{"uid":"cap_P3Rn1CZqlgFNQUaz053-5","slug":"maha-strategies-quantum-measurement-uncertainty-binomial-shot-count-b50c8f2e","name":"Maha Strategies Quantum Measurement Uncertainty — Binomial Shot-Count Statistics","description":"For agents reviewing shot-count results: return probabilities and binomial confidence intervals with the interval method and independence assumptions.","url":"https://www.mahastrategies.com/api/v1/micro/quantum-measurement-uncertainty?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method","bodyType","body"],"properties":{"body":{"type":"object","required":["dataClass","counts"],"properties":{"counts":{"type":"array","maxItems":32,"minItems":1},"dataClass":{"enum":["public","synthetic"],"type":"string"}},"additionalProperties":false},"type":{"type":"string","const":"http"},"method":{"enum":["POST"],"type":"string"},"bodyType":{"enum":["json","form-data","text"],"type":"string"}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object","required":["version","offerId","amountBaseUnits","inputDigest","result","boundaries","receiptDigest"],"properties":{"result":{"type":"object"},"offerId":{"enum":["quantum-measurement-uncertainty"],"type":"string"},"version":{"enum":["maha-microproducts/0.1"],"type":"string"},"boundaries":{"type":"array","maxItems":128,"minItems":0},"inputDigest":{"type":"string","maxLength":71},"receiptDigest":{"type":"string","maxLength":71},"amountBaseUnits":{"enum":["12001"],"type":"string"}},"additionalProperties":false}}}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.012001","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.012001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.012001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.012001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_BwCurQCQ3fZLXUESCwqL6","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.012001","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes probabilities and binomial confidence intervals from shot-count arrays using a specified interval method and independence assumptions","exampleAgentPrompt":"I have shot-count results from a quantum measurement experiment — the counts array is [42, 58, 37, 63] and the data is synthetic. Can you compute the binomial probabilities and confidence intervals with independence assumptions for those counts?","exampleUseCases":[{"title":"Quantum circuit shot-count analysis","prompt":"I ran a quantum circuit 100 times and got these shot counts: [34, 66, 51, 49, 29, 71]. The data is synthetic. Can you compute the binomial probabilities and confidence intervals so I can assess measurement uncertainty?"},{"title":"Pass/fail binomial proportion estimation","prompt":"I have public pass/fail counts from a hardware trial: [88, 12, 75, 25, 60, 40]. Please calculate the binomial confidence intervals and probabilities for each pair so I know the uncertainty bounds."},{"title":"Repeated binary measurement uncertainty report","prompt":"For a series of repeated quantum measurements with shot counts [100, 0, 95, 5, 82, 18] — marked as synthetic data — can you give me the binomial confidence intervals and probability estimates assuming independence between shots?"}],"resultDescription":"Returns a structured result object containing computed probabilities and binomial confidence interval boundaries for each supplied shot-count value, along with a version identifier, offer ID (quantum-measurement-uncertainty), input digest, amount in base units (12001), and a receipt digest for auditability.","failureModes":["Invalid or empty counts array (below minItems:1 or above maxItems:32) returns a validation error","Unrecognized dataClass value (must be 'public' or 'synthetic') causes schema rejection","Missing required body fields (dataClass or counts) returns a 400-level error","Non-integer or null values in counts array may fail schema validation","Payment failure or insufficient USDC balance prevents endpoint execution"],"whenToPreferThis":"Choose this endpoint when you have discrete shot-count arrays from quantum measurements or repeated binary trials and need statistically rigorous binomial probabilities with confidence intervals under independence assumptions. It is purpose-built for quantum measurement post-processing workflows where standard statistical libraries are not available inline, and where a compact, auditable per-call result with receipt digest is needed. Prefer it over generic statistics APIs when you need tight integration with the Maha microproduct receipt/audit trail.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T06:45:10.633Z","isFirstParty":false,"canonicalSlug":"maha-strategies-quantum-measurement-uncertainty-binomial-shot-count-b50c8f2e"}