Antimony sulfide is an emerging phase change material for optical and electrical memory and computation elements. It has additionally been reported as a ferroelectric, with recent evidence from hysteresis in piezoresponse force microscopy. Here, we complete a rigorous set of piezoresponse force microscopy experiments on a congruently crystallized Sb2S3 glass-ceramic, where piezoelectric coupling should be forbidden in glassy Sb2S3. We replicate previous results and reveal that the behavior is absent in glassy Sb2S3 but show that the response originates primarily from non-piezoelectric contributions to the signal caused by an applied voltage. This hysteretic behavior in piezoresponse force microscopy is quite similar to some electrochemically active non-ferroelectric oxides, but uniquely, it appears here with a very clear spatial contrast that is decoupled from surface topography. This shows that the electromechanical signal reflects bulk-like properties and reveals differences in electrical behavior of crystalline and amorphous phases of Sb2S3.

Status signaling drives human behavior and the allocation of scarce resources such as mating opportunities, yet the generative mechanisms governing how specific goods, signals, or behaviors acquire prestige remain a puzzle. Classical frameworks, such as Costly Signaling Theory, treat preferences as fixed and struggle to explain how semiotic meaning changes based on context or drifts dynamically over time, occasionally reaching tipping points. In this work, we propose a computational theory of status grounded in the theory of appropriateness, positing that status symbols emerge endogenously through a feedback loop of social observation and predictive pattern completion. We validate this theory using simulations of groups of Large Language Model (LLM)-based agents in the Concordia framework. By experimentally manipulating social visibility within naturalistic agent daily routines, we demonstrate that social interactions transform functional demand into status-seeking behavior. We observe the emergence of price run-ups and positive price elasticity (Veblen effects) for both real-world luxury items and procedurally generated synthetic goods, ruling out pretraining bias as the sole driver. Furthermore, we demonstrate that "influencer" agents can drive the endogenous formation of distinct subcultures through targeted sanctioning, and find that similar social influence effects generalize to non-monetary signaling behaviors. This work provides a generative bridge between micro-level cognition and macro-level economic and sociological phenomena, offering a new methodology for forecasting how cultural conventions emerge from interaction.

Accurate band offsets are essential for predictive continuum modeling of nanostructures such as quantum wells and quantum dots formed in strained Si/Si1-xGex and Ge/Si1-xGex heterostructures. Experimental offset data for these systems remain sparse away from endpoint compositions, making composition-dependent design difficult. We use atomistic first-principles density functional theory to compute valence- and conduction-band offsets across the full range 0 <= x <= 1. Random alloying is treated with special quasirandom structures, interface lineup terms are extracted from macroscopically averaged local Kohn-Sham potentials in thick periodic superlattices, valence-band spin-orbit coupling is included through species-resolved Mulliken weights, and conduction-band edges are refined using the screened hybrid Heyd-Scuseria-Ernzerhof functional. The resulting offsets show pronounced composition nonlinearity beyond the linear models explored in previous works, agree with experimental benchmarks, and reproduce the high-Ge slope change in the relaxed-alloy band gap. Analytic fitting expressions are provided for direct use in simulations, facilitating practical design of modern quantum technology devices.

Measurements of the event-by-event correlation between elliptic flow ($v_2$) and the mean transverse momentum ($[p_{\rm T}]$) using the modified Pearson correlation coefficient $ρ(v_2^2,[p_{\rm T}])$ are reported in pp collisions at $\sqrt{s} = 13$ TeV, and in p-Pb and Pb-Pb collisions at a center-of-mass energy per nucleon pair $\sqrt{s_{\rm NN}} = 5.02$ TeV. This analysis is based on the full LHC Run 2 dataset recorded by ALICE and is performed for the first time in small collision systems with the ALICE detector. In Pb-Pb collisions, the $ρ(v_2^2,[p_{\rm T}])$ measurement shows a non-monotonic dependence on charged particle multiplicity ($N_{\rm ch}$); it first decreases and then increases with an increase in multiplicity. The decreasing trends of $ρ(v_2^2,[p_{\rm T}])$ with increasing multiplicity are also observed in p-Pb and pp collisions for the presented multiplicity range. All three systems show consistent values of $ρ(v_2^2,[p_{\rm T}])$ for $N_{\rm ch} \lesssim 80$. These measurements are also compared with theoretical model calculations, including PYTHIA, where no collectivity is generated, as well as AMPT and IP-Glasma + MUSIC + UrQMD, which produce collective effects in small systems. These comparisons offer unique insights into the origin of collectivity in small systems. They improve the understanding of the initial geometry, size, and their correlations. The comparison also allows an investigation of the role of initial momentum correlations predicted by the Color Glass Condensate framework. The new measurements could not be explained by current state-of-the-art models, offering insights into the initial stage of collisions in small systems and also imposing strong constraints on the existing theoretical models. This will significantly advance our understanding of the collective phenomena observed in small systems at the LHC.

We analyse divergent diagrams of \(k\)-fold map-germs on \((\mathbb{C}^n,0)\), for $k, n \geq 2$, associated with reflections, adapting to the complex setting the theory of folds associated with involutions on \((\mathbb{R}^n,0)\). In the complex case, a \(k\)-fold is naturally related to a cyclic group generated by a reflection, which guides the analytic classification of singularities. Under the conditions of transversality and linearity of the associated reflections, certain conditions related to the nontrivial eigenvalues appear as invariants by simultaneous conjugacy. We also provide a complete classification of pairs of transversal linear reflections and the corresponding divergent diagrams.

In this work, we introduce and study the $p$-$α$-closest-center problem ($pα$CCP), which generalizes the $p$-second-center problem, a recently emerged variant of the classical $p$-center problem. In the $pα$CCP, we are given sets of customers and potential facility locations, distances between each customer and potential facility location as well as two integers $p$ and $α$. The goal is to open facilities at $p$ of the potential facility locations, such that the maximum $α$-distance between each customer and the open facilities is minimized. The $α$-distance of a customer is defined as the sum of distances from the customer to its $α$ closest open facilities. If $α$ is one, the $pα$CCP is the $p$-center problem, and for $α$ being two, the $p$-second-center problem is obtained, for which the only existing algorithm in literature is a variable neighborhood search (VNS). We present four mixed-integer programming (MIP) formulations for the $pα$CCP, strengthen them by adding valid and optimality-preserving inequalities and conduct a polyhedral study to prove relationships between their linear programming relaxations. Moreover, we present iterative procedures for lifting some valid inequalities to improve initial lower bounds on the optimal objective function value of the $pα$CCP and characterize the best lower bounds obtainable by this iterative lifting approach. Based on our theoretical findings, we develop a branch-and-cut algorithm (B&C) to solve the $pα$CCP exactly. We improve its performance by a starting and a primal heuristic, variable fixings and separating inequalities. In our computational study, we investigate the effect of the various ingredients of our B&C on benchmark instances from related literature. Our B&C is able to prove optimality for 17 of the 40 instances from the work on the VNS heuristic.

Large language models for code have achieved strong performance across diverse software analytics tasks, yet their real-world adoption remains limited by high computational demands, slow inference speeds, significant energy consumption, and environmental impact. Knowledge distillation (KD) offers a practical solution by transferring knowledge from a large model to a smaller and more efficient model. Despite its effectiveness, recent studies show that models distilled from a single source often exhibit degraded adversarial robustness, even when robustness-aware distillation techniques are employed. These observations suggest a fundamental limitation of single-source distillation in simultaneously transferring high-quality and robust knowledge. To overcome this limitation, we propose Mixture of Experts Knowledge Distillation (MoEKD), a KD framework that leverages a Mixture of Experts (MoE) architecture to enable more effective and robust knowledge transfer from multiple specialized experts into a compact model. MoEKD decomposes the distillation process into expert and router training, aggregation of expert knowledge through a learned routing mechanism, and distillation from the aggregated knowledge. We evaluate MoEKD on the vulnerability detection task using CodeBERT and GraphCodeBERT models. Experimental results show that MoEKD not only improves adversarial robustness by up to 35.8%, but also enhances predictive performance by up to 13%, compared to state-of-the-art KD baselines, including Compressor and AVATAR. Furthermore, an ablation study demonstrates that aggregating expert knowledge enables ultra-compact models to maintain competitive performance even when their size is reduced by approximately half. Overall, these results highlight the effectiveness of multi-expert knowledge aggregation in addressing key limitations of existing single-source KD approaches.

We prove the existence of spontaneous symmetry breaking in suitably low-energy eigenstates of certain gapless and frustrated many-body quantum systems, namely symmetric quantum perturbations to classical models which exhibit spontaneous symmetry breaking of a finite group at some positive temperature. Additionally, the classical model need not be local in space, as long as it satisfies a quantum analogue of the Peierls condition. As an example of our technique, we establish robust ferromagnetism in random-bond Ising models in $d= 2$ dimensions with sufficiently biased random couplings, with weak transverse field. Our mathematical technique is based on establishing quantum bottlenecks, similar to a "many-body WKB" method for evaluating tunneling rates. Using these same methods, we provide new proofs of metastability and the slow decay of the false vacuum, applicable to gapless metastable states. Our work represents a first step towards a rigorous classification of stable gapless quantum phases.

For most chemists, Kramers' degeneracy refers to the fact that for any radical system, every potential energy surface is at least doubly degenerate (with spin up and spin down, time-reversed solutions) for all nuclear positions $\mathbf{X}$. That being said, as is well-known to the community of spin chemists, one can experimentally detect a splitting of almost every rotational energy level for a doublet system -- highlighting the fact that nuclear motion breaks the spin degeneracy of such BO electronic states. Thus, as far as predicting experimental spectra, the implications of BO degeneracy are very limited unless one further includes a complete treatment of nuclear-electronic entanglement in a robust fashion; indeed, understanding radical molecules (and the degeneracy of their stationary states) can be extremely non-intuitive within the paradigm of Born-Oppenheimer potential energy surfaces. Now, as an alternative to BO theory, recent theory has suggested characterizing radical potential energy surfaces as functions of both nuclear position $\mathbf{X}$ and nuclear momentum $\mathbf{P}$, an approach which has been shown to recover a host of observables outside of BO theory, e.g., vibrational circular dichroism, Raman optical activity, and lambda doubling. Here, we show that such a technique predicts that different spin states will follow different (nondegenerate) potential energy surfaces and that the differences in these spin-dependent surfaces is quantitatively consistent with experimental spin-rotation couplings -- all without any contradiction with regard to Kramers' degeneracy. Thus, the present finding suggests there is still a great deal to learn about spin-resolved molecular reactivity, demanding a conceptual shift in our understanding of coupled spin-nuclear motion, especially in the context of chiral molecules and materials where spin-separation is known to arise.

Penrose's weak cosmic censorship conjecture asserts that spacetime singularities produced by gravitational collapse are generically hidden behind event horizons, thus preventing them from causally influencing distant observers and preserving the predictability of the exterior region. In this work, we probe this conjecture in a setup that deliberately violates one of its central assumptions - the dominant energy condition - by considering the spherical collapse of a phantom scalar field with negative energy density. In principle, such a field could produce a Schwarzschild geometry with negative mass and therefore no event horizon. Our aim is to assess whether, once the dominant energy condition is abandoned, the fully coupled evolution of matter and geometry can dynamically generate or expose naked singularities, thereby probing the robustness of cosmic censorship. To this end, we perform high-accuracy numerical relativity simulations based on fourth-order finite-difference schemes. Starting from smooth, asymptotically flat initial data representing regular phantom scalar wave packets, we follow their fully nonlinear evolution through collapse or dispersion. While an ordinary (positive-energy) scalar field exhibits the standard Choptuik critical behavior at the threshold of black-hole formation, the phantom field displays qualitatively different dynamics. For all amplitudes considered, we find no evidence for trapped surfaces, naked singularities, or alternative stationary end states. Instead, the phantom scalar field always disperses, suggesting that cosmic censorship remains dynamically preserved even in the presence of negative-energy matter.

While the superposition of quantum evolutions is known to produce interference effects, the interference between evolutions with regular and chaotic classical limits remains largely unexplored. Here, we use a Mach-Zehnder interferometer to investigate the superposition of two quantum evolutions, implemented via post-selection, and to compare it with the corresponding classical mixture. The quantum kicked top provides a natural platform for this study, as its classical dynamics ranges from regular to mixed to fully chaotic depending on the Hamiltonian parameters. We show that when a regular evolution is superposed with a chaotic one, the resulting subsystem entropy can exceed that of the classical mixture, provided the contribution of the chaotic branch dominates in the superposed quantum evolution. We further demonstrate that entropy production in such superpositions is strongly influenced by the structure of the underlying classical phase space. We further show that increased entropy generation can occur for purely regular dynamics at small values of the chaos parameter, given an appropriate choice of post-selection. These results reveal a nontrivial interplay between classical chaos and quantum interference in superposed quantum dynamics

We investigate the impact of spatial curvature, $Ω_k$, and dynamical dark energy on the cosmological constraints of the neutrino mass sum, $\sum m_ν$. Using a joint analysis of the latest CMB (Planck and ACT DR6), BAO (DESI DR2) and SNe Ia (DESY5 and DES-Dovekie) datasets, we perform an exploration of the neutrino mass parameter space. To mitigate prior-driven biases near the physical boundary, we implement a symmetric extension wrapper that allows for effective negative masses. We find that the inclusion of spatial curvature significantly modifies the posterior distributions, exhibiting a smooth transition across the $\sum m_ν= 0$ threshold. In the $Λ$CDM + $Ω_k$ + $\sum m_{ν,\mathrm{eff}}$ framework, we obtain $\sum m_{ν,\mathrm{eff}} = -0.011^{+0.052}_{-0.050}$, reducing the tension with the terrestrial lower limit of 0.06 eV from $2.59σ$ for the $Λ$CDM + $\sum m_{ν,\mathrm{eff}}$ model to $1.17σ$. For the most flexible scenario $w_0 w_a$CDM + $Ω_k$ + $\sum m_{ν,\mathrm{eff}}$, we find $\sum m_{ν,\mathrm{eff}} = -0.07 \pm 0.11$ with a tension of $1.13σ$, illustrating how the increased parameter freedom notably degrades the precision of the mass estimate compared to simpler extensions. Our results demonstrate that current cosmological bounds on $\sum m_ν$ are heavily influenced by boundary effects and geometric degeneracies.

We consider the problem of estimating the missing mass, partition function or evidence and its probability distribution in the case that for each sample point in the discrete sample space its (unnormalized) probability mass is revealed. Estimating the missing mass or partition function (evidence) is a well-studied problem for which, in different contexts, the harmonic mean estimator and the Good-Turing (and related) estimators are available. For sampling on a discrete set with revealed probability masses these estimators can be Rao-Blackwellized, leading to self-consistent estimators not involving an auxiliary distribution with known total mass. For the case of sampling from a mixture distribution this offers the perspective of anchoring the estimator at both ends: at the diffuse end (high temperature in statistical physics) via an explicit expression for the total probability mass and at the peaked end (low temperature) via the feature of repeated entries in the sample. Estimation is model-free, but to provide a probability distribution for the missing mass or partition function a model is needed for the distribution of mass. We present one such model, identify sufficient reduced statistics, and analyze the model in various ways -- Bayesian, profile likelihood, maximum likelihood and moment matching -- with the objective of eliminating the mathematical (nuisance) parameters for a final expression in terms of the observed data. The most satisfactory (explicit and transparent) result is obtained by a mixed method that combines Bayesian marginalization or profile likelihood optimization for all but one of the parameters with plain maximum likelihood optimization of the final parameter.

The brief (10 nanoseconds) transient radio emission from cosmic ray air showers carries key information about the energy and mass composition of high energy cosmic rays, but anthropogenic radio frequency interference has historically prevented radio-based cosmic ray studies from being carried out independently from other types of detectors. We describe a cosmic ray detection system for the Owens Valley Radio Observatory Long Wavelength Array that searches for radio emission from cosmic ray air showers without relying on an external trigger, and runs alongside the other observing modes of the array. The OVRO-LWA, located in Eastern California, recently completed an expansion to 352 dual-polarization antennas and new signal processing infrastructure. In order to detect cosmic rays in the presence of radio frequency interference (RFI), initial event classification and RFI rejection is performed on Field Programmable Gate Array boards, which each process a sampled voltage timeseries from both polarizations of a subarray of 32 antennas. Each board uses dedicated RFI veto antennas outside the air shower radio footprint to reject RFI events. We present the trigger design, RFI flagging strategy, and candidate cosmic rays.

Objective estimators of multimedia quality are often judged by comparing estimates with subjective "truth data," most often via Pearson correlation coefficient (PCC) or mean-squared error (MSE). But subjective test results contain noise, so striving for a PCC of 1.0 or an MSE of 0.0 is neither realistic nor repeatable. Numerous efforts have been made to acknowledge and appropriately accommodate subjective test noise in objective-subjective comparisons, typically resulting in new analysis frameworks and figures-of-merit. We take a different approach. By making only basic assumptions, we derive bounds on PCC and MSE that can be expected for a subjective test. Consistent with intuition, these bounds are functions of subjective vote variance. When a subjective test includes vote variance information, the calculation of the bounds is easy, and in this case we say the resulting bounds are "fully data-driven." We provide two options for calculating bounds in cases where vote variance information is not available. One option is to use vote variance information from other subjective tests that do provide such information, and the second option is to use a model for subjective votes. Thus we introduce a binomial-based model for subjective votes (BinoVotes) that naturally leads to a mean opinion score (MOS) model, named BinoMOS, with multiple unique desirable properties. BinoMOS reproduces the discrete nature of MOS values and its dependence on the number of votes per file. This modeling provides vote variance information required by the PCC and MSE bounds and we compare this modeling with data from 18 subjective tests. The modeling yields PCC and MSE bounds that agree very well with those found from the data directly. These results allow one to set expectations for the PCC and MSE that might be achieved for any subjective test, even those where vote variance information is not available.

This paper presents the measurement of $π^{\pm}$, K$^{\pm}$, and p($\bar{\text{p}}$) production in high-multiplicity proton-proton collisions at $\sqrt{s} = 13$ TeV at midrapidity ($|y| < 0.5$) using the ALICE detector at the LHC. The transverse-momentum ($p_{\rm T}$) spectra of these particles are reported for three high-multiplicity classes. The results show a mass- and multiplicity-dependent hardening of the $p_{\rm T}$ spectra and an enhancement of the p/$π$ ratio at intermediate $p_{\rm T}$. These features are similar to those observed in heavy-ion collisions, where quark-gluon plasma formation is expected. The new measurements have extended the highest average charged-particle multiplicity density per unit of pseudorapidity achieved in pp collisions, roughly a factor five higher than that in average inelastic pp collisions, thereby reducing the multiplicity gap between small and large collision systems. In addition, the results are further compared with previously published measurements and with model calculations obtained using distinct tunes of the PYTHIA 8 Monte Carlo generator, as well as with predictions from the EPOS4. The comparison of the $p_{\rm T}$-integrated K/$π$ and p/$π$ ratios across different collision systems and energies suggests that particle production scales with charged-particle multiplicity, rather than with collision energy or system size. While the PYTHIA 8 tunes and the EPOS4 model are able to reproduce some of these measurements, either quantitatively or qualitatively, none of them consistently describes all observed features of the data.

We introduce jacobian graphs, which are explicit families of regular graphs that are spectrally indistinguishable from random graphs, but whose local structure is very different from that of random graphs. The construction relies on the geometric properties of generalized jacobians of curves and on general equidistribution theorems for character sums over finite fields.

Given a correlation generated by a (possibly quantum) communication network, we study the amount of shared randomness required to generate it. We develop a novel upper bound for approximating distributions generated by arbitrary networks and showcase instances where it significantly outperforms the best-known upper bounds for the exact case. This demonstrates that one can have substantial savings in resources if small perturbations are acceptable. We derive our bound using Hoeffding's inequality and apply it to various commonly-used communication networks such as the Bell scenario and triangle scenario.

The global 21-cm signal provides a powerful probe of early-Universe astrophysics, but its detection is hindered by Galactic foregrounds that are orders of magnitude brighter than the signal and distortions introduced by beam chromaticity. These challenges require accurate foreground modelling, rigorous Bayesian model comparison, and robust validation frameworks. In this work, we substantially accelerate global 21-cm inference by exploiting GPU architectures, enabling likelihood evaluations to achieve near-constant wall-clock time across a wide range of model dimensionalities and data volumes. Combined with algorithmic parallelisation of Nested Sampling, this reduces the total inference runtime of this work from hundreds of CPU-years to approximately two GPU-days, corresponding to a cost reduction of over two orders of magnitude. Leveraging this capability, we advance the physically motivated forward-modelling approach, in which foregrounds are represented by a discrete set of sky regions by introducing a novel, observation-dependent sky-partitioning scheme that defines regions using the antenna beam-convolved sky power of a given observing window. We show that this scheme improves modelling performance in three ways: firstly, by enforcing a strictly nested region hierarchy that enables clear identification of the Occam penalty in the Bayesian evidence, facilitating principled optimisation of model complexity; secondly, by enabling more accurate recovery of spatially varying spectral indices, with posterior estimates centred within physically plausible ranges; and thirdly, by allowing complex foregrounds to be modelled for robust global 21-cm signal inference using substantially fewer parameters. Overall, this approach achieves validated recovery at lower region counts, corresponding to an approximate 40% reduction in foreground-model dimensionality.

The MAMBO mock galaxy catalogue, based on the Millennium Simulation with empirically assigned galaxy properties, provides predictions of FIR fluxes and physical parameters of Euclid-detectable galaxies. Predicted FIR flux distributions confirm that only the brightest Euclid sources will be detectable in existing FIR surveys. We employ stacking to measure the mean dust properties as a function of stellar mass and redshift. We find dust temperatures and infrared luminosities increase with redshift across all mass bins, while dust masses remain roughly constant. FIR number counts from MAMBO show overall good agreement with observations, and the total infrared luminosity function reproduces published estimates across most redshift ranges, extending to z~10. Comparing the Euclid Wide and Deep Surveys, we find that the EDS recovers the total IRLF to fainter luminosities and higher redshifts (up to z~6 in $I_E$), although its detectability falls below 80% at z>4, whereas the EWS becomes strongly incomplete beyond z~2. We also examine the dependence of the IRLF on environment. Schechter fits indicate that the faint-end slope $α$ flattens with redshift for cluster and protocluster galaxies, while remaining approximately constant for field populations. Imposing additional detection limits from Herschel-PACS and SPIRE shows that only the most luminous ($L_{IR}$ > $10^{12.5}$ $L_{\odot}$) galaxies remain detectable at z~4, but the limited MAMBO area (3.14$deg^2$) is inadequate for statistically robust (>3$σ$) constraints. Survey areas at least 30 times larger are required. Overall, the MAMBO FIR extension reproduces key number count and IRLF trends, provides realistic predictions for FIR-detected Euclid galaxies, and highlights the importance of synergies with current and future FIR/sub-mm facilities to probe environmental dependence with sufficient depth and area.

Axion dark matter (DM) is predicted to convert into radio waves in neutron star magnetospheres. We assess the detectability of this signal using a 5 m radio telescope to be installed at the Fan Mountain Observatory, operating in the UHF, L- and S-bands from 0.5 to 4~GHz. We demonstrate that such a telescope can search new parameter space for axion-like particles over a broad range from $2\,μ\text{eV}<m_a<17\,μ\text{eV}$ for axion-photon couplings $g_{aγγ} \gtrsim 2\times 10^{-12}\text{ GeV}^{-1}$ with a three year observing period assuming the standard halo model -- improving neutron star observations by more than an order of magnitude. The search is broadband and is thus complementary to other techniques in the same frequency range. We describe in detail our neutron star population model, noise model, and proposed observing strategy. Most constraining power comes from neutron stars at the Galactic centre, where the smooth DM halo is densest. If a DM spike exists at the Galactic centre, the search is sensitive in the QCD axion model band. UHF and L-band observations (0.5 to 2~GHz) represent the pathfinder phase of a wider program we call ``Axion Search with Telescope for Radio Astronomy'' (ASTRA). Future higher mass searches aimed at discovery potential for the post-inflation axion require further hardware development to cover S, C, X and Ku bands (2 to 18~GHz).

Cops and Robbers is a pursuit-evasion game played on graphs, of which many variants have been developed and studied. We introduce a variant of this game, "Sneaky-Active Cops and Robbers", where all cops and robber must move on their turn, and where the robber is allowed to move onto a cop position without being captured. We show that for reflexive graphs, this game is equivalent to the classical cops and robbers and that the cop number for a graph is invariant under $\times$-homotopy equivalence. We then develop further properties of this game, computing cop numbers for a number of graph families and developing results about the behavior of categorical and box products of graphs.

This article presents a comparison of various implementations of the Lattice Discrete Particle Model (LDPM) for the numerical simulation of concrete and other heterogeneous quasibrittle materials. The comparison involves the use of transient implicit and explicit solvers and steady-state (static) solvers and implementations for Central Processing Unit (CPU) as well as Graphics Processing Unit (GPU). The various implementations are compared on the basis of a set of benchmarks tests describing behaviors of increasing computational complexity. They include elastic vibrations, confined strain-hardening compressive response, tensile fracture, and unconfined strain-softening compressive response. Metrics of interest extracted from the simulations include macroscopic stress versus strain responses, computational times, number of iterations, and energy balance error. Pairwise comparison of final crack patterns is provided through the correlation coefficient and normalized root mean square error of the crack opening vectors. Moreover, for the most numerically challenging case of unconfined compression with sliding boundary conditions, the stability of the strain-softening response is tested by perturbing the solutions as well as changing the convergence criteria and time step size. Attached to this paper is the complete input data of the benchmark tests; this will allow researchers to run the examples and compare them with their own implementations. In addition, most of the reported implementations are publicly available in open source packages.

In the early fault-tolerant regime, where quantum resources remain limited, hybrid quantum-classical strategies offer one possible route toward quantum advantage. We introduce CANOE, the Classically Assisted Non-Orthogonal Eigensolver, as such an approach, distributing Rayleigh-Ritz basis states between quantum and classical hardware. This approach leverages the expressive power of quantum states, which are costly to reproduce classically, while augmenting them with a large pool of classically generated basis states that can be incorporated at negligible computational cost. We validate this through numerical simulations of a 76-qubit chromium atom system, quantifying how each additional quantum basis state enhances ground-state representability and how the inclusion of classical states further amplifies this improvement. Such a hybrid basis framework necessarily requires an efficient protocol on quantum hardware for evaluating overlaps between quantum and classical states in the resulting generalized eigenvalue formulation. We address this by introducing a histogram-based protocol and demonstrate through numerical simulations that it can approach chemical accuracy at moderate sampling cost. To solve the resulting generalized eigenvalue problem stably, CANOE incorporates a Schur-complement-based stabilization procedure that mitigates ill-conditioning caused by linear dependencies in the hybrid basis. Taken together, these results position CANOE as a practical framework for combining limited quantum resources with expansive classical resources for early fault-tolerant quantum simulations.

The inverse Faraday effect (IFE) refers to the generation of a DC magnetization by circularly polarized light through the transfer of optical angular momentum to electronic degrees of freedom. In conducting systems, this response can arise from two microscopic channels - spin polarization of itinerant electrons and orbital magnetization generated by circulating charge currents. However, the orbital contribution to the inverse Faraday effect in spin-orbit-coupled conducting systems remains largely unexplored. We present a theoretical analysis of the IFE in disordered two-dimensional electron systems with Rashba spin-orbit coupling using both the quantum kinetic equation and Green's-function diagrammatics. We find that in a noninteracting Rashba metal the orbital magnetization is strongly modified by spin-orbit coupling and can become comparable to, or exceed, the spin magnetization for realistic parameter regimes. When the radiation frequency approaches the Rashba spin splitting, both spin and orbital magnetizations exhibit resonant enhancement. These results clarify the microscopic origin of light-induced magnetization and highlight the interplay of spin and orbital mechanisms in optically driven magnetization dynamics in low-dimensional electronic systems.

The farthest-first traversal of Gonzalez is a classical $2$-approximation algorithm for solving the $k$-center problem, but its sequential nature makes it difficult to scale to very large datasets. In this work we study the effect of running farthest-first on a $δ$-cover of the dataset rather than on the full set of points. A $δ$-cover provides a compact summary of the data in which every point lies within distance $δ$ of some selected center. We prove that if farthest-first is applied to a $δ$-cover, the resulting $k$-center radius is at most twice the optimal radius plus $δ$. In our experiments on large high-dimensional datasets, we show that restricting the input to a $δ$-cover dramatically reduces the running time of the farthest-first traversal while only modestly increasing the $k$-center radius.

Existing methods for verifying access control policies require the policy to be complete and fully determined before verification can proceed, but in practice policies are developed iteratively, composed from independently maintained components, and extended as organisational structures evolve. We introduce robust property verification: the problem of determining what a policy's structure commits it to regardless of how pending decisions are resolved and regardless of subsequent extension. We define a support judgment $\Vdash_{P}ϕ$ stating that policy $P$ has robust property $ϕ$, with connectives for implication, conjunction, disjunction, and negation, prove that it is compositional (verified properties persist under policy extension by a monotonicity theorem), and show that despite quantifying universally over all possible policy extensions the judgment reduces to proof search in a second-order logic programming language. Soundness and completeness of this reduction are established, yielding a finitary and executable verification procedure for robust security properties.

In this paper, we consider a wave equation with strong damping and logarithmic nonlinearity. This paper aims to study the local and global existence, uniqueness and the uniform energy decay rate of a weak solution under some sufficient conditions on the initial data. Unlike previous literature restricted to the lower subcritical range $2 < γ< \frac{2(n-1)}{n-2}$, we successfully extend the validity of the well-posedness and stabilization results to the upper subcritical range $\frac{2(n-1)}{n-2} \leq γ< \frac{2n}{n-2}$.

A total graph is an ordered triple $(V_0, V_1, E)$, where $V_0, V_1$ are the sets of empty and full vertices, respectively, $V_0 \cap V_1 = \emptyset$, and the set of edges $E$ is a subset of \(\binom{V_0 \cup V_1}{2}\) $(E\cap(V_0 \cup V_1)=\emptyset)$. A simple graph is a total graph in which all vertices are full. We say that a total graph $G$ is locally irregular if every two adjacent vertices have different total degrees, where by the total degree of a vertex $v$ in $G$ we mean the number of edges in $G$ that contain $v$ plus 1 if $v$ is full, or plus 0 if $v$ is empty. A total coloring of a graph $G$ whose colors induce locally irregular total subgraphs is called locally irregular total coloring, and the minimum number of colors required in such a coloring of $G$ is denoted by ${\rm tlir}(G)$. In 2015, Baudon, Bensmail, Przybyło, and Woźniak conjectured that ${\rm tlir}(G)\leq 2$ for every graph $G$. In this paper, we prove this conjecture for cacti, subcubic graphs, and split graphs. We also provide a general upper bound for ${\rm tlir}(G)$ depending on the chromatic number of $G$, and a constant upper bound if $G$ is planar or outerplanar. In our proofs, we utilize special decompositions of graphs and the connection between acyclic vertex coloring and locally irregular total coloring.

We theoretically investigate a readout scheme of the quantum state of a superconducting qubit based on time delay of a single flux quantum (SFQ), also known as a fluxon, propagating in a Josephson transmission line (JTL). We concretely study the time-delay readout based on capacitive coupling between a transmon qubit and a JTL, and we evaluate the time delay depending on the qubit state. We also reveal a feature of the absence of fluxon pinning and exponential suppression of nonadiabatic transitions caused by the propagating fluxon, which is advantageous for the time-delay readout. We extend the analysis to a multi-level transmon as well. Owing to the spectral gap in the JTL, the radiative decay of the qubit mediated by the JTL is exponentially suppressed, and thus the transmission line itself also serves as a filter protecting the qubit. The readout scheme requires neither complicated wiring to low-temperature stages nor bulky microwave components, which are bottlenecks for integration of a large-scale superconducting quantum computer.