Papers

In beta-gallium oxide (beta-Ga2O3), Ga-ion implantation and annealing induce abundant point defects. To overcome conventional Wigner-Seitz (WS) defect analysis limitations, a defect identification algorithm based on similarity matching and DBSCAN clustering is developed for beta-Ga2O3. It distinguishes lattice atoms from defects at high concentrations and identifies eight Ga interstitial configurations (Gaia to Gaih). Comparing SRIM and MD data highlights electronic stopping effects: neglecting them overestimates ion range and defect concentration. Across five fluences (1 to 5 x 10^14 cm-2), 1373 K is the optimal recovery temperature. Multiscale analyses using hydrostatic stress, PRDF, and defect concentration reveal defect evolution. Ga interstitials (Gai) occupy tetrahedral and octahedral sites, driving a defect-mediated phase transition from beta- to gamma-Ga2O3. Increasing fluences reduce beta-phase recovery and increase gamma-phase transformation irreversibly. Oxygen interstitial (Oi) migration is sensitive to annealing temperature, which enhances O-sublattice recrystallization.

Deep learning surrogates have become powerful tools for simulating and forecasting complex dynamical systems, yet their utility remains limited by catastrophic error accumulation during long-term autoregressive rollouts. This behavior is partly tied to the nature of the underlying systems: chaotic spatiotemporal systems visit phase space unevenly, with dynamics dominated by recurrent, low-dimensional quiescent states and characterized by rare and dynamically complex regime transitions. Trained under a sample-wise uniform objective, standard neural surrogates allocate their finite capacity to the statistically more numerous low-dimensional quiescent states, systematically under-representing the transient regimes that trigger disproportionate, localized errors. Existing imbalanced-regression methods tackle this issue by reweighting samples according to target-space density. However, statistical target-space rarity does not coincide with the intrinsic dynamical rarity encoded in the recurrence geometry of the attractor. To address this, we introduce Dynamics-Aware Weighting (DAW), a data-centric objective reweighting framework. Using the local dimension $d$ from dynamical systems theory as an a priori measure of a state's dynamical complexity, DAW reshapes the loss landscape to allocate representational capacity toward the sparse, high-$d$ regimes where forecast errors are systematically large. On the chaotic KS equation, DAW consistently outperforms uniform training as well as weighting based on target-space rarity, and its randomly permuted ablation, reducing long-term autoregressive error relative to all baselines. Event-level analysis shows that DAW achieves this by suppressing the localized error amplifications incurred during sharp jumps in the local dimension $d$, which typically accompany complex physical processes such as wave-merging in the KS system.

Vibrational spectroscopy reports on molecular structure with chemical-bond specificity, but in biological systems the vibrational signals of a target chromophore are typically buried under contributions from the surrounding matrix. Resonance Raman (RR) spectroscopy addresses this problem by matching the excitation wavelength to an electronic transition of the chromophore of interest, which increases Raman cross sections by up to six orders of magnitude and restricts the enhanced modes to those coupled to the resonant electronic state. This chapter introduces the physical basis of resonance enhancement and shows how RR isolates chromophore-specific vibrational markers in complex biological systems. We then extend the same principle into the time domain with femtosecond stimulated resonance Raman spectroscopy (FSRRS). In FSRRS, the Raman pump is tuned across the visible range and can be placed in resonance with the transient absorption of a chosen excited-state species, which makes the Raman pump wavelength an additional experimental variable. Sampling this variable across the excited-state absorption manifold provides a selection criterion that separates coexisting transient species sharing a common vibrational window.

This study proposes a well-balanced formulation of weakly compressible smoothed particle hydrodynamics (WCSPH) for free-surface flows, which preserves hydrostatic equilibrium exactly at the discrete level–a property essential for reliable long-term simulations. Although well-balanced schemes are well established for mesh-based methods, the property remains largely unaddressed in WCSPH, where the particle approximation of the pressure gradient fails to balance the gravitational force exactly. The imbalance stems from two difficulties: the nonlinearity of the pressure-gradient-over-density term, and the approximation error of gradients evaluated by particle summation. The first is resolved by introducing an auxiliary potential variable that recasts the nonlinear term as the gradient of a single scalar, which reduces to a linear function of position under hydrostatic conditions. The second is resolved by a Riemann-based gradient approximation with kernel correction, which is first-order consistent and recovers linear fields exactly. These two ingredients ensure that the discrete potential gradient balances gravitational force exactly. Widely used techniques, including $\delta-$SPH, particle shifting and tensile instability control, are readily incorporated. The formulation is further extended to three dimensions and implemented on GPU with architecture-tailored optimizations. Hydrostatic tests with rectangular, triangular and Gaussian bottom topographies show that the proposed formulation attains the well-balanced property to machine precision, reducing the spurious velocity error of conventional SPH from $10^{-3}$ to the order of $10^{-13}$. More complex benchmarks confirm its robustness, accuracy and low pressure oscillation, with simulations of up to 17.53 million particles performed on a single consumer-grade GPU.

Core ionization is spatially localized, but the correlated valence response that screens the resulting hole need not be. Using the water dimer as a minimal hydrogen-bonded system, we ask whether acceptor-site O~1s ionization recruits valence channels on the neighboring donor molecule and how proton displacement redistributes that response. We introduce correlated shifted-start real-time $\Lambda$-coupled-cluster theory to connect the core-hole spectrum with orbital- and fragment-resolved screening pathways. At equilibrium, the satellite response contains donor-local and intermolecular charge-transfer-like contributions. Their intermolecular origin is supported by the strong suppression of both contributions when the monomers are separated. In a fixed-nuclei geometry scan, elongating the hydrogen-bonded donor O–H bond nearly doubles their combined share of the satellite response, while analysis of the first approximately 10~fs of the fixed-nuclei electronic response reveals stronger modulation involving a donor-localized valence orbital. More broadly, this work shows how localized core ionization can serve as a site-selective probe of electronic communication, with satellite structure revealing how nuclear geometry redirects many-electron screening through molecular environments.

We investigate localization phenomena and exact mobility edges in a quasiperiodic Aharonov-Bohm chain, where the 1D canonical diagonal and off-diagonal Aubry-André-Harper models are laterally coupled to an auxiliary sublattice threaded by a synthetic magnetic flux. By analytically computing the Lyapunov exponent via Avila's global theory of one-frequency Schrödinger operators, we derive exact expressions for mobility edges. In the diagonal limit, the coupling to the auxiliary sublattice generates hyperbolic mobility edges that exhibit a sign-changing divergence and can be continuously tuned by the magnetic flux. In the off-diagonal regime, the interference between quasiperiodic hopping and indirect tunneling through the auxiliary sublattice gives rise to exact anomalous mobility edges that separate critical and extended states. Critical states and anomalous mobility edges emerge even in the absence of incommensurately distributed zeros in the hopping modulation, a behavior distinct from that of conventional off-diagonal models. Our results establish a rigorous theoretical framework for engineering controllable mobility edges, with the synthetic flux providing a tunable experimental knob that paves the way for realizations in platforms such as superconducting quantum circuits and photonic waveguides.

Data scouting, introduced by the CMS collaboration in 2011, is a technique to extend the reach of the experiment beyond what full-event storage bandwidth allows: rather than the complete event record, only the physics objects already reconstructed by the High-Level Trigger (HLT) are persisted, which makes it affordable to record O(10) times more data than the standard physics stream. The price for this rate increase is in experimental resolution: online reconstruction has typically a lower resolution and a worse response, mostly due to shortcuts taken to speed up the reconstruction and to the use of suboptimal calibration constants. For this reason, scouting data has mostly been used when the resolution loss is negligible in absolute terms (muons) or with respect to the offline resolution (jets). In any case, the need to derive specific online-to-offline corrections has been a limiting factor. We show that a regression trained on a given object and the surrounding particle cloud can bring the gap between online and offline resolution within the typical uncertainty band of the offline data. This procedure could be applied to the scouting monitoring stream, the subset of scouting data also reconstructed offline. We demonstrate this on CMS Run-1 Open Data, reprocessed through paired HLT and offline passes over the same events. One architecture, applied unchanged to electrons and jets, suppresses residual biases by one to two orders of magnitude on various quantities (kinematics, isolation, energy composition) and achieves a resolution improvement. Measured differentially in p_T, the corrected objects fall inside the offline calibration uncertainties CMS quotes for this dataset, where the uncorrected HLT objects lie outside them: a corrected object can be treated with the standard, centrally provided calibration, bringing scouting data much closer to offline data for practical purposes.

Antiferromagnetic topological insulators provide a fertile platform where symmetry-breaking magnetic order is intertwined with topological electronic states. In particular, magnetic domain walls have attracted much attention, as they can be easily controlled by external fields as in general magnets, and moreover, host nontrivial electronic states distinct from those in bulks and sample surfaces. Here, we report a new antiferromagnetic topological insulator candidate DyPtBi, which hosts conductive magnetic domain walls controllable by uniaxial stress and magnetic field. We find that the resistivity exhibits abrupt increase upon the magnetic and structural phase transition. Concomitantly, the transverse ultrasonic mode shows remarkable softening of 6 %, indicating that the Dy 4f ferroquadrupolar order plays a vital role in the phase transition. Furthermore, we reveal by neutron experiments that applying compressive uniaxial stress aligns the magnetic domain state, leading to the strong resistivity enhancement of 14 % while eliminating the conductive magnetic domain walls. These findings demonstrate that DyPtBi exhibits topological electronic states entangled with multipolar degrees of freedom, providing a promising route for in situ control of topological properties.

We give in depth overview of charge-carrier mobility in p-type silicon double lateral-gate junctionless transistors (DLGJLT) through a mix of computer simulations and experimental results. The devices were built on low-doped silicon-on-insulator substrates using atomic force microscope nanolithography. Because the design uses air-gap side gates instead of a gate-oxide layer or junction, it allows electrical current to flow through a lightly doped silicon channel. This setup reduces impurity scattering and protects transport quality from interface damage. We used three-dimensional TCAD Sentaurus simulation tool to model the device's electrical behavior and confirm our experimental data for transconductance and drain conductance. We attempt to give a comprehensive view on the charge transition within the device.

Transformation method provides an efficient tool to control wave propagation inside the materials. Using the coordinate transformation approach, we study invisibility cloaks with sphere, cylinder and ellipsoid structures for electronic waves propagation. The underlying physics behind this investigation is the fact that the Schrödinger equation with position-dependent mass tensor and potentials has a covariant form that follows the coordinate transformation. Using this technique we obtain the exact spatial form of the mass tensor and potentials for a variety of cloaks with different shapes.

Extreme mass-ratio inspirals (EMRIs) can magnify small departures from Kerr dynamics into appreciable gravitational-wave phase shifts accumulated over many orbital cycles. We exploit this sensitivity to investigate the imprint of a rotating black hole's acceleration on an EMRI waveform. The spinning C metric poses two obstacles to the standard Kerr flux framework: the spacetime is not asymptotically flat, and the acceleration breaks the reflection symmetry that supports exactly equatorial circular timelike orbits. For sufficiently small acceleration $AM$, we therefore formulate the calculation in an intermediate Kerr-like wave zone satisfying $M/r\ll1$ and $Ar\ll1$, and construct a near-equatorial circular orbit by examining its coupled radial–polar stability. We derive the separated point-particle source for the spin$-2$ radial Teukolsky equation, construct a regular normalized angular solution, solve the radial equation using the Sasaki–Nakamura transformation and the Green function method, and couple the resulting horizon and far-zone fluxes to the adiabatic evolution of stable near-equatorial circular orbits. The framework recovers the Kerr limit and reproduces the dominant $l=2$ Kerr fluxes with relative errors of order $10^{-7}$. Acceleration modifies both radiation reaction and the orbital frequency, producing a characteristic nonmonotonic accumulated dephasing. For $M=10^6M_\odot$, $m_s/M=10^{-5}$, $a/M=0.7$, and $AM=3\times10^{-7}$, the dominant-mode dephasing slightly exceeds $1$ rad over one year. Thus even weak acceleration can generate an order-radian secular phase imprint on long-duration EMRIs within the controlled regime of the present approximation.

Estimating spectral density matrices for future space-based gravitational-wave detectors such as LISA is challenging due to the long duration of the data and the correlated instrumental noise across multiple time-delay interferometry channels. In this work, we investigate a specialized mean-field stochastic gradient variational Bayes (SGVB) procedure for fast posterior approximation in long-duration multivariate spectral density estimation. Based on the existing eigenbasis representation of the blocked Whittle likelihood approach, the posterior model applies a Cholesky factorization to represent the inverse spectral density matrix and models the resulting frequency-dependent entries with cosine basis functions, with a discounted regularized horseshoe prior assigned to the basis coefficients. We test mean-field SGVB as a stand-alone posterior approximation by comparing it with Hamiltonian Monte Carlo (HMC) targeting the same posterior model. In simulation studies based on autoregressive and moving average processes, SGVB produces posterior median spectral estimates close to those obtained from HMC at substantially lower computational cost. We then apply the method to two one-year, fixed-delay, stationary, noise-only LISA simulations and show that the SGVB spectral density estimates are consistent with HMC and Welch estimates across the LISA analysis band, while requiring substantially less computation. These results demonstrate that SGVB provides a scalable Bayesian approach to spectral density estimation for long-duration multivariate LISA noise analysis.

We study the thermal history of the primordial Universe in the presence of non-zero lepton and baryon asymmetries. Considering different scenarios, we determine the equation of state (EoS) of the Universe from T = 10 GeV down to T = 1 keV, spanning the QCD transition, hadron gas phase and neutrino decoupling epochs. Using a combination of numerical codes, we track the cosmic trajectories of chemical potentials associated with the baryonic, leptonic and electric charges, and follow the evolution of lepton asymmetries including through the era where neutrino oscillations take place. Combining peak theory with numerical-relativity simulations of the collapse threshold, we show the EoS-induced modifications to the primordial black hole (PBH) mass spectrum. We determine the associated Gravitational Wave (GW) signal, showing how lepton asymmetries and a particular spectral index of curvature perturbations can be hinted at by current ground interferometer-based GW observations. Finally, we discuss constraints and positive evidence for PBHs.

Synthesis of a target polymorph remains more empirical than predictive because crystallization often selects the most accessible nucleation pathway rather than the thermodynamically most stable phase. Here, we show that oxygen stoichiometry converts this empirical synthesis variable into a kinetic control parameter for anatase-rutile selection in TiO$_{2-x}$. Enhanced-sampling simulations reveal that oxygen content alters the nucleation-barrier landscape, switching the relative accessibility of anatase and rutile, even while rutile remains thermodynamically favored. Molecular dynamics simulations show the presence of a diffuse intermediate shell around the nucleus, where oxygen deficiency alters Ti-O coordination and connectivity and drives shell-local motif evolution from anatase-like toward rutile-like environments. A coupled-flux model that integrates barrier competition with shell-mediated attachment/exchange yields a relative nucleation-rate map consistent with reported oxygen-dependent synthesis trends. These results establish stoichiometry-controlled intermediate-shell motif evolution as a kinetic origin of polymorph selection and provide a framework for predicting target phases in composition-coupled crystallization.

We have used archival GALEX data to separate the cosmic ultraviolet background at the Galactic Poles into two components: the dust scattered light and an offset. We have modeled the dust-scattered light using a single- scattering model finding 1 sigma limits of 0.54 – 0.71 for the albedo (a) and 0.74 – 0.83 for the phase function asymmetry factor (g) at 1530 Å and 0.66 – 0.73 for a and 0.71 – 0.77 for g at 2360 Å, that is, the grains are moderately reflective and highly forward-scattering. The offsets are 277 – 284 photon units at 1530 Å and 513 – 520 photon units at 2360 Å. We have estimated other Galactic and extragalactic contributors to the offset finding that 161 +- 18 photon units is unaccounted for at 1530 Å and 335 +- 38 at 2360 Å. The offsets are constant over these regions with variances of 20 – 30 photon units.

We investigate electron injection into direct laser acceleration (DLA) in relativistic laser-driven plasma channels using particle-in-cell simulations. We identify and characterize a wavefront-guided injection mechanism, in which electrons are continuously fed into the plasma channel through the density pile-up layer at the laser-pulse front. Phase-space analysis reveals a localized injectable region within the pile-up layer, indicating that only a selected subset of electrons satisfies the conditions required for the subsequent direct laser acceleration. This mechanism provides a physical interpretation for the high-charge capability of DLA by explaining how electrons are continuously supplied to the accelerating channel. Beyond this continuous supply process, the injection dynamics are further modulated by the periodic variation of the carrier phase at the laser-pulse front. The spatial locations of injected electrons are found to be closely associated with magnetic-island structures formed under laser-phase modulation, suggesting that the laser wavefront not only supplies electrons but also organizes their entry into the accelerating channel. These findings advance the physical understanding of energetic-electron generation in relativistic laser-driven subcritical-density plasma channels and are relevant to the development of compact DLA-based particle and radiation sources.

The open-shell character of Kekulé graphene nanoflakes (GNFs) is conventionally rationalized by the gain of Clar aromatic $\pi$-sextets upon electron unpairing. While this rule successfully explains many quinoidal diradicaloids, it treats only the maximum number of sextets and neglects the multiplicity and spatial distribution of resonance configurations that realize the same Clar count. Here, we identify a second route to open-shell stabilization in which the maximum Clar-sextet number remains unchanged while the number of accessible Clar resonators increases substantially. We term this mechanism Clar-number-invariant resonance-space expansion. By enumerating closed-shell and open-shell Clar resonators and combining this analysis with a bonding entropy model (BEM), we show that electron unpairing can release closed-shell pairing constraints, enlarge the resonance manifold, and redistribute C–C bond occupancies away from localized single- and double-bond limits. The BEM-predicted number and spatial distribution of unpaired electrons correlate strongly with density-functional-theory diradical character, local magnetic moments, optimized C–C bond lengths, and relative energies across a broad set of GNFs. The resulting framework offers a graph-based and physically transparent route for screening open-shell carbon nanostructures and for designing tunable molecular spins without requiring an increase in the maximum Clar number.

This study introduces a coupled multi-domain framework to simulate direct current (DC) arcs, integrating thermal, fluid dynamic, and electromagnetic phenomena. We derive a two-dimensional (2D) axisymmetric model by simplifying the magneto-hydrodynamics (MHD) equations and implement it in MATLAB/Simulink. The model captures the spatiotemporal evolution of temperature, fluid velocity, and magnetic fields within a wall-stabilized arc column. Simulations across a 10 A to 1500 A current range show a pronounced radial temperature gradient, with central axis peaks and rapid peripheral decay. The approach's accuracy is validated by aligning the simulated velocity and magnetic fields with established physical paradigms. Additionally, the model accurately reproduces the inverse current-voltage characteristics observed in classical models and empirical studies, while transient analyses confirm rapid millisecond-scale voltage stabilization. This accessible computational model provides a robust foundation for investigating DC arc dynamics and facilitates system-level simulations for advanced circuit breakers, welding technologies, and plasma applications.

We consider an infinite one dimensional array of alternating charges embedded in a two-dimensional configuration space and subjected to a weak static electric field transverse to the lattice axis. Expansion of the Coulomb interaction about a lattice site gives a transverse restoring stiffness $\kappa \propto \zeta(3)/L^3$, defining the oscillator length $a_y$, while Bloch periodicity is retained along the lattice direction and the transverse motion is represented in a harmonic basis. The Coulomb matrix elements are governed by the dimensionless scale $\eta_{r-s}$, which couples the reciprocal-lattice transfer to the transverse oscillator length. A regularized one dimensional extension is also introduced through Coulomb regularization, yielding a finite diagonal offset and an exponentially decaying even-transfer coupling in reciprocal space. Small $\eta_{r-s}$ yields logarithmic, parity-dependent transverse-state coupling, while large $\eta_{r-s}$ approaches the one-dimensional Coulomb limit. In the finite-order spectrum, the latter approaches the Kronig Penney reference toward the band edge while retaining distinct Brillouin zone curvature. The formulation therefore identifies two characteristic quantities of the alternating lattice: the transverse restoring stiffness and the one-dimensional Madelung form, while retaining the two dimensional structure required to describe the response to a transverse electric field. Keywords: alternating charge lattice; Bloch states; Coulomb interaction; transverse electric field; regularization; reciprocal space coupling; Brillouin zone spectrum.

Mathematics has often been organized around an authorial subject: one person, or a small group, composing proofs through language, notation, and judgment. Large language models, proof assistants, formal libraries, and repositories now make another production unit technically credible: a human-machine assemblage. This article calls that unit a studio ecobiont and asks when it is epistemically legitimate. Its governance thesis is that human participation is substantive only when the system preserves traceable provenance, reconstructible human competence, capacity to challenge the result, effective authority to stop or withdraw it, and public responsibility. These conditions distinguish a governed studio from a degenerate studio whose human oversight is ceremonial. A comparison of Polymath, the Liquid Tensor Experiment, Danus, and the Jacobian counterexample episode shows that collaboration, formalization, technical orchestration, and epistemic governance are independent dimensions. The proposed understanding audit and contribution-authority trace are governance designs, not validated measures. No causal superiority over authorial practice is claimed.

The electromagnetic properties of a dilute unpolarized nonrelativistic neutron gas are described in the case when neutron-by-neutron scattering is negligible. The Gaussian (Maxwell-Boltzmann) and Fermi-Dirac one-particle density matrices for the neutron gas are considered, the typical space scale of variations of these density matrices being assumed to be much larger than the typical space scale of variations of the electromagnetic field. The Green functions for the static effective Maxwell equations are obtained. It is shown that a rarefied neutron gas does not possess a ferromagnetic instability even in a nonequilibrium state. The analog of Friedel oscillations is described. The properties of plasmon-polaritons in the neutron gas are revealed. It turns out that the dispersion law of longitudinal and transverse plasmon-polaritons has an infinite number of branches at a given momentum. The region of parameters where the plasmon-polaritons can be regarded as quasiparticles is found. The plasmon-polaritons on a Gaussian wave packet of a single electron are described. Their dispersion law proves to have an infinite number of branches at a given momentum. It is shown that there exist stable longitudinal plasmon-polaritons even on a single electron.

We investigate a proof-of-concept code designed to model the functionality of current generation astronomical fiber positioner instruments. This code accommodates an arbitrary number of fiber probes and astronomical targets. To establish the prerequisites for future fiber positioning technologies, we conduct a systematic analysis of both the observational and instrumentation parameter space (such as target density, fiber density, and exclusion and patrol radius). The tool assesses the efficiency and completeness of such a system by modeling the allocation of fibers to targets over multiple visits or observations, enabling the quantification of performance based on the specific parameters. This tool holds significance in delineating the technical specifications for future multi-object spectroscopy instrumentation. This will inform the development of new technologies for the next generation of telescopes using novel instrumentation techniques or the extension of existing technologies.

Dicke states $|J=N/2,m\rangle$ of a collection of $N$ atoms were central to Dicke's theory of superradiance. Except for the fully polarized end states, they are entangled many-body states; in particular, the single-excitation Dicke state is the W state well known in quantum information science. However, deterministic preparation of Dicke states with a prescribed spin projection remains challenging, especially without relying on postselection or heralding. Here we present a detuning-programmed Hamiltonian protocol using atoms or qubits in a dispersive cavity subject to a coherent transverse drive. In the absence of the drive, the off-resonant cavity produces an effective collective-spin interaction. By combining this cavity-mediated interaction with the coherent drive, tuning the atom–drive detuning enables the protocol, in principle, to target any allowed Dicke state along the symmetric Dicke ladder. Starting from the transverse-drive ground state, adiabatic ground-state interpolation prepares the selected Dicke state by ramping down the drive strength while ramping up the cavity-mediated interaction. After preparation, tuning the cavity into resonance with the atoms or qubits provides a direct way to probe the collective-emission response of the prepared Dicke state. We discuss implementation with superconducting circuit QED and show that the prepared states, especially the central Dicke state with $m=0$, provide resources for quantum sensing with Heisenberg-limited scaling.

The gravitational wave background detected by pulsar timing arrays is sourced by a finite population of supermassive black hole binaries, and is therefore anisotropic. We ask what measuring that anisotropy can teach us about the population, using models that span a wide range of effective source counts, all normalized to the measured background amplitude. We find four things. First, the expected anisotropy is produced by the single brightest binary: a dipole at the level of the published NANOGrav 95% upper limit would require one source to supply about 60% of the power in the band. Second, no model that also reproduces the measured strain spectrum contains a source that bright. In every case the loudest binary stays below the NANOGrav continuous-wave upper limit at every frequency it covers, consistent with the joint search of the 15-year data, which finds no resolved source. Third, because the anisotropy is produced by one source, compressing the sky to an angular power spectrum discards the phase information that locates it. Such a search is never more sensitive than looking for the source directly, and is strictly worse once more than a dipole is kept. Fourth, the published upper limits on the angular power spectrum therefore reflect the analysis prior rather than the data: they coincide with the 95th percentile of the prior induced by the square-root spherical harmonic basis adopted in the analysis. What does constrain the population today is the shape of the strain spectrum. Rare, bright sources depress the median spectrum below its mean, and fitting the measured spectrum already disfavors mass functions dominated by binaries above about 10^10 solar masses.

Quantifying the interactions between neighboring projects will be essential as carbon storage operations expand in scale. However, many existing basin-scale studies are deterministic or rely on hypothetical scenarios. In addition, simulations that do not fully account for neighboring projects may suffice for initial permitting. In this study, we develop a unified basin-scale model for the Broom Creek Formation in North Dakota. The model includes a total of five (existing and planned) projects, involving 18~injection wells with a maximum potential injection rate of 30~MTPA. The unified model, constructed by integrating publicly available geological and project data, contains $44\times10^6$ cells and requires over two days to run. To enable faster simulations, we present a multilevel treatment that combines four-level nested local grid refinement, constructed through the solution of a constraint-satisfaction problem, with optimized power averaging for permeability in coarse regions. After demonstrating the accuracy of the coarse model, we use it to assess uncertainty in key quantities of interest (QoIs), including total CO$_2$ injected and plume area after 50~years, across a wide range of geological realizations and model parameters. In addition, we develop a deep learning surrogate model, which is used in global sensitivity analyses to identify dominant contributors to QoI variance. Comparisons between the unified model and standalone project simulations are presented to quantify inter-project interference. This can be substantial in some cases, e.g., for one project, the median total CO$_2$ injected decreases from 271~MT (standalone) to 192~MT (unified model).

We prove that for every fixed inverse temperature $\beta < 1 / 2$, with high probability over the disorder, the single-site Glauber dynamics for the $n$-spin Sherrington-Kirkpatrick model mixes from every initial configuration to within total variation distance $\varepsilon$ in $O_{\beta}\left(n \log\left(n / \varepsilon\right)\right)$ steps. The bound holds uniformly over all external fields and is optimal up to constants depending only on $\beta$. The main ingredient is a deterministic criterion for optimal-order Poincaré inequalities in general Ising models, established via the integrated Bakry-Émery criterion together with a new two-spin estimate. A standard application of the localization-scheme framework of Chen and Eldan then upgrades the Poincaré inequality to a modified log-Sobolev inequality, yielding the optimal mixing-time bound. The main ideas underlying the proof of the Poincaré inequality were generated by GPT-5.6 Sol Ultra.

Deep thermalization concerns the emergence of universal pure-state statistics in projected ensembles at late times, yet the mechanism governing the initial growth of randomness remains unclear. Here, we study the short-time dynamics of projected ensembles generated from initially unentangled states, quantifying their randomness using frame potentials. For arbitrary Hamiltonians, provided the initial bath state has full support in the measurement basis, we show that the frame potentials to cubic order in time are determined entirely by the subsystem purity, and hence by the bipartite entanglement generated between the unmeasured subsystem and its complement. The entanglement timescale therefore sets the initial timescale for the growth of local randomness, independently of the bath measurement basis. For unitarily invariant Hamiltonian ensembles, we further relate the projected-ensemble frame potential at order $k$ to the $4k$-point spectral form factor, or equivalently to the $2k$th frame potential of the global unitary dynamics, establishing a direct connection between local and global randomness. Our results identify entanglement as the mechanism governing the onset of randomness in projected ensembles and clarify how local randomness emerges from global quantum dynamics.

AI data center power demand is spurring rapid deployment of on- and near-site natural gas turbines. The resulting nitrogen oxide NO$_x$ pollution is a growing concern but has not previously been quantified with atmospheric observations. Here we demonstrate space-based detection and quantification of NO$_x$ emissions from the SpaceXAI Colossus 2 power plant in Southaven, Mississippi. Using observations from the geostationary TEMPO satellite instrument, we detect a strong increase in local mean NO$_2$ column concentrations after the plant began operations in late 2025. We then use TEMPO to estimate two-week-average NO$_x$ source rates from August 2025 to August 2026, calibrating against continuous emission monitoring system (CEMS) data from US power plants. TEMPO first detected NO$_x$ emissions in December 2025 at 530$\pm$220 kg h$^{-1}$. We find that emissions increased through August 2026, averaging 870$\pm$165 kg h$^{-1}$ after February 2026, roughly 19$\pm$4 times higher than expected from the facility's March 2026 permit for 41 turbines operating under best available control technology (BACT) requirements ($\sim$47 kg h$^{-1}$). Emissions at the expected level would be undetectable by our TEMPO analysis.

Accurate modeling of the daily evolution of sea ice concentration (SIC) is central to improving the credibility and operational forecasting capability of deep learning-based sea ice prediction. However, existing deep learning methods often couple the underlying sea ice evolution relationships and data errors within high-dimensional nonlinear mappings, making it difficult to construct a stable and verifiable evolution core and apply it reliably to practical forecasting. To address this issue, this study proposes a reanalysis-forecast dual-domain decoupled framework for learning sea ice evolution operators. The framework builds upon a lightweight physical baseline to generate daily evolution trajectories, employs a temporally constrained joint multi-lead compensation network to com?pensate for unresolved processes, and introduces an ice-mass?aware transport mechanism to suppress numerical dissipation. In the forecasting stage, the parameters of the base evolution core are fixed, while a lightweight variable-semantic adaptation mechanism calibrates inter-domain distributions and evolution responses, thereby separating forecast-domain errors from base evolution errors. Experiments show that the constructed base evolution core can accurately and stably simulate daily sea ice evolution at both short-term and annual scales under reanal?ysis forcing, and can be effectively transferred to the forecast domain through lightweight adaptation, achieving stable prac?tical forecasting capability while preserving the base evolution structure. The source code will be made publicly available at https://github.com/zhangmaqun65535/SNM upon acceptance of this manuscript.

Our recently published papers reporting results of Direct Numerical Simulation (DNS) of forced convection flows in porous media suggest that in a porous medium the size of turbulent structures is restricted by the pore scale. Since the turbulent kinetic energy is predominantly contained within large eddies, this suggests that turbulent flow in a porous medium may carry less energy that its counterpart in a clear fluid domain. We use this insight to develop a practical model of turbulent flow in composite porous/fluid domains. In such domains, most of the flow is expected to occur in the clear fluid region; therefore, in most cases the flow in the porous region either remains laminar or starts its transition to turbulence even if the flow in the clear fluid region is fully turbulent. This conclusion is confirmed by comparing appropriate Reynolds numbers with their critical values. Therefore, for most cases, using the Forchheimer term in the momentum equation and the thermal dispersion term in the energy equation may result in a sufficiently good model for the porous region. However, what may really affect turbulent convection in composite domains is the roughness of the porous/fluid interface. If particles or fibers that constitute the porous medium (and the pores) are relatively large, the impact of the roughness on convection heat transfer in composite porous/fluid domains may be much more significant than the impact of possible turbulence in the porous region. We use the above considerations to develop a practical model of turbulent flow in a composite porous/fluid domain, concentrating on the effect of interface roughness on turbulence.