Instrumentation and Detectors
Design and commissioning of the miniBELEN neutron counter for the study of $(\alpha,n)$ reactions
Nil Mont-Geli, Ariel Tarifeño-Saldivia, Max Pallàs et al. (+27 more)
The miniBELEN detector is a moderated
neutron counter based on the use of $^3$He tubes and high-density polyethylene as moderator. The detector has been designed to have a
neutron detection efficiency that is nearly independent from the initial
neutron energy for ($\alpha$,n) reactions with alpha-particle energies up to 15 MeV. In order to achieve that, an innovative design methodology based on the use of cadmium
neutron filters has been used. Monte Carlo calculations of the detector response have been validated using a $^{252}$Cf fission source. Measurements of the relatively well-known ($\alpha$,n) thick-target yields on aluminum have been found to be consistent with data from previous works. A method has been developed to correlate the counting rate ring ratios with the mean
neutron energy and validated using previous time-of-flight measurements of the aluminum ($\alpha$,n) spectra and with a $^{252}$Cf fission source. Submitted to The European Physical Journal - Plus
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All authors Nil Mont-Geli, Ariel Tarifeño-Saldivia, Max Pallàs, Ángel Perea, Luis Mario Fraile, Guillem Cortés, Sílvia Viñals, José Luis Tain, Gastón Garcia, Daniel Soler, Odette Alonso-Sañudo, María José G. Borge, José Antonio Briz, Francisco Calviño, Daniel Cano-Ott, Alfredo De Blas, Begoña Fernández, Roger Garcia, Vicente Garcia Tavora, Enrique M. González-Romero, Carlos Guerrero, Andrés Illana, Trino Martínez, Víctor Martínez-Nouvilas, Emilio Mendoza, Enrique Nácher, Amanda Nerio Aguirre, Julio Plaza, Olof Tengblad, José Manuel Udías
Fluid Dynamics
Process Microstructure Coupling in Reduced Gravity Laser Welding via Open-Source Multiphysics Simulation Framework
Rakibul Islam Kanak, Taslima Hossain Sanjana, Apurba Sarker et al. (+1 more)
Supplying spare parts from Earth for in space repair is economically prohibitive and logistically slow, posing a major barrier to sustainable space operations. As lunar and Martian missions accelerate in the coming decades, the feasibility of in-situ repair methods, particularly
laser based welding, must be rigorously evaluated. The micro scale physics governing weld quality are fundamentally altered by variations in
gravity and ambient pressure, yet their coupled influence across different welding regimes remains poorly understood. This work introduces a fully open-source thermo-fluid-microstructure modeling framework with computational fluid dynamics (CFD) and cellular automata (CA) to quantify how gravitational conditions reshape weld pool behavior across multiple welding regimes and spatial scales. The framework further enables prediction of the resulting microstructure from imposed process parameters, providing an accessible pathway for future research in in space manufacturing (ISM). As a demonstration, the article analyzes
laser welding of Al6061 across three process regimes (conduction, transition, and keyhole) and four gravitational environments (Earth, Moon, Mars, and International Space Station (ISS)). Analysis reveals that reduced
gravity suppresses buoyancy-driven convection, thereby altering melt pool geometries.
Vacuum conditions increase
laser energy deposition, while microgravity promotes equiaxed grain formation via reduced melt convection. The framework captures keyhole dynamics, thermal histories, and grain morphologies with high fidelity, validated against experimental data. These findings establish process microstructure relationships critical for reliable metallic fabrication in space and provide a reproducible platform for future in-space manufacturing research.
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All authors Rakibul Islam Kanak, Taslima Hossain Sanjana, Apurba Sarker, Sourav Saha
Physics and Society
Comparison of Mathematical Models for Subscription Services Using Optimization Problems and Quantum Information Theory -Feasibility of Implementing Optimization Problem Algorithms on Quantum Computers-
Misao Fukuda
The purpose of this research is to explore whether it is possible to construct a design theory for subscription services for intangible goods from a time discounting perspective, based on
quantum information theory, which is the foundational theory for
quantum computers and similar technologies. To this end, we propose a mathematical model of subscription services using optimization problems based on optimal growth theory from standard economics, and with reference to microeconomics, we define utility as a value function of customer satisfaction derived from
quantum mutual information, an
entropy measure in
quantum information theory, by considering time discounting. We propose the quantification of customer satisfaction and the formulation of consumer surplus. In the mathematical model of subscription services, the existence of a minimum value in the time-discounted customer satisfaction value function under budget constraints, and the realization of a mathematical expression for consumer surplus, could be explained by the laws of behavioral economics. This yielded new insights into the design of individually customized customer experiences, enhanced the feasibility of constructing economic models based on
quantum information theory and the mathematical design of customer experiences, raised the possibility that mathematical models using
quantum information theory can achieve greater economic welfare than standard economics, and increased the feasibility of implementing optimization problem
algorithms on
quantum computers.
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General Physics
Exponential parallelism in practice: a comparative feature on quantum computing and instantaneous noise-based logic
Laszlo B. Kish
Exponential parallelism, a defining principle of advanced computational systems, holds promise for transformative impacts across several scientific and industrial domains. This feature paper provides a comparative overview of
Quantum Computing (QC) and Instantaneous Noise-based Logic (INBL), focusing on their practical strengths, limitations, and applications rather than exhaustive technical depth. Both paradigms leverage exponentially large
Hilbert spaces:
quantum computing achieves this via
quantum superposition, while INBL realizes it through the product space of classical noise processes.
Quantum computers attain universality for all computational operations, whereas current INBL frameworks are universal only for Boolean logic; notably, essential superposition operations-such as AND and OR gates-are absent, precluding implementations of
algorithms like Shor's. However, for certain problem classes where full universality is not required, INBL and
quantum computing can offer equivalent time and hardware complexity, as observed with the Deutsch-Jozsa
algorithm. Remarkably, for search tasks such as phonebook lookup, Grover's
quantum algorithm provides a quadratic O(n^0.5) speedup compared to the classical approach, while INBL achieves an exponential speedup, requiring only logarithmic time in the size n of the phonebook O(log n). Such INBL
algorithms could, in principle, be adapted to
quantum hardware to attain similar performance. Importantly, INBL hardware is considerably simpler, being implementable with modest modifications to conventional PC architectures equipped with a true random number generator, and it inherently avoids the decoherence and error correction challenges of
quantum systems.
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Optics
$\mathcal{PT}$-like phase transitions from square roots of supersymmetric Hamiltonians
Jacob L. Barnett and Ramy El-Ganainy
We introduce a general framework for realizing $\mathcal{PT}$-like phase transitions in non-Hermitian systems without imposing explicit parity–time ($\mathcal{PT}$)
symmetry. The approach is based on constructing a
Hamiltonian as the square root of a supersymmetric partner energy-shifted by a constant. This formulation naturally leads to bipartite dynamics with balanced gain and loss and can incorporate non-reciprocal couplings. The resulting systems exhibit entirely real spectra over a finite parameter range precisely when the corresponding passive
Hamiltonian lacks a zero mode. As the non-Hermitian parameter representing gain and loss increases, the spectrum undergoes controlled real-to-complex transitions at second-order exceptional points. We demonstrate the versatility of this framework through several examples, including well-known models such as the Hatano–Nelson (HN) and complex Su–Schrieffer–Heeger (cSSH)
lattices. Extending the formalism to $q$-commuting
matrices further enables the systematic realization of higher-order exceptional points in systems with unidirectional couplings. Overall, this work uncovers new links between non-Hermitian physics and supersymmetry, offering a practical route to engineer photonic arrays with tunable spectral properties beyond what is achievable with explicit $\mathcal{PT}$-
symmetry.
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History and Philosophy of Physics
The Great January Comet of 1910 (C/1910 A1): A Key Opportunity Missed by New Zealand Astronomers
John Drummond, Wayne Orchiston, Carolyn Brown et al. (+1 more)
C/1910 A1 was one of the Great Comets of the twentieth century. Although it was widely observed from the Northern Hemisphere, it was first discovered by observers south of the Equator. The comet arrived just months before the widely anticipated apparition of Comet 1P/Halley and was significantly more spectacular. As a result, the two comets were confused, and many who, in later years, talked about how prominent Comet 1P/Halley was in 1910 were often remembering C/1910 A1. In this paper, we present the results of a detailed search through historical records and media publications in Aotearoa / New Zealand, to investigate how extensively C/1910 A1 was observed from New Zealand. We compare our results with observations reported for Comet 1P/Halley later in 1910, finding that surprisingly few observations of C/1910 A1 were made by New Zealand observers. We discuss cases where the comet was misidentified as being an early sighting of 1P/Halley and compare the observations made in New Zealand with international observations/records/accounts. We find that, although the Great January Comet of 1910 was observed from New Zealand, it was witnessed by few compared to other parts of the world, meaning that the apparition of C/1910 A1 was something of a missed opportunity for New Zealand astronomers.
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All authors John Drummond, Wayne Orchiston, Carolyn Brown, Jonathan Horner
Fluid Dynamics · Cross-listed from astro-ph.SR
Modeling stellar convective transport with plumes : II. Transport Properties of Locally and Non-locally driven Convection
Youhei Masada, Tomoya Takiwaki and Nobumitsu Yoko
We perform three-dimensional hydrodynamic simulations of two idealized regimes of
stellar convection: a cooling-driven model (Model C) and an
entropy-gradient-driven model (Model S). The two regimes exhibit striking contrasts: while Model S develops large, relatively stationary eddies excited at depth, Model C is dominated near the surface by intermittent plume-like downflows that produce broad non-Gaussian velocity distributions and a turbulent energy flux that exceeds Model S by nearly an order of magnitude in the upper convection zone. Conventional gradient-
diffusion (GD) closures reproduce the transport in Model S but significantly underestimate it in Model C, demonstrating that plume-driven convection lies beyond the scope of local, gradient-based models. To address this, we introduce a Time-Space Double Averaging (TSDA) method that extracts coherent fluctuations, yielding a diagnostic variable $\tilde{\boldsymbol{u}}$ that peaks where the flux is largest. Building on this insight, we propose a modified GD closure in which the turbulent diffusivity is corrected by a plume-mediated term, achieving quantitative agreement with simulation results. Although the closure requires a calibrated model parameter and a careful choice of the averaging window, it provides a physically transparent framework that links coherent plume dynamics to mean-field transport, and offers a pathway toward improved subgrid models for non-
equilibrium stellar convection zones.
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Instrumentation and Detectors
Finding Trafficked Radiological Materials via Coherent Elastic Neutrino-Nucleus Scattering
Brianna N Ryan, Harold Douglas Pinckney D Pinckney, Michael P Short et al. (+1 more)
The potential to use
neutrinos for
nuclear non-proliferation has been heavily debated due to the tension between production abundance and low interaction rate. A newly detected
neutrino interaction channel, coherent elastic
neutrino-
nucleus scattering (CE$\nu$NS), could potentially end this debate due to its improved cross-section compared to other
neutrino interactions. This paper presents a feasibility study for the use of CE$\nu$NS superconducting detectors to find trafficked radiological materials. To do this, we calculated the minimal activity required for situational detection under ideal conditions, without background, at 95% confidence level. This analysis was performed for four commonly smuggled radioisotopes: $^{137}$Cs, $^{109}$Cd, $^{192}$Ir, and $^{57}$Co. Using these results, we conclude that CE$\nu$NS could be used to discover trafficked $^{137}$Cs sources with an activity above the PBq level, but that it is not applicable for finding other radioactive sources. This framework can also be applied to other
nuclear security concerns, such as safeguarding generation IV
nuclear reactors.
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All authors Brianna N Ryan, Harold Douglas Pinckney D Pinckney, Michael P Short, Joseph A Formaggio
Physics and Society
Regime shifts and transformations in social-ecological systems: Advancing critical frontiers for safe and just futures
Juan C. Rocha, Caroline Schil, Emilie A. L. Lindkvist et al. (+24 more)
Current research challenges in sustainability science require us to consider nonlinear changes e.g. shifts that do not happen gradually but can be sudden and difficult to predict. Central questions are therefore how we can prevent harmful shifts, promote desirable ones, and better anticipate both. The regime shifts and transformations literature is well-equipped to address these questions. Yet, even though both research streams stem from the same intellectual roots, they have developed along different paths, with limited exchange between the two, missing opportunities for cross- fertilisation. We here review the definitions and history of both research streams to disentangle common grounds and differences. We propose avenues for future research and highlight how stronger integration of both research streams could support the development of more powerful approaches to help us navigate toward safe and just futures.
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All authors Juan C. Rocha, Caroline Schil, Emilie A. L. Lindkvist, Reinette Biggs, Thorsten Blenckner, Anne-Sophie Crépin, Ingo Fetzer, Carl Folke, Amanda Jiménez-Aceituno, Nielja Knecht, Jan J. Kuiper, Steven J. Lade, Carla Lanyon-Garrido, Romi Lotcheris, Romina Martin, Vanessa Masterson, Petr Matous, Michele-Lee Moore, Magnus Nyström, Per Olsson, Laura M. Pereira, Garry Peterson, André Pinto da Silva, Sasha Quahe, Maja Schlüter, Lan Wang-Erlandsson, Hannah Zoller
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Lattice Thermal Transport Beyond the Quasiparticle Approximation: Nontrivial Spectral Competition between Three- and Four-Phonon Interactions
Yi Xia
The breakdown of the quasiparticle approximation (QPA) for
phonons in strongly anharmonic materials necessitates advanced first-principles frameworks for accurate
lattice dynamics and thermal transport predictions. We develop a comprehensive beyond-quasiparticle approximation (BQPA) approach incorporating both three- (3ph) and four-
phonon (4ph) interactions and apply it to investigate
lattice thermal conductivity ($\kappa_{\rm L}$) in MgO, PbTe, and AgCl – materials that span a broad spectrum of anharmonicity, from weak to severe anharmonic regimes with overdamped
phonons. We reveal that while BQPA consistently increases $\kappa_{\rm L}$ relative to QPA due to
phonon softening when considering only 3ph interactions, the inclusion of additional 4ph interactions hardens the
phonon spectrum and suppresses this enhancement, bringing BQPA and QPA predictions into close agreement via subtle spectral competition effects across all three compounds. These findings highlight that accurate modeling of $\kappa_{\rm L}$ in strongly anharmonic materials requires treating both full
phonon spectral function and higher-order anharmonicity on equal footing. Our work establishes a systematic framework for modeling thermal transport in systems with overdamped
phonons and provides critical insights for materials design beyond the limits of conventional
phonon transport theory.
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Physics and Society
Impacts of bridging nodes on the epidemic activation mechanisms
José Carlos M. Silva, Diogo H. Silva, Wesley Cota et al. (+2 more)
Bridging nodes, which connect critical components of a network, play an important role in maintaining structural integrity and facilitating communication within the network, representing indirect yet relevant connections. Epidemic triggering mechanisms in networks often involve long-range mutual activation of hubs, mediated by paths composed of low-degree nodes. While low-degree nodes are abundant in networks, their role in bridging central nodes in epidemic activation mechanisms has not been thoroughly analyzed. Starting with a backbone network with a power-law degree distribution, we investigate the role of adding degree-2 bridging nodes that are preferentially attached to hubs. Our findings reveal that bridging nodes can mediate an indirect feedback interaction between hubs that modifies the epidemic localization and activation mechanisms of the epidemic processes with recurrent infections. In particular, the collective activation observed in the presence of waning immunity, which produces a finite epidemic threshold in power-law networks with degree exponent $\gamma>3$, is altered to a localized activation with a vanishing threshold. Our numerical results are analytically supported by the non-backtracking
matrix properties that emerge in the recurrent dynamical message-passing theory.
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All authors José Carlos M. Silva, Diogo H. Silva, Wesley Cota, Francisco A. Rodrigues, Silvio C. Ferreira
Physics and Society
Opinion formation at Ising social networks
Kristina Bukina and Dima L. Shepelyansky
We study the process of opinion formation in an Ising social network of scientific collaborations. The network is undirected. An Ising
spin is associated with each network node being oriented up (red) or down (blue). Certain nodes carry fixed, opposite opinions whose influence propagates over the other
spins, which are flipped according to the majority-influence opinion of neighbors of a given
spin during the asynchronous Monte Carlo process. The amplitude influence of each
spin is self-consistently adapted, and a flip occurs only if this majority influence exceeds a certain conviction threshold. All non-fixed
spins are initially randomly distributed, with half of them oriented up and half down. Such a system can be viewed as a model of elite influence, coming from the fixed
spins, on the opinions of the crowd of non-fixed
spins. We show that a phase transition occurs as the amplitude influence of the crowd
spins increases: the dominant opinion shifts from that of the elite nodes to a phase in which the crowd
spins' opinion becomes dominant and the elite can no longer impose their views.
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Geophysics
Development of an Uncertainty Workflow to Support Landsat TIRS Split Window-Derived Surface Temperature Products
Amirhossein Hassanzadeh, Robert Mancini, Aaron Gerace et al. (+2 more)
Current Landsat Level 2 surface temperature products are derived using a single-channel (SC) methodology to estimate per-pixel surface temperature (ST) maps from Level~1 radiance data. A known issue with the Level 2 uncertainty, however, is its susceptibility to overestimation of uncertainty due to its dependence on Landsat's cloud mask, which is prone to false-positives. Beginning with Collection 3, the split window (SW) approach will serve as the surface temperature
algorithm for the level-2 product, reflecting its adaptability across conditions which necessitates the development of a dedicated uncertainty workflow. We introduce an improved uncertainty workflow, based on a physical parameter called total precipitable water (TPW), that more adequately estimates the uncertainty associated with surface temperature estimates. We leveraged a SW
algorithm for estimating surface temperature to drive the uncertainty methodology discussed here. First, considering Landsat is not equipped with the optical channels necessary for deriving TPW, we create an XGBoost-based machine learning pipeline that relates TIRS bands 10 & 11 image radiance to TPW using the MODIS product as reference. The resulting modeling approach achieves a mean absolute error in estimating TPW of 0.54 [cm] and a coefficient of determination (R2) as high as 0.89. Secondly, we propose an improved (SW-based) uncertainty workflow that also uses standard error propagation but incorporates uncertainty as a function of TPW. Our work fills the gap in the operational surface temperature
algorithms and their corresponding uncertainty workflow tailored for Landsat 8 and 9, and machine learning based models for predicting atmospheric water vapor using thermal infrared sensor bands on board Landsat 8 and 9.
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All authors Amirhossein Hassanzadeh, Robert Mancini, Aaron Gerace, Rehman Eon, Matthew Montanaro
Fluid Dynamics
Current effects on wind generated waves near an Ocean Eddy Dipole
Nelson Violante-Carvalho, Thiago de Paula, Leandro Calado et al. (+5 more)
Ocean eddy dipoles are among the most common mesoscale features and may be ubiquitous across the global oceans. However, wave-current interactions in their proximity have not been extensively studied. Here we examine the impact of surface currents on the wave field near an ocean eddy dipole. Using the WW3 wave model, we conducted idealized numerical simulations to assess the influence of different configurations on the spatial variability of Significant Wave Height ($H_s$). Additionally, a two-month hindcast of a strong dipole event in the Southwestern Atlantic Ocean was performed using three distinct surface current products: SSalto/Duacs, HYCOM NCODA and GlobCurrent. Among these, HYCOM, which incorporates ageostrophic effects, provided a more detailed representation of oceanic energy compared to GlobCurrent and SSalto/Duacs, which primarily reflect geostrophic components. The hindcast assessment employed denoised altimeter-derived $H_s$ data, with a spatial resolution of approximately 6~km. The greatest increase in wave energy occurs in the region between the peak values of positive and negative vorticity, where the opposing surface currents reach their maximum intensity. Therefore, dipoles act as converging lenses for surface waves, channeling their refraction towards the central jet. Despite its poorer spatial and temporal resolutions, SSalto-Duacs surface current data provides more reliable $H_s$ fields, in the study region where geostrophic dynamics are expected to be significant or even dominant. HYCOM captures a broader range of dynamical processes, essential for accurately representing the total energy, though discrepancies with SSalto/Duacs data may arise from assimilation inaccuracies and model limitations.
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All authors Nelson Violante-Carvalho, Thiago de Paula, Leandro Calado, Felipe Marques dos Santos, Luiz Mariano Carvalho, Andre Luiz Cordeiro dos Santos, Wilton Z. Arruda, Leandro Farina
Biological Physics · Cross-listed from cond-mat.stat-mech
Dissimilarity measures for generalized Lotka-Volterra systems on networks
Nicolás A. Márquez, Maryam Chaib De Mares and Alejandro P. Riascos
In this paper, we introduce a general framework to quantify dissimilarities between generalized Lotka-Volterra dynamical processes, ranging from classical predator-prey systems to multispecies communities interacting on networks. The proposed measures capture both transient and stationary dynamics, allowing systematic comparisons across systems with varying interaction parameters, network weights, or
topologies. Our analysis shows that even subtle structural changes can lead to markedly distinct outcomes: in two-species systems, interaction strength and initial conditions strongly affect divergence, while in small directed networks, differences that are invisible at the adjacency-
matrix level produce divergent dynamics. In modular networks, the fraction and distribution of negative interactions control the transition from stable to unstable dynamics, with localized perturbations within cliques yielding different global outcomes than distributed ones. Beyond structural variations, the framework also applies when modified processes follow distinct nonlinear equations, demonstrating its versatility. Taken together, these results highlight that dynamical dissimilarity measures provide a powerful tool to analyze robustness, detect structural sensitivity, and predict instabilities in nonlinear systems. More broadly, this approach supports the comparative analysis of biological systems, where complex interaction networks and nonlinear dynamics are central to stability and resilience.
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Physics and Society
Extracting resilience events from utility outage data based on overlapping times and locations
Arslan Ahmad and Ian Dobson
To study power system resilience with real data, it is necessary to group individual power outages recorded by utilities into events in which outages cluster and overlap due to extreme weather. We show how to automatically group utility outage data into resilience events based on their time and location. Each outage is represented as a cylinder in three-dimensional space, with a disk centered at the outage location in the geographic plane and a vertical extent corresponding to a limited outage duration, so that two outages overlap in time and space if their cylinders intersect. The grouping
algorithm can be implemented as a graph whose nodes are the outages and whose edges represent the overlaps of outages in time and space, so that events are the connected components of the graph. Extending time-based grouping to both time and location is particularly useful when extracting events from outage data collected across a wide area, as it prevents unrelated outages from being incorrectly merged into anomalous events solely due to temporal overlap. We propose a metric to tune the parameters of the grouping
algorithm to minimize anomalous events. The grouping of outages into events works with both detailed utility outage data and web-scraped EAGLE-I outage data. Results are validated against NOAA storm event records and DOE-417 reports. The automatically extracted events from utility data closely match documented major weather events.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Attention-Enhanced Convolutional Autoencoder and Structured Delay Embeddings for Weather Prediction
Amirpasha Hedayat and Karthik Duraisamy
Weather prediction is a quintessential problem involving the
forecasting of a complex, nonlinear, and chaotic high-dimensional dynamical system. This work introduces an efficient reduced-order modeling (ROM) framework for short-range weather prediction and investigates fundamental questions in dimensionality reduction and reduced order modeling of such systems. Unlike recent AI-driven models, which require extensive computational resources, our framework prioritizes efficiency while achieving reasonable accuracy. Specifically, a ResNet-based convolutional autoencoder augmented by block
attention modules is developed to reduce the dimensionality of high-dimensional weather data. Subsequently, a linear operator is learned in the time-delayed
embedding of the latent space to efficiently capture the dynamics. Using the ERA5 reanalysis
dataset, we demonstrate that this framework performs well in-distribution as evidenced by effectively predicting weather patterns within training data periods. We also identify important limitations in generalizing to future states, particularly in maintaining prediction accuracy beyond the training window. Our analysis reveals that weather systems exhibit strong temporal correlations that can be effectively captured through linear operations in an appropriately constructed
embedding space, and that projection error rather than inference error is the main bottleneck. These findings shed light on some key challenges in reduced-order modeling of chaotic systems and point toward opportunities for hybrid approaches that combine efficient reduced-order models as baselines with more sophisticated AI architectures, particularly for applications in long-term
climate modeling where computational efficiency is paramount.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci
Distortion-Driven Carrier Decoupling in Doped LiMgPO4
Zhihua Zheng, Xiaolong Yao, Cailian Yu et al. (+3 more)
The interplay between
lattice distortions and charge carriers governs the properties of many functional
oxides. In alkali-doped LiMgPO4, a significant enhancement in dosimetric response is observed, but its microscopic origin is not understood. Using non-adiabatic molecular dynamics, we reveal a fundamental mechanism of carrier decoupling driven by a hierarchy of
lattice distortions. We show that electrons localize into stable small polarons on an ultrafast timescale, trapped by the strong local potential induced by the dopant, while holes form more delocalized polarons that migrate efficiently through a
lattice smoothed by global strain. The stark contrast between the dynamics of trapped electrons and mobile holes explains the suppressed recombination and enhanced energy storage. These results present a clear physical picture of how multiscale
lattice distortions can independently control electron and hole transport, offering new insights into the physics of polarons in complex materials.
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All authors Zhihua Zheng, Xiaolong Yao, Cailian Yu, Menghao Gao, Fangping Ouyang, Shiwu Gao
Physics and Society
Universalities in the Avalanche Dynamics of Novelties and Non-Novelties and some Notes on the Heaps law
Filippo Santoro, Alberto Petri and Francesca Tria
Unprecedented events intertwine with the repetition of the past in natural phenomena and human activities. Key statistical patterns, such as Heaps' and Taylor's laws and Zipf's law, have been identified as characterizing the dynamical processes that govern the emergence of novelties and the abundance of repeated elements. Observing these statistical regularities has been pivotal in motivating the search for modeling schemes that can explain them and clarify key mechanisms underlying the appearance of new elements and their subsequent recurrence. In this study, we analyze sequences of novel and non-novel elements, referred to as avalanches, in real-world systems. We show that avalanche statistics provide a complementary characterization of innovation dynamics, extending beyond the three fundamental laws mentioned above. Although arising from collective dynamics, some systems behave as a single instance of a
stochastic process. Others, such as natural
language, exhibit features that we can only explain by a superposition of different dynamics. This distinction is not apparent when considering Heaps' law alone, while it clearly emerges in the avalanche statistics. By interpreting these empirical observations, we also advance the theoretical understanding of urn-based models that successfully reproduce the observed behaviors associated with Heaps', Zipf's, and Taylor's laws. We derive analytical expressions that accurately describe the probability distributions of avalanches and the Heaps law beyond its asymptotic regime. Building on these results, we derive a scaling relation that we show also holds in real-world systems, indicating a form of universality in the dynamics of novelty.
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Geophysics
Exploring Ultra Rapid Data Assimilation Based on Ensemble Transform Kalman Filter with the Lorenz 96 Model
Fumitoshi Kawasaki, Atsushi Okazaki, Kenta Kurosawa et al. (+1 more)
Ultra-rapid data assimilation (URDA) is a method that rapidly updates preemptive forecasts derived from observations without integrating a dynamical model each time additional observations become available. Due to its computational efficiency, we anticipate that URDA will be beneficial for application to numerical weather prediction (NWP); however, the properties of URDA in nonlinear models and its applicability to NWP have not been sufficiently elucidated. Therefore, this study investigates the analytical properties of URDA in nonlinear models and explores inflation and localization that effectively enhance its performance, both of which are generally essential for NWP. We first analytically demonstrate that preemptive forecasts obtained by URDA in nonlinear models are approximately equivalent, under the tangent linear approximation, to forecasts integrated from the analysis. Furthermore, we conduct numerical experiments using the 40-variable Lorenz 96 model. The results show that multiplicative inflation that deliberately deflates (i.e., using an inflation factor less than 1) the forecast ensemble perturbations used to compute the ensemble transform
matrix of URDA improves forecast accuracy and inflates ensemble spread moderately. This is presumably attributable to the fact that deflating the forecast ensemble perturbations brings the ensemble transform
matrix closer to the identity
matrix and reduces the increment of the ensemble mean. With regard to localization, we show that, although R-localization is crucial, advective localization that accounts for the advection of the influence of observations is more effective.
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All authors Fumitoshi Kawasaki, Atsushi Okazaki, Kenta Kurosawa, Shunji Kotsuki
Computational Physics · Cross-listed from quant-ph
Quantum Orthogonal Separable Physics-Informed Neural Networks
Pietro Zanotta, Ljubomir Budinski, Caglar Aytekin et al. (+1 more)
We introduce
Quantum Orthogonal Separable Physics-Informed Neural Networks (QO-SPINNs), which replace selected dense hidden transformations in physics-informed PDE models with
quantum-compatible orthogonal maps. A pyramidal reconfigurable-beamsplitter
circuit realizes these maps with $\Theta(d)$
circuit depth. Under the stated signed-readout access model and fixed per-call failure probability, a width-$d$ map has sequential access-cost upper bound $\mathcal O(d\log d/\epsilon^2)$, which is asymptotically smaller than the $\Theta(d^2)$ cost of conventional direct dense multiplication when $\epsilon(d)^{-2}\log d=o(d)$. Because unary state preparation discards magnitude, we retain each hidden-state norm classically and restore it after readout, yielding the exact map $Wh$ under ideal readout. We study this construction in two complementary settings: forward PDE regression and a norm-controlled residual model for representation geometry and uncertainty quantification. In the norm-controlled model, structural orthogonality yields explicit bi-Lipschitz bounds, while finite-readout analysis relates sufficient reconstruction precision to a prescribed physical-coordinate resolution through trained-model constants. This makes the access-cost condition assessable for trained checkpoints, although favorable fixed-resolution scaling across widths is not established. A post-hoc
Bayesian-linear covariance provides uncertainty from the same frozen predictor, and cross-PDE transfer shows that strong distance-awareness can persist even when absolute coverage calibration fails. All
Quantum Orthogonal (QO) layers are evaluated by classical simulation: the results therefore characterize a
quantum-compatible structured neural primitive rather than demonstrating a practical
quantum-hardware advantage.
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All authors Pietro Zanotta, Ljubomir Budinski, Caglar Aytekin, Valtteri Lahtinen
Fluid Dynamics
A carrier-wave factored one-way Navier–Stokes method for boundary-layer instability modelling
E. J. Badcock and S. Mughal
We present M-OWNS, a spatial marching method that combines the carrier-wave factoring of the parabolised stability equations (PSE) with a recursive one-way Navier–Stokes (OWNS-R) projection framework. A distinct numerical resolution and efficiency advantage is offered by the approach, in modelling disturbance and instability state
evolution. A spectral resolution comparison analysis shows that to leading order, for any excited eigenfunction whose
eigenvalue lies closer to the carrier wavenumber than to the origin, the wave-factored system resolves the mode at a coarser streamwise numerical step size relative to the unfactored system. A non-iterating variant, with the carrier wavenumber determined from the base flow, temporal frequency and spanwise wavenumber alone, achieves equivalent resolution accuracy at identical per-step cost to unfactored OWNS. For the fixed-carrier variant, M-OWNS reduces the total solve count by factors of two to eight relative to unfactored OWNS across the test cases considered, with larger reductions possible when the iterated closure condition of PSE is suitable. The method is validated across incompressible and subsonic flat-plate boundary-layers, three-dimensional crossflow disturbances, and a Mach~4.5 hypersonic boundary-layer with four forcing configurations: eigenfunction inlet forcing, wall suction/blowing, multi-mode freestream forcing and randomised inlet forcing. The wall suction/blowing case is validated against a fully
elliptic linear harmonic Navier–Stokes solver. For deterministic forcing scenarios, M-OWNS captures disturbance amplitudes, acoustic radiation fields, and modal synchronisation sequences at coarser streamwise resolution than unfactored OWNS. Under broadband randomised forcing, M-OWNS resolves mixed-mode disturbance development at half the numerical cost relative to standard OWNS.
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Applied Physics · Cross-listed from cond-mat.mes-hall
Electron Tunneling Enhances Thermal Conductance through Metal-Insulator-Semiconductor Junctions
Yizhe Liu and Bo Sun
The presence of interfaces in
semiconductor devices substantially hinders thermal transport, contributing disproportionately to the overall thermal resistance. However, approaches to enhance interfacial thermal transport remain scarce without changing the interface structure, as the intrinsic electron and
phonon properties of constituent materials set an upper limit. Here, we find a new thermal transport pathway, electronic heat tunneling, to enhance interfacial thermal conductance through metal-
insulator-
semiconductor junctions. By applying photoexcitation or bias voltage, we observe remarkable thermal conductance increases in operando, opening a new channel for efficient interfacial heat dissipation. The electron
quantum tunneling pathway is parallel to conventional
phonon-mediated interfacial thermal transport, and violates the Wiedemann-Franz law since this pathway deviates from the paradigm of diffusive transport. Moreover, we develop a tunneling mismatch model to describe the enhanced thermal conductance, originating from tunneling heat flux. Our Letter demonstrates a previously unexplored heat transport mechanism to enhance thermal conductance, bypassing the need for interface engineering. These findings emphasize the essential need to understand
semiconductor thermal properties under realistic operating conditions.
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Fluid Dynamics
Re-examining the boundary conditions in modelling SAW-driven acoustofluidic streaming
Qinran Wei, Suyu Ding, Yang Zhao et al. (+4 more)
Numerical simulations of surface acoustic wave (SAW)-induced acoustic streaming are highly sensitive to the choice of second-order boundary conditions. This study systematically compares the no-slip (NS) and Stokes slip (SD) boundary conditions through different numerical approaches. Two- and three-dimensional simulations based on the Reynolds stress method are performed for standing SAW and travelling SAW devices. Results are validated against particle image velocimetry measurements of streaming patterns and velocities. We show that the SD condition yields Lagrangian velocity fields in significantly better agreement with experiments than the NS condition, accurately capturing
vortex number, rotation direction, and amplitude across varying device geometries and operating conditions. In contrast, the NS condition overpredicts velocities by 1-2 orders of magnitude and often fails to reproduce experimentally observed
vortex structures. These findings highlight the essential role of the Stokes drift boundary condition in modelling acoustic streaming and provide clear guidance for its use in future simulations of SAW-based acoustofluidic systems.
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All authors Qinran Wei, Suyu Ding, Yang Zhao, Yuanpeng Ma, Dachuan Sang, Dong Zhang, Xiasheng Guo
Instrumentation and Detectors
From the Virgo interferometer calibration to the bias and uncertainty of the h(t) detector strain during the O4 run
Cervane Grimaud, Florian Aubin, Benoît Mours et al. (+6 more)
Since the first gravitational wave detection in 2015, ground-based interferometer sensitivities have significantly improved, requiring highly precise calibration to ensure accurate reconstruction of the h(t) strain signal. In this talk we will outline the Virgo interferometer calibration steps performed in preparation of the O4b run started in April 2024. We will first describe the
Photon Calibrator power devices intercalibration allowing for a 0.48% precision on mirror displacement. Before explaining how the
Photon Calibrator is used to calibrate every Virgo mirror actuators. We will also discuss the monitoring of the h(t) strain reconstruction during the run showing that, on the 10 Hz to 2 kHz band, the reconstructed strain achieves a precision of 2% in modulus and 30 mrad in phase. Special emphasis will be given on the newly developed frequency-dependent bias and uncertainty computation method and the resulting online unbiasing of the h(t) strain.
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All authors Cervane Grimaud, Florian Aubin, Benoît Mours, Thierry Pradier, Loïc Rolland, Monica Seglar-Arroyo, Hans Van Haevermaet, Pierre Van Hove, Didier Verkindt