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Physics Physics

physics Watch Physics

Thursday 12 March

History and Philosophy of Physics · Cross-listed from cs.DC

Subtime: Reversible Information Exchange and the Emergence of Classical Time

Paul L. Borrill

We formalize the concept of subtime – a reversible mode of information interchange within entangled systems – and show how classical time emerges as an asymptotic limit through decoherence. Building on the photon clock model, in which a single photon confined between two ideal mirrors creates an alternating causality regime, we develop a process-theoretic formalization using the Oreshkov–Costa–Brukner framework extended with an explicit time-reversal duality condition. We introduce Perfect Information Feedback (PIF) as the information-theoretic realization of this reversibility, demonstrating that mutual information is conserved in any closed causal loop and that entropy quantifies the degree of unreflected causality. We define the Reversible Causal Principle (RCP): every causal relation possesses a conjugate dual, and entropy, energy dissipation, and the classical arrow of time appear only when these alternating components decohere or fail to reflect perfectly. The framework unifies Wheeler–Feynman absorber theory, Bennett's reversible computation, Shannon's communication theory, and the process matrix formalism under a single symmetry principle, and identifies experimentally accessible signatures in reversible digital links and quantum switch experiments. The arrow of time, in this picture, records the universe's imperfect causal echo.
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Plasma Physics

Tearing Stability Prediction Combining Toroidal Calculations With a Two-Fluid Slab Layer

D.A. Burgess, N.C. Logan, J.-K. Park et al. (+1 more)

A new classical TM stability simulation workflow has been developed that solves the resistive inner-layer equations in a plasma slab to yield a linear, quasi-toroidal TM growth rate $\gamma$ and mode rotation frequency $\omega$. This workflow combines two-fluid and drift MHD effects in a slab approximation of the resistive inner layer (SLAYER) with an effective tearing stability index as $\Delta(\gamma,\omega) = \Delta' - \Delta_\mathrm{crit}$. SLAYER is used to calculate the inner-layer $\Delta(\gamma,\omega)$, the STRIDE code is used to calculate a toroidal $\Delta'$ that includes shaping effects, and the toroidal $\Delta_\mathrm{crit}$ incorporates effects of thermal conduction on Glasser stabilization. This workflow is rapid and numerically robust across reactor-relevant plasma conditions, and yields growth rates that closely align with analytic predictions in well-documented linear growth rate regimes. Using synthetic equilibria, TM stability was calculated across scans of plasma $\beta$, inverse aspect-ratio, and toroidal current profile gradient. These scans effectively benchmarked this STRIDE+SLAYER workflow against existing models and showed reliable stability predictions in shaped H-mode-like plasmas. This capability to quickly and robustly predict classical tearing stability in tokamaks will facilitate the mapping of TM stable operational regimes and design of safe discharge trajectories in future devices.
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All authors D.A. Burgess, N.C. Logan, J.-K. Park, C. Paz-Soldan

Plasma Physics

Design and mechanical analysis of the PRAGYA tokamak vacuum vessel

Ravi Gupta, Rahul Babu Koneru, Saptarshi Rajan Sarkar et al. (+4 more)

PRAGYA is India's first privately developed low aspect ratio tokamak designed by Pranos Fusion Energy. The device is designed for a plasma major radius (R0) of about 0.4 m, a plasma minor radius (a) greater than 0.18 m, a plasma current (Ip) of up to 25 kA, and a toroidal magnetic field (B_T) of 0.1 T. The PRAGYA vacuum vessel incorporates several distinctive features, including a toroidal electrical break to minimize induced eddy currents and a double O-ring arrangement to reduce vacuum leakage. This paper presents the final design of the PRAGYA vacuum vessel and a comprehensive three-dimensional (3D) finite element model (FEM) assessment of its structural performance. The analysis evaluates the effects of self-weight, atmospheric pressure loading, and thermal stress arising from in-situ baking. The results confirm that the design satisfies the required safety margins under these combined loading conditions, providing a robust foundation for subsequent plasma operations in this compact tokamak.
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All authors Ravi Gupta, Rahul Babu Koneru, Saptarshi Rajan Sarkar, Santosh Ansumali, Animesh Kuley, Roshan George, Shaurya Kaushal

Chemical Physics · Cross-listed from cond-mat.mtrl-sci

Why ice is so slippery

Sigbjørn Løland Bore, B.N.J. Persson and Henrik Andersen Sveinsson

We simulate nanoscale ice–glass friction from first principles and upscale it by modelling frictional heating. Nanoscale simulations alone overestimate friction and miss its velocity dependence. Frictional heating warms the contact toward the melting point, thickening the premelting film tenfold and cutting its viscosity a hundredfold; friction drops with velocity, matching experiment. Premelting forms the film without sliding or heating, but its slipperiness hinges on frictional heating, as Bowden and Hughes proposed in 1939, without melting. Snow, other materials and coatings remain open.
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Optics

Modeling Light Propagation and Amplification Efficiency in Highly Multimode, Yb-doped Fiber Amplifiers

D. L. Smith, K. Wisal, B. Huang et al. (+5 more)

Multimode fibers have been proposed for mitigating nonlinear effects in high-power fiber amplifiers, allowing for significant power scaling. Most previous studies on light propagation in continuous-wave fiber amplifiers focus on single mode or few mode fibers. Here we develop a tractable numerical model to simulate light propagation in narrowband, highly multimode fiber amplifiers, which takes into account gain saturation, pump depletion and mode-dependent gain. We consider a frequency domain, field based model, with modal gain being dependent on both intramodal gain and gain-induced mode coupling. We derive coupled equations for the evolution of signal modal amplitudes, pump power and population inversion, and numerically solve these equations using a finite-difference method. For highly multimode excitations, the optical intensity in the fiber is speckled and various modes grow at different rates, due to differential overlap with the gain medium and spatial hole burning. Our analysis is applied to Yb-doped fibers, with a quasi-quantitative analysis of the specific case of Yb, identifying different regimes in which either spontaneous emission (SE) or amplified spontaneous emission (ASE) limit amplifier efficiency, especially for larger core and multimode fibers. Finally, we incorporate ASE and spectrally resolved optical channels into our model and demonstrate the experimentally verifiable phenomenon of ASE suppression with sufficient input signal power. Our model can be combined with existing models for various nonlinear effects, providing a useful tool for quantitatively studying nonlinearity mitigation and power scaling in multimode fiber amplifiers.
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All authors D. L. Smith, K. Wisal, B. Huang, S. C. Warren-Smith, O. Henderson-Sapir, H. Cao, D. J. Ottaway, A. D. Stone

Optics

Unidirectional exceptional point of reflectionless states in a magnonic mirror array

Zi-Qi Wang, Yuan-Peng Peng, Yi-Pu Wang et al. (+1 more)

Exceptional points (EPs) in non-Hermitian systems are singularities where both eigenvalues and eigenvectors coalesce. In scattering systems, EPs correspond to the merging of scattering states, leading to reflectionless (RL) behavior. A reflectionless exceptional point (RL EP) arises when two RL states further coalesce, yielding an anomalous quartic spectral response. While RL EPs have been explored in bidirectional systems, their unidirectional realization remains elusive. Here, we experimentally demonstrate a unidirectional RL EP by engineering collective states in an anti-Bragg magnonic mirror array. Inversion symmetry is broken using a giant spin ensemble that couples to a waveguide at three spatially separated points, enabling unidirectional reflectionless. At the RL EP, the reflection spectrum flattens and broadens significantly beyond the Lorentzian profile. The observed spectral valleys also expose dark-state behaviors that are typically inaccessible through conventional measurements. Our results provide a route toward controlling collective coherence in open systems and developing broadband unidirectional devices.
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All authors Zi-Qi Wang, Yuan-Peng Peng, Yi-Pu Wang, J. Q. You

Physics and Society · Cross-listed from cs.SI

HawkesRank: Event-Driven Centrality for Real-Time Importance Ranking

Didier Sornette, Yishan Luo and Sandro Claudio Lera

Quantifying influence in networks is important across science, economics, and public health, yet widely used centrality measures remain limited: they rely on static representations, heuristic network constructions, and purely endogenous notions of importance, while offering little semantic connection to observable activity. We introduce HawkesRank, a dynamic framework grounded in multivariate Hawkes point processes that models exogenous drivers (intrinsic contributions) and endogenous amplification (self- and cross-excitation). This yields a principled, empirically calibrated, and adaptive importance measure. Classical indices such as Katz centrality and PageRank emerge as mean-field limits of the framework, clarifying both their validity and their limitations. Unlike static averages, HawkesRank measures importance through instantaneous event intensities, enabling prediction, transparent endo-exo decomposition, and adaptability to shocks. Using both simulations and empirical analysis of emotion dynamics in online communication platforms, we show that HawkesRank closely tracks system activity and consistently outperforms static centrality metrics.
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Optics · Cross-listed from quant-ph

Quantum photonic frequency processor on thin-film lithium niobate

Ran Yang, Wei Zhou, Dong-Jie Guo et al. (+11 more)

The rapid development of photonic quantum information processing necessitates precise and programmable control over optical frequency, a capability critical not only for achieving photon indistinguishability but also for exploiting a virtually unbounded frequency dimension. However, efficient and scalable processing of frequency-encoded photon states remains challenging, primarily due to the limited nonlinear optical interaction in most photonic materials. Here, by harnessing the high-performance thin-film lithium niobate electro-optic (EO) platform, we demonstrate an integrated quantum photonic frequency processor that enables coherent and programmable control of photon frequency with high precision. We establish a scalable architecture for frequency-encoded quantum information processing. Using a fully integrated photonic chip, we realize a universal set of frequency-encoded quantum logic gates, including arbitrary single-qubit rotation gates and the two-qubit controlled-phase gate. Furthermore, we demonstrate its application in high fidelity characterization of frequency-bin entangled states. Our work reveals the unprecedented potential of utilizing the frequency degree of freedom in integrated quantum photonic systems.
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All authors Ran Yang, Wei Zhou, Dong-Jie Guo, Hong-Ming Ke, Linrunde Tao, Ying Wei, Jia-Chen Duan, Yu Cui, Kunpeng Jia, Zhenda Xie, Zhongjin Lin, Xinlun Cai, Yan-Xiao Gong, Shi-Ning Zhu

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

Bootstrap Embedding for Interacting Electrons in Phonon Coherent-state Mean Field

Shariful Islam, Joel Bierman and Yuan Liu

We develop a fermi-bose bootstrap embedding (fb-BE) framework for the ground state of interacting elec- trons coupled to phonon mean field. The method combines bootstrap embedding for correlated electrons with a self-consistent coherent-state mean-field treatment for phonons. This method models the interacting electron-phonon problem as a system of correlated electrons traveling in a self-consistently specified potential landscape, allowing for efficient treatment of large lattice systems. Convergence of the methods for frag- ment size and total system size are demonstrated for one-dimensional Hubbard-Holstein model for up to 350 sites. Finite-size scaling is performed to extrapolate to infinite system size. Benchmarking against density matrix renormalization group for small 8-site system at half- and quarter-filling shows orders-of-magnitude runtime advantage. The comparison further reveals that the method performs best in regimes dominated by localization, such as the Mott insulating phase and the strong-coupling tiny polaron regime, where the local embedding ansatz is still valid. However, due to the mean-field treatment for phonons, we find limitations of our methods in the weakly coupled delocalized region and at the Peierls transition, where quantum phonon fluctuations and long-range kinetic correlations become substantial.
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Optics · Cross-listed from q-bio.NC

Miniaturized microscopes to study neural dynamics in freely-behaving animals

Weijian Zong and Weijian Yang

Head-mounted miniaturized microscopes, commonly known as miniscopes, have undergone rapid development and seen widespread adoption over the past two decades, enabling the imaging of neural activity in freely-behaving animals such as rodents, songbirds, and non-human primates. These miniscopes facilitate numerous studies that are not feasible with head-fixed preparations. Recent advancements have enhanced their capabilities, allowing for faster imaging, larger fields of view, and deeper brain penetration. In this review, we examine the latest progress in one-photon and multi-photon miniscopes. We highlight the unique opportunities these devices present for neuroscience research, discuss the current technical challenges, and explore emerging technologies that promise to advance the development of miniscopes.
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Optics

Towards polarization steganography

Valeria Tena-Piñon, Atefeh Akbarpour, Przemyslaw Litwin et al. (+6 more)

We propose and experimentally demonstrate a polarization–based steganographic scheme using partially polarized vector beams. In our approach, the spatially dependent polarization structure of the optical field serves as the carrier through which the hidden information can be retrieved. By engineering a vector beam whose polarization states populate a prescribed region of the Poincaré sphere, specifically, the equatorial disk, we establish a nontrivial mapping between transverse spatial coordinates and polarization states. Information retrieval is achieved by applying a spatial mask derived from a parametric curve defined within this region of the Poincaré sphere, followed by spatially resolved polarization analysis. We demonstrate the selective reconstruction of various parametric shapes, including polygonal and smooth curves, confirming that the hidden patterns are retrieved through the combined use of spatial filtering and polarization–domain mapping. Our results establish partially polarized vector beams as a flexible and experimentally accessible platform for polarization–based information hiding.
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All authors Valeria Tena-Piñon, Atefeh Akbarpour, Przemyslaw Litwin, Adad Yepiz, Fernando Torres-Leal, Raul I. Hernandez-Aranda, Mateusz Szatkowski, Blas M. Rodriguez-Lara, Benjamin Perez-Garcia

Fluid Dynamics

Rayleigh-Taylor Unstable Flames: Thin and Thick

Elizabeth P. Hicks

A Rayleigh-Taylor (RT) unstable flame is a thin burning interface sandwiched between heavy fuel and light ash layers. RT unstable flames play an important role in complex systems like novel aviation turbine engines, storage facilities for alternative fuels and refrigerants and Type Ia supernovae. Simulations of these systems must use subgrid models of RT flame behavior, but choosing the subgrid model is difficult because RT unstable flames have characteristics of both the classical RT instability and turbulent combustion. In this paper, we investigate whether the flame structure of RT unstable flames can be described using ideas from turbulent combustion theory. We use a large parameter study of Boussinesq model flames and direct measurements of the internal flame structure to show that RT unstable flames can be thickened by their own self-generated turbulence, but that the structure of these thickened flames differs from turbulent flames. Finally, we discuss the implications for modelling RT unstable flames in practical applications.
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Wednesday 11 March

Atmospheric and Oceanic Physics

Constructing efficient score functions for rare event simulation in high-dimensional ocean-climate models

Lucas Esclapez, Valérian Jacques-Dumas, Reyk Börner et al. (+2 more)

Calculating transition probabilities between different states of multistable climate tipping systems is computationally challenging in high-dimensional models. Targeted algorithms, such as the Trajectory-Adaptive Multilevel Splitting (TAMS) method, require an adequate score function to be successful, i.e., to provide an estimate of a transition probability with an acceptable variance when only a relatively small ensemble of model trajectories can be computed. Here, we present a data-driven method to derive a score function based on projecting the model dynamics in a reduced state space. Using a spatially two-dimensional partial differential equation model of the Atlantic Meridional Overturning Circulation, we show that this score function performs better than currently available ones. Using the new score function, transition probabilities can be determined with low variance, even in the case of small noise amplitudes. Besides purely noise-induced transitions, we also consider the scenario of combined stochastic and time-dependent deterministic forcing, presenting a strategy to efficiently simulate AMOC tipping events in global ocean and climate models subject to transient climate change.
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All authors Lucas Esclapez, Valérian Jacques-Dumas, Reyk Börner, Laurent Soucasse, Henk A. Dijkstra

Computational Physics

SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs

Yadi Cao, Sicheng Lai, Jiahe Huang et al. (+12 more)

Evaluating LLM agents for scientific tasks has focused on token costs while ignoring tool-use costs like simulation time and experimental resources. As a result, metrics like pass@k become impractical under realistic budget constraints. To address this gap, we introduce SimulCost, the first benchmark targeting cost-sensitive parameter tuning in physics simulations. SimulCost compares LLM tuning cost-sensitive parameters against traditional scanning approach in both accuracy and computational cost, spanning 2,643 single-round (initial guess) and 2,304 multi-round (adjustment by trial-and-error) tasks across 11 simulators from fluid dynamics, solid mechanics, and plasma physics, whose costs are analytically defined and platform-independent. A twelfth simulator, a production plasma code measurable only by wall clock, is reported separately. Frontier LLMs achieve 45-62% success rates in single-round mode, dropping to 34-50% under high accuracy requirements, rendering their initial guesses unreliable especially for high accuracy tasks. Multi-round mode improves rates to 66-81%, but LLMs are 1.5-2.7x slower than traditional scanning, making them uneconomical choices. We also investigate parameter group correlations for knowledge transfer potential, and the impact of in-context examples and reasoning effort, providing practical implications for deployment and fine-tuning. We open-source SimulCost as a static benchmark and extensible toolkit to facilitate research on improving cost-aware agentic designs for physics simulations, and for expanding new simulation environments. Code and data are available at https://github.com/Rose-STL-Lab/SimulCost-Bench
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All authors Yadi Cao, Sicheng Lai, Jiahe Huang, Yang Zhang, Zach Lawrence, Rohan Bhakta, Izzy F. Thomas, Mingyun Cao, Chung-Hao Tsai, Zihao Zhou, Yidong Zhao, Hao Liu, Alessandro Marinoni, Alexey Arefiev, Rose Yu

Geophysics

Unstable Slip in Fault Gouge Driven by Temperature and Water

Li Wang, Jie Meng, Dongpo Wang et al. (+2 more)

Microscale granular sliding within fault gouge is fundamental to earthquake nucleation, yet the mechanism by which temperature affects friction through interfacial water remains poorly understood. Here, large-scale molecular dynamics simulations were conducted on a hydrophilic quartz-water-quartz interface over 300-500 K to quantify temperature-dependent changes in frictional strength, real contact area, and water-layer structure. Results show that both the friction coefficient and friction force decrease monotonically with increasing temperature, following near-linear relationships of $\mu \propto T^{-1}$ and $F_t \propto A$, indicating that frictional weakening is primarily governed by temperature-driven contact restructuring. Structural analyses further show that heating progressively disrupts the hydrogen-bond network in the first adsorption layer, reduces adsorption-layer density, and weakens radial distribution peaks, demonstrating a transition of interfacial water from an ordered, strongly adsorbed state to a more diffuse, weakly bound configuration with delayering and quasi-phase-transition behavior. This interfacial reconstruction weakens intergranular bridging and structural cohesion, promoting a shift from structural locking to water-mediated lubrication. These results suggest that frictional stability under coupled temperature-water conditions is strongly controlled by the thermal evolution of interfacial water structure.
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All authors Li Wang, Jie Meng, Dongpo Wang, Gongji Zhang, Helge Hellevang

Computational Physics · Cross-listed from cond-mat.mtrl-sci

UniMatSim: A High-Throughput Materials Simulation Automation Framework Based on Universal Machine Learning Potentials

Yanjin Xiang, Yihan Nie, Yunzhi Gao et al. (+2 more)

Universal machine learning interatomic potentials (UMLIPs) offer accuracy close to first-principles calculations at a fraction of the cost, showing significant potential for large-scale material simulations. However, the fragmented UMLIPs ecosystem lacks unified interface standards and integration frameworks, hindering their automated deployment in high-throughput workflows. To address this, we present UniMatSim, a modular Python framework. It systematically integrates various UMLIPs (e.g., CHGNet, M3GNet, MACE) and automates workflows from structural optimization to stability verification. The framework enables seamless model switching via abstracted interfaces, incorporates task orchestration, and provides standardized modules for key properties (elasticity, phonons, molecular dynamics), including automated handling for low-dimensional materials. As a test case, using the 2D Lieb lattice system, we constructed a multi-stage high-throughput screening workflow covering structural optimization, elastic stability, and phonon spectrum calculations. Starting from 1,176 candidate compositions, a four-model consensus pipeline yields 393 stable structures. These are refined by magnetic-state screening and DFT band-structure calculations to 59 Lieb-lattice candidates with staggered-magnetic-band characteristics. Results show UniMatSim significantly improves computational efficiency and reproducibility, providing a reliable infrastructure for data-driven materials discovery and design.
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All authors Yanjin Xiang, Yihan Nie, Yunzhi Gao, Haidi Wang, Wei Hu

Optics · Cross-listed from cs.CV

MAD: Microenvironment-Aware Distillation – A Pretraining Strategy for Virtual Spatial Omics from Microscopy

Jiashu Han, Kunzan Liu, Yeojin Kim et al. (+2 more)

Bridging microscopy and omics would allow us to read molecular states from images-at single-cell resolution and tissue scale-without the cost and throughput limits of omics technologies. Self-supervised pretraining offers a scalable approach with minimal labels, yet how to encode single-cell identity within tissue environments-and the extent of biological information such models can capture-remains an open question. Here, we introduce MAD (microenvironment-aware distillation), a pretraining strategy that learns cell-centric embeddings by jointly self-distilling the morphology view and the microenvironment view of the same indexed cell into a unified embedding space. Across diverse tissues and imaging modalities, MAD achieves state-of-the-art prediction performance on downstream tasks including cell subtyping, transcriptomic prediction, and bioinformatic inference. MAD even outperforms foundation models with a similar number of model parameters that have been trained on substantially larger datasets. These results demonstrate that MAD's dual-view joint self-distillation effectively captures the complexity and diversity of cells within tissues. Together, this establishes MAD as a general tool for representation learning in microscopy, enabling virtual spatial omics and biological insights from vast microscopy datasets.
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All authors Jiashu Han, Kunzan Liu, Yeojin Kim, Saurabh Sinha, Sixian You

Optics

Saturable absorption in defect-rich diamond nanophotonics

Christopher Coutts, Nicholas J. Sorensen, Elham Zohari et al. (+3 more)

Diamond is a leading quantum photonics platform due to its ability to host qubits based on crystal defects such as nitrogen-vacancy centres. Fabricating nanophotonic devices from defect-rich diamond, which underpins many quantum sensing technologies, promises enhanced performance and integrability of diamond quantum sensors. Here we demonstrate microdisk cavities fabricated from defect-rich diamond that support optical modes with high quality factor (${Q}\sim7\times10^4$ at $1042\,$nm) and show that they exhibit saturable absorption. Power-dependent spectroscopy measurements spanning 979$\,$nm to 1604$\,$nm are used to observe intensity-dependent cavity loss and extract wavelength-dependent absorption coefficients and saturation intensities. At 1047$\,$nm, we observe saturation and measure a saturation intensity of $2.1\,(8)\,$MW/cm$^2$ and an absorption coefficient of $0.53\,(2)\,$cm$^{-1}$. These results provide insight into defect-mediated optical loss in diamond nanophotonics and suggest strategies to harness defect-induced nonlinearities in future diamond photonic devices.
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All authors Christopher Coutts, Nicholas J. Sorensen, Elham Zohari, Sean McNaney, Sigurd Flågan, Paul E. Barclay

Fluid Dynamics

Laminar-to-Turbulent Transition of Yield-Stress Fluids in Pipe and Channel Flows

Shivam Prajapati, Prasoon Suchandra, Vivek Kumar et al. (+3 more)

We present direct numerical simulations (DNS) of laminar to turbulent transition in Herschel-Bulkley (HB) yield-stress fluids flowing through pipes and rectangular channels. The simulations employ a Herschel-Bulkley formulation that captures the yield-stress-driven plug, its breakdown, and the emergence of near-wall turbulent structures, enabling direct resolution of the transition mechanisms. The DNS cover a broad range of generalized Reynolds numbers, Re_G = 378 to 5300, allowing us to resolve plug formation, transition onset, and fully turbulent regimes. In pipe flow, the simulations reproduce the characteristic transition sequence, which includes a strong plug and negligible turbulence at low Re_G, a sharp rise in turbulence intensity and u'rms within a narrow transitional window (Re_G ~ 2000 to 3000), and wall-dominated turbulence with a weakened core at higher Re_G. Transition occurs only when local Reynolds stresses exceed the yield stress. The resulting regime boundaries (Re_G < 1735 laminar, 1735 < Re_G < 2920 transitional, and Re_G > 2920 turbulent) align with trends reported for Carbopol fluids. This work provides the first DNS resolving the complete laminar to turbulent transition in HB fluids for both pipe and channel configurations, offering unified insight into plug breakdown, turbulence localization, and the role of yield stress in transition mechanisms. Experimental validation using a 3.6 m acrylic channel with particle image velocimetry (PIV) is planned to further assess the DNS predictions and quantify geometry-dependent transition thresholds.
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All authors Shivam Prajapati, Prasoon Suchandra, Vivek Kumar, Ardalan Javadi, Suhas Jain, Cyrus Aidun

Atmospheric and Oceanic Physics

Leveraging higher-order time integration methods for improved computational efficiency in a rainshaft model

Justin Dong, Sean P. Santos, Steven B. Roberts et al. (+2 more)

Cloud and precipitation microphysics packages in atmospheric general circulation models typically use first-order time integration methods with a large time step, requiring ad hoc limiters and substepping of the sedimentation scheme to prevent numerical instability. We investigate alternative methods for rain microphysical processes in the current Energy Exascale Earth System Model (E3SMv3), provided by the Predicted Particle Properties (P3) scheme. Using an offline rainshaft model containing P3's rain microphysics as a proxy for E3SMv3, we find that rain microphysics is underresolved in time at E3SMv3's default 300s time step. Accurately resolving the rainshaft model processes in time requires an over 100x reduction in time step, increasing wall clock time by 40x. However, higher-order time integrators based on Runge-Kutta methods offer improved solution accuracy for a given computational cost. Adaptive time stepping is key to obtaining computationally efficient microphysics results, eliminating the need for specialized substepping procedures in the sedimentation process. An adaptive second-order Runge-Kutta method approximates a high-temporal-resolution reference solution at only 2.6x the cost of the default P3 scheme; this method achieves high accuracy greater than 15x more efficiently than simply reducing the time step of P3 in the rainshaft model. We also analyze the timescales of the rain processes to obtain insight about the maximum time step each process is able to take while maintaining stability and accuracy, and about how individual processes should be grouped together for most efficient results.
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All authors Justin Dong, Sean P. Santos, Steven B. Roberts, Christopher J. Vogl, Carol S. Woodward

Fluid Dynamics

Integral analysis based diagnostics of turbulence model errors in skin friction

Shyam S. Nair, Vishal A. Wadhai, Robert F. Kunz et al. (+1 more)

Error diagnostics for turbulence models have traditionally focused on engineering quantities of interest, such as the skin-friction coefficient, $C_f$, most often by comparing the predicted $C_f$ against reference data. In wall-bounded turbulent boundary layers, however, $C_f$ results from several physical mechanisms – viscous effects, turbulence, pressure gradients, and mean-flow development – whose relative importance depends on the flow conditions. Modeling errors in these mechanisms vary across turbulence closures, and identifying them offers valuable physical insight for model evaluation and improvement. We propose a diagnostics framework that systematically isolates and quantifies such errors using the angular momentum integral (AMI) formulation. The method is applied to five transport-type Reynolds-averaged Navier-Stokes (RANS) models in two test cases: a canonical zero-pressure-gradient flat-plate boundary layer and flow over a three-dimensional hill. For the flat-plate case, comparison with direct numerical simulation (DNS) data shows that all models reproduce $C_f$ reasonably well, but often through strong error cancellation, particularly between the turbulent torque and mean-flux contributions; individual terms can deviate by more than 20% of $C_f$. For the hill case, where wall-resolved large-eddy simulation (WRLES) is used as the reference, errors are significantly larger. The dominant erroneous contribution differs by model and may exceed several times the local $C_f$, depending on streamwise position. In separated-flow regions, the error cancellation that was observed in the flat-plate case largely disappears for the hill case, and the leading source of error shifts between mechanisms. These results highlight the value of mechanism-resolved diagnostics and provide guidance for targeted turbulence-model improvements.
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All authors Shyam S. Nair, Vishal A. Wadhai, Robert F. Kunz, Xiang I. A. Yang

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

Strong Prevalence of Hammerhead Velocity Distributions Close to the Heliospheric Current Sheet

Srijan Bharati Das, Jaye L. Verniero, Samuel T. Badman et al. (+13 more)

The solar wind undergoes non-adiabatic heating as it travels away from the Sun. The velocity phase space distribution of non-equilibrium ions in the solar wind indicate a source of free energy that could contribute significantly to this heating. Parker Solar Probe (PSP) has observed velocity distributions containing highly anisotropic, perpendicularly diffused proton beams with a distinctly constricted gap between the core and beam populations. These distributions resemble a “hammerhead" shape and were first reported in the fourth PSP encounter. Numerical simulations have reproduced the qualitative nature of hammerheads under certain initial conditions, but have not convincingly captured the prevalence or extreme attributes of the observed beam. This necessitates a broad study of the occurrence conditions and the associated plasma processes to better guide simulations. We statistically investigate the occurrence of these structures from 20 recent PSP encounters, and find that hammerheads dominantly occur around the Heliospheric Current Sheet (HCS). As the inclination of the HCS at PSP crossing points increases over the rising phase of the solar cycle, the occurrence of hammerheads is increasingly concentrated in narrow time periods around the HCS crossings. For comparison with previous work, we present statistical trends in the anisotropy of the proton beam and its connection to the density of proton beams as well as the drift speed of the beam to the core. Our study establishes a consistent occurrence pattern of hammerhead distributions around the HCS indicating hammerheads are diagnostics of energization processes associated with the HCS and its escaping wind.
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All authors Srijan Bharati Das, Jaye L. Verniero, Samuel T. Badman, Robert Alexander, Michael Terres, Federico Fraschetti, Kristoff W. Paulson, Fernando Carcaboso, Tatiana Niembro, Roberto Livi, Davin Larson, Ali Rahmati, Yeimy J. Rivera, Niranjana, Kristopher G. Klein, Michael L. Stevens

Medical Physics

MRI2Qmap: multi-parametric quantitative mapping with MRI-driven denoising priors

Mohammad Golbabaee, Matteo Cencini, Carolin Pirkl et al. (+3 more)

Magnetic Resonance Fingerprinting (MRF) and other highly accelerated transient-state parameter mapping techniques enable simultaneous quantification of multiple tissue properties, but often suffer from aliasing artifacts due to compressed sampling. Incorporating spatial image priors can mitigate these artifacts, and deep learning has shown strong potential when large training datasets are available. However, extending this paradigm to MRF-type sequences remains challenging due to the scarcity of quantitative imaging data for training. Can this limitation be overcome by leveraging sources of training data from clinically-routine weighted MRI images? To this end, we introduce MRI2Qmap, a plug-and-play quantitative reconstruction framework that integrates the physical acquisition model with priors learned from deep denoising autoencoders pretrained on large multimodal weighted-MRI datasets. MRI2Qmap demonstrates that spatial-domain structural priors learned from independently acquired datasets of routine weighted-MRI images can be effectively used for quantitative MRI reconstruction. The proposed method is validated on highly accelerated 3D whole-brain MRF data from both in-vivo and simulated acquisitions, achieving competitive or superior performance relative to existing baselines without requiring ground-truth quantitative imaging data for training. By decoupling quantitative reconstruction from the need for ground-truth MRF training data, this framework points toward a scalable paradigm for quantitative MRI that can capitalize on the large and growing repositories of routine clinical MRI.
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All authors Mohammad Golbabaee, Matteo Cencini, Carolin Pirkl, Marion Menzel, Michela Tosetti, Bjoern Menze

Applied Physics · Cross-listed from quant-ph

QuaNTUM: A Modular Quantum Communication Testbed for Scalable Fiber and Satellite Integration

Julien Chénedé, Tjorben Matthes, Josefine Krause et al. (+2 more)

Secure communication is essential for modern society, from financial transactions to critical infrastructure. As classical encryption faces threats from advancing computational power, quantum communication provides a fundamentally secure alternative based on physical laws. We present QuaNTUM (Quantum Network at the Technical University of Munich), a modular and extensible quantum communication testbed enabling scalable experiments across fiber-based campus networks and satellite-ground links. The terrestrial network connects research institutions in Garching near Munich via single-mode fibers in a star topology with polarization-maintaining components, multiplexers, and time-synchronized analysis modules. Active polarization control and real-time feedback support stable qubit transmission for high-fidelity quantum key distribution and entanglement distribution. A key feature is the integration of deterministic solid-state single-photon sources, including defects in hexagonal boron nitride and excited erbium atoms, with initial deployments on small satellites to bridge terrestrial and free-space channels. As an open-access platform, QuaNTUM enables protocol development, device benchmarking, and hybrid network research, providing a foundation for scalable quantum communication and future global quantum networks.
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All authors Julien Chénedé, Tjorben Matthes, Josefine Krause, Asli Cakan, Tobias Vogl

Optics · Cross-listed from quant-ph

Focusing Surface-Acoustic-Wave Resonators on Thin-Film Lithium Niobate with Transverse-Mode Suppression

Ryo Sasaki, Ryusuke Hisatomi, Rekishu Yamazaki et al. (+3 more)

Surface-acoustic-wave (SAW) resonators are a promising platform for constructing hybrid quantum systems, where confined acoustic waves enable strong interaction with various physical systems. Focusing SAW resonators, reducing mode volume while suppressing diffraction losses, have recently been investigated for application in such hybrid systems. However, the resonator leads to additional transverse-mode resonances, which cause undesired responses. In this work, we develop focusing SAW resonators on a thin-film lithium niobate on sapphire. A film thinner than the SAW wavelength allows a highly confined acoustic-wave mode to be localized on the substrate surface. By using contoured electrodes following a two-dimensional Gaussian beam shape, we make the SAW mode focused to nearly a diffraction-limited and confirm it via optical imaging. Furthermore, by engineering the spatial mode overlap of the interdigital transducer electrodes, we suppress the excitation of higher-order transverse modes.
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All authors Ryo Sasaki, Ryusuke Hisatomi, Rekishu Yamazaki, Yuya Yamaguchi, Yasunobu Nakamura, Atsushi Noguchi

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

Post-processing Probabilistic Forecasts of the Solar Wind by Data Mining Similar Scenarios

Daniel E. da Silva, Yash Parlikar, Shaela I. Jones et al. (+1 more)

The solar wind speed at Earth is one of the most important parameters regarding the effects of space weather on society. Thus far, most approaches for predicting the solar wind speed produce a single-value time series without uncertainty, or utilize ensemble methods which require custom calibration development. In this study, a method is developed that produces calibrated probabilistic forecasts of the solar wind speed using skew normal distributions and a novel extension of analog ensembles. In our extension, the single-value predictions from a baseline model of the next $\Delta t$ days are used along with $\Delta window$ hours of recent observations and single-value predictions to create a forecasting scenario vector that is compared against a historical database for outcomes. The baseline model used is the combined Air Force Data Assimilative Photospheric Flux Transport-Wang Sheeley Arge (ADAPT-WSA) model and the WSA point parcel simulation, but the method is directly applicable to other deterministic models including components such as Enlil or the Heliospheric Upwind Extrapolation with time dependence model (HUXt). The approach works notably well on the benchmark of whether observations fall within the $p^{th}$ percentile $p\%$ of the time (for $p$ between 0 and 100). Falling back on the mean or median of the predicted distribution as a non-probabilistic prediction yields a direct improvement in root-mean-square error (RMSE) over the original WSA point parcel simulation, and is shown to beat $\approx$ 1 solar rotation recurrence for 1-5 day ahead forecasts.
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All authors Daniel E. da Silva, Yash Parlikar, Shaela I. Jones, Charles N. Arge

Fluid Dynamics

Irreversible Port-Hamiltonian Formulations for 1-Dimensional fluid systems

Ahlam Ouardi, Arijit Sarkar, Hector Ramirez et al. (+1 more)

The Irreversible Port-Hamiltonian Systems (IPHS) framework is extended to the modelling of non-isentropic fluids with viscous dissipation in the Eulerian description. Building on earlier IPHS formulations for diffusion-driven and non-convective distributed systems, it is shown that convective transport can be consistently encompassed by the framework by modifying the underlying differential operators. After revisiting the constitutive relations of non-isentropic fluids in both Eulerian and Lagrangian coordinates, it is demonstrate how these systems fit within an extended IPHS formulation. Furthermore, an extended parametrisation of the boundary port variables which ensures that the first and second laws of Thermodynamics are fulfilled allows to define a general class of boundary controlled IPHS.
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All authors Ahlam Ouardi, Arijit Sarkar, Hector Ramirez, Yann Le Gorrec

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

Exceptional Optical Phonon Coherence in Enriched Cubic Boron Arsenide via Suppression of Three-Phonon Scattering

Tong Lin, Fengjiao Pan, Gaihua Ye et al. (+8 more)

Cubic boron arsenide (BAs) is a promising semiconductor for next-generation electronics due to its outstanding ambipolar mobility and thermal conductivity, the latter of which is attributed to the suppression of three-phonon scattering. However, precisely accounting for different high-order anharmonic scattering processes is challenging from both theory and experiment, so that questions remain open regarding the ultimate limit of phonon lifetime and thermal conductivity in BAs. Here we show that this gap nearly eliminates three-phonon scattering for zone-center optical phonons in a wide temperature range, leading to a record-high, isotope purity-limited phonon coherence with a quality factor above $3.7\times 10^3$ for >98% enriched $^{11}$BAs below 100 K. We discriminate three decoherence mechanisms by their temperature-dependent contribution to the damping rate using high-resolution Raman and Fourier transform infrared spectroscopy. For the as-synthesized crystals, we find that defect scattering has negligible contributions to the linewidth of optical phonons in comparison to isotope scattering. These results provide critical insights into the intrinsic and extrinsic scattering mechanisms of optical phonons in BAs, motivating further studies to quantify anharmonic effects and realize superior phonon transport.
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All authors Tong Lin, Fengjiao Pan, Gaihua Ye, Sanjna Sukumaran, Cynthia Nnokwe, Ange Benise Niyikiza, William A. Smith, Stephen B. Bayne, Rui He, Zhifeng Ren, Hanyu Zhu

Fluid Dynamics · Cross-listed from math.NA

A Machine Learning-Enhanced Hopf-Cole Formulation for Nonlinear Gas Flow in Porous Media

V. S. Maduri and K. B. Nakshatrala

Accurate modeling of gas flow through porous media is critical for many technological applications, including reservoir performance prediction, carbon capture and sequestration, and fuel cells and batteries. However, such modeling remains challenging due to strong nonlinear behavior and uncertainty in model parameters. In particular, gas slippage effects described by the Klinkenberg model introduce pressure-dependent permeability, which complicates numerical simulation and obscures deviations from classical Darcy flow behavior. To address these challenges, we present an integrated modeling framework for gas transport in porous media that combines a Klinkenberg-enhanced constitutive relation, Hopf-Cole-transformed mixed-form linear governing equations, a shared-trunk neural network architecture, and a Deep Least-Squares (DeepLS) solver. The Hopf-Cole transformation reformulates the original nonlinear flow equations into an equivalent linear system closely related to the Darcy model, while the mixed formulation, together with a shared-trunk neural architecture, enables simultaneous and accurate prediction of both pressure and velocity fields. A rigorous convergence analysis is performed both theoretically and numerically, establishing the stability and convergence properties of the proposed solver. Importantly, the proposed framework also naturally facilitates inverse modeling of pressure-dependent permeability and slippage parameters from limited or indirect observations, enabling efficient estimation of flow properties that are difficult to measure experimentally. Numerical results demonstrate accurate recovery of flow dynamics and parameters across a wide range of pressure regimes, highlighting the framework's robustness, accuracy, and computational efficiency for gas transport modeling and inversion in tight formations.
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Computational Physics

Reliable Viscosity Calculation from High-Pressure Equilibrium Molecular Dynamics: Case Study of 2,2,4-Trimethylhexane

Gözdenur Toraman, Dieter Fauconnier and Toon Verstraelen

Viscosity is a fundamental property of liquid lubricants, yet it is challenging to determine accurately, especially at high pressures. Although equilibrium molecular dynamics (EMD) simulations are a promising alternative to resource-intensive experiments, practical challenges remain in assessing the sufficiency of simulation time and in controlling uncertainties in the Green-Kubo formalism due to the finite amount of trajectory data. In this work, we extend the STable AutoCorrelation Integral Estimator (STACIE), a recently developed algorithm for estimating transport properties. First, we introduce the Lorentz model to estimate the viscosity and the exponential correlation time from the low-frequency power spectrum of deviatoric pressure fluctuations. Second, we show how to supplement the three conventional off-diagonal elements of the pressure tensor ($P_{xy}$, $P_{yz}$ and $P_{zx}$) with two additional uncorrelated deviatoric pressure components for shear viscosity calculations. Using these improvements, we apply STACIE to calculate the shear viscosity of 2,2,4-trimethylhexane from EMD simulations. We demonstrate STACIE's capability to reliably calculate viscosity under high-pressure conditions, offering a robust and automated solution with validated uncertainty quantification. Our results, when compared to the outcomes of the 10th International Fluid Properties Simulation Challenge, underscore the need for long EMD simulations. Large deviations from experimental viscosities in previous works were primarily due to insufficient simulation times and ad hoc post-processing choices, rather than the limitations of the force fields used. Unlike previous studies, our viscosity estimates agree well with experimental results (relative error < 6%) up to the highest pressure of 1 GPa, highlighting the improved reliability and accuracy of STACIE's systematic approach to viscosity predictions.
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