Computational Physics
CVT Archives and Chemical Embedding Measures for Multi-Objective Quality Diversity in Molecular Design
Dominic Mashak and Jacob Schrum
Nonlinear optical (NLO) materials are essential for photonic technologies, yet discovering optimal NLO molecules requires balancing multiple competing objectives across vast chemical spaces. Previous work showed that Multi-Objective MAP-Elites (MOME) with grid-based archives discovers diverse, high-quality molecules for electro-optic applications. However, uniform grid partitioning wastes archive capacity on chemically infeasible regions while undersampling high-density areas. We apply MOME with Centroidal Voronoi Tessellation (CVT) archives whose
cells are defined by learned
embeddings from ChemBERTa-2 Multi-Task Regression reduced via UMAP, capturing chemical similarity beyond simple structural features. We investigate a four-objective NLO molecular design problem: maximizing the $\beta / \gamma$ hyperpolarizability ratio, constraining HOMO-LUMO gap and linear polarizability to target ranges, and minimizing energy per atom. Our results demonstrate that
embedding-based measures in CVT archives yield significantly higher median global hypervolume and multi-objective quality diversity scores, while filling nearly all native archive niches.
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Geophysics
Simulating Subterranean Fluid Injection through Iteration on the VirtualQuake Model
Spence Norwood and John Rundle
This work extends the VirtualQuake earthquake simulation framework to incorporate the effects of fluid injection on fault stability and induced seismicity. Reworking VirtualQuake into a system using stress point sources, instead of rectangular segments, the new model offers increased
geometric flexibility, greater stability, and the re-addition of cross-fault interactions. This approach is paired with the addition of fluid injection modeling, through the distribution of inflationary stress sources, according to invasion percolation, simulating both the stress effect of the injection on nearby faults, and deformation from the injection itself. The model captures both immediate and long-term impacts of injection cycles, including hydraulic fracturing processes and post-injection pressure dissipation. Results show that while single injections produce limited stress changes, repeated injections generate persistent high-pressure regions that progressively destabilize nearby faults, increasing the likelihood of seismic events. This model
evolution offers a tool for the evaluation and characterization of long term risks from commercial injection.
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Fluid Dynamics
Aggregation Effects on Heat Transfer in Viscoplastic Nanofluid Entrance Flows
Deepa Madivalar, Vishwanath Kadaba Puttanna and A Kandasamy
This study numerically investigates heat transfer enhancement in laminar, incompressible viscoplastic nanofluid flow through the entrance region of a circular cylinder with a uniformly heated wall, including the effects of both, non-aggregation and aggregation of nanoparticles. Nanofluid properties are modeled using Brinkman and Maxwell models in the case of non-aggregation, and Krieger-Dougherty, Maxwell-Bruggeman models in the case of aggregation, while the viscoplastic behavior is described by the Bingham-Papanastasiou model. The governing boundary layer equations are solved using a finite-difference method. The effects of yield stress and nanoparticle volume fraction (up to 5%) on friction, pressure drop, and Nusselt number are analyzed, and performance evaluation criteria are evaluated to identify the optimal volume fraction for maximum efficiency.
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Classical Physics · Cross-listed from cond-mat.soft
Taylor dispersion in a soft tube
Aditya Jha, Masoodah Gunny, Joshua D Mcgraw et al. (+2 more)
Diffusion of a solute along a tube is enhanced by hydrodynamic flow, a phenomenon known as Taylor dispersion. In microfluidic applications, the compliance of the tube boundaries modifies the hydrodynamic flow and thus solutal transport. Here, we develop the theory of solutal dispersion in a soft, axisymmetric tube where the tube walls respond to the hydrodynamic pressure through a Winkler response. By deriving the modified macro-transport equation for the solutal concentration dynamics based on multiple-time-scale analysis, we explore the influence of softness on solutal transport for steady and pulsatile configurations. Our main finding is that softness enhances the effective advection velocity and dispersion coefficient, which might have practical implication in biology and microfluidic technology.
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All authors Aditya Jha, Masoodah Gunny, Joshua D Mcgraw, Yacine Amarouchene, Thomas Salez
Fluid Dynamics
Haematocrit and Shear Rate Modulate Local Cell-free Layer Thickness and Platelet Margination in Blood Flow Along a Sinusoidal Wall
Eleonora Pero, Giovanna Tomaiuolo, Stefano Guido et al. (+2 more)
The geometry of blood vessels strongly affects hemostasis and thrombosis through red blood
cell (RBC) dynamics and platelet margination. Growing platelet aggregates, in turn, reshape the local vessel wall topography, leading to a strongly coupled system. However, it is not well understood how surface heterogeneities alter local hemodynamics and platelet margination, thereby driving further aggregate growth. This study investigates how hematocrit (Ht) and shear rate affect RBC dynamics,
cell-free layer (CFL) thickness, and platelet margination near a sinusoidal wall. The sinusoidal wall, with crests and valleys aligned with the flow direction, serves as a model of the flow-aligned platelet aggregates observed in microfluidic experiments [Pero et al., CRPS, 2024]. We perform three-dimensional immersed-boundary-
lattice-Boltzmann simulations of particulate blood flow with deformable RBCs and nearly rigid spherical platelets. Our results show that platelet margination is primarily governed by Ht and is more pronounced in regions where the CFL thickness is similar to the platelet size. At low Ht, platelets preferentially accumulate at crests, promoting high-amplitude aggregate growth. Increasing Ht leads to a more uniform platelet distribution along the surface, consistent with experimental observations. The sinusoidal geometry generates a pronounced crest-valley wall shear rate gradient, suggesting that distinct shear-dependent adhesion pathways may dominate at different surface locations. Our findings provide mechanistic insights into the morphological
evolution of platelet aggregates and may ultimately inform targeted therapeutic strategies for thrombosis based on shear-sensitive drug-delivery.
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All authors Eleonora Pero, Giovanna Tomaiuolo, Stefano Guido, Claire Denham, Timm Krueger
Plasma Physics
Development of a 3D-CNN-based Prediction Model for Migration Barriers in Plasma-Wall Interactions
Seiki Saito, Keisuke Takeuchi, Hiroaki Nakamura et al. (+5 more)
Understanding the long-term transport of hydrogen isotopes in
plasma-facing materials, such as tungsten, is critical for the steady-state operation of
magnetic confinement fusion reactors. However, dynamically updating the transition parameters for kinetic Monte Carlo (kMC) simulations as the atomic structure evolves under continuous
plasma irradiation remains a severe computational bottleneck. Conventionally, calculating these migration barriers requires the iterative and computationally expensive Nudged Elastic Band (NEB) method. To overcome this limitation, this article presents a highly efficient surrogate model for predicting migration barriers using a three-dimensional Convolutional Neural Network (3D-CNN), establishing the final component necessary to realize on-the-fly molecular dynamics (MD) and kMC hybrid simulations. The proposed deep learning model takes a two-channel volumetric input, the local three-dimensional potential energy distribution and the voxelized spatial coordinates of the initial and final trapping sites, to directly output the migration barrier as a scalar value. Trained on a comprehensive
dataset of tungsten-hydrogen configurations evaluated using the Embedded Atom Method (EAM) potential, the model demonstrated robust predictive accuracy, achieving a Mean Absolute Error (MAE) of 0.124 eV and a high coefficient of determination of 0.890. Furthermore, utilizing GPU acceleration, the inference time is reduced to approximately 2.7 milliseconds per barrier, achieving a speed-up ratio of over 23,000 compared to conventional NEB calculations. This extraordinary acceleration effectively resolves the computational barrier of transition rate evaluations, paving the way for large-scale, dynamic modeling of
plasma-wall interactions.
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All authors Seiki Saito, Keisuke Takeuchi, Hiroaki Nakamura, Yasuhiro Oda, Kazuo Hoshino, Yuki Homma, Shohei Yamoto, Yuki Uchida
Plasma Physics
Evolution of SPI-induced disruptions in ASDEX Upgrade
P. Heinrich, G. Papp, S. Jachmich et al. (+23 more)
Disruptions are a major concern for future fusion reactors based on the tokamak principle. To ensure machine protection, the thermal loads and vessel forces that arise during disruptions have to be mitigated reliably. For the ITER disruption mitigation system (DMS), the shattered pellet injection (SPI) technology has been selected. It can provide a
prompt delivery of the injection material into the
plasma core, with the mitigation efficiency depending on fragment size and velocity. A highly flexible SPI system was built and installed at the tokamak ASDEX Upgrade (AUG) to aid the finalization process of the ITER DMS and provide crucial input for modeling. The SPI-induced disruptions in the 2022 AUG experiments follow a typical chain of events, which are discussed in this paper: The first light, main fragment arrival,
plasma movement event, MARFE, thermal quench/
plasma current spike, current quench, and vertical displacement event phase. Depending on the injection parameters, these phases may vary significantly or some might not be present at all. In this paper, we will focus on the characterization of these disruption phases and figures of merit for the mitigation efficiency, depending on the SPI configuration. With increasing amount of assimilated neon in the
plasma - primarily influenced by the neon content in the pellet but also the shattering parameters - the disruptions exhibit different behaviors. This disruption
evolution seems to be a continuous process, with the most prominent feature being the changing disruption time scales and
plasma current time trace shape during the CQ from convex (poorly or unmitigated) $\rightarrow$ concave (well mitigated/radiation dominated). Depending on the injection, pre-TQ durations between 15 - 0.5 ms and early CQ durations ($\Delta \textrm{t}_\textrm{CQ}^{100 \rightarrow 80}$) between 13.3 - 8.2 ms had been achieved at AUG.
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All authors P. Heinrich, G. Papp, S. Jachmich, J. Artola, M. Bernert, P. de Marné, M. Dibon, R. Dux, T. Eberl, O. Ficker, P. Halldestam, J. Hobirk, M. Hoelzl, F. Klossek, M. Lehnen, T. Lunt, M. Maraschek, A. Patel, T. Peherstorfer, N. Schwarz, U. Sheikh, B. Sieglin, J. Svoboda, W. Tang, the ASDEX Upgrade Team, the EUROfusion Tokamak Exploitation Team
Fluid Dynamics · Cross-listed from cond-mat.stat-mech
Quantitative analysis of fluctuating hydrodynamics in uniform shear flow
Hiroyoshi Nakano and Yuki Minami
Many theoretical predictions in fluctuating hydrodynamics under uniform shear flow have lacked precise quantitative verification because assessing the impact of analytical approximations is difficult and microscopic particle-based simulations have inherent limitations. To address this problem, we perform direct numerical simulations of the fluctuating Navier-Stokes equations with shear-periodic boundary conditions. We provide a decisive validation of two seminal frameworks: the Lutsko-Dufty theory for nonequilibrium long-range correlations, and the dynamic renormalization group (RG) theory pioneered by Forster, Nelson, and Stephen for anomalous transport. First, we demonstrate that the predictions of the Lutsko-Dufty theory are quantitatively valid from the viscous-dominated, short-wavelength regime to the shear-dominated, long-wavelength regime. Second, we test the quantitative predictive capability of the dynamic RG approach and show that the one-loop RG prediction is accurate even when the renormalization correction is comparable to the bare viscosity, a regime in which conventional perturbation theory fails. Our findings solidify the foundations of these classical theories, paving the way for quantitative analyses using fluctuating hydrodynamics.
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Optics · Cross-listed from quant-ph
Non-Markovian exceptional points in waveguide quantum electrodynamics
Stefano Longhi
Spontaneous emission of a
quantum emitter, such as an excited atom, is a fundamental process in
quantum electrodynamics (QED), typically associated with exponential decay to the ground state accompanied by irreversible
photon emission. This simple Markovian picture, however, is profoundly modified in the presence of time-delayed feedback, structured continua, or cooperative emission, as occurs when an emitter radiates in front of a mirror, when several emitters radiate collectively, or in the case of a
giant atom. In such regimes, strong non-Markovian dynamics arise from
photon reabsorption and interference effects, leading to pronounced deviations from exponential decay. Here we demonstrate the emergence of exceptional points (EPs) in these highly non-Markovian waveguide-QED environments, i.e., non-Markovian EPs. These EPs appear directly in the relaxation dynamics as sharp transitions to oscillatory behavior, manifested by the appearance of real zeros in the excited-state amplitude. We analyze in detail the spontaneous emission of
giant atoms with two or more coupling points, highlighting the mechanisms leading to non-Markovian EPs, and show that similar phenomena arise in other waveguide-QED settings, such as the collective spontaneous emission of spatially separated point-like emitters. Our results reveal waveguide-QED systems as experimentally accessible platforms for realizing and exploring non-Markovian EP physics.
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Optics · Cross-listed from cond-mat.str-el
Novel Light-Induced States in Triangular Metallic Magnet
Yao Wang
Novel nonequilibrium states of magnet induced by light attract considerable
attention both in nature of physics and apply. In this work, we systematically explore the electronic and
magnetic states of a double-exchange model on a triangular
lattice under the irradiation of circularly polarized continuous wave field, by means of molecular dynamics calculation. Several exotic nonequilibrium
magnetic states are discovered, including a
vortex state, long-range
magnetic orders at the $\Gamma$ and $\textbf{K}/2$, as well as quasi(dynamical)-long-range
magnetic order at the $\textbf{K}$ and $\textbf{M}$, respectively. Correspondingly, the
evolution of electron bands and fillings are also uncovered. These results offer a promising candidate approach for the optical control of exotic
magnetic and electronic states.
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Optics
Mode Conversion of Gaussian Beams at Dielectric Interfaces
Eli Meril
We investigate mode conversion of $\mathrm{TEM}_{00}$ Gaussian beams upon transmission through planar dielectric interfaces. We show that the angle-dependent Fresnel coefficients act as a spatial filter, inevitably generating higher-order spatial modes. Using a vector angular spectrum formulation and numerical simulations, we reveal that this polarization-dependent filtering induces a coupling from $\mathrm{TEM}_{00}$ into higher-order Laguerre-Gaussian modes, yielding a quadrupolar field pattern. We quantify the associated amplitude and phase deviations, showing that the mode fidelity decreases significantly as the beam waist approaches the diffraction limit.
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Physics and Society
Scale-free congestion clusters in large-scale traffic networks: a continuum modeling study
Yuki Chiba, Norikazu Saito, Yuki Ueda et al. (+1 more)
Recent empirical studies have reported that spatiotemporal congestion clusters in urban traffic exhibit scale-free statistics, with cluster size following a power-law distribution. In this study, we address whether macroscopic continuum descriptions of traffic flow are capable of generating such scale-free spatiotemporal congestion patterns. To this end, we analyze the second-order Aw-Rascle-Zhang model on directed networks under junction coupling. The governing equations are solved by a high-order discontinuous Galerkin scheme, and junction fluxes are determined by an optimization-based coupling procedure enforcing conservation and admissibility at intersections. Congestion is defined by thresholding the road-averaged density, and spatiotemporal clusters are extracted as connected components in space and time. Numerical experiments on
lattice networks of varying sizes reveal that the cluster size follows a robust power-law distribution. Moreover, when rescaled by the linear system size inherent to the two-dimensional network geometry, the distribution collapses onto an approximately universal curve, indicating finite-size scaling governed by the linear system size. The observed power-law statistics and finite-size scaling are reminiscent of scale-invariant dynamics characteristic of self-organized criticality. These results demonstrate that macroscopic continuum traffic models can reproduce large-scale statistical features observed in real urban congestion dynamics.
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All authors Yuki Chiba, Norikazu Saito, Yuki Ueda, Hiroaki Yoshida
Optics · Cross-listed from quant-ph
Decoherence-Induced Multiphoton Interference
Yifan Du, Jiuyi Zhang, Daniel López Martínez et al. (+3 more)
Decoherence is usually deemed detrimental to
quantum information processing. Its control and minimization require significant costs and operating overheads, constituting a major hurdle to the practical deployment of
quantum technologies. Yet,
quantum mechanics provides for counterintuitive, sometimes surprisingly useful, phenomena and effects associated with decoherence, leading to unusual practical utilities. Here we demonstrate such an example of fundamental interest and practical potential, where
quantum interference is created among multiple
photons through their dissipative coupling to a shared reservoir. On a thin-film lithium niobate chip, we dissipatively link two spontaneous parametric down-converters through a common, highly lossy channel to create phase-sensitive multiphoton states. Our results show that faithful correlations can be established among two, three, and four
photons, and tuned by shifting the relative phase between the driving pumps for the converters. This experiment highlights an under-explored territory in
quantum science and technology, where loss and decoherence serve as resources, rather than adversaries, for
quantum information processing.
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All authors Yifan Du, Jiuyi Zhang, Daniel López Martínez, Santosh Kumar, Misagh Izadi, Yuping Huang
Atomic Physics · Cross-listed from quant-ph
Granularity Noise Limit in Atomic-Ensemble-Based Metrology
Chen-Rong Liu, Chuang Li, Runxia Tao et al. (+4 more)
Conventional noise analysis in atomic-ensemble sensing assumes a continuous-medium approximation, thereby treating the atomic system as a deterministic dielectric. Here, we demonstrate that this assumption breaks down due to the discrete, particulate nature of the ensemble, giving rise to an intrinsic "atomic granularity noise" (AGN) that fundamentally competes with the optical measurement noise (OMN, typically
photon shot noise). By introducing a discrete-atom statistical framework, we derive a unified noise-scaling law governed by a single dimensionless resource ratio, $\mathcal{R} = \bar{N}_{\mathrm{ph}}/\bar{N}_{\mathrm{at}}$ at (the
photon-to-atom flux ratio). This law predicts a continuous crossover from an OMN-limited regime to an AGN-limited regime. Crucially, our results reveal a counter-intuitive constraint for sensor optimization: increasing optical probe power – standard practice to mitigate OMN – can paradoxically degrade sensitivity by driving the system into the AGN-dominated regime. Furthermore, we identify a critical resource threshold, $\mathcal{R}_{\mathrm{crit}}$, beyond which
quantum-enhanced metrology using non-classical light fails to improve sensitivity, as it becomes limited by the AGN.
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All authors Chen-Rong Liu, Chuang Li, Runxia Tao, Yixuan Wang, Mingti Zhou, Xinqing Wang, Ying Dong
Fluid Dynamics
Ultrasound-controlled stream splitting in a microfluidic coflow
D. Ghosh, S. Z. Hoque, T. Sujith et al. (+3 more)
Precise control of multiphase microfluidic flows underpins applications ranging from chemical processing to biomedical diagnostics. We investigate the response of a
liquid–
liquid coflow in a rectangular microchannel to an externally applied standing acoustic field. Acoustic excitation destabilizes an otherwise stable interface, giving rise to a sequence of reversible interfacial regimes: waviness, splitting, relocation, and stream-droplet breakup. Remarkably, a distinct splitting regime emerges, where a continuous stream partially splits into droplets at tunable locations while retaining a thin residual stream. Unlike conventional droplet breakup, this regime avoids complete disruption of the main flow, enables droplet generation at high capillary numbers, and allows spatial control over droplet formation. Extending across a broad range of capillary numbers, we examine how variations in flow conditions and applied acoustic power influence these regimes. Combining experiments, numerical simulations, and theoretical scaling, we elucidate the mechanisms governing this droplet generation mode and the associated regime transitions. Systematic measurements show that droplet size and residual stream thickness are governed primarily by hydrodynamic parameters, whereas the acoustic field controls the onset and spatial location of the breakup. These results establish a simple avenue for stream splitting and drop generation on-demand in a microfluidic coflow, opening new possibilities for spatially programmable manipulation of multiphase flows.
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All authors D. Ghosh, S. Z. Hoque, T. Sujith, N. S. Satpathi, L. Malik, A. K. Sen
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Rationalizing defect formation energies in metals and semiconductors with semilocal density functionals
Jorge Vega Bazantes, Timo Lebeda, Akilan Ramasamy et al. (+4 more)
The study of defects in materials is of utmost importance for technological applications and the design of new materials. In this work, we analyze the performance of density functional approximations on two prototypical sets of defective systems: monovacancies in eight fcc metals, and interstitials in the
semiconductor Si-diamond. Specifically, we compute defect formation energies using the local density approximation, the Perdew-Burke-Ernzerhof generalized gradient approximation, the meta-generalized gradient approximations (meta-GGAs) strongly constrained and appropriately normed (SCAN), its regularized version (r2SCAN), the Lebeda-Aschebrock-Kummel (LAK) meta-GGA, and the Heyd-Scuseria-Ernzerhof screened hybrid functional. For metals, the local density approximation shows better performance compared to the other approximations, whereas for silicon, the meta-generalized gradient approximation Lebeda-Aschebrock-Kummel yields outstand- ing accuracy, surpassing the hybrid functional and approaching the results of more computationally demanding
Quantum Monte Carlo methods. To rationalize the different performances, we study the semilocal ingredients rs, s and {\alpha} in both the pristine and defective structures. We identify critical regions that indicate the observed trends of the defect formation energies and pave the way for improving density functional approximations.
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All authors Jorge Vega Bazantes, Timo Lebeda, Akilan Ramasamy, Kanun Pokharel, Ruiqi Zhang, John Perdew, Jianwei Sun
Atmospheric and Oceanic Physics
Near real-time monitoring of global land-ocean cover dynamics
Lixing Wang, Tao Li, Xinyu Dou et al. (+1 more)
Monitoring the dynamics of global land-ocean cover is fundamental for regulating the Earth's
climate and sustaining terrestrial and marine ecosystems. However, existing
datasets and research often exhibit limitations in temporal resolution and timeliness, lack coupled analysis of land cover and sea ice dynamics, and fail to incorporate the perspective of Earth system safety thresholds. Here, we developed an integrated monitoring framework by fusing multi-source remote sensing and reanalysis data, generating a 5-day resolution time series (2018-2025) of global land cover and sea ice coverage with near-real-time update capability. Our analysis reveals distinct latitudinal and regional patterns, with forests dominating (27.0% of global land area) tropical and subtropical regions. At the national scale, land cover composition and seasonal rhythms vary significantly, with countries like China, India, and the US exhibiting divergent patterns such as bimodal cropland fluctuations and alternating snow/ice dominance. Temporally, vegetated cover types exhibit seasonal cycles peaking during Northern Hemisphere summer, and a pronounced anti-phase seasonal pattern is observed between Arctic and Antarctic sea ice coverage. Crucially, safety threshold analysis indicates the global forest cover indicator (~60%) is approaching the 54% lower safe limit, with a declining trend in recent years. Concurrently, Arctic sea ice coverage in September occasionally drops to 23%, below its critical upper limit of 27.6%. Temperature presents a significant negative correlation with sea ice cover (R = -0.78, p < 0.001), with asymmetric freezing and melting rates. By quantifying the proximity of key indicators to their safety thresholds, this study provides a robust, integrated framework for early-warning assessment, thereby offering vital scientific support for global
climate adaptation and sustainable policymaking.
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All authors Lixing Wang, Tao Li, Xinyu Dou, Zhu Liu
Chemical Physics · Cross-listed from quant-ph
Molecular Excited States using Quantum Subspace Methods: Accuracy, Resource Reduction, and Error-Mitigated Hardware Implementation of q-sc-EOM
Srivathsan Poyyapakkam Sundar, Prince Frederick Kwao, Alexey Galda et al. (+1 more)
Problems in
quantum chemical simulations, especially achieving accurate excited-state potential energy surfaces, are among the primary applications to achieve
quantum utility. On near-term
quantum hardware, variants of the variational
quantum eigensolver (VQE)
algorithms are the primary choice for chemistry simulation. In this study, a combination of leading ground and excited state
quantum algorithms for general excited states, namely, ADAPT-VQE/LUCJ and q-sc-EOM, are utilized to calculate accurate excited state potential energy surfaces in challenging bond-breaking scenarios and compared with the classical scalable EOM-CCSD method. This work investigates avenues toward
quantum utility in excited-state
quantum chemistry using the q-sc-EOM approach. We assess its accuracy while mitigating major scaling bottlenecks through the Davidson
algorithm and basis rotation grouping, reducing the measurement scaling from O(N$^{12}$) to O(N$^{5}$), and implementing the method on
quantum hardware with various error mitigation strategies to reduce gate and measurement errors in excited states. The hardware implementation of the q-sc-EOM
algorithm, augmented by mitigation of M3 readout error and
symmetry projection, produces reasonably accurate excited-state energies with gate noise identified as the predominant source of error. This paves the way for accurate and scalable, generally applicable
quantum excited-state methods with potential for
quantum utility while identifying critical problems that require advancements.
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All authors Srivathsan Poyyapakkam Sundar, Prince Frederick Kwao, Alexey Galda, Ayush Asthana
Fluid Dynamics
Influence of van der Waals forces on the instability of a liquid film in a tube
Yixiao Mao, Chengxi Zhao, Yixin Zhang et al. (+2 more)
The instability of a
liquid film in a nanotube is significantly influenced by van der Waals forces. A theoretical framework based on the axisymmetric Stokes equations is developed to investigate their effects through linear stability analysis. The model reveals that van der Waals forces markedly enhance perturbation growth, reduce the dominant wavelength, and lower the critical film thickness that distinguishes collapse from non-collapse regimes. Direct numerical simulations of the Navier-Stokes equations both confirm these theoretical predictions and extend the analysis into the nonlinear regime. In this regime, van der Waals forces are found to alter the interfacial morphology and suppress the formation of satellite lobes. Both rupture and collapse follow a universal temporal scaling law with exponent 1/3 and exhibit self-similar behavior near the singularity.
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All authors Yixiao Mao, Chengxi Zhao, Yixin Zhang, Kai Mu, Ting Si
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Historical Foundation and Practical Guideline for Ferroelectric Switching Kinetic Studies
Yi Liang, Pat Kezer and John T. Heron
Electrical measurements of ferroelectric switching kinetics are widely used to probe the dynamics of polarization reversal, yet the influence of the measurement
circuit is often underappreciated. In this paper, we show that the interplay between ferroelectric capacitors and
circuit elements produces distorted, time-dependent voltage waveforms across the device, particularly in the sub-ns regime. We examine how these
circuit contributions affect polarization transients extracted from PUND measurements. The resulting distortions scale with supply voltage, capacitor dimensions, and lumped
circuit elements, but are not accounted for in conventional experimental analyses or analytical model fitting. We then critically assess existing nucleation and growth models and show that neglecting the time-varying voltage profile can lead to unphysical interpretations of switching kinetics, most notably in the extracted growth dimensionality represented by the Avrami exponent. Finally, we outline guidelines for future studies, emphasizing the need for direct voltage monitoring and
circuit-aware de-
embedding, as well as modeling frameworks that incorporate voltage-dependent nucleation and growth rates based on intrinsic material parameters.
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Atomic Physics · Cross-listed from nucl-th
Predictions of charge density distributions for nuclei with $Z \geq 8$
Yun Dong Wang, Tian Shuai Shang, Hui Hui Xie et al. (+3 more)
A deep neural network (DNN) has been developed to accurately predict
nuclear charge density distributions for
nuclei with
proton numbers $Z \geq 8$. By incorporating essential
nuclear structure features, the model achieves a significant improvement in predictive accuracy over conventional methods. The charge density distributions are analyzed using a
Fourier-Bessel (FB) series expansion, and the DNN is trained on a comprehensive
dataset derived from relativistic continuum Hartree-Bogoliubov (RCHB) theory calculations. The model demonstrates exceptional performance, with root-mean-square deviations of 0.0123 fm and 0.0198 fm for charge radii on the training and validation sets, respectively, remarkably surpassing the precision of the original RCHB calculations. Beyond advancing
nuclear physics research, this high-precision model provides critical data for applications in atomic physics,
nuclear astrophysics, and related fields.
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All authors Yun Dong Wang, Tian Shuai Shang, Hui Hui Xie, Peng Xiang Du, Jian Li, Haozhao Liang
Computational Physics · Cross-listed from cs.LG
Jeffreys Flow: Robust Boltzmann Generators for Rare Event Sampling via Parallel Tempering Distillation
Guang Lin, Christian Moya, Di Qi et al. (+1 more)
Sampling physical systems with rough energy landscapes is hindered by rare events and metastable trapping. While Boltzmann generators already offer a solution, their reliance on the reverse Kullback–Leibler divergence frequently induces catastrophic mode collapse, missing specific modes in multi-modal distributions. Here, we introduce the Jeffreys Flow, a robust generative framework that mitigates this failure by distilling empirical sampling data from Parallel Tempering trajectories using the symmetric Jeffreys divergence. This formulation effectively balances local target-seeking precision with global modes coverage. We show that minimizing Jeffreys divergence suppresses mode collapse and structurally corrects inherent inaccuracies via
distillation of the empirical reference data. We demonstrate the framework's scalability and accuracy on highly non-convex multidimensional
benchmarks, including the systematic correction of
stochastic gradient biases in Replica Exchange
Stochastic Gradient Langevin Dynamics and the massive acceleration of exact importance sampling in Path Integral Monte Carlo for
quantum thermal states.
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All authors Guang Lin, Christian Moya, Di Qi, Xuda Ye
Space Physics · Cross-listed from astro-ph.SR
Statistics of blob properties in two types of coronal streamers
Haiyi Li, Zhenghua Huang, Maria S. Madjarska et al. (+4 more)
Previous studies have shown that a streamer blob might originate in the lower corona and thus be affected by activity in that region. While the base of one streamer might differ from that of another, it can be cataloged into two distinct types: active region streamers (ARSs) that have active regions at their base, and quiet equatorial streamers (QESs) that do not have an active region underneath.The difference between the blob properties in ARSs and those in QESs remains unknown. By analyzing the whole-year observations from SOHO/LASCO/C2 in 2018, we carried out a statistical analysis of the properties of propagating blobs in ARSs and QESs. We found that the properties of streamer blobs are very different from one blob to another. The occurrence rate of blobs in ARSs is about twice as high as that in QESs. On average, the ARS blobs have significantly higher initial velocities and slightly higher accelerations, but slightly lower heights of first appearance than the QES blobs. There is a weak positive correlation between the initial velocities and heights of first appearance in the two groups of streamer blobs. The correlation between the accelerations and heights of first appearance in ARS blobs is negative, while that in QES blobs is positive. Our results provide statistical evidence that a higher degree of activity at the coronal base of a streamer can cause more dynamic blobs higher up, and that it affects the structures of the
solar wind originating in the region.
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All authors Haiyi Li, Zhenghua Huang, Maria S. Madjarska, Youqian Qi, Hui Fu, Ming Xiong, Lidong Xia