Papers

We observe a ball bouncing down a Galton board with any number of directions. At each peg it either keeps its direction with some fixed probability or randomly turns to one of the other directions. Its bin measures how often it went each way, a point of a simplex. When the ball rarely turns, the most likely bins are the corners, which only a ball that never turns can reach. We ask when the best bin of each face of the simplex becomes as likely as a corner. To first order every face catches up at the same moment. We break this tie at second order, with an explicit constant for each face. Hence on a long board, as the expected number of turns grows to any fixed multiple of the length's logarithm, the most likely bin jumps once, from the corners straight to the center. A nonuniform start or a weak external field changes the constants, potentially allowing an intermediate face to win.

Supercooled first-order phase transitions provide an attractive framework for generating observable gravitational waves (GWs), but the accompanying entropy injection dilutes any pre-existing baryon asymmetry, motivating baryogenesis during or after the phase transition. Cold baryogenesis offers a promising mechanism in which bubble collisions generate Higgs winding configurations and the Chern-Simons number through out-of-equilibrium dynamics. In the present study, we perform three-dimensional lattice simulations of a two-field model where the scalar field responsible for the phase transition is separated from the Higgs sector. Using realistic initial conditions obtained from bounce solutions, we follow the bubble expansion and collisions and study the generation of Chern-Simons number. It is found that efficient Chern-Simons production persists even for strongly non-degenerate potentials with large latent heat, which are favorable for enhancing GW signals. We also estimate the resulting baryon asymmetry using the simulated Chern-Simons dynamics and an effective CP-violating operator. Our results demonstrate that cold baryogenesis remains viable in the strongly supercooled regime, providing an important step toward establishing baryogenesis from cosmological first-order phase transitions.

The spin density and Josephson current at equilibrium are studied numerically in a superconductor-normal metal-superconductor (SNS) junction with extrinsic spin-orbit interaction in the N segment. This system preserves structural inversion symmetry. We find that the Josephson current generates the spin Hall effect, resulting in an opposite spin density near the two edges of the N segment. We also find that a Zeeman magnetic field with gradient applied to the N segment generates an anomalous phase shift due to the inverse spin Hall effect, resulting in a diode effect when higher harmonics of the Josephson current are present. These results are consistent with those of a previous theoretical study based on diagrammatic perturbation theory. We find that the diode effect becomes more pronounced when stronger coupling between the N and S segments enhances the higher harmonics.

Pure gravity quantum gravity (pure gravity QG) is non-renormalizable at two and higher loop level. One of the main characteristics of objects occurring in QG is their Lorentz covariance. QG necessitates the analysis of a collection of Lorentz covariant terms of higher and higher order, which is not feasible using renormailization. This paper describes how the regularization technique known as covariant spectral regularization (CSR) can be used to analyze Lorentz covariant 4-tensor valued measures on Minkowski space. The graviton vacuum polarization tensor is cast as such a measure and CSR is used to obtain a well defined and finite function representing this tensor. This is then used to compute the Feynman amplitudes for examples of one-loop, two-loop and $n$-loop graviton-graviton scattering in pure gravity QG. The CSR method results in functions (densities) representing divergent Feynman integrals without requiring renormalization or counterterms. Therefore it can be used to analyze arbitrarily complicated multiloop QG Feynman diagrams without being crippled by a proliferation of counterterms, as is classical QG.

We investigate sorted mutability, $\zeta_S$, as an information-based quantity with an explicit entropic character. We show that $\zeta_S$ is directly proportional to the diversity of a data sequence and can therefore be expressed in terms of Shannon entropies, establishing a connection between compression-based measures and conventional information theory. In contrast to regular mutability, which preserves the sequential ordering of the data, sorted mutability removes this ordering and provides a static characterization of the distribution of observed values. We illustrate these properties in two complementary settings: the two-dimensional ferromagnetic Q-clock model and wind-power production data. For the Q-clock model, sorted mutability and diversity display the same temperature dependence, consistent with their analytical relation, while conventional thermodynamic observables provide an independent reference. In the case of wind power, we report monthly results for sorted mutability and diversity, showing proportional time evolutions. These results support sorted mutability as a useful, easy-to-calculate entropic functional for analyzing both equilibrium and non-equilibrium data sets.

Natural supercavitation behind conical cavitators generates a vapor-filled envelope that, when sustained over the full body of a high-speed underwater vehicles, reduces hydrodynamic skin-friction drag and enables performance levels unattainable in fully wetted flow. Accurate prediction of maximum cavity length and maximum cavity radius and local cavity profile as functions of cavitation number and cone half-angle is essential for both the static design and the real-time shape management of super-cavitating torpedo cavitators. Classical analytical models provide computationally inexpensive predictions but exhibit systematic disagreements in the practically important regime of moderate cavitation number and large angle, where slender-body assumptions begin to break down. Existing data-driven machine learning approaches offer higher accuracy but are constrained by the prohibitive cost of multiphase computational fluid dynamics (CFD) sweeps over the full design space. This study proposes a physics-guided multi-fidelity surrogate framework based on Extended Hierarchical Kriging (PG-EHK) that addresses this challenge by fusing the multiple competing analytical cavity formulas as non-level low-fidelity (LF) trend functions corrected by a sparse set of high-fidelity (HF) CFD data. It simultaneously incorporates the analytical models regardless of their local fidelity ordering, using Bayesian-estimated scaling factors to construct the trend function as physical baseline. The resulting surrogate maps operational condition inputs to cavity geometry responses using fewer than 20 high-fidelity CFD evaluations. Cross-validation on five independent hold-out CFD cases demonstrates that the proposed PG-EHK surrogate achieves 61% reduction in prediction error compared to the best-performing individual analytical approach.

Rapid advances in AI have opened a new era for physics, enabling unprecedented capabilities in research and discovery. However, these advances also bring challenges in verifying, trusting, and reusing the results they so rapidly produce. Formalization is a necessary part of the solution to these challenges. In this paper, as well as giving an overview of the role of AI and formalization in physics, we make the case that: (1) formalization is an essential layer for AI-driven discoveries in both computational and theoretical physics; (2) AI is lowering the barrier to, and increasing the efficiency of, formalization in physics, though it remains weaker at choosing definitions and designing libraries than at writing proofs; (3) the speed AI brings to formalization in physics currently comes at the cost of trust, credit, and community; (4) shared, community-reviewed formal libraries such as Physlib should be central in making progress in this field, both as a trusted, reusable foundation for physics results and as the environment in which AI systems can reason about physics; (5) formalizing physics raises challenges beyond those in mathematics, most importantly that a checked proof does not establish that its definitions faithfully capture the intended physics. We also give our perspectives on near-term and long-term directions in these areas.

Nearby compact gamma-ray sources can move appreciably during the Fermi-LAT mission and thus evade searches that assume a stationary sky. Compact dark matter halos, dark matter spikes around primordial black holes (PBH), and evaporating PBH provide potential examples. We perform a novel all-sky search for steady point sources moving at 0.25 deg/yr-0.8deg/yr in ten years of 1-100 GeV Fermi-LAT data. For a transverse speed of 200 km/s, this angular range probes distances of roughly $3.0\times10^3$ AU to $9.7\times10^3$ AU. We find 577 candidate tracks, consistent with $533\pm27.0$ tracks in time-scrambled skies. We place a model-independent 90% upper limit of 80.8 recovered signal tracks. At peak calibrated sensitivity, this corresponds to fewer than 123 steady, full-sky sources with an incident $E^{-2}$ photon spectrum. We give the calibrated detection efficiency of the search to steady point sources and use it to derive illustrative constraints on both evaporating PBHs and PBHs surrounded by annihilating dark matter halos.

acousticHelmholtzFoam is an OpenFOAM application that computes time-harmonic acoustic pressure fields in heterogeneous gas-liquid media on unstructured polyhedral meshes. The complex pressure is stored as real and imaginary volume fields, the material coefficients are constructed from a volume-of-fluid phase fraction with geometric face-fraction averaging, and open boundaries are truncated by Cartesian perfectly matched layers (PMLs) whose damping tensor is generated by the companion utility setPMLFields. The two coupled real-valued equations are discretized with the cell-centred finite-volume operators of OpenFOAM and assembled explicitly, including processor couplings and boundary contributions, into a distributed PETSc matrix that is solved by default with the MUMPS sparse direct solver. The solver writes pressure amplitude, complex velocity, acoustic radiation pressure and time-averaged momentum flux for acoustic-force evaluation. This paper documents the implemented equations, the case interface, the assembly and solution algorithm, the build procedure and the test infrastructure. A layered gas-liquid-PML case with an analytical solution serves as an end-to-end regression: on 8000 cells the whole-domain relative complex-pressure error is $1.197\times10^{-3}$, and serial and MPI solutions on up to eight ranks agree to within $10^{-12}$ in relative $L_2$ norm. A single-axis acoustic-levitator height sweep with constant-volume spheroidal drops demonstrates the two-phase material input and the force output, and strong- and problem-size-scaling measurements characterize the direct-solver workflow. The numerical formulation and its verification are presented in a companion paper (arXiv:2610.01593).

We investigate intra-chain exciton energy transfer (EET) in a conjugated polymer using a reduced three-level donor-acceptor model that separates vertical excitations from vibrationally relaxed states. Population dynamics are obtained with the hierarchical equations of motion (HEOM), enabling a non-Markovian treatment of system-bath (S-B) interactions. Case studies on donor-acceptor (D-A) pairs with small and large energy gaps reveal competition among coherent hopping, vibrational relaxation, and Förster resonance energy transfer (FRET). Varying the hopping and the S-B relaxation rate highlights roles of exciton transfer, thermal relaxation, and dipole-mediated coupling. The results show that energy gap, hopping, and relaxation jointly control intrachain EET.

We examine a Planck-scale regular black-hole remnant in neutron-star matter using a T-duality-inspired effective geometry and explicitly separate geometrical results from assumptions about absorption and emission. Within the static family, the surface-gravity temperature grows as $(M-M_{\rm ext})^{1/2}$ after a small mass increase. A constant-greybody Stefan–Boltzmann approximation gives a Hawking power proportional to $(M-M_{\rm ext})^2$ and can produce a stable lower balance point and an unstable growth threshold under stated hypotheses. For $l_0=\ell_{\rm Pl}$, however, the formal lower equilibrium has an excess mass of only $10^{-45}$–$10^{-46}\,\mathrm{kg}$ for order-unity absorption efficiency, so the canonical description is inconsistent with individual neutron captures. For a fiducial area-scale absorption cross section with unit coefficient, the mean capture interval is $5.4\times10^8\,\mathrm{yr}$ and the initial nonradiating growth timescale is $9.1\times10^{27}\,\mathrm{yr}$. Under this assumption, a Planck-mass remnant inside a neutron star is therefore effectively inert and, without additional feeding, cannot destroy the star within the age of the Universe. A stationary capture–relaxation state additionally requires an effective microscopic emission law; it is not established by zero temperature alone. Hydrodynamic accretion requires control of wave effects and a mean-free-path criterion; its onset corresponds to masses of order $10^{11}$–$10^{12}\,\mathrm{kg}$ for representative matter parameters. Direct zero-point-length corrections there are negligible, of order $10^{-40}$ at a femtometre. We discuss conditional growth thresholds, critical slowing near an unstable balance, dark-matter feeding, angular-momentum transfer, and the requirements for neutron-star survival constraints.

The existence of energy is the main criterion for (i) providing a common core to the materiality of all types of classical matter and (ii) denying that the gravitational field of General Relativity is a type of matter. Extending this criterion to quantum field theory, though formally straightforward, carries new conceptual consequences for the interpretation of gravity. Renormalization of the quantum matter stress-energy tensor forces a local, purely geometric term, built from the metric alone, into the conserved stress-energy, and this has two faces. It grants the metric a material significance alongside its spatio-temporal one (the egalitarian view); and it binds gravitational to non-gravitational energy so tightly that the two cannot be split apart without a choice of vacuum that a generic spacetime does not supply (the unificationist view). The latter poses a dilemma: either gravitational energy is meaningless, but then so is the energy of the non-gravitational quantum fields, and only classical fields remain matter; or both are meaningful, and the metric thereby acquires the material significance of a matter field. On neither horn does the classical divide between matter and spacetime survive quantization.

The Search for Extraterrestrial Intelligence programme aims to find evidence of extraterrestrial intelligence. SETI scientists pursue this objective by searching for technosignatures primarily in the radio or optical spectrum. The IAA SETI Committee has been developing protocols to offer guidelines in case of an actual extraterrestrial signal reception. These protocols establish procedures to confirm the authenticity of the signal and its actual extraterrestrial nature, as well as the committee's role in managing the discovery in relation to the scientific community and the general public, targeting scientific queries in relation to the management and development of equipment and methodologies employed in current SETI search. The project A Sign in Space part 2 aims to actively engage the global SETI community and the global telescope network, with scientific facilities responding and coordinating themselves to confirm the extraterrestrial nature of the received signal. The project develops some of the societal, scientific and technological methodologies already employed in the interdisciplinary work A Sign in Space. Here, we established a global collaboration between SETI scientists, radio observatories and the European Space Agency to test the communication and technological pipeline and protocols leading to the reception of a simulated extraterrestrial signal by a network of radio telescopes across the globe. We also employed an ESA spacecraft for system validation. A Sign in Space part 2 aims to further implement deep space technologies in SETI search through a structured and sustained programme, in collaboration with ESA, the SETI Institute and the Italian Institute for Astrophysics. The project will aim to stage and test the entire Post Detection procedure, implementing the protocol as envisioned by the IAA SETI committee.

We investigate cosmological constraints on a $(3+1)$ neutrino framework containing an additional partially thermalized, eV-scale sterile neutrino alongside the three active species. Rather than assuming full thermalization, we allow the sterile abundance to vary independently through its physical mass $m_s$ and contribution $\Delta N_{\rm eff}$ to the effective number of relativistic species. The sterile state is modeled as a thermally distributed non-cold relic with a temperature below that of the active-neutrino background. We consider flat and non-flat $\Lambda$CDM and $w_0w_a$CDM cosmologies, all including the same $(3+1)\nu$ sector. The models are constrained using Planck 2018 CMB data, DESI DR2 BAO, Pantheon+ Type Ia supernovae, a conservative compilation of $f\sigma_8$ measurements, and the recent H0DN. Oscillation-informed priors are imposed on the active-neutrino mass splittings, while the eV scale sterile-mass range is motivated by short-baseline oscillation searches and global $(3+1)$ analyses. We find that allowing additional freedom in the late-time cosmological background substantially changes the inferred sterile-neutrino sector. The effective sterile mass increases from $m_{s,\rm eff}\sim0.11\pm0.05~{\rm eV}$ in flat $\Lambda$CDM$+(3+1)\nu$ to $\sim0.35\pm0.12~{\rm eV}$ in the non-flat $w_0w_a$CDM$+(3+1)\nu$ model. The corresponding sterile abundance shifts from $\Delta N_{\rm eff}\lesssim0.1$ to $\Delta N_{\rm eff}\simeq0.35\pm0.15$, while remaining well below the fully thermalized limit, $\Delta N_{\rm eff}\simeq1$. The non-flat $w_0w_a$CDM models also show $\sim 2.8\sigma$ preference for open spatial geometry, $\Omega_k\simeq0.0045\pm0.0016$, and yield $H_0\simeq70.9\pm0.7~{\rm km\,s^{-1}\,Mpc^{-1}}$ and $S_8\simeq0.785\pm0.015$. These models improve the minimum $\chi^2$ by approximately $21$-$25$ relative to flat $\Lambda$CDM$+(3+1)\nu$.

When computing tree-level amplitudes of the nonlinear sigma model (NLSM) via the BCFW on-shell recursion relation, boundary terms are inevitable. Here, the BCFW recursion relation refers to the original prescription with momentum-shifts on two external legs, as opposed to the generalized versions with redefined momentum-shifts. We propose a simple general scheme that determines the boundary terms of NLSM amplitudes recursively from lower-point amplitudes. Hidden zeros and mass dimensions severely constrain boundary terms, allowing us to compute these terms from the $2$-split property of the tree amplitudes. Combined with the existing rules in the literature for obtaining the two currents in the $2$-split from on-shell amplitudes, this scheme enables the recursive construction of boundary terms for higher-point amplitudes from lower-point amplitudes.

A recent ALICE measurement reports a finite strangeness enhancement in the toward-leading region of high-multiplicity proton-proton collisions. In this work, the trigger transverse momentum, $p_{\rm T}^{\rm trigg}$, dependence is investigated using ${\rm K}^{0}_{\rm S}$ and $\Xi^{\pm}$ production in PYTHIA8, with and without color ropes, and EPOS-LHC. For $3 < p_{\rm T}^{\rm trigg} < 15$~GeV/$c$, EPOS-LHC and PYTHIA8 with color ropes exhibit a multiplicity-dependent increase of the toward-leading $\Xi^{\pm}/{\rm K}^{0}_{\rm S}$ ratio, while the rope-free PYTHIA8 baseline shows a weaker dependence. With increasing trigger momentum, the enhancement is strongly suppressed in EPOS-LHC for $p_{\rm T}^{\rm trigg}\gtrsim10$~GeV/$c$, whereas it remains approximately unchanged in PYTHIA8 with color ropes. This contrasting behavior is consistent with a reduced core contribution in EPOS-LHC and a local string-overlap mechanism in PYTHIA8 with color ropes. The trigger transverse momentum thus provides a model-sensitive probe of the mechanisms contributing to the apparent strangeness enhancement in the jet-like region of the pp collisions.

The problem of incompressible fluid mixing is long-studied, yet many questions remain open. This paper aims to address the question “what do efficient flow fields for mixing look like, and how do they behave?” Inspired by the dynamic and geometric approach to optimal mass transport, we formulate a version of the fluid mixing problem as an optimal control problem for transport of a passive scalar, in which the dynamics are given by the continuity equation together with an incompressibility constraint. We then develop a geometric framework around this problem which parallels that of classical optimal transport: the optimal control problem induces a metric on the set of reachable states (analogous to the Wasserstein metric), and this metric carries a formal Riemannian structure when the optimal control objective is induced by an inner product. Using this structure, we decompose our problem into a series of more fundamental geometric problems and derive (formal) necessary conditions for optimality, geodesic equations, and gradient flows for mixing. Specializing the control objective to the kinetic energy recovers the incompressible Euler equation, connecting our framework to the geometric hydrodynamics of Arnold. The resulting problem appears to be ill-posed, however, suggesting that the kinetic energy is an unnatural measure of mixing effort. Specializing instead to the enstrophy, which we argue is better suited to mixing, yields the Euler-Poincaré (EPDiff) geodesic equation for the right-invariant homogeneous $\dot{H}^1$ metric on the group of volume-preserving diffeomorphisms, and we present numerical simulations of both geodesics and gradient flows in this case. Along the way, we generalize the classical Helmholtz decomposition of vector fields, rederive the Clebsch representation of incompressible flows, and develop a parallel to the Otto calculus of optimal transport.

Achieving nanoscale light confinement and long-range propagation is a central challenge in nanophotonics, with important implications for controlling molecular photophysical processes and energy transfer. Monolayer transition-metal dichalcogenides (TMDs) support in-plane exciton-polaritons (IPEPs), deeply subwavelength optical modes in the visible range. In this regime, electromagnetic fields vary on length scales comparable to the exciton size, making spatial nonlocality in the excitonic optical response essential. Here, we develop a microscopic theory of the nonlocal excitonic optical response and investigate the near-field properties of IPEPs in hexagonal boron nitride (hBN)-encapsulated monolayer WS$_2$. Combining a two-band massive Dirac fermion description with a generalized Mott-Wannier treatment, we derive a nonlocal electric susceptibility that accounts for both the center-of-mass and internal relative motion of excitons. Spatial nonlocality in the excitonic optical response shifts the polariton dispersion toward lower in-plane wavevectors compared with the results based on the local-response approximation. This reduces high-wavevector contributions and produces smoother near-field distributions that extend over larger lateral distances while retaining nanoscale confinement. Furthermore, at higher excitation energies, multiple exciton-polariton modes contribute at distinct wavevectors, and their relative contributions can be tuned by varying the thickness of the capping hBN layer. These insights elucidate the fundamental role of spatial nonlocality in the polaritonic properties of van der Waals heterostructures.

Uncertainty quantification in machine learning models is essential for nuclear energy applications. While machine learning models can make both uncertainty and point predictions, these models are often significantly more difficult to train jointly than models that make point predictions alone. Split conformal prediction is a family of methods for computing distribution-free prediction intervals by calculating nonconformity scores corresponding to a target quantile in a calibration dataset. Although conformal prediction only guarantees marginal coverage, normalizing nonconformity scores enables predictive interval widths to be calculated on a per-sample basis, providing an approximation to conditional coverage. In this work, we connect uncertainty predicting neural networks to pre-trained networks that estimate shielding factors in multigroup neutron cross sections. We train the uncertainty models on the same OpenMC data used by the pre-trained models, whose weights and biases remain fixed. The outputs of the uncertainty models are the standard deviations of the residual, separated into contributions from the model and tally uncertainty. Their corresponding variances are combined in quadrature to provide a normalizing factor for conformal prediction, providing interval widths that are adaptive on a per-sample basis. Baselines for comparison are established using Mondrian conformal prediction, and by using the ground truth OpenMC uncertainties as normalizers in the conformal framework. We use predicted uncertainty interval widths and the severity of predictions that overshoot the interval widths as bases for comparing our normalizer with the baselines. We find that our method dramatically reduces both interval widths and the degree to which predictions fall outside these widths.

Quasicrystals reveal that long-range order can exist without translational periodicity, but deterministic routes for designing strongly bonded quasicrystalline interfaces remain unexplored. Here, we show that such interfaces can be engineered by growing epitaxial SrTiO3 membranes on a sacrificial layer, releasing them, twisting them by prescribed angles, and bonding them onto a chosen substrate. SrTiO3 bilayers twisted by 45{\deg} form an octagonal quasicrystalline interface with eight-fold rotational symmetry, whereas trilayers assembled with successive 30{\deg} rotations form a dodecagonal interface with twelve-fold symmetry. Selected-area and nano-beam electron diffraction, multislice electron ptychography, atomic-resolution dark field imaging, Fourier analysis, and real-space tiling establish long-range quasicrystalline order with electronic reconstruction evident from electron energy-loss spectroscopy after annealing. Atomistic simulations based on machine-learned interatomic potentials show that octagonal order emerges as the bilayer twist angle approaches 45{\deg}. Polarization-dependent X-ray absorption spectroscopy in 1.5 nm twisted bilayers reveals a twist-dependent electronic response, and terahertz-field-induced second-harmonic generation circular dichroism identifies a symmetry-dependent nonlinear optical response at the 45{\deg} quasicrystalline condition. Twisted oxide membranes therefore provide an extendable route to engineer quasiperiodic order and couple it to interfacial bonding, orbital reconstruction, and nonlinear optical response in complex oxides.

We study the logarithmic corrections to the asymptotic trajectories of massive particles. These corrections enter the calculation of the soft-log sector of the radiative field at null infinity in four-dimensional gravitational scattering. We first isolate the part of the metric which enters the particle equations of motion. We show that the nonlinear source can only affect this sector through homogeneous modes on the hyperboloid, and that matching to the proposed soft tower implies that these modes vanish, except for the first mode. We show that this mode cannot affect the trajectory coefficients at leading order in $G$. We then invert the matter energy-momentum tensor on the particle worldlines to obtain the trajectory coefficients at leading order in $G$ and at every logarithmic order using Legendre polynomials. The first two coefficients reproduce the known results at orders $G$ and $G^2$.

Rare-earth substitution strongly modifies the structure, metallicity, and superconducting behavior of Ruddlesden-Popper (RP) nickelates, but its impact on their magnetic interactions remains unclear. Here, we combine x-ray absorption spectroscopy (XAS) and resonant inelastic x-ray scattering (RIXS) to resolve the multiorbital electronic structure and magnetic excitations of Pr$_4$Ni$_3$O$_{10}$. The absence of an overlapping rare-earth resonance provides direct access to the Ni $L_3$ edge, while polarization-dependent measurements at the Ni $L$- and O $K$-edges resolve distinct planar and out-of-plane Ni-O hybridization channels. Momentum-resolved RIXS reveals dispersive magnetic excitations that soften toward the incommensurate spin-density-wave wave vector. An effective spin-wave analysis yields a sizable intra-trilayer exchange coupling, comparable to the leading in-plane interactions and robust against rare-earth substitution. Our results identify the multilayer architecture, rather than rare-earth substitution alone, as a key control knob of the magnetic interactions in these materials.

Active rods are elongated, self-propelled particles that serve as effective models for motile microorganisms, such as bacteria and sperm cells. When confined to a microfluidic channel, active rods exhibit a distinctive motility pattern: they tend to swim against the fluid flow along channel walls. In pressure-driven channel flow, they alternate between long upstream runs along the walls and short downstream spurts in the bulk. This behavior has practical implications for bacterial contamination of catheters and microfluidic devices against the flow. We study the spreading of a population of active rods along long microchannels using a hierarchy of models. Monte Carlo simulations of a three-dimensional model show that net upstream transport depends non-monotonically on the flow rate, decreases with rotational diffusion, and depends on the shape of the channel cross-section. The simulations also show that upstream and downstream persistence times follow exponentially decaying distributions. This motivates the derivation of a one-dimensional, two-state velocity-jump model. For exponentially distributed persistence times, we derive the evolution equation for the concentration of continuously injected rods and determine its long-time limit in closed form. This analysis reveals a concentration plateau upstream of the source when the mean upstream velocity is positive and exponential decay otherwise. Using parameters measured from the three-dimensional simulations, the one-dimensional model reproduces the concentration profiles from the Monte Carlo simulations, and these results are consistent with recent experimental observations of bacterial contamination in microfluidic devices.

Interpreting GW190521 remains challenging due to its exceptionally high total mass and correspondingly small number of observable gravitational-wave cycles, which gives rise to degeneracies between different physical interpretations. Motivated by the outstanding questions surrounding the event, we present a comprehensive reanalysis of GW190521 using waveform models drawn from multiple families, including a model that includes both eccentricity and spin-precession. We find evidence that the source was highly eccentric, with an inferred eccentricity of $0.81^{+0.05}_{-0.01}$ at 5 Hz, and show that non-eccentric interpretations arise from failing to probe the high-likelihood region at large eccentricities. We further demonstrate that when eccentricity is included in the analysis, there is no indication of spin precession, suggesting that the apparent precession in quasicircular analyses is at least partially driven by an eccentricity–spin-precession degeneracy. While all waveform models favor a comparable-mass binary, one model admits a secondary mode at more asymmetric masses. We find a robust probability $(\geq97\%)$ that the primary black hole lies within the pair-instability supernova mass gap ($\sim60-130\,M_\odot$), whereas the probability that the secondary lies in the gap depends on the waveform model. Through inference of GW190521-like injections, we show that the waveform systematics observed in the analysis of GW190521 could arise from the response of models to unmodeled eccentricity, rather than from intrinsic differences between waveform models. When analyzing a quasicircular spin-precessing injection similar to GW190521, we find no significant model dependence in the inferred parameters. Finally, because the inferred eccentricity lies beyond the calibration regime of current models, we test its robustness by recovering highly eccentric numerical-relativity waveforms.

Uncertainty quantification in thermoreflectance measurements of multilayer structures is challenging because thermophysical-property extraction involves nonlinear inverse problems with strongly coupled parameters. Covariance-based analytical propagation is efficient but assumes local linearity and approximately Gaussian fitted variables, whereas Monte Carlo (MC) propagation captures non-Gaussian behavior but is computationally expensive and can be unreliable when simultaneously fitting parameters spanning very different orders of magnitude. Here, we address these issues by combining normalized MC sampling, used to obtain reliable benchmark distributions, with physics-based variable transformations for analytical uncertainty propagation. From the multilayer heat-diffusion equation, we identify natural coordinates: the interfacial thermal resistance 1/G, the substrate combinations sqrt(k_z k_r) and sqrt(k_z C), and the thin-film combinations k_r/C, hC, and Ch^2/k_z. Across several representative multilayer systems and thermoreflectance modalities, these coordinates are approximately Gaussian even when the original physical parameters are skewed. Performing covariance-based propagation in the transformed space and mapping the results back to physical parameters yields asymmetric confidence intervals that closely match normalized MC benchmarks. The approach preserves the non-Gaussian uncertainty structure of the recovered parameters while avoiding repeated nonlinear refitting, providing a fast and physically interpretable methodology for thermoreflectance uncertainty quantification in multilayer systems governed by diffusive heat conduction.

Plasma edge simulations with codes like EMC3-EIRENE are widely used to study fusion magnetic confinement devices. However, numerical errors can significantly impact the simulation solution and are often insufficiently characterized. These errors consist of the statistical error, bias, and time integration error, resulting from the finite sampling and tracking of Monte Carlo particles, and the discretization error, resulting from a finite grid resolution. This work presents the first comprehensive numerical error analysis of EMC3-EIRENE simulations in stellarator geometries, focusing on edge plasmas in the Helically Symmetric eXperiment (HSX). Fundamental plasma and neutral quantities are analyzed, and error reduction rates are compared against theoretical expectations. The statistical error, bias, and time integration error are fully characterized; however, quantification of the discretization error remains challenging because of the complex grid geometries used in EMC3-EIRENE. The commonly used volume averaged relative change metric is shown to systematically underestimate the statistical error, highlighting a critical flaw in EMC3-EIRENE analysis, where convergence is claimed despite significant noise remaining in the simulation solution. Dominant contributions of the time integration error are shown to differ in stellarator simulations compared to tokamak simulations, related to the relative importance of cross-field transport between the two devices. Based on these results and existing literature, we establish best practices towards improved accuracy and efficiency in general stellarator modeling with EMC3-EIRENE.

We argue that pattern recognition and step-by-step reasoning are two ends of a spectrum. A large language model (LLM) learns to reason step-by-step when data is structured such that the next token depends on a small amount of preceding context. Inference in LLMs resembles pattern recognition when the next token depends on a large amount of preceding context. If the next token depends on only the $c$ most recent tokens, reasoning traces are paths on a De Bruijn graph whose nodes are $c$-length contexts and edges are next-token transitions between contexts. The set of reasoning traces of a task forms a directed acyclic subgraph of the De Bruijn graph. An LLM that has learned all edges of this subgraph can compose them to solve longer, unseen tasks, i.e., it reasons step-by-step. We prove that the number of edges is vanishingly small compared to the number of reasoning traces. Empirically, the number of training samples a transformer needs is a power law in the number of edges, so learning to reason step-by-step is sample efficient. We can induce De Bruijn structure in any task by maintaining a “state” that makes future reasoning independent of the past. The frequency of states in the reasoning trace determines $c$. We show, by fine-tuning Qwen2.5-1.5B-Instruct to solve equations and answer questions about stories, that frequent states (small $c$) result in higher accuracy but greater fragility to perturbations at test time. LLMs trained with a large $c$ are only as good as models that perform pattern recognition without reasoning. A moderate density of states balances accuracy and robustness. We show that real-world data has De Bruijn structure: Qwen3-14B and Qwen3-32B retain over 75% of their accuracy on GSM8K, MATH-500 and GPQA-Diamond when attention is restricted to a sliding window less than 15% as long as the full reasoning trace.

The optical theorem dictates that the wave scattering of an object in the forward direction is proportional to the total power extinguished from the excitation. For passive objects, this relationship is a by-product of the intuitive notion that scattering and absorption necessarily create shadows, and that zero forward scattering, i.e., no shadow, can only be obtained if the object is fully transparent, i.e., it neither scatters nor absorbs. Materials with gain can be in principle leveraged to suppress forward scattering while preserving a large scattering signature in other directions. However, sufficient optical gain is challenging to realize, and it inherently leads to instabilities and nonlinearities. Here, we experimentally demonstrate shadow-free \ scattering from a passive high-index dielectric sphere by exciting it with a complex frequency signal tailored to mimic the presence of material gain. We achieve as much as 26dB suppression of the forward scattering when compared with optimal monochromatic excitations, while preserving strong scattering in other directions. More broadly, our results demonstrate how complex frequencies offer a natural pathway to enhance control over the scattering signature of passive objects, with implications for a range of photonic applications.

Atmospheric warming raises evaporative demand, but actual evapotranspiration (ETa) may track demand or decouple under water limitation. Here, we quantified demand-tracking ability from regression slopes relating deseasonalized ETa and reference evapotranspiration (ETo) anomalies across California during 2008-2024. Forests and croplands retained similar positive tracking under severe drought, whereas grasslands and shrublands showed weak or negative responses. Despite similar demand tracking, forest responses were consistent with subsurface-storage access, whereas cropland responses reflected managed water access and crop-system adjustment. Positive ETa-ETo coupling on active fields coexisted with a higher statewide crop-attributed fallow share of managed cropland than under no drought, showing that active-field estimates alone did not capture whole-crop-system adjustment. Late-period demand-tracking ability was lower at 54.9% of grid cells, with larger regional declines accompanying greater groundwater-storage losses. Our results indicate that similar ETa responses mask contrasting modes of water access, requiring joint consideration of hydrology and management when interpreting drought responses.

The rapid growth of low-cost and open-source spectrophotometers has created a need for systematic methodologies to evaluate and compare alternative instrument architectures. This study presents a comparative assessment of three representative open-source spectrophotometric platforms, encompassing discrete multispectral sensing and continuous-spectrum imaging approaches. Their performance was evaluated against a commercial Thermo Scientific Genesys 30 spectrophotometer in terms of spectral agreement, portability, implementation complexity, and cost. The results demonstrate that no single architecture is universally optimal; instead, each presents distinct trade-offs that determine its suitability for specific applications. Multispectral sensor-based systems offer compact, low-power solutions for field deployment, whereas imaging-based platforms provide spectral performance closer to laboratory-grade instrumentation. All hardware designs, firmware, and software developed in this work are released as open-source resources to support reproducibility and further development. The study highlights the importance of matching instrument architecture to application requirements and proposes a practical framework for the evaluation and selection of low-cost spectrophotometers, facilitating the adoption of open-source analytical tools for water quality monitoring and related applications.