Papers

We study a spin-$\frac12$ impurity coupled to the boundary of a strongly correlated spin-$s$ Takhtajan–Babujian chain, an integrable model whose low-energy physics is described by a perturbed $SU(2)_{2s}$ Wess–Zumino–Witten conformal field theory. While boundary conformal field theory determines the low-energy universality class of the weak-coupling regime, exact Bethe Ansatz methods reveal a sequence of boundary quantum phase transitions in which impurity-bound states emerge and reorganize the Hilbert space into multiple excitation towers built on distinct boundary configurations. This tower restructuring provides the organizing principle for a rich boundary phase diagram extending beyond the conventional Kondo regime. Weak antiferromagnetic coupling realizes the overscreened $2s$-channel Kondo universality class, whereas stronger couplings generate localized boundary modes and qualitatively new screening mechanisms. To describe the resulting thermodynamics, we develop a generalized thermodynamic Bethe Ansatz framework that captures the multi-tower structure across all regimes. The impurity entropy reproduces the boundary conformal field theory prediction in the overscreened Kondo regime but develops pronounced nonmonotonic temperature dependence once boundary-bound states appear, in quantitative agreement with large-scale finite-temperature matrix-product-operator simulations. Complementary dynamical calculations reveal sharp threshold features in the impurity spectral function that directly track the underlying tower structure. Together, boundary conformal field theory, exact Bethe Ansatz, generalized thermodynamic Bethe Ansatz, and tensor-network simulations provide a unified description of impurity screening, boundary-bound-state formation, and excitation-tower reconstruction in a correlated spin-$s$ chain.

While the necessity of a moiré potential for fractional Chern insulators (FCIs) in rhombohedral graphene-hBN superlattices, first predicted in Ref. 1, is now grounded in experiments, a theory of its origin and importance remains at large. We present a mechanism—the moiré capacitor effect—that enhances the moiré potential by electrostatically imprinting the valence charge density onto the conduction bands. We derive the analytical form of this term and reveal its crucial role in stabilizing a parent state with Chern number $C=1$ at filling $\nu=1$. We propose a parent state theory which posits that stability of the Chern insulator and flatness of its hole excitations are necessary for obtaining FCIs upon doping. We then perform multi-band exact diagonalization calculations to confirm the emergence of FCIs at $\nu = 2/3$ in the presence of the moiré capacitor effect. Our FCI state is stabilized by inter-band fluctuations, unlike in the moire-free case which collapses with band-mixing. We provide the first consistent theory for this state in aligned samples and explain its absence in unaligned ones.

Leakage beyond the computational subspace is a major source of error in multilevel quantum hardware. We show that any \( [[n,k,d]] \) stabilizer code can be embedded isometrically into a single \(D\)-dimensional system while preserving its complete error-correcting structure. We further derive a necessary and sufficient condition for exact leakage correction, proving that leakage is correctable precisely when it does not distinguish between logical states. These results establish a unified framework for quantum error correction in multilevel quantum systems.

Is it possible to find an objective classification criterion that organizes the complexity of gust-induced loads across many flight conditions? And one that remains as interpretable as a labelling based on coarse parameters, such as the flight attitude? Our approach encodes a large number of experimental observations through a machine-learned representation and applies a summarization procedure to select a minimal subset of highly significant exemplars. The exemplars provide a similarity-based objective classification criterion of all the observations, they can be more conveniently inspected by experts and can become subject of more refined experiments. We demonstrate the approach on a database of 3480 pressure-load measurements induced by random gusts on a flying-wing model across six flight attitudes. We find nine fundamental response types that recur across multiple attitudes; analysis of a type's transient response enables physical intuition into the underlying fluid mechanics.

This paper analyzes the 112 sensor videos released under the PURSUE (Presidential Unsealing and Reporting System for UAP Encounters) initiative. Redactions to on-screen displays limit information available for identifying the reported unidentified anomalous phenomena (UAP). Converting the rate at which any object transits across part or all of a frame from pixels per frame to a physical velocity requires (1) the range to the object, (2) the velocity of the observing aircraft, (3) the aspect angle between the object's path and observer, and (4) the field angle of the camera. No PURSUE video provides this set of information. In one clip (DOW-UAP-PR113), the object crosses depression-angle markings, which allows reconstruction of the camera's field of view. Even this clip does not provide sufficient information to distinguish between a bird flying at close range and a large craft traveling at Mach 5 a kilometer away. A second clip (DOW-UAP-PR149) includes a vessel of known size in the frame, which can be used as a reference to calculate an upper bound of Mach 0.4 on the object's relative velocity. Without further information, the PURSUE sensor videos in their present form cannot fully resolve unidentified cases or conclusively indicate anomalous velocities.

Morphology transfer of 2D Janus MXenes into nanoscrolls unlocks unusual properties. Although a scalable synthesis route has been experimentally verified, the atomistic mechanism underlying nanoscroll formation remains poorly understood. We use large-scale reactive molecular dynamics simulations, validated against density functional theory (DFT) and experimental structural and elastic properties, to investigate stability and quantify the driving forces and geometry governing nanoscroll formation in three Janus MXenes, (Tx)Ti2C(Ty), where (Tx) and (Ty) denote the bottom and top surface terminations among bare (-b), -O, and -OH. Both square and infinitely wide flakes with lengths ranging from 10 to over 120 nm are simulated. We find that 1-7% lattice-induced strain generates a bending moment in these structures. The sheet scrolls, curves, or forms a nanotube depending on the resulting curvature and initial sheet size. For MXenes with an initial length of 120 nm, multiwalled nanoscrolls form with interlayer distances of around 0.7 nm and inner diameters of about 7 nm for (O)Ti2C(OH) and (b)Ti2C(OH), whereas (b)Ti2C(O) instead produces a much larger interlayer distance of around 1.7 nm and an inner diameter exceeding 20 nm. We show that spontaneous scrolling of a Janus MXene in the presence of an anchored nanoparticle produces a core@shell composite, in which the particle locally deforms the nanoscroll and widens the interlayer channels. This locally tunable, enlarged interlayer spacing offers a promising design route for MXene-based energy-storage electrodes. However, our simulations reveal H2 gas release during encapsulation, which promotes nanobubble formation that can reduce battery life.

We formulate generative modeling as a path integral in which flow-based, diffusion-based, variational, and adversarial models arise as different evaluation principles for a single master action. Its Martin-Siggia-Rose-Janssen-de~Dominicis (MSRJD) form separates free from interacting probability flows and opens them to diagrammatic perturbation theory. The expansion yields a one-loop correction to deterministic samplers at no stochastic-sampling cost, which we validate on solvable and nonlinear drifts, where it reduces a 53 % tree-level error to 1.6 %. Imperfect learned scores enter as insertions and yield a response-weighted score-matching objective, and symmetry-equivariant drift design becomes an operator expansion with EFT power counting.

The convergence of AI and quantum computing requires a new approach to cybersecurity. Credible experts estimate that by 2030 a cryptographically relevant quantum computer will be capable of breaking the encryption that underpins all of our digital communication. One of the most disruptive technology in history is coming and it's expected to change everything. In this context academic institutions will contribute to their states' future economic prosperity by leveraging their strengths and resources, particularly talent development, in key and emerging areas prioritized across the state. We report on current efforts to develop a Pathways Plus to Quantum Information Science (QIS) degree, a set of dual credit courses for high-school (HS) students and incoming college students pursuing a minor or specialization in Quantum Computing (QC). As of today, in the US, quantum topics appear on the HS curriculum standards in just two states: OH (Computing) and TX (Physics). Reaching out to HS and even middle school students (and their teachers) presents obvious long-term benefits in terms of workforce development for the quantum industrial ecosystem. Standing in the way of successful, widespread introduction of QC and QIS topics in HS and middle school are three distinct obstacles: (a) lack of materials at the right level for students and instructors, (b) funding and support for professional development for teachers, and (c) lack of state standards. In this paper we address all three aspects with a special focus on the benefits of quantum virtual labs and ZX calculus in the classroom.

We present a stability analysis of a dark-fluid model described as a non-relativistic, rotating, non-viscous, self-gravitating fluid. We assume spherical symmetry and model the matter by a polytropic equation of state. The resulting coupled nonlinear partial differential equation system is solved using a self-similar ansatz known from the Guderley-Landau-Stanyukovich problem. We find that three of the four Lyapunov exponents are negative, while only one is positive. This indicates one unstable direction and three contracting directions in phase space. The single positive exponent is relatively small, suggesting that the self-similar solution is only weakly unstable and remains dynamically robust over the investigated interval.

Within classical general relativity, we compare a sharp timelike junction and a smooth finite-width spacelike initial-data embedding of a positive-excess virialized halo in a homogeneous Lambda-FLRW environment. On the ordinary branch, timelike Israel matching at the virial boundary produces a negative surface layer: a distributional representation of the environmental compensation omitted by the sharp construction. We replace this zero-width source by a finite-width, background-relative underdensity whose local rest-frame energy density remains positive. The resulting conformally flat, constant-mean-curvature ADM initial slice satisfies the Hamiltonian and momentum constraints, with the residuals converging under resolution refinement. At finite radius, its geometric and matter variables return to the local-effective FLRW data within the declared tolerances: the constructed slice contains no residual distributional layer and satisfies the reconstructed weak, null, and dominant energy conditions. For radii beyond the numerical endpoint, the exterior is defined by the exact analytic local-effective FLRW solution. The GCT framework supplies the global motivation clock interpretation, while the present calculations are local-effective classical-GR calculations with the bound-sector constants c0 and G0 held fixed: no radial GCT lapse or constant interpolation is constructed.

We consider two two-dimensional (2D) electronic systems in the presence of a perpendicular homogeneous electric field that generates a Rashba spin-orbit interaction (RSOI): a system of non-interacting electrons in a 2D conductor, modeled using the 2D Schrödinger equation (SE), and a single-layer graphene system, modeled using a 2D Dirac equation (DE) for massless fermions. In both cases the RSOI is expressed via an $SU(2)$ Rashba vector potential ${\bf A}_{R}$. We demonstrate that ${\bf A}_{R}$ cannot be eliminated from either the 2D SE or the 2D DE via a gauge transformation. Nevertheless, for a plane wave solution, an $SU(2)$ matrix exists that eliminates ${\bf A}_{R}$ from the resulting 1D SE. This unitary matrix is an Aharonov-Casher (AC) phase factor, and facilitates the calculation of the AC phase in the Schrödinger scheme. The plane wave solution for the DE contains two components of ${\bf A}_{R}$: $A_{R, k}$ in the direction of the wave vector ${\bf k}$, and $A_{R, n}$ normal to ${\bf k}$. The latter generates an effective electron mass that cannot be eliminated from the DE. The former generates an AC phase that can be eliminated by a time-dependent unitary transformation. Thus, the Dirac AC phase is time-dependent, i.e., it is a dynamical phase. This is in contradistinction to the Schrödinger AC phase which is geometrical.

This paper develops a phase-plane formulation of gravitational light deflection by static and spherically symmetric black holes, with Schwarzschild spacetime as the principal case. Instead of perturbing the null trajectory and locating the displaced outgoing asymptote, we represent the orbit through an amplitude and an intrinsic phase. The bending angle then follows from the excess physical azimuth accumulated while the intrinsic phase advances between two fixed asymptotic endpoints. For Schwarzschild spacetime, the exact radial first integral reduces the amplitude evolution to a cubic algebraic relation. Its physical branch generates the local phase factor through a single inverse algebraic map. Lagrange inversion then yields an explicit all-order weak-deflection coefficient formula in powers of the invariant ratio \(M/b\). Each coefficient separates into an algebraic phase contribution and a universal trigonometric moment, which explains the alternating rational and \(\pi\)-dependent structure of the Schwarzschild series. Independent comparison with the exact radial scattering integral and conventional orbit perturbation reproduces the standard weak-bending coefficients. The same phase framework extends to general static spherical geometries, while the Schwarzschild cubic represents an especially simple member of a broader algebraic class. The branch singularity of the phase map also coincides with the critical photon orbit and governs the convergence of the weak-deflection expansion.

We solve the Fokker-Planck equation for a Brownian particle in a tilted cosine potential and derive the intermediate scattering function (ISF), which captures the full spatio-temporal dynamics of the system. The model consists of a single overdamped Brownian particle in one dimension. We derive a generalized ISF comprising two wave vectors to describe correlations in the periodic potential. Exploiting the periodicity via Bloch's theorem, we formulate the problem within a spectral-theoretical framework and numerically compute the corresponding eigenfunctions and eigenvalues, from which we obtain the ISF and the probability density. Using time-dependent perturbation theory, we expand the ISF and derive low-order moments, including the mean-square displacement, time-dependent diffusivity, skewness, and the non-Gaussian parameter. Our analytical results are validated by Brownian-dynamics simulations and analyzed focussing on different regimes of the tilting force. The results are compared to a harmonic approximation and the deterministic limit.

We derive the Friedmann dynamics and apparent-horizon thermodynamics of a spatially flat McVittie spacetime in Gravity's Rainbow and construct a consistent non-accreting perfect-fluid sector with an effective rainbow Hubble rate. The Einstein equations, trapping horizon, surface gravity, Misner–Sharp energy, unified first law, and Clausius relation form a closed thermodynamic system reproducing the Friedmann dynamics. We then introduce a low-energy rainbow deformation and constrain it using 32 cosmic-chronometer measurements and 1580 Pantheon+ light curves with the full covariance matrix. Combined with the Planck matter-density prior, the fit gives $H_0=68.75\pm2.63~\mathrm{km\,s^{-1}\,Mpc^{-1}}$, $\Omega_m=0.3157\pm0.0070$, and $\epsilon=0.0106^{+0.0234}_{-0.0231}$. The resulting constraints establish the observational viability of small late-time rainbow corrections and place the general-relativistic limit within the preferred parameter region.

Near a bandwidth-tuned Mott transition, the Fermi velocity $v_F$ and quasiparticle residue $Z$ of a metal often vanish. Here, we show that analogous phenomena emerge in twisted bilayer graphene (TBG) at integer fillings and can be captured by an emergent heavy-fermion framework within a projective active-band limit. Unlike models incorporating remote bands, our effective heavy-fermion description arises from mixed-valence Mott physics via decoupled charge and local-moment sectors. In the charge sector, active bands $c(\mathbf{k})$ hybridize with an emergent orthogonal fermion $\psi(\mathbf{k})$ to open a large Mott gap at $|\mathbf{k}| > k_*$ ($k_*$ sets the momentum-patch size) and a quadratic band-touching semimetal near $\mathbf{k}=0$ at neutrality ($\nu=0$). The orthogonal fermion is a linear combination of the doublon and holon excitations and may be written as $\psi_i \sim (\delta n^f_i+\frac{1}{2})^{-1} f_i$. An emergent Kondo coupling $J_K \sim U$ ($U$ is the local Hubbard interaction) between $\psi$ and local moments $\psi'$ frames the Mott transition as a Kondo screening transition, tuned by the twist angle $\theta$. Away from the magic angle, a Kondo-screened heavy semimetal develops below $T_K$ (the Kondo temperature) with vanishing $Z$. Introducing anti-Hund's coupling $J_A$ generates an s-wave fully gapped or nematic, nodally gapped superconducting dome near the Mott boundary even at $\nu=0$. At other integer fillings $\nu = \pm 1, \pm 2$, increasing bandwidth first drives the small-gap Mott state into an intermediate quadratic band-touching semimetal before entering a heavy Fermi liquid with large Fermi surfaces. Our results establish a unified framework for emergent heavy fermion physics with both itinerant carriers and local moments from the $f$ orbital.

Entanglement is a defining feature of quantum mechanics, and its relation to quantum criticality is of considerable current interest. Here we show that measurable spin and charge fluctuations provide an entanglement witness of quantum criticality in the two-impurity Kondo model, which has experimental realizations in terms of coupled quantum dots and magnetic impurities added to surfaces. We use density-matrix renormalization group and numerical renormalization group calculations to resolve the non-Fermi-liquid critical point separating two independently Kondo-screened impurities from an inter-impurity singlet and interpret it as a change in the dominant entanglement partner of each local moment: from entanglement of the local moment with an extended set of conduction-electron degrees of freedom to entanglement with the other impurity. This reorganization is accompanied by a singular response of the impurity-bath entanglement and the inter-impurity susceptibility. We show how the same structure is encoded in the quantum Fisher information of collective spin and charge operators at zero and finite temperatures, connecting the entanglement picture to experimentally accessible dynamical response functions. Our results establish impurity systems as controlled settings in which quantum-critical entanglement can be detected through measurable correlations, and provide further insight into the possibility of understanding heavy-fermion physics in terms of entanglement.

We introduce a framework to classify quantum phases, phase transitions, and non-equilibrium dynamics of interfaces separating ordered bulk domains in 2D quantum magnets - equivalently, confining strings in dual lattice gauge theories - based on effective 1D Hamiltonians governing geometric fluctuations. Building on a "holographic" approach from [Phys. Rev. Lett. 129, 120601 (2022)], here reinterpreted as an exact bosonization, we uncover a rich quantum phase structure, with a variety of stiff and rough interface phases described by gapped and gapless 1D ground states, respectively, all distinguishable through the statistics of 2D wave-function snapshots. Our framework allows us to predict distinct spatiotemporal scaling laws for non-equilibrium curvature-driven interface dynamics across parameter space, which can be readily probed in existing experiments. We finally show that our approach enables the unprecedented experimental opportunity of directly measuring charge full counting statistics and symmetry-resolved properties of an encoded 1D system, as we explicitly demonstrate by numerically simulating a neutral-atom array experiment.

We develop a probabilistic cavity-contiguity framework for proving replica-symmetric convergence of local marginals in mean-field Gibbs systems. The approach is based on cavity decompositions of the Hamiltonian together with direct comparison of probability measures through Radon-Nikodym derivatives and Hellinger-type estimates. At a conceptual level, the method separates the concentration of the relevant order parameters from the identification of the asymptotic cavity model and the comparison of the associated Gibbs measures. In contrast with interpolation-based approaches, the argument relies only weakly on the Gaussianity of the disorder and naturally accommodates concentration tools such as Poincaré and log-Sobolev inequalities. Rather than pursuing maximal generality, with the aim of making the method transparent, we implement the framework in a canonical example: the high-temperature Sherrington-Kirkpatrick model. In this setting, we prove that the marginal law of a fixed spin converges in total variation toward the effective one-dimensional cavity measure predicted by the replica method. Beyond the specific result for the Sherrington-Kirkpatrick model, the paper illustrates a broader cavity-contiguity methodology which is expected to extend naturally to other mean-field Gibbs systems, particularly Bayesian inference models with or without mismatch.

We construct phase transitions that proliferate condensable anyons in general 2+1d topological orders, including non-abelian ones. The central tool that provides a systematic approach to this question is the Symmetry Topological Field Theory (SymTFT). For a given topological order, we identify the relevant symmetry from the transparent lines generated by the condensable anyons, and thereby realize the topological order in terms of a 3+1d SymTFT sandwich. The proliferation phase transition is realized by coupling scalar fields to the anyons purely on the symmetry boundary of the SymTFT. We illustrate the construction for abelian theories, as well as non-abelian ones, $D(S_3)$ and $SU(2)_k$ Chern-Simons theories, and extend it to anomalous anyons.

We investigate how galaxy star formation activity depends on environment using a sample of 81,647 SDSS galaxies selected over $0.03\leq z\leq0.075$ and $9.7\leq\log_{10}(M_\star/h^{-2}M_\odot)\leq11.0$, including 18,426 members from 572 clusters in the GalWCat19 catalog. We characterize environment in two complementary ways: (1) nearest-neighbor density for the full sample, and (2) clustercentric radius and host halo mass for GalWCat19. The sSFR distribution remains bimodal across all environments, with distinct quenched and star-forming components. As local density increases, the quenched component becomes more prominent, while the characteristic sSFR of the star-forming component decreases by approximately $0.29$–$0.35$ dex from the lowest- to highest-density classes. Within clusters, the quenched fraction decreases with increasing projected clustercentric radius, while the star-forming peak shifts by approximately $0.42$ dex toward lower sSFR from the outskirts to the inner cluster region. This extends the picture from previous studies, in which environmental trends are primarily associated with changes in the quenched fraction, by showing that galaxies remaining in the star-forming population also exhibit systematically suppressed sSFR in denser environments. The dependence on host halo mass is weaker and is most apparent among lower-stellar-mass galaxies in the inner cluster regions. By measuring the environmental quenching efficiency at fixed stellar mass, we find excess quenching in cluster environments beyond that expected from stellar-mass quenching alone. These results show that environment is associated not only with an increased probability of quenching, but also with suppressed star formation among galaxies that remain star forming, with local density and clustercentric radius showing the strongest associations.

We cast general imaging as multiparameter quantum estimation of band-limited spatial-frequency amplitudes. For separable (single-copy) measurements, we compute precision limits using semidefinite programming to evaluate the Nagaoka-Hayashi Cramér-Rao bound. We then introduce an architecture for a measurement apparatus based on diffractive optical neural networks and photon counting that saturates this bound. Extending the framework to arbitrary objects and many amplitudes, we show image reconstructions in which our architecture recovers fine features at the quantum limit, outperforming direct imaging. Together, these results open a scalable route to saturating multiparameter quantum limits in superresolution microscopy, telescopy, and remote sensing.

Quantum simulation is expected to be a main application of quantum computers with realistic utility in quantum chemistry, materials science and beyond. However, preparing excited or general eigenstates is a central challenge, particularly when the desired eigenvalue is not known in advance, or when the overlap with the initial state is insufficient. We introduce the Dominant Eigenstate Filtering via Eigenprobability Amplification and Thresholding (DEFEAT) algorithm that identifies and filters the eigenstate with the largest overlap with the supplied initial state. Our key observation is that we do not need prior knowledge of the target eigenvalue, as we construct efficient twirling superoperators that map initial states to eigenprobability density operators $\rho$, diagonal in the Hamiltonian eigenbasis and encoding its spectral weights, alongside its block-encoding implementation. Our crucial innovation is the quadratic amplification of probabilities via the factorisation $\rho=\rho_{\rm sqrt}^\dagger\rho_{\rm sqrt}$, analogous to the recently introduced sum-of-squares spectral amplification (SOSSA), which we use here to amplify the separation between dominant and subdominant components. Thresholding then yields the dominant-eigenstate projector. Compared with conventional phase estimation, DEFEAT improves the dependence on the overlap with the initial state while requiring substantially fewer ancillary qubits. We prove that the query complexity of the filtering step is optimal up to logarithmic factors and establish a complementary lower bound for eigenstate preparation under purified query access to $\rho$. We validate in numerical simulations that the convergence rate of DEFEAT matches our theoretical results. Our results provide a general eigenvalue-agnostic primitive for dominant eigenstate filtering and preparation, and for estimating properties of dominant eigenstates.

The min-plus process is a stochastic coagulation-annihilation-type process on the binary tree, of interest in mathematics, physics, and computer science as a tractable instance of max-type recursive distributional equations. We carry out large Monte Carlo simulations at effective tree depths up to $N=60$ that provide finite-depth corroboration of the Beta(2,1) stretched-exponential limit for its root value $X_{N}$ at $p=1/2$, on the asymmetric $\sqrt{N}$ side of the random-homogeneous-systems classification recently introduced by Chen, Duquesne, and Shi and by Morfe. Off criticality, our simulations confirm the sub-critical closed form $\mathbb{P}(X_{\infty}=1)=(1-2p)/(1-p)$ within Monte Carlo error and document a super-critical mean growth exceeding the elementary $(2p)^{N}$ lower bound at the depths we reach. For a Bernoulli($q$)-initial-condition variant, we identify an elementary closed-form identity at $p=1/2$ that pins down the order parameter $\mathbb{P}(X_{N}=0)=q$ exactly, locates the absorbing-state phase transition at $p_{c}=1/2$ in the operator-mixing probability rather than in the initial-zero density, and shows that the conditional law on positives deforms substantially with $q$. Our simulations use a level-wise recursion and an FFT-based precomputed leaf table which reduce the effective simulation depth while preserving the recursive tree law and may be useful for the simulation of related recursive equations on large trees.

We report a measurement of the total cross section for muon antineutrino charged-current quasi-elastic scattering on hydrogen, $\bar \nu_\mu {\rm H} \to \mu^+ n$, in the NOvA near detector using a $1.2\times10^{21}$ proton-on-target exposure in the NuMI beam. A selection based on topological and kinematic constraints yields 35,509 signal events in the hydrogen-rich ($10.8\%$) detector, providing the highest statistics of (anti)neutrino–hydrogen interactions measured to date. Backgrounds from (anti)neutrino interactions on heavier nuclei are constrained using dedicated data control samples, significantly reducing the related systematic uncertainties. We obtain a value $\sigma (\bar \nu_\mu {\rm H} \to \mu^+ n) = 0.538 \pm 0.009 ({\rm stat}) \pm 0.010 ({\rm syst}) \pm0.055 ({\rm flux}) \times 10^{-38}$ cm$^2$ for the total cross section at an average energy of 1.9 GeV, the most precise total cross-section measurement of this process to date. The combined statistical and non-flux systematic uncertainty is more than four times smaller than the flux uncertainty, allowing a future use of this measurement to constrain the absolute $\bar \nu_\mu$ flux.

Accelerated aging is widely used to study the long-term behavior of materials within laboratory time scales, particularly for materials exposed to solvent environments over extended periods. This is especially important for additively manufactured (AM) polymers, whose increasing use in naval and commercial undersea applications requires reliable methodologies for assessing durability under in-service conditions. A common approach relies on elevating the temperature below the glass transition or melting temperature to accelerate degradation. However, the temperature limits for accelerated aging of AM polymers remain poorly understood, particularly because temperatures beyond a threshold may activate deformation and degradation mechanisms that are absent under service conditions. To address this gap, this paper investigates fused deposition modeling (FDM) Acrylonitrile Butadiene Styrene (ABS) exposed to saltwater and deionized (DI) water to establish a temperature threshold for accelerated aging in aqueous environments and propose a methodology for determining such thresholds. Controlled geometries and varying print directions were employed to explicitly probe the underlying mechanisms. We show that samples exposed to temperatures above the threshold exhibit pronounced shrinkage and warping along the printing direction due to the relaxation of process-induced internal stresses. These observations establish an accelerated-aging temperature threshold of 50$^\circ$C for ABS, beyond which additional mechanisms absent under service conditions become active. Additionally, the resulting geometric distortions are masked in thick geometries but become highly pronounced in thin structures. Moreover, solvent ionic content strongly influences water uptake, with saltwater reaching saturation in 1 day, whereas DI water did not reach saturation even after 30 days and exhibited greater mass uptake.

Many nonlinear models across physics, chemistry, and biology exhibit multiple solutions for the same parameters, and capturing this entire solution set is essential for understanding pattern-forming systems. Yet existing learned surrogates are fundamentally single-valued: neural operators map each parameter to a single output, and physics-informed neural networks converge to one branch. We develop PatternFormer (PF), a large language model-based framework for learning the multiple solutions of nonlinear partial differential equations. By transforming unordered coexisting solutions into canonical sequences, PF produces structured solution sets in a single autoregressive pass, terminating automatically for finite families and enforcing physical residual constraints for unbounded ones. On nonlinear elliptic problems it recovers all solution branches in one inference step; on Gray–Scott it generates coexisting Turing patterns, including physically valid states absent from the reference data and beyond training. PF can also be sequentially fine-tuned across multistable systems, toward general foundation models for solution landscapes.

Strong coupling to a magnetic texture makes an electron propagate through an emergent curved space. We show that an elementary vortex realizes the exterior spatial geometry of an Ellis wormhole: an ultrastatic throat with radius fixed by the topological charge and Hund exchange, cut off at short distances by the microscopic core. Two separable signatures follow directly: the electron deflection collapses onto a single Ellis curve governed by the vortex winding and exchange coupling, while the spin Berry phase produces a half-flux Aharonov–Bohm response switched on and off by winding parity. The same metric can be emulated in a designer honeycomb lattice, where the valley-symmetrized wave-packet response follows the predicted exterior geodesic. These signatures are accessible through real-space electron deflection and scattering, providing experimentally distinct probes of the emergent geometry and Berry flux. The magnetic vortex thus turns a topological defect into a tunable curved-space lens for electrons in quantum materials and designer lattices.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is widely used for local chemical investigations across a broad range of materials and systems. However, its operation is expensive in expert time: a trained researcher must supervise the acquisition continuously, tuning parameters as the experiment proceeds, often across a campaign spanning multiple days. Here, we present PACE-SIMS (Pause-Assess-Correct-Execute for SIMS), an agentic workflow that runs a SIMS study as a human-AI collaboration. In this workflow, the researcher specifies the scientific questions and quality requirements, and an AI agent builds the plan and, after approval, executes it autonomously, pausing at checkpoints to judge each measurement and to correct, retry, or escalate. To validate the approach, we applied it to a study of chemical composition in 18O-enriched WOx films. During this randomized, blind two-polarity study (8.1 hours, 35 measurements), the agent applied three rule-governed corrections and diagnosed an unanticipated source excursion without requiring event-specific control logic to be programmed in advance. The same run returned transferable measurement science, including a composition calibration and the deposition's tracer-delivery mechanism, from less than two hours of researcher attention. The developed agentic architecture is not specific to SIMS and can be applied to other analytical techniques, with the primary target being destructive measurements, for which optimization-based methods are poorly suited.

We present new Karl G. Jansky Very Large Array S-band (2-4 GHz) observations of the edge-on spiral galaxy NGC 891, complemented by C-band data, to investigate the structure of its radio continuum halo. Using rotation measure synthesis we detected an extended polarized halo, with most spatially extended polarized emission confined to Faraday depths within +/- 150 rad m-2. We identified a localized region in the north-east side of the galaxy that shows an enhancement in polarized intensity (not in percentage polarization). By combining the radio data with H-alpha and diffuse X-ray maps, we discuss a possible origin for this structure: a superbubble powered by clustered supernovae. Across the disk and halo, the percentage polarization decreases toward the midplane but shows a mild wavelength dependence, despite the edge-on orientation of NGC 891. This behavior implies that the depolarization cannot be dominated by small-scale Faraday rotation within the disk. Instead, it is possible that most of the observed polarized emission arises on the Earth-facing side of the galaxy. Our peak rotation measure (RM) map shows a smooth transition along the major axis, consistent with a large scale axisymmetric magnetic field. Using H-alpha and UV data, we analyzed the distribution of H II regions and found that they are parts of different spiral arms. We also identified a faint, isolated H II region at a galactocentric radius of 16.9 kpc, with both H-alpha and far-UV counterparts, indicating star formation outside the thin disk.

Global weather reanalyses and forecasts resolve the evolving atmospheric state on coarse grids, but site-specific applications require predictions at arbitrary locations where near-surface conditions also depend on unresolved terrain and land-surface properties. Existing probabilistic downscalers address this gap using hand-crafted topographic and surface descriptors. We ask instead whether Earth observation foundation models can provide transferable subgrid surface representations for probabilistic weather downscaling. We augment a convolutional conditional neural process (ConvCNP) that downscales coarse ERA5 reanalysis fields at ~25 km resolution with a learned local surface descriptor, obtained by compressing a patch of TESSERA embeddings at 10 m resolution. Although these embeddings summarize annual surface conditions, they improve downscaling by encoding persistent surface properties that capture a location's departure from the coarse-grid atmospheric state. Across five climatically diverse regions, the embedding improves point and probabilistic skill at stations held out in both space and time, overall improving CRPS skill by 11.5% for 2 m temperature and 6.2% for 10 m wind speed relative to a topography-only ConvCNP baseline. A hand-crafted descriptor incorporating richer surface information than topography alone captures comparable persistent subgrid signal but yields far smaller predictive gains than the learned embedding representation. These improvements persist when forecasts from the Aurora AI model replace ERA5 reanalysis fields and when predicting at newly deployed weather station networks. To our knowledge, this is the first evidence that long-timescale Earth observation embeddings can support short-timescale weather downscaling where subgrid departures are systematically structured by persistent surface properties.