Vacuum electron-positron pair production is investigated using the Dirac-Heisenberg-Wigner formalism in spatially inhomogeneous electric fields. The external field, given by $E(x,t){\mathbf{e}}_x$, exhibits a strong positional dependence and a strict spatial antisymmetry—i.e., $E(-x)=-E\left(x\right)$. Our results demonstrate that this antisymmetry fundamentally reshapes the pair-creation dynamics, yielding results that differ qualitatively and quantitatively from those obtained under spatially symmetric or fully asymmetric field configurations. We further analyze multipulse field profiles with systematically varied field separations and show that the separation distance exerts a decisive influence on both the integrated pair yield and the detailed structure of the momentum spectrum. Crucially, precise control over the relative spatial positioning of the fields proves essential for engineering desired features in the pair momentum spectrum. We also find that numerical results are in excellent agreement with the analytical approximation for both small and large separation distances. These findings provide robust theoretical guidance for optimizing vacuum pair production in experimentally accessible spatiotemporal field configurations and reveal dynamical effects arising specifically from spatial field antisymmetry.

Artificial spin ice provides a versatile setting for emergent gauge fields and magnetic monopole excitations. Here, we propose a driven-dissipative polariton realization of artificial spin ice, in which the circular polarization of each link mode plays the role of an Ising degree of freedom, while an auxiliary lossy vertex mode dynamically enforces a local ice-rule constraint. Adiabatic elimination of the vertex mode yields an effective spin ice penalty, favoring the two-in two-out manifold in the steady state. We show that local polarization flips generate monopole-antimonopole defects, and that sequential flips transport these defects across the lattice while defining a Dirac string. In an extended spin ice geometry, the vertex charges and their dynamics can be directly reconstructed from polarization-resolved real-space imaging. Our results establish polariton lattices as a controllable driven-dissipative platform in which local ice-rule constraints and monopolelike vertex defects can be generated, manipulated, and reconstructed through polarization-resolved optical measurements.

The fluctuations in the phonon vacuum state can lead to zero point density fluctuations in a material, which in turn lead to local zero point fluctuations of the dielectric properties of the material. We argue that the density fluctuations lead to a fluctuating force on a test charge, such as an electron, located a short distance outside of the material. This force is due to fluctuating dipole moments inside the material and produces Brownian motion of the electron. We calculate the mean squared velocity of the electron in both the normal and transverse directions relative to the boundary of the material. The result is nonzero in both directions, but larger in the normal case. We estimate the magnitude of this quantum Brownian motion and find that, in some cases, it can exceed the effects of both thermal motion and quantum momentum uncertainty. This suggests that the effect may be observable and could constitute a source of quantum noise in nanoscale devices. It also potentially offers a means to remotely sense zero point density fluctuations in a material.

Quantum networks enable forms of nonlocality beyond the standard Bell scenario, with a multitude of potential applications. Continuous-variable (CV) platforms are particularly attractive for large-scale networks, offering deterministic entanglement generation and favorable prospects for long-distance distribution. Here, we present a formalism to study CV network nonlocality using pseudospin measurements. Considering the linear chain and star configurations, we derive the maximal violations of the corresponding network locality inequalities for arbitrary two-mode states. Using two-mode squeezed vacuum states, we show that the strength of nonlocality in the star configuration remains independent of the network size. Moreover, the nonlocal correlations persist even at arbitrarily high temperatures provided the squeezing exceeds a critical threshold. Further, we demonstrate non-Gaussianity as an enhancer of network nonlocality through illustrations of various classes of non-Gaussian resources. Remarkably, a coherent superposition of single-photon subtractions across modes achieves maximal violation for arbitrarily small squeezing. Finally, we provide schematics of an experimentally feasible implementation of CV network nonlocality based on the isomorphism between pseudospin and spatial parity observables.

To overcome the fast oscillatory behavior of correlation functions for extracting scattering phase shift in real-time quantum simulations encountered in the work of Guo et al. [Phys. Rev. D 113, 054512 (2026)], we propose and test two solutions in the present work. One is to simulate Hermitian systems in imaginary time, and the other is to simulate non-Hermitian systems in real time. We demonstrate that both approaches lead to the problem of nonunitary quantum evolution that can be solved by combining two quantum algorithms: block encoding and Hadamard test. The combined quantum algorithm does not require midcircuit measurements or adjustment of the input parameters of the Hamiltonian and can be easily implemented on quantum computers. Numerical tests on quantum simulators show that both approaches agree with exact solutions for a sufficiently long time before the signal is lost in statistical fluctuations. The results bode well for using non-Hermitian and imaginary-time simulations to circumvent oscillations inherent in real-time simulation of other quantum systems. In particular, the non-Hermitian approach shows a decisive advantage over the imaginary-time one on the number of required ancillary qubits, and hence is more practical to scale up.

Quantum batteries can be charged by performing a work “instantaneously” in the limit of a large number of cells, achieving a so-called quantum advantage. In general, the work exhibits statistics that can be represented by a quasiprobability in the presence of initial quantum coherence in the energy basis. Here, we show that these two concepts of quantum thermodynamics, which apparently appear disconnected, can show a simple relation. Specifically, if a certain work distribution shows negativity asymptotically in the limit of a large number of cells and in a certain time interval, then we surely get a quantum advantage in the charging process. In particular, we prove this for a direct charging protocol performed with a class of charging Hamiltonian operators.

Recent discoveries of multi-Q magnetic structures in centrosymmetric compounds have stimulated growing interest in their microscopic origin and observable properties. Here, we calculate the dynamical magnetic structure factor for a double-Q magnetic structure and compare it with that of a single-Q configuration. Our results demonstrate how inelastic neutron scattering can distinguish the double-Q state from competing single-Q states in this square-lattice setting.

The XZZX code is a variant of the surface code tailored to address biased noise in realistic quantum devices. We propose a simulated annealing (SA) decoder for the XZZX code. Our SA decoder is amenable to parallelization because its Markov chain Monte Carlo updates are simple and local. To initialize SA, we use a recovery configuration produced by our greedy-matching decoder. Although $Z$-biased noise is commonly assumed in realistic quantum devices, we instead focus on $Y$-biased noise. Under $Y$-biased noise, the minimum-weight perfect matching (MWPM) decoder becomes suboptimal because it cannot take into account the fact that a $Y$ error contains both $X$ and $Z$ components on the same qubit. Our numerical simulations for the code capacity noise model, where only data qubits suffer errors, show that our SA decoder achieves higher accuracy than the MWPM decoder. They also show that, under moderately $Y$-biased noise, our SA decoder achieves accuracy comparable to that of a decoder based on IBM ILOG CPLEX Optimizer (CPLEX), which uses integer programming to find a minimum-energy error configuration consistent with the measured syndrome. In our greedy-matching decoder, we randomize the tie breaking among equal-weight pairs. This randomness generates a variety of initial configurations for SA, which improves the convergence of our SA decoder. These results suggest that combining SA with our greedy-matching initializer is a promising approach to decoding the XZZX code under $Y$-biased noise in the code capacity noise model.

Previous theoretical studies have shown that attosecond electron dynamics can, in principle, be captured in electron momentum spectroscopy (EMS) using ultrashort electron pulses. By including further analytical considerations on the scattering probability, we here study the effect of the finite transversal extend of the projectile electron wave packet. We find that in wave packet scattering, the target momentum distribution is probed solely in a finite spatial region. This is evident from a spatially filtering Gabor transform appearing in the scattering probability, replacing the full momentum wave function appearing in the conventional plane wave treatment. In addition, by spatially shifting the target with regard to the wave packet focus, we illustrate the influence of vacuum dispersion, i.e., the spatial broadening of the wave packet as it propagates. Our findings are significant for the possibility to correctly interpret future attosecond-EMS results and the considered effects reflect fundamental aspects of wave packet scattering. The EMS setup may, therefore, constitute a useful framework for understanding scattering with finite wave packets.

We present a method for the numerical analysis of superconducting quantum circuits combining lumped elements, either linear or nonlinear (i.e., Josephson junctions), and distributed coplanar waveguide (CPW) structures. CPW transmission lines and multiline couplers are directly modeled without discretizing them into lumped-element equivalents, and the circuit Hamiltonian parameters are extracted by using the energy-participation ratio (EPR) method. This approach enables fast and accurate extraction of mode frequencies, anharmonicities, cross-Kerr interactions, and Purcell decay rates without relying on full electromagnetic simulations, while naturally accounting for higher-order modes of distributed components. We have implemented the proposed method in a Python framework, QuLTRA (Quantum hybrid Lumped and TRansmission lines circuits Analyzer), which we have used to validate the approach against full electromagnetic simulations (Ansys HFSS, pyEPR), existing circuit-analysis tools (QuCAT), and designs reported in the literature. The comparisons show excellent agreement with orders-of-magnitude reductions in computational time relative to full-wave solvers. We demonstrate applications including Purcell-protected readout, multimode ultrastrong coupling, and multiplexed qubit readout, illustrating how the method can support fast and reliable early-stage circuit design.

We numerically study confined channel flow around an obstacle using a two-dimensional soft-particle model, inspired by experiments performed in the same geometry. We systematically vary the polydispersity, the external driving force, and the packing fraction of the system. Our simulations capture a broad range of plastic flow phenomenologies, from highly directional, slidinglike motion characteristic of crystalline materials to more isotropic and localized rearrangements typical of amorphous systems. We identify a threshold value of polydispersity that marks the crossover between crystallinelike and amorphouslike plasticity. In addition, we observe the existence of a critical external force, associated with the phenomenon of yield drag, above which the system reaches steady flow and below which it remains arrested. We determine a critical packing fraction above which such yield-drag behavior emerges. Our results provide a comprehensive framework for understanding the interplay between disorder, driving, and the presence of an obstacle in channel flows.

Finite-time thermodynamic transformations generally dissipate energy, as required by the second law, so identifying and investigating energetically optimal processes remain relevant for understanding and designing efficient thermal devices. In this context, we present here a systematic experimental benchmark of the finite-time minimum-work compression protocol derived by Schmiedl and Seifert for an overdamped Brownian particle in a harmonic trap. By parametrically controlling the trap stiffness, we compare the full work statistics of the analytical optimal protocol with those obtained under linear driving across a broad range of protocol durations and amplitudes. We find that the optimal protocol consistently reduces both the mean work and the work variance relative to linear driving. Although the Schmiedl-Seifert protocol was primarily derived to minimize the mean work, our data show, in the present setting, a clear reduction in fluctuations and high-work tails under realistic bandwidth-limited actuation. This observation connects our benchmark to the growing interest in higher-order cumulants and to current developments in stochastic-thermodynamic control.

The gradient boosting regressor, an ensemble learning technique, is utilized to correct the residuals in nuclear mass excess across six different nuclear mass models. The corrected residuals are substantially reduced and further improved by applying a weighted averaging method, which benefits from partial error cancellation among the models. Our proposed conflated model, combining ensemble learning with model averaging (ELMA), achieves a root mean square error (RMSE) of approximately 57 keV, well below the critical threshold of 100 keV, for the full dataset of the Atomic Mass Evaluation (AME2020). ELMA also improves predictions for nuclei beyond the training region, with the weighted ensemble reducing the RMSE by approximately 25%–45% relative to the best individual mass model on independent extrapolative datasets. The reliability of the ELMA approach is further validated through the calculation of $\alpha$-decay $Q$ values, where a clear reduction in deviations from experimental data is observed compared to individual nuclear mass model predictions. We have also compiled a mass excess and binding energy of 6300 nuclei, obtained using our framework and serves as a valuable resource for nuclear physics research and is publicly available through the ELMA web interface (https://ddnp.in/).

High-dimensional biomedical studies routinely confront three coupled obstacles: structured population heterogeneity, latent technical confounding, and representational inequity that can degrade inference for under-represented groups. We develop the model-based equitable learning framework (M-ELF), a probabilistic inference architecture that unifies (1) a hierarchical mixture of factor analyzers for subgroup-aware latent structure learning, (2) a negative-control-informed adjustment that removes latent confounding through a partitioned Gaussian conditioning argument, and (3) a spectral-entropy equity regularizer that discourages representation collapse within minority subpopulations using a normalized Vendi score. The M-ELF formulation makes explicit the assumptions required for valid deconfounding and for cross-population comparability of latent factors. The model yields a scalable variational-EM procedure that couples conjugate mixture-factor updates with differentiable spectral regularization. We establish conditions for generic identifiability (up to standard mixture label switching and random-effect rotations), derive exact confounder-elimination statements for the conditional model, and provide an ascent and stationarity analysis for the regularized algorithm. Simulations and a real breast-cancer gene-expression application illustrate that, relative to unadjusted analysis, M-ELF attenuates associations with technical confounders by up to $\sim 86\%$ while preserving factor recovery under equity regularization. In the TCGA breast-cancer data, M-ELF attained higher PAM50 subtype agreement (adjusted Rand index) and lower batch association than the specialized deconfounders RUV-2 and PEER, with the equity weight $\gamma$ mildly trading off subtype agreement against representation balance. In the model-based simulations, specialized methods can achieve higher factor recovery on individual metrics, and the equity penalty produces only modest changes in cross-population diversity. M-ELF's advantage is the unified probabilistic treatment of subgroup structure, negative-control deconfounding, and equity-aware representation, and $\gamma$ should be selected against the scientific end point.

Rydberg sensors offer a unique approach to radio-frequency (rf) detection, leveraging the high sensitivity and quantum properties of highly excited atomic states to achieve performance levels beyond classical technologies. Nonlinear responses and distortion behavior in Rydberg atom receivers are critical to evaluating and establishing performance metrics and capabilities such as spur-free dynamic range and tolerance to unwanted interfering signals. We report here on the measurement and characterization of nonlinear behavior and spurious response of a Rydberg atomic heterodyne receiver. Single-tone and two-tone testing procedures are developed and implemented for measurement of harmonic and intermodulation distortion in Rydberg atomic receivers based on multiphoton Rydberg spectroscopy and radio-frequency heterodyne signal detection and demodulation in an atomic vapor. For a predetermined set of atomic receiver parameters and rf carrier wave in the super high frequency band near-resonant to a cesium Rydberg transition, we measure and characterize atomic receiver selectivity, bandwidth, roll-off, compression point (P1dB), second-order (IP2) and third-order (IP3) intercepts, and spur-free dynamic range. Receiver intermodulation distortion is characterized for the case of an interfering signal wave applied at two frequency offsets relative to the near-resonant reference local oscillator, $\mathrm{\Delta }F/F={10}^{-4}$ at 6 dB and ${10}^{-6}$ at 22 dB single-tone bandwidths, respectively. We observe that under suitable operating conditions the atomic receiver can exhibit a suppression of harmonic and intermodulation distortion relative to that of classical receiver mixer amplifiers.

The non-Hermitian spinful Aubry-André-Harper model in the presence of Rashba-type spin-orbit coupling and a spatially varying textured magnetic field is studied. Interestingly, our analysis produces a butterfly spectral map due to the nontrivial extent of localization of the states in the spectrum. This spectral map also exhibits an asymmetric spin alignment with respect to the wings of the butterfly. Our analysis also suggests that the onset of such a spectral map is a combined effect of the non-Hermiticity, spin-orbit interaction, and the textured magnetic field.

Continuous far-field zone focusing of flexural wave is highly desirable for applications such as structural health monitoring, energy harvesting, and advanced sensing. In this work, we propose a metalens design paradigm capable of focusing flexural wave across a continuous zone in the far-field region. The metalens is based on an intelligently designed metagrating, in which each unit cell consists of two elliptical holes etched through a thin aluminum plate. Each unit is designed to deflect the incoming waves along a prescribed direction with tunable reflection phase and near-unitary reflection efficiency. The metagrating is engineered such that different unit cells direct the incident wave toward distinct subregions within the target focusing zone. When the reflection phase is uniformly maintained across the metagrating, a continuous extended focusing zone is formed through the superposition of wave beams reflected from all unit cells. This approach achieves a focusing area of approximately $2900{\lambda }^2$ in the far field, with an average intensity enhancement factor of 9.0 and an almost homogeneous intensity distribution. The compact planar architecture of the metalens not only offers a flexible and practical solution for far-field zone focusing, but also holds promise as a versatile planar component suitable for system integration.

Terahertz (THz) spectroscopy holds transformative potential for noninvasive sensing, yet characterizing individual nanoparticles in complex biological environments remains challenging due to the far-field diffraction limit. While near-field dipolar theory is well established, its application to characterizing/identifying nanoparticles immersed in complex media at THz frequencies is largely unexplored. This work utilizes numerical simulations of magneto-optical (MO) heterodimers—comprising $n$-doped indium antimonide ($\left[n\text{-InSb,}\text{GaSe}\right]$) and isotropic or birefringent particles (e.g., ${\text{SiO}}_2, \text{GaSe}$)—under counterpropagating, circularly polarized THz illumination. The analytical framework is supported by a numerical validation against full-wave simulations. We demonstrate that while far-field observables like absorption cross sections are often dominated by the MO-active particle, mechanical variables—specifically induced binding forces and spin/orbital torques—exhibit superior sensitivity for detecting “hidden” neighboring components. Because these mechanical signatures depend directly on near-field interactions, they provide higher information density regarding interparticle coupling. Key findings reveal material-specific spectral “hot spots” and “zeros” that serve as robust calibration markers even within dispersive biological surrogates. We show that the spin torque on non-MO particles is significantly modified by MO-neighbor proximity, a phenomenon controllable via static magnetic fields. While experimental implementation in complex media presents significant challenges, our results establish a theoretical roadmap for using optomechanical signatures as high-resolution detection channels for diagnostics, signal transduction, and low-energy nanocircuit control.