[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84147-en":3,"doc-seo-84147-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},84147,2336464648746,"Skyler","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","QANTIS Hardware Calibrated Sequential POMDP Belief Updates on IBM Heron","Autonomous systems under partial observability act on beliefs rather than raw sensor events. QANTIS treats a quantum processor as a calibrated belief-update service: it receives a prior belief and an observation model, estimates a rare-event evidence term, and returns a classical posterior for a downstream planner. This paper tests whether the service can be reused across sequential decision steps on IBM Heron without corrupting the planner-facing posterior. A controlled hardware case study compares no amplification, guarded Grover amplification, and all-step fixed-point amplification, verifying matching action selection under reported 8- and 12-step runs.","QANTIS: Hardware–Calibrated Sequential POMDP Belief Updates on IBM Heron  \nBayram Y¨uksel Eker   \nNeura Parse Ltd. London, United Kingdom  \nSuayb S. Arslan   \nDept. of Computer Engineering Bo˘gazic¸i University Istanbul, Turkey  \n¨Ozg¨ur Nazlı   \nDept. of Physics Izmir University of Economics Izmir, Turkey  \nMustafa Serhat Demirgil   \nFaculty of Engineering University of Toronto Toronto, Canada  \nFurkan Deligz   \nIstanbul Technical University Istanbul, Turkey  \narXiv :2607 .06760v 1 [ cs .AI ] 7 Jul 2026  \nAbstract—Autonomous systems under partial observability acton beliefs, not raw sensor events. QANTIS treats the quantum processor as a calibrated belief-update service in that loop: it receives a prior and an observation model, estimates the rareevent evidence term, and returns an ordinary posterior to a classical planner. This paper asks whether that service can be reused across a sequential Tiger POMDP horizon on present IBM Heron hardware without corrupting the planner-facing posterior. We answer with a controlled hardware case study rather than an end-to-end autonomy or wall-clock speedup claim. The study compares no amplification, guarded Grover amplification, and allstep fixed-point amplification on the same trajectory, then checks whether the returned posterior would change the downstream action. All-step FPAA preserves the Tiger posterior across the reported 8-step and 12-step primary runs, and the 20-step and 32-step controls remain inside the same operating band. In every reported decision check, the hardware posterior and the exact Bayes posterior select the same immediate action. Boundaryaware BIQAE stabilizes amplitude estimation near zero and near one, while a rare-event sweep maps the logical sample-complexity envelope for one-in-a-million evidence. The result is an operating envelope for a hardware-calibrated belief-update primitive, not a standalone hardware-advantage claim.  \nIndex Terms—quantum computing, POMDP inference, belief updating, amplitude amplification, Bayesian amplitude estimation, NISQ hardware, IBM Heron  \nI. INTRODUCTION  \nAutonomous systems under partial observability do not act directly on raw sensor events. They first turn each noisy observation into a posterior belief, and only then does a classical planner choose what to do next. The difficult case is a rare observation: the evidence term is small, classical sampling can become expensive, and any inference error is carried forward as the next prior.  \nThis paper studies one narrow hardware question. Can a calibrated quantum belief-update primitive be reused across several POMDP decision steps on present IBM Heron hardware without damaging the posterior that the planner receives? The answer is a controlled hardware case study. We do not claim an end-to-end autonomous-system demonstration, a wallclock speedup, or a validated large-state autonomy stack. The  \nTABLE I  \nOPERATIONAL CONTRACT OF THE QANTIS BELIEF-UPDATE SERVICE . THE PAPER EVALUATES THIS MODULE , NOT THE WHOLE AUTONOMY STACK AROUND IT.  \n\n| Stage | Contract checked in this paper |\n| --- | --- |\n| Input | A prior belief and observation model from the classical planner. |\n| Quantum step | Estimate the rare-event evidence term using calibrated amplification and BIQAE. |\n| Safety check | Compare the returned posterior with exact Bayes and verify whether the same action would be chosen. |\n| Output | An ordinary posterior distribution; downstream planning remains classical and out of scope. |\n\nvalidated object is smaller and easier to audit: the plannerfacing posterior returned by the QANTIS inference core in Fig. 1.  \nThe paper uses a small acronym set repeatedly: amplitude amplification (AA) boosts rare evidence events; fixed-point AA (FPAA) uses softer phases to avoid overshoot; BIQAE estimates the resulting amplitude; and the POMDP is the classical beliefand-action model. The reason for using AA is simple: in the rare-event regime it changes the inference-side sampling burden f","cbCaicl62W3NZHKh","https://ap.wps.com/l/cbCaicl62W3NZHKh","pdf",204000,1,10,"English","en",105,"# Introduction\n## Operational contract of the QANTIS belief-update service\n## Claim hierarchy and evidence scope","[{\"question\":\"What problem does QANTIS address in partially observable autonomous systems?\",\"answer\":\"It focuses on updating a planner-facing belief under rare observations, where the evidence term is small and inference errors can accumulate across steps.\"},{\"question\":\"How is the QANTIS belief-update service designed to interact with classical planning?\",\"answer\":\"It estimates the rare-event evidence term using calibrated quantum procedures and outputs an ordinary posterior distribution while keeping downstream planning classical.\"},{\"question\":\"What is the key validation result on IBM Heron hardware?\",\"answer\":\"The study finds that all-step fixed-point amplification preserves the Tiger POMDP posterior across the primary 8-step and 12-step runs, with hardware posteriors selecting the same immediate action as the exact Bayes posterior in every reported decision check.\"}]",1784193430,25,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"qantis-hardware-calibrated-sequential-pomdp-belief-updates-on-ibm-heron","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/qantis-hardware-calibrated-sequential-pomdp-belief-updates-on-ibm-heron/84147/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does QANTIS address in partially observable autonomous systems?","Question",{"text":75,"@type":76},"It focuses on updating a planner-facing belief under rare observations, where the evidence term is small and inference errors can accumulate across steps.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the QANTIS belief-update service designed to interact with classical planning?",{"text":80,"@type":76},"It estimates the rare-event evidence term using calibrated quantum procedures and outputs an ordinary posterior distribution while keeping downstream planning classical.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the key validation result on IBM Heron hardware?",{"text":84,"@type":76},"The study finds that all-step fixed-point amplification preserves the Tiger POMDP posterior across the primary 8-step and 12-step runs, with hardware posteriors selecting the same immediate action as the exact Bayes posterior in every reported decision 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