Papers

Interferometry is a powerful method for studying many fundamental phenomena ranging from gravitational waves to anyon excitations. Besides loss of coherence in the interferometer paths, quantum mechanics sets an incompressible bound for linear interferometry arising from the quantum noise of the light beam, called the shot noise limit. Here, we implement a non-linear quantum interferometer that uses a microwave cavity and a magnetic field resilient anharmonic superconducting quantum circuit made of granular aluminum. The circuit enables interferometry beyond the shot noise limit. A direct application of our findings is the detection of dark matter (axions or dark photons), high-frequency gravitational waves or astronomical masers.

We investigate the capability of variational quantum circuits in detecting a topological phase transition within the toric code model subjected to a uniform magnetic field. The detection is carried out via shot-based computations of both the ground state energy and the global entanglement. We begin by employing well-established renormalization techniques to construct a quantum circuit that accurately represents the pure toric code under periodic boundary condition. This circuit is subsequently parameterized to enable a shot-based variational simulation of the ground state in the presence of the magnetic field. Our results demonstrate that even for the minimal lattice sizes and a finite number of measurement shots, the ground state energy exhibits a distinct singularity at the transition point which can be reliably approximated through finite-size scaling analysis. Furthermore, we introduce a secondary variational circuit designed to compute the global entanglement of the generated ground state. We observe that both global entanglement and its conditional counterpart display the expected qualitative behavior at the transition point, consistent with the topological nature of the phase transition. To evaluate the practical viability of our variational approach on real quantum hardware, we systematically examine the detrimental effects of gate noise on the analysis. We find that the topological phase exhibits a notable robustness against noise, manifesting as a linear decrease in the transition point with increasing noise strength.

Robust entanglement at room temperature is a central challenge for solid-state quantum information processing and quantum-enhanced sensing. Here we demonstrate room-temperature storage of entanglement in a silicon carbide (SiC) quantum node by coherently transferring an electron-nuclear entangled state onto long-lived nuclear-spin memory qubits. Using a shallow single color center in 4H-SiC, conventionally denoted PL6, we realize a fully addressable three-qubit register composed of one electron-spin processor and two strongly coupled $^{29}$Si nuclear-spin memory qubits. This platform enables the deterministic generation of high-fidelity entangled states, including a nuclear-spin Bell state with a fidelity of $94 \pm 2\%$ and a three-qubit Greenberger-Horne-Zeilinger (GHZ)-type state with a fidelity of $89 \pm 4\%$. By implementing a SWAP-gate protocol in the strong hyperfine-coupling regime, the electron-nuclear entanglement is transferred to the nuclear-spin memory with a fidelity of $92.5 \pm 2.5\%$, extending the entanglement lifetime by a factor of 240. We further confirm the generality of this approach in an additional heterogeneous $^{29}$Si-$^{13}$C nuclear-spin register and, through a statistical survey of 200 single PL6 centers, show that multi-nuclear-spin registers occur naturally with probabilities above 10%. These results position shallow SiC color centers as a powerful platform for entanglement-assisted quantum sensing and scalable room-temperature quantum technologies.

Quantum Natural Language Processing (QNLP) uses pregroup grammars to translate grammatical structure into diagrammatic representations and quantum circuits. Recent Hindi QNLP work has shown that Hindi-specific pregroup grammars can support grammar-sensitive compositional models, but grammatical type assignment is still largely manual, limiting scalability. This paper formulates automatic Hindi pregroup supertagging as a token-level classification task. Using a manually annotated corpus of 380 Hindi sentences, we evaluate lexical, contextual, prompting-based, lexical-repair, and suffix/morphology-aware methods. Results show that simple lexical and contextual models are strong in this low-resource setting: contextual backoff achieves the best completed accuracy of 64.56%, while raw Qwen2.5 prompting reaches only 11.65%. Lexical repair raises LLM-assisted prediction to 64.08%, demonstrating the value of constraining generative outputs with symbolic grammar knowledge. Diagnostic analysis further shows that seen and unambiguous tokens are much easier than unseen tokens, and suffix/morphology features improve karaka-token accuracy but not overall performance. These results show that automatic Hindi pregroup assignment is feasible and can reduce reliance on manual annotation in future multilingual QNLP pipelines.

On a cloud-accessed quantum processor the classical optimizer of a variational algorithm communicates with the device through submitted jobs, and each job carries a queueing and turnaround overhead that does not depend on how many circuits it contains. We study a simple consequence of this for the quantum approximate optimization algorithm (QAOA). An optimizer whose next set of trial parameters is known before any result returns can evaluate the whole set in one job, whereas a sequential optimizer such as COBYLA spends one job per function evaluation. We compare a batched pattern search with COBYLA on IBM's \ibmfez\ processor for cardinality-constrained portfolio selection with six to twelve assets, giving both optimizers the same number of jobs and the same number of shots. At every size the batched search reaches, after its first job, a parameter quality that the serial optimizer takes several jobs to match, and the two methods converge to comparable final values; repeating the eight-asset comparison from four starting points gives the same ordering each time. The instances are small enough to be solved exactly, which lets us check that the device's output distribution is correlated with the true ranking of portfolios and is clearly separated from a control circuit of the same depth with the cost layer removed. A short scan over circuit depth at classically optimal parameters shows that on this device the measured solution quality peaks at two or three QAOA layers. The protocol is described in enough detail to be reproduced, and the notebooks and raw counts are released.

Symmetry reduces the capacity of a quantum learning model, but the imposed group must match both the measured information and the label transformation. We establish a finite-measurement theory for inferring this group from candidate transformations. The central structural result identifies observable-invisible transformations with the stabilizer of a projected state whenever the probe span is invariant. It turns recovered generators into a valid subgroup and identifies the continuous invisible space with its Lie algebra. For finite dictionaries, an unbiased shadow statistic distinguishes zero from positive squared expectation discrepancies with an inverse-gap measurement rate, improving the inverse-square-gap rate of uniform discrepancy estimation. A commuting qubit lower bound proves the gap dependence optimal at fixed snapshot scale, and simultaneous intervals support data-dependent tolerances. Task validation then tests either the joint distribution through a characteristic kernel or its encoded mean through a classical–quantum discrepancy. An exact group-average identity relates the latter to joint-state asymmetry and specifies its conversion to binary task breaking mass. Projection bias quantifies the cost of excessive symmetry, while an $\ell_1$ readout bound quantifies the capacity gained by relaxing it. At an invariant pure-state backbone, retained and nontrivial breaking sectors are Fisher-orthogonal. Ising-chain calculations connect finite-shot recovery, label-dependent symmetry, and physical sector drift. These results determine which symmetry the measurements support and provide the statistical and geometric basis for a subsequent release decision.

This article investigates a cascade of quantum systems within an SLH-network. The original definition of an SLH-network depends on an open conjecture regarding the essential selfadjointness of the generator of the time evolution of the network. This problem is avoided by using the so-called braid-map, which leads to a rigorous definition of the SLH-network. An expression is derived for the time-evolution of the network with finite delay. The series product is recovered in the instantaneous feed-forward limit as a theorem that no longer depends on the conjecture.

Quantum State Tomography (QST), Quantum Process Tomography (QPT), and Quantum Network Tomography (QNT) are related parameter-estimation problems that aim to reconstruct different physical quantities. QST estimates an unknown quantum state, represented by its density matrix, from the measurement outcomes. QPT characterises an unknown quantum channel using known input states and measurements of the corresponding outputs. QNT, in contrast, aims to infer parameters associated with individual links from end-to-end probe measurements collected at accessible monitor nodes. A key distinction among the three tomography problems lies in the conditions required to achieve identifiability, the ability to determine unknown parameters uniquely from the available measurement statistics. In QST and QPT, the experimenter can choose an Informationally Complete (IC) measurement set. QNT limits the reachable measurements to what topology and monitor placement allow, so the admissible probe paths fix the information available about the link parameters. This work studies all three tomography problems through a common Fisher Information Matrix (FIM). We factorise QNT FIM and show that its rank equals the rank of the path-link incidence matrix at every interior parameter value, so local and global identifiability coincide. We then show that QST and QPT attain full rank under IC settings, QNT loses rank when the probe paths leave link parameters indistinguishable, and increasing the number of copies scales the FIM eigenvalues while leaving its rank fixed.

Motivated by Haag duality in quantum spin systems, we show that Haag duality for a pair of commuting factors generated by increasing sequences of finite-dimensional matrix algebras is equivalent to the asymptotic vanishing of a suitable conditional mutual information. For spin systems, let an annulus separate a finite region from the exterior. Haag duality then holds for a region $A$ if and only if the mutual information of the inner region and the exterior, conditioned on the part of $A$ inside the annulus, vanishes as the outer radius becomes large. As a corollary, assuming a strict area law with subleading corrections, Haag duality holds for single cones, and it holds for unions of two or more disjoint cones precisely when the topological entanglement entropy vanishes. For translation-invariant pure states on spin chains, half-chain Haag duality is equivalent to vanishing entropy density.

Classical-to-quantum I/O is a critical bottleneck for data-intensive quantum workloads. Quantum Oracle Sketching (QOS) has been proposed to address this problem. We identify its practical requirements, including the representation of data as a probability distribution over oracle addresses, the relation between sample count, approximation error, and update cost, and the coherence and runtime support required for online execution. To study QOS on current quantum computing devices, we develop an offline realization that compiles sample blocks into empirical phase oracles and evaluate it using DNA fingerprinting. The application converges with relatively few samples, while exact phase fusion combines repeated updates to the same address. However, the compiled circuits remain too deep for current quantum computing devices. Practical QOS therefore requires lower depth oracle synthesis and interactive quantum runtimes.

Trapped-ion Quantum Charge-Coupled Devices (QCCD) are a leading contender for quantum computing, but their scalability is constrained by control wiring and electronics. Wiring using Integrated Switching Electronics (WISE), a recently proposed QCCD architecture, reduces wiring through multiplexing and integrated switching hardware. However, this leaves an execution model with limited parallelism and limited flexibility in ion movement. Further, these devices need to be paired with a quantum error correction (QEC) code to enable fault-tolerant quantum computation (FTQC). Can WISE architectures efficiently support FTQC requirements? Which QEC choices, device and control parameters are practical? We present WISER, a cross-layer design-space exploration framework for trapped-ion systems with multiplexed control. WISER combines a WISE-specific SAT-based compiler, a physics-informed noise model and logical-memory simulation to estimate logical error rates, logical clock speeds and control power across hardware parameters and QEC families. Its compiler reduces routing time by $2.6$–$18.8\times$ relative to a greedy WISE-compatible baseline. Our analysis provides concrete design guidance. Two-ion traps with $16$-way multiplexing, $8\times$ lower than the original WISE proposal, give the fastest logical clock that meets our reliability and cold-stage power targets. With current hardware parameters, the distance-7 surface code is the only evaluated code to meet our early-FTQC screen, at $4.58\,$Hz and $2.04\,$W of DAC power per logical qubit. At this operating point, ion transport and recooling take $94$–$96\%$ of the WISE cycle, and even without them sample-and-hold electrode charging leaves millisecond-scale syndrome-extraction rounds.

In molecular variational quantum eigensolver (VQE) calculations for a fixed electron-number sector, the projected-sector energy alone does not certify that a prepared state is physically valid. We show that a state can have zero projected-sector error while almost all of its probability mass lies outside the target particle-number sector. We therefore evaluate ansatz families using three quantities: projected-sector error, leakage outside the physical sector and parameter count. Our noiseless experiments show that particle-preserving UCC-style families eliminate leakage induced by ansatze, but do not guarantee ground-state accuracy. In the parameter-budget comparison experiments, the one-shot ranking rules select identical generator sequences and yield identical errors. The adaptive hybrid procedure achieves lower mean projected-sector errors at selected budgets. Using established Kraus invariant-subspace criteria, we also express channel-induced leakage through a positive operator and discuss global and local depolarizing noise analytically. This gives a practical diagnostic framework for comparing ansatze beyond energy alone.

Quantum Amplitude Amplification (QAA), the generalization of Grover's algorithm, is well-positioned for combinatorial optimization and is particularly promising for Quadratic Unconstrained Binary Optimization (QUBO) problems. QAA is appealing due to its ability to drive the quantum system to a target state, yielding the globally optimal solution with probability over $90$+%. However, realizing QAA for application-scale optimization currently exceeds quantum hardware capacity, which is further compounded by unresolved algorithmic challenges regarding the choice of free parameters. In this study, we address these issues by utilizing a realistic traffic flow QUBO problem to investigate the implementation of QAA as a heuristic solver. Specifically, allowing the diffusion operator parameter to take non-$\pi$ values expands the capabilities of QAA. This unlocks a new multiple-shot, low-iteration strategy that aims for a high cumulative probability rather than maximizing the probability of a single basis state. Using $25$-qubit simulations, our results demonstrate that heuristic QAA addresses two of the main challenges cited in previous studies. Firstly, heuristic QAA works even at a single iteration, reducing circuit depth by orders of magnitude compared to standard QAA. And secondly, we show that the problem-dependent parameters necessary for reaching optimal algorithmic performance can be reliably approximated with minimal upfront classical computing overhead.

We derive a unified set of scaling equations for Bose-Einstein condensates in time-dependent harmonic traps, connecting the weakly interacting Gaussian regime to the strongly interacting Thomas-Fermi regime. The exact Gross-Pitaevskii ground-state density is taken as a fixed profile in rescaled coordinates, with its dynamics described by three scaling factors corresponding to compression or expansion along the three spatial directions. The resulting equations contain no adjustable parameter, since their coefficients are determined once from the initial state. They recover analytically the Gaussian variational and Thomas-Fermi scaling equations in their respective limits and satisfy an axis-resolved virial theorem. The approach also yields the global phase and the low-lying collective-mode frequencies of the condensate. We benchmark the model against three-dimensional Gross-Pitaevskii simulations and against measured expansion energies. The model remains accurate across all interaction regimes, in strongly anisotropic traps, and along time-dependent sequences including a relatively fast quench, up to the point where the underlying frozen-profile hypothesis, shared by all three scaling approaches, breaks down.

The minimum loss required to reproduce non-Hermitian dynamics depends on how many physical modes each reservoir can address coherently. Established positive-matrix criteria bound this cost. We construct a phase-controlled cubic-root Su-Schrieffer-Heeger chain in which three-mode reservoirs attain the unrestricted passivity threshold throughout its phase diagram and halve the minimum pair-supported loss at a tuned point. The bound constrains exact conditional trajectories, including time-dependent Markov controls, rather than preparation of one final state. A connected-chain protocol tests effective reservoir support through calibrated finite-time emission. Full system-auxiliary propagation then bounds conditional fidelity and target yield for every one-particle input. A coherent controller that accurately prepares the selected endpoint fails this propagator test. A singular-value bound excludes every unitary realization of the same conditional map. These results connect local reservoir access to a measurable loss cost for prescribed dynamics.

Non-Markovian quantum-state diffusion (QSD) provides a microscopic trajectory description of open-system dynamics, but trajectories associated with a chosen initial state are not directly reusable as quantum channels. We develop a constructive framework that converts the QSD propagator into an input-independent Kraus channel for a fixed bath preparation and a selected evolution time. The construction incorporates reservoir memory through a finite-mode approximation of the bath covariance and yields a deterministic channel representation that can be compressed for approximate implementation with a system-ancilla circuit. For the qubit systems considered here, the construction closes exactly in vacuum and extends systematically to finite temperatures. Two-qubit examples with structured reservoirs validate the vacuum channel construction, illustrate its finite-temperature extension for a chosen initial state, and show that the complexity of the reservoir description can differ substantially from the ancilla space required for quantum realization. The framework therefore establishes a direct bridge from microscopic reservoir memory to reusable non-Markovian quantum simulation and provides a foundation for optimized hardware implementations and extensions to larger systems and multitime dynamics.

Differential privacy provides a mathematical framework for guaranteeing privacy for sensitive data. In quantum information processing, the interaction of privacy constraints with quantum resources such as entanglement remains a question of interest. Given that the utility of many protocols, and often the presence of a quantum advantage, relies on quantum resources such as entanglement, it is crucial to understand when a privacy requirement for a quantum channel is compatible with the channel's ability to preserve entanglement. We study this question for quantum local differential privacy (QLDP). Our main result shows that every $\varepsilon$-QLDP channel with a $d$-dimensional input is entanglement-breaking whenever $\varepsilon\leq\log\frac{d}{d-1}$. We also prove an approximate version for $(\varepsilon,\delta)$-QLDP, where channels in the same high-privacy regime are close in diamond norm to an entanglement-breaking channel. We further prove a composition result for a collection of private quantum channels having entangled inputs and global measurements in the high-privacy regime. Finally, we apply our results to private quantum learning theory. We prove that any learning protocol using arbitrary quantum memory on copies of the output of an entanglement-breaking channel can be simulated by a protocol that measures the corresponding unprocessed input copies one at a time while storing only classical information. Combining this result with our high-privacy entanglement-breaking theorem, we show that under sufficiently private local noise, a learning protocol with quantum memory for purity testing and bipartite product testing is subject to the sample complexity lower bounds for protocols with single-copy measurements on the noiseless tasks. We also obtain stronger sample complexity lower bounds when a single highly private channel acts on the entire multipartite input.

It is now well-established that classical statistical mechanics emerges from the entanglement structure of quantum chaotic systems, as quantified by the (subsystem) eigenstate thermalization hypothesis (ETH). While this statement rests on the well-studied bipartite entanglement of the eigenstates of such systems, recent years have shown that many-body states are often characterized by multipartite entanglement, raising the question: what are the universal multipartite entanglement features of chaotic eigenstates? We answer this question in part by studying a tripartite generalization of the ergodic bipartition ansatz through the lens of two tripartite entanglement probes, the Rényi tripartite multi-entropy and the Rényi reflected entropy. We derive leading-order analytical expressions for the ensemble averages of both quantities using a saddle-point analysis. Beyond these measures, we obtain the average of the Rényi-2 reflected density matrix, $\rho_{AA^*}^{(2)}$,which controls the Rényi-2 reflected entropy. We show that $\rho_{AA^*}^{(2)}$ in a chaotic eigenstate is well-described by this ensemble average which, unlike an ordinary reduced density matrix, takes three qualitatively distinct forms across subsystem-size regimes, which may be viewed as a tripartite generalization of subsystem ETH. We benchmark our analytical predictions against exact diagonalization of the mixed-field Ising model.

Discrete-time quantum walks exhibit ballistic spreading that is highly sensitive to decoherence. We study the long-time dynamics of a one-dimensional discrete-time quantum walk under Pauli noise acting on the coin. Choosing the unitary coin such that its invariant Bloch-sphere axis is orthogonal to the axis fixed by the conditional shift, we identify the distinct effects of noise aligned with either dynamical axis or orthogonal to both. Using a Fourier-space Pauli-superoperator formalism, we derive expressions for the first two position moments and long-time asymptotics for X-, Y-, Z-, and depolarizing noise. All channels induce a crossover from ballistic to diffusive spreading, with a second moment growing linearly at long times. The approach to this regime is channel dependent: it is exponentially fast for X-, Z-, and depolarizing noise, but algebraic, with a leading $t^{-1/2}$ correction, for Y-noise. The position distributions retain distinct finite-noise signatures, including a Gaussian-like profile with a central depression for Y-noise. In the maximal-noise limit, depolarizing, Y-, and Z-noise yield the classical binomial distribution for arbitrary initial coin states, whereas X-noise does so only when the initial state has no component along the noise axis. Thus, the quantum-to-classical transition is governed by the relative alignment of the noise, the coherent walk dynamics, and the initial state.

Realizing fault-tolerant quantum computing requires mapping logical programs to heterogeneous quantum error correction (QEC) codes and diverse fault-tolerant execution models, scheduling physical resources, and coupling to real-time classical control and feedback. Specialized tools exist for each step but rely on manual composition and translation that discard assumptions and provenance, separating resource estimates from the compiler artifacts they describe, and making it difficult to validate correctness, compare architectures, or attribute costs to specific design choices. We present CUDA-Q Logical, an extensible compiler infrastructure for retargetable fault-tolerant compilation, analysis, and execution. Interoperable with CUDA-Q and other mainstream front-ends, CUDA-Q Logical progressively lowers target-independent logical programs through a constrained logical virtual machine, QEC microcode, physical gate schedules, and real-time control plans, with each layer preserving semantics and provenance, while verifying composition and resource constraints. By deriving every resource estimate directly from compiler artifacts, the framework unifies compilation and resource analysis, enabling successively refined estimates and principled cross-architecture comparison while permitting QEC codes, execution models, decoders, and hardware architectures to be introduced as modular extensions. Across workloads ranging from application-architecture studies to qLDPC surgery and detector-error-model composition, we show that schedule-derived estimates reconcile with established independent models. Crucially, this compiler-visible structure exposes cost drivers hidden by aggregate analytical formulas, carries QEC artifacts intact into simulation, and demonstrates a complete compilation pipeline for fault-tolerant quantum computing.

How rapidly does order give way to randomness, and can quantum coherence accelerate this process? We address these questions through the paradigmatic problem of card shuffling, formulated as a random walk on the symmetric group $S_n$. We first recast the random-transposition walk studied by Diaconis and Shahshahani, as well as more general walks generated by conjugacy classes of $S_n$, in continuous time. We then identify the transition matrix of each classical walk with a permutation Hamiltonian generating a corresponding unitary quantum walk. Purely unitary evolution, however, does not generically converge to the uniform distribution in the classical sense of mixing: coherence preserves information rather than erasing it. We therefore embed the problem into a quantum stochastic walk, where coherent dynamics competes with the dissipative process responsible for classical mixing. In this setting, quantum coherence assists randomization. We prove that it can only decrease the distance from the uniform distribution in the computational basis and can therefore accelerate mixing. An analysis of the slowest mode yields a criterion for the coupling strength required to produce an appreciable speedup. Finally, numerical results reveal a scaling collapse of the ratio between quantum and classical mixing times onto a simple one-parameter form. Our results illustrate how coherence and dissipation can cooperate in the emergence of randomness in walks on permutation groups.

Sequential circuits provide an optimal linear-depth route to unitarily preparing long-range ordered quantum states, but circuit-level noise can be far more damaging than noise applied after preparation: local errors may be propagated by subsequent gates into nonlocal defects that destroy the target order. In this work, we present classes of unitary sequential circuits that prepare certain non-trivial orders in the presence of Pauli noise. Our constructions exploit the spatial structure of the syndromes of the target state, which in certain cases allows us to systematically suppress the propagation of errors using strictly local gates. The strategy can be applied both to symmetry-breaking order, for which we present a 3D example, and to topological order, which we showcase on a 4D version of the toric code. We also highlight how this stability against errors necessitates non-Clifford gates, and how measurement-feedback loops can be used to stabilize lower-dimensional states as well.

Linear Optical Quantum Computing (LOQC) is emerging as a promising technology in large-scale quantum computing. Corresponding devices, including linear optical circuits, are rapidly growing in size and fabrication precision. However, even with improved quality, the circuits still exhibit imperfections leading to photon loss or phase noise that vary across the circuit. Already small deficiencies can have a vast impact on both accuracy and efficiency. For computations that do not require the entire linear optical circuit, so-called subcircuits, one can choose where to perform the computation, opening optimization opportunities that are addressed by subcircuit compilation. Current compilers spread the subcircuit's computation across the entire circuit, connecting the same input and output ports, thereby failing to fully exploit the optimization opportunities. However, given the subcircuit's reduced size compared to the entire circuit, one can keep its implementation localized and intentionally route photons to connect good input and output ports. This, however, is a highly non-trivial task, as numerous options must be weighed against one another, and the quality of the solution is influenced by a wide range of hardware parameters. In particular, the reflectivities of imperfect beam splitters can lead to photon losses during routing, which must be traded off against losses at the input and output ports due to imperfect transmission rates. Since current compilers do not account for these effects, we propose the first efficient subcircuit compilation method that optimizes for the coincidence rate, the probability of successfully measuring all desired photons, by handling hardware imperfections. Our evaluations demonstrate significant improvement over existing methods in robustness against phase noise and significantly increased coincidence rates across all benchmarks of up to plus 33.2%.

We construct a class of integrable chiral fermionic quantum field theories with interactions that depend on both space and time. The construction starts from a unitary, regular, difference-form two-body scattering matrix satisfying braiding unitarity and the Yang–Baxter equation. Each freely moving right- or left-moving particle carries a characteristic coordinate that remains constant along its trajectory, and the scattering matrix depends on differences of these coordinates. The many-body amplitudes form a discrete connection over the coordinate-ordering sectors. The Yang–Baxter equation gives local path independence, while periodic winding on a spatial circle produces quantum Knizhnik–Zamolodchikov (qKZ) difference equations expressing global flatness. Once a reference amplitude satisfying the exchange and qKZ constraints is specified, these transport equations determine the exact wavefunction in every fixed-particle-number sector. Independent reparametrizations of the right- and left-moving characteristics give couplings that depend on both space and time. For the chiral $SU(2)$ Gross–Neveu realization, we solve the qKZ equations for this full characteristic family using off-shell Bethe vectors. The resulting amplitudes are written in the characteristic labels, and their pullbacks give exact many-body wavefunctions for the corresponding space-time-dependent couplings. The two-body amplitude is a ratio of Gamma functions that resums the phase shifts from successive scattering processes. Equal-slope affine maps give a spatially homogeneous specialization in which the coupling depends only on time, and the Bethe ansatz with constant coupling is recovered when the qKZ step vanishes.

We propose a framework for understanding the information loss paradox in the context of canonical quantum gravity. We first revisit several approaches to black hole evaporation that do not involve an event horizon. In these models, we assume that each time slice corresponds to a coherent state in the gravitational phase space. Due to this property, the quantum state associated with a given spatial configuration will have a nonzero overlap with another spatial configuration. We show how this property can account for both semi-classical dynamics and unitary time evolution. We introduce an explicit toy model that follows semi-classical time evolution at the coarse-grained level; in addition, its time evolution is unitary at the fine-grained level. The only price that one must pay is the violation of the entropy bound; we discuss reasons why this may be justifiable.

We introduce a general mechanism for engineering moment-selective temporal designs with hierarchically structured aperiodic drives. At special control settings where the driven dynamics is constrained by a finite symmetry group, lower-order moments can already reproduce Haar statistics while a selected higher-order deviation remains nonzero. A small static detuning from such a setting generically produces an exponentially long lifetime whose exponent scales inversely with the square of the detuning. We illustrate this mechanism in qubit systems through exact Fibonacci and silver-mean constructions with tetrahedral and icosahedral resonances, for which the first retained non-Haar moments occur at orders $3$ and $6$, respectively. We further show that stochastic control fluctuations produce a qualitatively different cutoff from coherent detuning. Finally, we propose a finite-time signature of the long-lived moment that can be measured without requiring observations over exponentially long times.

Future quantum communication networks will conceivably support cryptographic tasks that require entanglement among more than two users. Quantum secret sharing is a prime example where entanglement provides a direct means to coordinate untrusted parties with security from eavesdropping in a multi-party setting. However, the canonical GHZ-based protocols can be vulnerable to participant attacks, in which untrusted parties try to learn the secret without collaborating. Here, we experimentally evaluate a discrete-variable $(n,n)$-threshold quantum secret-sharing protocol whose finite-key analysis provides composable security against general attacks, including participant attacks. Using two domain-engineered entangled photon pair sources, we generate 4-qubit GHZ states at rates above $5\times10^3$ fourfold events per second and a maximum asymptotic secret key rate of $750 \pm 10$ bits per second. We then distribute the state through a 4-arm star network comprising 20k̃m of fibre in total. From the measured event rates and error statistics, we infer that a randomised 24-hour execution with the optimised basis probability would yield a composable finite-key lower bound of 8.7 Mbits, under the assumption that the measured source and device statistics remain stationary.

Quantum kernels promise exponentially large feature spaces, but expressive circuits render their Gram matrices uninformative, bandwidth tuning collapses them toward classical RBF, and the practical consensus is that quantum kernels add nothing on classical data. We answer another productive question, an architectural one: whether the structure of an encoding circuit can carry an inductive bias that tuned classical kernels lack. We introduce AeRot, a quantum kernel fusing amplitude encoding of l2-normalized delay windows with a grouped single-qubit rotation layer that assigns contiguous temporal blocks to each qubit, making the circuit delay-window-aware. On Lorenz-63 kernel ridge regression with cross-validated bandwidths over 100 seeds, AeRot outperforms tuned RBF and Matern-5/2, the advantage emerging at physical horizons >= 0.15 tu and reaching +0.137 mean R^2 at 0.25 tu (5 qubits, window 32). Linear-stability analysis of the window tail localises the advantage to the unstable saddle-approach regime: AeRot wins 83% of windows in the most unstable decile, with the win rate rising monotonically with tail instability and a sign flip at the local stability boundary. The difficulty is fold-branch ambiguity: trajectories approaching the saddle are locally diverging, and Euclidean kernels struggle to resolve which lobe the trajectory will commit to. Structural diagnostics confirm Gram matrices structurally distinct from tuned RBF, with strictly higher target-kernel alignment at every horizon. The gain is architectural: a finite-sample inductive-bias effect of temporally structured encoding on a folded attractor, with no computational-separation claim attached. To our knowledge this is the first mechanistic localisation of quantum-kernel advantage to a specific dynamical regime of a classical system.

In epsilon-near-zero (ENZ) materials, the vanishing real linear permittivity results in the leading-order contribution to the displacement field being nonlinear in the electric field, making conventional canonical quantization approaches highly non-trivial. Existing treatments generally quantize the linear modes first and introduce nonlinear interactions subsequently, an ordering that becomes inadequate in the ENZ regime. Here, we provide, to our knowledge, the first effective single-excitation quantization in which the near-zero linear response, leading nonlinearity, and loss jointly determine the elementary excitation. Using a solvable microscopic atomic system as a theoretical scaffold, we find that this excitation is a polariton: a dressed quasiparticle with partly field and partly material excitations whose coefficients can be parameterized by macroscopic susceptibilities. While this work considers a leading-order $\chi^{(3)}$ nonlinearity, the framework could be generalized to include other nonlinear corrections, including a controllable second-order susceptibility $\chi^{(2)}$ and systematic higher-order contributions $\chi^{(n)}$, $n>2$. Our findings pave the way toward practical applications in quantum photonics, such as single-photon non-demolition detection, by leveraging the strong nonlinearities intrinsic to zero-index materials.

We prove optimal trace-norm relaxation for the one-dimensional Lindbladian associated with the Witten differential $a=h\partial_x+V'$ which annihilates the classical Gibbs density: if $\lambda_1(h)$ is the first positive eigenvalue of $H=a^*a$, then the relaxation rate is $\gamma_h=\lambda_1(h)/(2h)$. It applies to initial operators whose Schwartz kernels, after a Gibbs conjugation, satisfy $ L^2 $ estimates for the restriction to the diagonal and for the normal derivative. An appendix by Chat GPT 6 presents a stronger result specialised to positive initial data.