Papers

We present a numerical study of a blockade Hamiltonian with a local $\mathbb{Z}_2$ symmetry. For such models, the existence of a topologically ordered ground state has been proven rigorously for weak Rabi driving [T. F. Maier et al., PRX Quantum 6, 030340 (2025)]. However, the phase diagram beyond weak driving is still an open question. We perform large-scale infinite-size density matrix renormalization group (iDMRG) simulations on a cylinder and map out the full phase diagram of the model. We find a single continuous phase transition between the topologically ordered phase and a trivial paramagnetic phase, and confirm numerically the stability of the topologically ordered phase up to Rabi drives comparable to the characteristic energy scale of the system. Furthermore, we compute the excitation gaps and show that the charge gap remains open across the phase transition and charges become confined in the trivial phase. On the other hand, the gap in the symmetric sector closes at the transition, consistent with the condensation of flux excitations.

A fundamental prediction of quantum mechanics is that observables can be measured through ideal measurements, that is, measurements that give the same outcome when repeated and do not disturb any observable that is jointly measurable. In terms of quantum instruments, such an ideal measurement is described by projective effects together with the associated Luders state-update rule. Here, we show that quantum mechanics allows for self-testing any ideal measurement. Using solely the output statistics of bipartite Bell tests in which a non-demolition measurement is sometimes added, it is possible to certify in a device-independent manner whether the added measurement is ideal.

Feature selection for imbalanced classification tasks such as credit card fraud and consumer default detection requires balancing predictive relevance, inter-feature redundancy, and computational feasibility. We benchmark three computing paradigms, classical branch-and-bound optimization (Gurobi), photonic entropy computing (QCI Dirac-3), and simulated photonic boson sampling (Piquasso), across thirteen feature-selection methods on two datasets: ULB Credit Card Fraud (30 features) and AmEx consumer default (159 features). Each method is routed to the solver matched to its mathematical structure. On ULB, Dirac-3 MI-Spearman matches the all-features model using 13 of 30 features (mean F1 0.873 +/- 0.023 over five runs, best run 0.896), and Piquasso is the best method at k=5. On AmEx, performance rises steadily with the feature budget and every paradigm approaches F1 = 0.80 only near the full feature set. Most differences between Gurobi and Dirac-3 on identical methods fall within run-to-run variation; the large gaps occur where the certified optimum generalizes poorly, most sharply for distance correlation on AmEx at k=25 (Gurobi F1 = 0.422 vs. a Dirac-3 mean of 0.746). At matched budgets, F1 varies about ten times more across methods on ULB than on AmEx, which we trace to how concentrated the predictive signal is in each feature space.

Here, we report the fabrication and characterization of single crystal diamond films on a two-inch wafer-scale containing three-dimensional layered structures of negatively charged nitrogen-vacancy color centers (NV$^{-}$). The (100)-oriented layered diamond films were grown by chemical vapor deposition (CVD) to create spatially separated regions of enhanced emission associated with NV$^{-}$ centers. Such localized emission enhancement as well as 2D and 3D arrays of spins could enable close-packed architectures for emerging quantum devices, such as data processors, memory cells, and magnetic sensors. A cyclic sequence of CVD growth and oxygen-plasma etching is employed, resulting in the in-situ formation of layered inverted pyramidal structures with flat $\{$111$\}$ sidewalls. These pits are subsequently overgrown by nitrogen-doped diamond to achieve NV$^{-}$-rich facets with a uniform N-V bond arrangement and improved nitrogen incorporation efficiency.

We study a finite-width Majorana shutter as a local, time-dependent scattering defect and determine which features of its infrared memory are insensitive to the microscopic spatial profile. For a smooth shutter, the zero-frequency scattering matrix is fixed by the integrated coupling, while finite-width corrections vanish in the long-wavelength limit. A time-dependent switch then produces an infrared Bogoliubov kernel whose singular part is controlled by the change in this scattering matrix. We examine the many-body response through three observables. The overlap of the pre- and post-shutter Gaussian vacua exhibits Anderson orthogonality, with an exponent set by the scattering angle. A lattice calculation of the post-quench quasiparticle number resolves its logarithmic infrared growth, reaching the predicted coefficient in the slow-switch test and reproducing the expected dependence on the scattering-angle change. When the entanglement cut passes through the shutter, the entropy follows the effective-central-charge description of a conformal defect, with parameter-free agreement at the percent level, improving for the wider shutter. When the shutter lies inside the interval, its contribution remains a subleading finite-size correction. A local bilinear correlator approaches the expected Majorana power law and shows no stable logarithmic amplitude. These results show that the same low-frequency scattering data control distinct global and spatial observables, while their infrared coefficients are not interchangeable. The remaining limits are also made explicit: the finite-memory correction to the continuum kernel and the controlled continuum limit of large-interval spatial entropy.

Predicting many molecular properties requires accurate ground-state energies of molecular Hamiltonians. Quantum-selected configuration interaction (QSCI) obtains such energies by measuring an input state to select important electronic configurations and classically diagonalizing the Hamiltonian in the subspace they span. ADAPT-QSCI, an adaptive extension of QSCI, improves the input state through iterative circuit growth. For single-reference molecules, the sampling distribution is dominated by the Hartree-Fock (HF) configuration, so most measurements reproduce a configuration already known. We reduce this redundancy by placing the HF configuration in the diagonalization subspace classically, before any measurement. This invalidates the operator-selection criterion of ADAPT-QSCI, and we derive a consistent replacement with energy and gradient in closed form, adding no query to the quantum device. At the per-iteration shot budgets previously used for ADAPT-QSCI, the proposed scheme reaches chemical accuracy with approximately $63\%$ and $43\%$ of the CNOT gates for $\mathrm{H}_4$ and $\mathrm{H}_6$, and $44\%$ and $40\%$ of the total shots. The advantage depends on the budget, however: in the infinite-shot limit the $\mathrm{H}_4$ CNOT count increases to $125\%$ of that of ADAPT-QSCI. These results identify the per-iteration shot budget as a key design variable governing resource savings in QSCI-based algorithms.

The dimensionality of entanglement in high-dimensional quantum systems is quantified by the Schmidt number, whose large value signals potential advantages for quantum communication and quantum computation. A commonly used approach to practical Schmidt-number detection in finite-dimensional systems is based on the estimation of fidelities to pure states with large entanglement dimensionality or lower bounds to these fidelities. However, for mode-entangled continuous-variable systems, the corresponding measurements are typically difficult to realize. Here, we introduce and assess fidelity bounds for Schmidt-number detection based on practically more accessible measurements of the first and second statistical moments of arbitrary continuous-variable quantum states. We provide analytical formulas that allow evaluating these bounds and test them for families of Gaussian and non-Gaussian states, including two-mode squeezed thermal states and photon-added displaced two-mode squeezed vacuum states. We compare our bounds to other methods for the certification of high-dimensional entanglement based on the same measurements.

The spectral fluctuations in complex quantum systems are modeled in terms of spectra from random matrices. Quantitative agreement with random matrices holds only when the quantum spectrum is a pure sequence, and not a composite spectrum that mixes levels from different symmetry sectors. It was shown earlier that discrete symmetries in composite spectra can be detected using higher-order spacing ratio statistics provided the symmetry sectors are of equal dimensions. The general case is when the symmetry sectors have unequal dimensions, and the symmetries of the Hamiltonian system are unknown or only partially known. In this work, we address how the number of symmetry sectors can be determined from a composite spectrum arising in Hermitian and non-Hermitian settings. A Best Subset Technique is proposed for determining the number of the symmetry sectors by comparing the spectral fluctuations to that of an appropriate random matrix ensemble without requiring de-symmetrization. It is demonstrated using spectra from Gaussian, Wishart and Ginibre ensembles, and also for spectra drawn from many-body quantum systems.

We develop a finite-state geometric framework based on third-order Bargmann invariants for evaluating Chern numbers and characterizing local quantum-state geometry. Using gauge-invariant state overlaps, the framework evaluates the Chern number directly on discretized parameter spaces while retaining local geometric information through the phase-derived density and the complementary amplitude density, as well as signatures associated with changes in topological character. We apply the construction to the Qi–Wu–Zhang, $1/3$- and $1/4$-flux Hofstadter, SSH, and Rice–Mele models, including a rank-$2$ extension for isolated composite subspaces and applications to closed-loop and parameter-space topology. The resulting framework organizes Chern topology and local geometric information directly from finite-state data, providing a compact state-based description without relying on dynamical evolution.

Quantum-classical auxiliary-field quantum Monte Carlo (QC-AFQMC) is a promising route to using quantum computers for strongly correlated electronic structure problems, but its scalability is limited by a classical post-processing bottleneck: the measured quantum trial state must be used to evaluate overlaps, force biases, and local energies for many walkers throughout the AFQMC propagation. Existing matchgate-shadow approaches avoid the exponential cost of generic classical shadows, but their post-processing remains expensive for large systems. In this work, we show that particle-number-preserving fermionic shadows, implemented as orbital-rotation shadows, are able to drastically reduce QC-AFQMC post-processing costs. We derive efficient estimators for overlaps and their derivatives, giving $O(N^3)$ scaling for overlaps and force biases and $O(N^4)$ scaling for local energies per shadow and walker and with $O(N)$ Cholesky vector. For fixed normalized target determinants, we also prove that the overlap estimator is unbiased with variance upper bounded by $O(\eta)$, where $\eta$ is the particle number, yielding a sufficient budget of $O(\eta/\epsilon^2)$ ideal independent measurements for additive overlap error $\epsilon$. We combine these estimators with a novel virtual-correlation-energy treatment and a GPU implementation and demonstrate QC-AFQMC using orbital-rotation shadows. Performance projections for $\pi$-conjugated molecules up to pentacene with a (22e, 22o) active space and 356 total orbitals show that the full classical post-processing workflow can be completed in slightly more than two days on 8$\times$A100 graphics processing units (GPUs). These results significantly reduce classical post-processing costs for QC-AFQMC and motivate further improvements in preparation and measurement of the trial state on quantum hardware.

Fast control of long-lived quantum registers often relies on an auxiliary degree of freedom, a mediator, but real mediator excitation can introduce decoherence, leakage, or loss when the mediator is not the coherence-optimized component. We introduce dispersive interaction via analytical linear inversion (DIAL), an analytical control construction for excitation-suppressed interaction engineering in mediator-coupled quantum registers. In the dispersive regime, we show that off-resonant driving of an effective two-level mediator transition yields a diagonal Hamiltonian whose Pauli-\(Z\) interaction rates depend linearly on the drive intensities through a transfer matrix determined by the register-resolved transition spectrum. This establishes a direct linear map from experimentally accessible controls to induced multi-qubit interactions, enabling control design without iterative propagation of the full driven dynamics. We turn this structure into the target-aware DIAL algorithm, which selects favorable off-resonant tones and determines their drive intensities for a prescribed target interaction. We benchmark the resulting controls across 100 register realizations for each register size \(n=2,3,4,5\), targeting the highest-order interaction \(Z_1\cdots Z_n\) with an interaction phase of magnitude \(\pi/4\), which generates an \(n\)-qubit GHZ state up to local equivalence. Propagation under the full driven mediator-register dynamics yields typical gate fidelities above \(0.997\), while the maximum transient mediator excitation remains near \(1\%\) on average, far below what is typically possible with resonant Rabi drives. The manuscript is accompanied by an open-source Python package implementing the target-aware DIAL algorithm and the associated numerical validation workflow.

We present and theoretically analyze a method for direct estimation of the second-order correlation function $g^{(2)}(0)$ from the click statistics of a multiplexed detector composed of M binary on-off detection channels. The method uses linear estimators of the first and second moments of the photon-number operator and can provide accurate results even for optical fields with substantial mean photon numbers. For a fixed number of channels, the detection range can be extended by introducing additional losses before the detector. We demonstrate the performance of the method for coherent, thermal, amplitude-squeezed, and photon-added coherent states. We also derive a nonclassicality criterion based on the estimated correlation function and show how the method can be adapted to unbalanced detectors. Our work establishes direct estimation of $g^{(2)}(0)$ as a simple and versatile method for quantitatively characterizing quantum light using multiplexed click detectors.

In a world fraught with uncertainty, it behooves us to consider the most disastrous possible outcomes, in order that we can best mitigate against them. Often these are extreme risk events – of high consequence, but low probability. Yet, the rarity of such events limits our ability to study them; there is a paucity of past occurrences to draw upon, and sampling such rare events from models is typically costly in time. Here, we introduce an approach for rare-event sampling based on quantum stochastic models. This integrates the memory advantages of quantum stochastic modelling – and its associated efficient means of preparing quantum sample states – with the `speed-ups' of quantum amplitude amplification, to yield simultaneous reductions in spatial and temporal computational complexity compared to classical Monte Carlo-based approaches.

In our paper, we show that a two-qutrit Werner state admits a local hidden-variable model for all values of the parameter in a scenario involving two projective measurements per site, with three outcomes per measurement. To this end, we derive a simple sufficient condition under which a two-qutrit state satisfies the Collins-Gisin-Linden-Massar-Popescu inequality for arbitrary choices of Alice's and Bob's observables, and show that the Werner state always satisfies this condition. Next, we use the fact that any two-qutrit state satisfying the Collins-Gisin-Linden-Massar-Popescu inequality for arbitrary choices of Alice's and Bob's observables admits a local hidden variable model.

The center of mass of a Bose–Einstein condensate in a harmonic trap oscillates at the trap frequency independently of the interactions. Without interactions a parity-time-symmetric gain-loss gradient leaves this frequency unchanged, and a cloud of the ground-state width is translated rigidly while the atom number is periodically modulated. With interactions the protection is lost, because the gain and the loss change the number of atoms; the modulated atom number drives the width of the cloud, and the width acts back on the center of mass. At small gain the period grows quadratically with the gain strength, with a coefficient that in the Thomas–Fermi regime is set by the size of the cloud alone. The family of periodic orbits continued from the Kohn oscillation can be followed up to a critical gain, where it comes into resonance with highly excited states of the trap, and over the computed families this critical gain decreases with the amplitude of the oscillation and with the size of the cloud. A five-variable moment model reproduces the period and the width of the cloud along the orbits nearly up to the critical gain.

Stochastic semiclassical gravity represents stress–energy fluctuations through the Einstein–Langevin noise kernel. We examine its Newtonian projection for specified closed, particle-number-conserving non-relativistic sources and distinguish the source covariance from a reduced matter channel. The connected one-particle covariance is state dependent and differs from the universal potential-noise law postulated in the Diósi–Penrose model. To relate the source spectrum to dephasing, we define a separate static probe subject to a prescribed Gaussian noise law. For a finite-variance source operator in an isolated non-degenerate eigenstate, the full connected spectral measure has a gap around zero. The probe dephasing exponent is then bounded and its long-time slope vanishes. Stationary doublets can instead carry static or low-frequency spectral lines, while a specified freely spreading Gaussian source gives a finite limiting exponent. Continuum results depend on preparation, normalisation, infrared regularisation and the order of limits. We also compare coherent and incoherent many-body preparations and establish no-signalling for fixed classical-noise channels. These results identify the spatial, temporal and dynamical assumptions needed to relate source fluctuations to a matter-decoherence model. They do not exclude Markovian limits in other number-conserving non-relativistic preparations.

An alchemical resource theory admits a nonfree state that can be exactly replicated by free operations and whose finitely many copies enable exact simulation of arbitrary quantum instruments. The only known nontrivial examples, imaginarity and parity asymmetry, exhaust the qubit case (arXiv:2609.12988) and exhibit an all-or-nothing property: any nonmaximal resource exactly simulates only free unitaries. We introduce aquaternionicity for even-dimensional qudits $d\ge4$, based on a quaternionic structure represented by an antiunitary $\Theta$ with $\Theta^2=-I$. It is extremal in two senses: every pure state is alchemical, and alchemicality is maximally abundant under mixing. Within this framework, for any nontrivial $d$-dimensional resource theory and pure alchemical state $g$, the admissible pure-mixing set satisfies $\dim\mathcal M_g\le 2d-4,$ which aquaternionicity saturates for every pure state. Conversely, these two extremal properties characterize the quaternionic structure. Because every pure state is alchemical, the initial resource can be chosen to match the known noise structure. Moreover, when the noisy resource states remain within a common isotropic subspace, the same free processor works exactly for all of them while returning the resource unchanged. This enables recalibration-free exact simulation, including universal quantum computation, and is realized for standard dephasing and dissipative noise, where aquaternionicity substantially outperforms imaginarity and parity asymmetry.

We give quantum algorithms for Hamiltonian simulation, linear differential equations, and linear systems with square-root dependence on sparsity. For an $s$-sparse Hermitian matrix with row and column Euclidean norms bounded by $\eta$, evolution for time $t$ to error $\epsilon$ uses $\mathcal{O}(\sqrt{s}\tau+\sqrt{s\tau\log(1/\epsilon)}+\log(1/\epsilon))$ queries, where $\tau=\eta|t|$. The same bound holds for time-dependent Hamiltonians with coherent time-indexed sparse access and certified time discretisation. Our construction combines an exact entrywise representation with Cayley transducers. A joint lower bound nearly matches the time, sparsity, and precision dependence, ruling out a uniformly additive bound in $\sqrt{s}\tau$ and $\log(1/\epsilon)$. For dissipative linear differential equations we obtain $\mathcal{O}(\bar g[\sqrt{s}(\tau+\sqrt{\tau})+1]\log(C\bar g/\epsilon))$ queries, where $\tau$ is the evolution time multiplied by a norm bound, $\bar g$ bounds the ratio of combined input and source norms to the final-solution norm, and $C$ is an absolute constant. We sharpen this bound by separating Hamiltonian and dissipative components, and treat general constant generators. Lower bounds capture joint parameter dependence for time-dependent equations and precision hardness for constant positive semidefinite dissipation. For linear systems, a Cayley walk and Chebyshev filter give $\mathcal{O}(\kappa\sqrt{s}\log(1/\epsilon))$ queries when $\|A\|\le1$ and $\|A^{-1}\|\le\kappa$, and we give an alternative proof of a matching joint lower bound. We also give gate-efficient implementations of time-independent Hamiltonian simulation and the dissipative ODE solver, including Lipschitz time dependence, retaining the query bounds with polylogarithmic overhead in inverse precision given efficient entry decoding, arithmetic, and required source preparations.

The first-principles quantum simulation of the full electronic Hamiltonian of a material model of realistic size appears daunting even in a future era of fully fault-tolerant quantum computers. In contrast, classical simulations of material excited states rely on heuristic quasiparticle frameworks, such as the GW approximation and Bethe-Salpeter equation, where only a few quasiparticles are explicitly considered. Here we give a detailed description of quasiparticle quantum simulation for multi-excitonic states within the BSE. We develop an explicit first-quantized, orbital-based block encoding of the multi-exciton BSE Hamiltonian for qubitization, and reduce its cost using integral factorization and crystal symmetries. For a materials model of size $N$, and a fixed number of quasiparticles, the resulting algorithms require $\widetilde{O}(N)$ Toffoli gates and $O(\log N)$ logical qubits, or, using space-time tradeoffs, $\widetilde{O}(\sqrt{N})$ Toffoli gates and $\widetilde{O}(\sqrt{N})$ logical qubits, achieving up to a sixth power reduction in Toffoli count, or up to exponential reduction in qubit count, versus standard full Hamiltonian simulation techniques that have been explored in materials simulation. Resource estimates for the classically challenging problem of triexcitonic eigenvalue estimation across a range of semiconductor models of a realistic physical size of $O(10^3)$ atoms, show that our Toffoli-optimized implementation reduces the Toffoli count by $10^6-10^7$ relative to full Hamiltonian simulation estimates, while a qubit-optimized implementation requires only a few hundred logical qubits. More broadly, these results show that classical heuristic frameworks will be essential in the design of future fault-tolerant quantum algorithms for materials.

Preparing Gibbs states through dissipative dynamics requires controlling convergence for the chosen Hamiltonian $H$ and coupling operators. However, efficient implementation requires convergence guarantees from the spectral gap of the generator of the dynamics, which remains a crucial challenge. Recent results address the challenge by restricting the dynamics with structural assumptions about the Hamiltonian and its interactions. For the Chen-Kastoryano-Gilyen (CKG) construction and arbitrary finite-dimensional Hamiltonians, we prove an explicit comparison that converts a spectral gap estimate for the infinite-temperature generator into a lower bound on the spectral gap of the CKG quantum Gibbs sampler at every finite positive inverse temperature $\beta$. It allows a single spectral gap estimate at infinite temperature to certify convergence across Hamiltonians and temperatures. Such an estimate is often known from a classical spectral gap estimate, such as the classical random walk spectral gap. For Hodge Laplacians of simplicial complexes as Hamiltonians, we construct coupling operators whose generator at infinite temperature has the same spectral gap as a classical simplicial down-up walk. A positive spectral gap of the walk and bounded spectral width $W=\lambda_{\max}(H)-\lambda_{\min}(H)$ give a generator spectral gap independent of the number of simplices at every fixed temperature. We then establish conditions under which the sampler approximately prepares zero-energy (harmonic) states in polynomial evolution time. This provides a conditional convergence guarantee for the state preparation in the thermal approach to quantum topological data analysis.

We study how memory affects the thermalization of a qubit in a repeated-interaction model. In our model, a memory qubit interacts repeatedly with the system, while both qubits undergo collisions with fresh thermal ancillas. We derive exact closed evolution equations for their populations and mutual coherence, and demonstrate memory effects using a causal-break operation. Although the system converges to the target thermal state, the thermalization behavior shows non-monotonic approach. We also find a Mpemba-like reversal, in which the number of collisions required for thermalization depends non-monotonically on the temperature of the target state. Within the initial-state family considered, both phenomena require initial coherence between the system and memory or an imbalance in their excited-state populations.

What does quantum error correction do to relativistic proper time? We show that when two error-corrected quantum memories follow distinct worldlines and are controlled by local references, their local correction histories factor exactly from the proper-time difference between them. Error correction therefore does not erase time dilation: when the memories are compared, the accumulated difference appears as a relational phase rotation. During locally referenced operation this rotation is invisible to every local error syndrome; at discrete phases admitted by a code, the final relational evolution instead returns exactly as a deterministic logical gate, including an $S$-type Clifford gate at a $\pi/2$ excursion. These results connect fault-tolerant quantum information with relativistic clocks and establish protected quantum memories as a platform for preserving proper-time information and for long-coherence tests of quantum evolution involving relativistic proper time.

We propose a programmable quantum read-only memory based on Gray code encoding, termed GQROM, designed to efficiently load classical data into quantum circuits. This architecture mitigates critical bottlenecks in near-term quantum computing by reducing initialization overhead and gate-induced errors. By utilizing Gray code, in which consecutive addresses differ by only a single bit, GQROM minimizes state transition complexity. We demonstrate the architecture's flexibility in accessing targeted data through initial-state modification. The entire design, including a systematic EDA flow, was implemented and validated on the Qiskit platform, confirming its practical feasibility. These results underscore GQROM's potential as a scalable and hardware-friendly solution for efficient state preparation in quantum circuits.

Hyperedge faults remain a major challenge in circuit-level quantum error correction. Accurately exploiting hyperedge correlations often requires substantial computational resources, which complicates real-time decoding. Matching-based decoders are fast and scalable, but their pairwise graph representation limits the use of higher-order fault information. Here, we introduce Syndrome Motif Projection (SMP), a general framework for incorporating hyperedge information into matching-based decoding. The key idea is that a hyperedge fault produces a characteristic local syndrome motif. Observing such a motif provides evidence for the corresponding fault. SMP extracts this information directly from the measured syndrome with linear-complexity preprocessing while preserving the matching backend. It can therefore serve as a lightweight front end to existing scalable and real-time matching decoders. We demonstrate SMP across surface code memories, color code memories, and logical gate circuits. On Google's Willow experimental surface code data, SMP improves both standard and correlated matching and outperforms the tested belief matching baseline. For color code memories, SMP combined with Chromobius reduces logical failure probabilities by up to 77.8%. For logical gate circuits, SMP reduces the failure probability of a six-CNOT circuit by 35.5% relative to logical observable matching while achieving performance comparable to iterative belief matching. These results demonstrate that SMP provides a lightweight and transferable approach to hyperedge decoding, with a clear path toward integration into scalable real-time decoding architectures for fault-tolerant quantum computation.

In the photoreceptor compass model, a light-generated, spin-correlated radical pair undergoes singlet-triplet interconversion driven by Zeeman and anisotropic hyperfine interactions, leading to orientation-dependent reaction yields. In this study, we consider simultaneously the spin environment and the boson environment surrounding the radical-pair system and concentrate on the correlated memory effect of the spin bath. In the linear-response limit, the spin bath is mapped to an effective Gaussian environment. The system dynamics and yields under its influence together with the bosonic bath are propagated uniformly using the hierarchical equations of motion (HEOM) or equivalently the dissipaton equations of motion (DEOM) method. The HEOM/DEOM is non-Markovian and non-perturbative, exact for Gaussian environments. Corresponding results of the Markovian Lindblad master equation are also shown for comparison. Numerical demonstrations highlight the non-Markovian memory effect as a crucial ingredient for radical-pair magnetoreception.

We show that for any $R,\epsilon >0$ and any prime $p\geq 2$, there exists an infinite family of $p$-ary quantum low-density parity-check (QLDPC) codes, rate $R$, checks of weight $O_\epsilon(1)$, and normalized distance at least $\delta_{\mathrm{GV}}(p,R)-\epsilon$. Here, $\delta_{\mathrm{GV}}(p,R)$ denotes the quantum Gilbert-Varshamov (GV) bound for $p$-ary stabilizer codes. In fact, we construct an ensemble of such QLDPC codes, such that a random code from this ensemble is close to the GV bound with high probability. Moreover, this ensemble matches the performance of random stabilizer codes on several quantum channels. Specifically, it approaches the quantum capacity of the erasure channel and the hashing bound for memoryless Pauli channels, including the depolarizing channel. A significant challenge in working with QLDPC codes is that they are necessarily degenerate, i.e., contain many low-weight stabilizers. A key contribution of our work is a construction of QLDPC codes with quantitative control on their degeneracy. These codes are obtained by combining known constructions of asymptotically good QLDPC codes with the expander-based distance amplification procedure of Alon, Edmonds, and Luby [FOCS'95]. Our random ensemble is constructed by starting with these low-degeneracy QLDPC codes near the quantum Singleton bound and concatenating each coordinate with a random inner code. This can be viewed as a quantum analogue of Thommesen's construction, and as an LDPC version of a result of Ouyang, with an appropriately designed outer code.

We show that adaptive Bayesian estimation in fluorescence state detection reduces to a comparison of elapsed time with two arithmetic time sequences fixed by the bright and dark count rates and confidence parameters $\epsilon_d$ and $\epsilon_b$. No probabilities are computed in real time and the resulting implementation, which we term sequential deadline detection, is provably optimal in mean detection time. The analysis permits closed-form expressions for detection-time distributions, mean detection times, error rates of both channels accounting for miscalibrated rates, decay between the states during detection, and afterpulsing in single photon counting modules. The predictions are validated by Monte Carlo simulation and demonstrated by fluorescence detection with Ba$^+$

Removing an input-scaling module changes both a classifier and the perturbations reaching its encoder. A robustness difference can therefore reflect the comparison rule as well as the module. We demonstrate this problem in a four-qubit quantum-attention detector on generated power-grid trajectories. A learned scaling module appears beneficial at a fixed physical attack budget, but matching an upper bound on perturbations at the encoder reverses the ordering. Neither comparison alone establishes a robustness benefit caused by the module. The initial test also perturbs clean examples into attacked examples while retaining their original labels; tests restricted to already attacked examples do not establish a benefit. Replacing a trained model's input scales disrupts detection. Retraining its linear classification layer restores the detection rate, but changes individual predictions, leaving the comparison descriptive rather than causal. Two further design checks explain why the input quantum Fisher information regularizer cannot train this model's query parameters, and why removing confidence bounds does not establish a larger certified radius. The evidence is limited to ten seeds, exact simulation, synthetic data, and a restricted set of attacks; classical baselines achieve better clean prediction. The practical lesson is to specify which perturbation budget is fixed, check that attacks preserve labels and interventions preserve predictions, and distinguish exploratory controls from confirmatory evidence.

Quantum Fourier sampling may help audit the spectral learnability of delay-based physical unclonable functions (PUFs). We ask whether that promise survives access matching, a strong classical comparator, and oracle synthesis. Three gates structure the evaluation. Structure: low degree is not small support at reachable challenge lengths; for 4-XOR at $n=14$, degree $\le d_f(0.1)$ admits $91\%$ of all $2^n$ characters and the median $90\%$-mass set spans a third of the spectrum. Algorithmics: constructing the phase oracle logically implies classical membership access, making Kushilevitz–Mansour the correct baseline; across 45 tasks it exhausts each finite domain, and no 4-XOR ideal-sampling case reaches $90\%$ mass within $2^n$ calls. A quantum-kernel diagnostic appears more favorable, with geometric difference rising to $2.151$ at $N=512$ challenges, but it correlates $0.991$ with $1/\sqrt{\lambda_{\min}(K_C)}$ for the classical Gram matrix $K_C$, and the 4-XOR label-complexity ratio does not exceed a balance-preserving permutation null ($p=0.930$). Trace-normalized geometric difference can therefore grow through classical ill-conditioning alone, without task-label alignment. Implementation: a simulator-validated fixed-point phase oracle based on the quantum Fourier transform admits an $18.9\%$ routed-depth reduction, yet the least certified precisions have estimated durations of $1.18$–$1.55\times$ the median dephasing time $T_2$ of the mapped qubits on a static backend snapshot, without hardware execution. We find no end-to-end advantage in the evaluated regime, although ideal sampling does use fewer coherent calls on the thresholded task. The contribution is the Three-Gate Quantum Audit Protocol: a reproducible procedure separating an ideal query advantage from a realizable security benefit. This is not a claim about deployed silicon and not an impossibility result.

Quantum Fisher information adds over independent probes, so a single parameter is best measured probe by probe. We show that Gaussian measurements, the linear optics and homodyne detection of optical and microwave experiments, break this rule: two independent modes are better measured together. The uncertainty principle leaves a linear detector half of phase space, and for two modes the choice of half is a resource. Bell homodyne, a balanced beam splitter followed by two homodyne detectors, beats the best separate readout when the modes differ in quadrature width and in how the width responds to the parameter. Heterodyne detection splits a mode on a beam splitter to read both quadratures and pays one unit of vacuum noise for the empty port. Bell homodyne fills that port with the second mode, so the noise turns into signal. We prove that the gain stays below $(\sqrt2-1)^2=17.157\%$ for every parameter carried by widths. For thermal modes at one temperature, the canonical case, a gain was conjectured impossible. We prove that any frequency difference opens a temperature window and that the gain peaks at $12.699\%$ at frequency ratio $3.318$, where Bell homodyne is the optimal Gaussian measurement. Standard hardware reaches the gain: two coupled resonators with two homodyne detectors, or a phase-preserving amplifier whose idler band is fed by the same thermal source.