Papers

The gravitational-wave (GW) census contains mass and spin structure consistent with contributions from black holes assembled through repeated mergers in dense environments. Connecting that structure to formation physics requires models that are both physically interpretable and tractable within population inference. We construct an autodifferentiable, physics-based phenomenological model in which each dense environment is represented by a coagulation response and a population of such environments produces an observable merger-rate density. Embedded in the gwkokab Poisson-likelihood framework, this model enables joint inference of natal-population and interaction parameters from the GW census. Applied to GWTC-5.0, the framework shows why simple pairwise coagulation models struggle to reproduce the observed high-mass, comparable-mass population and tests alternative interaction structures against the data, while retaining an explicitly modeled natal component.

We study the effect of self-propulsion in the approach to the glassy regime of 2D bidisperse mixtures of frictional discs, confined to a horizontal plane, and fluidized by vertical vibrations. The discs are designed either to be passive, that is, exhibiting isotropic motion in the plane, or active, with a preferred polar mobility. When dynamics in mixtures of large active and small passive discs are compared to mixtures of large and small passive discs, the active system shows faster dynamics at equal area fractions. To explore whether activity merely speeds up motion, we select active and passive mixtures with the same relaxation time and compare their dynamics. Many indicators show that dynamical heterogeneity is much greater in the active glass with longer-ranged spatial velocity correlations, larger temporal variations in displacement, and higher amplitude of the four-point correlator. In this very crowded regime, despite frequent collisions, the activity directions of the discs remain persistent. However, the activity direction of the discs remains spatially uncorrelated, and furthermore, the particle displacements are not aligned with the activity direction, thus presenting a puzzle as to how activity leads to such strong heterogeneity.

Based on the conjectured (and checked for tree-type quivers) quiver Yangian/Coulomb branch algebra correspondence, we give a quiver Yangian interpretation of the monopole formulas for 3D $\mathcal N=4$ good $A$-type quiver gauge theories, also known as the $T_\rho(SU(N))$ theories. Using the algebra action on the $\frac12$-BPS vortices, we reorganize the generators of the truncated shifted quiver Yangian into boundary-adapted generators, and obtain the classical relations in terms of $U(N)$ Casimirs on the Slodowy slice $\mathcal S^{\mathfrak{gl}_N}_\rho$, whose coordinates are given by these boundary-adapted generators. We also show that the boundary-adapted generators and the Casimir relations have the correct fugacities as predicted by the Hall-Littlewood expression of the monopole formula for $T_\rho(SU(N))$, hence reconstructing it as the Hilbert series of the truncated shifted quiver Yangian.

Metal-insulator transitions in correlated materials are often accompanied by a change of crystal structure. They are commonly described within a coherent lattice approximation, which combines a correlated treatment of the electrons with a lattice represented by one or a few classical distortion coordinates fixed by minimizing an energy. The structural degrees of freedom then carry no entropy of their own, even though the partition of the transition entropy between electrons and lattice is often what decides the transition temperature. Here we develop a stochastic semiclassical extension of dynamical mean-field theory in which correlated electrons and fluctuating lattice distortions are evolved together, extending previous formulations from linear to nonlinear electron-phonon interactions and from a single to several coupled lattice modes. The resulting non-conservative Langevin equations have deterministic forces, damping, and correlated noise generated self-consistently by the interacting electronic subsystem. Applying the approach to a minimal two-orbital model containing the two symmetry-distinct distortions of the monoclinic phase of vanadium dioxide, we find that the two distortions melt at well separated temperatures, giving an insulating, an intermediate metallic, and a high-symmetry phase. The two transitions have different origins: the melting of the dimerization is driven by the coupling to the correlated electrons and is captured already within the coherent lattice approximation, whereas the restoration of the undistorted structure requires the entropy of the fluctuating lattice. Since the electronic subsystem is treated within nonequilibrium dynamical mean-field theory, the framework can be extended in future work to photoexcited systems with nonthermal electronic distributions.

We address a measurement-driven, single-bath quantum engine that generates usable work using quantum measurement backaction. The working medium is a two-parameter $(p,q)$-deformed harmonic oscillator, whose nonlinear spectrum modifies the energy gaps sampled by a nonselective Gaussian measurement and the work exchanged during quasistatic adiabatic strokes. The cycle starts from a Gibbs state and consists of an adiabatic change of $(\omega,p,q)$, measurement of the final effective position quadrature, a reverse adiabatic stroke, and thermalization with the original bath. Using a consistent first-law convention, we derive the measurement heat, adiabatic work contributions, thermalization heat, and reduced working-medium efficiency. We also express the measurement stroke via a transition matrix and identify passivity/unitality conditions that ensure nonnegative measurement heat. Numerical scans show that, within the finite-basis, spectral-ordering, and engine-operation checks used in this work, deformation can enhance measurement-induced energy input and extracted work relative to the undeformed oscillator. The physical engine regime is selected by $\QM>0$, $\Wcyc<0$, $\QT<0$, and $0<\eta<1$. The reported efficiency is reduced and excludes measurement-apparatus costs.

Context. Chromatic Anisoplanatism arises in Adaptive Optics because atmospheric refraction makes rays of different wavelengths follow different paths through the atmosphere resulting in different wavefronts at the sensing wavelength and the science wavelength, introducing a correction error that grows rapidly with zenith distance. Aims. Using numerical simulations based purely on geometric optical propagation we aim to validate the theoretical framework describing wavefront errors caused by Chromatic Anisoplanatism. We characterize the resulting phase variance and Strehl ratio loss for telescope apertures up to 39 m, retrieving their second-order statistics. Methods. We compare the analytical expressions for the Chromatic Anisoplanatism wavefront phase variance against independent Monte Carlo simulations. The framework models an 8-layer approximation of the median Cerro Armazones turbulence profile using Kolmogorov and von Karman turbulence models. We simulate pupil diameters from 4.2 to 39 m with lambda_WFS = 589.16 nm for the wavefront sensing and lambda_Sci = 1.25 microns as the science wavelength. A phase-screen recombination strategy increases the number of quasi-independent realizations up to ~ 5 x 10^5, optimizing statistical accuracy. Results. Simulated phase variances match theoretical predictions well across all apertures, though theory slightly overestimates variance in the von Karman case. The Strehl Ratio loss exceeds 30% for zenith angles >= 70 deg. The residual wavefront is dominated by high spatial frequencies; removing tip-tilt reduces phase variance by <= 1% for apertures >= 10 m. The massive dataset reveals highly non-Gaussian probability density functions for the phase variance and Strehl Ratio values, both characterized by non-zero skewness and kurtosis, and long tails toward rare, high wavefront phase variance and/or low Strehl Ratio error events.

Quantum resource distillation converts imperfect resource states into highly resourceful targets and is a central task in quantum information processing. When distillation is probabilistic, unfavorable outcomes may be discarded and the quality of the output is evaluated conditioned on success, leading to a notion of reliability that differs from the deterministic setting. Here we study the conditional error exponents of probabilistic quantum resource distillation under approximately resource-nongenerating instruments and derive its general connection to the postselected composite quantum hypothesis testing against the corresponding set of free states. This reduction leads naturally to scale-invariant projective distinguishability measures and provides finite-blocklength bounds for a broad class of resource theories. We apply the framework to entanglement, coherence, and magic. For entanglement and magic, we obtain exact zero-rate asymptotic characterizations of the conditional error exponent in terms of regularized projective distinguishability, while for coherence we derive general finite-blocklength and asymptotic bounds. For representative entangled and magic states, the resulting quantities can be evaluated analytically and reveal regimes in which postselection yields a strictly larger conditional error exponent than deterministic distillation. Furthermore, we also show that the conditional error exponents for probabilistic entanglement distillation under a strictly positive success probability constraint are smaller than those with no constraints on the success probability.

We present an unsupervised search for anomalous dijet events in proton–proton collision data using neural spline flow density estimation. A normalizing flow model is trained on a high-dimensional feature space comprising jet, dijet, and event-level observables to learn the dominant Standard Model background directly from data, without assuming a specific signal hypothesis. Events assigned low likelihood under the learned density are identified as potential anomalous events. Using this approach on a CMS Open Data dijet sample, we investigate extreme events in the tail of the anomaly-score distribution and perform an extensive validation and robustness study. This study includes feature-level statistical comparisons, mass decorrelation tests, permutation-based null tests, and evaluations of training stability. The selected anomalous events exhibit notable departures from the background-only expectation, primarily in jet-substructure observables, while remaining stable under several known sources of bias in unsupervised learning. The identified anomalies are distributed across the kinematic phase space and do not exhibit a narrow structure in the dijet invariant-mass spectrum. Instead, they show correlated deviations across multiple observables, consistent with a multivariate difference in jet substructure and event topology rather than a localized resonance. While no claim of new physics is made, this study demonstrates that neural spline flow-based density estimation can be sensitive to rare, structured deviations in collider data and may provide a model-independent exploratory tool for searches for physics beyond the Standard Model at the LHC.

We investigate whether an Fe–dehydroindigo coordination polymer can support Haldane-chain physics in its intrinsic, substrate-free limit. Spin-orbit-coupled density-functional-theory calculations and magnetic energy mapping yield a nearly isotropic antiferromagnetic coupling, together with much weaker single-ion anisotropy. Using these parameters, exact diagonalization and density-matrix renormalization group calculations give a nondegenerate ground state separated from the lowest triplet-derived excitations by a gap of about $13$–$14$~meV, on the scale expected for the spin-1 Haldane gap. The anisotropy produces only a small splitting of the low-energy modes. The dynamical spin structure factor places the lowest spectral weight near the antiferromagnetic wave vector $q=\pi$. These results identify the isolated cis-dehydroindigo chain as a material-specific coordination-polymer platform whose microscopic interactions place it in a gapped regime consistent with Haldane-chain physics.

The nearby $\pi$ Mensae system contains the eccentric giant planet b on a 5.7 yr orbit, the 6.27 day transiting sub-Neptune c, and a candidate planet d on a 123 day orbit between them. Published estimates place the eccentricity of d between approximately 0.2 and 0.4. We reanalyze 772 published velocities with three-Keplerian fits and explore three-dimensional b-d dynamics with N-body integrations. The high-eccentricity solution persists when the phase or apsidal prior is widened; exact importance reweighting to a population-informed Beta eccentricity prior gives $e_{d}=0.378^{+0.050}_{-0.049}$. In 20 kyr integrations, 84.5% of configurations near the prograde and retrograde coplanar endpoints survive, compared with 21.3% across $60^\circ \leq I_{bd} < 120^\circ$; stellar collisions dominate the failures. Secular forcing by b moves 53 of 62 one-Myr survivors initialized with $e_{d} \leq 0.1$ into $0.3 \leq e_{d} \leq 0.5$. Representative b+d configurations remain viable for 100 Myr, whereas controls with c and general relativity retain fewer systems. The outer giant can therefore excite the observed eccentricity of d while constraining its viable orbit toward prograde or retrograde near-coplanar configurations.

FBPIC (Fourier-Bessel particle-in-cell) is a high-performance simulation code for relativistic plasma and accelerator physics. Its original accelerator backend relies on Numba CUDA, which limits its direct deployment on accelerators using the HIP (Heterogeneous-Compute Interface for Portability) programming environment, such as DCU (Deep Computing Unit) accelerators. In this work, we develop an accelerator backend compatible with HIP that enables FBPIC to run efficiently on DCU platforms while preserving its Python user interface and high level simulation workflow. For the evaluated LWFA (laser-wakefield acceleration) workloads, the proposed backend achieves 1.32-1.54x speedups over the original FBPIC implementation on an NVIDIA V100 GPU and enables efficient execution on the DCU platform. We also summarize the key lessons learned from porting FBPIC to the DCU platform. Multi-DCU experiments achieve a 1.88x strong-scaling speedup on four accelerators and a 2.72x increase in aggregate throughput at approximately 68% weak-scaling efficiency, with communication analysis identifying inter-node communication and synchronization as the main scalability limitations. Beyond FBPIC, the proposed approach provides a practical reference for porting and optimizing other scientific computing applications developed with Python on heterogeneous accelerator platforms.

We present a census of dust, molecular gas, and galaxy structure in 18 dusty star-forming galaxies (DSFGs) at $z=3.09$ embedded in Ly$\alpha$-traced cosmic web filaments in the core of the SSA22 proto-cluster, using multi-band ALMA, JWST imaging, and JVLA CO(1–0). Using up to six ALMA bands and Herschel/SPIRE data, we construct rest-frame far-infrared spectral energy distributions. The DSFGs span two orders of magnitude in far-infrared luminosity ($L_{\rm FIR}\sim10^{11}$–$10^{13}L_\odot$), with median values of $\log(L_{\rm FIR}/L_\odot)=11.56^{+0.32}_{-0.37}$ and $T_{\rm dust}=25^{+6}_{-3}{\rm K}$. For eight DSFGs with high-resolution ($\sim1$ kpc) JWST and ALMA imaging, we measure stellar and dust surface densities and find a positive correlation, suggesting that structural compaction of the stellar component proceeds together with that of the interstellar medium. We report 12 detections of CO(1–0), 18 of CO(3–2), four each of CO(8–7) and CO(9–8), and one of CO(12–11). The median brightness temperature ratio between CO(3–2) and CO(1–0) is $r_{31}=0.66^{+0.05}_{-0.04}$, consistent with field galaxies at similar redshifts. The high-$J$ CO lines show relatively low excitation, and the CO(8–7)/CO(3–2) ratio correlates with star-formation rate surface density, suggesting that molecular gas excitation is primarily regulated by star formation. Lower-mass galaxies show excess molecular gas fractions and depletion times relative to field scaling relations. By combining quiescent galaxy samples in the same field, we identify a sequence from gas-rich systems with low stellar surface density to gas-poor, compact systems with high stellar surface density. These results suggest that massive galaxy evolution in dense environments is governed by a baryon cycle linking gas supply, star formation, and structural transformation within the cosmic web environment.

Entangling rates describe a direct entangling channel, but give no information when that channel is forbidden. For finite-dimensional analytic pure-state dynamics, we show that the onset of genuine $(n+1)$-partite entanglement is determined by the contact order $m_\star$ between the physical trajectory and the $S|E$ product manifold. It is the first Taylor order that cannot be reproduced by any product curve, or equivalently the first nonvanishing order of the Fubini–Study distance from the product manifold. We derive a time-ordered recursion that removes curvature-induced kinematic terms and computes $m_\star$ from the Taylor coefficients of $H(t)$. This provides a geometric description of an entanglement cascade, in which new subsystems can join multipartite entanglement only after one or more interaction steps. A symmetry-protected three-qubit model realizes $m_\star=2$, and a three-mode bosonic example shows that genuine tripartite entanglement can arise even when the two newly formed reduced pairs remain separable.

Neural network quantum states (NQS) for representing spin-$\frac{1}{2}$ systems are typically built from Multi-Layer Perceptrons (MLPs) with binary visible variables, in which the input spins are first combined through linear affine maps before more expressive nonlinear transformations are applied. The standard way for representing multi-categorical systems, namely spin-1 and spin-2, or the q-state quantum Potts systems with more than two local degrees of freedom, is a unary or one-hot encoded MLP architecture. Following a few similar studies, I observe that while the one-hot construction is the mathematically faithful encoding for systems with more than two local states such as spin-$S$ models with $S > 1/2$ or $q$-state Potts models, its parameter count grows with the number of local states, and the resulting optimization landscape can hinder convergence. I find numerically that allowing $\log \Psi$ to be a nonlinear function of the raw multi-valued spin variable is a natural categorical generalization: it preserves the labelling freedom of the local basis and reproduces the one-hot model with strictly fewer parameters, often with improved trainability. I first benchmark this idea on shallow Restricted Boltzmann Machines (RBMs), equipping them with several distinct nonlinear connections, for spin-1, 2, and 3 Heisenberg chains. I then turn to Kolmogorov-Arnold Networks (KANs), where each edge carries a learnable univariate nonlinearity, and show that they provide a strictly more expressive realization of the same principle. Finally, I demonstrate that this framework captures the critical behaviour of the quantum Potts Hamiltonian, recovering its phase transition.

The algebraic structure of the equation governing the propagation of an elastic SHwave through an isotropic inhomogeneous layer surrounded by two homogeneous half-spaces is revisited. It is shown that the problem under a quartic variation has a hidden sl(2) symmetry based on which quasi-exact solutions are available via a completely analytical approach. This is of particular interest as the approach proposed for the corresponding tri-confluent Heun equation can be generalized to some other classes of geometries as well and the complicated considerations in case of Heun equations are absent.

Machine-learning-based inverse design can accelerate the discovery of materials with targeted properties, but conventional structure–property models often require large training datasets and generalize poorly beyond their training distribution. Here, we present a differentiable inverse design framework based on a graph neural network molecular dynamics simulator. By combining a short dynamical initialization with physics-based refinement during simulation, the framework enables optimization well beyond the conditions represented in the training data. Using disordered elastic networks, we show that a simulator trained only on non-auxetic systems with Poisson's ratios between 0.1 and 0.4 can design strongly auxetic networks with values as low as -0.3. The framework also produces stress–strain responses outside the range observed during training, creates localized mechanical defects absent from the training data, and generalizes across system size, enabling optimization of networks tested up to 5000 nodes despite being trained only on networks with fewer than 200 nodes.

Precise stellar masses and physical parameters for binary and multiple star systems require, respectively, well-constrained orbital solutions and independent stellar-atmosphere modeling. Existing open-source software addresses these separately, and hierarchical triple systems additionally require simultaneous fitting of their inner and outer orbits, a treatment few existing tools provide. We present PySeshat, an open-source Python package unifying binary and hierarchical-triple orbit determination with stellar SED fitting in a single, validated pipeline. The package fits visual, spectroscopic, and combined binary orbits by least-squares, and hierarchical-triple orbits through two parallel formalisms, one of which fits both inner and outer orbits simultaneously rather than sequentially. Both share a common Bayesian posterior-sampling layer. A second module fits two-component synthetic spectra to a binary's combined, unresolved photometry to recover each component's temperature and radius. The software was validated against twelve real, published benchmark systems, cross-checked against three independent orbit-fitting packages and real space-telescope archive data. All twelve benchmark systems reach fit quality consistent with their published solutions. Comparing the simultaneous and sequential triple-fitting formalisms on the same real systems shows the simultaneous approach is not merely preferable but necessary: one system's orbital configuration cannot be represented by the sequential formalism at all. Fitting four independently published systems' photometry reveals a degeneracy in recovering individual temperatures for near-twin-temperature stellar components from unresolved light, independent of how much photometric data is available. The package provides a validated, open, and extensible pipeline for binary and multiple star system analysis, publicly released and freely installable.

In this paper, we investigate the optical properties of Kerr-Newman-Bertotti-Robinson (KN-BR) black holes. We use the separability of null geodesics to analyze unstable spherical photon orbits and determine the radial extent of the photon shell. Because the spacetime is not asymptotically flat, we construct the critical curve on the screen of a finite-distance zero-angular-momentum observer. We then perform backward ray tracing for a geometrically thin and optically thin disk that extends from the outer region to the event horizon, and examine the resulting images, intensity profiles, critical-curve areas, and inner-shadow areas. We find that the genuine neutral Kerr-BR$_0$ and specially charged Kerr-BR$_s$ configurations have nearly identical optical appearances. It is remarkable that for the KN-BR black holes increasing the electric charge reduces the characteristic image size in the Kerr-Newman limit but enlarges it in the magnetized configurations considered here. We also find that the external magnetic field strongly increases the apparent image scale, while the observer inclination affects the inner-shadow area more significantly than the critical-curve area. These results may provide useful theoretical insight for future observations aimed at identifying such exotic magnetized black holes.

Quantum entanglement growth is commonly summarized by a single entropy, obscuring where correlations reside in the exponentially large Schmidt spectrum and how they form. Here, we introduce Schmidt-scale concentration and dominant Schmidt scale, two coordinates that locate the probability maximum across logarithmic windows in ordered Schmidt-rank space. Applied to quenches of a random-field spin chain, these coordinates distinguish rapid transport of the dominant scale to higher Schmidt rank at weak disorder from strongly suppressed transport despite continued logarithmic entropy growth at strong disorder. The disorder-averaged dynamics exhibit an ordered hierarchy: entropy production peaks first, spectral roughness and exact nonlocal magic peak next, and dominant-Schmidt-scale transport becomes typical only after a substantial delay. Moreover, a solvable head–tail model and controlled numerical experiments reveal the physical origin of this hierarchy: the spectral path determines the order of events, local dynamics on active exchange bonds set their early timing, and intra-subsystem many-body dressing further delays dominant-Schmidt-scale transport. These results establish the Schmidt-scale coordinates as powerful dynamical probes for uncovering fine-grained entanglement structures distinguishing entanglement production, entanglement-spectrum reorganization, and dominant-Schmidt-scale transport beyond entropy alone.

We investigate the 248~keV nuclear recoil excess reported by LUX-ZEPLIN (LZ) in a leptophobic inelastic dark matter framework, in which the mass splitting naturally suppresses low-energy recoils. We find two viable branches, including the endothermic solution with a high dark matter mass $m_\chi \gtrsim400$~GeV and the exothermic one with a mass of tens GeV. Remarkably, the exothermic dark matter scenario with $m_\chi\sim55$~GeV can simultaneously account for the LZ excess, the Galactic Center GeV gamma-ray excess, and the AMS-02 antiproton excess. The favored annihilation cross-section is slightly below the one required for the observed relic abundance, resulting in an overabundant relic in the minimal setup. An additional neutrino-portal mediator can provide the required depletion while leaving the gamma-ray and antiproton signals essentially unchanged. We further show that paleo-detectors provide a powerful probe of the inelastic interpretation, requiring exposures of $\sim10$ and $\sim100$~mg Gyr for the endothermic and exothermic scenarios, respectively.

We develop a generalized finite-temperature proton-neutron BCS framework using the superoperator formalism, incorporating both isovector and isoscalar monopole pairing channels. Numerical calculations for a schematic equidistant multilevel model and realistic even-even Ge isotopes demonstrate the emergence of proton-neutron ($pn$) pairing reentrance in even-even asymmetric ($N>Z$) nuclei with preexisting like-nucleon pairing correlations. This nonmonotonic behavior arises from thermal excitations that partially lift Pauli blocking of single-particle orbitals near the chemical potentials, thereby enlarging the phase space for $pn$ pair formation. We uncover a delicate interplay between thermal unblocking and like-nucleon pairing, which can either suppress or enhance $pn$ correlations depending on temperature and shell filling. A qualitative analysis of Fermi charge-exchange strength functions in hot $^{72}$Ge, which neglects the residual interaction between thermal quasiparticles, suggests that $pn$ pairing reentrance may alter the transition strength distribution around $T\approx1$~MeV. This indicates that finite-temperature $pn$ correlations could potentially impact stellar weak-interaction rates in $rp$-process and supernova environments.

Convex optimization on polytopes arises in many areas of science. When the polytope is given implicitly or has exponentially many vertices and facets, standard methods may not apply or be ineffective. This is the case for moment polytopes, such as the entanglement polytopes, which play a foundational role in quantum information and algebraic complexity. They give rise to important entanglement measures and tensor parameters such as the quantum functionals, yet general effective methods for computing these quantities have been elusive. In this paper we address this challenge. We develop a first-order framework called Hadamard mirror descent to optimize suitable convex functions over moment polytopes and, more generally, the gradient sets of geodesically convex functions. It operates locally and does not rely on any explicit description of the polytope. Our framework extends mirror descent, an effective and widely used framework for convex optimization, from the Euclidean setting to Hadamard manifolds, and is motivated by a recent work by Hirai, which we interpret as a Hadamard version of mirror flow. Applying the framework to entanglement polytopes yields the first efficient first-order algorithms to compute the quantum functionals, the symmetric quantum functional, and the G-stable ranks, as well as a new direct algorithm for the non-commutative rank.

Quantum coherence is a central resource in quantum information science, yet general frameworks and constraints governing its dynamics remain limited. Although quantum coherence lacks a general monotonicity law, we establish an exact integral fluctuation theorem (FT) for coherence dynamics, formulated in terms of Kirkwood-Dirac (KD) quasiprobability trajectories and valid for arbitrary initial states and dynamics. This integral FT deviates from the standard unit-valued form, and the complex deviation, termed the anomaly, quantifies a weighted overlap between the residual final-state coherence and the coherence generated from the dephased input. The real part of the anomaly yields bounds on coherence change, while its imaginary part constrains the second-order moment of the stochastic coherence change weighted by the imaginary parts of the KD quasiprobabilities. Our results establish general statistical constraints on coherence dynamics, demonstrating the utility and broad applicability of FTs for studying quantum-resource dynamics.

The origin of a cosmic ray particle with an ultra-high energy of 2.44 x 10^20 eV recorded by the Telescope Array is discussed by assuming that it is a heavy nucleus, namely an iron or silicon nucleus. Iron is chosen as a heaviest element in cosmic rays, while silicon is chosen to find out how much the theoretical results obtained vary with the mass of the heavy nucleus. Assuming extragalactic origin of the particle with such energy, the constraints on the distances to possible sources are analysed using a routine calculation of the cosmic ray propagation in extragalactic space. These possible sources are discussed.

The ability to engineer chiral light-matter interactions is a valuable resource for realizing quantum networks and non-reciprocal quantum optics. Here, we demonstrate chiral coupling between light and a negatively charged exciton state, i.e., a four-level system, embedded in a standard photonic-crystal waveguide. By controlling the orientation and strength of an external magnetic field, we tune the polarization of the individual optical transition dipoles relative to the fixed elliptically polarized waveguide mode. In a two-sided waveguide, an optimized oblique magnetic field allows a selected transition to decay exclusively into a single propagation direction, enabling near-unity directional emission ($0.99^{+0.01}_{-0.02}$), despite the waveguide exhibiting imperfect polarization for chiral coupling. We further observe two tunable chiral branching ratios, the directional analogue of optical cyclicity, for two $\Lambda$-systems, with one reaching $134_{-77}^{+\infty}$. The magnetic-field-dependent spectroscopy also allows reconstruction of the local guided-mode polarization at the emitter via the Stokes parameters relative to the emitter's dipole moments. Finally, we demonstrate that this local chirality enables coherent control of an electron spin via an optical Raman process mediated by waveguide driving. Building on the simultaneous realization of a large branching ratio, directionality and spin control achieved at the same oblique magnetic-field angle, we propose a protocol with high tolerance to photon loss for generating high-fidelity remote spin-spin entanglement. Our magnetic control opens a reconfigurable and generic route for enhancing on-chip chiral spin-photon coupling in standard nanophotonic interfaces without the need to carefully engineer the polarization of the waveguide.

Multiple principal element alloys (MPEAs) exhibit complex phase equilibria involving multinary solid solutions and intermetallics, which makes it challenging to predict their temperature-composition phase diagrams. Their vast compositional space makes first principles methods prohibitively expensive, while CALPHAD is limited by scarce experimental data. Here, we present a computationally efficient framework to predict the solvus phase boundaries, and hence, phase fields, in refractory MPEAs composed of Cr, Hf, Mo, Nb, Ta, Ti, V, W, and Zr. The approach combines DFT calculated binary mixing enthalpies with sub regular solution models to construct phase diagrams without fitting higher order interactions, enabling efficient scaling across composition space. Validation against 36 binary and 15 ternary phase diagrams demonstrates good agreement, with both experimental results and CALPHAD calculations. We find that the prediction accuracy is enhanced by incorporating lattice dependent energetics through sub regular solution models and including temperature-dependent elemental phase transitions. The framework captures miscibility gaps, solid solution stability, and intermetallic formation, with predicted miscible temperatures typically within 300 K of experimental values. Overall, this work establishes a scalable, first principles based route for highthroughput prediction of phase diagrams in refractory MPEAs. A publicly accessible web interface has also been developed to allow interactive exploration of the predicted phase diagrams, available at https://raptor.engr.wustl.edu.

We describe how laser-cooled and trapped alkali-metal atoms have been used as pressure sensors in the high- and ultra-high-vacuum regimes operating with relative uncertainties of just over a percent at pressures from a few nPa and up to a few tens of $\mu$Pa. These sensors can serve as primary standards of pressure as the determination of pressure requires only knowledge of collision cross sections between atoms and molecules, eliminating the need for calibration with other devices. The collision cross sections can be measured independently or computed with rigorous quantum methods at percent relative accuracies. We argue that this technology has advanced sufficiently to provide an alternative to the existing, expensive pressure standard in the ultra-high vacuum regime, the orifice flow standard. Experiments with trapped atoms can be used to calibrate cheaper pressure sensors (such as devices based on ionization gauges). However, the technology has not yet matured enough to be of use in other research fields because of the complexity and cost of the experiments. We propose a roadmap for this new pressure standard for vacuum metrology.

We investigate the level shifts in protonium using the framework of non-relativistic effective field theory (NREFT). Our study is prompted by the PUMA collaboration's plans to probe the neutron-to-proton ratio in the nuclear density tail using antiprotonic atoms – a method for which light atoms provide an important benchmark. We calculate the corrections to the Deser-Goldberger-Baumann-Thirring formula for the complex level shift of S-wave states from the unitary cusp and Coulomb photon exchange. Structure dependent corrections enter at the next order. For higher-partial-wave states, they enter already at leading order. Using input from chiral NNbar interactions, we compare to other calculations and measurements from LEAR.

Moire materials provide a versatile platform realizing emergent electronic states arising from enhanced correlation due to flat bands. A variety of phenomena including superconductivity, low dimensional ferromagnetism, Mott insulating phase, and topological phenomena have been reported in such systems. To date, moire phenomena have been predominantly explored in artificially assembled low dimensional van der Waals structures, where relative twist and lattice alignment are controlled during device fabrication. Recently, intrinsically grown bulk moire crystals have emerged as a complementary materials platform, in which lattice mismatch between constituent layers generates a coherent moire superlattice throughout the bulk crystal. Here, we report the evidence of bulk superconductivity in single crystals of a recently reported bulk Moire material [Sr6TaS8]1+x[TaS2]8 at ambient pressure. The material exhibits a bulk superconducting transition at Tc = 2.5 K, evidenced consistently by electrical transport, magnetic susceptibility, and heat capacity measurements on single crystals. Structural characterization by X-ray diffraction and atomic resolution electron microscopy establishes the composite, incommensurate crystal structure and scanning tunnelling microscopy reveals a long-wavelength surface modulation due to the incommensurate structure. The observation of bulk superconductivity establishes superconductivity as an emergent phase in this intrinsically synthesized moire material and highlights bulk moire crystals as a promising platform for investigating correlated quantum phenomena beyond artificially assembled two-dimensional structures.

The first goal of this paper is to give a new family of special function related to the Debye functions. By using these function and generating function method, we derive many novel formulas and relations involving the Debye functions, multiple Hurwitz Lerch zeta function which interpolate the Apostol-Bernoulli numbers of higher order at negative integers. Proof method of theorems in this paper are different from those of theory of analytic numbers. The second goal of this paper is to show that special values and integral presentations of this function are closely related to unification of the Debye functions, the moment generating function for the negative binom distribution, the generating functions for the Apostol-type numbers of higher-order, and the Frobenius-Euler numbers, the Bernoulli numbers, and the Stirling numbers etc. Moreover, we give recurrence relations, Maclaurin's series expansion, and approximation formula for unification of the Debye functions. Finally, we give further remarks, observations and applications in mathematical physics on the results of this paper.