Grover-AA on POMDP Belief Oracle
Under the paper's oracle model, amplitude amplification changes rare-evidence query scaling from O(P(e)⁻¹) to O(P(e)⁻¹ᐟ²). This is a logical sample-complexity result, not a wall-clock hardware claim.
00Quantum decision research
Quantum Autonomous Navigation, Tracking & Intelligence System
QANTIS studies hardware-calibrated rare-evidence estimation and planner-facing POMDP belief updates on IBM Heron. The quantum processor returns an ordinary posterior; policy and action remain classical.
2 public arXiv preprints · arXiv:2607.06760v1 · IBM Heron · MIT (Community Edition)
- Canonical spelling
- QANTIS · Q-A-N-T-I-S
- Research context
- Quantum · IBM Heron · POMDP
- Primary records
- arXiv:2603.00785 · arXiv:2607.06760
01Research model
A calibrated belief-update service, not an autonomous stack.
The public surface explains the method, reported results, reproducibility record, and limits. It does not turn a controlled hardware study into a production claim.
Planner-Facing Posterior Checks
Across the reported sequential Tiger POMDP checks, the hardware-derived posterior and exact Bayes posterior selected the same immediate action. Policies and action execution remain with the classical planner.
FPC-QAOA for Multi-Target Data Association
The foundational paper casts multi-target data association as a QUBO and reports an 11-variable FPC-QAOA hardware feasibility case. Classical Hungarian and GNN baselines remain faster and exact on the tested small instance, so this is not an advantage claim.
Composable Error Mitigation
Across the foundational study, ZNE helped reported circuits below roughly 100 ISA gates and hurt examples above roughly 1,000. The result is a circuit- and backend-specific operating map, not a universal mitigation rule.
- 01
Classical input
A prior belief and observation model define the update requested by the planner.
- 02
Evidence estimation
IBM Heron circuits estimate the rare-event evidence term under a calibrated operating envelope.
- 03
Ordinary posterior
The service returns a classical posterior rather than replacing the planner or policy layer.
- 04
Decision check
The study compares the resulting immediate action with the action selected by exact Bayes.
02Public records
Two papers. One continuous research line.
The 2026 records separate foundational hardware feasibility from the later sequential belief-update study.
Public arXiv preprint · February 28, 2026
QANTIS: A Hardware-Validated Quantum Platform for POMDP Planning and Multi-Target Data Association
arXiv:2603.00785v1
31 pages · 4 figures · 12 tables · quant-ph + cs.AI
The foundational QANTIS paper reports a hardware campaign counted as 45 experiments across POMDP belief conditioning and multi-target data association on three IBM Heron backends; the count is not 45 independent replications.
Paper recordOpen +Close −
- Grover amplitude amplification for POMDP belief conditioning
- Closed-loop hybrid quantum-classical Tiger POMDP
- FPC-QAOA for multi-target data association
- 45 reported campaign experiments across IBM Heron backends, not independent replications
Public arXiv preprint · July 7, 2026
QANTIS: Hardware-Calibrated Sequential POMDP Belief Updates on IBM Heron
arXiv:2607.06760v1
10 pages · 6 figures · cs.AI + quant-ph
CC BY 4.0
A controlled hardware case study that treats the quantum processor as a calibrated belief-update service: it receives a prior and observation model, estimates rare-event evidence, and returns an ordinary posterior to a classical planner.
Paper recordOpen +Close −
- Sequential Tiger POMDP runs at 8 and 12 primary steps
- 20-step and 32-step controls within the reported operating band
- Boundary-aware BIQAE near zero and one
- Immediate-action agreement with exact Bayes in every reported check
Publication record and research keywordsRecord +
Attribution
Author and citation details are maintained in the linked arXiv records.
Keywords
Quantum computing · POMDP · Amplitude amplification · Fixed-point amplitude amplification · BIQAE · Sequential belief updating · QAOA · Multi-target tracking · Data association · NISQ · Error mitigation · IBM Heron
03Explore and access
Test the decision logic.
The interactive surface is didactic. It helps explain evidence routing; it is not the research implementation or an autonomous decision system.
01 · InferCalibrated belief
Turn noisy, partial, or rare observations into a calibrated posterior belief — the single source of truth that every downstream step depends on.
Grover-AA on POMDP belief
O(P(e)⁻¹) → O(P(e)⁻¹ᐟ²) query-complexity change under the paper's oracle model; not a wall-clock result
BIQAE
Boundary-aware Bayesian quantum amplitude estimation under bounded depth
Hellinger distance ≤ 0.0149
vs ideal distribution across T=8 hardware steps (Tiger POMDP)
qantis / decision-engine.infer
Inputs
- Raw sensor stream
- Prior model
- Observation noise model
Outputs
- Posterior belief
- Confidence intervals
- Calibration diagnostics
Stack
Can compose with qmesh → signed run manifest → offline-verifiable provenance chain.
Click a step above to inspect inputs, outputs, and the techniques QANTIS uses at that stage.
Community and collaborator access.
The public repository carries the inspectable community surface. Collaboration scope is discussed separately and does not change the public claim boundary.
Compare editions
18 rows
| Feature | Community Edition · public · MIT | Collaborator Edition · private · partners only |
|---|---|---|
| Backend abstraction layerframework | Public connectors | Hardened, multi-vendor, optimised |
| Configuration & reproducibilityframework | Included | Included |
| Error mitigation pipelineframework | Baseline (ZNE, Pauli twirling) | Full mitigation & calibration stack |
| Benchmarking infrastructureframework | Illustrative | Full experimental harness |
| Infer — calibrated beliefengine | Basic surface | Calibrated, production-grade |
| Risk — event & tail-riskengine | Basic surface | Calibrated, production-grade |
| Optimise — feasible decisionsengine | Basic surface | Calibrated, production-grade |
| Verify — trust & diagnosticsengine | Basic surface | Calibrated, production-grade |
| POMDP planning (Tiger reference)applications | Included | Included |
| Multi-Hypothesis Tracking (MHT)applications | Included | Included |
| Quantum-Bio Intelligenceapplications | Not included | Included |
| CRISPR moduleapplications | Not included | Included |
| Sensor fusion · adversarial robustness · mission orchestrationapplications | Not included | Included |
| Hardware campaign artefactsops | Aggregate results in cited preprints; raw campaign artefacts not bundled | Available by governed engagement |
| Comparative benchmarks vs classical SOTAops | Not included | Included |
| Confidential datasets & mission profilesops | Not included | Included |
| Supportops | Community, best-effort | Dedicated engineering |
| Licenceops | MIT | Commercial / partner agreement |
04Hardware evidence
Report the operating point, not a universal promise.
Results below are reported observations from controlled IBM Heron studies. They are not wall-clock speedup, production readiness, or quantum-advantage claims.
- Probability Amplification
- 0.179 → 0.907
- one reported Grover operating point
- Hellinger Distance
- 0.0015
- hardware posterior vs exact Bayes
- Usable Shots
- 1463 → 7429
- accepted-event usable-shot yield
- QPUs Tested
- 3
- IBM Heron backends
Validated route
Problem → Simulation → Hardware → Public record
Reported backends
ibm_torino · ibm_fez · ibm_marrakesh
2 arXiv preprints · IBM Heron QPUs · Sequential posterior checks
B01The foundational study found ZNE useful below ~100 ISA gates
B02The same study found ZNE harmful above ~1000 ISA gates
B0311-variable FPC-QAOA hardware case; quality degraded at 19 variables
05Code and reading
Reproduce the work, then inspect the limits.
Three packages keep shared infrastructure, POMDP research, and tracking research composable. QANTIS can also use qmesh as an experiment-substrate layer without merging their claims.
quantum-common
Shared utilities, circuit primitives, error mitigation (ZNE, Pauli twirling), and backend abstraction layer for IBM Qiskit Runtime.
quantum-pomdp
POMDP belief-state oracle construction, Grover amplitude amplification, closed-loop hybrid planning loop, and Tiger POMDP reference implementation.
quantum-mht
Multi-target data association via QUBO formulation, FPC-QAOA solver, classical MHT baseline, and cost-matrix construction for tracking scenarios.
Synthesis4 field notes
Synthesis01
Two QANTIS IBM Heron papers, one increasingly precise research question.
QANTIS moved from a cross-backend campaign reported as 45 experiments to a controlled sequential belief-update service. Reading both papers together shows what survived hardware testing, what was narrowed, and what still needs stronger evidence.
15 min readQuantum research
Synthesis02
A critical review of QANTIS hardware evidence and its limits.
The QANTIS result is credible when read narrowly: calibrated shallow belief updates can remain close to exact Bayes in controlled hardware runs. The evidence does not establish wall-clock advantage, general scale, or end-to-end autonomy.
16 min readQuantum research review
Synthesis03
A QANTIS reproducibility checklist for quantum hardware evidence.
The right reproducibility unit is not a notebook screenshot or a best metric. It is a versioned campaign bundle that reconstructs the posterior, its hardware context, its classical reference, and the decision it affected.
14 min readQuantum reproducibility
Synthesis04
Where QANTIS quantum inference belongs in an autonomous system.
The credible role for near-term quantum hardware is not an autonomous brain. It is a replaceable inference service inside a classical perception-to-action loop, invoked only when its calibration and depth gates pass.
14 min readQuantum AI systems
Technical deep dive6 field notes
Technical deep dive01
QANTIS as a calibrated belief-update service.
QANTIS does not replace the planner. Its hardware-tested inference core accepts a prior and observation model, estimates the difficult evidence term, and hands a conventional probability distribution back to classical software.
14 min readQuantum decision systems
Technical deep dive02
QANTIS FPAA and sequential belief stability.
The headline FPAA run achieved a maximum Hellinger distance of 0.009 at 32,768 shots per step. At 10,000 matched shots, the maximum was about 0.033, so the evidence supports stability rather than equal-budget superiority.
13 min readSequential inference
Technical deep dive03
QANTIS boundary-aware BIQAE where amplitudes become fragile.
On the reported Pittsburgh backend calibration, boundary error fell from 0.6317 to 0.00224 at amplitude 0.01 and from 0.4890 to 0.00773 at amplitude 0.95.
13 min readQuantum calibration
Technical deep dive04
QANTIS rare-event evidence: an envelope, not an advantage claim.
The rarest tested row closely tracks the analytic accepted-event probability, but transpilation keeps the circuit shallow. The result maps a logical sample-complexity envelope rather than validating deep circuits or wall-clock speedup.
14 min readRare-event inference
Technical deep dive05
QANTIS posterior fidelity when the action stays the same.
The reported 8-step matched-shot, 20-step, and 32-step checks show the same immediate action as exact Bayes with zero scored cumulative value loss under the tested Tiger rule.
12 min readDecision assurance
Technical deep dive06
QANTIS on IBM Heron: circuit depth defines the current boundary.
The paper's exploratory scaling probes distinguish state-space size from compiled circuit depth. Optimized four-state cases map a shallow corridor; deeper chains become noise-frontier markers.
14 min readQuantum hardware
Collaborate on one bounded research question.
Start with the classical baseline, hardware envelope, evidence plan, and a result that remains useful even when the quantum route does not earn promotion.