arXiv subjects

Özgür E. Müstecaplıoğlu

Publications and source records attributed to Özgür E. Müstecaplıoğlu.

At least 19 recordsLinked to original sources

arXiv2026

Finite-Size Effects in Quantum Metrology at Strong Coupling: Microscopic vs Phenomenological Approaches

Equilibrium quantum metrology is often formulated under assumptions of weak system-bath coupling and thermodynamic limit scaling, which may not be valid for realistic finite-size (FS) quantum devices. Here, we establish how strong coupling (SC) and FS effects jointly modify achievable precision bounds for equilibrium quantum probes. Considering a transverse-field anisotropic XY spin chain coupled to a thermal environment, first utilize we derive a full polaron transform to derive the effective Hamiltonian at equilibrium. Then, using the bare Hamiltonian and the obtained effective Hamiltonian and taking into account the role of FS effects in the calculation of partition function, we derive an analytic expressions for the quantum Fisher information (QFI) for a general parameter for the equilibrium state in weak coupling (WC) and SC regimes, respectively. In contrast to this microscopic approach, we also utilize the Hill's phenomenological nanothermodynamics to calculate an effective QFI expression at SC. Our results, presented for specific cases of magnetometry and thermometry, reveal that considering FS and SC effects lead to substantial and systematic deviations in QFI, even for moderate system sizes, and that commonly used thermodynamic-limit approximations can significantly misestimate precision. This work also highlights the inadequacy of phenomenological approaches in describing the metrological capability and thermodynamic behavior of systems at SC. Our work establishes a consistent framework for evaluating metrological performance of realistic, finite quantum devices operating beyond the weak-coupling paradigm.

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arXiv2026

Boundary-accessible work in a collision-charged topological quantum battery

Quantum batteries store energy in nonequilibrium quantum states. The ergotropy sets the work extractable by an arbitrary global unitary, but a device usually exchanges energy through a single local port. It remains unclear how much stored work such a port can deliver, and whether topological edge modes help. We study a dimerized spin chain of Su-Schrieffer-Heeger (SSH) type. Excited two-level ancillas charge it at one end by repeated collisions, and an initially empty two-level load discharges it at the same site. An exact free-fermion mapping yields a bound on the load work for all number-conserving quadratic extraction protocols. The load gains extractable work only if a single-particle mode of the battery holds more than half an excitation. Resonant charging fills the topological edge mode above this threshold. A single boundary pulse then delivers 98.6% of the maximal load work allowed by the bound for representative parameters. Under the same six-collision controls, the trivial-phase load remains passive. Within the protocol that selects the load pulse for maximum delivered work, cycle power peaks at a finite collision number while delivered work continues to increase over the scanned range. Over the tested range, the advantage survives hopping disorder, which preserves chiral symmetry. On-site disorder breaks this symmetry and leaves a finite fraction of loads passive. Topology thus supplies a localized access channel, while spectral matching and symmetry decide whether stored energy becomes usable local work.

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arXiv2026

The Quad-$C_5$ Graph: Maximum Contextuality Gap on Eight Vertices

Quantum measurements can exhibit contextuality: their outcomes cannot always be explained by assigning pre-existing values that are independent of which compatible measurements are performed together. The Klyachko-Can-Binicioğlu-Shumovsky (KCBS) inequality provides the canonical minimal test of this effect for a single three-level quantum system, or qutrit, using five measurement events arranged as a pentagon. Here we ask whether a larger but still compact set of measurement events can produce a stronger separation between quantum predictions and the corresponding noncontextual limit. We perform an exhaustive search over all 11,117 connected non-isomorphic graphs with eight vertices, where each vertex represents a measurement event and edges connect pairs of events that cannot occur together. We identify a sparse ten-edge graph, which we call Quad-$C_5$, as the unique maximizer of this separation at the reported numerical precision. The graph can be understood as four overlapping KCBS pentagons, with every edge shared by two pentagons. Quad-$C_5$ already demonstrates contextuality in a qutrit, for which we obtain an exact analytical result and find the same violation above the noncontextual bound as in the original KCBS test. The larger quantum-noncontextual separation allowed by the graph, however, becomes accessible in a four-level quantum system, where numerical optimization reaches the full graph-theoretic quantum bound and yields a larger contextuality gap than the standard eight-vertex Wagner-graph benchmark while requiring fewer pairwise constraints. Quad-$C_5$ therefore provides a compact connection between minimal qutrit contextuality and stronger contextuality tests available in higher-dimensional quantum systems.

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arXiv2026

Squeezing- and non-Gaussianity-enhanced quantum thermometry and magnetometry via quadratic interactions in optomechanical-like systems

Standard optomechanical sensors operating in the low-temperature regime often face fundamental precision limits imposed by vacuum fluctuations. Here, we demonstrate that moving beyond conventional radiation-pressure interactions and exploiting quadratic coupling can surpass these limits, generating intrinsic squeezing and non-Gaussian features in the probe state. We study quantum thermometry and magnetometry in a coupled two-resonator system, focusing on estimating the temperature of a thermal bath and an external magnetic field. The resonators are assumed to be in thermal equilibrium with a common bath, while a weak magnetic field acts on one of the resonators. We perform measurements on a single resonator, which serves as the probe to estimate both parameters. We compute the quantum Fisher information of the probe for two different interaction models between the resonators. Our results show that the counter-rotating terms in the quadratic interaction naturally induce squeezing at intermediate coupling and strong non-Gaussian correlations as the coupling increases further. These effects yield orders-of-magnitude enhancement in sensitivity in the low-temperature and weak-field regimes compared to standard radiation-pressure couplings. Finally, we investigate multiparameter estimation and find that, although the optimal measurements remain compatible, statistical correlations between parameters prevent the simultaneous estimation of temperature and magnetic field from attaining single-parameter precision.

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arXiv2026

Coherence-Enhanced Spatial Quantum Thermometry

Quantum thermometry has long promised sensitivities beyond classical limits, with recent paradigms highlighting quantum coherence as a primary driver of precision. While most studies focus on single-point temperature estimation, we extend this framework to the spatial domain. We consider a probe two-level system (TLS) coupled asymmetrically to an auxiliary TLS that equilibrates with a sample of profile T(x). The reduced probe state carries coherence in its local basis that remains temperature-sensitive after the probe transition has frozen out, yielding a Fisher information exponentially larger at low temperature than that of a population-only readout. An exact reparametrization converts the thermometric precision into a local spatial distinguishability bound; its validity requires only a sufficiently small relative temperature uncertainty and yields an explicit measurement budget. Adding auxiliary TLSs shifts the array's optimal working temperature upward and broadens the useful sensing window, with the achievable gain ultimately limited by the total available coupling rather than by an indefinite scaling law. Finally, we propose a microwave Mach-Zehnder interferometer that maps the temperature-dependent probe coherence onto an experimentally accessible quadrature observable.

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arXiv2026

Distribution of Bell State Entanglement in Qubit Networks via Collision Models

We investigate the selective generation of Bell-pair entanglement in three qubit networks using a standard quantum collision model. By varying the network geometry, the node contacted by the ancilla, and the interaction Hamiltonians, we identify configurations in which high pairwise concurrence and Bell state fidelity are generated between different target qubits, including nonadjacent qubits and qubits not directly coupled to the ancilla. For comparison, we also consider the continuous time unitary evolution of the complete ancilla network system, sampled at the same discrete time intervals. This reference calculation clarifies how discarding each outgoing ancilla and removing its correlations from subsequent dynamics modifies the attainable entanglement and preparation time. Our results provide a proof of principle demonstration of geometry dependent Bell pair generation and routing in small qubit networks.

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arXiv2026

Correlation Enhanced Autonomous Quantum Battery Charging via Structured Reservoirs

In this work, we investigate autonomous charging of a quantum battery coupled to a structured reservoir composed of two qubits, each locally coupled to its own bosonic thermal bath. Moreover, the reservoir interacts with a charger-battery architecture through three configurations: (I) direct coupling between reservoir qubits and battery, (II) collective coupling among reservoir qubits, charger, and battery, and (III) collective coupling between reservoir qubits and charger together with a local charger-battery interaction. Using incoherent and coherent initial states, we analyze stored energy, ergotropy, and charging power of the battery, and derive upper and lower bounds on extractable work in terms of free energy of coherence and correlations exchanged between subsystems. Our results show that global and local coherences, as well as total correlations, act as quantum resources that enhance autonomous charging. Additionally, we demonstrate that the free energy stored in the quantum battery splits into contributions from coherence and correlations, providing numerical evidence supporting the derived ergotropy bounds. Importantly, this work highlights how structured reservoirs enable autonomous and resource-enhanced quantum battery operation.

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arXiv2026

Data and code for collision-model Dicke-state preparation: depth-fidelity frontiers, circuit costs, and superconducting-processor measurements

Dicke states are multipartite entangled states in which a fixed number of quantum excitations is coherently shared among many qubits. Originally introduced in the context of cooperative emission and superradiance, they are now important resources for quantum sensing, networking, and collective quantum phenomena. Preparing prescribed Dicke states with high fidelity, however, remains challenging, particularly as the system size and excitation number increase. Here we present an open dataset and accompanying code for preparing Dicke states using a collision-based quantum protocol. The dataset covers systems from five to fourteen qubits over a broad range of excitation numbers and records how the best-found noiseless preparation fidelity changes with circuit depth. It also provides circuit-resource estimates and experimental measurements for selected states on the 54-qubit IQM Emerald superconducting processor. The accompanying code reproduces the processed data and validation checks, providing a reusable benchmark for studying the trade-off between state-preparation fidelity, circuit cost, and hardware noise.

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arXiv2026

Topological Engine Monitor: Persistent Homology-Based Fault Detection in Finite-Time Quantum Engines

The reliable operation of finite-time quantum heat engines is fundamentally limited by control imperfections that induce nonadiabatic phase accumulation and quantum friction, degrading the stability of the thermodynamic cycle. Traditional monitoring relies on energetic observables such as instantaneous cycle work; however, under finite-time driving, these quantities exhibit strong fluctuations, obscuring reliable single-shot fault detection without extensive statistical averaging. Here, we apply a topological data analysis (TDA)-based approach to establish a non-invasive, purely geometric framework for diagnosing control failures in finite-time quantum Otto engines. We construct time-delay embeddings from weak measurements and map the dynamics into persistent homology diagrams. We define a scalar quality index based on Wasserstein and Bottleneck distances that tracks control degradation and anticipates cyclic failure. By encoding topology via persistence images and silhouettes, we achieve highly robust classification of degraded operation across diverse noise profiles. We benchmark the TDA-based approach (topological engine monitor, TEM) against a standard multi-feature statistical baseline (spectral-statistical monitor, SSM) across progressively realistic noise settings, from global timing jitter to correlated adiabatic noise and coherence injection. We find that as noise becomes more localized and realistic, the conventional SSM approach degrades while the TEM remains robust. Finally, a pixel-wise Pearson correlation analysis reveals that the method captures microscopic signatures of quantum friction. Our results demonstrate the potential of topology-based diagnostics for non-ideal quantum thermodynamic devices.

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arXiv2026

Dissipation-protected energy storage in interacting multilevel quantum batteries

Dark and subradiant states have emerged as a promising resource for stabilizing open quantum batteries against dissipation, but existing studies are largely limited to qubit ensembles and symmetry-based constructions. Here we introduce a systematic, thermodynamically consistent framework for identifying long-lived energy storage states in interacting multilevel quantum batteries, combining the Davies master equation with a Morris-Shore (MS)-type decomposition of dissipative coupling blocks. Focusing on a minimal model of two interacting qutrits coupled to a common bath, we analytically construct dark, bright, and funnel states-excited states that decay exclusively into protected manifolds. We also derive quantitative robustness conditions governed by the ratio of interaction strength to anharmonicity. We show that multilevel ladder structure and exchange interactions enable energetic storage states beyond the qubit case. Numerical simulations confirm that these states exhibit long-lived energy storage under typical Markovian dissipation. Finally, we show that high-energy funnel states provide a natural design target for multilevel quantum batteries, as their decay pathways are highly structured and directed toward protected manifolds. The knowledge and understanding of these pathways offers a principled basis for developing future protection and control strategies in superconducting multilevel platforms.

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arXiv2026

Collective-dissipation-induced dark and metastable-like states for enhanced quantum battery performance

We investigate the role of symmetry-protected dark states and metastable-like frozen states in the autonomous charging dynamics of open quantum batteries described by a transverse-field Ising model. By comparing local and collective dissipation over a range of system sizes, temperatures, and magnetic phases, we demonstrate that collective dissipation generates symmetry-protected dark states together with a much larger set of frozen (metastable) states, forming an extended protected Hilbert space. We derive the multiplicity of the collective dark sector analytically, showing that it follows the Catalan sequence for even system sizes, while such states are absent for odd sizes. Our results show that collective dissipation can enhance ergotropy and charging power, with its advantage depending on temperature, magnetic phase, and system size. While the number of dark and frozen states is identical in the ferromagnetic and antiferromagnetic phases, the achievable ergotropy differs substantially because of the different spectral locations of these protected states. In particular, the antiferromagnetic configuration exhibits considerably larger extractable work owing to the favorable positioning of the protected subspaces within the many-body energy spectrum. Finally, we analyze the active Hilbert-space fraction and show that metastable protection provides an effective mechanism for suppressing dissipative losses while preserving efficient charging pathways. These results establish the dark-state and frozen-state sectors as key resources for optimizing the performance of open quantum batteries through engineered dissipation.

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arXiv2026

Physics-Informed Learning of Effective Error Processes from Limited Noisy Transmon Measurements for Robust QAOA Reliability

We study whether limited finite-shot calibration measurements from a hidden transmon-inspired simulator can be used to learn compact, task-relevant effective error models for variational-algorithm reliability. Each physical element is modeled as a weakly anharmonic qutrit with coherent control imperfections, dissipation, dephasing, leakage, readout assignment error, and sampling noise, while the learner receives only selected local tomography data and, in the three-qubit extension, targeted pair probes. The learned objects are local affine Bloch response maps supplemented by process-relative edge residuals, and they are tested through their ability to reproduce and mitigate deformations of QAOA/MaxCut cost landscapes in simulation. The results show that strongly incomplete local data can still support useful response-map inference, that regularized linear models become competitive with neural networks in the scaled three-qubit setting, and that pair probes provide useful edge-level information, giving the clearest edge-residual prediction gain at the full pair-probe budget and a measurable downstream QAOA benefit. In the best non-oracle test, a Clifford-data-regression-style local-inverse correction reduces the finite-shot QAOA landscape error from $0.18187\,[0.17576,0.18798]$ to $0.01811\,[0.01751,0.01871]$, corresponding to a $10\times$ improvement. The study supports a hardware-aware, measurement-efficient calibration strategy, while incorporating leakage-explicit diagnostics and a non-oracle regression-style correction.

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arXiv2026

Quantum in Biology, Quantum for Biology, and Biology for Quantum: Mapping the Evidence and the Road Ahead

Quantum science and biology now intersect in three complementary directions: quantum in biology, quantum for biology, and biology for quantum. This review provides a structured narrative evidence map of that interface rather than an exhaustive catalogue or formal systematic review. For each topic, we ask what the mechanistic or technological claim is, which quantum resource is invoked, what the strongest experiments and models establish, which classical alternatives or engineering confounds remain competitive, and what decisive tests or benchmarks would most strongly change confidence. The most mature quantum-in-biology cases remain mechanistically constrained tunneling in some enzymatic hydrogen-transfer reactions and radical-pair spin chemistry as a viable framework for magnetoreception, whereas several higher-visibility topics remain suggestive but unresolved under physiological conditions. In quantum for biology, the central issue is whether quantum-enabled tools improve biological inference relative to strong classical baselines under realistic calibration, dose, throughput, and uncertainty constraints. In biology for quantum, the strongest claims arise when biomolecular structure or self-assembly measurably improves fabrication, integration, or robustness in quantum devices. Summary tables in the Appendix provide a compact cross-map view of the current evidence, major confounds, and the experiments or benchmarks most likely to discriminate between competing explanations.

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arXiv2026

Fidelity-informed neural pulse compilation of a continuous family of quantum gates with uncertainty-margin analysis

We develop a fidelity-informed neural pulse-compilation framework for a continuous family of single-qubit gates on a three-qubit liquid-state nuclear magnetic resonance (NMR) processor. Instead of decomposing each target unitary into a sequence of calibrated basis gates, the method learns a direct map from the axis-angle parameters of an arbitrary U_2 in SU(2) operation to a piecewise-constant radio-frequency control sequence that implements the desired transformation. Training is performed end-to-end through the time-ordered propagator of the driven Hamiltonian using global-phase-insensitive unitary fidelity as the learning signal. We show numerically that a single model generalizes across a continuous range of gate parameters and experimentally validate representative compiled pulses on a benchtop three-qubit NMR device. In addition, we analyze sensitivity to structured perturbations in Hamiltonian and control parameters by introducing a prescribed uncertainty set and performing a comparative risk-aware redesign based on right-tail Conditional Value-at-Risk (RU-CVaR). This stage produces pulse solutions with broader tolerance margins within the chosen uncertainty model. The results demonstrate continuous pulse-level gate synthesis in an experimentally accessible setting and illustrate a hardware-aware compilation strategy that can be extended to other quantum platforms. While the uncertainty model considered here is tailored to NMR, the neural compilation and risk-aware optimization framework are general and may be useful in architectures where calibration overhead, parameter drift, or control constraints make repeated per-gate optimization costly.

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arXiv2026

Spin-1 quantum annealing with anisotropy-controlled intermediate-state pathways

Quantum annealing offers a promising strategy for solving complex optimization problems by encoding the solution into the ground state of a problem Hamiltonian. While most implementations rely on spin-$1/2$ systems, we explore the performance of quantum annealing on a spin-$1$ system where the problem Hamiltonian includes a single ion anisotropy term of the form $D\sum (S^z)^2$. Our results reveal that for a suitable range of the anisotropy strength $D$, the spin-$1$ annealer reaches the ground state with higher fidelity. We attribute this performance to the presence of the intermediate spin level and the tunable anisotropy, which together enable the algorithm to traverse the energy landscape through smaller, incremental steps instead of a single large spin flip. This mechanism effectively lowers barriers in the configuration space and stabilizes the evolution. These findings suggest that higher spin annealers offer intrinsic advantages for robust and flexible quantum optimization, especially for problems naturally formulated with ternary decision variables.

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arXiv2026

Non-Associativity Induced Modifications of Open-System Quantum Dynamics: General Master Equation and a Two-Qubit Ising Case Study

Nonassociative deformations of phase-space structures arise naturally in the presence of magnetic charge, where the Jacobi identity for momentum components fails and the corresponding Moyal product becomes nonassociative. While such structures are well understood at the level of single-particle kinematics, their implications for open-system quantum dynamics remain largely unexplored. Here we derive a Born-Markov master equation for a system coupled to a bath when the underlying operator product is weakly nonassociative. The deformation enters through associators appearing in the second-order kernel, while pairwise operator products and dissipators retain their standard form. The resulting correction is dispersive and modifies the Liouville-von Neumann part of the generator without introducing additional dissipative channels. We then embed this structure into a two-qubit transverse-field Ising model using a Stratonovich-Weyl representation and an Ising-aligned twisted Poisson structure. In the zero-temperature limit, the nonassociative terms produce a nonlinear correction in which the instantaneous population imbalance of each qubit feeds back into the dynamics as a state-dependent longitudinal field. Numerical simulations in the weak-coupling regime, where the Born-Markov derivation is quantitatively controlled, show that increasing the nonassociativity parameter suppresses steady-state entanglement by up to 59%, reduces purity, and increases entropy, while leaving the relaxation timescale set by the dissipative rates unchanged. These results demonstrate that weak nonassociativity manifests as a coherent, population-dependent deformation of open-system dynamics rather than an additional dissipative mechanism.

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arXiv2026

Optimizing quantum sensing networks via genetic algorithms and deep learning

We investigate the optimization of graph topologies for quantum sensing networks designed to estimate weak magnetic fields. The sensors are modeled as spin systems governed by a transverse-field Ising Hamiltonian in thermal equilibrium at low temperatures. Using a genetic algorithm (GA), we evolve network topologies to maximize a perturbative spectral sensitivity measure, which serves as the fitness function for the GA. For the best-performing graphs, we compute the corresponding quantum Fisher information (QFI) to assess the ultimate bounds on estimation precision. To enable efficient scaling, we use the GA-generated data to train a deep neural network, allowing extrapolation to larger graph sizes where direct computation becomes prohibitive. Our results show that while both the fitness function and QFI initially increase with system size, the QFI exhibits a clear non-monotonic behavior - saturating and eventually declining beyond a critical graph size. This reflects the loss of superlinear scaling of the QFI, as the narrowing of the energy gap signals a crossover to classical scaling of the QFI with system size. The effect is reminiscent of the microeconomic law of diminishing returns: beyond an optimal graph size, further increases yield reduced sensing performance. This saturation and decline in precision are particularly pronounced under Kac scaling, where both the QFI and spin squeezing plateau or degrade with increasing system size. We also attribute observed even-odd oscillations in the spectral sensitivity measure and QFI to quantum interference effects in spin phase space, as confirmed by our phase-space analysis. These findings highlight the critical role of optimizing interaction topology - rather than simply increasing network size - and demonstrate the potential of hybrid evolutionary and learning-based approaches for designing high-performance quantum sensors.

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arXiv2026

Harnessing Floquet dynamics for selective metrology in few-qubit systems

Periodically driven quantum systems can function as highly selective parameter filters. We demonstrate this capability in a finite-size, three-qubit system described by the transverse-field Floquet Ising model. In this system, we identify a period-doubling (PD) dynamical phase that exhibits a stark asymmetry in metrological sensitivity to the magnetic field applied on the qubits and to the coupling strength between the qubits. The PD phase originates from $π$-pairing, where the initial state exhibits strong overlap with $π$-paired Floquet eigenstates, leading to robust period-doubled dynamics and enhanced metrological sensitivity. The analysis of quantum Fisher information reveals that the PD regime significantly enhances precision for estimating the Ising interaction strength while simultaneously suppressing sensitivity to the transverse magnetic field. Conversely, non-PD regimes are optimal for sensing the transverse field. This filtering effect is robust for larger system sizes and is quantifiable using experimentally accessible observables, such as magnetization and two-qubit correlations, via the classical Fisher information. Our work shows that distinct dynamical regimes in finite-size Floquet systems can be harnessed for targeted quantum sensing.

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