Papers

The evolution of a charged lepton in the field of an electromagnetic plane wave can be described as a superposition of Volkov states. Here we demonstrate that imposing specific momentum correlations among Volkov states produces a spatiotemporally structured wavepacket whose probability-density peak travels at an arbitrary, tailored velocity. This velocity can be chosen independently of both the field amplitude and the velocity expectation value. The imposed momentum correlations modify the expectation-value trajectory, providing a measurable signature of the arbitrary velocity within a physical observable.

We present a hardware-validated reference dataset for variational ground-state energy calculations of the hydrogen molecule H\(_2\) on several IBM Quantum processors available in 2026. Using a standardized workflow, we benchmark the impact of shot count, backend choice, optimization strategy, and runtime variability on the achievable energy accuracy relative to exact diagonalization. The resulting dataset and analysis provide a transparent baseline for assessing the current capabilities and limitations of IBM Quantum hardware for quantum-chemistry applications, and are meant to ease the entry for new users by providing a comprehensive overview of choices and their effects as well as runtime efforts and costs that can be expected. Across the configurations studied here, circuit simplification through tapered mappings provides the most consistent accuracy gains, resilience level 1 improves accuracy at a substantial cost premium, and session-based execution yields no systematic accuracy advantage over single-job execution despite markedly higher billed time.

The non-Hermitian skin effect (NHSE) refers to the accumulation of an extensive number of eigenstates at system boundaries under open boundary conditions (OBCs). As a dynamical consequence, wave packets in such systems drift and ultimately accumulate at a boundary, giving rise to the dynamical skin effect (DSE). While strong quasiperiodic potentials are known to suppress the DSE by inducing localization, we show that the introduction of Ornstein-Uhlenbeck (OU) noise unexpectedly restores it. Using perturbative analysis, we demonstrate that noise effectively maps the non-Hermitian Schrödinger dynamics onto a non-reciprocal master equation, whose complex spectrum develops a noise-induced point gap. This mechanism enables delocalization, reinstates directional transport, and revives the DSE even in regimes where the static NHSE is absent. Moreover, the relaxation dynamics exhibit a non-monotonic dependence on noise strength, reflecting a competition between noise-assisted delocalization and noise-induced decoherence. Our results uncover a noise-enabled mechanism for resurrecting the DSE and suggest a new route for controlling transport in quasiperiodic, open quantum systems.

Quantum annealing (QA) is a promising approach for solving combinatorial optimization problems; however, it is known to exhibit unfair sampling, in which degenerate ground states are not sampled with equal probability even for sufficiently long annealing times. Fair sampling is important in applications such as solution diversity assessment and combinatorial counting, yet the mechanism of unfair sampling remains poorly understood, particularly in constrained combinatorial optimization problems. In this work, we investigate unfair sampling of QA in weighted graph bipartitioning problems (GBP), a representative constrained optimization problem. We study how the penalty coefficient in the penalty method affects sampling fairness. Through numerical simulations and experiments on the D-Wave Advantage2 system, we show that increasing the penalty coefficient reduces unfair sampling in a representative single instance, and that this qualitative behavior is also observed on actual hardware. A scaling analysis over randomly generated instances with up to 12 spins reveals that, while this trend does not hold universally, more than 70% of instances exhibit monotonically increasing sampling fairness as the penalty coefficient increases, even at the largest system size studied. These results show that increasing the penalty coefficient improves sampling fairness, though at the cost of ground-state probability under practical annealing conditions, and call for a deeper theoretical understanding of unfair sampling in constrained optimization problems.

Device-independent quantum key distribution (DI-QKD) provides the highest level of cryptographic security by certifying secrecy through observed Bell inequality violations, independent of the internal device physics. However, the transition from theory to practice is obstructed by the dual challenge of closing the detection loophole and achieving viable key rates over fiber distances. In this paper, we present a comprehensive theoretical framework for DI-QKD implemented on topological Majorana Zero Mode (MZM) processors. While MZMs offer a native parity-readout basis that simplifies Bell-state measurement, their viability as QKD nodes is fundamentally constrained by the interplay between storage latency and quasiparticle poisoning. We bridge the gap between microscopic hardware noise and macroscopic security by: (i) developing a hardware-native error model that maps MZM-specific processes, including poisoning rates, braid infidelities, and readout anisotropy, directly to the CHSH Bell parameter $S$; (ii) introducing a loss-disciplined protocol that monitors setting-conditional efficiencies to strictly enforce detection-loophole closure in a heralded architecture; and (iii) providing a composable finite-size security proof based on the Entropy Accumulation Theorem (EAT). Our analysis reveals that while topological protection stabilizes the system against calibration drift, the achievable secure distance is strictly bounded by the poisoning-induced visibility collapse during the photonic round-trip time. We identify specific hardware thresholds, particularly the suppression of poisoning rates to $\Gamma_p \tau_{\text{max}} \ll 1$ and high-fidelity sensor integration, as the critical path for viable topological quantum networks.

It was recently conjectured and verified for the transverse-field Ising model [Phys. Rev. B 113, 165102 (2026)] that, after a sudden quench within the same equilibrium phase, the initial ground state has its largest overlap with the final ground state. We show that this phase-based criterion is generally false, even in translationally invariant free-fermion systems. For Hamiltonians that factorize into independent $2\times 2$ momentum sectors, we derive the exact necessary-and-sufficient condition for ground-state overlap dominance: the initial and final sector Bloch vectors must have positive dot product for every momentum. This result proves the conjecture in classes where same-phase quenches enforce this geometric condition, but gives explicit same-phase counterexamples in Kitaev chains, where excited final eigenstates can dominate the overlap distribution. We further show that the same obstruction controls real-time Fisher-zero crossings, allowing dynamical quantum phase transitions without crossing an equilibrium phase boundary.

The efficient execution of fault-tolerant quantum algorithms is fundamentally limited by the production rate of magic states required for non-Clifford operations. While circuit optimization typically targets T-depth, static T-depth does not reliably predict executable performance under bounded T-state delivery. We introduce a model that captures demand-supply imbalance using two key quantities: slack ratio, a structural indicator of scheduling flexibility, and Delta_max, a measure of cumulative demand surplus. We show that Delta_max is a strong schedule-level indicator of execution slowdown and yields a provable lower bound on executable makespan for a fixed schedule. Empirical evaluation on constructed directed acyclic graph (DAG) families, with arithmetic circuits and exact quantum Fourier transform (QFT) traces providing additional grounding, shows that slack ratio is a stronger structural predictor than T-depth for stall and inversion risk, while Delta_max is the strongest predictor of slowdown. Across 4,904 instances, the lower bound shows zero violations, with 88.9% of cases within one cycle. These results highlight the importance of explicitly modeling delivery constraints in fault-tolerant quantum compilation.

Absence of thermalization after a global quantum quench is a well-established numerical observation in integrable many-body systems, and can be empirically related to a violation of the eigenstate thermalization hypothesis (ETH) in such models. Still, in many of those examples a weaker version of the conventional ETH (wETH) has been numerically reported or even rigorously proven. In this paper we show analytically and illustrate numerically that the absence of thermalization is already possible after a local quench. A closely related finding is a strong violation of the ETH, meaning that not even the wETH is fulfilled anymore. In our analytical explorations we focus on XX-spin-chain models with open boundary conditions, where the local quench is generated by initiating the system in thermal equilibrium and then suddenly switching on (or slightly changing) a single-spin impurity either at the end or in the center of the chain. Numerically we observe qualitatively similar phenomena also for more general XXZ-models in the case of an end-impurity, but not in the case of a central impurity.

Quantum computing is increasingly offering concrete solutions toward the simulation of nuclear structure, with the potential to overcome the exponential scaling that limits classical diagonalization methods in large spaces. A particularly efficient encoding scheme, based on collective like-nucleon pairing modes, reduces the qubit requirements by half and avoids the non-local operator strings of standard fermion-to-qubit mappings. While this quasiparticle framework provides accurate results for semimagic nuclei, it does not adequately describe open-shell systems where proton-neutron correlations become important. In this work, we apply Brillouin-Wigner perturbation theory to systematically improve the quasiparticle description of open-shell nuclei in the $sd$ shell, reaching an energy relative error below $0.2\%$ compared to the nuclear shell model. Furthermore, to make the effective Hamiltonian suitable for quantum simulation, we introduce a mean-field Hartree-Fock approximation of the non-quasiparticle resolvent, achieving ground-state energies typically within $2\%$ of the exact shell-model result. This represents a systematic improvement over the bare quasiparticle Hamiltonian while remaining within the reach of near-term quantum devices.

Superconducting quantum computing is advancing toward the thousand- and even million-qubit regime, making wafer-scale fabrication an essential pathway for achieving large-scale, cost-effective quantum processors. This manufacturing paradigm imposes new requirements on quantum-chip electronic design automation (Q-EDA): design tools must not only generate layouts (GDSII files) that satisfy quantum-circuit physical constraints but also ensure that the design data can be seamlessly converted into a complete set of manufacturing files executable by a wafer foundry, thereby enabling reliable translation from design intent to physical chip. This paper focuses on this critical data-conversion pipeline and presents a systematic treatment of the Q-EDA technology stack for wafer-scale fabrication. Starting from GDSII as the single authoritative data source, we analyze the key stages including process-design-kit (PDK)-based design rule checking (DRC), layout-versus-schematic (LVS) verification, design for manufacturability (DFM) optimization, wafer layout planning, and mask data preparation (MDP). We describe the concrete architecture of a Q-EDA system, present nine quantum-specific DRC rules together with their physical underpinnings and a multi-layer process stack model, and benchmark the manufacturing data-flow coverage of mainstream Q-EDA tools. Finally, we discuss the core challenges and future directions in this field.

We present an analytically tractable model of a driven quantum harmonic emitter, such as an oscillating charged dipole, emitting radiation via resonance fluorescence. With this model we are able to characterize the quantum mechanical correlations that are built up at early times between the drive, the resonant emitter, and its fluorescence. We describe detection strategies that can reveal these quantum signatures in experiments by performing joint measurements on the quantum emitter and its fluorescence field. In particular, we show that simultaneous quantum measurements of a driven quantum emitter and its fluorescence can be used to probe the quantum noise of the driving field, relative to the maximally classical coherent state of the driving field, in short-time experiments. We conclude by discussing the applications to quantum sensing in quantum optical, quantum acoustic, and quantum gravitational scenarios of interest.

Two-dimensional materials that exhibit optically active spin and valley degrees of freedom represent one of the most fascinating – and potentially most technologically useful – platforms for the ultrafast interaction of light and matter. Here we show, via the example of Cr$_2$SO, that two dimensional altermagnets host valley states controllable by femtosecond laser light: linearly polarized light pulses excite charge at one of two inequivalent valleys, with which valley charge is excited at determined by the polarization vector direction. This underpins a rich spin and valley physics including: (i) valleytronics $-$ the generation of nearly 100$\%$ spin polarized valley currents, as well as (ii) a "ghost Hall" effect $-$ the ultrafast creation of states in which spin and charge currents are orthogonal without invoking Hall physics. Our findings establish 2d altermagents as a platform providing a new route for the control of spin- and charge currents at ultrafast times.

Solid-state platforms are particularly attractive for quantum optics because they facilitate on-chip integration and are compatible with established semiconductor and photonic technologies. However, a major challenge in solid-state quantum optics is the fabrication of arrays of identical emitters, such as quantum dots. In this work, we propose moire superlattices as a novel solid-state platform for manipulating light at the single-photon level. Moire superlattices form arrays of artificial-atom states characterized by nearly identical optical transition energies, tunable spacing, and highly adjustable electronic structures. They naturally operate as atomically thin, scalable, periodic emitters, making them ideal for quantum applications. Additionally, the extensive materials database of moire superlattices offers spectral coverage spanning a broad range of optical wavelengths.

We present an analytical theory of greedy peeling decoding for bivariate bicycle (BB) codes under circuit-level noise. The deferred greedy decoder achieves 330x latency reduction over belief propagation (BP) at p = 10^{-3} while maintaining identical logical error rate. Our main theoretical contribution is a closed-form collision resolution factor A_0 = |true collisions| / |birthday collisions|, derived from XOR syndrome analysis with no free parameters, that quantifies the fraction of detector-sharing fault pairs genuinely blocking iterative peeling. For the [[144,12,12]] Gross code, A_0 = 0.8685 (within 0.5% of the empirical value), with shared-2 pairs (4-cycles) always resolving under peeling. We show A_0 depends on the mean fault-graph degree d-bar rather than code size: A_0 = 0.87 for d-bar = 52 (Gross family) versus A_0 = 0.76 for d-bar = 17 ([[32,8,6]]). We establish a syndrome code stopping distance d_S = n/4.5 for the Gross family and demonstrate that [[32,8,6]] (d_S = 4) enables two-shot streaming decoding: T = 2 rounds achieve 89% peeling success with 1.29 +/- 0.03 LER ratio versus T = 12, at estimated latency ~50 ns. The full formula P_peel = exp(-A_0 * gamma_analytic * exp(-BTp) * n * p^2) is validated across five BB codes, four noise levels, and four values of T with R^2 = 0.86. Cross-platform reproduction of the Kunlun [[18,4,4]] experiment matches their hardware LER within 0.73 percentage points.

Color centers associated with group-IV dopants in diamond with long-lived nuclear spins have emerged as major candidates for distributed quantum computing nodes and quantum repeaters. Several proof-of-principle experiments have already been demonstrated. A key operation for long-distance entanglement-distribution protocols are fast and robust gates between the electron spin and a nuclear spin. Here, we investigate numerically for an existing experimental platform of a Germanium-vacancy (GeV) center with a strongly-coupled ${}^{13}$C spin, how such gates can be implemented via quantum optimal control. In the presence of realistic noise we investigate different parameter regimes and gate operations and obtain robust two-qubit gates with fidelities exceeding $99.9 \%$. The framework provides a scalable strategy for group-IV quantum nodes and can be adapted to related architectures.

Pulse-level compilation can reduce the depth and calibration overhead associated with decomposing continuously parameterized quantum operations into fixed gate libraries, but conventional optimal control requires a new optimization for each target and can be sensitive to hardware uncertainty. We introduce a physics-informed neural compilation framework that learns a reusable map from continuously parameterized single-qubit gate targets directly to experimentally admissible control waveforms. The compiler is trained end-to-end through differentiable quantum dynamics without precomputed optimal-pulse labels, and its robustness is improved by first diagnosing physically relevant failure modes and then applying tail-risk-aware fine-tuning. On a three-qubit liquid-state nuclear magnetic resonance (NMR) model, the learned compiler generalizes across Haar-distributed single-qubit targets with mean nominal fidelity above 0.99 and generates new pulses in submillisecond inference time. Matched benchmarks reveal complementary advantages: robust gradient ascent pulse engineering (GRAPE) achieves the highest per-target fidelity, whereas the trained neural compiler amortizes the optimization cost across the target family, enabling substantially faster online pulse generation. Risk-aware training substantially broadens tolerance to radio-frequency (RF)-amplitude errors, including perturbations beyond the training range. Experiments on a three-spin NMR processor reproduce the predicted broadening of the RF-tolerance response, although the absolute experimental correlations are lower than the simulated values. These results establish a general workflow combining amortized machine learning, physical sensitivity diagnosis, risk-aware control, optimal-control benchmarking, and hardware testing, providing a route toward fast and robust pulse-level compilation for repeatedly varying quantum operations.

Accessing quantum advantage (QA) is a legitimate task in energy harvesting devices, and it is potentially reshaping thermodynamic concepts. In this respect, the resourceful quantum non-Gaussian (QNG) states are promising candidates that precisely enable universal quantum operations to enhance thermodynamic performance with capabilities beyond what Gaussian states can achieve. We recently proposed [K. Adhikary, D. W. Moore, and R. Filip, Quantum Sci. Technol. 10, 035048 (2025)] the QNG state generation scheme, which serves as the framework for this study and is directly integrated into the battery setting to figure out QA. By leveraging coherence in the engineered QNG states, we aim to optimize the performance of quantum batteries for various Gaussian charger profiles under unitary dynamics. We further exploit the degree of thermal broadening and environmental coupling to the charger, which is capable of fostering stable performance under precise thermal management. This study provides a proof-of-concept for exploiting thermodynamic resources in quantum energy storage units.

We show that quantum computational imaging is advantageous in the setting of low-dose electron microscopy of beam-sensitive specimens. Two qudits placed near the electron beam enable full transfer of quantum information between the electron microscope and a quantum computer in the proposed scheme, providing the specimen is a phase object. We present a quantum algorithm that identifies the correct image among n candidate images, where n is larger than the effective dimension of the Hilbert space of the imaging electron.

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

Stationary multi-magnetometer arrays are routinely deployed in geomagnetic observatories, laboratory shielded rooms, and ground-based monitoring stations. The standard analysis pipeline reduces each sensor to an independent power spectrum, discarding any inter-sensor structure that is itself diagnostic of measurement health and of localised magnetic activity. This paper develops a purely theoretical framework for a deliberately simple visualisation that maps the short-time Fourier (STFT) power spectra of three concurrent magnetometers into the red, green, and blue channels of a single image: the cross-sensor RGB spectrogram. Inter-sensor coherence appears as neutral grey or white, while spectral energy that is unique to one or two sensors stands out as saturated colour. We formalise the construction of the image, derive its time-frequency resolution properties, give an explicit account of the per-channel normalisation choice, and present a colour-anomaly taxonomy that distinguishes coherent broadband activity, single-sensor faults, asymmetric pairwise sources, and slow temporal drift. A companion long-window variant is described for resolving features in the ultra-low frequency (ULF) band. The construction is presented without reference to any particular dataset or implementation; it is intended as a self-contained methodological building block that can be inserted into any monitoring pipeline whose front end is a synchronously sampled magnetometer triad. Because the construction operates on scalar magnitude time series alone, it applies equally to classical fluxgate sensors and to quantum magnetometers – optically pumped magnetometers (OPMs), nitrogen-vacancy (NV) centre arrays, and superconducting quantum interference devices (SQUIDs) – where distinguishing quantum-limited noise from technical artefacts is a central diagnostic challenge.

We analyze a class of one-dimensional quantum systems characterized by a position-dependent kinetic term arising as the continuum limit of an inhomogeneous tight-binding model with spatially varying hopping amplitudes. In this limit, the Schrodinger equation takes the so-called BenDaniel-Duke form with an effective mass, scaling as $m_{eff}(x) = m_{eff}|x|^{\alpha}$ with $\alpha > 0$, leading to a framework we term sluggish quantum mechanics, where particle motion is progressively suppressed at larger distances. Both without any external potential and with $V_{ext}(x)=\frac{1}{2}m_{eff}\omega^2 |x|^{\alpha+2}$, we obtain the eigenfunctions and the quantum propagators exactly. We then investigate the problem of $N$ noninteracting spinless fermions in the trap, determining the many-body ground-state wavefunction and the joint probability density function of the positions of the $N$ fermions. We show that the many-body quantum probability density in the ground state forms a determinantal point process whose correlation kernel can be computed for any $N$, giving access to the average density as well as higher order correlation functions for any finite $N$. Moreover, we analyze the scaling form of this kernel in the large $N$ limit in the bulk, near the edge, and close to the origin. Our results show that the scaled average density profile for large $N$ has a finite support symmetric with respect to the origin, but has a non-monotonic shape with a vanishing minimum at the origin for any $\alpha>0$. One of the key findings of our work is that the scaled kernel near the origin $x=0$ for $\alpha>0$ is neither the Bessel nor the Airy kernel (that are standard for trapped fermions), but is new, and is given by a sum of two Bessel kernels with different indices. Our results thus provide a framework relevant to engineered optical lattices with position-dependent tunneling.

We propose a novel measurement-free scheme for stabilizing a spin-oscillator hybrid qubit via autonomous quantum error correction. The engineered Lindbladian renders the code space into an attractive steady-state subspace, realized by coupling the storage mode to a rapidly cooled bath through a controlled beam-splitter and spin-dependent displacement interactions. The continuous variable-discrete variable hybrid approach to autonomous quantum error correction preserves the hardware efficiency of conventional dissipation engineering while simplifying the required system-bath coupling. The construction is compatible with simple logical gates and leverages primitives already demonstrated in experimental platforms, such as trapped-ion systems, suggesting a practical route to hardware-efficient, noise-biased logical qubits without repeated syndrome measurements and feedforward.

The search for quantum-like wave formulations of the Navier-Stokes (Schrödinger-Navier-Stokes, SNS for short) equations describing classical dissipative fluids has met with increasing attention in the recent years, due to the large portfolio of potential applications in science and engineering. A SNS formulation of classical fluids was first presented in a largely un-noticed paper by Dietrich and Vautherin back in 1985(Journal de Physique). In this paper, we revisit this specific SNS approach and assess its viability for quantum implementations based on Carleman embedding/linearization techniques. Specifically, we i) Clarify in full mathematical detail why the SNS dissipator presents a steep challenge for quantum computers and propose a way out strategy based on the Hamilton-Jacobi (HJ) formulation of fluid dynamics; ii) Develop a corresponding quantum algorithm using a new technique based on a tensor-network representation of Carleman embedding of the HJ equations (CHJ) which permits substantial memory savings; iii) Emulate the CHJ quantum algorithm on a classical computer and analyse its convergence and accuracy for the specific case of Kolmogorov-like flows at moderate Reynolds numbers. To the best of our knowledge, this is the first quantum algorithm based on a quantum-like wave formulation of the genuine Navier-Stokes equations, including pressure, dissipation and vorticity.

We present a strategy for the quantum simulation of many-body lattice models with constrained Hilbert spaces. We focus on lattice gauge theories (LGTs), which underlie a wide range of phenomena in particle physics, condensed matter, and quantum information. In present-day quantum computing platforms, perfect restrictions of the Hilbert space to the desired gauge sectors are beyond reach: for LGTs, violations of the local constraint are unavoidable, posing a formidable challenge for the emulation of the underlying physics. Here, we develop a Floquet-engineering framework that restructures departures from a target sector such that a series of emergent local symmetries occurs hierarchically in time and in a controllable way. This leads to a set of approximate dynamical selection rules that strongly restrict inter-sector couplings, resulting in a pronounced, symmetry-controlled hierarchy of lifetimes for the state population to spread among sectors. Concretely, this protects $U(1)$ LGTs against violations of the {defining} local symmetry. While some sectors remain very long-lived, others are destabilized on shorter timescales. We numerically verify our theory for the one-dimensional $U(1)$ quantum link model. In addition, we reveal that `defects', whose movement accounts for violations of the gauge constraint, are kinetically constrained, becoming mobile only through the assistance of intra-sector dynamics, which we describe using an effective quantum marble model. Our results can thus be used to extend the lifetime, in the spirit of passive error correction, of quantum simulations of complex many-body problems when emergent or desired local symmetries are only implemented approximately.

We derive an upper bound on the maximum balanced bipartite entanglement entropy of ground states of many-body Hamiltonians defined on a graph, agnostic to any particular model, that possesses a nontrivial automorphism group. We show that the entropy is bounded by the logarithm of a weighted sum of multiplicities of irreducible representations of the bipartition-preserving automorphism subgroup. This bound complements the known degeneracy-based bound, with neither universally dominating the other. For the complete graph $K_n$, the new bound yields an exponential improvement from linear to logarithmic scaling in the system size, consistent with the exact value of the entropy.

Most quantum machine learning (QML) pipelines still rely on static encodings such as angle and amplitude maps, and this limits their ability to handle temporal information. To address this limitation, this paper uses spike-based data representation as an effective encoding mechanism that incorporates temporal structure into quantum feature preparation. Specifically, we propose Spiking-Phase Adaptive Temporal Encoding (SPATE), a novel spike-driven temporal encoding method that converts real-valued tabular features into leaky integrate-and-fire spike trains and maps spike statistics to quantum rotations, augmented with a small set of temporal qubits through controlled phase operations. An encoding-centric evaluation protocol is also introduced to assess representation quality independently of the classifier, covering centered kernel-target alignment (CKTA), Fisher-style separability, inter/intra-class distance ratios, silhouette score, normalized entropy, and pairwise total-variation (TVpair) collapse indicators. Under stratified cross-validation, SPATE yields stronger representations across multiple datasets. For example, SPATE reaches a CKTA of 0.966 and a Fisher score of 7.37 on Blobs, compared with a CKTA of 0.632 and a Fisher score of 0.70 using angle encoding, and achieves a CKTA of 0.506 on Moons, compared with 0.015 using angle or amplitude encoding. These gains translate into stronger hybrid quantum neural network performance within a fixed qubit budget across several tasks, including an accuracy of 0.826 and an AUC of 0.978 for Wine, as well as an accuracy of 0.840 and an AUC of 0.923 for Moons. These results demonstrate that SPATE provides a practical spike-to-phase interface for building more informative quantum feature representations under constrained resources.

We construct a class of quantum many-body systems hosting an $\mathfrak{su}(3)$-invariant scar subspace, extending the conventional paradigm of quantum many-body scars beyond equally spaced spectra and single-directional tower structures. Our construction is based on local constraints that realize an algebraic closure within the scar subspace. As a result, the spectrum in the subspace is no longer equally spaced, but instead forms a multidirectional lattice structure parametrized by multiple independent quantum numbers. This leads to qualitatively new dynamical signatures: instead of single-frequency revivals, the system exhibits multifrequency oscillations governed by integer linear combinations of distinct energy scales. Importantly, the stability of the scar subspace does not rely on exact solvability of individual eigenstates. We show that algebraic closure preserves the invariant subspace even under perturbations that render the eigenstates analytically intractable, thereby realizing quantum many-body scars on an unsolvable reference state. Our results identify algebraic closure as a unifying mechanism underlying scar subspaces beyond the conventional $\mathfrak{su}(2)$ paradigm, and open a route toward richer nonthermal dynamics in nonintegrable quantum systems.

The quantum computing community is increasingly positioning quantum processors as accelerators within classical HPC workflows, analogous to GPUs and TPUs. However, many real-world applications require scaling to hundreds or thousands of physical qubits to realize logical qubits via error correction. To reach these scales, hardware vendors employing diverse technologies – such as trapped ions, photonics, neutral atoms, and superconducting circuits – are moving beyond single, monolithic QPUs toward modular architectures connected via interconnects. For example, IonQ has proposed photonic links for scaling, while IBM has demonstrated a modular QPU architecture by classically linking two 127-qubit devices. Using dynamic circuits, Bell-pair-based teleportation, and circuit cutting, they have shown how to execute a large quantum circuit that cannot fit on a single QPU. As interest in quantum computing grows, cloud providers must ensure fair and efficient resource allocation for multiple users sharing such modular systems. Classical interconnection of QPUs introduces new scheduling challenges, particularly when multiple jobs execute in parallel. In this work, we develop a multi-programmable scheduler for modular quantum systems that jointly considers qubit mapping, parallel circuit execution, measurement synchronization across subcircuits, and teleportation operations between QPUs using dynamic circuits.

We present a directional-transport (DT)-based remote CZ gate and compiler for zoned neutral-atom arrays that overcomes movement-bound entanglement limitations. Current AOD-based shuttling faces row/column non-crossing constraints, device-speed limits, and hardware-restricted range - bottlenecks for long-distance connectivity. Our approach reserves AODs for channel setup and micro-tuning while making DT the default for remote entanglement. Under antiblockade, a detuning-modulated pi-pulse sequence drives directional transport of a Rydberg excitation along a dynamic and resettable ancilla corridor, realizing a CZ gate between stationary, non-adjacent qubits. This cuts entangling-stage duration by approximately 50 to 90 percent versus AOD-only baselines and enables long-distance connectivity beyond objective-limited shuttling.

Recent experiments on K3C60 revealed a giant enhancement of the light-induced superconducting-like optical response for pump frequencies near 10 THz, with an efficiency roughly two orders of magnitude larger than for off resonant excitation. Here we show that a resonant enhancement of pair correlations arises naturally in a driven purely electronic model of K$_3$C$_{60}$ with ab initio parameters. The underlying mechanism is a symmetry constrained two-photon pathway: the first photon drives the system from the even-parity ground state to an intermediate odd-parity manifold, while the second photon induces a transition to an even-parity excited state with enhanced pair correlations. Larger-cluster calculations show that the corresponding resonance energy is strongly renormalized downward with system size and connectivity, reflecting the kinetic-energy gain of delocalized photo-excited doublon-holon configurations. A simplified single-orbital model reproduces this scaling trend and reaches a 14-site fcc cluster, where the resonant peak is pushed to 30 THz, with a trend compatible with a further reduction toward the experimental 10 THz scale in larger systems. Varying the Hubbard coupling strength, we find that the resonance is lowest and the pairing enhancement strongest near intermediate couplings, where doublon-holon excitations are both well defined and mobile. Our results establish a purely electronic mechanism for resonant light-enhanced pair correlations in K$_3$C$_{60}$ and support the interpretation of the experimental 10 THz resonance as optical access to a paired many-body excited state rather than improved metallicity. More broadly, they suggest that related resonant pathways may arise in other intermediate-coupling Hubbard materials.