Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Principled Operator Learning in Ocean Dynamics: The Role of Temporal Structure
Vahidreza Jahanmard, Ali Ramezani-Kebrya and Robinson Hordoir
Neural operators are becoming the default tools to learn solutions to governing partial differential equations (PDEs) in weather and ocean
forecasting applications. Despite early promising achievements, significant challenges remain, including long-term prediction stability and adherence to physical laws, particularly for high-frequency processes. In this paper, we take a step toward addressing these challenges in high-resolution ocean prediction by incorporating temporal
Fourier modes, demonstrating how this modification enhances physical fidelity. This study compares the standard
Fourier Neural Operator (FNO) with its variant, FNOtD, which has been modified to internalize the dispersion relation while learning the solution operator for ocean PDEs. The results demonstrate that entangling space and time in the training of integral kernels enables the model to capture multiscale wave propagation and effectively learn ocean dynamics. FNOtD substantially improves long-term prediction stability and consistency with underlying physical dynamics in challenging high-frequency settings compared to the standard FNO. It also provides competitive predictive skill relative to a state-of-the-art numerical ocean model, while requiring significantly lower computational cost.
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Computational Physics · Cross-listed from cs.LG
Scaling Laws and Symmetry, Evidence from Neural Force Fields
Khang Ngo and Siamak Ravanbakhsh
We present an empirical study in the
geometric task of learning interatomic potentials, which shows equivariance matters even more at larger scales; we show a clear power-law scaling behaviour with respect to data, parameters and compute with “architecture-dependent exponents”. In particular, we observe that equivariant architectures, which leverage task
symmetry, scale better than non-equivariant models. Moreover, among equivariant architectures, higher-order representations translate to better scaling exponents. Our analysis also suggests that for compute-optimal training, the data and model sizes should scale in tandem regardless of the architecture. At a high level, these results suggest that, contrary to common belief, we should not leave it to the model to discover fundamental inductive biases such as
symmetry, especially as we scale, because they change the inherent difficulty of the task and its scaling laws.
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Medical Physics
Stochastic numerical head phantoms to enable virtual imaging studies of transcranial photoacoustic computed tomography
Hsuan-Kai Huang, Joseph Kuo, Seonyeong Park et al. (+3 more)
Transcranial photoacoustic computed
tomography (PACT) is an emerging neuroimaging modality, but skull-induced aberrations can result in severe image artifacts if not compensated for during image reconstruction. The development of advanced image reconstruction methods for transcranial PACT is hindered by the lack of well-characterized, clinically relevant evaluation frameworks. Virtual imaging studies offer a solution, but require realistic numerical phantoms. To address this need, this study introduces a framework for generating ensembles of realistic 3D numerical head phantoms for virtual imaging studies. The framework uses adjunct CT data to create anatomical phantoms, which are then enhanced with stochastically synthesized vasculature and assigned realistic optical and acoustic-elastic properties. The utility of the framework is demonstrated through a case study on the impact of skull modeling errors on transcranial PACT image quality. By allowing researchers to assess and refine reconstruction methods meaningfully, the presented framework is expected to accelerate the development of transcranial PACT.
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All authors Hsuan-Kai Huang, Joseph Kuo, Seonyeong Park, Umberto Villa, Lihong V. Wang, Mark A. Anastasio
Computational Physics · Cross-listed from astro-ph.IM
Time-Dilation Methods for Extreme Multiscale Timestepping Problems
Philip F. Hopkins and Elias R. Most
Many astrophysical simulations involve extreme dynamic range of timescales around 'special points' in the domain (e.g. black holes,
stars,
planets, disks,
galaxies, shocks, mixing interfaces), where processes on small scales couple strongly to those on large scales. Adaptive resolution, multi-physics, and hybrid numerical methods have enabled tremendous progress on the spatial, physics, and numerical challenges involved. But often the limiter for following the long timescales of global
evolution is the extremely short numerical timestep required in some subdomains (which leads to their dominating simulation costs). Recently several approaches have been developed for tackling this in problems where the short timescale solution is sampled and then projected as an effective subgrid model over longer timescales (e.g. 'zooming in and out'). We generalize these to a family of models where time
evolution is modulated by a variable but continuous in space-and-time dilation/stretch factor $a({\bf x},\,t)$. This extends previous well-studied approaches (including reduced-speed-of-light and binary orbital dynamics methods), and ensures that the system comes to correct local steady-state solutions, and derive criteria that the dilation factor/timesteps/resolution must obey to ensure good behavior. We present a variety of generalizations to different physics or coupling scales. Compared to previous approaches, this method makes it possible to avoid imprinting arbitrary scales where there is no clear scale-separation, and couples well to Lagrangian or Eulerian methods. It is flexible and easily-implemented and we demonstrate its validity (and limitations) in test problems. We discuss the relationship between these methods and physical time dilation in GRMHD. We demonstrate how this can be used to obtain effective speedup factors exceeding $\gtrsim 10^{4}$ in multiphysics simulations.
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Physics and Society
Large scale statistically validated comorbidity networks
Paride Crisafulli, Tobias Galla, Antti Karlsson et al. (+3 more)
We obtain comorbidity networks starting from medical information stored in electronic health records collected by the Wellbeing Services County of Southwest Finland (Varha). Based on the data, we associate each patient to one or more diseases and construct complex comorbidity networks associated with large patient cohorts characterized by an age interval and sex. The information about diseases in electronic health records is coded using the highest granularity present in the international classification of diseases (ICD codes) provided by the World Health Organization. We statistically validate links in each cohort comorbidity network and furthermore partition the networks into communities of diseases. These are characterized by the over-expression of a few disease categories, and communities from different age or sex cohorts show various similarities in terms of these disease classes. Moreover, all the detected communities for all the cohorts can be organized into a hierarchical tree. This allows us to observe a number of clusters of communities, originating from diverse age and sex cohorts, that group together communities characterized by the same disease classes. We also perform a dismantling procedure of statistically validated comorbidity networks to highlight those categories of diseases that are most responsible for the compactedness of the comorbidity networks for a given cohort of patients.
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All authors Paride Crisafulli, Tobias Galla, Antti Karlsson, Salvatore Miccichè, Jyrki Piilo, Rosario N. Mantegna
Atmospheric and Oceanic Physics · Cross-listed from eess.IV
Chlorophyll-a Mapping and Prediction in the Mar Menor Lagoon Using C2RCC-Processed Sentinel 2 Imagery
Antonio Martínez-Ibarra, Aurora González-Vidal, Adrián Cánovas-Rodríguez et al. (+1 more)
The Mar Menor, Europe's largest hypersaline coastal lagoon, located in southeastern Spain, has undergone severe eutrophication crises, with devastating impacts on biodiversity and water quality. Monitoring chlorophyll-a, a proxy for phytoplankton biomass, is essential to anticipate harmful algal blooms and guide mitigation strategies. Traditional in situ measurements, while precise, are spatially and temporally limited. Satellite-based approaches provide a more comprehensive view, enabling scalable and long-term monitoring. This study aims to overcome limitations of chlorophyll monitoring, often restricted to surface estimates or limited temporal coverage, by developing a reliable methodology to predict and map chlorophyll-a concentrations across the water column of the Mar Menor. This work integrates Sentinel 2 imagery with buoy-based ground truth to create models capable of high-resolution, depth-specific monitoring, enhancing early-warning capabilities for eutrophication. Sentinel 2 images were atmospherically corrected using C2RCC processors. Buoy data were aggregated by depth. Multiple ML
algorithms, including CatBoost, XGBoost, SVMs, and MLPs, were trained and validated using a cross-validation scheme with multi-objective optimization functions. Band-combination experiments and spatial aggregation strategies were tested to optimize prediction. The results show depth-dependent performance. The Root Mean Squared Logarithmic Error (RMSLE) obtained ranges from 0.34 at the surface to 0.39 at 3-4 m, while the R2 value was 0.76 at the surface, 0.76 at 1-2 m, 0.70 at 2-3 m, and 0.60 at 3-4 m. Generated maps successfully reproduced known eutrophication events. The study delivers an end-to-end, validated methodology chlorophyll mapping. Its integration of multispectral band combinations, buoy calibration, and modeling offers a transferable framework for other turbid coastal systems.
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All authors Antonio Martínez-Ibarra, Aurora González-Vidal, Adrián Cánovas-Rodríguez, Antonio F. Skarmeta
Physics and Society
A Triad of Networks and a Triad of Fusions for the Other Climate Crisis
Emilio Porcu, Tobia Filosi and Horst Simon
Shaw and Stevens call for a new paradigm in
climate science criticizes Large Scale Determinism in favor of (i) embracing discrepancies, (ii) embracing hierarchies, and (iii) create disruption while keeping interpretability. The last 20 years have seen a plethora of contributions relating complex networks with
climate data and
climate models. We provide a view of
climate networks through a triad of frameworks and associated paradigms: (a) networks of data, where both (geographical) nodes and their links (arcs) are determined according to some metrics and/or statistical criteria; (b)
climate data over networks, where the structure of the network (for both vertices and edges) is topologically pre-determined, and the
climate variable is continuously defined over the (nonlinear) network; finally, (c) networks for data, referring to the huge machinery based on networks within the realm machine learning and statistics, with specific emphasis on their use for
climate data. This paper is not a mere description of each element of the network triad, but rather a manifesto for the creation of three classes of fusions (we term them bridges). We advocate and carefully justify a fusion within to provide a corpus unicuum inside the network triad. We then prove that the fusion within is the starting point for a fusion between, where the network triad becomes a condition sine qua non for the implementation of the Shaw-Stevens agenda. We culminate with a meta fusion that allows for the creation of what we term a Shaw-Stevens network ecosystem.
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Accelerator Physics
Neutron production with a 10 kW HiCANS based on SATELIT, a CEA-Saclay target with liquid lithium
L. Thulliez, N. Berton, R. Boudouin et al. (+33 more)
High-Current Accelerator-driven
Neutron Sources (HiCANS) are currently under development across Europe to address the shortage of medium-scale
neutron sources, as many research
nuclear reactors have been decommissioned over the past several years. At CEA-Saclay, a HiCANS has been developed utilizing the IPHI accelerator, which delivers a 3 MeV
proton beam with a current of up to 100 mA, and the CEA-Saclay
liquid lithium target named SATELIT. In 2024-2025, a successful experimental campaign was conducted, during which a 10 kW
proton beam was directed at the
liquid lithium target for nearly 100 h to generate
neutrons via the 7Li(p,n)7Be
nuclear reaction. Throughout the experimental campaign, a total deposited beam power of 840~kW.h was accumulated, including two continuous operational days exceeding 11 h each. A polyethylene moderator coupled with SATELIT enabled the extraction of a thermal
neutron beam, with a flux measured at 1.4 m from the extraction point exceeding $10^6$ n.cm$^{-2}$.s$^{-1}$, which is sufficient for numerous
neutron applications. The next step for the long-term operation of this facility involves developing strategies to mitigate the radiological concerns associated with the accumulation of 7Be within the system. Overall, this work demonstrates that such facilities can play a significant role in the future of medium-scale
neutron sources in Europe.
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All authors L. Thulliez, N. Berton, R. Boudouin, N. Cavalière, S. Cazaux, T. Chaminade, N. Chauvin, D. Chirpaz, J.-L. Courouau, Q. Cridling, P. Daniel-Thomas, J. Darpentigny, G. Debras, G. Disset, A. Drouart, E. Dumonteil, R. Duperrier, R. Ferdinand, E. Giner Demange, J.-C. Guillard, N. Jonqueres, T. Lebrun, D. Loiseau, J. Mendes, B. Mom, F. Ott, C. Péron, J. Phocas, Y. Reinert, A. Roger, Y. Sauce, F. Senée, M. Trocmé, C. Veyssière, D. Vurpillot, X. Wohleber
Physics Education
Science ouverte et collaborative pour l'élaboration d'un banc automatisé de caractérisation de pertes en commutation par opposition
Nicolas Rouger, Luiz Villa, Matthieu Masson et al. (+7 more)
The switching losses of power transistors are generally measured using the so-called double pulse method. Measuring the opposition of two switching
cells is a complementary method that is more accurate but indirect. However, implementing this method can be more complex and requires calibration steps and comprehensive control, with the added issue of thermal management. In this context, we proposed to address this topic through open and collaborative science, first in the form of a two-day hackathon, followed by monthly open sessions. More than 20 participants contributed to the two-day hackathon, followed by monthly sessions for those wishing to continue working together. This enabled us to set up an automated bench, in open science, including the generation of switching commands, the configuration and control of measuring instruments, and the hardware part. Here we present and share our work and this open approach.
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All authors Nicolas Rouger, Luiz Villa, Matthieu Masson, Pauline Kergus, Joseph Kemdeg, Lorenzo Leijnen, Jean Alinei, Adrien Colomb, Ayoub Farah-Hassan, Arnauld Biganzoli
Medical Physics
Statistical Shape Modelling of the Nasosinusal Anatomy
Michele Bertolini, Silvia Tonghini, Marco Rossoni et al. (+5 more)
The human nose exhibits a huge variation in shape among individuals. All these variants alter the airflow through the nasal cavity and can impact how we smell odors. To acquire a better understanding of physiological and pathological functioning, it is important to study the effects of these modifications. SSM, or Statistical Shape Modelling, is a widely used methodology for considering morphological differences within a population. In the literature, only a few studies analyze nasal anatomy in its entirety, including paranasal sinuses, whose
segmentation is particularly challenging due to their complexity and variability. This work aims at creating a highly accurate SSM for the nasosinusal complex. A traditional, greyscale thresholding-based
segmentation approach was chosen, relying on Mimics software (Leuven, Belgium). 40 computed
tomography (CT)
datasets were considered. After
segmentation, post-processing was performed to obtain watertight meshes using 3-Matic software (Leuven, Belgium), which was also used for the SSM generation. The generated model shows all relevant landmarks that typically characterize a nasosinual complex. 32 different modes are needed to explain 95% of the total variance. As a preliminary output, this study showed the feasibility and consistency of a statistical model of the nasosinusal anatomy. However, additional studies involving a larger sample size and a more robust validation process could be conducted.
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All authors Michele Bertolini, Silvia Tonghini, Marco Rossoni, Marina Carulli, Susanne Weise, Christian Jan Baldus, Giorgio Colombo, Monica Bordegoni
Physics and Society
Leveraging Cellular Automata for Real-Time Wildfire Spread Modeling in California
Connor Weinhouse and Jameson Augustin
Wildfires are becoming increasingly frequent and devastating, and therefore the technology to combat them must adapt accordingly. Modern predictive models have failed to balance predictive accuracy and operational viability, resulting in consistently delayed or misinformed fire suppression and public safety efforts. The present study addresses this gap by developing and validating a predictive model based on cellular automata (CA) that incorporates key environmental variables, including vegetation density (NDVI), wind speed and direction, and topographic slope derived from open-access
datasets. The presented CA framework offers a lightweight alternative to data-heavy approaches that fail in emergency contexts. Evaluation of the model using a confusion
matrix against burn scars from the 2025 Pacific Palisades Fire yielded a recall of 0.860, a precision of 0.605, and an overall F1 score of 0.711 after 50 parameter optimization trials, with each simulation taking an average of 1.22 seconds. CA-based models can bridge the gap between accuracy and applicability, successfully guiding public safety and fire suppression efforts.
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Physics and Society
How the coupling of green finance and green technology innovation affect synergistic effect of pollution and emission carbon reduction: evidence from China
Guoqiang Liu and Ruijun Xie
Amid China's dual-carbon transition, the synergistic
alignment of green finance with green-technology innovation is pivotal for co-controlling pollution and CO2 emissions. Using panel data for 266 Chinese prefecture-level cities over 2007-2023, We construct the coupling coordination index system of green finance and green technology innovation via a coupling-coordination model and systematically analyzes influencing mechanism of synergistic effect of pollution and carbon reduction. Four findings emerge.(1) The coupled-coordination significantly enhances the synergy, and energy efficiency plays a partial intermediary role in the relationship between the two.(2) The effect is heterogeneous: pronounced in the eastern and western regions, negligible in the central region, and stronger in non-resource-based and non-Yangtze River Basin cities.(3) A double-threshold model reveals a non-linear strengthening pattern as green-finance depth increases.(4) Spatial Durbin estimates show positive spillovers: the coupling of green finance and green technology innovation not only improves the level of local coordination, but also drives the improvement of environmental performance in adjacent areas. These results provide quantitative guidance for allocating green-finance resources, elevating green-innovation efficiency, and designing regionally coordinated mitigation policies.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Ab initio study on photocatalytic properties of PtSSe-WXY Janus heterostructures
Shivprasad S. Shastri, Antonio Cammarata and Tomas Polcar
Semiconductor photocatalysis offers a sustainable route for converting
solar energy into chemical energy, enabling the production of clean fuels and valuable chemical products. To this aim, we explore van der Waals
heterostructures made up of Janus PtSSe and WXY (X, Y $=$ S, Se, Te and X $\neq$Y), in the context of photocatalytic applications. The redox capabilities of various
heterostructure configurations (atom facing types and stacking orders) are evaluated by aligning the absolute band edge positions with respect to redox potentials of hydrogen and oxygen
evolution reaction (HER and OER) and CO$_2$ reduction reactions. The stability of photocatalyst candidates are checked by layer binding energy calculations and ab initio molecular dynamics simulations. The optical absorption spectra suggest good light absorption in the visible range. Further, strain engineering is applied as a way to tune band edges and evaluate the possible use of the
heterostructures as photocatalysts. This study shows that van der Waals
heterostructure bilayers composed of Janus PtSSe and WSeTe in specific
geometric configurations can be potential materials as photocatalysts for HER, OER and CO$_2$ reduction reactions. Finally, we suggest that, although systems made up of PtSSe and WSTe cannot be used for photocatalytic applications, they can be explored for applications in thermoelectric energy conversion or infrared photovoltaics.
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Data Analysis and Statistics
Optimal Binning for Small-Angle Neutron Scattering Data Using the Freedman-Diaconis Rule
Jessie E. An, Chi-Huan Tung, Changwoo Do et al. (+1 more)
Small-Angle
Neutron Scattering (SANS) data analysis often relies on fixed-width binning schemes that overlook variations in signal strength and structural complexity. We introduce a statistically grounded approach based on the Freedman-Diaconis (FD) rule, which minimizes the mean integrated squared error between the histogram estimate and the true intensity distribution. By deriving the competing scaling relations for counting noise ($\propto h^{-1}$) and binning distortion ($\propto h^{2}$), we establish an optimal bin width that balances statistical precision and structural resolution. Application to synthetic data from the Debye scattering function of a Gaussian
polymer chain demonstrates that the FD criterion quantitatively determines the most efficient binning, faithfully reproducing the
curvature of $I(Q)$ while minimizing random error. The optimal width follows the expected scaling $h_{\mathrm{opt}} \propto N_{\mathrm{total}}^{-1/3}$, delineating the transition between noise- and resolution-limited regimes. This framework provides a unified, physics-informed basis for adaptive, statistically efficient binning in
neutron scattering experiments.
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All authors Jessie E. An, Chi-Huan Tung, Changwoo Do, Wei-Ren Chen
Plasma Physics
The impact of plasma turbulence on atomic reaction rates in the detached ASDEX Upgrade divertor
Konrad Eder, Wladimir Zholobenko, Andreas Stegmeir et al. (+2 more)
Numerical modeling of the edge and scrape-off layer (SOL) must account for atomic processes such as hydrogenic ionization and recombination, charge-exchange, and line radiation. Their reaction rates depend non-linearly on density and temperature and are thus sensitive to turbulent fluctuations, whose inclusion/omission may significantly affect model outcomes. We quantify the impact of fluctuations by studying global
turbulence simulations of the edge and SOL of ASDEX Upgrade in both attached and detached divertor conditions. While the effect of fluctuations is minimal for the attached state, pronounced localized discrepancies emerge in colder, detached conditions. The inclusion of turbulent fluctuations, when compared to mean-field calculations, causes a factor of 2 reduction in ionization and radiation rates local to the detachment front in the confined edge region. The effect arises from fluctuations crossing below the ionization energy threshold, facilitated by low mean temperature and increased fluctuation amplitudes at the detachment front. The rate reduction (rather than rate increase) is explained by the character of divertor fluctuations (negative density-temperature correlation, i.e., cold and dense blobs), notably distinct from characteristic fluctuations found at the outboard-midplane (positive correlation, i.e., hot and dense blobs). Furthermore, the cold and dense fluctuations enable efficient
plasma recombination even at average temperatures above the recombination threshold. In detached conditions, the combined
plasma particle source from ionization and recombination is, therefore, effectively reduced by at least 50% when compared to the standard mean-field source.
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All authors Konrad Eder, Wladimir Zholobenko, Andreas Stegmeir, Kaiyu Zhang, Frank Jenko
Medical Physics · Cross-listed from cs.HC
Differential Analysis of Pseudo Haptic Feedback: Novel Comparative Study of Visual and Auditory Cue Integration for Psychophysical Evaluation
Nishant Gautam, Somya Sharma, Peter Corcoran et al. (+1 more)
Pseudo-haptics exploit carefully crafted visual or auditory cues to trick the
brain into "feeling" forces that are never physically applied, offering a low-cost alternative to traditional haptic hardware. Here, we present a comparative psychophysical study that quantifies how visual and auditory stimuli combine to evoke pseudo-haptic pressure sensations on a commodity tablet. Using a Unity-based Rollball game, participants (n = 4) guided a virtual ball across three textured terrains while their finger forces were captured in real time with a Robotous RFT40 force-torque sensor. Each terrain was paired with a distinct rolling-sound profile spanning 440 Hz - 4.7 kHz, 440 Hz - 13.1 kHz, or 440 Hz - 8.9 kHz; crevice collisions triggered additional "knocking" bursts to heighten realism. Average tactile forces increased systematically with cue intensity: 0.40 N, 0.79 N and 0.88 N for visual-only trials and 0.41 N, 0.81 N and 0.90 N for audio-only trials on Terrains 1-3, respectively. Higher audio frequencies and denser visual textures both elicited stronger muscle activation, and their combination further reduced the force needed to perceive surface changes, confirming multisensory integration. These results demonstrate that consumer-grade isometric devices can reliably induce and measure graded pseudo-haptic feedback without specialized actuators, opening a path toward affordable rehabilitation tools, training simulators and assistive interfaces.
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All authors Nishant Gautam, Somya Sharma, Peter Corcoran, Kaspar Althoefer
Atomic Physics
Two-photon rubidium clock detecting 776~nm fluorescence
River Beard, Kyle W. Martin, John D. Elgin et al. (+2 more)
The optical atomic clock based on the $5S_{1/2} \rightarrow 5D_{5/2}$ two-
photon transition in rubidium is a candidate for a next generation, manufacturable, portable clock that fits in a small size, weight, and power (SWaP) envelope. Here, we report the first two-
photon rubidium clock stabilized by detecting 776~nm fluorescence. We also demonstrate the use of a multi-pixel
photon counter as a low voltage substitute to a photomultiplier tube in the feedback loop to the clock
laser.
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All authors River Beard, Kyle W. Martin, John D. Elgin, Brian L. Kasch, Sean P. Krzyzewski
Computational Physics · Cross-listed from math.NA
Multi-Level Hybrid Monte Carlo / Deterministic Methods for Particle Transport Problems
Vincent N. Novellino and Dmitriy Y. Anistratov
This paper presents multilevel hybrid transport (MLHT) methods for solving the neutral-particle Boltzmann transport equation. The proposed MLHT methods are formulated on a sequence of spatial grids using a multilevel Monte Carlo (MLMC) approach. The general MLMC
algorithm is defined by recursively estimating the expected value of the correction to a solution functional on a neighboring grid. MLMC theory optimizes the total computational cost for estimating a functional to within a target accuracy. The proposed MLHT
algorithms are based on the quasidiffusion (variable Eddington factor) and second-moment methods. For these methods, the low-order equations for the angular moments of the angular flux are discretized in space. Monte Carlo techniques compute the closures for the low-order equations; then the equations are solved, yielding a single realization of the global flux solution. The ensemble average of the realizations yields the level solution. The results for 1-D slab transport problems demonstrate weak convergence of the functionals. We observe that the variance of the correction factors decreases faster than the computational cost of generating an MLMC sample increases. In the problems considered, the variance and cost of the MLMC solution are driven by the coarse-grid calculations.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Insights into the OER, ORR, and HER Activity of a New MXene-Family SnSiGeN4 Photocatalyst for Water Splitting: A First-Principles Study
Chhatra Bahadur Subba, Bhanu Chettri, Amel Laref et al. (+4 more)
The development of efficient and cost-effective catalysts for clean energy conversion remains a central challenge in materials science. Although platinum serves as the
benchmark catalyst, its scarcity and high cost hinder large-scale deployment. In this study, we propose a newly predicted SnSiGeN4 MXene-family monolayer as a promising candidate for the oxygen
evolution reaction (OER), oxygen reduction reaction (ORR), and hydrogen
evolution reaction (HER). Using first-principles calculations, we systematically investigated its electronic, vibrational, and optical properties across multiple exchange-correlation functionals, including hybrid approaches, revealing a wide and tunable band gap. Simulated infrared and Raman spectra further confirm the dynamical stability and the presence of catalytically active sites. Guided by these findings, we studied photocatalytic reaction analyses that demonstrate that the computed overpotentials for OER, ORR, and HER are comparable to those of Pt-based catalysts and outperform Ir-based systems, positioning SnSiGeN4 as a sustainable, high-performance platform for next-generation UV-visible-light-driven photocatalysis.
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All authors Chhatra Bahadur Subba, Bhanu Chettri, Amel Laref, Zeesham Abbas, Amna Parveen, Dibya Prakash Rai, Zaithanzauva Pachuau
Chemical Physics
Evaluating Multiconfigurational Trials for Accurate Phaseless Auxiliary-Field Quantum Monte Carlo on 3d Transition Metal Complexes
Hung T. Vuong, Ankit Mahajan, John L. Weber et al. (+3 more)
In this study, we evaluate multi-configurational trial wave function protocols for phaseless auxiliary field
quantum Monte Carlo (ph-AFQMC) on transition metal containing systems. First, we
benchmark vertical ionization potentials for 22 3d transition metal complexes against published high-accuracy ph-AFQMC values in a double
zeta basis set. We then compute the vertical ionization potential for a set of six metallocenes using our best-performing protocol, alongside ph-AFQMC using a configuration interaction singles and doubles (CISD) trial state. We also analyze the performance of canonical coupled-cluster theory with singles, doubles and perturbative triples (CCSD(T)), as well as its local approximation using domain-based local pair natural orbitals (DLPNO-CCSD(T1)) using different reference orbitals. To reach the complete-basis-set (CBS) limit, we examine several extrapolation schemes and report CBS-limit ph-AFQMC and CCSD(T) values alongside experimental results. We find that ph-AFQMC with the best-performing trial in a triple
zeta basis, followed by CBS correction from DLPNO-CCSD(T1) with unrestricted B3LYP reference orbitals, yields small deviations from experiment at modest cost. Using a CISD trial state in ph-AFQMC gives the closest agreement with experiment (errors < 2 kcal/mol), albeit with lower scalability.
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All authors Hung T. Vuong, Ankit Mahajan, John L. Weber, James Shee, David R. Reichman, Richard A. Friesner
Atmospheric and Oceanic Physics
Project Severe Weather Archive of the Philippines (SWAP). Part 2: Baseline Climatology of Close Proximity Soundings in Hailstorm Environments across Luzon, Philippines
Generich H. Capuli
The environments of severe thunderstorms that produced hail were examined using 171 proximity soundings (2005-2024) archived in the 3rd Data Release of Project SWAP. These soundings were categorized based on their geographical occurrence into three hail-prone environments across Luzon, Philippines. Key parameters describing instability, vertical wind shear, and moisture were calculated to assess the environmental conditions for hail production. The probability of hail occurrence, expressed as a function of W$_{\text{MAX}}$ ($\sqrt{2 \times \text{CAPE}}$) and 0-6 km bulk shear (DLS), revealed patterns distinct from those reported in other regions. Hail events in Luzon were most likely under high CAPE conditions, where boundary-layer moisture was sufficient, mid- and low-level lapse rates were steep, and lifting condensation levels were high. Surprisingly, weak DLS was common across Luzon hail environments, diverging from existing severe weather climatologies, yet large DCAPE indicated environments conducive to damaging wind events. When DLS was replaced with the shear magnitude between the cloud base and
equilibrium level, the probability of hail occurrence increased, better aligning with global severe weather climatologies. This finding is supported by hodograph analyses, which show largely unidirectional wind profiles: strong speed shear aloft but weak directional shear in the low-levels. Parameters such as W$_{\text{MAX}}$SHEAR, W$_{\text{MAX}}$SHEAR$_{\text{LCL-EL}}$, and BWD$_{\text{LCL-EL}}$ emerge as potential discriminators between non-severe and severe thunderstorms capable of producing hail, and as useful metrics for assessing convective storm severity in Luzon and possibly countrywide. Finally, two recurring severe setups conducive to hail were identified: (1) an easterly regime associated with trade winds, and (2) a westerly regime linked to the Asian summer monsoon.
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Applied Physics
Self-Resetting Soft Ring Enables Autonomous and Continuous Leaping under Uniform Light
Fangjie Qi, Caizhi Zhou, Haitao Qing et al. (+2 more)
Jumping is an efficient locomotion strategy to traverse cluttered, uneven, or unstable environments in nature, yet replicating continuous, autonomous leaping in soft
robots remains challenging due to limited energy storage and reliance on human intervention or latches. Here, we report a millimeter-scale, self-resetting soft ring that achieves repeated vertical and stable horizontal leaps under uniform infrared illumination without external control. The ring-shaped
liquid crystal elastomer body twists to store elastic energy, which is suddenly released when a rigid tail strikes the ground, propelling the
robot. During the airborne phase, the twisted body autonomously untwists, resetting for the next cycle. By tuning
geometric asymmetry and the center of mass, the
robot transitions between crawling, directional leaping, and vertical jumping. Optimized configurations yield vertical jumps exceeding 80 body heights and directional horizontal leaps over 3 body lengths. Beyond controlled motion on flat ground, the
robot demonstrates resilient and robust locomotion across slopes, parallel hurdles, and diverse cluttered natural terrains including grass, wet sand, and mulch. This work establishes a new paradigm of twisting-enabled, photothermally powered soft
robots capable of autonomous, continuous leaping, with potential applications in environmental
navigation, swarm robotics, and unstructured terrain
navigation.
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All authors Fangjie Qi, Caizhi Zhou, Haitao Qing, Haoze Sun, Jie Yin
Plasma Physics
Si3N4 membrane as entrance window for plasma-generated vacuum ultraviolet (VUV) radiation
Luka Hansen, Görkem Bilgin and Jan Benedikt
Vacuum ultraviolet (VUV) radiation produced by an atmospheric pressure
plasma was successfully measured down to wavelengths of 58.4nm utilizing a 20nm thin Si3N4 membrane to transfer the VUV radiation into a
vacuum monochromator. This method allows measurements without disturbing the
plasma or the spectra. He2 absorption could be observed by filling the monochromator with He. Transmission of the Si3N4 membrane in the region of the He2 excimer continua (58nm to 100 nm) could indirectly be measured and confirms literature values.
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Chemical Physics
Is Platinum a Proton Blocking Catalyst?
Aparna Saksena, Yujun Zhao, J. Manoj Prabhakar et al. (+3 more)
Platinum, to date, is the most widely applied electrocatalyst for hydrogen
evolution reaction (HER) in acidic media. It is assumed to be a
proton-blocking catalyst with only surface-limited adsorption of the reaction intermediates. Here, we critically evaluate the bulk interaction of Pt with hydrogen (H), and its heavier isotope deuterium (D), by monitoring operando mass change of the Pt electrode during galvanostatic heavy/water splitting by employing an electrochemical quartz
crystal microbalance. Unexpectedly, we observe an irreversible temporal mass gain and a change in the reaction's overpotential, arising from
diffusion of H/D into Pt, confirmed by atom probe
tomography and thermal desorption spectroscopy. Sub-surface concentration of at least ca. 15 at. % of D in Pt was observed, diffusing down to a depth of more than 10 nm. Analytical description quantified the
diffusion coefficient of D in Pt to be 3.2X10^-18 cm2Xs-1. These findings challenge the existing credence of Pt-
proton interaction being limited to the surface, prompting the expansion of the catalyst design strategies to account for property-modifying bulk
diffusion of H/D in the Pt
matrix
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All authors Aparna Saksena, Yujun Zhao, J. Manoj Prabhakar, Dierk Raabe, Baptiste Gault, Yug Joshi
Applied Physics · Cross-listed from cond-mat.soft
Toggling stiffness via multistability
Hugo de Souza Oliveira, Michele Curatolo, Renate Sachse et al. (+1 more)
Variable stiffness is a key capability in biological and robotic systems, enabling adaptive interaction across tasks and environments. Mechanical metamaterials offer an alternative to conventional mechatronic solutions by encoding stiffness variation directly into monolithic structural architectures, reducing the need for discrete assemblies. Here, we introduce a multistable mechanical metamaterial that exhibits a toggleable stiffness effect in which the effective shear stiffness switches discretely between stable mechanical configurations. Mechanical analysis of surrogate beam models of the unit
cell reveals that this behavior originates from the rotation transmitted by the support beams to the curved beam, governing the balance between bending and axial deformation. Consequently, the shear stiffness ratio between the two states can be tuned by varying the slenderness of the support beams or by incorporating localized hinges that modulate rotational transfer. Experiments on 3D-printed prototypes validate the numerical predictions and confirm consistent stiffness toggling across different geometries. Finally, we demonstrate a monolithic soft clutch that leverages this effect to achieve programmable, stepwise stiffness modulation. This work establishes a design strategy for toggleable stiffness using multistable metamaterials, with potential applications in soft robotics and smart structures where adaptive compliance is of paramount importance.
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All authors Hugo de Souza Oliveira, Michele Curatolo, Renate Sachse, Edoardo Milana
Atomic Physics · Cross-listed from quant-ph
Subspace Leakage Error Randomized Benchmarking of Mølmer-Sørensen Gates
R. T. Sutherland, A. C. Hughes, J. P. Marceaux et al. (+3 more)
We demonstrate a new technique that adapts single-
qubit randomized benchmarking to two-
qubit Mølmer-Sørensen gates. We use the controllable gate phase to generate Cliffords that act on a two-state subspace, enabling benchmarking of two-
qubit gates without single-
qubit operations. In addition to quantifying the gate infidelity, the protocol provides valuable information about the type of error by distinguishing between those that conserve the two-state subspace and those that result in leakage out of it. We demonstrate the protocol for calibrating and validating all-electronic maximally entangling gates in a trapped-ion
quantum computer, achieving a two-
qubit gate error of $2.6 (2)\times10^{-4}$.
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All authors R. T. Sutherland, A. C. Hughes, J. P. Marceaux, H. M. Knaack, C. M. Löschnauer, R. Srinivas
Optics
Engineering High-Order Harmonic Generation through Gas Confinement at Sub-Millimeter Lengths
Agata Azzolin, Gaia Giovannetti, Oliviero Cannelli et al. (+23 more)
Attosecond light sources based on high-order harmonic generation (HHG) constitute to date the only table-top solution for producing coherent broadband radiation covering the spectral range from the extreme ultraviolet to the soft X-rays. The so-called emission cutoff can be extended towards higher
photon energies by increasing the driving wavelength at the expense of conversion efficiency. An alternative route is to overdrive the process by using higher
laser intensities, with the challenging requirement of interacting with higher
plasma densities over short propagation distances. Here, we address this challenge by using a differentially pumped glass chip designed for optimal gas confinement over sub-mm lengths. By driving HHG with multicycle pulses at either 800 nm or 1500 nm, we demonstrate a cutoff extension by a factor of two compared to conventional phase matching approaches and surpassing the present record using multicycle fields. Our three-dimensional propagation simulations, in excellent agreement with the experiment, confirm that gas confinement is crucial since efficient phase matching of cutoff harmonics occurs only for short propagation lengths. Additionally, we show that the high
photon energy component is not only temporally confined to the leading edge of the driving pulse, but also spatially confined in the near-field to an off-axis contribution due to reshaping of the driving field along propagation inside the medium. Our findings contribute to the fundamental understanding of HHG across different regimes.
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All authors Agata Azzolin, Gaia Giovannetti, Oliviero Cannelli, Sabine Rockenstein, Guangyu Fan, Md S. Ahsan, Lorenzo Colaizzi, Erik P. Månsson, Noah Tettenborn, Linda Oberti, Davide Faccialà, Fabio Frassetto, Anna Gabriella Ciriolo, Dario W. Lodi, Alia Ashraf, Cristian Manzoni, Rebeca Martínez Vázquez, Michele Devetta, Roberto Osellame, Luca Poletto, Salvatore Stagira, Caterina Vozzi, Terry Mullins, Vincent Wanie, Andrea Trabattoni, Francesca Calegari
Plasma Physics
Investigating Solid-Fluid Phase Coexistence in DC Plasma Bilayer Crystals: The Role of Particle Pairing and Mode Coupling
Siddhartha Mangamuri, Lénaïc Couëdel and Surabhi Jaiswal
This article presents a detailed investigation of solid-fluid phase coexistence in a
bilayer dusty
plasma crystal subjected to varying confinement ring bias voltages in a DC glow discharge argon
plasma. Melamine formaldehyde particles were employed to form a stable, hexagonally ordered
bilayer crystal within a confinement ring electrically isolated from the grounded cathode. By systematically adjusting the confinement ring bias, a distinct phase coexistence emerged characterized by a fluid-like melted core surrounded by a solid crystalline periphery. Crucially, analysis of the
phonon spectra revealed frequency shifts that deviate significantly from the predictions of classical monolayer Mode-Coupling Instability (MCI) theory. Stability analysis further demonstrated that dynamic interlayer particle pairing and the associated increase in non-reciprocal interaction strength are strongly correlated with the onset of structural destabilization. These findings highlight previously underappreciated mechanisms driving the melting transition in
bilayer dusty
plasmas, offering a more comprehensive understanding of phase behavior in complex
plasma systems. The results underscore the importance of interlayer coupling and confinement effects in tuning structural transitions.
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Applied Physics
Nonlinear Dynamics and Fermi-Pasta-Ulam-Tsingou Recurrences in Macroscopic Ultra-low Loss Levitation
Mehrdad M. Sourki, Wisdom Boinde, Ali N. Amiri et al. (+1 more)
Macroscopic systems, when governed by nonlinear interactions, can display rich behavior from persistent oscillations to signatures of ergodicity breaking. Nonlinearity, long regarded as a nuisance in precision systems, is increasingly recognized as a gateway to new physical regimes. While such dynamics have been extensively studied in optics and atomic physics, macroscopic systems are rarely associated with long-lived coherence and nonlinear control and remain an untapped platform for probing the fundamental nonlinear processes. Here, we report the observation of long-lived oscillatory dynamics in millimeter-scale levitated dielectric quartz particles exhibiting clear signatures of nonlinear mode coupling, a positive largest Lyapunov exponent of 0.0095 s^-1, and partial energy recurrences-phenomena strongly reminiscent of the
Fermi-Pasta-Ulam-Tsingou physics. We observe dissipation rates below 4*10E-6 Hz, limited by our ability to measure dissipation in presence of nonlinear dynamics. We estimate an intrinsic acceleration sensitivity of 62*10E-12 g/sqrt(Hz), at room temperature. The
magnetic trap is constructed from a static arrangement of permanent magnets, requiring no external power or active feedback. Our findings open a path toward leveraging nonlinear dynamics for novel applications in sensing, signal processing, and statistical mechanics.
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All authors Mehrdad M. Sourki, Wisdom Boinde, Ali N. Amiri, Mahdi Hosseini
Fluid Dynamics
Whipped and mixed warm clouds in the deep sea
Hans van Haren
Turbulence is indispensable to redistribute nutrients for all life forms larger than microbial, on land and in the ocean. Yet, the development of deep-sea
turbulence was not studied in three dimensions to date. As a disproportionate laboratory, an array of nearly 3000 high-resolution temperature sensors had been installed for three years on the flat 2500-m deep bottom of the Mediterranean Sea. The time series from the half-cubic hectometer mooring-array allows for the creation of unique movies of deep-sea water motions. Although temperature differences are typically 0.001degrC, variable convection-
turbulence is observed as expected from geothermal heating through the flat seafloor. During about 40% of the time, an additional
turbulence, 3 times stronger in magnitude, is observed from slantwise advected warmer waters to pass in turbulent clouds. Besides turbulent clouds and seafloor heating, movies also reveal weakly turbulent interfacial-wave breakdown that commonly occurs in the open ocean far away from boundaries.
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