Papers

Variational quantum algorithms such as VQE and VQD are promising for near-term electronic structure calculations, but for periodic solids their reach is limited by the cost of building a faithful second-quantized Hamiltonian, typically via DFT plus Wannierization or hand-fit tight-binding parameters. SlaKoNet addresses this by combining deep learning with the Slater-Koster tight-binding formalism to fit hopping and overlap parameters across 65 elements, enabling deterministic Hamiltonian construction for any crystal built from these elements. Here we couple a SlaKoNet model trained on JARVIS-TBmBJ with a Qiskit-based VQD algorithm, replacing costly Hamiltonian construction with a universal neural Hamiltonian generator. The resulting SlaKoNet-VQD workflow is structure-agnostic, differentiable, and suited to high-throughput bandstructure screening. We benchmark on silicon, recovering the full eight-band structure along the standard k-path with mean absolute deviation of 1.78 meV from exact diagonalization on a 3-qubit simulator, and extend to five conventional superconductors (Al, Ta, Nb, V, ZrN) with similar accuracy. We demonstrate execution on IBM Quantum hardware for a k-point ground-state calculation on aluminum (MAE ~0.37 eV). We further promote the Hamiltonian to a correlated Hubbard model solved via dynamical mean-field theory, recovering weakening correlations across group-5 metals and strong quasiparticle renormalization in La2CuO4, identifying the impurity problem as a natural quantum solver target. This pipeline enables high-throughput VQA benchmarking across the periodic table and gradient-based ansatz-Hamiltonian co-optimization for materials discovery. Web app: https://atomgpt.org/quantum.

We investigate the collective dynamics of a bundle of charged particles undergoing cyclotron motion in a uniform magnetic field when subjected to a short-duration electric pulse. Using the geometric framework based on the evolution of trajectory congruences, we analyze how the pulse affects the expansion, shear, and rotation of a small family of trajectories. We show that the geometric imprint persists after the pulse has vanished, manifesting as a memory of the transient perturbation. Unlike gravitational memory effects, this does not manifest itself in focusing behaviour of the trajectories, and instead implies a restructuring of the shear component before and after the pulse. We offer direct analytic and regression based arguments for the same.

Animals navigating complex vertical environments must secure stable footholds, a challenge for species without feet. While arboreal climbing has evolved repeatedly in snakes, the physical mechanisms they use to scale broad, nearly flat surfaces remain poorly understood. By measuring three-dimensional body kinematics and per-contact forces on a smooth vertical wall with protruding posts, we show that cornsnakes climb by dynamically balancing forces across a highly redundant network of 5 to 16 simultaneous contacts–far exceeding the three contacts minimally required for physical stability. Using a computational model and a robotic climber, we demonstrate that while simple body undulations and passive friction are mechanically sufficient to climb this terrain, snakes systematically deviate from this passive baseline. While downward climbing relies primarily on friction, ascending snakes actively generate positive mechanical work at their contacts to propel themselves. Furthermore, we found that whenever a snake engages a new contact, it triggers a stereotyped, system-wide redistribution of force that seamlessly integrates the new foothold without disrupting whole-body balance. These results reveal how a continuous, flexible body can transform sparse environmental features into a robust, fault-tolerant network. This mechanism provides a biomechanical framework for understanding the repeated evolution of limbless climbing and offers physical principles for designing agile robots for unstructured terrain.

Rapidly scaling autonomous science is limited not only by algorithms, compute or data volume, but by which physical records a platform exposes before action. We formulate physically accessible decision-making (PADM) and a measurement-access risk frontier: the Bayes-optimal target risk minimized over records realizable under cost, bandwidth, latency, disturbance, memory and actuation constraints. The frontier gives a no-free-autonomy limit: automation cannot collapse decision uncertainty by computation alone; an optimal controller cannot remove target components absent from its record, and closing that gap requires expanded access, auditing, tolerated disturbance, slower operation or restricted deployment. In monitored feedback, displacement-only control remains exposed to a hidden switching force, whereas a finite-bandwidth cue recovers part of the missing projection before action. A chemistry-aware candidate-ranking audit with a 1000-target stress panel, Gaussian sensing, hidden-regime decisions and cost-aware/thermodynamic channel selection provide reproducible checks. PADM identifies target-specific audit value and residual oracle gaps before deployment.

We extend the persistent homology analysis of~\paperone{} to the full Roman–Byzantine trade network (0–1453\,ce), using 2{,}599 nodes and 4{,}503 trimodal edges calibrated against the orbis Geospatial Network Model. Five results are reported. % (i)~The $H_t{=}0$ western sub-network result of~\paperone{} is a data-coverage artifact: with full western representation ($N_{\rm west}=987$, $\beta_1\approx52$ cycles per decade) a baseline East–West entropy gap of $+2.22$ units is present from 0\,ce and grows at $+3.3\times10^{-3}$\,yr$^{-1}$, predating the Theodosian partition by four centuries. % (ii)~A hub-selection artifact in degree-heterogeneous networks can reverse the sign of the inferred Phase~III slope, requiring full-coverage or stratified sampling for reliable structural-break detection. % (iii)~Decomposing Byzantine resilience into geographic ($H_{\rm geo}$) and economic ($H_{\rm eco}$) components reveals a peak decoupling ratio $R_d = H_{\rm eco}/H_{\rm geo} = 47.7$ at 620\,ce, falling to 13.9 at 640\,ce, quantifying the McCormick–Ward-Perkins historiographical debate as a contrast between two network layers operating on different timescales. % (iv)~The inter-decade $W_2$ Wasserstein velocity identifies the Late Roman–Early Byzantine transition (495\,ce) as the highest topological-velocity event of the 1,453-year record; the cross-network Wasserstein ratio increases by $150$–$300\times$ after the Chrysobull of 1082\,ce, providing an independent diagram-space analogue of $R_d$. Both the Western collapse (476\,ce) and the Byzantine endpoint (1453\,ce) occur at $H^{\ast}\approx0.524$, interpreted as a candidate topological percolation threshold.

We study products of independent Haar matrices interspersed with a fixed corank-one projection. As the matrix dimension $N$ and product length $L$ grow with $L/N\to\tau$, we prove that the empirical distribution of squared singular values converges to the free multiplicative Poisson law with $S$-transform $S(z)=\exp(\tau/(1+z))$, for both the unitary and orthogonal ensembles. Lagrange inversion yields its moments explicitly, proving Beenakker's conjectured Erlang formula for every moment order.

Efficient concentration and transport of electromagnetic energy through electromagnetically thick structures often requires resonant phenomenon and careful design considerations. Here, we introduce a realistic non-resonant approach based on electromagnetically thick self-dual metasurfaces that can funnel electromagnetic waves through subwavelength regions and without requiring magnetic materials. By satisfying the self-duality condition, the proposed metasurfaces support impedance-matched propagation and enable reflectionless energy transfer regardless of the metasurface thickness or structural details. This mechanism also allows selected control over the internal field while maintaining reasonable operational bandwidth. Metasurface elements are designed individually, and full-wave simulations confirm the predicted behavior in sample representative cases. The proposed framework provides a general strategy for robust electromagnetic energy routing and confinement, with potential impact in nonlinear optics, sensing and particle manipulation, near-field imaging, advanced absorber technologies, and wide-angle antenna systems.

We extend recent work on the relation between classical surface theory and partial differential equations, focusing on equations of pseudo-spherical type in the sense of Chern–Tenenblat and on a non-trivial generalization motivated by the Lund–Regge system describing surfaces immersed in $S^3$. As our main application, we study a generalized Konno–Oono system with three dependent variables introduced in a previous paper by one of the authors. We construct an associated parameter-dependent overdetermined linear problem and we establish the existence of infinitely many non-trivial local conservation laws, hence, integrability. The latter is the most technically demanding part of this paper: it requires a refined analysis of a Riccati pseudo-potential expansion, the use of stereographic coordinates at the full equation manifold level, the construction of special representatives, and a direct proof of non-triviality in horizontal cohomology. We also analyse an illustrative class of travelling wave solutions and show that they can be used to generate surfaces immersed in $S^3$ whose Gaussian curvature changes sign periodically, while their mean curvature are non-vanishing periodic functions. In a limit case, we obtain surfaces that are locally congruent to generalized Clifford tori.

Despite riddles, mysteries, and enigmas the theory of elementary particles has not changed for 50 years. We argue that the current paradigm – Wilsonian quantum field theory – is inadequate for resolving the puzzles, and should be replaced by a new paradigm based on the Holographic Principle. We show how a simplified but still very rich standard model emerges from de Sitter holography in the flat-space limit and explain why the puzzle of huge quantum corrections to the cosmological constant simply does not occur in the holographic paradigm.

In the USA, periodontal diseases, a spectrum of inflammatory conditions, affect 4 out of 10 adults (>=30 years). Current standards of care in clinical assessment of these diseases are invasive, subjective, only semi-quantitative, and primarily detecting later stages. Applications of ultrasonography in periodontology has been emerging in recent years. Despite such growing interest, Quantitative ultrasound (QUS) approaches remain largely unexplored and their utility for longitudinal characterization of oral inflammation has yet to be established. Here, we present one of the early investigations into the potential of QUS techniques for inflammation monitoring. In a staggered study involving a pig cohort (N=8), interdental gingival tissues at three interproximal oral sites from four quadrants were enrolled. The study involved baseline and five inflammation timepoints. Inflammation was induced using two complementary approaches at each site. Two QUS parameters of attenuation coefficient slope (ACS) and backscatter intensity (BSI) were investigated. Sex and oral sites were also used to stratify the longitudinal QUS estimates with inflammation. Results showed that both ACS and BSI were statistically significant from the healthy baseline across all oral sites at week 2 and|or 4 (combined sexes). Overall, inflammation inoculation was associated with a decrease in ACS and an increase in BSI. For BSI, week4 and/or week 2 remained statistically significant across males and females at all oral sites. ACS variations were spread across oral sites and sexes, with PM4-Dis as overall non-significant. The 2D classification (baseline from week 2) accuracy, were 92%, 82%, and 74.2% for M1-Dis, PM4-Dis, and PM3-Dis, respectively This study is among early implementation of QUS approaches for periodontal inflammation characterization.

Three groups of 32 ultrahigh-entropy compositionally complex ceramics (CCCs) containing 16-19 components were synthesized and characterized. The first group of 15 CCCs forms single ultrahigh-entropy fluorite or pyrochlore phases in 12 compositions, while two compositions exhibit fluorite-fluorite dual phases, observed for the first time. Compared with ternary A2B2O7 pyrochlore, these ultrahigh-entropy CCCs are more prone to ordering (pyrochlore formation), surprisingly even more at higher size disorder (more lattice distortion), with suppressed dual-phase formation relative to five-component high-entropy ceramics. Two new 19-component series, denoted as "19CCC-P|Fy" and "19CCC-P|Fz", form single ultrahigh-entropy fluorite or pyrochlore phases. The 19CCC-P|Fy series, maintaining a 2:2 ratio of 3+ and 4+ cations, exhibits a pyrochlore-to-fluorite order-disorder transition (ODT) at y ~ 0.84, consistent with the linear projection of the pyrochlore superstructure peak intensity as an order parameter. In contrast, the 19CCC-P|Fz series with non-2:2 ratios of 3+ and 4+ cations show an abrupt ODT at z ~ 0.41-0.44, despite a projected transition at z ~ 0.64 from the order parameter.

We investigate the thermodynamic microstructure, quasinormal mode spectrum, and greybody factors of the exact, static, spherically symmetric black hole in Einstein-Skyrme theory, building on the recently established first law that promotes the Skyrme couplings K and {\lambda} to extensive variables. Using Ruppeiner geometry, we construct the scalar curvature from the Hessian of the mass. The curvature remains finite at the second-order (heat-capacity) phase transition but diverges in the extremal, zero-temperature limit. Throughout the physically admissible region the curvature retains a single sign, indicating microscopic interactions of one dominant (attractive) type whose strength grows towards extremality. We perform a Joule-Thomson-like isenthalpic expansion and prove analytically that the corresponding coefficient is strictly negative across the entire physical parameter space, implying the black hole always cools as {\lambda} increases at a fixed mass, with no inversion temperature. Turning to perturbations, we derive the effective potential for massless scalar fields. The solid-angle-deficit coupling K controls its shape-substantially lowering the barrier-while at fixed K the quartic coupling {\lambda} produces only minor changes. Rigorous lower bounds on greybody factors are obtained in closed form using Visser's method: increasing K raises the bound, since a larger horizon lowers the centrifugal barrier, whereas increasing {\lambda} mildly suppresses low-frequency transmission. Our results provide the first comprehensive study of the thermodynamic microstructure and perturbative spectroscopy of this rare analytic hairy black hole, complementing and extending the existing thermodynamic analysis into previously unexplored territory.

More than 80 years ago Kramers published a paper calculating how fast a Brownian particle escapes from a potential well over an activation barrier. Since then Kramers' model has been widely adopted by nuclear physics, biophysics and chemical physics communities as a description of activated barrier crossing. From a chemical kinetics perspective, Kramers' theory provides a mapping from continuous dynamics to discrete-state chemical kinetics. Motivated by recent developments, this Perspective provides a rigorous way of performing such a mapping, explaining why and how Kramers' theory works from several points of view. Specifically, we consider transitions of a Brownian particle between two potential wells corresponding to the “reactant” and the “product” of a chemical reaction. A central unifying idea is to divide the equilibrium ensemble of possible states of the system into two sub-ensembles corresponding to the reactant and product states and then to consider fluxes between these sub-ensembles. Importantly, naive separation based on the location measured relative to the barrier top does not result in a mapping that is physically tenable, and instead the past of the trajectory should be considered. Thus constructed reactant and product ensembles provide an internally consistent description of the problem when also viewed from two different perspectives: one based on the definition of the rate as a conditional transition probability per unit time and the other based on the relaxation modes of the time-evolution operator governing the dynamics.

Multiphysics simulation with lattice Boltzmann methods (LBM) requires a scheme hand-derived for each partial differential equation (PDE), a labor-intensive, error-prone bottleneck. We recognize our recently proposed class of LBM schemes as a discrete-kinetic relaxation approximation of conservation laws and generalize its hand derivation to an automated one for systems of hyperbolic, parabolic, and mixed-type conservation laws. The derivation splits into three steps: First, the PDE system is equivalently rearranged into a first-order cascade of conservation laws: every spatial derivative in flux or source becomes an auxiliary variable, recursively for higher derivatives, so all fluxes are algebraic and updates stay local. Second, the augmented system is approximated by a discrete-velocity kinetic relaxation model with linear, constant-coefficient transport: all nonlinearity resides in a local equilibrium embedding the flux exactly in its first moment, trading the low-Mach truncation for an a priori checkable sub-characteristic wave-speed bound. Third, the relaxation system is discretized by a standard LBM, yielding collide-and-stream algorithms running unchanged on existing solvers. A symbolic compiler using a domain-specific language encapsulates these steps: unlike existing LBM code generators, which start from the discrete scheme, it automatically derives equilibrium, gradient-tracking cascade, and grid scaling from the declared PDE alone. We exercise it across twelve PDE systems, including compressible Navier–Stokes–Fourier flow, resistive magnetohydrodynamics, and nonlinear elasticity. Manufactured-solution verification confirms convergence at or near second order in double precision, retained in single precision by a reference- and equilibrium-shifted formulation. Targeting OpenLB, the generated GPU kernels reach up to 96% of the memory-bandwidth roofline.

We consider the dynamics of inertial particles in unsteady fluid flows. At low Reynolds numbers, where the drag force is linear in the relative velocity, it is well-known that the dynamics admit an attracting, invariant, slow manifold which emerges as the perturbation of a normally hyperbolic critical manifold. However, at high Reynolds numbers, where the drag force is quadratic in the relative velocity, the critical manifold is no longer normally hyperbolic, and therefore its persistence has remained an open problem. Here, we resolve this issue by a particular application of the blowup method, which transforms the equations of motion to a generalized weighted cylindrical coordinate system, thereby desingularizing the dynamics on the critical manifold. We subsequently prove that the critical manifold persists under sufficiently small perturbations and derive the reduced equations of motion on the perturbed slow manifold to arbitrary accuracy. Our reduced equation differs from its linear-drag counterpart in its asymptotic expansion as well as its convergence rate. Using two examples, we demonstrate the validity of our slow manifold reduction. We also showcase an application of the reduced equations to the problem of source inversion in a turbulent dispersion model.

In this work, we investigate the relationship between quantum coherence and multiparameter quantum estimation in a graphene-based system. We focus on the estimation of two relevant physical parameters, namely the temperature $T$ and the wave vector $k_x$, and analyze how their variations affect both quantum coherence and the achievable metrological precision. The minimum variances associated with the estimation process are evaluated through the quantum Cramér–Rao bound within both simultaneous and independent estimation schemes. Our results show that quantum coherence is enhanced in the low-temperature regime and around $k_x=0$, while it decreases progressively as either the temperature or the wave vector increases. However, the regions where coherence is maximal do not necessarily coincide with those of optimal estimation precision. In particular, the variance associated with temperature estimation exhibits a divergent behavior near $T=0$, indicating that the system becomes weakly sensitive to small temperature variations in this regime. By contrast, the estimation of the wave vector $k_x$ is more directly related to the coherence properties of the system, with improved precision obtained near $k_x=0$. Furthermore, we introduce the ratio $\Gamma$ to compare the total variances obtained from the independent and simultaneous estimation schemes. This quantity provides a useful measure of the relative difference between the two strategies when the parameters are estimated separately or jointly.

Global Navigation Satellite Systems (GNSS), best known for positioning, also serve weather science, as atmospheric water vapour delays their signals. This delay, the Zenith Wet Delay (ZWD), is a direct, all-weather measure of column moisture. Although assimilated into numerical weather prediction for decades, ZWD is not yet used by leading Machine Learning Weather Models (MLWM), despite addressing a known deficiency: the underestimation of severe precipitation. Here we present the first integration of GNSS-derived ZWD into Aurora, a state-of-the-art weather foundation model. Our extended Aurora learns ZWD with skill comparable to its pretrained variables. More importantly, including ZWD systematically improves forecasts when fine-tuning for 6-hour accumulated precipitation. Gains grow with severity, reaching an 8.8% increase in Equitable Threat Score at the 99th percentile, while the precipitation power spectrum becomes more realistic at synoptic and planetary scales. GNSS observations therefore encode information that MLWM can exploit for high-impact precipitation.

The integration kernels for polylogarithm functions on a compact Riemann surface of arbitrary genus $h$ are shown to close as the surface undergoes a non-separating degeneration to one of genus $h{-}1$. Explicit formulas are obtained for the non-separating degeneration of the multivariable Enriquez connection for genus $h$ with an arbitrary number of variables to the Enriquez connection for genus $h{-}1$ with two additional punctures whose Lie algebra generators are related to the original ones by the characteristic Bernoulli generating functions known from the degeneration at $h=1$. Analogous degeneration formulas are obtained for the single-valued DHS kernels at the leading order in the real degeneration parameter that is adapted to relating modular tensors at genus $h$ and $h{-}1$.

For low-mass stars (M < 1.4 Msun), the connection between stellar rotation and magnetic activity governs stellar spin-down, shapes the environments of their exoplanets, and provides an age-diagnostic via magneto-gyro-chronology. Recently, unexpected phenomena known as the intermediate rotation period gap and the rotational stalling have been discovered. These are likely due to internal angular momentum redistribution, and mark departures from a smooth spin-down evolution. These features have been shown to cause enhanced magnetic activity on the photosphere, as measured by the photometric index from light curves (Sph), in both cluster and field stars. However, their influence on other magnetic activity proxies, and particularly in field stars, remains poorly understood. In this work, we study the impact of the intermediate-period gap on chromospheric magnetic activity as traced by the Ca ii infrared triplet (IRT) index. We target the stars observed by the Kepler mission, as this is the largest and most reliable sample of field stars with measured rotation periods sensitive to the gap. We calculate the Ca ii IRT index for the Kepler stars using the spectroscopic information from the Gaia mission data release three (DR3). We study the rotation-activity relation as a function of spectral type, finding that K dwarfs are more active than G dwarfs, which in turn are more active than F dwarfs. For main-sequence stars, we find that chromospheric magnetic activity is also enhanced after the intermediate-period gap, mirroring its effect on the photospheric Sph index. Our work reveals that the intermediate-period gap marks a genuine transition in stellar magnetic behavior, not only at the photosphere but also at the chromosphere. This highlights the need to account for its signatures across activity proxies, as well as its impact on exoplanet habitability and the age-rotation-activity relation.

Blind quantum computing (BQC) allows a client to delegate quantum computations to a remote server without revealing the input, computation, or output. In addition to being blind, the client can sometimes also verify that the server has performed their instructions correctly, a property known as verifiability. A key part of realizing such verifiable BQC (VBQC) is choosing the design of the client device: many architectures have been proposed, each with different hardware requirements, security properties, and performance characteristics, making it difficult to identify which is most suitable for a given implementation. In this work, we present a comparative analysis of client architectures for VBQC with a matter-qubit server. We restrict our analysis to single-server, single-client protocols with information-theoretic security based on measurement-based quantum computation. We identify three main categories of client: emission-based, measurement-based, and rotation-based, each with multiple variants depending on how the client interacts with the server. We evaluate each across different dimensions: we compare guarantees of existing corresponding security proofs, we derive equations for the rate at which each client can execute a protocol, we provide an overview of each architecture's error behaviour, and discuss hardware cost and design considerations. Client architectures implementing measurement-based remote state preparation and reflection-based teleportation emerge as strong default candidates, but as the right choice remains context-dependent, we provide a framework for navigating considerations to guide the selection of the most suitable architecture for a given setting.

Natural supersymmetry (SUSY) models remain viable even in the face of LHC Run 2 sparticle search limits. However, the LZ experiment has placed strong limits on light higgsino dark matter even when the higgsinos carry only their thermally-produced abundance, with the bulk of the dark matter composed of axions. One way out is the possibility of WIMP direct detection blind spots where cancellations in direct detection (DD) couplings lead to tiny DD rates. We examine natural SUSY models with mu <0 and \mu >0 but find that the surviving blind spots all lie in the unnatural region where the superpotential |mu | parameter is much greater than the weak scale gaugino masses; the few natural candidates are excluded by LHC soft-dilepton searches and by the measured Higgs mass. Within NUHM2/NUHM3-type gravity-mediated models with positive gaugino masses and assuming a thermally produced neutralino fractional abundance, direct-detection blind spots do not rescue stable light higgsino dark matter in the electroweak-natural region. Thus, within this framework, stable light higgsino dark matter is disfavored, although special circumstances like large entropy dilution of all relics is still possible. This points to SUSY models with unstable light higgsinos as perhaps the preferred alternative.

Shell structure in finite quantum systems gives rise to sudden changes in observable properties, while pairing correlations often compete against such discontinuities. The region near the doubly magic nucleus $^{132}$Sn provides a fertile ground for testing the combined effect of shell structure and pairing. Here, we provide a novel phenomenological interpretation of existing mass data in the vicinity of the $Z=50$ and $N=82$ shell closures, which we further investigate by performing original Hartree-Fock-Bogolyubov (HFB) mean-field calculations for even-$Z$ nuclei: we find that the proton shell structure enhances an asymmetry of the neutron odd-even staggering in binding energies. We also report mass measurements of $^{137,138}$Sb, including the first experimental mass determination of $^{138}$Sb, performed using TRIUMF's Ion Trap for Atomic and Nuclear Science (TITAN). Together with existing experimental data, our results reveal an interplay between shell structure and pairing in odd-$Z$ nuclei which is more challenging to interpret phenomenologically or using HFB, thereby motivating future experimental and theoretical pairing studies in heavy neutron-rich nuclides.

Deep-learning-based climate downscaling aims to learn relationships from historical low-resolution (LR) and high-resolution (HR) climate data to generate HR climate projections. However, this setting faces a temporal out-of-distribution (OOD) challenge: models trained on historical data are commonly applied to future projections whose distributions may differ substantially from the training period. This study investigates temporal OOD shift for daily temperature downscaling over the Continental United States using paired LR-HR model simulations. We propose a temporal domain-adaptive downscaling framework that combines supervised HR reconstruction on historical data with domain alignment between historical and future climate distributions. Experiments across future validation periods show that the proposed domain-adaptive model consistently outperforms statistical and deep-learning-based bias-correction methods, with the largest gains occurring when the temporal distribution shift is strongest. Spatial analyses indicate stronger improvements over high-elevation and topographically complex regions, along with higher spatiotemporal correlation with the HR target. The extreme analysis shows that domain adaptation also reduces upper-tail temperature bias relative to the non-adaptive model. These results demonstrate that temporal domain adaptation can improve the robustness of HR climate projections under non-stationary climate conditions.

The temporal Clauser-Horne-Shimony-Holt (CHSH) inequality witnesses the nonclassicality of temporal correlations, but its violation is generally degraded by environmental noise. Here, we show that violation of the temporal CHSH inequality can be revived through coherent control of noisy quantum evolutions. We compare two physically distinct implementations: coherent control of noisy evolutions induced by interaction of the system with independent environments, and coherent control of two physically distinct, unitarily equivalent Stinespring dilations of the same noisy channel. Although these constructions generate identical deterministic system dynamics, they induce distinctly different post-selected evolutions. With a focus on the amplitude damping channel (ADC), we show that coherent control of equivalent dilations extend the range of temporal CHSH inequality violation well beyond both the incoherently controlled, or deterministic, scenario and what is achievable with independent environments. Under setting-independent post-selection of the coherent control implementation, the resulting violation further certifies that the channel is not strongly CHSH nonlocality-breaking. Our results identify the choice of Stinespring dilation as an operationally relevant resource in coherently controlled tests of temporal quantum correlations.

As quantum networks move toward practical deployment, standardized performance monitoring becomes essential. This article proposes a structured monitoring framework for quantum networks with performance metrics, including quality (e.g., entanglement fidelity, QBER, loss, dark count rate), throughput and latency (e.g., entanglement rate, waiting time), timing (e.g., coincidence window, production and coincidence jitter), and exogenous factors (e.g., temperature, humidity, vibrations). These measurements enable real-time observability, benchmarking, and control, supporting use cases such as fault diagnosis, adaptive timing, and entanglement routing. Additionally, we implement a non-invasive prototype environmental monitoring system integrated with the quantum network infrastructure at Oak Ridge National Laboratory, demonstrating practical feasibility of live data collection and alert generation. Furthermore, we discuss the challenges of real-time monitoring and the trade-offs between observability and system performance. This work establishes a foundation for developing advanced quantum network monitoring systems and lays the groundwork for future autonomous control and quantum software-defined networking.

We present the first complete analysis of nonlinear causality and local well-posedness for a very general class of bulk and shear viscous theories of relativistic transient fluid dynamics, which encompasses (i) the original Israel-Stewart theory derived from entropy-current arguments, (ii) approaches derived from kinetic theory, and (iii) resummed gradient-expansion based formulations as particular subcases. Our work establishes, for the first time, simultaneously necessary and sufficient algebraic conditions for causality, alongside sufficient conditions guaranteeing strong hyperbolicity, in the full nonlinear regime. These results are rigorously proven for both systems coupled to Einstein's equations featuring a dynamic metric and on a fixed background, with or without a cosmological constant, and include baryon conservation (in the absence of heat/diffusion currents). The conditions are purely algebraic, require no simplifying spacetime symmetry assumptions or a specific equation of state, and allow all transport coefficients to depend on the dissipative currents. We also demonstrate that the normalization, orthogonality, symmetry, and tracelessness physical constraints on the dynamical variables are properly propagated during the lifetime of the solutions. Our results provide a readily usable toolset with which one can investigate the domain of applicability of relativistic viscous fluid dynamics in numerical and phenomenological studies in heavy-ion collisions and astrophysics.

We consider random sequential adsorption (RSA) of aligned squares and derive the low-coverage expansion of the availability function alpha(q), the fraction of positions accessible to an additional square, up to fourth order in the coverage q. At low coverage, the reduction of available space can be understood in terms of geometric overlap between exclusion regions created by previously deposited squares. A single square blocks a finite area; pairs of squares may have overlapping exclusion zones, reducing the total blocked area; similarly, three and four squares can share a common overlap region, leading to higher-order corrections. These contributions can be systematically accounted for through an inclusion-exclusion expansion based on the geometry of overlapping exclusion regions, with alternating signs dictated by inclusion-exclusion. The expansion terminates exactly at fourth order, since no more than four deposited squares can simultaneously overlap the exclusion region of a trial insertion. The coefficients are obtained by explicit enumeration of all such geometrically admissible configurations and are further confirmed by numerical simulations on a discrete lattice, showing agreement within statistical uncertainty.

In this work we design a multi-layer model of composite contact lens drug release. Such lenses have been designed by encapsulating drug-polymer films in contact lens hydrogels. Composite lenses can promote sustained discharge of drug and achieve near zero-order release kinetics, thus surpassing other ocular delivery methods that are limited by short residence times and an undesirable initial burst release. Our model is informed by in vivo data, and includes three coupled partial differential equation layers to simulate the composite lens. We mathematically investigate the effect of composite contact lens design characteristics on the time to $50\%$ therapeutic drug release ($t_{50}$) in the vial, eye, and blister pack settings. In the eye setting, we incorporate our prior model that considers the effect of many blinks on the pre- and post-lens tear film drug concentrations. We simulate drug cumulative release profiles and study the variability of $t_{50}$ across: (1) the ratio of the drug-polymer film to hydrogel diffusion coefficients, (2) the centerline of the polymer film within the hydrogel, and (3) the polymer film thickness. In the blister pack setting, we study storage questions that may inform future commercial design. This work may help medical professionals better understand the mechanics of contact lens drug delivery and predict targeted tissue transport of ophthalmic drugs.

Manipulating coexisting multi-space topological states within a single material is a critical frontier for low-power spintronic applications, for which perpendicular electric-field gating offers a highly precise tuning mechanism. Using first-principles calculations and atomistic spin simulations, it is demonstrated that Janus monolayer MnBi2Se2Te2 can exhibit simultaneous momentum-space and real-space topological phase transitions under an external electric field. Specifically, the electric field drives momentum-space transitions across a topologically trivial state (C = 0), a low-Chern-number quantum anomalous Hall state (C = -1), and a high-Chern-number state (C = 2). Concurrently, by actively tuning the competition between the Dzyaloshinskii-Moriya interaction and magnetic anisotropy, the electric field induces real-space magnetic transitions from a uniform ferromagnetic state to an isolated skyrmion state, and ultimately to a skyrmion-spiral domain coexistence phase. Electric-field-induced variations in both the QAHE and magnetic textures may give rise to multiple topological phase transitions, involving distinct topological regimes: a purely k-space topology, RK-joint skyrmions, and pure real-space skyrmions. These findings establish a powerful material platform and efficient route for the synergistic control of coexisting topological orders, making it highly promising for next generation multi-functional spintronic devices.

The detection and characterization of organic molecules within water ice is vital for interpreting observations of icy moons and comets. However, organic-ice interactions often distort intrinsic water-ice absorption features, complicating infrared (IR) spectral analysis. This study evaluated Optical Photothermal Infrared (O-PTIR) spectroscopy as a non-destructive, sub-micrometer resolution technique to detect and quantify embedded organics. Using a temperature-controlled sample environment to maintain ice stability, frozen mixtures of amino and hydroxy acids were analyzed across a broad concentration range. L-glycine was successfully detected down to approximately $10^{-6}\text{ M}$, yielding an experimental limit of detection (LOD) of $0.2\,\mu\text{M}$ and a limit of quantification (LOQ) of $3.83\,\mu\text{M}$. Furthermore, O-PTIR measurements of binary mixtures containing L-glycine and lactic acid demonstrated the capacity to differentiate and quantify multiple organic components within a single ice matrix. Notably, a broad absorption feature centered near the water-bending mode appeared exclusively in organic-bearing ice samples and was absent in pure $\text{H}_2\text{O}$ and $\text{D}_2\text{O}$ controls. Comparative analysis in these matrices revealed that embedded organics actively perturb intrinsic ice features, providing new constraints on organic-ice interactions. Ultimately, these results demonstrate that O-PTIR spectroscopy can reliably detect, quantify, and spatially resolve organic compounds in water ice while preserving crucial sample context. The technique offers a promising framework for future laboratory investigations of icy planetary materials and directly informs the interpretation of spectroscopic data from volatile-rich space environments.