Papers

Autonomous coding agents perform well on many conventional programming tasks, but scientific computing demands a rigorous validation paradigm that extends beyond simple functional test completion: generated code must preserve physical fidelity, differentiable workflows, framework-native semantics, and scalable representations. We introduce Open Research Benchmark for Integrated Tasks in Quantum Computing (ORBIT-Q) to address this gap. At its core, ORBIT-Q contributes a carefully curated suite of complex, research-level quantum workflows that serves as a challenging testbed for modern scientific programming. ORBIT-Q combines a rigorous multi-tier verification pipeline to support two orthogonal comparisons: different agent harness and model configurations at a fixed quantum software framework, and different quantum software frameworks at a fixed agent. In our systematic evaluations, TensorCircuit-NG (TC) exhibits the highest capability and performance efficiency among the evaluated quantum software frameworks under agent-driven programming, and Codex with GPT-5.5 is the strongest tested agent configuration on TC. However, a significant performance and design gap remains between frontier autonomous agents and human expert reference implementations. We further evaluate two efficiency dimensions: agent-side resource use and artifact-side runtime. Together, these results establish ORBIT-Q as a rigorous benchmark for autonomous scientific programming, framework-agent synergy, and quantum software performance.

Quantum state tomography is an essential tool for characterizing quantum systems and underpins nearly every experimental realization of quantum technologies. Conventional tomography relies on performing a sequence of projective measurements on many identical copies of a quantum state, requiring the measurement apparatus to be reconfigured between successive acquisitions. As the Hilbert-space dimension increases, the number of required measurements grows rapidly; in practice, additional overcomplete measurements are often performed to improve robustness to experimental imperfections. Here, we introduce a tomography platform based on structured anisotropic media that performs informationally complete measurements of photonic polarization qubits within a single acquisition. The approach employs three liquid-crystal metasurfaces with spatially varying optic-axis orientations that transform the input polarization into a far-field distribution of discrete transverse-momentum modes. Each diffraction pattern uniquely determines the polarization state, enabling its reconstruction without sequential changes to the measurement apparatus. Unlike previous implementations, our scheme is intrinsically photon-number independent: the same optical device operates identically for arbitrary photon numbers, while the desired photon-number sector can be selected afterwards through post-selection of the corresponding $n$-fold coincidence events. We experimentally demonstrate single-frame quantum state tomography of both single- and two-photon polarization states, providing a simple and scalable route toward efficient quantum-state characterization.

We study spin effects in twisted-electron propagation through the entrance or exit region of an axially symmetric magnetic coil. Starting from the Foldy-Wouthuysen reduction of the Dirac equation, we derive a paraxial spinor equation in which the longitudinally varying solenoidal field produces, in addition to the usual diagonal Zeeman term, a transverse Pauli coupling proportional to the fringe-field gradient. The scalar transverse dynamics is treated exactly by the Ermakov mapping, which absorbs the longitudinally dependent focusing into a metaplectic scaling transformation and reduces the orbital evolution to that of a stationary two-dimensional oscillator. On this background, the transverse Pauli term is treated perturbatively and yields an explicit first-order correction for arbitrary realistic solenoidal profiles. Axial symmetry implies conservation of the total projection of angular momentum, so each spin flip is accompanied by a compensating one-quantum change of orbital angular momentum. In addition, the linear coordinate structure of the perturbation restricts the first-order dynamics to at most two neighboring radial sidebands for each incoming oscillator component. We derive the corresponding transition amplitudes and show how their phases are governed jointly by the Ermakov accumulation and the diagonal spin-orbital rotation. The resulting framework provides a direct way to quantify spin-orbit mixing of twisted electrons in realistic magnetic lenses and solenoidal beam-line elements, and it identifies a route toward controlled spin-OAM conversion in engineered sequences of magnetic-field edges.

Schrödinger cat states, formed from superpositions of well-separated coherent states, are promising resources for bosonic quantum information. We construct parent Hamiltonians for entangled multimode cat states by separating the selection of local coherent-state branches from the correlations and symmetries that determine their global superposition. GHZ-, cluster-, and W-type cat states illustrate three distinct mechanisms for this construction. In the limit of well-separated branches, the resulting oscillator Hamiltonians reduce to familiar qubit parent models based on correlations, stabilizers, and exchange symmetry. The same constraint structure also provides a common basis for coherent preparation, dissipative stabilization, and state certification.

We propose the first error-tolerant secure key leasing (SKL) for public-key encryption. As with SKL in prior works, our protocol consists of a lessor and lessee. In the protocol, the lessor encodes its secret key into quantum states and leases the key to the lessee. Then, the lessor can ask the lessee to return the secret key at a later point. The lessor is able to check whether the lessee has returned its key honestly. However, our protocol works even when the leased secret key is subject to noise. The lessee decrypts the ciphertext correctly, and the lessor verifies the return of the secret key correctly when the amount of error is below a certain threshold. Our improved protocol does not change the encoding of the secret key, and thus adds no overhead to the quantum information processing. Our most significant result is a framework to analyze the trade-off between robustness against error and security. We bridge the security of the error-tolerant SKL and that of the error-tolerant certified deletion with shortened codes, which is a relatively less explored concept in coding theory.

While typical online estimation methods can estimate the multiparameter dynamics of many systems, they may not be sufficient for a system with highly noisy measurement and rapid detection rate. In this paper, we create a hybrid estimation method by augmenting the sequential Monte Carlo (SMC) sampler, an online estimation method with an offline technique known as the time-batch estimation technique. By continuously monitoring the system, we may divide signals into batches and average them into an averaged trajectory. The system dynamics is then evolved with batch-averaged Kraus maps, for which we derive a highly efficient approximation. To facilitate the adoption of our algorithm, we present a modular derivation of the SMC methods and showcase our algorithm as an explicit example. We then implement our algorithm on the measurement signals obtained from superconducting-qubit experiments under two types of measurement setting: a fluorescence measurement and a dispersive $z$-measurement. The algorithm's hyperparameter values are chosen from independent numerical simulation, while the accuracy of our estimation is validated by a signal reconstruction method. Our results show that, for the fluorescence case, our algorithm can estimate the system's parameters better than the standard calibration method, and, for the dispersive case, our estimation is capable of finding an unexpected jump in parameter values that the standard calibration method could not find.

For the precision-based measurements, Mach-Zehnder interferometry is a widely used technique. There are various ways to enhance the precision of Mach-Zehnder interferometer (MZI), e.g., having a non-classical input state is one of the ways to enhance the precision of the phase estimation performed by MZI. The phase estimation performed by MZI is investigated here by considering that the input states of MZI are different combinations of photon added and subtracted squeezed coherent states (PASCS and PSSCS). Using quantum Fisher information, it is shown that the use of PASCS in both the input modes of MZI, provides the most precise estimate of the unknown phase. This system is also analyzed in two different measurement scenarios – single intensity detection (SID) and intensity difference detection (IDD). Systematic analysis has established that the intensity measurement might not be an optimal measurement scheme for phase estimation in MZI as phase and intensity correspond to non-commuting observables. The impact of the photon loss on the MZI-based phase estimation setup is also studied and it is found that PASCS is robust against photon loss, when the loss in MZI is low.

Under Gaussian collective dephasing parallel to the signal, the superdecoherence of an $N$-atom Greenberger–Horne–Zeilinger (GHZ) state cancels its gain in Fisher information, so GHZ frequency sensitivity is limited to an atom-number-independent floor. We demonstrate that this floor is a property of Gaussian diffusion: a single common phase kick can at most randomize the phase of an $N$-atom coherence, so discrete events at rate $\Gamma$ cannot dephase any coherence order faster than $2\Gamma$. At the same single-atom coherence time, finite-rate Poisson kicks with an absolutely continuous amplitude law therefore saturate the order-$N$ decay rate and restore Heisenberg scaling. We prove that Gaussian diffusion is the worst case for GHZ and Dicke-cat probes under this calibration, that only the Brownian component of Lévy phase noise sets the asymptotic floor, and that the $1/N$ exponent is optimal for parallel Ramsey protocols. These results identify the counting statistics of the common noise, rather than its spectrum, as the property that bounds superdecoherence.

We propose two-stage optimized strategies for full-period optical phase estimation with single-mode Gaussian states and Gaussian measurements under a fixed energy constraint. In the first stage (Stage I), displaced squeezed probes and heterodyne measurements provide coarse localization of the phase to a window on the circle. In the second stage (Stage II), squeezed-vacuum probes with adaptive homodyne measurements perform efficient phase estimation inside the selected window. We derive a generalized Cramér-Rao bound for this family of two-stage Gaussian strategies, which contains the contribution from local parameter estimation in Stage II plus an overshoot penalty from coarse localization errors in Stage I. For E <= 25 photons and squeezing limited to 12 dB, protocols using displaced squeezed states in Stage I reduce the optimized two-stage bound relative to protocols using coherent states in Stage I, and remain within a factor of 3 to 30 of the idealized local squeezed-vacuum quantum Cramér-Rao bound.

Primordial black holes (PBHs) form when large primordial curvature perturbations re-enter the Hubble radius and exceed the classical collapse threshold. These perturbations originate as quantum fluctuations of the inflationary vacuum, motivating a quantum-information description of the PBH-producing scalar sector. We develop a conservative extension of the standard PBH and scalar-induced gravitational-wave (SIGW) framework in which Gaussian quantum discord is used as a diagnostic of residual quantum correlations, not as a new PBH-formation criterion. We describe each \((\bm k,-\bm k)\) pair as a two-mode Gaussian state and show that, in the pure squeezed limit, discord grows rapidly with the squeezing parameter, so low discord thresholds are automatically satisfied for strongly squeezed modes. The nontrivial regime is the mixed state produced by decoherence. Using a Lindblad open-system description, we motivate a Gaussian loss channel for the scalar covariance matrix and distinguish the discord from a covariance-survival factor \(Q_{\rm dec}(k)\). If the decoherence channel suppresses the scalar two-point covariance, PBH abundance can be affected through the classical collapse variance, while the SIGW spectrum is modified more directly by the factors \(Q_{\rm dec}(ku)Q_{\rm dec}(kv)\) inside the radiation-era convolution. For a narrow scalar peak and slowly varying \(Q_{\rm dec}\), this gives the benchmark scaling \(\Omega_{\rm GW}^{\rm eff}\simeq Q_{\rm dec}^2\Omega_{\rm GW}^{\rm class}\). Thus quantum discord and decoherence provide a controlled way to characterize the quantum-to-classical transition of PBH-producing perturbations, with the clearest imprint appearing in scalar-induced gravitational waves.

Three-level systems exhibit quantum interference effects absent in two-level systems, making them important for quantum optics. Here, we study the coherent interaction of a Lambda-type three-level system with free electrons shaped by optical near fields. By treating the electron train as a quantum drive, we show that the interplay between electron modulation and the three-level system's transition pathways induces tunable interference patterns. This interaction effectively realizes electron-mediated coherent population trapping (CPT). We identify a regime that enables complete population transfer between the two lower states and the preparation of a high-coherence superposition, manifested as dark states. In particular, these driven-dissipative steady states are independent of the initial state. Our work proposes shaped free electrons as a platform for steady-state coherent control of three-level systems, enabling atomic-scale state engineering.

We use the (1+1)-dimensional Schwinger model to investigate the nonequilibrium dynamics of a finite lattice system under a constant external electric field. The lattice Hamiltonian is constructed under open boundary conditions. The vacuum state is prepared using the variational quantum eigensolver (VQE). Scans over the external field strength show the flip of the vacuum state at several field strengths. The critical field strengths agree with theoretical predictions. We further investigate the real-time evolution of the zero-field vacuum under an external electric field using a second-order Trotter-Suzuki decomposition. By comparison with exact diagonalization (ED), we verify that the quantum-simulation protocol reproduces the main features of field-induced boundary charge separation, decay of the vacuum-state fidelity, and quasiperiodic energy redistribution between the electric-field energy term and the fermionic sector. Our results indicate that combining VQE-based state preparation with digital real-time evolution provides a useful approach for studying nonequilibrium dynamics in strong-field lattice gauge theories.

Quantum error mitigation (QEM) is usually benchmarked by expectation-value accuracy, but many near-term workflows use those values only to make downstream choices such as argmin selection, ranking, top-k filtering, optimizer-step acceptance, or phase labeling. This creates a structural mismatch: accuracy is measured in the ambient landscape space, whereas shift-invariant decisions depend only on gaps. We develop a quotient-space theory of finite-shot QEM for downstream decisions. The minimal decision-complete object is the residual gap law; in Gaussian finite-shot regimes it is summarized by effective margins and a decision kernel. The QEM-specific point is that this kernel is not free: it is the pullback of shared physical device noise through the mitigation map. We prove quotient factorization, gap-law minimality, a marginal no-go theorem, a QEM pullback theorem, Gaussian decision-risk formulas, and a fixed-allocation shot-level converse. Finite-shot Qiskit Aer simulations demonstrate the predicted divergence in the evaluated regimes. Clifford-data regression can be decision-flat while improving mean-squared error, and probabilistic error cancellation can improve accuracy while worsening decision risk through sampling overhead. Decision-aware selection modestly reduces static held-out failure relative to accuracy-based selection, often by retaining Raw, but the dynamic success target is not reached. Pre-registered stress tests under a calibrated device-noise model and on a hardware micro-cell probe robustness beyond these regimes. The operational implication in the evaluated regimes is to select QEM methods through residual gap geometry, not from expectation-value accuracy alone.

As a hallmark of nonclassical light, squeezed light is of profound theoretical interest and holds broad practical promise for emerging quantum technologies. In this work, we investigate steady-state optical quadrature squeezing in the open quantum Rabi-Stark model by employing the quantum dressed master equation. Both numerically and analytically, we find that positive (negative) Stark coupling tends to enhance (suppress) the squeezing effect. The quadrature squeezing exhibits distinct signatures associated with both first- and second-order quantum phase transitions (QPTs). Notably, a sharp vanishing of squeezing is observed across the first-order QPT, suggesting its potential as a sensitive probe of such transitions. In the vicinity of the second-order QPT, we further demonstrate that the squeezing factor displays finite-size scaling behavior, indicating a promising route toward the realization of near-perfect squeezing. Moreover, we establish a quantitative criterion for the disruption of quantum criticality induced by thermal fluctuations, which may offer valuable guidance for future experiments. These findings contribute to a deep understanding of nonclassical light in light-matter interacting systems and provide useful insights for the design of strong optical squeezing states.

We propose a two-way entanglement-based quantum secure direct communication (QSDC) protocol in which information is encoded as the value of a continuously tunable parameter and decoded from empirically estimated joint-outcome histograms over windows of detected pairs. The protocol uses a fixed two-qubit polarization Hilbert space and only standard coincidence-based polarization measurement at the receiver, with the symbol alphabet enlarged not by increasing the carrier Hilbert-space dimension but by exploiting temporal integration over a window of pairs to resolve distinguishable joint-outcome probability distributions. Under an idealized model in which the source is maximally entangled, the encoding operation is strictly local, and the channel imprints no parameter-dependent signature on the traveling photon, the reduced state of the traveling photon is maximally mixed and independent of the encoded parameter. Consequently, passive interception of the in-flight subsystem alone yields no information about the encoded message. We further develop a quantitative trace-distance framework for bounding any parameter-dependent leakage that may arise from non-ideal channel and device effects in practical implementations. The protocol introduces protocol-level design parameters not available in fixed-alphabet two-way QSDC, specifically a runtime-tunable alphabet size and native support for continuous-time analog modulation, which may be advantageous in operating environments where channel conditions vary on protocol-relevant timescales.

Singular interactions can reshape quantum spectra by changing admissible wavefunction domains. In this study, we investigate this mechanism in the Klein–Gordon equation for a non-central Schiöberg-type hyperbolic potential with double ring-shaped angular barriers. Equal scalar and vector couplings separate the radial and angular dynamics. We solve the angular equation exactly on each hemisphere with principal boundary conditions and treat the radial equation with the Greene–Aldrich approximation, obtaining Jacobi-polynomial wavefunctions and an implicit relativistic quantization condition. With this boundary realization, the equatorial inverse-square singularity splits configuration space into reflection-related sectors with identical angular spectra. Reducing the barrier to zero while retaining the equatorial wall selects the odd-reflection spectral branch of the regular full-domain problem; a single hemisphere has no intrinsic parity. The nonrelativistic limit recovers the corresponding Schrödinger formulation. State-resolved nonrelativistic and relativistic benchmarks quantify the centrifugal error. In a dimensionless relativistic example, the relative error in the remaining binding exceeds unity near threshold although the absolute energy error decreases. For NaH and Na$_2$, low-lying central-radial vibrational energies agree reasonably with spectroscopic reference values, whereas the global radial shape limits near-dissociation accuracy and gives an incorrect NaH bound-state count.

We propose a quantum algorithmic protocol for calculating astrophysical opacities. Our implementation uses first- and second-quantized representations of interacting electronic and photonic subsystems and Hamiltonian simulation via the interaction picture. Inferring opacity from momentum-resolved measurements of the photonic register yields a direct relationship between qubit count and spectral range/resolution. Logical resource estimates for the classically challenging problem of solar iron opacity are comparable to another high-energy-density physics problem (Rubin et al., PNAS 121(3) (2024)).

A solvable charger–battery model is introduced in which quantum coherence controls both where a quantum battery's charge is stored and how robustly it survives noise. Charging converts the charger's coherence into charger–battery entanglement and splits the deposited work between a locally extractable part and a correlation-locked part accessible only through joint operations; for a qubit, the split obeys an exact complementarity, and at maximal coherence, the battery is locally passive with the entire charge locked in correlations. Robustness follows local accessibility: the stored energy and locally extractable work are population-based, immune to pure dephasing, and limited only by relaxation, with an energy half-life, whereas the correlation-locked work is fragile to both dephasing and relaxation. Dephasing, global and local depolarization, and amplitude damping are treated through a single gain–loss competition algebra, and the resulting storage lifetimes are made concrete with superconducting-transmon parameters.

Efficient quantum error correction and fault-tolerant quantum computing require scalable, high-fidelity long-range connectivity. In neutral-atom quantum computers, this is commonly achieved through atom transport, but shuttling introduces latency and motional heating that worsen with system size. Here, we introduce a neutral-atom architecture based on static atomic buses, in which auxiliary mediator atoms enable long-range entangling operations without qubit transport. The architecture naturally supports long-range stabilizer measurements in high-rate LDPC codes and transversal logical gates between neighboring surface-code patches, enabling a modular framework for efficient logical memories, Clifford computation, and magic-state distillation. To realize these capabilities, we co-design optimal-control protocols for bus-mediated controlled-Z gates that incorporate both microscopic neutral-atom dynamics and architectural constraints. We obtain smooth bus-mediated gates with fidelities approaching 99.9% and durations of a few hundred nanoseconds by combining time-optimal control with interaction-flatness and robustness constraints. Large-scale simulations of quantum error correction and logical entangling operations between neighboring surface-code patches predict more than an order-of-magnitude improvement in logical error rates compared with atom-shuttling architectures under realistic noise. The architecture achieves logical gate times of approximately 100 us and quantum-error-correction cycle times of about 1 ms for code distances d<12. These results establish static atomic buses as a practical alternative to atom shuttling for scalable fault-tolerant neutral-atom quantum computing.

The measurement cost for estimating expectation values of Hamiltonians is a central bottleneck in variational quantum algorithms. Grouping strategies significantly reduce this cost, with overlapping techniques being the state of the art in the field. Overlapping grouping methods require i) a non-overlapping grouping of the Hamiltonian, typically obtained from the Sorted Insertion (SI) algorithm as initialization, and ii) the construction of covariance dictionaries from approximate wavefunctions to guide the optimization. It was recently shown that different initializations can potentially reduce measurement costs for overlapping methods. Motivated by these findings, we introduce variance-aware SI (VarSI), a family of covariance-informed non-overlapping Pauli grouping heuristics to reduce measurement counts. VarSI grouping leverages the covariance dictionaries, already required by overlapping methods, to construct better non-overlapping groups. We propose three variants: a global greedy grouping insertion rule, a variance-informed SI analog, and a local refinement step initialized from SI or our variance-informed variant. We showcase the use of groupings generated by our VarSI heuristic algorithms to initialize overlapping methods using the iterative coefficient-splitting (ICS) algorithm. Molecular benchmarks with 130 Hamiltonians demonstrate consistent, non-overlapping measurement improvements over SI of 38% and enhanced downstream ICS results when initialized from VarSI groups. We find that the initializations considered here achieve up to 70% measurement reductions for ICS, compared to the standard SI initialization with mean reductions of 9–15.3% depending on qubit mappings and covariance dictionaries used. These results show that non-overlapping grouping remains a consequential design step even when the final estimator uses overlapping fragments.

Quantum entanglement is a powerful resource for quantum-enhanced technologies. However, its reliable quantification remains challenging due to the exponential scaling of the Hilbert space with system size, which renders full state tomography infeasible. Moreover, experimentally estimating entanglement typically requires a large number of measurement samples leading to a significant overhead. In this work, we present two models, a feed-forward neural network and an attention-based model, to accurately predict the bipartite second Renyi from projective measurements of quantum states. We benchmark their performance against standard classical shadow estimators and find that the machine-learning approaches achieve higher accuracy and improved sample efficiency across a range of system sizes. Our results demonstrate the potential of machine learning for scalable and efficient estimation of quantum correlations.

Consistent families of locally defined probability distributions that do not admit a joint global distribution are known as contextual, with primary examples arising in quantum theory. In this paper, we study such families of distributions using the theory of simplicial distributions, and further develop the theory for possibilistic distributions defined over the Boolean semiring. We characterize possibilistic collapses of simplicial distributions geometrically using bundle scenarios. Using this characterization together with a new connectivity condition on the total space of a bundle scenario, we provide a criterion for detecting extremal simplicial distributions. In parallel, we develop an analogous theory for presheaves on simplicial complexes, describe possibilistic collapses of empirical models on them using event scenarios together with a categorical extremality condition, and relate the two frameworks via a comparison result. We provide examples of contextual simplicial distributions that arise from our criteria on scenarios of interest in quantum foundations, such as Bell scenarios and boundaries of standard simplices, the latter connecting to Vorob'ev's classical theorem on acyclic complexes.

Efficient representations of multipartite quantum states play a fundamental role in quantum information theory, providing both conceptual insight and practical tools for characterizing entanglement. Motivated by the axiomatic framework for graph states [Phys. Rev. A 85, 062313 (2012)] and its subsequent extension to hypergraph states [Phys. Rev. A 87, 022311 (2013)], we introduce an axiomatic construction of matroid states, a new family of multipartite quantum states associated with matroids. Our constructions are based on a set of axioms analogous to those that define graph and hypergraph states, yielding a consistent quantum representation of arbitrary matroids. Two ways of constructing matroid states are proposed: the first is defined in terms of circuits, and the second in terms of independent sets. In both approaches, we establish the existence of universal global operators that satisfy desirable properties such as locality, symmetry, commutativity, and are associated with the combinatorial structure of matroids. Furthermore, we establish a hierarchy connecting graph, matroid, and hypergraph states within a unified framework. Additionally, we show how to obtain an arbitrary graph state by applying suitable families of matroid states, whose corresponding operators are the generators of the stabilizer subgroup of the graph state. These results identify matroid theory as a natural combinatorial language for the efficient description of multipartite quantum states and open new perspectives for the investigation of quantum entanglement and related combinatorial structures.

Quantum regression tasks for predicting properties of quantum states are commonly addressed using variational quantum algorithms. While variational quantum circuits are highly expressive and allow to achieve reasonable accuracy, training these circuits may demand a considerable amount of time and resources. In this work, we propose an approach of constructing problem-specific quantum regression models with encoding relevant symmetries and regularizing the variance. The proposed method is based on finding the coefficients of the linear combination of suitably chosen observables. Although it requires the knowledge of the symmetries of the problem in question, the method does not involve parameterized quantum circuits, and the training is done efficiently once the observables are measured. We demonstrate this method on two examples: Prediction of the transverse field strength in the Ising model, and quantification of entanglement in bipartite qubit systems. Our approach is accurate and less resource-intensive than conventional variational methods.

The elementary excitation spectrum of a many-body quantum system encodes many key properties, including phenomena as diverse as transport, thermalisation and ground state structure. Excitation spectra of strongly correlated systems are typically encoded in dynamical structure factors, which are demanding to measure experimentally and challenging to compute classically. Here we use quench spectroscopy on a superconducting quantum processor to extract excitation spectra of spin chains of $L=101$ spins. By tailoring the combination of quench protocol and observable, we selectively access distinct excitation sectors across several phases of the spin-$1/2$ XXZ chain, resolving free magnons, multi-magnon bound states, and two-spinon continua. Notably, we demonstrate that the protocol does not rely on ground state preparation: in the classically challenging gapless regime, we extract spectra directly from the quench dynamics of easily prepared product states, a procedure that is natural and straightforward on quantum hardware. Our work establishes quench spectroscopy as a fast and flexible probe of many-body excitation spectra on digital quantum hardware, introduces a novel quench protocol that does not require costly state preparation routines, and provides a scalable route towards regimes where classical simulation may become intractable.

A central challenge in quantum thermodynamics is to access work fluctuations in coherent processes without distorting the energetics of the unmeasured evolution. In standard two-point schemes, the initial energy measurement dephases coherent inputs, causing the measured average work to differ from that of the unmeasured evolution. Here, we develop an operational scheme for accessing work statistics for closed quantum systems based on the abstract notion of variation in the Heisenberg picture Hamiltonian. This scheme preserves energetically relevant coherences, thereby faithfully reproducing unmeasured work, while still producing positive probabilities. We derive modified Jarzynski and Crooks relations, as well as a thermodynamic uncertainty relation, identifying coherence-induced correction terms. Furthermore, we show that this scheme can reliably quantify the performance of a coherent engine in situations where the two-point energy measurement would suppress work output. In addition, the scheme requires only a single measurement and can predict the work associated with a subsequent unitary transformation. We exploit this feature to construct a Maxwell-demon protocol that can outperform energy-based feedback engines for coherent work extraction. Our results establish this scheme as a framework for accessing coherent work fluctuations without erasing the coherence that drives quantum thermodynamic performance.

Variational quantum algorithms (VQAs) are a leading approach to near-term quantum computation, but their utility is limited by barren plateaus and other pathologies in their loss landscapes. Existing landscape theories based on dynamical Lie algebras, Jordan-algebraic Wishart systems, approximate t-designs, and Haar-random circuits are foundational, but they often neglect the finite-depth geometry of realistic ansätze and are therefore ill-suited to the shallow-depth regime, where VQAs are poor approximators of 2-designs and trainability is most feasible. This work introduces Krylov algebras, algebraic structures induced by the Krylov span of a finite generator set acting on one or more seed vectors, as a framework for VQA landscape theory. We show that VQA reachable manifolds can be approximated in a numerically robust, geometrically faithful fashion by Krylov-Lie algebras and groups, and that these structures induce canonical invariant measures for computing expectation values and variances under general sampling measures. In particular, we derive weighted non-Haar variance formulas that recover the usual Lie-algebraic Haar formulas as a special case while isolating non-Haar effects into explicit correction terms. We also show that the common heuristic that sufficiently deep circuit ensembles must converge to Haar fails in general without additional hypotheses, identify concrete obstructions to naive Haar convergence, and recover convergence under natural necessary and sufficient ergodic conditions. Lastly, our formulas further imply that non-Haar contributions to landscape statistics may mitigate barren plateaus by reweighting the visible sectors of the loss landscape, suggesting that VQAs may be more trainable than recent literature has posited.

Multiplex CRISPR-Cas9 gene editing requires selecting one guide RNA per target gene subject to cross-gene interactions: a constrained combinatorial problem that can be formulated as a Quadratic Unconstrained Binary Optimization (QUBO) and solved via the Quantum Approximate Optimization Algorithm (QAOA). The one-hot per-gene constraint is conventionally enforced by adding quadratic penalty terms to the cost Hamiltonian, but penalty coefficient selection is heuristic and penalties amplify hardware noise. An alternative is to enforce the constraint structurally via the XY-mixer, which preserves feasibility by construction. We present COMET, a systematic comparison of penalty-based and XY-mixer QAOA on a three-gene, twelve-qubit multiplex editing instance targeting the immune-checkpoint genes PDCD1, LAG3, and HAVCR2. In simulation, the XY-mixer exceeds 95% probability of the optimum by QAOA depth p=3, while three penalty variants spanning an order of magnitude in penalty coefficient remain below 6% at every depth. On IBM's ibm_kingston (Heron r2) processor, the XY-mixer's simulator-hardware energy gap stays within |0.8| across all depths, while the worst-tuned penalty variant's gap reaches +53.9. We provide an honest account of where the structural guarantee partially breaks under gate-level noise. The twelve-qubit instance is classically trivial; our contribution is a methodological comparison of constraint-enforcement strategies in a biologically motivated domain, with real-hardware validation.

Simulating molecules is a major application of quantum computing, with the potential to overcome exponential scaling constraints of classical computation. Researchers use different methods in order to evaluate the readiness of NISQ computers in order to test current simulation capabilities. We present an integrated repository with reproducible benchmarks of over 10 different ansatzes from published papers and two different truncation methods, applicable to any set of mapped hamiltonians, providing a single pipeline for comparing performance along multiple axes, including variance and computational time, among others. We apply them to simulate different amino acids, using hamiltonians taken from the QMProt Dataset. We then ran four separate experiments. First, we quantified noise resilience by optimizing the same hardware-efficient ansatzes under identical initialization while sweeping PennyLane noise channels and strengths, and measuring parameter drift, cosine similarity of optimal parameters, and energies evaluated on noiseless versus noisy backends. We then studied barren-plateau-related trainability via gradient-variance diagnostics and optimization trajectories across initialization strategies and ansatzes depth on small systems. We then compared adaptive versus fixed ansatzes at matched parameter budgets, reporting outer-loop iterations, wall time, and especially total cost-function evaluations to fairly contrast greedy adaptive growth with layered hardware-efficient circuits. Lastly, we mapped accuracy versus expressive capacity by sweeping the number of retained adaptive operators and recording ground-state energy error relative to classical references.

We develop a quantitative theory for the emergence of quantum many-body chaos as integrability is broken via a tunable parameter. In a circuit model of free fermions, 'doped' with a tunable density of integrability-breaking gates, we uncover the microscopic mechanisms underpinning the crossover from early-time integrable behaviour to late-time chaos through the lens of the out-of-time-ordered correlators (OTOCs). The integrability-breaking gates act as local, in spacetime, hotspots which locally amplify the OTOCs such that an accumulation of them eventually leads to fully-developed chaos. We identify the explicit characteristic time and length scales governing this crossover, as well as the dependence of the chaotic OTOC characteristics – such as the butterfly velocity and front broadening – on the integrability-breaking parameter.