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Physics Physics

physics Watch Physics

Wednesday 11 March

Optics · Cross-listed from quant-ph

Remote engineering of particle-like topologies to visualise entanglement dynamics

Fazilah Nothlawala, Bereneice Sephton, Pedro Ornelas et al. (+6 more)

Skyrmions are a particle-like topology with a quantised skyrmion number, realised across condensed matter and photonic platforms alike. In quantum photonics, they constitute an emerging resource, promising robust quantum information encoding, so far realised as single photon and bi-photon entangled states. Here we report the first visualisation of tripartite entanglement dynamics through topological structure using spin-skyrmion entangled states, where the topology of a single photon is remotely controlled through the spin of its entangled partner. We visualise our tripartite state theoretically by introducing the notion of a topological Bloch sphere that completely captures the entanglement and topolological features of the state. By leveraging this state, we realise the first quantum multiskyrmions, comprising multiple localised skyrmions within a single structure, that emulate signatures of their magnetic counterparts. We verify this experimentally and show that traversing our topological sphere reveals entanglement-driven particle-like motion of the localised topological structures. These dynamics unveil a physical manifestation of tripartite entanglement correlations which we illustrate by example of GHZ-like states, enabling a visualisation of multiple Bell states encoded within our system. Our work opens exciting possibilities for quantum sensing by mapping complex quantum channel features onto topological observables of multipartite states and offers a promising avenue for harnessing quantum topologies for multi-level encoding quantum communication schemes.
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All authors Fazilah Nothlawala, Bereneice Sephton, Pedro Ornelas, Mwezi Koni, Bruno Piccirillo, Liang Feng, Isaac Nape, Vincenzo D'Ambrosio, Andrew Forbes

Physics and Society

Discontinuous Wealth-Gradient Transition Driving Cooperation

Hyun Gyu Lee, Hyeong-Chai Jeong and Deok-Sun Lee

The universal prevalence of cooperation is puzzling, as defection typically yields higher payoffs than cooperation, motivating searches for hidden pathways to cooperation. Here we study a game-theoretic model on a lattice structured population in which interaction payoffs are scaled by the minimum of participants' accumulated wealth, reflecting real-world heterogeneity and incorporating the influence of past strategic choices. This wealth scaling allows frequent cooperators to surpass defectors in payoffs through their greater wealth even at high cooperation costs where defection would otherwise dominate. At the elevated critical cost-benefit ratio, the wealth gradient at the cooperator-defector boundary in one dimension exhibits a discontinuous transition. We show that slowing and effective stalling of the boundary trigger an explosive buildup of the wealth gradient, driving the dominance of cooperation below the critical ratio. Remarkably, this promotion of cooperation is stronger at higher temperatures, revealing a constructive role of fluctuations.
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Accelerator Physics · Cross-listed from cond-mat.mtrl-sci

Microstructural Characterization of Nb3Sn Thin Films Using FIB Tomography

Eric Viklund, David N. Seidman and Sam Posen

The accelerating gradient of Nb3Sn superconducting radiofrequency (SRF) cavities is currently limited, and the underlying cause remains an open question in the field. One leading hypothesis attributes this limitation to the presence of tin-deficient regions within the Nb3Sn coating, which can suppress the superheating field. Due to the relatively large coherence length of Nb3Sn, defects near the surface may significantly interact with the RF field. However, these subsurface defects have proven difficult to characterize. This research aims to investigate the structure and distribution of subsurface Sn deficient regions to better understand their influence on cavity performance. We employ focused ion beam (FIB) tomography to analyze the subsurface microstructure of Nb3Sn thin films. This technique enables three-dimensional reconstruction of both the tin distribution and the grain structure within the film. By correlating Sn content with grain structure, we find that Sn deficient regions are more prevalent that previously thought. However, the Sn deficient regions are consistently located below the surface of the film where RF fields are strongly attenuated by supercurrent screening and are likely not a limiting factor for cavity performance.
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Optics

Arbitrary Polarization Generation in Magneto-optical Metasurfaces Enabled by Bound States in the Continuum

Siyuan Gao, Guangtai Lu, Satoshi Iwamoto et al. (+1 more)

The generation of arbitrary polarization states of light is essential for optical communication and photonic information processing. Photonic crystal and metasurface platforms supporting bound states in the continuum (BICs) provide a powerful route for polarization engineering through tailoring the radiation from the resonant modes. However, existing approaches typically rely on static structural symmetry breaking or off-normal radiation, which limits continuous polarization tuning of vertical radiation. Here, we demonstrate a magnetooptical metasurface that generates arbitrary polarization states of light at normal radiation. By applying an external magnetic field with variable rientation, a symmetry-protected BIC is transformed into a quasi-BIC whose radiation polarization can be continuously tuned. The magneto-optical perturbation drives the controlled migration of polarization singularities in momentum space, allowing the emitted states to continuously span the entire Poincaré sphere without structural modification. This approach establishes a compact platform for actively tunable polarization sources and polarizationencoded photonic devices.
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All authors Siyuan Gao, Guangtai Lu, Satoshi Iwamoto, Yasutomo Ota

Plasma Physics

Beam-Plasma Collective Oscillations in Intense Charged-Particle Beams: Dielectric Response Theory, Langmuir Wave Dispersion, and Unsupervised Detection via Prometheus

Brandon Yee, Wilson Collins, Michael Iofin et al. (+1 more)

We develop a theoretical and computational framework for beam-plasma collective oscillations in intense charged-particle beams at intermediate energies (10-100 MeV). In Part I, we formulate a kinetic field theory governed by the Vlasov-Poisson system, deriving the Lindhard dielectric function and random phase approximation (RPA) polarization tensor for three beam distribution functions. We prove via the dielectric function epsilon(omega,q)=0 the existence of undamped Langmuir wave modes above a critical beam density n_c, obtain explicit beam-plasma dispersion relations, and show that Landau damping vanishes above the particle-hole continuum. The plasma frequency Omega_p^2 = ne^2/(m*epsilon_0) is fixed by the f-sum rule independently of distribution shape; higher dispersion coefficients depend on velocity moments. Space charge effects drive anomalous beam broadening with sqrt(n-n_c) onset and Friedel oscillations at q=2k_F. The beam-plasma transition belongs to the 3D Ising universality class via renormalization group analysis. In Part II, we validate these predictions using Prometheus, a beta-VAE trained on static structure factor data S(q) from particle-in-cell (PIC) beam simulations. Prometheus detects collective plasma oscillation onset in Gaussian and uniform distributions, confirms their absence in the degenerate Fermi gas (n_c -> 0), and resolves the Kohn anomaly at q=2k_F. Dispersion analysis of S(q,omega) from PIC simulations verifies the distribution-independent Omega_p predicted by the f-sum rule. All six validation checks pass. Predicted signatures – density-tunable plasma resonances at omega_p proportional to sqrt(n), anomalous beam broadening with sqrt(n-n_c) onset, and Friedel oscillations – are accessible at existing intermediate-energy beam facilities.
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All authors Brandon Yee, Wilson Collins, Michael Iofin, Jiayi Fu

Instrumentation and Detectors

Development of an Extensible Unified Control System Using the STARS Framework and Common Commands for Detector Control

Ryutaro Nishimura, Yuki Shibazaki, Daisuke Wakabayashi et al. (+5 more)

A zooming optical system comprising two Fresnel zone plates (FZPs) was developed and installed at the AR-NE1A beamline of the Photon Factory, High Energy Accelerator Research Organization (KEK), Japan. To ensure reliable and versatile operation, we implemented a dedicated control architecture based on the Simple Transmission and Retrieval System (STARS) framework and the newly proposed STARS Common Commands for Detector Control (CCDC)—a data-acquisition (DAQ) state model and command set designed specifically for detector control. The system serves both as a practical control system for the zooming optics and as a demonstration of modular extensibility using STARS and detector interoperability through CCDC. The system has been commissioned, and its performance has been verified at the AR-NE1A beamline. The architecture enables flexible configuration of optical components and provides a unified interface for both routine operation and advanced experimental protocols.
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All authors Ryutaro Nishimura, Yuki Shibazaki, Daisuke Wakabayashi, Yoshio Suzuki, Keiichi Hirano, Hiroaki Nitani, Takashi Kosuge, Noriyuki Igarashi

Computational Physics · Cross-listed from cond-mat.str-el

Ab initio quantum embedding description of magic angle twisted bilayer graphene at even-integer fillings

Raehyun Kim, Woochang Kim, Kevin D. Stubbs et al. (+2 more)

Magic angle twisted bilayer graphene (MATBG) hosts narrow moiré bands with meV-scale energy splittings, making its correlated phases sensitive to both material parameters and modeling choices in low-energy downfolding. We develop an ab initio quantum-embedding workflow that derives interacting flat-band Hamiltonians from Kohn-Sham density functional theory (KS-DFT) of a relaxed, unstrained structure. Our model combines constrained random phase approximation (cRPA) screening, controlled double-counting subtraction, and an automated gauge-fixing procedure based on the selected columns of the density matrix (SCDM) that is compatible with symmetry-resolved many-body calculations. Solving the resulting models using Hartree-Fock (HF) and coupled cluster singles and doubles (CCSD), we recover robust insulating Kramers intervalley coherent (KIVC) states at charge neutrality ($\nu=0$) and at electron doping ($\nu=+2$). The main new physical effect appears on the hole-doped side: at $\nu=-2$ we observe a fragile semimetal with a weak $\sqrt{3}\times\sqrt{3}$ Kekulé modulation and enhanced intervalley-scattering peaks in the Fourier-transformed local density of states. Although the underlying KS-DFT band structure is nearly particle-hole symmetric, the effective interacting Hamiltonian exhibits a pronounced particle-hole asymmetry at $\nu=\pm 2$ that we trace to momentum-dependent single-particle renormalizations generated by subtraction terms constructed from reference densities consistent with the KS-DFT filling. Our work provides a first-principles route for connecting microscopic electronic structure, screened interactions, subtraction choices, and scanning tunneling microscopy signatures in MATBG.
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All authors Raehyun Kim, Woochang Kim, Kevin D. Stubbs, Steven G. Louie, Lin Lin

Chemical Physics

Generalized Einstein Relations between Absorption and Emission Spectra in the Electric-Dipole Approximation

Jisu Ryu and David M. Jonas

Recently, Ryu et al. showed that two broadened bands connected by a set of four Einstein-coefficient spectra for stimulated and spontaneous single-photon transitions will obey detailed balance at equilibrium if the spectra satisfy generalized Einstein relations. Here, quantum mechanical expressions for Einstein-coefficient spectra are obtained in the electric-dipole approximation using an intramolecular Boltzmann distribution and the quantized field operators in isotropic, dispersive media of Nienhuis and Alkemade. These expressions suggest relationships between Einstein-coefficient spectra and dipole-strength spectra. The electrodynamic relationship between the spectral density for electromagnetic energy and the spectral density for the square of the electric field is developed and used to define dipole-strength spectra in terms of conditional transition probabilities per unit time. These rigorously relate dipole-strength spectra to Einstein-coefficient spectra, thus establishing quantum formulas for dipole-strength spectra and new generalized Einstein relations between dipole-strength spectra. For transitions between two bands, the dipole-strength spectra depend on a single total dipole strength but replace Einstein's degeneracy ratio and transition frequency with a change in standard chemical potential and a single underlying lineshape that is manifested differently in the four spectra. At equilibrium, the relations specify the Stokes' shift between forward and reverse transitions. The relationships between dipole-strength spectra, spontaneous emission spectral densities and stimulated transition cross sections depend on the refractive index, the dielectric constant, and the local field, but not on the derivative of the refractive index. The broadband relationships reduce to known relationships for narrow spectra inside materials and for line spectra in vacuum.
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Computational Physics

A mapping-based projection of detailed kinetics uncertainty onto reduced manifolds

Vansh Sharma, Shuzhi Zhang, Rahul Jain et al. (+1 more)

Propagating uncertainties introduced by chemical reaction rate parameters to high-fidelity numerical simulations of complex combustion devices is necessary to ascertain impact on computational predictions. However, the high cost of detailed computations combined with the need to conduct multiple simulations to propagate uncertainty makes such an estimation computationally challenging. In order to reduce the computational cost, a two-step framework for quantifying uncertainty introduced by detailed chemical kinetics model parameters using reduced chemistry models is developed here. First, reduced-manifold states are uniquely reconstructed in full-composition space by following trajectories at an unburnt mixing state and integrating forward to a prescribed progress variable constraint. Second, parametric uncertainty is propagated by sampling perturbed rate coefficients from mechanism covariance matrices and integrating each realization to the target state, yielding uncertainty maps for reduced-space quantities. The method is applied in two configurations: a subsonic multi-tube combustor with interacting jet flames and recirculation, and a three-dimensional reacting high-speed flowpath. Uncertainty-instrumented estimated are reported for a trajectory time (time for the reconstructed unreacted mixture to reach the local target state) and for the time to equilibrium, revealing order-of-magnitude spatial variations driven by mixing, stratification, and residence-time effects. The largest relative variability occurs in low-to-intermediate temperature regimes associated with induction and the onset of heat release, where branching-related chemistry amplifies sensitivity, particularly away from stoichiometric conditions. The method provides a scalable route to spatially resolved, physically interpretable chemistry-UQ for practical reacting-flow simulations.
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All authors Vansh Sharma, Shuzhi Zhang, Rahul Jain, Venkat Raman

Optics

Information-Theoretic Spectroscopy: Universal Sparsity of Extinction Manifold and Optimal Sensing across Scattering Regimes

Proity Nayeeb Akbar

The inverse reconstruction of material properties from optical extinction efficiency (Qext) is constrained by the high-dimensional nature of Mie scattering. We demonstrate that the Qext manifold possesses an intrinsic, physics-governed sparsity universal across dielectric materials. By analyzing the spectral topology of a diverse polymer library, we identify a critical Information Bottleneck at the onset of the Mie transition (r approx 0.1 um), where a peak in spectral entropy signifies a fundamental limit on signal compressibility. While the Fast Fourier Transform (FFT) is conventionally used for spectral analysis, we show it is physically mismatched for this domain; its periodic boundary assumptions induce spectral leakage that forces a massive basis expansion to resolve Mie ripples. Conversely, the Discrete Cosine Transform (DCT) mirrors the non-periodic geometry of extinction profiles, uncovering inherent compressibility by capturing over 90% of signal energy using fewer than 10 harmonic modes. Even at the Mie bottleneck, the DCT maintains a 12-fold compression advantage over the FFT at a 99% energy threshold. Notably, while both bases converge to identical error floors for a fixed energy threshold, the DCT achieves this fidelity with significantly lower hardware overhead. Stress-testing under 10% additive Gaussian noise confirms the Information Bottleneck is spatially and structurally invariant, proving this complexity peak is a fundamental physical constant of the manifold. By mapping this sparsity onto a compressed sensing architecture, we resolve a 2.5-20 um spectral range using between 22 and 170 sensors: enabling a 51%-94% reduction in hardware complexity that breaks the traditional Nyquist sampling limit (350 sensors) for high-fidelity clinical and remote sensing applications.
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Optics

Single-shot in situ pulse-duration measurement using plasma grating

Jimin Wang, Yanlei Zuo, Kainan Zhou et al. (+10 more)

Accurate measurement of the pulse duration of ultrashort, ultra-intense laser pulses at focus is essential for strong-field science. Most existing diagnostics, however, cannot allow direct in situ measurement in the focal region because of damage-threshold limits and unavoidable spatial averaging. We present a direct single-shot far-field diagnostic based on a plasma grating. In this method, the pulse duration is encoded in the axial length of an interference-written plasma grating and retrieved from the corresponding Bragg-diffraction signal. Comparison with near-field (pre-focus) autocorrelator measurements and far-field (at-focus) scanning measurements confirms single-shot pulse-duration retrieval in the focal region over 35-130 fs, and the method remains effective at a peak intensity of $\sim 10^{16}{\rm W/cm^2}$. In principle, the measurable range can be extended to 15-300 fs and to higher peak intensities. The method is insensitive to the laser central wavelength and offers a practical approach to far-field diagnostics in high-power laser systems.
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All authors Jimin Wang, Yanlei Zuo, Kainan Zhou, Zhaoli Li, Pengyu Wei, Xiao Wang, Jie Mu, Xiaodong Wang, Xiaoming Zeng, Zhaohui Wu, Hao Peng, C.Riconda, S.Weber

Space Physics · Cross-listed from astro-ph.SR

Full Dynamical Model (SOCOL:14C-Ex) of 14C Atmospheric Production and Transport in Application to Miyake Events

Kseniia Golubenko, Ilya Usoskin, Edouard Bard et al. (+2 more)

Extreme solar particle events (ESPEs) are caused by rare, enormously strong solar eruptions and can produce globally detectable spikes in tree-ring radiocarbon 14C, known as Miyake events, which serve as precise chronological tie-points and indicators of extreme solar activity. After production, radiocarbon is subjected to the complex carbon cycle, including large-scale atmospheric transport, which is crucially important for fast and strong Miyake events with highly inhomogeneous 14C production. A new 3D dynamical model, SOCOL:14C-Ex, of the radiocarbon atmospheric production and transport is presented here, which can model fast changes in the 14C atmospheric concentrations with high temporal and spatial resolution. Precise response curves of $\Delta^{14}$C to a reference ESPE (100xGLE#69) were computed for various event dates. They can be directly applied to analyse Miyake events under different conditions. Seven strong events over the past 14 millennia (AD 993, AD 774, 664 BC, 5260 BC, 5411 BC, 7177 BC, and 12351 BC) were analysed by fitting the reference curves to the available annual D14C data, identifying the most probable values and confidence intervals of their parameters – strength, event's date and background level. By applying corrections for the geomagnetic and atmospheric (CO2) factors, the strengths of the corresponding ESPEs were assessed. The strongest ESPE is confirmed to be that of 12351 BC, while that of AD 774 remains the strongest event during the Holocene. To conclude, a new tool, based on the radiocarbon atmospheric transport model SOCOL:14C-Ex, is presented to analyse fast changes in the $^{14}$C production.
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All authors Kseniia Golubenko, Ilya Usoskin, Edouard Bard, Sergey Koldobskiy, Eugene Rozanov

Chemical Physics · Cross-listed from quant-ph

Geo-ADAPT-VQE: Quantum Information Metric-Aware Circuit Optimization for Quantum Chemistry

Mohammad Aamir Sohail and Toshiaki Koike-Akino

Adaptive ansatz construction has emerged as a powerful technique for reducing circuit depth and improving optimization efficiency in variational quantum eigensolvers. However, existing adaptive methods, including ADAPT-VQE, rely solely on first-order gradients and therefore ignore the underlying geometry of the quantum state space, limiting both convergence behavior and operator-selection efficiency. We introduce Geo-ADAPT-VQE, a geometry-aware adaptive VQE algorithm that selects operators from a pool using the natural gradient rule. The geometric operator-selection rule enables the ansatz to grow along directions aligned with the underlying quantum-state geometry, thereby improving convergence and reducing the algorithm's susceptibility to shallow local minima and saddle-point regions. We further provide an asymptotic convergence result. We present numerical simulations involving five molecules, which demonstrate that Geo-ADAPT-VQE achieves faster and more stable convergence compared to existing methods, while producing significantly shorter ansatz. In particular, Geo-ADAPT achieves up to 100-fold reduction in energy error compared to existing methods.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG

Data-Driven Integration Kernels for Interpretable Nonlocal Operator Learning

Savannah L. Ferretti, Jerry Lin, Sara Shamekh et al. (+3 more)

Machine learning models can represent climate processes that are nonlocal in horizontal space, height, and time, often by combining information across these dimensions in highly nonlinear ways. While this can improve predictive skill, it makes learned relationships difficult to interpret and prone to overfitting as the extent of nonlocal information grows. We address this challenge by introducing data-driven integration kernels, a framework that adds structure to nonlocal operator learning by explicitly separating nonlocal information aggregation from local nonlinear prediction. Each spatiotemporal predictor field is first integrated using learnable kernels (defined as continuous weighting functions over horizontal space, height, and/or time), after which a local nonlinear mapping is applied only to the resulting kernel-integrated features and optional local inputs. This design confines nonlinear interactions to a small set of integrated features and makes each kernel directly interpretable as a weighting pattern that reveals which horizontal locations, vertical levels, and/or past timesteps contribute most to the prediction. We demonstrate the framework for South Asian monsoon precipitation using a hierarchy of neural network models with increasing structure, including baseline, nonparametric kernel, and parametric kernel models. Across this hierarchy, kernel models achieve near-baseline performance with far fewer trainable parameters, indicating that much of the relevant nonlocal information can be captured through a small set of interpretable integrations when appropriate structural constraints are imposed.
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All authors Savannah L. Ferretti, Jerry Lin, Sara Shamekh, Jane W. Baldwin, Michael S. Pritchard, Tom Beucler

Optics

Engineering the Frozen Mode Near a Stationary Inflection Point in Coupled Single-Mode Waveguides with Lateral Gratings

Albert Herrero-Parareda, Nathaniel Furman, Bradley J. Thompson et al. (+3 more)

We introduce a systematic approach to designing slow-light photonic integrated circuits supporting a frozen mode associated with a third-order exceptional point of degeneracy (EPD), known as a stationary inflection point (SIP). The proposed approach employs three-way coupled waveguides incorporating lateral gratings and operating at telecommunication wavelengths. We investigate two distinct waveguide configurations and demonstrate the formation of SIPs through full-wave eigenmode simulations. We also analyze the sensitivity of the dispersion characteristics to geometric perturbations and realistic fabrication constraints. A periodic waveguide with integrated tapered terminations is fabricated and experimentally characterized, revealing spectral features that are qualitatively consistent with numerical predictions. Simulations of finite-length structures further demonstrate substantial group-delay enhancement near the SIP frequency. These results establish a practical approach to realizing frozen-mode waveguides and integrating SIP-based slow-light functionalities into silicon photonic circuits.
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All authors Albert Herrero-Parareda, Nathaniel Furman, Bradley J. Thompson, Ricky Gibson, Ilya Vitebskiy, Filippo Capolino

Tuesday 10 March

Applied Physics

Theoretical Ion Sputtering Yields from Loose Powders using a Multiscale Monte Carlo Approach

Sebastien Verkercke, Deborah Berhanu, Caixia Bu et al. (+5 more)

Ion sputtering from loose powders remains poorly understood despite its relevance to planetary science and industry. We developed a multiscale Monte Carlo model to simulate sputtering from powders, using a higher-fidelity approach for the target geometry compared to voxel-based methods. Simulating Kr+ ions impacting Cu powders and flat slabs, we show that sputtering from loose powders differs markedly from that of flat slabs or rough surfaces. The main differences are: (1) for incident angles a > 0 degree relative to the bulk normal, the escaping sputtering yield is dominated by backward-directed ejecta for all ion energies; (2) for a < 60 degrees, the yield peaks toward the ion-beam origin, similar to the opposition effect seen in optical observations of airless bodies; (3) the angular distribution peak is half or less than that of a flat slab; (4) as ion energy increases, no evolution occurs from primary to secondary knock-on sputtering in the ejecta angular distribution. We attribute these behaviors to the powders interconnected voids. Ions penetrate these voids and sputter underlying grains; the ejecta then preferentially escape toward the ion-beam origin, where shadowing is minimal. We derive two fitting functions: 1) relating the escaping sputtering yield of a powder to that of a flat surface, depending only on porosity, incident angle, mean local incidence angle, and the corresponding flat slab yield; 2) providing the double-differential angular distribution of the escaping ejecta for porosities > 0.49. These provide a potentially universal fitting function of the absolute doubly-differential escaping sputtering yield from loose powders.
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All authors Sebastien Verkercke, Deborah Berhanu, Caixia Bu, Benjamin Clouter-Gergen, Francois Leblanc, Jesse R. Lewis, Liam S. Morrissey, Daniel W. Savin

Atmospheric and Oceanic Physics

Developing Machine Learning-Based Watch-to-Warning Severe Weather Guidance from the Warn-on-Forecast System

Montgomery Flora, Samuel Varga, Corey Potvin et al. (+1 more)

While machine learning (ML) post-processing of convection-allowing model (CAM) output for severe weather hazards (large hail, damaging winds, and/or tornadoes) has shown promise for very short lead times (0-3 hours), its application to slightly longer forecast windows remains relatively underexplored. In this study, we develop and evaluate a grid-based ML framework to predict the probability of severe weather hazards over the next 2-6 hours using forecast output from the Warn-on-Forecast System (WoFS). Our dataset includes WoFS ensemble forecasts valid every 5 minutes out to 6 hours from 108 days during the 2019–2023 NOAA Hazardous Weather Testbed Spring Forecasting Experiments. We train ML models to generate probabilistic forecasts of severe weather akin to Storm Prediction Center outlooks (i.e., likelihood of a tornado, severe wind, or severe hail event within 36 km of each point). We compare a histogram gradient-boosted tree (HGBT) model and a deep learning U-Net approach against a carefully calibrated baseline generated from 2-5 km updraft helicity. Results indicate that the HGBT and U-Net outperform the baseline, particularly at higher probability thresholds. The HGBT achieves the best performance metrics, but predicted probabilities cap at 60% while the U-net forecasts extend to 100%. Similar to previous studies, the U-Net produces spatially smoother guidance than the tree-based method. These findings add to the growing evidence of the effectiveness of ML-based CAM post-processing for providing short-term severe weather guidance.
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All authors Montgomery Flora, Samuel Varga, Corey Potvin, Noah Lang

General Physics

High energy particle collisions under Cauchy horizon

A. V. Toporensky and O. B. Zaslavskii

We consider particle collision inside the inner horizon of the Reissner-Nordstrom metric in the so-called R region. We show that there exist scenario in which the enrgy in the center of mass frame grows unbounded. In contrast to the standard scenarios of high energy collisions in black hole background in the R region, fine tuning of particle parameters is not require. The effect found in this work can be considered as a massive particle counterpart of wave processes that contribute to instability of the inner black hole horizon.
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General Physics

Off-diagonal solutions in Einsteingravity modeling f(R) gravity and dynamical darkenergy vs Lambda CDM cosmology

Sergiu I. Vacaru

Modified gravity theories (MGTs) have long been studied as alternatives to general relativity (GR) and the standard Lambda CDM cosmological model. For example, exponential f(R) models often yield better fits to observational data, suggesting that Lambda CDM may be inadequate. In this work, we argue that the gravitational and accelerating cosmology paradigm can remain close to GR and Lambda CDM if one considers broader classes of off-diagonal cosmological solutions of the Einstein equations. These solutions are constructed using the anholonomic frame and connection deformation method (AFCDM), which enables the decoupling and integration of nonlinear systems of partial differential equations in nonholonomic dyadic variables with connection distortions. The resulting off-diagonal Einstein manifolds and cosmological models are characterized by nonholonomic constraints, nonlinear symmetries, and effective cosmological constants. Such structures allow one to approximate cosmological effects, mimic features of MGTs, and describe gravitational polarization, local anisotropies, and dark energy and dark matter phenomena within GR.
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Instrumentation and Detectors

Reduced Thermodynamic-Topological Observables for Multiscale Dissipative Systems. A fusion-relevant shell-model study of detection, design screening, and conservative operation

Andrea Caffagni

We introduce a reduced set of thermodynamic-topological observables for ordered multiscale dissipative systems. An interface-local quadratic reduction produces bounded integrity and residual channels, a flux-force stability channel, a weighted path-graph bottleneck channel, and a coarse-graining drift indicator. The goal is practical rather than universal: a compact and interpretable layer of observables that can be computed repeatedly and compared across regimes. The main case study is a fusion-relevant MHD Sabra shell model. Across 400 synthetic anomalous-dissipation probes, the local Prigogine-style channel detects 400/400 events, while a composite alarm detects 399/400 with lower latency. When an OPCR trigger and an energy-collapse proxy are both observed within the same event, the earliest OPCR trigger leads the proxy by 11.29+/-13.49 model-time units on average (median 6.15, IQR [1.23, 17.22]; 255/313 early cases). A scan over 5000 coupling geometries raises the best log-Cheeger conductance from a baseline mean 0.07475+/-0.00171 to 0.09465 (+26.6%), whereas the current minimum-Phi geometry remains below the baseline mean. For operation, integrity-aware actuation and a conservative Phi-instrumented variant achieve 3.01x and 3.02x the recovery-per-unit-power efficiency of a uniform baseline. These numerics support a topology-first reading of the framework: hlog is credible as a Phase-1 design-screening observable, whereas Phi is presently best viewed as an operational or certification score. For fusion, the natural target is stellarator configuration screening, where magnetic topology dominates. A short appendix gives a toy neural-network portability check and is not used for the paper's main claims.
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Optics

Avalanche Sensing via Kerr frequency comb in an Optical Microcavity

Chenchen Wang, Qingyi Zhou, Lan Yang et al. (+1 more)

Sensors based on optical microcavities enhance light-matter interactions within an ultraconfined volume, enabling high-sensitivity detection across a wide range of sensing applications. In these systems, environmental perturbations modify the intrinsic resonance properties of the cavity, typically manifested as frequency shifts, linewidth broadening, or mode splitting. However, the minimum resolvable change in these spectral properties fundamentally limits the overall sensor sensitivity. Here, we propose a new avalanche sensing scheme enabled by Kerr nonlinearity. Instead of relying on the detection of frequency shifts, our approach exploits abrupt state transitions in a Kerr frequency comb to amplify weak perturbations. We provide a theoretical analysis of the underlying mechanism of this scheme and validate the concept through both coupled-mode theory (CMT) modeling and full-wave electromagnetic simulations.
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All authors Chenchen Wang, Qingyi Zhou, Lan Yang, Zongfu Yu

Chemical Physics · Cross-listed from quant-ph

Light-Matter Interactions Beyond the Dipole Approximation in Extended Systems Without Multipole Expansion

Rishabh Dora, Roman Korol, Vishal Tiwari et al. (+2 more)

We present a general theoretical framework to capture light-matter interactions beyond the electric-dipole approximation (EDA), applicable to extended nano- and microscale materials interacting with spatially structured electric fields without truncation at finite multipolar order. The approach is based on the Power-Zienau-Woolley (PZW) Hamiltonian for light-matter interactions and a representation of the material's Hamiltonian in a basis of maximally localized Wannier functions (MLWFs), obtainable from first-principles calculations. We utilize this approach to clarify the limitations of the ubiquitous dipole approximation. We consider electric fields with both uniform and non-uniform intensities and a range of ratios of system size to the wavelength of light. Through this analysis, we identify the conditions under which the EDA breaks down, leading to significant errors in the light-induced dynamics. Contrary to conventional belief, we find that the EDA is remarkably robust for uniformly illuminated 1-D or 2-D materials when light propagates perpendicular to the material. For 3-D materials or non-perpendicular illumination of lower-dimensional materials, conventional wisdom holds and the EDA begins to break down when the wavelength becomes comparable to the system size. Furthermore, the EDA fails when the material is illuminated partially or non-uniformly. For slowly varying field intensities this failure can be corrected by finite-order multipolar corrections. However, for fields that vary substantially, correcting via multipolar terms becomes computationally impractical. In contrast, our approach captures beyond-dipole light-matter interactions at the computational cost of a standard dipole calculation. This efficiency enables accurate first-principles simulations of spatially structured light-matter dynamics in nanoscale devices, quantum materials, and interfaces.
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All authors Rishabh Dora, Roman Korol, Vishal Tiwari, Rahul Chourasiya, Ignacio Franco

Optics · Cross-listed from cond-mat.mtrl-sci

A fully solution-processed organic microcavity laser in the strong light-matter coupling regime

Hassan A. Qureshi, Henri Lyyra, Akseli Korkeamäki et al. (+3 more)

Solid-state semiconductor lasers underpin technologies from telecommunications and data storage to sensing, medical diagnostics, and emerging quantum communication. Polaritons-hybrid exciton-photon states have further extended this reach, enabling room-temperature quantum effects such as low-threshold lasing and single-photon nonlinearities. Organic semiconductors are ideal for polaritonics due to their large exciton binding energy, strong optical nonlinearities, and straightforward processing, making them attractive for both classical and quantum photonics. While solution-processed organic films have been widely explored, their optical cavities have almost always been fabricated using vacuum deposition, limiting the realization of truly scalable and low-cost devices. Here, we report the first organic laser microcavities fabricated entirely by solution processing, which operate in the strong coupling regimeThe resulting platform can be driven reliably to high excitation densities, where we observe a reversible, interaction-driven redistribution of the polariton condensate, revealing a distinct polariton lasing behaviour in organic microcavities. Together, the fabrication approach and the observed lasing dynamics establish a route toward scalable polaritonic and quantum photonic technologies and provide new opportunities for studying nonlinear polariton physics in organic systems.
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All authors Hassan A. Qureshi, Henri Lyyra, Akseli Korkeamäki, Oskar Tuomi, Antti J. Moilanen, Konstantinos S. Daskalakis

Data Analysis and Statistics · Cross-listed from stat.ML

Bayesian Hierarchical Models and the Maximum Entropy Principle

Brendon J. Brewer

Bayesian hierarchical models are frequently used in practical data analysis contexts. One interpretation of these models is that they provide an indirect way of assigning a prior for unknown parameters, through the introduction of hyperparameters. The resulting marginal prior for the parameters (integrating over the hyperparameters) is usually dependent, so that learning one parameter provides some information about the others. In this contribution, I will demonstrate that, when the prior given the hyperparameters is a canonical distribution (a maximum entropy distribution with moment constraints), the dependent marginal prior also has a maximum entropy property, with a different constraint. This constraint is on the marginal distribution of some function of the unknown quantities. The results shed light on what information is actually being assumed when we assign a hierarchical model.
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Plasma Physics · Cross-listed from astro-ph.HE

Linear Mode Conversion in Ultramagnetized Pair Plasmas: Single-Parameter Scaling

Dawei Dai, Ashley Bransgrove, Anirudh Prabhu et al. (+1 more)

In neutron star (NS) magnetospheres, plasma waves propagate as normal modes with distinct propagation dynamics that strongly influence observable signals. This letter presents a unified theory of linear mode conversion between Alfv'en (A), superluminal ordinary (O), and extraordinary (X) modes, incorporating the effect of magnetic-field geometry and local plasma response. Magnetic field-line curvature induces A-X conversion for low frequencies and O-X conversion at high frequencies, whereas plasma gradients alone do not drive X-mode coupling. We show that a single dimensionless parameter controls both conversion channels. The conversion efficiency follows the universal nonadiabatic transition probability of a multilevel quantum system. Efficient conversion occurs within a narrow angular window between the wave vector and magnetic field, localizing potential conversion sites in the NS magnetosphere. This linear mechanism naturally accounts for complex polarization features observed in pulsars and some fast radio bursts.
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All authors Dawei Dai, Ashley Bransgrove, Anirudh Prabhu, Jens F. Mahlmann

Physics and Society

The propensity for disobedience: Rule-breaking, compliance and social phase transitions

Nuno Crokidakis

We develop a mathematical model to describe the persistence of rule-breaking behaviors in societies, such as traffic violations, disregard for legal restrictions and other forms of noncompliance. Using a replicator-type dynamics with utility functions incorporating individual benefits, institutional punishment and social sanctions, we first built a general formulation of the system. Within this framework, we analyze two distinct models differing in the nature of social feedback. In the presence of positive feedback, the system exhibits bistability, with widespread compliance and widespread violation as stable equilibria, and the transition between these states occurs discontinuously once a critical threshold is crossed, resembling a first-order phase transition. By contrast, when negative feedback is present, the population undergoes a continuous phase transition between compliant and noncompliant collective states, driven by an increasing collective cost of rule-breaking. Numerical simulations and analytical results illustrate how changes in enforcement, social tolerance or perceived benefits can shift the system across critical thresholds separating distinct collective regimes. The results provide a theoretical explanation for the fragility of social order under weak institutions and highlight possible pathways to promote compliance.
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Optics · Cross-listed from cond-mat.stat-mech

Bridge Scaling in Conditioned Henyey-Greenstein Random Walks

Claude Zeller

We study fixed-length bridge paths – half-space excursions that start and end at a planar boundary – for three-dimensional random walks with Henyey-Greenstein scattering angles and exponentially distributed step lengths, using Monte Carlo simulation over asymmetry parameter g from 0 to 0.95 and path lengths from 4 to 200 steps. The key structural feature is that the walk evolves on a two-dimensional Markovian state space (depth, direction cosine) rather than the scalar depth coordinate alone. Four anomalies with respect to classical Brownian-excursion theory are reported. The mean amplitude scales super-diffusively, as path length to a power of 0.57–0.58 for isotropic scattering, nine standard deviations above the Brownian prediction of 0.5, with no sign of convergence out to 200 steps. The diffusion coefficient scales as the transport mean free path to the power 0.415 rather than the predicted 1.0. The midpoint depth distribution is Rayleigh rather than half-normal, consistent with a two-dimensional Bessel process. The bridge-conditioned mean direction cosine converges to minus two-thirds at the final step, independently of the asymmetry parameter and initial direction – the classical Milne result anchored by the H-function moment identity. All anomalies are attributed to the two-dimensional state-space structure. The two anomalous exponents sum to approximately unity, suggesting a common geometric origin. Whether this constitutes a permanent universality-class shift or an anomalously slow crossover to Brownian-excursion behaviour remains the primary open question.
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Instrumentation and Detectors

Polarized Target Nuclear Magnetic Resonance Measurements with Deep Neural Networks

Devin Seay, Ishara P. Fernando and Dustin Keller

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.
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Plasma Physics

Interpretive Modeling of plasma evolution during fueling experiments at CMFX

S. Mackie, J. G. van de Lindt, J. L. Ball et al. (+7 more)

The Centrifugal Mirror Fusion Experiment (CMFX) is an axisymmetric magnetic mirror with a central cathode which generates an azimuthal, radially sheared, supersonic \( E \times B \) flow. The induced rotation stabilizes, confines, and heats the plasma. The diagnostic set on CMFX is sparse, giving limited insight to the state of the plasma. In this work, we developed a time-dependent interpretive analysis framework that uses applied voltage, input power, and measured neutron yield rate to infer evolving plasma conditions throughout a discharge. The 0D MCTrans++ code serves as the core physics model, incorporating centrifugal effects, viscous heating, and angular momentum confinement to infer plasma parameters from operating conditions and experimental observables. An iterative Newton's method was implemented to solve for the plasma state evolution consistent with experimental measurements averaged over successive time intervals. The interpretive analysis was applied to experiments comparing different fueling strategies, revealing a path to improved performance via several short puffs of fuel spread across the discharge. This insight led to operations at voltages up 70 kV. Deuterium neutron yields up to \(1.5 \times 10^7\) n/s were measured, and ion temperature was inferred to reach 950 eV. Until CMFX gains a more complete diagnostic set, this interpretive analysis framework provides useful insight into the evolution of centrifugal mirror plasmas.
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All authors S. Mackie, J. G. van de Lindt, J. L. Ball, A. Perevalov, W. Morrissey, Z. Short, B. L. Beaudoin, C. A. Romero-Talamas, J. Rice, R. A. Tinguely

Computational Physics · Cross-listed from astro-ph.IM

The Cosmological Simulation Code OpenGadget3 - Implementation of Self-Interacting Dark Matter

Moritz S. Fischer, Marc Wiertel, Cenanda Arido et al. (+7 more)

Dark matter (DM) could be subject to non-gravitational self-interactions which is relevant to resolve potential problems of cold DM on small scales. Their impact on astrophysical objects such as galaxies and galaxy clusters allows for constraining the strength of this scattering and eventually further properties of the cross-section. To model self-interacting dark matter (SIDM), N-body simulations are a crucial tool widely employed by the SIDM community. In this paper, we describe the SIDM implementation in the cosmological hydrodynamical N-body code OpenGadget3 and release it to the public. It is capable of simulating elastic scattering for various differential cross-sections, including strongly anisotropic cross-sections. Beyond single-species models, the code also allows simulating a two-species model with cross-species interactions. In addition to describing the numerical schemes for modelling various flavours of SIDM, we discuss the technical challenges of implementing them. Moreover, we demonstrate through several test problems that OpenGadget3 can accurately simulate DM self-interactions. Furthermore, we assess the performance of the code and provide scaling tests. Lastly, we highlight remaining challenges in the context of SIDM and describe directions for improving the current state of the art.
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All authors Moritz S. Fischer, Marc Wiertel, Cenanda Arido, Yashraj Patil, Antonio Ragagnin, Klaus Dolag, Marcus Brüggen, Mathias Garny, Andrew Robertson, Kai Schmidt-Hoberg