Version 6.1 develops an integrated research framework for a modular particle detector usingmultiple quantum correlation resources.The architecture does not posit one universal quantum resource. Instead, it defines a resourcestackH = {C, D, S, V, E}, (1)together with an adaptive controller operating on measured resource estimates, uncertaintyintervals, detector conditions, and environmental covariates.The V6.1 architecture introduces five major extensions: 1. leakage-resistant experimental data partitioning;2. explicit calibration and domain-shift correction;3. uncertainty-aware adaptive resource selection;4. multi-objective classification and energy inference;5. hierarchical reproducibility and falsification criteria.The detector is represented as a conditional measurement system:p(Y | P, Z, Q, Θ), (2)where P denotes particle state, Z environmental conditions, Q the quantum subsystem, andΘ the locked experimental configuration.The adaptive controller selects a resource or resource subset using a preregistered utilityfunction:r⋆ = arg minr∈HLr. (3)Unlike a simple point-estimate controller, V6.1 explicitly propagates uncertainty and allowsan abstention state when the available evidence does not justify a classification.The primary validation framework evaluates classification, energy reconstruction, backgroundrejection, calibration, calibration transfer, robustness, and independent replication.Version 6.1 additionally integrates an explicit sensor platform layer, an event-conditioningchannel, a multi-resource feature vector, and a readout-and-timing block.No experimental result is claimed.
Version 6.1 develops an integrated research framework for a modular particle detector usingmultiple quantum correlation resources.The architecture does not posit one universal quantum resource. Instead, it defines a resourcestackH = {C, D, S, V, E}, (1)together with an adaptive controller operating on measured resource estimates, uncertaintyintervals, detector conditions, and environmental covariates.The V6.1 architecture introduces five major extensions: 1. leakage-resistant experimental data partitioning;2. explicit calibration and domain-shift correction;3. uncertainty-aware adaptive resource selection;4. multi-objective classification and energy inference;5. hierarchical reproducibility and falsification criteria.The detector is represented as a conditional measurement system:p(Y | P, Z, Q, Θ), (2)where P denotes particle state, Z environmental conditions, Q the quantum subsystem, andΘ the locked experimental configuration.The adaptive controller selects a resource or resource subset using a preregistered utilityfunction:r⋆ = arg minr∈HLr. (3)Unlike a simple point-estimate controller, V6.1 explicitly propagates uncertainty and allowsan abstention state when the available evidence does not justify a classification.The primary validation framework evaluates classification, energy reconstruction, backgroundrejection, calibration, calibration transfer, robustness, and independent replication.Version 6.1 additionally integrates an explicit sensor platform layer, an event-conditioningchannel, a multi-resource feature vector, and a readout-and-timing block.No experimental result is claimed.
Constructing optimal quantum information protocols without complete knowledge of the underlying states or channels is a central challenge. We address this challenge by developing universal correlation detection as a common building block for quantum communication. Our detectors distinguish a bipartite state from the product of its marginals and attain the same first-order asymptotic performance as optimal tests constructed with complete state information. For general bipartite quantum states, knowledge of a single marginal suffices: a detector depending only on that marginal is first-order optimal for every compatible state. For classical-quantum states, the detector is fully universal and requires no prior state information. By combining these detectors with position-based decoding and convex splitting, we construct channel-independent coding schemes that achieve capacity for a range of communication tasks. These results turn universal correlation detection into a systematic tool for universal protocol design, providing a unified route to designing capacity-achieving protocols for many communication tasks over unknown quantum channels.
Quantum metrology exploits physical resources whose parameter sensitivity can exceed that ofconventional measurement strategies under appropriate conditions. However, a resource that isoptimal under one noise, temperature, drift, preparation, or detection regime need not remainoptimal under another.Version 6.1 proposes an adaptive hierarchy metrology architecture in which a predefined set ofprotocol families is available: H = {C, D, S,E}.The central methodological correction of Version 6.1 is that coherence, discord, steering, andentanglement are not themselves identified with quantum Fisher information. Instead, each resourcecorresponds to a physically specified preparation–encoding–noise– measurement protocol. Theresulting parameterized density operator defines the quantum Fisher information (QFI), while theactual measurement defines the classical Fisher information (CFI).The adaptive system therefore estimates, for each candidate protocol,FQr(θ|z), FCr(θ|z), Ir(θ|z) = FCr(θ|z)τr,where r denotes the protocol family, z denotes the measured operating context, and τr is thetotal wall-clock cost per useful trial.The primary optimization target is the information rate, not raw QFI.Selection is uncertainty-aware. Rather than choosing the resource with the largest pointestimate, the system may use lower confidence bounds, switching penalties, feasibility constraints,and hysteresis:rt = arg maxr∈Ft[LCB1−α (Ir|zt) − Pswitch(r, rt−1)] .Version 6.1 additionally introduces an overhead-aware net advantage quantity:Anet =Iadaptmaxr Ifixed,r·11 + ηoverhead,where ηoverhead accounts for characterization, switching, computational, and dead-time coststhat may not be entirely captured by the per-shot cycle-time τr.The test remains locked against target-outcome leakage: the primary adaptive policy may usecalibration and context variables, but it must not use the target measurement outcomes of theheld-out test block to modify the selection rule.The system is evaluated against fixed-resource baselines under equalized wall-clock budgets andheld-out operating conditions. Primary analysis uses paired information-rate comparisons withhierarchical uncertainty estimation.The framework includes preregistered thresholds, falsification criteria, robustness analysis,selection regret, switching stability, shadow-mode validation, missing-data rules, reproducibilityrequirements, audit logs, synthetic reference implementations, and a staged experimental validationplan.
Version 6.1 develops the Quantum Correlations Stack into a complete multi-resource researcharchitecture.The framework integrates six principal resource families:1. quantum coherence;2. quantum discord;3. quantum steering;4. contextuality;5. entanglement;6. Bell nonlocality.Version 6.1 introduces and preserves a formal separation between:witness ̸= estimator ̸= certification ̸= selection ̸= application utility. (1)Each resource is represented by an estimated state, uncertainty, certification status, imple-mentation cost, latency, robustness, and application utility.A resource-state vector is defined asR = (RC , RD, RS, RV , RE, RB, uC , uD, uS, uV , uE, uB). (2)The selection problem is extended from scalar optimization to constrained multiobjectiveoptimization:R⋆ ∈ arg minR∈HcertF(R; A), (3) where Hcert contains only resources that pass preregistered certification criteria.The Pareto frontier is explicitly retained so that the architecture does not artificiallymanufacture a unique winner from an arbitrary weighting scheme.The framework additionally specifies:• resource certification;• witness-based evidence versus full resource estimation;• uncertainty propagation;• multiplicity control;• classical and quantum reference states;• resource-conversion accounting;• FMEA risk analysis;• Go/No-Go criteria;• configuration locking;• digital audit trails;• economic-cost separation;• independent reproduction;• computational reference implementation.No experimental result is claimed.
Version 6.1 develops an integral framework for an analog quantum simulator of spin modelsbased on programmable superconducting-qubit arrays.The principal objective is not merely to construct a quantum device, but to establish atraceable mappingcontrol parameters −→ Hreal −→ quantum evolution −→ observables −→ classical reference.The framework supports transverse-field Ising, XY, XXZ, Heisenberg, long-range, anddisordered spin Hamiltonians.Version 6.1 introduces an explicit Hamiltonian- identification layer between hardwarecalibration and scientific validation.The realized Hamiltonian is decomposed into target terms, static calibration errors, dynamiccontrol errors, crosstalk, leakage, decoherence, and residual unwanted interactions.Validation is organized hierarchically:1. hardware calibration;2. Hamiltonian identification;3. state-preparation validation;4. readout calibration;5. static observable validation;6. dynamical observable validation;7. finite-size benchmarking;8. statistical equivalence testing;9. cross-device reproducibility;10. independent analytical reproduction. The statistical framework replaces the inadequate criterion of “statistical significance ofagreement” with an equivalence framework based on preregistered tolerances.The primary hypothesis is therefore formulated using two one-sided tests (TOST) or anequivalent confidence interval criterion:|∆O| < ϵO.Version 6.1 additionally specifies:• a supplementary Bayesian posterior probability of equivalence as a robustness check;• an explicit distinction between engineering no-go and physical falsification.The framework also specifies negative controls, positive controls, blind analysis, lockedanalysis code, exclusion rules, uncertainty propagation, data provenance, and reproducibilityrequirements.No experimental result or quantum advantage is claimed.
One of the main foci of modern applied quantum information theory\nis the production of large-scale quantum entanglement involving many\nparticles, to achieve the next-generation quantum technologies. Although a full-scale quantum computer is still far away in time, in the next\nfew years we can expect to have quantum devices composed of up to a\nhundred controllable qubits. The primary challenge in moving towards\nsuch devices lies in the development of reliable and resource-efficient\ndetection techniques to prove genuine quantum advantage. The main\nobjective of this thesis is to investigate novel methods to detect the presence of quantum correlations in such systems, in particular, quantum\nentanglement and quantum nonlocality.\nThe first part of this thesis is dedicated to entanglement detection\nin large-scale quantum systems. Our main goal is to develop a novel\nprobabilistic method in which entanglement is seen as an ability of a\nquantum system to accomplish certain information-processing tasks.\nWe show that for certain classes of large (e.g. few tens of qubits) quantum states, even a single copy of a quantum state suffices to detect\nentanglement with a high confidence. Compared to the standard detection methods, this makes our method exceptionally resource-efficient.\nThe developed probabilistic scheme applies to multiple classes of states, vital for quantum computation, such as cluster states or ground\nstates of local Hamiltonians.\nIn the second part of this thesis, we develop a generic framework\nfor translating any entanglement witness into a resource-efficient probabilistic scheme. We show that the confidence level of entanglement\ndetection grows exponentially fast with the number of detection events,\nwhich makes this ansatz very efficient and reliable. Furthermore, we\npresent the first experimental performance of our method by verifying\nthe presence of entanglement in a photonic six-qubit cluster state.\nThe third part of this thesis describes the extension of our entanglement verification method to quantum nonlocality. Concrete examples\nare presented where we convert Bell’s inequalities into the probabilistic\nprocedure and incorporate our method into self-testing schemes. We\nshow that the performance of our method significantly exceeds the ability of the existing methods for detection of quantum nonlocality and\nself-testing.\nThe last part of this thesis is a study of the weak-convergence properties of random variables generated by quantum measurements. Beginning with a sequence of random variables generated by repeated\nunsharp quantum measurements, we study the limit distribution of\nmeasured relative frequency. We provide the de Finetti-type of representation theorem for all separable states, showing that the measured\ndistribution can be well approximated by a mixture of normal distributions. Additionally, we investigate the convergence rates and show\nthat the relative frequency converges to some constant at the rate of\norder 1=pN for all separable inputs. Finally, we provide an example of\na strictly unsharp quantum measurement where we obtain better scaling by using entangled inputs. We find such behaviour of entangled\nstates relevant for quantum information processing.