Papers

In a recent work \href{https://doi.org/10.1103/PRXQuantum.2.010325}{PRX QUANTUM 2 (2021) 010325}, a new way of investigating quantum gravity signatures using quantum information theoretic techniques, have been proposed. The primary result of this analysis revealed that non-Gaussianity can arise only through the consideration of a quantum model for the gravity part. Compared to classical gravity, only quantum gravity can result in non-quadratic operators in the Hamiltonian which leads to the non-Gaussian behavior. In our current analysis, we have considered a more realistic scenario taking into effect leading order post-Newtonian corrections in the analysis. We have stayed with the same model of a Bose-Einstein condensate placed inside a harmonic trap potential which indeed works as the detector of the non-Gaussianity generated due to quantum gravitational effects. Bose-Einstein condensates are experimentally well studied; apart from being a single quantum system, they include Feshbach resonances, which helps tuning the strength of the electromagnetic interactions which in principle can be set to zero. This is important since it can help distinguish quantum gravity from electromagnetic interactions without affecting gravitational interactions, and any non-Gaussianity can then be solely attributed to quantum gravity. We observe that the signal to noise ratio gets slightly damped due to the post-Newtonian effects taken under consideration.

The underground cosmic-ray muon rate is modulated by atmospheric temperature. It can be explained by the theories of Barrett, Gaisser, and others. However, the Daya Bay Neutrino Experiment observes a nonlinear temperature dependence. We find that, when deriving the temperature dependence of the muon rate, existing theories consider only the impact of the local temperature on muon production at the layer where muons are produced. In this work, we provide a more general solution to the cascade equations that fully depicts how the entire temperature profile influences the final muon rate. The corresponding definitions of the effective temperature weight and temperature coefficient are also presented. We have examined the results using the numerical tool MCEq with real atmospheric temperature inputs. A linear modulation is recovered and verified. This work can help explain the nonlinear effect observed at Daya Bay and provide a more refined theoretical framework for calculating the temperature coefficient in other experiments.

We study Family-Vicsek scaling of charge, spin, and energy fluctuations in the one-dimensional Hubbard model at infinite temperature. Using a quantum generating function approach, we compute time-dependent cumulants of transferred conserved quantities and analyze how the corresponding roughness depends on subsystem size and time. We start by focusing on a single interface at half the chain and determine the transport exponents. Then we turn to fluctuations of a small finite interval and study the Family-Vicsek universality of fluctuations over an extended timescale. We find that the long-time scaling behavior is controlled by integrability. In the free limit, charge, spin, and energy all display ballistic transport. In the interacting integrable Hubbard chain, charge and spin cross over to a KPZ scaling regime, while the energy sector remains ballistic. Once integrability is broken by a next-nearest-neighbor density interaction, the long-time dynamics becomes diffusive in all sectors. In every case we also observe a short-time microscopic regime with apparently universal ballistic growth before the hydrodynamic scaling window sets in. The Family-Vicsek setup allows us to determine the growth, the saturation as well as the dynamical exponents.

Plasmon-exciton hybrids, or plexcitons, offer deeply subwavelength light-matter interactions with versatile pathways for energy redistribution. Incorporating chirality into such systems is particularly compelling, enabling spin-sensitive optical functionality that can operate on ultrafast timescales and within ultracompact volumes. Despite recent progress in chiral plexcitonic systems, how structural chirality and plasmon-exciton coupling determine chiroptical spectra and ultrafast energy flow remains elusive. Here we realize chiral plexcitons by functionalizing intrinsically chiral gold helicoid nanoparticles with molecular J-aggregates. Within a non-Hermitian framework, we trace the microscopic origin of the helicoid chiroptical response and its coupling to the excitonic transition, revealing how the helicity of light selectively addresses distinct hybrid responses. At the spatiotemporal extreme, we find that the gap-localized response not only enhances polarization-sensitive contrast but also strengthens the local hybrid interaction, leading to accelerated ultrafast relaxation. Together, these space-, time-, and polarization-resolved measurements provide a physically grounded and experimentally benchmarked picture of chiral plexcitonic coupling, identifying chirality as a practical control parameter for selectively steering nanoscale energy pathways and dynamics.

Subsurface imaging interpretation bridges observed geophysical data and quantitative geological models, supporting hydrocarbon exploration, CO2 storage assessment, and geohazard monitoring. Over the past decade, machine learning and deep learning have substantially reshaped interpretation workflows. This review synthesizes the 2015-2025 literature across four tasks: structural interpretation, geobody identification, seismic facies analysis, and property estimation, tracing the field's evolution from classical machine learning through deep learning to emerging domain foundation models, and how these tasks couple within a single interpretation system. The task remains fundamentally different from other AI applications, facing ambiguous signals, interpretive non-uniqueness, sparse semantics, unfixed target locations, and scarce reliable annotations. We synthesize three defining challenges: interpretation under complex geological conditions, cross-survey semantic generalization under low information density, and the absence of reliable benchmarks. Addressing them will hinge on integrating human expertise, physical constraints, and geological priors into training and inference, and on treating uncertainty quantification as an intrinsic model output. We outline a forward-looking agenda: unified, jointly modelled interpretation systems with cross-task consistency; priors evolving from physics toward language and multimodal supervision; end-to-end uncertainty propagation; human-AI collaboration and agent-orchestrated workflows; and a more rigorous evaluation science supported by an AI-ready data ecosystem. The review is accompanied by an open benchmark resource (CIG-Bench), covering fault segmentation, relative geologic time estimation, geobody segmentation, and property modeling, with synthetic datasets, pretrained baselines, and quantitative evaluation: https://douyimin.github.io/CIG-bench

We present a theoretical study of global and azimuthal-angle-dependent $\Lambda$ hyperon polarization in isobaric $^{96}_{40}$Zr+$^{96}_{40}$Zr collisions at $\sqrt{s_{NN}}=200$~GeV using the TRENTo3D initial condition model coupled to the (3+1)-D viscous hydrodynamic model CLVisc. A longitudinal flow velocity gradient, controlled by $f_v$, is introduced into TRENTo3D for the first time, providing an essential source of initial vorticity in this symmetric isobaric system. Within the isothermal polarization framework, the model provides a simultaneous description of STAR measurements of the global polarization $-P^{y}$ (centrality, $p_T$, and $\eta$ dependences) and the azimuthal modulation coefficients $P_{y,\mathrm{c0}}$ and $P_{y,\mathrm{c2}}$. The $p_T$ dependence reflects the competition between thermal vorticity and shear contributions: the thermal term decreases with $p_T$, while the shear term rises and increasingly shapes the curvature of the total polarization. In this decomposition, $P_{y,\mathrm{c2}}$ is dominantly shear-driven and serves as a clean probe of shear-induced polarization. Scans of $f_v$, $k_T$, and nuclear structure provide complementary constraints on the initial state, while the bulk-viscosity dependence is also examined; the five nuclear structure configurations from the STAR isobar blind analysis yield nearly indistinguishable polarization. For $P_z$, the isothermal scenario captures the azimuthal modulation but overpredicts the high-$p_T$ modulation amplitude, and comparison with the standard thermal treatment shows that neither scenario achieves a unified description of all observables.

Understanding vehicle movement on road networks is closely related to various practical and theoretical issues. While recent works have focused on which cost vehicles minimize while moving, how they move to minimize that cost remains less explored. In this work, we analyze large-scale data of individual vehicle trajectories in real-world road networks to identify cost-minimizing movement patterns of vehicles and the influence of road network structure on such movement. We observed that vehicle movements exhibit three phases: the beginning, middle, and end of trips. At the beginning and end, vehicles detour more, lose directional memory quickly, and travel at lower speeds than during the middle. In contrast, during the middle, they tend to detour less, maintain directional memory, and travel faster than at the beginning and end. Finally, at the beginning and end, vehicles exhibit similar detour and velocity patterns, except the direction of movement. To understand these patterns, we propose a double-layered network model mimicking the hierarchical structure of real-world road networks. We found that when vehicles move across our model network while minimizing travel time, they tend to concentrate on high-level roads, and the three observed movement phases are reproduced. Consequently, when a vehicle moves between a given origin-destination pair, it must enter and exit these high-level roads. This causes it to deviate from the trajectory that minimizes travel distance between the same origin-destination pair – particularly at the beginning and end of the trip. Our results reveal common patterns underlying individual vehicle movements that appear highly diverse at first glance, demonstrating that these patterns emerge because vehicles leverage the characteristics of hierarchical road networks to minimize travel time.

Aims. We expand the planetary census around massive stellar hosts through a long-term campaign of high-precision radial velocity (RV) measurements on evolved stars. Methods. We analyse data acquired with the CORALIE spectrograph covering 15-18 years on HD125136, HD127195, and HD220218. Stellar parameters are derived through different methods for a comprehensive characterization of each star. We then evaluate the presence of planetary signals in the RV time series using the Bayesian inference tool kima. Finally, we design an observing strategy aimed at mitigating the impact of pulsations on evolved stars and test its effectiveness on the low-luminosity red giant HD127195. Results. We detect signals that are accurately modelled by Keplerian curves in the RV data of the three stars: one on HD 125136, two on HD 127195, and one on HD 220218. While the signals on the first two stars seem to be of planetary origin, the signal on the third one shows several signs of stellar activity. We therefore identify a planetary companion around HD125136 with a minimum mass of 2.26 MJup on an 850 d orbit, and on HD127195 we identify a system composed of planets with 0.66 MJup and 0.78 MJup with orbital periods of 535 d and 834 d, respectively. Conclusions. We detect three massive planets around two low-luminosity red giant stars in a region of the parameter space that is poorly populated in both stellar mass and planetary orbital periods. The dedicated observing campaign on HD127195 showcases how stellar pulsations can be efficiently averaged out to below 5 m/s in low-luminosity giant stars.

We implement GPU acceleration of collinear and noncollinear density functional theory (DFT) calculations in the numerical atomic orbitals (NAOs) code OpenMX by offloading matrix multiplications and eigenvalue solves (plus selected auxiliary steps) to cuBLAS/cuSOLVER and OpenACC. Benchmarks on the Pegasus supercomputer (per node: a 48-core Intel Xeon Platinum 8468 CPU and one NVIDIA H100 GPU) compare GPU-accelerated and CPU-only runs under identical settings. For a 512-atom collinear case on two nodes (two GPUs total), the GPU-accelerated calculation achieves a 2.02 times speedup over a CPU-only run on two nodes (96 CPU cores total); for a 384-atom noncollinear case on two nodes (two GPUs total), the speedup is 2.60 times over two CPU-only nodes (96 cores). These results demonstrate practical GPU-accelerated DFT in an NAO-based code for both collinear and noncollinear calculations.

A data-driven reduced-order modelling framework is proposed for wall-bounded turbulent flows to forecast the intermittent near-wall dynamics over extended time horizons from sparse sensor measurements. The approach combines a $\beta$-VAE-GAN, which compresses high-dimensional flow fields into a low-dimensional latent space, with a sensor-conditioned Transformer that forecasts the evolution of the latent variables. The temporal module employs Easy Attention, a static time-mixing operator that replaces the learnable query-key mechanism of standard self-attention at reduced computational cost, combined with an adapted AdaLN-Zero modulation mechanism for sensor-based conditioning. Evaluated on the Minimal Flow Unit ($Re_\tau = 200$) at $y^+ = 14$, the compression stage recovers $87\%$ of the turbulent kinetic energy within a four-dimensional latent space, exceeding the standard $\beta$-VAE baseline by more than $10\%$. The latent dimensions autonomously encode the characteristic timescales of the flow, with specific coordinates capturing the low-frequency signature of the near-wall regeneration cycle ($T^+ \approx 1724$), establishing the physical interpretability of the learnt representation. The sensor-conditioned Transformer maintains accurate forecasts over $17{,}288\,t^+$ from an initialisation window of only $128\,t^+$, whilst end-to-end inference reconstructs $82\%$ of the turbulent kinetic energy. The principal limitation is the attenuation of rare, extreme-amplitude events, a consequence of the encoder prioritising the most statistically recurrent flow states within the low-dimensional bottleneck. Nevertheless, the framework accurately reproduces the alternating active and quiescent phases of the regeneration cycle, demonstrating its suitability as a surrogate model for the intermittent dynamics of wall-bounded turbulence.

Living organisms, from bacteria to humans, are more likely to survive if their traits enhance fitness. In populations well adapted to their environmental niches, natural selection proceeds via rarely beneficial mutations. But when a catastrophe wipes out niche diversity, sudden adaptation often follows. Here, we present a data-validated theory of natural selection in the wake of catastrophe and unveil a simple law that emerges during recovery: the mean fitness relaxes inversely with time, with a prefactor proportional to the number of traits coupled to the post-catastrophe environment. We put our approach to test using experimental fitness landscapes measured following antibiotic administration to E. coli. The resulting mean trait adaptation is not described by gradient ascent on a fitness landscape, instead it follows an algorithm known as Levenberg-Marquardt optimization. Near fitness peaks, evolutionary trajectories are biased against greediness - from an optimization perspective, post-catastrophic selection is optimistic.

We have studied the higher-twist distributions of the proton, including T-even and T-odd transverse momentum-dependent parton distributions (TMDs). Under the umbrella of the light-front framework, we have chosen two distinctive approaches of quark-spectator systems for comparison, one inspired by the soft-wall AdS/QCD and another with a dipolar form factor at the nucleon-quark-diquark vertex. The comprehensive picture at higher-twist provided by both T-even and T-odd TMDs not only aids deeper insights into the internal structure of the proton in the quark sector but also provides an interpretation of different components of the energy-momentum tensor in quantum chromodynamics. Hence, using these standard parton distribution functions, further predictions regarding the physical insights of gravitational TMDs in momentum space are also provided.

Alloys inevitably contain interphase boundaries, whose energetics govern nucleation processes and precipitate morphology. In Cu-Ni-Si alloys, Mn addition markedly changes grain boundary (GB) precipitation behavior. While GB precipitation of stable Ni$_2$Si in Mn-free alloys is associated with degraded mechanical properties, Mn addition instead promotes film-shaped Mn$_6$Ni$_{16}$Si$_7$ (G-phase) precipitation, which is correlated improved mechanical properties. However, the atomic origin of the contrasting GB phase selection and morphology remains unclear. Here we perform machine-learning interatomic potential (MLIP) calculations to investigate the effect of interphase-boundary atomic structure on GB precipitates in Cu-Ni-Si alloys with and without Mn. The MLIP calculations reliably reproduce DFT-level energetics for interfacial bonding and microstructural configurations, and further predict that Mn addition favors GB precipitation of Mn$_6$Ni$_{16}$Si$_7$ rather than Ni$_2$Si. Experimentally, Mn-free alloys are observed to exhibit irregularly-shaped Ni$_2$Si precipitates with open-boundary-like Cu/Ni$_2$Si interfaces, whereas Mn-added alloys exhibit film-like G-phase at GBs. Large-scale atomistic interface calculations reveal that the coherent interface structure between Cu and Ni$_2$Si favors the formation of plate-like strained Ni$_2$Si precipitates in the matrix. Upon coarsening and stress release, an out-of-phase coherent-like interface can form at GBs, generating a local repulsive region that gives rise to surface-like open-boundary structures and explains the irregular morphology of GB stable Ni$_2$Si precipitates. In contrast, Cu/Mn$_6$Ni$_{16}$Si$_7$ interfaces remain predominantly incoherent with moderate boundary energies and no pronounced repulsive regime, thereby stabilizing continuous interfacial contact and explaining film-shaped GB precipitation.

In their seminal works Herglotz (1905) and Wiechert and Zoeppritz (1907) have solved the so-called Travel Time Tomography Problem (TTTP) in the 1-D case. However, the question about stability estimates and uniqueness theorems for an n-D n>= 2 TTTP with formally determined incomplete input data still mostly stands open after more than one hundred years period. \textquotedblleft Formally determined input data" means that the number p of free variables in the input data equals the number $n$ of free variables in the unknown right hand side of the governing nonliniear eikonal PDE, p=n. Some previous publications demonstrate that it is possible to develop well performed numerical methods for the TTTP with formally determined input data, which indicates the importance of such data for practical applications. This is the first publication in which the above question is addressed. More precisely, we consider a semi-discrete case, in which a PDE generated by the eikonal equation is written in finite differences with respect to n-1 variables. In addition, it is assumed that the solution of that semi-discrete PDE is represented via a truncated Fourier-like series with respect to a special orthonormal basis of functions, which depend only on the position of the point source. Under these conditions, Lipschitz stability estimate is proven, and this estimate implies uniqueness. An important tool of this paper is a new Carleman estimate. Carleman Weighted Spaces are introduced. Carleman estimates were not applied previously to address questions about stability estimates and uniqueness theorems for the TTTP.

The influence of static electric fields on the electronic structure and dissociation behavior of the polar diatomics \ce{HF} and \ce{HCl} is investigated using quantum chemical calculations. Ground- and excited-state potential energy surfaces (PESs) are computed as a function of bond distance and external electric field strength to examine field-induced modifications of chemical bonding. The calculations reveal pronounced bond softening and progressive destabilization of both molecules with increasing field intensity. Notably, the ground-state PES of \ce{HCl} becomes entirely dissociative at field strengths of approximately 450 MV/cm, whereas \ce{HF} requires a substantially stronger field of nearly 700 MV/cm to induce dissociation. This difference reflects the greater polarizability and weaker bond localization in \ce{HCl} relative to \ce{HF}, providing a molecular-scale perspective on the contrasting macroscale acid strengths of the two species. Field-dependent dipole moments further demonstrate the stronger electronic response of \ce{HCl} to external perturbations, highlighting how molecular polarizability drives electric-field-induced bond activation. Ultimately, these results map out a detailed picture of field-controlled dissociation in hydrogen halides, supporting the view that local electric fields generated by surrounding hydrogen-bonding networks play a key role in modulating bond activation and condensed-phase acidity.

Calibration of gravitational-wave detectors reconstructs the strain h(t) from the detector output, and bias and uncertainty in this reconstruction directly affect downstream analyses. In ground-based interferometers, time-dependent correction factors (TDCFs) are estimated from calibration lines to track temporal variations of the detector response, while the underlying model parameters are periodically updated using broadband swept-sine calibration measurements (SSCMs). However, if a model-measurement bias exists between the measured transfer function and the reference model, the TDCFs inferred from calibration lines can introduce a systematic deviation into the reconstructed strain. We propose a statistical framework to estimate and correct this bias using repeated measurement-to-model ratios at the calibration-line frequencies. The bias correction factors are estimated with a rolling random-effects model based on restricted maximum likelihood (REML) and incorporated into the TDCF estimation, with their uncertainty propagated to the reconstructed response. Applying the method to KAGRA O4c data, we find that the uncorrected response shows deviations of up to approximately 7% in magnitude and 5 degrees in phase relative to the SSCM-based reference in representative examples. The correction reduces these deviations, with a modest increase in the propagated uncertainty due to the included correction-factor uncertainty. This framework provides a practical way to combine broadband reference models with calibration-line-based tracking when model-measurement bias is present.

Sparse linear systems from PDE discretizations are central to scientific computing, yet no existing JAX-ecosystem solver simultaneously provides GPU-accelerated algebraic multigrid (AMG), automatic differentiation (AD), and distributed multi-GPU execution. JAX-AMG fills this gap by wrapping the NVIDIA AmgX solver suite as a native JAX primitive, exposing AMG and Krylov methods with configurable preconditioners through a unified interface compatible with JIT compilation, reverse-mode AD via adjoint methods, batched solves, and MPI-based distributed execution. Solver caching amortizes setup costs across repeated solves, making JAX-AMG practical for PDE-constrained optimization and inverse problems. The result is a robust, scalable sparse linear algebra layer that integrates seamlessly into differentiable simulation and scientific machine learning pipelines.

We present the transformation-response framework, an operational reformulation of quantum mechanics. A quantum state is not a Hilbert space object but the catalog of a system's responses to all physical transformations: for each operation $g$ from the system's local group $G$, an interference experiment gives a complex value $\chi(g)$. The collection $\{\chi(g): g\in G \}$ is the characteristic function and defines the state. The only postulate is that $\chi$ is positive-definite, encoding the requirement that no superposition of transformations yields negative probability. From this single assumption, the entire standard formalism is derived: Hilbert space via GNS construction, Born rule via Bochner theorem, Schrödinger equation from group automorphisms, and especially Feynman path integral as a Trotter limit. The framework is background-independent and time-neutral: time is a coordinate along a one-parameter subgroup of $G$. It also reveals a new physical constraint, product order positivity, which may lead to testable predictions. The framework provides a unified, economical, and falsifiable foundation for quantum theory rooted in operational primitives.

A superconducting diode effect is shown to arise in ferromagnetic superconductors through the nonreciprocal dynamics of magnetic domain walls. Specifically, we show that current-driven dynamics of a magnetic domain wall under a certain external field can exhibit a nonreciprocal Walker breakdown, possessing two distinct direction-dependent critical currents beyond which the domain wall precesses continuously. In ferromagnetic superconductors, the constant rotation of a domain wall is shown to give rise to phase slips, opening up dissipation channels, whereby the nonreciprocal Walker breakdown is mapped to the superconducting diode effect. For the nonreciprocal Walker breakdown of a magnetic domain wall, we analytically examine its dependence on the magnetic field and the Gilbert damping and verify the theoretical results with micromagnetic simulations. We then extend the analysis to ferromagnetic superconductors by considering additional effects from the superconductivity and identify criteria for experimental conditions to realize the predicted superconducting diode effect. Our work demonstrates that topological defects, such as domain walls, in magnetic superconductors can serve as an intrinsic nanoscale platform for nonlinear nonreciprocal superconducting functionalities within a single homogeneous material, circumventing the need for complicated engineered heterostructures and thereby enabling the miniaturization of superconducting devices down to the nanometer scale that is challenging to achieve with conventional Josephson junctions.

Heavy quark expansion theory provides the standard theoretical framework for understanding the lifetimes of weakly decaying heavy-flavor hadrons. Within this framework, the matrix elements of four-quark operators play a crucial role in explaining the lifetime differences among hadrons containing the same heavy quark. In this work, we calculate these matrix elements at leading order using full QCD sum rules, with particular emphasis on deriving the corresponding HQET sum rules by taking the heavy-quark limit. While this limit is straightforward for most contributions, it turns out to be rather nontrivial for certain ones. Numerical analyses show that the results obtained from the two approaches are consistent with each other. We further clarify the origin of the large discrepancies reported in the literature between full QCD sum rule and HQET sum rule results. This work contributes to a deeper understanding of the relationship between the two sum-rule approaches and is expected to facilitate future applications of QCD and HQET sum rules in the study of heavy-flavor hadrons. The findings presented here may be of interest to both practitioners of QCD sum rules and researchers working on effective field theories.

With the commissioning of the James Webb Space Telescope (JWST), near- and mid-infrared observations are rapidly extending into the wavelength regime where emission from small dust grains in circumplanetary disks (CPDs) is expected to dominate. We aim to systematically investigate how individual physical parameters of CPDs shape their infrared spectra and to improve the robustness of spectral fitting and physical interpretation of current and future observations. Building on our previous parametric CPD models, we employ a parameter-grid approach combined with radiative transfer simulations to explore the dependence of observable spectra on disk structure and dust properties. We identify the physical mechanisms responsible for the main spectral features and parameter degeneracies, and present the global trends emerging from the parameter study. We also demonstrate the applicability of the models by fitting representative observational data. Our results provide a structured theoretical framework for interpreting near- and mid-infrared observations of CPDs with JWST and related facilities.

We study the relativistic nature of the interactions that, at tree level, generate spin correlations between two electrons in Møller scattering, as well as in an extended process involving a witness particle $C$. The corresponding processes, $e^{-}e^{-}\rightarrow e^{-}e^{-}$ and $e^{-}e^{-}C\rightarrow e^{-}e^{-}C$, are analyzed both in the center-of-mass frame and, for the former process, in a Lorentz-boosted frame where Wigner rotations arise. It is found that, through a nonrelativistic approximation of the scattering amplitudes, dipole-dipole and current-dipole interactions are responsible for the emergence of these correlations. This is evidenced by the variation of the von Neumann entropy of one electron for initially separable states, and of $C$ for an initially prepared three-particle entangled W-state. In Wigner rotations, the invariance of entropy under local unitary transformations is maintained at the expense of the emergence of quantum coherence in the density matrix at large rapidities. As a consequence, the final states of both particles are evaluated and shown to encode information about the scattering process through their spin expectation values. This framework is then used to comment on the correlations in the inelastic process $e^{-}e^{+}\rightarrow\mu^{-}\mu^{+}$, for which some research has reported differing results.

The Wisconsin H$\alpha$ Mapper (WHAM) surveyed the entire Galactic sky in H$\alpha$ ($\vert v_{\rm LSR}\vert \lesssim 100\, {\rm km\,s^{-1}}$) to approximately 0.1\,Rayleigh (R), albeit with a 1-degree beam. %The resulting WHAM Sky Survey, along with large area %imaging in [\ion{S}{2}] and [\ion{N}{2}], laid the foundation for Warm Ionized %Medium (WIM) science. \cite{rcm+05} reported “point sources" which stood out against the Galactic background in space and velocity. Half of the sources are associated with plausible planetary nebulae and OB stars. Reynolds et al (2005) suggested sub dwarfs for one quarter of the sources. Here, we investigate one such source, WPS\,46, for which Reynolds et al (2005) suggested the sub-dwarf PG\,0931+691 to provide the source of ionization. With the Keck Cosmic Web Imager we found numerous nebular emission lines within the vicinity of WPS\,46, but we failed to find H$\alpha$ emission in the arc-minute vicinity of PG\,0931+691. The line ratios (BPT diagram and [\ion{S}{2}]/H$\alpha$) combined with the morphology are more consistent with AGN or LI(N)ER-like ionization than with pure warm ionized medium or \ion{H}{2} region-like photoionization. Separately, we offer compelling reasons to argue that PG\,0931+691 cannot be the source of ionizing power for WPS\,46. We suggest that WPS\,46 is associated with an intermediate velocity complex (IVC) and that H$\alpha$ and nebula emission may arise as a result of a shock. We conclude by outlining a plan of action of using SDSS's Local Volume Mapper along with deep narrow band imagery obtained by amateur astronomers to explore and study the ionized sky on sub-degree scales, in general, and specifically studies of IVC and high-velocity complexes.

Misconceptions are "alternate hypotheses" that are incorrect according to established theories of how the world works. Often held with confidence by students, they are relatively context-insensitive, can seem like common-sense views, and are noted for being resistant to remediation using traditional instruction. To find misconceptions in Newtonian mechanics, we analyze ~34,000 administrations of the pioneering Force Concept Inventory using a flexible multidimensional item-response model for multiple-choice data. In contrast to most earlier work, we allow answer choices within each question to have different directions in the multidimensional space of student knowledge, essential for concept inventories in which distractors often codify distinct misconceptions. We uncover 22 robust, partly-overlapping dimensions whose distractors share a coherent theme identifiable with a misconception or misunderstanding. Motivated by the realization that many mirror previously-accepted theories of mechanics, we broadly sort these by historical era: Ancient (learned by infants but codified by Greeks), Medieval (reactions and extensions of Aristotelian ideas), and Post-Newtonian (including known modern misconceptions as well as two which appear novel). We also present a simple approach for computing "misconception scores" for students and classes. Examining these scores before and after instruction reveals surprisingly varied patterns of remediation in our sample: some misconceptions persist largely unchanged by instruction, while others are better remediated in below- or above-average students. In general, we find that many misconceptions are poorly remediated for students of average or lower ability. We hope our work will serve as a guide for developing, evaluating, and improving interventions for these while providing physics instructors with a valuable tool for class-level formative assessment.

Cellular automata (CA) are widely used to study how simple rules generate life-like behavior, typically through local interactions. Here, we introduce a Separable-Field Cellular Automaton (SFCA), in which conventional local-neighborhood interactions are replaced by updates governed by a normalized global coupling field. Each cell is updated according to q = n/n_max, with survival and birth controlled by threshold intervals S and B. Systematic scans over interval widths and positions revealed four outcome classes: extinction, fixed points, cycles, and long transients. The phase diagram was organized by the relative geometry of S and B: fixed points were enriched when B was contained within S, whereas long transients concentrated near the boundary between partial overlap and no overlap. A fine scan across this transition revealed a narrow long-transient ridge separating two distinct cycle-dominated regimes: a dense, high-change-rate branch approximating global period-2 alternation and a sparse, low-change-rate, stripe-like branch. Damage-spreading analyses were consistent with delayed selection between these cyclic attractor families and provided no evidence for sustained exponential trajectory separation. Finite-size analyses showed that the ridge persists across all tested lattice sizes, although its position shifts systematically with system size. These results show that structured long-lived dynamics can arise under separable global coupling with a field matrix of rank at most one, suggesting that nontrivial collective organization can persist under strongly compressed interaction architectures.

We analyze five-neighbor particle cellular automata whose conventional two-dimensional fundamental diagrams are multivalued, but whose mean flow is uniquely determined by introducing a second density. We first consider binary rules for which the second density is conserved, and then examine rules for which the second density is not conserved but converges asymptotically. These examples give three-dimensional fundamental diagrams in which the mean flow is determined by the particle density and the second density. We then investigate whether this single-valued structure is preserved under real-valued max-plus extensions. There are some rules where two different max-plus extensions are introduced, and numerical simulations show that both extensions preserve the same single-valued three-dimensional fundamental diagram. These observations imply that, in constructing real-valued max-plus extensions, it is important to choose the flux function and the second density consistently.

The sub-parsec proximity around the Sgr A$^\star$ supermassive black hole (SMBH) in the center of the Milky Way contains an inner cluster of eccentric S-stars with randomly oriented orbits, a midway-disk of clockwise-rotating stars (CWSs), and a surrounding population of off-the-disk stars (ODSs). Despite their diverse kinematic properties, all three-populations appear to be massive (WR/O/B types) and have similarly limited life span $\tau_\star \sim 6-15$ Myr. Several scenarios, including star formation induced by SMBH's close encounters with one or more gas clouds as well as impulsive close scattering by a putative intermediate-mass companion (IMC) of Sgr A$^\star$ possible an intermediate-mass black hole (IMBH), have been proposed to explain piecemeal for the origin and dynamical evolution of S-stars, CWSs, ODSs, as well as hyper-velocity stars in the Galaxy. But, their coexistence and the origin of a recently discovered zone of avoidance in S-stars' eccentricity-peri-centric-distance distribution remain enigmatic. Here, we construct a unified model to comprehensively take into account these stars' interaction with each other, their single natal disk, and an independent IMC. We show their disparate present-day orbits would only be concurrently attainable, within their multi-Myr age, under the combined influence of IMC's secular perturbation and these stars' resonant relaxation in a depleting gaseous-disk environment.

Surface-level reactor antineutrino experiments usually have substantial cosmic ray induced neutron backgrounds, particularly with shallow overburden. The Array of Lattice for Anti-neutrino Reactor Monitoring (ALARM) is a plastic scintillator based experiment designed for reactor power monitoring. It will be deployed about 44 m from the core of a reactor at the Taishan Nuclear Power Plant. Placed at a depth of 9.6 meters below the surface, cosmic ray induced fast neutrons constitute a significant background, making an effective neutron shielding system essential for the experiment. For the shielding design of ALARM, we tested the shielding performance of three materials water, HDPE, and 40% boron-doped HDPE (BHDPE) against both fast and thermal neutrons. A thermal neutron detector composed of an EJ426 scintillator setup was first used to measure the shielding efficiency of these materials at various thicknesses using neutrons from an Am-Be source. A 30-cm thickness of BHDPE achieved a shielding efficiency exceeding 95% for both fast and thermal neutrons. Monte Carlo simulations of the EJ426 setup yielded results consistent with the experimental data. Simulation results for the shielding performance of the full ALARM shielding assembly are also presented.

The structural properties of bosonic dark matter stars are systematically investigated, presenting precise scaling relations for the mass, radius, central density, and the properties of dark matter particles. The dark matter equation of state is derived from a complex scalar field theory with a quartic self-interaction potential $V(\phi) = \frac{\lambda}{4} |\phi|^4$, considering boson masses $m_{\phi}$ ranging from $10^{-9}$ to $10^{3}$ GeV and self-coupling constants $\lambda$ ranging from $0.01\pi$ to $100\pi$. The scaling relation for the maximum mass of bosonic dark matter stars, the corresponding critical radius and critical central density are obtained as \[ M_{\text{max}} = 0.1 \frac{\sqrt{\lambda}}{m_\phi^2} M_\odot, \qquad R(M_{\text{max}}) = 0.9 \frac{\sqrt{\lambda}}{m_\phi^2} \ \text{km}, \qquad \varepsilon_{\text{max}} = 2.1 \times 10^5 \frac{m_\phi^4}{\lambda} \ \mathrm{MeV/fm^3}, \] where $m_\phi$ is in GeV, the relations for $R(M_{\text{max}})$ and $\varepsilon_{\text{max}}$ are first put forward. The fitting relative error is less than $4\%$. Based on these scaling relations, we further provide global analytical fits for the stable branch. The relationships between mass and central density as well as radius and central density can be described by a unified function of the form: \[ \tilde{Y} = \frac{A}{\left[1 + \left(5\tilde{\varepsilon}\right)^h\right]^s}, \] where for $Y=M$, $\tilde{M} \equiv M/M_{\text{max}}$, $A=1$, $h=-2$, $s=0.42$; for $Y=R$, $\tilde{R} \equiv R/R(M_{\text{max}})$, $A=1.634$, $h=1$, $s=0.28$; and $\tilde{\varepsilon} \equiv \varepsilon_0/\varepsilon_{\text{max}}$. The fitting relative error is less than $0.1\%$. Furthermore, we find a simple quadratic polynomial mass-radius relation for bosonic dark matter stars.

Nuclear bound-state $\beta^-$ decay ($\beta_{\text b}$ decay) is a novel weak-interaction process that becomes possible when atoms are highly ionized, such as in stellar environments or heavy-ion storage rings. In this work we present a systematic theoretical calculations for the $\beta_{\text b}$-decay half-lives of interesting candidates for the first time, where both allowed Gamow-Teller transitions and first-forbidden transitions are taken into account by the microscopic projected shell model, and the lepton phase space is calculated by the Takahashi-Yokoi model. We analyzed the structure informations for hundreds of nuclei near the $\beta$-stability line, and select 16 interesting candidates belonging to two categories, i.e., nuclei with negative $Q$ values and positive $Q$ values in neutral atoms respectively. Among these candidates, we recommend $^{243}\mathrm{Am}^{95+}$, $^{194}\mathrm{Os}^{76+}$, $^{227}\mathrm{Ac}^{89+}$, $^{228}\mathrm{Ra}^{88+}$, $^{241}\mathrm{Pu}^{94+}$, $^{247}\mathrm{Cm}^{96+}$ and $^{250}\mathrm{Cm}^{96+}$ as promising ones for future studies of storage-ring experiments because their $\beta_{\text{b}}$-decay half-lives are predicted to be much shorter than the half-lives in neutral atoms. These findings provide essential nuclear inputs for astrophysical models and identify specific candidates where experimental verification would be most valuable.