test varies pulse ordering and atom geometry independently, with matched controls and a coherence measurement. The Nature study supports Fibonacci-driven quantum effects; it does not establish this geometric mechanism." }, "result_interpretations": { "classical": { "title": "The calculation check passed.", "finding": "Before using a quantum machine, we checked that the program calculates the six-atom experiment correctly. Independent calculations agreed within the recorded error limits.", "insights": [ { "title": "What counted as a pass?", "text": "The simulation had to agree with a separate calculation of the same six atoms. The recorded numerical limit was 0.1 percentage points; the measured largest difference was about 0.006 percentage points." }, { "title": "What this lets us do", "text": "Use the checked program in the next prediction experiment. The test for that experiment is whether it finds known protein-binding regions more accurately." } ] }, "simulation": { "title": "CUDA-Q passed the calculation check.", "finding": "We used two short DNA samples near OXTR. For each sample, we prepared its numerical measurements in eight ways: ordinary measurements, Fibonacci numbers, Phi Ratio, Alpha, Beta, Gamma, Epsilon and a shuffled comparison. That made 16 CUDA-Q programs. The GPU results passed the calculation check. The DNA sequences themselves stayed unchanged.", "insights": [ { "title": "The goal of this first check", "text": "Verify that CUDA-Q runs the intended six-atom experiment. A result outside the agreed error limits means we stop and fix the calculation before relying on it." }, { "title": "What “calculated” means in the charts", "text": "It is the predicted atom behaviour from a separate computer calculation with hardware noise left out. It is a comparison value, not a target for biological success." }, { "title": "What happened with the sequences?", "text": "The computer calculation predicted more excited-state readings for Gamma and Epsilon in both samples, and fewer for Alpha and Beta. The 100-shot GPU samples vary around those predictions." }, { "title": "What earns a positive biological result?", "text": "CTCF is one transcription factor, a protein that binds DNA. The completed classical pilot tested predictions against CTCF laboratory measurements. It found no clear gain from Fibonacci spacing and Phi Ratio. The next quantum test asks whether the atom readings improve those predictions, including M9 P24, beyond ordinary and shuffled inputs." } ] }, "quantum": { "title": "Aquila returned all 16 runs. Agreement with the calculation was mixed.", "finding": "The machine returned usable readings for every program. Alpha and Beta gave fewer excited-state readings in both samples, as the computer calculation predicted. Gamma and Epsilon gave more in sample 1 but fewer in sample 2.", "insights": [ { "title": "Was this the result we wanted?", "text": "We wanted usable measurements from every program. We got them. We also wanted to see how closely the machine followed the calculation; that agreement was mixed." }, { "title": "Does “fewer” mean better?", "text": "No. It means fewer atoms were read in the excited state. “As predicted” means the calculation also said fewer. It does not mean better protein-binding prediction." }, { "title": "What needs checking again?", "text": "Repeat the same inputs with the run order mixed up. If the Gamma and Epsilon differences persist beyond measurement variation, investigate hardware effects and the program before interpreting them biologically." }, { "title": "What is the next biological test?", "text": "Astra has completed the first classical comparison against known CTCF-binding regions. Next, test whether the quantum readings add predictive value. Keep ordinary and shuffled controls: the shuffled version also produced a large atom response in this first batch." } ] } }, "records": { "execution-timing": { "source": "Recorded Amazon Braket task metadata", "definition": "Elapsed wall time from submission to completion, including queue and execution; not QPU processing duration.", "study_01": { "submitted_at": "2026-10-25T01:05:00.993000+00:00", "completed_at": "2026-10-25T01:21:52.327000+00:00", "elapsed_seconds": 1011.334, "first_result_seconds": 196.056, "task_count": 16, "tasks": [ { "case": "chr3-8745472-8745728-alpha", "task_id": "941daa0a-4939-411e-a7f1-88fcb16baaca", "state": "COMPLETED", "submitted_at": "2026-10-25T01:06:19.236000+00:00", "completed_at": "2026-10-25T01:18:15.050000+00:00" }, { "case": "chr3-8745472-8745728-beta", "task_id": "ea4bb9a4-c91a-492a-80a7-c59fd051a807", "state": "COMPLETED", "submitted_at": "2026-10-25T01:06:20.037000+00:00", "completed_at": "2026-10-25T01:19:09.159000+00:00" }, { "case": "chr3-8745472-8745728-epsilon", "task_id": "1cbb29aa-c1b8-49bb-af31-dd18a7cbd480", "state": "COMPLETED", "submitted_at": "2026-10-25T01:06:21.697000+00:00", "completed_at": "2026-10-25T01:20:58.123000+00:00" }, { "case": "chr3-8745472-8745728-fibonacci", "task_id": "aff105ae-441b-49d7-a5b0-9797edc60b05", "state": "COMPLETED", "submitted_at": "2026-10-25T01:06:17.596000+00:00", "completed_at": "2026-10-25T01:16:26.685000+00:00" }, { "case": "chr3-8745472-8745728-gamma", "task_id": "f30cda70-0079-41e9-aa40-72e24b51f15d", "state": "COMPLETED", "submitted_at": "2026-10-25T01:06:20.873000+00:00", "completed_at": "2026-10-25T01:20:03.424000+00:00" }, { "case": "chr3-8745472-8745728-ordinary", "task_id": "393fd233-18b4-47f4-ba5e-af2d142e8512", "state": "COMPLETED", "submitted_at": "2026-10-25T01:06:16.433000+00:00", "completed_at": "2026-10-25T01:15:32.365000+00:00" }, { "case": "chr3-8745472-8745728-phi", "task_id": "17ffbfd0-8304-4b30-a749-8d0c91eab2d9", "state": "COMPLETED", "submitted_at": "2026-10-25T01:06:18.417000+00:00", "completed_at": "2026-10-25T01:17:20.787000+00:00" }, { "case": "chr3-8745472-8745728-shuffled", "task_id": "8408039a-06e1-4782-910f-44a9313c8e12", "state": "COMPLETED", "submitted_at": "2026-10-25T01:06:22.576000+00:00", "completed_at": "2026-10-25T01:21:52.327000+00:00" }, { "case": "chr3-8752896-8753152-alpha", "task_id": "1408321b-3bbf-42d0-98d8-b2a3f6a2282d", "state": "COMPLETED", "submitted_at": "2026-10-25T01:05:04.678000+00:00", "completed_at": "2026-10-25T01:10:59.347000+00:00" }, { "case": "chr3-8752896-8753152-beta", "task_id": "21a80a56-064a-4940-8ed9-9d77122436c7", "state": "COMPLETED", "submitted_at": "2026-10-25T01:05:05.470000+00:00", "completed_at": "2026-10-25T01:11:53.494000+00:00" }, { "case": "chr3-8752896-8753152-epsilon", "task_id": "46eac414-f077-4214-81ef-e21635955bb9", "state": "COMPLETED", "submitted_at": "2026-10-25T01:05:07.583000+00:00", "completed_at": "2026-10-25T01:13:42.064000+00:00" }, { "case": "chr3-8752896-8753152-fibonacci", "task_id": "4d690682-bbcd-471f-84fe-d7d29ab4f0f3", "state": "COMPLETED", "submitted_at": "2026-10-25T01:05:02.535000+00:00", "completed_at": "2026-10-25T01:09:11.173000+00:00" }, { "case": "chr3-8752896-8753152-gamma", "task_id": "056c9488-bd07-469c-93e2-edf24e8fff9c", "state": "COMPLETED", "submitted_at": "2026-10-25T01:05:06.755000+00:00", "completed_at": "2026-10-25T01:12:47.788000+00:00" }, { "case": "chr3-8752896-8753152-ordinary", "task_id": "92a97488-675a-4126-838a-75ff29e0c539", "state": "COMPLETED", "submitted_at": "2026-10-25T01:05:00.993000+00:00", "completed_at": "2026-10-25T01:08:17.049000+00:00" }, { "case": "chr3-8752896-8753152-phi", "task_id": "fd03b07f-1c48-40a1-8510-05bcfa38987b", "state": "COMPLETED", "submitted_at": "2026-10-25T01:05:03.835000+00:00", "completed_at": "2026-10-25T01:10:05.401000+00:00" }, { "case": "chr3-8752896-8753152-shuffled", "task_id": "f4bc57c5-2ab1-463e-8e3b-88c7c61e4eb0", "state": "COMPLETED", "submitted_at": "2026-10-25T01:05:08.657000+00:00", "completed_at": "2026-10-25T01:14:38.144000+00:00" } ] }, "earlier_connection_test": { "task_id": "3ae0ec02-160e-45a0-8f37-c88c1bbccda7", "state": "COMPLETED", "submitted_at": "2026-10-24T04:07:26.498000+00:00", "completed_at": "2026-10-24T22:59:41.681000+00:00", "elapsed_seconds": 67935.183 }, "interpretation": "Both experiments completed. 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"study_version": "1.0.0", "updated_on": "2026-10-25", "state": "qualification_complete", "stages": { "question": { "state": "ready", "label": "Ready for a question" }, "model": { "state": "complete", "label": "Model checks passed", "message": "All 16 programs passed numerical checks. Wolfram Quantum Framework independently verified the reference Hamiltonian and evolution." }, "simulation": { "state": "complete", "label": "16 GPU runs complete", "message": "All eight representations were simulated for two OXTR windows. CUDA-Q compiled programs ran through qBraid on an NVIDIA GPU at zero credit cost." }, "hardware": { "state": "complete", "label": "16 Aquila runs complete", "message": "All 16 tasks returned 100 measurements each. 1,541 measurements began with all six atoms present. The recorded quantum comparison is available under Quantum results." }, "evidence": { "state": "specified", "label": "Prediction evaluation follows", "message": "This first batch checks the measurement route. The larger benchmark compares held-out occupancy predictions against strong classical baselines." }, "result": { "state": "complete", "label": "Measurement comparison ready", "message": "Classical, GPU and Aquila measurement results are available. This is the first measurement phase; the biological prediction question remains open." }, "classical": { "state": "complete", "label": "Numerical checks complete" } }, "jobs": [ { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add543a2a6c33b9a67fcf6a", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add544c2a6c33b9a67fcf6e", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add545d2a6c33b9a67fcf75", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add546f2a6c33b9a67fcf7d", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add54802a6c33b9a67fcf85", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add54912a6c33b9a67fcf8b", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add54a32a6c33b9a67fcf90", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add54b52a6c33b9a67fcf99", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add54c82a6c33b9a67fcf9e", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add54dd2a6c33b9a67fcfa2", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add54ef2a6c33b9a67fcfae", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add55002a6c33b9a67fcfb4", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add55112a6c33b9a67fcfbd", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add55222a6c33b9a67fcfc1", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add55332a6c33b9a67fcfc5", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add55442a6c33b9a67fcfcf", "state": "COMPLETED" }, { "provider": "qBraid", "id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add55542a6c33b9a67fcfd5", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "92a97488-675a-4126-838a-75ff29e0c539", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "4d690682-bbcd-471f-84fe-d7d29ab4f0f3", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "fd03b07f-1c48-40a1-8510-05bcfa38987b", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "1408321b-3bbf-42d0-98d8-b2a3f6a2282d", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "21a80a56-064a-4940-8ed9-9d77122436c7", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "056c9488-bd07-469c-93e2-edf24e8fff9c", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "46eac414-f077-4214-81ef-e21635955bb9", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "f4bc57c5-2ab1-463e-8e3b-88c7c61e4eb0", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "393fd233-18b4-47f4-ba5e-af2d142e8512", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "aff105ae-441b-49d7-a5b0-9797edc60b05", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "17ffbfd0-8304-4b30-a749-8d0c91eab2d9", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "941daa0a-4939-411e-a7f1-88fcb16baaca", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "ea4bb9a4-c91a-492a-80a7-c59fd051a807", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "f30cda70-0079-41e9-aa40-72e24b51f15d", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "1cbb29aa-c1b8-49bb-af31-dd18a7cbd480", "state": "COMPLETED" }, { "provider": "Amazon Braket / QuEra", "id": "8408039a-06e1-4782-910f-44a9313c8e12", "state": "COMPLETED" } ], "result": null, "reports": { "classical": { "state": "complete", "kind": "classical", "study_id": "oxtr-qrc-01", "study_version": "1.0.0", "title": "The Fibonacci representations change the response to the same OXTR DNA.", "finding": "Holding the DNA window and six-atom model fixed, changing its mathematical representation changes the calculated quantum response. The effects differ between the two OXTR windows: the representations do not act as one interchangeable Fibonacci pattern.", "receipt": { "run_id": "oxtr-qrc-01-local-qualification", "model_version": "1.1.0-qualification", "execution": "classical-cpu", "backend": "SciPy reference + CUDA-Q CPU + Wolfram Quantum Framework", "completed_at": "2026-10-25T00:54:32.397532+00:00", "input_sha256": "0a86b5247d1a8e950d525debeed806109f009f6c51c70555eafcef4199336b33" }, "metrics": [ { "label": "Model cases checked", "value": 16 }, { "label": "Maximum final numerical difference", "value": "0.0000583 in probability" }, { "label": "Wolfram reference difference", "value": "0.00000000726 in probability" } ], "details": [ "Six atoms, full 64-state evolution, all 15 pair interactions. Same coordinates, pulses and interactions in the GPU and Aquila programs.", "Two motif-rich 256-base OXTR windows were selected without occupancy labels. They qualify execution and are not an independent prediction test.", "Native Fibonacci, Phi Ratio, Alpha, Beta, Gamma and Epsilon are compared with ordinary and shuffled inputs.", "Gamma and Epsilon produce distinct simulated responses. At 100 shots, measurement uncertainty can be larger than that difference." ], "phase": "qualification", "insights": [ { "title": "What this tells us about the occupancy question", "text": "We have generated distinct candidate features from OXTR DNA. This batch did not compare them with measured transcription-factor occupancy, so improved prediction has not yet been established." }, { "title": "The contribution of this first experiment", "text": "It identifies which representations alter the calculated response and tests whether a physical quantum processor reproduces those changes. Those are concrete properties to examine before interpreting a response as biological information." } ] }, "simulation": { "state": "complete", "kind": "simulation", "study_id": "oxtr-qrc-01", "study_version": "1.0.0", "title": "Gamma and Epsilon increase the simulated response in both DNA windows.", "finding": "Among the six proposed representations, Gamma and Epsilon produce the largest increases over ordinary input in the ideal model. The GPU samples accompany that reference calculation below. A larger atom response is not a measure of better binding-site prediction.", "receipt": { "run_id": "oxtr-qrc-01-gpu-qualification", "model_version": "1.1.0-qualification", "execution": "cudaq-gpu", "backend": "CUDA-Q compiled programs → qBraid NVIDIA GPU", "completed_at": "2026-10-25T01:03:34.356758+00:00", "input_sha256": "0a86b5247d1a8e950d525debeed806109f009f6c51c70555eafcef4199336b33", "task_id": "qbraid:qbraid:sim:gpu-sv-cd19-qjob-6add544c2a6c33b9a67fcf6e" }, "metrics": [ { "label": "Study simulations", "value": "16 × 100 shots" }, { "label": "Ordering check", "value": "Passed · 8 shots" }, { "label": "GPU charge", "value": "0 credits" } ], "details": [ "The circles show simulated excitation probabilities, not protein binding probabilities. Every point includes 100-shot sampling uncertainty.", "The acceptance check uses six binomial standard errors plus two counts; it is an execution check, not a predictive-performance result.", "No classifier was trained in this qualification batch. OXTR occupancy evaluation remains a separate phase using held-out biological evidence." ], "phase": "qualification", "response_data": "oxtr-qrc-qualification.json", "insights": [ { "title": "Native Fibonacci and Phi Ratio", "text": "Native Fibonacci changes the ideal response by -2.2 and -0.0 percentage points in windows 1 and 2. Phi Ratio changes it by -2.8 and -0.2. Their effect is much smaller in the second window." }, { "title": "Alpha and Beta", "text": "Both reduce the ideal response in both windows: Alpha -1.6 and -2.5 percentage points; Beta -0.6 and -1.7. The individual M9 P24 paths generate different responses." }, { "title": "Gamma and Epsilon", "text": "Gamma increases the ideal response by +1.7 and +3.1 percentage points; Epsilon by +2.0 and +6.1. Their different path ordering remains visible even though they use the same six period positions." }, { "title": "Why the shuffled control matters", "text": "The shuffled representation increases the second-window response by 7.4 percentage points, more than any proposed Fibonacci representation. Response size alone cannot identify a specific Fibonacci benefit." } ] }, "quantum": { "state": "complete", "kind": "quantum", "study_id": "oxtr-qrc-01", "study_version": "1.0.0", "title": "Aquila reproduces some changes—and reveals a mismatch for Gamma and Epsilon.", "finding": "Alpha and Beta reduce the observed response in both OXTR windows, matching the direction predicted by the model. Gamma and Epsilon increase it in the first window but decrease it in the second. The hardware therefore does not reproduce one consistent ordering of the representations across both DNA windows.", "receipt": { "run_id": "oxtr-qrc-01-aquila-qualification", "model_version": "1.1.0-qualification", "execution": "aquila-qpu", "backend": "QuEra Aquila via Amazon Braket", "completed_at": "2026-10-25T01:21:52.327Z", "input_sha256": "0a86b5247d1a8e950d525debeed806109f009f6c51c70555eafcef4199336b33", "task_id": "92a97488-675a-4126-838a-75ff29e0c539" }, "metrics": [ { "label": "Quantum programs", "value": "16 × 100 shots" }, { "label": "Fully occupied measurements", "value": "1,541 / 1,600" }, { "label": "Average difference from reference", "value": "2.68 percentage points" } ], "details": [ "The average absolute difference covers all 21 observables in each of 16 programs. It is descriptive, not an occupancy-prediction score.", "59 measurements began with at least one atom missing and are excluded from the conditional response. 0 measurements were reported as failed.", "An atom absent at readout can indicate excitation or loss. The displayed 95% intervals cover sampling uncertainty and do not include every hardware error.", "These completed measurements qualify the execution route. Whether the representations improve OXTR occupancy prediction remains an independent biological test.", "All contrasts are exploratory descriptions. There is one hardware task per representation and window, run in a fixed order. Sampling uncertainty, drift and systematic errors limit causal or repeatability claims; multiple comparisons have not been used to declare a significant winner." ], "phase": "qualification", "response_data": "oxtr-qrc-qualification.json", "insights": [ { "title": "Native Fibonacci and Phi Ratio", "text": "Native Fibonacci changes the measured response by -3.8 and +1.3 percentage points in windows 1 and 2. Phi Ratio changes it by -1.4 and -0.7. These are observed differences from ordinary input, not changes in biological binding probability." }, { "title": "Alpha and Beta", "text": "Alpha changes the measured response by -5.2 and -3.0 percentage points; Beta by -1.3 and -1.9. Their downward direction matches the model in both windows. This small batch does not establish that the pattern repeats reliably." }, { "title": "Gamma and Epsilon", "text": "Gamma changes the measured response by +0.9 and -0.7 percentage points; Epsilon by +3.7 and -1.6. The second-window reversal shows that the ideal model does not fully describe these hardware measurements." }, { "title": "The control and the OXTR question", "text": "The shuffled control has the largest measured response in window 2 (+11.0 percentage points). We have measured representation-dependent responses, but have not established a Fibonacci-specific predictive benefit. Occupancy labels were not tested in this batch." } ] }, "comparison": { "state": "complete", "classical_run_id": "oxtr-qrc-01-local-qualification", "quantum_run_id": "oxtr-qrc-01-aquila-qualification", "finding": "The first experiment shows that Fibonacci, Phi Ratio and the four M9 P24 paths generate different calculated responses to OXTR DNA. Aquila reproduces some directional changes but not all; the shuffled control also generates a strong response. This gives us candidate quantum features and a concrete simulation–hardware mismatch to investigate. It does not yet answer whether those features improve transcription-factor occupancy prediction: no occupancy predictor or held-out biological test was run." } }, "updated_at": "2026-10-25T01:22:56.336442+00:00", "phase": "qualification", "status_label": "First measurement phase complete", "caption": "16 GPU simulations and 16 Aquila programs complete. Explore both sets of responses. OXTR occupancy prediction remains to be evaluated." }, "oxtr-qrc-study": { "schema": "universal-informatics/oxtr-qrc-study/v1", "id": "oxtr-qrc-01", "version": "1.0.0", "status": "measurement_qualification_complete", "question": "Do quantum responses generated from Fibonacci and M9 P24 representations improve our ability to predict transcription factor occupancy around OXTR?", "gene": "OXTR", "method": "Quantum reservoir computing", "created_on": "2026-10-25", "scope": "The first measurement phase has completed CPU and GPU checks and all 16 Aquila programs. Held-out occupancy prediction remains to be evaluated.", "atlas": { "id": "fibonacci-m9-p24", "sha256": "55da8b5e3406368cece4476720ca9d9208627e30a827fca30533d3235d74d8ff", "alpha": { "residues": [ 0, 1, 1, 2, 3, 5, 8, 4, 3, 7, 1, 8, 0, 8, 8, 7, 6, 4, 1, 5, 6, 2, 8, 1 ], "display_values": [ 9, 1, 1, 2, 3, 5, 8, 4, 3, 7, 1, 8, 9, 8, 8, 7, 6, 4, 1, 5, 6, 2, 8, 1 ] }, "beta": { "interval_sums": [ 4, 17, 16, 23, 10, 11 ], "interval_residues": [ 4, 8, 7, 5, 1, 2 ], "display_cycle": [ 4, 8, 7, 5, 1, 2 ], "intervals": [ { "from_index": 0, "to_index": 4, "interior_indices": [ 1, 2, 3 ], "interior_values": [ 1, 1, 2 ], "sum": 4, "residue": 4 }, { "from_index": 4, "to_index": 8, "interior_indices": [ 5, 6, 7 ], "interior_values": [ 5, 8, 4 ], "sum": 17, "residue": 8 }, { "from_index": 8, "to_index": 12, "interior_indices": [ 9, 10, 11 ], "interior_values": [ 7, 1, 8 ], "sum": 16, "residue": 7 }, { "from_index": 12, "to_index": 16, "interior_indices": [ 13, 14, 15 ], "interior_values": [ 8, 8, 7 ], "sum": 23, "residue": 5 }, { "from_index": 16, "to_index": 20, "interior_indices": [ 17, 18, 19 ], "interior_values": [ 4, 1, 5 ], "sum": 10, "residue": 1 }, { "from_index": 20, "to_index": 0, "interior_indices": [ 21, 22, 23 ], "interior_values": [ 2, 8, 1 ], "sum": 11, "residue": 2 } ], "minimal_cycle": [ 4, 8, 7, 5, 1, 2 ], "native_doubling": true, "recognised_doubling_cycle": [ 1, 2, 4, 8, 7, 5 ], "rotation_to_recognised": 4, "m9_doubling_cycle_present": true, "start_value": 4, "start_interval_clock_positions": [ 24, 4 ], "start_interval_values": [ 1, 1, 2 ], "circle_positions": 9, "cycle_length": 6, "endpoint_rule": "Exclude endpoints, include wraparound; raw residues used for sums. Empty interiors sum to zero." }, "gamma": { "alpha_indices": [ 0, 4, 8, 12, 16, 20 ], "clock_positions": [ 24, 4, 8, 12, 16, 20 ], "clockwise_values": [ 9, 3, 3, 9, 6, 6 ], "triangle_paths": [ [ 0, 8, 16, 0 ], [ 4, 12, 20, 4 ] ] }, "epsilon": { "alpha_indices": [ 0, 8, 20, 12, 4, 16, 0 ], "traversal_values": [ 9, 3, 6, 9, 3, 6, 9 ], "three_step_repeat": true, "formation_id": "6-nodes-offset-0", "clock_positions": [ 24, 8, 20, 12, 4, 16, 24 ], "rotation_degrees": 0.0, "status": "Proposed geometric traversal; physical interpretation not assessed." }, "orientation": "clockwise from north", "grids": "Alpha/Gamma/Epsilon: 24 period positions; Beta: 9 residue positions" }, "reference": { "species": "Homo sapiens", "assembly": "GRCh38 / hg38", "chromosome": "chr3", "start_0based": 8740380, "end_exclusive": 8779628, "length_bp": 39248, "gene_id": "ENSG00000180914", "canonical_transcript": "ENST00000316793.8", "gene_start_1based": 8750381, "gene_end_1based": 8769628, "gene_strand": -1, "selection": "Ensembl OXTR gene body plus 10,000 bases on each genomic side", "scope": "A defined locus window; distal regulatory elements outside it are not captured. Overlapping records may extend beyond its boundaries.", "origin_genomic_base_0based": 8779627, "direction": "OXTR minus strand; descending genomic coordinates", "clockwise_from": "north", "coordinate_convention": "0-based, end-exclusive" }, "template": { "id": "rydberg-reservoir-global-pulse-v1", "qubits": 6, "geometry": "Six sites on a regular hexagon; ring radius and nearest-neighbour separation 9 micrometres, with one vertex at north. Positions are fixed throughout each run.", "radius_m": 9e-06, "omega_rad_s": 2000000, "detuning_bound_rad_s": 4000000, "duration_s": 4e-06, "input_slots": 24, "edge_ramp_s": 2e-07, "input": "A 24-slot vector of motif/spacing descriptors. Each encoding uses the same source features and identical normalization fitted on training data only.", "encoding": "Global detuning varies with the input; fixed nonzero drive permits noncommuting evolution. Canonical representation weights/order define registered alternatives. No local detuning access is assumed.", "output": "Six excitation probabilities and fifteen labelled pair probabilities at the final time; additional times require distinct tasks and a new frozen version.", "model": "H(t)/hbar = Omega(t)/2 sum_i X_i - Delta_x(t) sum_i n_i + sum_i