Computational Physics
Structure-Preserving MHD-Driftkinetic Discretization for Wave-Particle Interactions
Byung Kyu Na, Stefan Possanner and Xin Wang
We present a structure-preserving discretization of the hybrid magnetohydrodynamics (MHD)-driftkinetic system for simulations of low-frequency wave-particle interactions. The model equations are derived from a variational principle, assuring energetically consistent couplings between MHD fluids and driftkinetic particles. The spatial discretization is based on a finite-element-exterior-calculus (FEEC) framework for the MHD and a particle-in-
cell (PIC) method for the driftkinetic. A key feature of the scheme is the inclusion of the non-quadratic particle
magnetic moment energy term in the
Hamiltonian, which is introduced by the guiding-center approximation. The resulting discrete
Hamiltonian structure naturally organizes the dynamics into skew-symmetric subsystems, enabling balanced energy exchange. To handle the non-quadratic energy term, we develop energy-preserving time integrators based on discrete gradient methods. The
algorithm is implemented in the open-source Python package $\texttt{STRUPHY}$. Numerical experiments confirm the energy-conserving property of the scheme and demonstrate the capability to simulate energetic particles (EP) induced excitation of toroidal Alfvén eigenmodes (TAE) without artificial dissipation or mode filtering. This capability highlights the potential of structure-preserving schemes for high-fidelity simulations of hybrid systems.
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Chemical Physics
General framework for quantifying dissipation pathways in open quantum systems. III. Off-diagonal system-bath couplings
Ignacio Gustin, Chang Woo Kim and Ignacio Franco
This paper extends the previously reported theory of dissipation pathways [J. Chem. Phys. 160, 214111 (2024)] to incorporate off-diagonal subsystem-bath coupling, which is often required to model molecular systems where the environment directly influences transitions and couplings between subsystem states. We systematically derive master equations for both population transfer and dissipation into individual bath components, for which we also rigorously prove energy conservation and detailed balance. The approach is based on second-order perturbation theory with respect to the subsystem-bath couplings, whose form is not limited to any specific model. The accuracy of the developed method is tested by applying it to diverse model
Hamiltonians involving linearly coupled harmonic oscillator baths and comparing the outcomes against the hierarchical equations of motion (HEOM) method. Overall, our method accurately quantifies the contributions of specific bath components to the overall dissipation while significantly reducing the computational cost compared to numerically exact methods such as HEOM, thus offering a path to examine how vibronic interactions steer non-adiabatic processes in realistic chemical systems.
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Optics
Self-Image Multiplicity in a Concave Cylindrical Mirror
Thach A. Nguyen, Kaitlyn S. Yasumura, Duy V. Tran et al. (+1 more)
Concave mirrors are fundamental optical elements, yet some easily observed behaviors are rarely addressed in standard textbooks, such as the formation of multiple reflected images. Here we investigate self-imaging – where the observer is also the observed object – using a concave cylindrical mirror. We predict the number of self-images visible from different observation points and classify space into regions by image count. We then test these predictions with an inexpensive stainless-steel concave cylindrical mirror commonly found in teaching labs. This activity links geometrical optics principles to direct observation and provides a ready-to-use classroom demonstration and student exercise.
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All authors Thach A. Nguyen, Kaitlyn S. Yasumura, Duy V. Tran, Trung V. Phan
Atmospheric and Oceanic Physics
Score-based generative emulation of impact-relevant Earth system model outputs
Shahine Bouabid, Andre Nogueira Souza and Raffaele Ferrari
Policy targets evolve faster than the Coupled Model Intercomparison Project cycles, complicating adaptation and mitigation planning that must often contend with outdated projections.
Climate model output emulators address this gap by offering inexpensive surrogates that can rapidly explore alternative futures while staying close to Earth System Model (ESM) behavior. The focus is on emulators designed to provide inputs to impact models. Using monthly ESM fields of near-surface temperature, precipitation, relative humidity, and wind speed, it is shown that deep generative models have the potential to model the joint distribution of variables relevant for impacts. The specific model proposed uses score-based
diffusion on a spherical mesh and runs on a single mid-range graphical processing unit. A thorough suite of diagnostics is introduced to compare emulator outputs with their parent ESMs, including their probability densities, cross-variable correlations, time of emergence, or tail behavior. The emulator performance is evaluated across three distinct ESMs in both pre-industrial and forced regimes. The results show that the emulator produces distributions that closely match the ESM outputs and captures key forced responses. They also reveal important failure cases, notably for variables with a strong regime shift in the seasonal cycle. Although not a perfect match to the ESM, the inaccuracies of the emulator are small relative to the magnitude of internal variability in ESM projections. This suggests that the generative emulators can be useful in supporting impact assessment. Priorities for future development toward daily resolution, finer spatial scales, and bias-aware training are discussed. Code is made available at https://github.com/shahineb/climemu.
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Plasma Physics
Non-local transport in Radiation-Hydrodynamics codes for ICF by efficient coupling to an external Vlasov-Fokker-Planck code
Abetharan Antony, Robert Kingham, Stefan Mijin et al. (+1 more)
Accurately incorporating non-local transport into radiation-hydrodynamics codes, and indeed any fluid system, has long been elusive. To date, a simplified and accurate theory that can be easily integrated has not been available. This limitation affects modeling in inertial confinement fusion and
magnetic confinement fusion systems, among others, where non-local transport is well-known to be present. Here, we present a coupling methodology between a full Vlasov-Fokker-Planck (VFP) electron kinetic code and radiation-hydrodynamics (rad-hydro) codes. The VFP code is used to adjust native electron transport in the rad-hydro code, thus enabling improved transport without the need to integrate a full electron VFP solver into the rad-hydro code. This approach necessitates only occasional invocation of the VFP code, reducing computational intensity compared to following the dynamic
evolution entirely with the VFP code on fluid time scales. We illustrate that the methodology is more accurate than other simplified methods in thermal decay systems relevant to inertial confinement fusion and can replicate standard theoretical results with high accuracy.
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All authors Abetharan Antony, Robert Kingham, Stefan Mijin, Marty Marinak
Physics and Society
The influence of Political trust on the acceptance of Violence
Mario Villagran
The choice of protest tactics in a social movement has often been analyzed based on the demands, participants, and internal characteristics of the movement. However, recent evidence highlights the context or setting in which the demonstration takes place as another key element in the process; Using structural equation modeling, studies have shown a link between high perceptions of injustice in the treatment received by authorities and a greater acceptance of non-normative and/or violent methods of protest. In line with this approach, this article aims to examine the extent to which another form of authority legitimacy – such as political trust – affects the overall justification for the use of violence by both protesters and the police. Using longitudinal data from Chile (2016 – 2019), which captures the collective protests of the “Social Outbreak”, three analytical approaches – fixed effects, cross-lagged, and multilevel models – demonstrate that declining political trust not only weakened public acceptance of police violence but also increased tolerance toward protesters' use of violent tactics. This relationship adds a new dimension to the analysis of violent protests, suggesting that low political trust in many modern states may be a contributing factor to the increasing radicalization of demonstrations in recent years.
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Fluid Dynamics · Cross-listed from cs.LG
FoilDiff: A Hybrid Transformer Backbone for Diffusion-based Modelling of 2D Airfoil Flow Fields
Kenechukwu Ogbuagu, Sepehr Maleki, Giuseppe Bruni et al. (+1 more)
The accurate prediction of flow fields around airfoils is crucial for aerodynamic design and optimisation. Computational Fluid Dynamics (CFD) models are effective but computationally expensive, thus inspiring the development of surrogate models to enable quicker predictions. These surrogate models can be based on deep learning architectures, such as Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), and
Diffusion Models (DMs).
Diffusion models have shown significant promise in predicting complex flow fields. In this work, we propose FoilDiff, a
diffusion-based surrogate model with a hybrid-backbone denoising network. This hybrid design combines the power of convolutional feature extraction and
transformer-based global
attention to generate more adaptable and accurate representations of flow structures. FoilDiff takes advantage of Denoising
Diffusion Implicit Model (DDIM) sampling to optimise the efficiency of the sampling process at no additional cost to model generalisation. We used encoded representations of Reynolds number, angle of attack, and airfoil geometry to define the input space for generalisation across a wide range of aerodynamic conditions. When evaluated against state-of-the-art models, FoilDiff shows significant performance improvements, with mean prediction errors reducing by up to 85% on the same
datasets. The results have demonstrated that FoilDiff can provide both more accurate predictions and better-calibrated predictive uncertainty than existing
diffusion-based models.
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All authors Kenechukwu Ogbuagu, Sepehr Maleki, Giuseppe Bruni, Senthil Krishnababu
Optics
Optical Computing with Spectrally Multiplexed Features in Complex Media
Xue Dong, Kai Lion, Fei Xia et al. (+4 more)
Artificial intelligence (AI) has rapidly evolved into a critical technology; however, electrical hardware struggles to keep pace with the exponential growth of AI models. Free space optical hardware provides alternative approaches for large-scale optical processing, and in-
memory computing, with applications across diverse machine learning tasks. Here, we explore the use of broadband light scattering in free-space optical components, specifically complex media, which generate uncorrelated optical features at each wavelength. By treating individual wavelengths as independent predictors, we demonstrate improved classification accuracy through in-silico majority voting, along with the ability to estimate uncertainty without requiring access to the model's probability outputs. We further demonstrate that linearly combining multiwavelength features, akin to spectral shaping, enables us to tune output features with improved performance on classification tasks, potentially eliminating the need for multiple digital post-processing steps. These findings illustrate the spectral multiplexing or broadband advantage for free-space optical computing.
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All authors Xue Dong, Kai Lion, Fei Xia, YoonSeok Baek, Ziao Wang, Niao He, Sylvain Gigan
Computational Physics · Cross-listed from cond-mat.soft
Mixing of a binary passive particle system using smart active particles
Thomas Jacob, Siddhant Mohapatra, Rajalingam A et al. (+2 more)
Controlled activity of active entities interacting with a passive environment can generate emergent system-level phenomena, positioning such systems as promising platforms for potential downstream applications in targeted drug delivery, adaptive and reconfigurable materials, microfluidic transport and related fields. The present work aims to realise an optimal mixing of two segregated species of passive particles by introducing a small fraction of active particles (2% by composition) with adaptive and intelligent behaviour, directed by a trained Artificial Neural Network-based
agent. While conventional run-and-tumble particles can induce mixing in the system, the smart active particles demonstrate superior performance, achieving faster and more efficient mixing. Interestingly, an optimal mixing strategy doesn't involve a uniform dispersion of active particles in the domain, but rather limiting their motion to an eccentrically placed zone of activity, inducing a global rotational motion of the passive particles about the system centre. A transition in the directionality of the passive particles' motion is observed along the radius towards the centre, likening the active particles' motion to an ellipse-shaped void with a defined surface speed. Situated at the intersection of active matter and machine learning, this work highlights the potential of integrating adaptive learning frameworks into traditional active matter models.
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All authors Thomas Jacob, Siddhant Mohapatra, Rajalingam A, Sam Mathew, Pallab Sinha Mahapatra
Plasma Physics
A Particle-in-Cell Simulation Framework for Thomson Scattering Analysis in Inertial Confinement Fusion
Ziang Zhu, Yifan Liu, Jun Li et al. (+11 more)
In inertial confinement fusion (ICF), Thomson scattering (TS) is a widely used diagnostic technique for probing
plasma conditions. We present a first-principles numerical approach to obtaining scattered light signals of ion acoustic features with high resolution in angle and frequency space using particle-in-
cell simulations under typical ICF conditions. Our method demonstrates good agreement with existing theories for thermal collective TS. In the super-thermal collective regime, the results align with theory when the driven
plasma modes are well-matched in wave vectors to the probe and collecting beams. Moreover, we also find that TS signals can remain significant even under imperfect wave-vector matching-a result that contradicts the conventional expectation that the TS spectrum strictly follows the
plasma density spectrum. We attribute this discrepancy to a beating wave mechanism arising from the interaction between the probe beam and driven
plasma density modulations. Our work thus provides a practical framework for interpreting TS signals from driven ion modes, a common yet complex feature in ICF
plasmas.
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All authors Ziang Zhu, Yifan Liu, Jun Li, Han Wen, Shihui Cao, Yin Shi, Qing Jia, Chaoxin Chen, Yaoyuan Liu, Hang Zhao, Tao Gong, Zhichao Li, Dong Yang, Jian Zheng
Computational Physics · Cross-listed from quant-ph
Filtered Quantum Phase Estimation
Gwonhak Lee, Minhyeok Kang, Jungsoo Hong et al. (+2 more)
Accurate state preparation is a critical bottleneck in many
quantum algorithms, particularly those for ground-state energy estimation. Even in fault-tolerant
quantum computing, preparing a
quantum state with sufficient overlap with the desired eigenstate remains a major challenge. To address this, we develop a unified cost-aware framework for filtered-state preparation that enhances the overlap of a given input state through spectral filtering. The framework covers
polynomial and trigonometric realizations of filters and makes explicit the trade-off among overlap amplification, preparation success probability, and filter-implementation cost. As representative examples, we analyze Gaussian filters and introduce a modified Krylov-subspace-based filter that improves the success-probability/overlap trade-off relevant to filtered state preparation. Within this framework, we study a filtered variant of
quantum phase estimation (FQPE) that mitigates the unfavorable dependence on the initial overlap present in standard QPE. Numerical experiments on
Fermi-Hubbard models show that FQPE reduces the total runtime by more than two orders of magnitude in the high-precision regime, with overlap amplification exceeding a factor of one hundred.
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All authors Gwonhak Lee, Minhyeok Kang, Jungsoo Hong, Stepan Fomichev, Joonsuk Huh
Atomic Physics · Cross-listed from quant-ph
Higher symmetry breaking and non-reciprocity in a driven-dissipative Dicke model
Jacquelyn Ho, Yue-Hui Lu, Tai Xiang et al. (+3 more)
Higher
symmetries in interacting many-body systems often give rise to new phases and unexpected dynamical behavior. Here, we theoretically investigate a variant of the Dicke model with higher-order discrete
symmetry, resulting from complex-valued coupling coefficients between
quantum emitters and a bosonic mode. We propose a driven-dissipative realization of this model focusing on optomechanical response of a driven atom tweezer array comprised of $n$ sub-ensembles and placed within an optical cavity, with the phase of the driving field advancing stepwise between sub-ensembles. Examining stationary points and their dynamical stability, we identify a phase diagram for $n\geq 3$ with three distinctive features: a $\mathbb{Z}_n$ ($\mathbb{Z}_{2n}$)
symmetry-breaking superradiant phase for even (odd) $n$, a normal unbroken-
symmetry phase that is dynamically unstable due to non-reciprocal forces between emitters, and a first-order phase transition separating these phases. This $n$-phase Dicke model may be equivalently realized in a variety of optomechanical or opto-magnonic settings, where it can serve as a testbed for studying high-order
symmetry breaking and non-reciprocal interactions in open systems.
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All authors Jacquelyn Ho, Yue-Hui Lu, Tai Xiang, Tsai-Chen Lee, Zhenjie Yan, Dan M. Stamper-Kurn
Optics
Unleashing HHG Efficiency: The Role of Driving Pulse Duration
Robert Klas, Martin Gebhardt, Jan Rothhardt et al. (+1 more)
High harmonic generation (HHG) is a crucial technology for compact, high-brightness extreme ultraviolet (XUV) and soft X-ray sources, which are key to advancing both fundamental and applied sciences. The availability of advanced driving
lasers, with tunable wavelength, power, and pulse duration, opens new opportunities for optimizing HHG-based sources. While scaling laws for wavelength are well understood, this work focuses on how pulse duration impacts HHG efficiency and introduces a unified framework that links microscopic dynamics to macroscopic performance. We establish a practical scaling law for the single-atom dipole moment under phase-matching conditions, demonstrating a 1/t dependence at 515 nm wavelength. By connecting this microscopic scaling to macroscopic conversion efficiency, we provide clear guidelines for optimizing HHG output across different gases and driving wavelengths. Furthermore, we identify fundamental constraints, including the carrier-envelope-phase (CEP) walk-off, which limits efficiency at longer driver wavelengths and becomes especially significant for very short pulses. All predictions are based on simple, accessible formulas, eliminating the need for complex numerical simulations. Experiments confirm these predictions and highlight when short pulses are advantageous, particularly in scenarios where CEP walk-off and absorption effects are minimized. These findings offer practical principles for designing next-generation HHG sources, capable of Watt-level average power and extended spectral reach, enabling more versatile and powerful HHG-based XUV and soft X-ray sources.
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All authors Robert Klas, Martin Gebhardt, Jan Rothhardt, Jens Limpert
Fluid Dynamics
Stability of surfactant-laden double-layered viscoelastic fluids flowing over an inclined plane
Md. Mouzakkir Hossain, Mohamin B.M. Khan and Youchuang Chao
The linear dynamics and instability mechanisms of double-layered weakly viscoelastic fluid flowing over an inclined plane are analyzed in the presence of insoluble surfactant at both the free surface and interface. The constitutive equation of the non-Newtonian flow field follows the rheological property of Walters' $B^{''}$ model. The Orr-Sommerfeld-type boundary value problem is derived using the classical normal-mode approach and numerically solved within the framework of the Chebyshev spectral collocation method. Numerical analysis detects three distinct types of instabilities: surface, interface, and interface surfactant modes. The viscoelasticity of both the top and bottom layers strengthens the surface wave instability in the longwave region. On the other hand, the behavior of interfacial wave instability depends on both viscosity and density stratification. Stronger top-layer viscoelasticity suppresses interfacial instability, while increased bottom-layer viscoelasticity amplifies it, provided the viscosity ratio $m>1$. However, in the case of $m<1$, top-layer viscoelasticity provides strong interfacial wave stabilization in the longwave region but becomes comparatively weak in the shortwave regime. The viscoelasticity of the bottom layer has a destabilizing/stabilizing effect on the interfacial wave in the longwave/shortwave regions. Meanwhile, top-layer viscoelasticity stabilizes the interfacial surfactant mode. However, this mode can be destabilized in the vicinity of the instability threshold but is effectively stabilized far away from the onset of instability by higher bottom-layer viscoelasticity.
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Optics
Designing Coherent Optical Environment for Dynamic Optical Manipulation with a Simple Control Beam
Xiaoshu Zhao, Xu Yuan, Hongxia Zheng et al. (+2 more)
We propose a framework for designing coherent optical environments that enable versatile and dynamic optical manipulation. In contrast to conventional material-based near-field platforms, our approach employs a structured coherent light field – optimized via a back-propagation-based inverse design
algorithm – as the manipulation environment. This light-based platform allows a simple control beam, such as a single plane wave or a low-numerical-aperture Gaussian beam, to steer micro-objects effectively. By establishing a one-to-one correspondence between control beam parameters (e.g., phase/polarization of a plane wave) and particle trapping positions, our method enables real-time and versatile control of particles. A wide range of two- and three-dimensional trajectories – including circles, squares, tree-like paths, and epicycle-deferent curves – can be achieved solely by modulating the phase of the control beam. This design strategy for the structured-light environments offers a dynamically reconfigurable, all-optical, and contact-free platform for advanced optical manipulation in free space, with promising applications in nanorobotics, biological probing, and beyond.
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All authors Xiaoshu Zhao, Xu Yuan, Hongxia Zheng, Huajin Chen, Zhifang Lin
Chemical Physics
A Universal Deep Learning Force Field for Molecular Dynamic Simulation and Vibrational Spectra Prediction
Shengjiao Ji, Yujin Zhang, Zihan Zou et al. (+4 more)
Accurate and efficient simulation of infrared (IR) and Raman spectra is essential for molecular identification and structural analysis. Traditional
quantum chemistry methods based on the harmonic approximation neglect anharmonicity and
nuclear quantum effects, while ab initio molecular dynamics (AIMD) remains computationally expensive. Here, we integrate our deep equivariant tensor
attention network (DetaNet) with a velocity-Verlet integrator to enable fast and accurate machine learning molecular dynamics (MLMD) simulations for spectral prediction. Trained on the QMe14S
dataset containing energies, forces, dipole moments, and polarizabilities for 186,102 small organic molecules, DetaNet yields a universal and transferable force field with high-order tensor prediction capability. Using time-correlation functions derived from MLMD and ring-
polymer molecular dynamics (RPMD) trajectories, we computed IR and Raman spectra that accurately reproduce anharmonic and
nuclear quantum effects.
Benchmark tests on isolated molecules, including polycyclic aromatic hydrocarbons, demonstrate that the DetaNet-based MD approach achieves near-experimental spectral accuracy with speedups up to three orders of magnitude over AIMD. Furthermore, the framework extends seamlessly to molecular and inorganic
crystals, molecular aggregates, and biological macromolecules such as polypeptides with minimal fine-tuning. In all systems, DetaNet maintains high accuracy while significantly reducing computational cost. Overall, this work establishes a universal machine learning force field and tensor-aware MLMD framework that enable fast, accurate, and broadly applicable dynamic simulations and IR/Raman spectral predictions across diverse molecular and material systems.
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All authors Shengjiao Ji, Yujin Zhang, Zihan Zou, Bin Jiang, Jun Jiang, Yi Luo, Wei Hu
Physics and Society · Cross-listed from q-fin.ST
Panel regression for the GDP of the Central and Eastern European countries using time-varying coefficients
Vygintas Gontis and Lesya Kolinets
The integration of Central and Eastern European (CEE) countries into the European Economic Area serves as a valuable experiment for the regional economic development theory. The long-lasting convergence of these economies with more advanced Western Europe exhibits a few standard features and varying policies implemented. Even the Baltic countries, which started from very similar starting positions, demonstrate their unique trajectories of development. We propose a panel data regression model that allows coefficients to vary over time, offering a method to compare the contributions of several macroeconomic factors to the GDP growth of CEE countries. In particular, we regress the annual change of GDP per capita in PPP terms as a function of achieved GDP, price, trade, investment, and debt levels. Although other authors have extensively investigated selected regressors, the quantitative comparison of their contribution to GDP growth is a new result of the proposed method. Time-varying slope coefficients in this approach describe the external economic environment in which countries implement their own policies. The panel consists of 11 Central and Eastern European countries (Bulgaria, Czechia, Estonia, Croatia, Latvia, Lithuania, Hungary, Poland, Romania, Slovenia, and Slovakia), which have been observed annually from 1995 to 2024. While the main selected factors of this investigation contribute to economic growth, in agreement with previous findings, the role of private debt appears vital in determining growth pace. Our results serve as an argument for the further theoretical and empirical investigation of private debt contribution to economic growth.
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Optics
Quantum Emission in Monolayer WSe2 Transferred onto InP Nanowires
Palwinder Singh, Jasleen Kaur Jagde, Megha Jain et al. (+10 more)
Localized
quantum emitters in transition-metal dichalcogenides (TMDs) have recently emerged as solid-state candidates for on-demand sources of single
photons. Due to the role of strain in the site-selective creation of TMD emitters, their hybrid integration into photonic structures such as cavities and waveguides is possible using pick-and-place methods. Here we investigate
quantum emission from a hybrid structure consisting of a monolayer of WSe2 interfaced with horizontally aligned InP nanowires (NWs). Our experiments reveal multiple narrow and bright emission peaks in the 715-785 nm spectral range and g(2)(0) as low as 0.049, indicating strong antibunching and good single
photon purity. The faceted nature of III-V NWs provides unique opportunities for strain engineering, including the potential for placement of emitters on the top surface for optimal coupling. Our findings pave the way for realizing hybrid
quantum light sources for integrated
quantum photonics that could combine III-V
quantum dots with TMD emitters into a single platform.
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All authors Palwinder Singh, Jasleen Kaur Jagde, Megha Jain, Edith Yeung, David B. Northeast, Simona Moisa, Seid J. Mohammed, Jean Lapointe, Una Rajnis, Annika Kienast, Philip J. Poole, Dan Dalacu, Kimberley C. Hall
Fluid Dynamics
Consistent kinetic modeling of compressible flows with variable Prandtl numbers: Double-distribution quasi-equilibrium approach
R.M. Strässle, S.A. Hosseini and I.V. Karlin
A consistent kinetic modeling and discretization strategy for compressible flows across all Prandtl numbers and specific heat ratios is developed using the quasi-
equilibrium approach within two of the most widely used double-distribution frameworks. The methodology ensures accurate recovery of the Navier-Stokes-
Fourier equations, including all macroscopic moments and dissipation rates, through detailed hydrodynamic limit analysis and careful construction of
equilibrium and quasi-
equilibrium attractors. Discretization is performed using high-order velocity
lattices with a static reference frame in a discrete velocity Boltzmann context to isolate key modeling aspects such as the necessary requirements on expansion and quadrature orders. The proposed models demonstrate high accuracy, numerical stability and Galilean invariance across a wide range of Mach numbers and temperature ratios. Separate tests for strict conservation and measurements of all dissipation rates confirm these insights for all Prandtl numbers and specific heat ratios. Simulations of a thermal Couette flow and a sensitive two-dimensional shock-
vortex interaction excellently reproduce viscous Navier-Stokes-
Fourier-level physics. The proposed models establish an accurate, efficient and scalable framework for kinetic simulations of compressible flows with moderate supersonic speeds and discontinuities at arbitrary Prandtl numbers and specific heat ratios, offering a valuable tool for studying complex problems in fluid dynamics and paving the way for future extensions to the
lattice Boltzmann context, by application of correction terms, as well as high-Mach and hypersonic regimes, employing target-designed reference frames.
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Optics
Diffraction-limited operation of micro-metalenses: fundamental bounds and designed rules for pixel integration
Nicolas Kossowski, Christina Kyrou, Rémi Colom et al. (+5 more)
Metasurfaces provide a compact, flexible, and reliable solution for controlling the wavefront of light. In imaging systems, micro-lens arrays are integrated with pixel
matrices to reduce optical crosstalk, enhance
photon collection efficiency, and improve spatial resolution. However, as the aperture size of the photonic devices decreases, fundamental limitations associated with diffraction emerge. Here, we theoretically analyze and experimentally demonstrate that these constraints also affect the performance of small functionalized apertures, including metasurfaces and metalenses, emphasizing the increasing impact of diffraction at small pixel sizes. Despite their design versatility, our findings reveal the necessity of accounting for fundamental diffraction properties to optimize the performance of miniature optical metasurfaces.
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All authors Nicolas Kossowski, Christina Kyrou, Rémi Colom, Pierre-Marie Coulon, Virginie Brändli, Jean-Luc Reverchon, Samira Khadir, Patrice Genevet
Optics
Broadband-operational orbital angular momentum generation in nonlocal metasurfaces with maximum efficiency approaching 80%
Keren Wang, Kaili Sun, Jing Du et al. (+5 more)
Nonlocal metasurfaces provide a compact route to generating momentum-space optical
vortices but are limited by steep dispersion typically associated with high-quality (Q) factor resonances, resulting in narrowband and inefficient operation. Here, we introduce a reflection-type nonlocal metasurface that hybrid-couples a bound state in the continuum (BIC) with two degeneracy points (DPs). This engineered interaction enables on-demand control of dispersion, radiative Q-factors, and polarization states of guided resonances, yielding quasi-flat dispersion and enhanced scattering strength. Full-wave simulations predict near-unity on-resonance conversion and overall efficiencies above 90%, representing a three- to fourfold efficiency improvement and more than fifteenfold bandwidth expansion over conventional designs. Experiments confirm broadband operation from 1480 to 1600 nm, achieving peak efficiency approaching 80% and orbital angular momentum (OAM) purity up to 91.7% under flat-top illumination, while suppressing edge effects and mitigating positional sensitivity and numerical-aperture (NA) dependence. As a proof of concept, we demonstrate direct conversion of zero-order Bessel beams into OAM Bessel (perfect
vortex) beams with enhanced wavelength tunability, underscoring the versatility of this approach over diverse illumination conditions. This record-high performance establishes a practical and scalable pathway toward broadband, high-efficiency
vortex generation, opening new opportunities across high-dimensional optical communications, advanced imaging, and
quantum photonics.
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All authors Keren Wang, Kaili Sun, Jing Du, Peijuan Dai, Hao Zhou, Lujun Huang, Zhanghua Han, Wei Wang
Biological Physics · Cross-listed from q-bio.NC
Simultaneously Determining Regional Heterogeneity and Connection Directionality from Neural Activity and Symmetric Connection
Jiawen Chang, Zhuda Yang and Changsong Zhou
The spatiotemporal patterns of neural dynamics are jointly shaped by directed structural interactions and heterogeneous intrinsic features of the neural components. Despite well-developed methods for estimating directionality in network connections from network of homogeneous nodes, how local heterogeneity impacts on directionality estimation remains poorly understood. In particular, the role of excitatory-inhibitory interactions in shaping network directionality and how these interactions should be incorporated into reconstruction frameworks remain largely unexplored. Here, we present a novel reconstruction framework that simultaneously estimates effective heterogeneity across network nodes and asymmetric network connections from neural activity and symmetric connection, both are assessible in experimental data, validated using macaque cortical connectivity data and several
circuit models. We found that the estimated local heterogeneity remains consistent across various forms of parameterized local
circuit heterogeneity. Furthermore, we demonstrated and quantified how hidden local inhibitory populations only modify within-region connection strengths, elucidating the functional equivalence between dynamics of excitatory-inhibitory networks and purely observing excitatory networks when estimating effective heterogeneity and asymmetry. Finally, we demonstrated the sampling interval effect in estimating network interactions with respect to the sampling resolution. Together, our results not only provide a unified framework for evaluating relative functional contributions of local heterogeneity and asymmetry to overall system dynamics but also reveal the fundamental limitations and scaling principles in reconstructing neural
circuit connectivity from experimental observations.
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Optics
Binary $ZnSe:Fe^{2+}$ and ternary $ZnMgSe:Fe^{2+}$ optical crystals for mid-IR applications
Sergei V. Naydenov, Oleksii K. Kapustnyk, Igor M. Pritula et al. (+3 more)
In this study, binary $ZnSe:Fe^{2+}$
crystals and ternary $Zn_{1-x}Mg_{x}Se:Fe^{2+}$
crystals $(0 < x < 0.6)$ were grown by the vertical Bridgman method in graphite crucibles under high argon pressure. A comparative characterization of the structural, energetic, and optical parameters of the obtained
crystals was performed. Theoretical explanations of the observed experimental characteristics, including the specific red-shift of the absorption and emission spectra with increasing solid-solution concentration, are provided. These results could be useful for the development of new
laser media based on simple and complex AIIBVI
crystals and for targeted engineering of their optical properties.
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All authors Sergei V. Naydenov, Oleksii K. Kapustnyk, Igor M. Pritula, Dmitro S. Sofronov, Igor S. Terzin, Nazar O. Kovalenko
Biological Physics
Mapping gene expression dynamics to developmental phenotypes with information entropy analysis
Ben Ansbacher, Malachy Guzman, Jordi Garcia-Ojalvo et al. (+1 more)
The development of multicellular organisms entails a deep connection between time-dependent biochemical processes taking place at the subcellular level, and the resulting macroscopic phenotypes that arise in populations of up to trillions of
cells. A statistical mechanics of developmental processes would help to understand how microscopic genotypes map onto macroscopic phenotypes, a general goal across biology. Here we follow this approach, hypothesizing that development should be understood as a thermodynamic transition between non-
equilibrium states. We test this hypothesis in the context of the fruit fly, Drosophila melanogaster, a model organism used widely in genetics and developmental biology for over a century. Applying a variety of information-theoretic measures to public transcriptomics
datasets of whole fly embryos during development, we show that the global temporal dynamics of gene expression can be understood as a process that probabilistically guides embryonic dynamics across macroscopic phenotypic stages. In particular, we demonstrate signatures of irreversibility in the information complexity of transcriptomic dynamics, as measured mainly by the permutation
entropy of indexed ensembles (PI
entropy). Our results show that the dynamics of PI
entropy correlate strongly with developmental stages. Overall, this is a test case in applying information complexity analysis to relate the statistical mechanics of biomarkers to macroscopic developmental dynamics.
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All authors Ben Ansbacher, Malachy Guzman, Jordi Garcia-Ojalvo, Arjendu K Pattanayak
Optics
Brilliant source of 19.2 attosecond soft X-ray pulses below the atomic unit of time
Fernando Ardana-Lamas, Seth L. Cousin, Juliette Lignieres et al. (+1 more)
Electronic correlations occur on attosecond timescales, dictating how chemical bonds form, energy flows, and materials respond to light. Capturing such many-body processes requires light pulses of similar duration. The soft X-ray water window is vital because it encompasses the principle absorption edges of carbon, nitrogen, and oxygen that underpin chemistry, biology, and materials science. However, generating and characterising isolated attosecond pulses that reach into the soft X-ray water window has remained a challenge. We addressed this need and report an isolated attosecond soft X-ray pulse with a duration of 19.2 attoseconds. This pulse reaches into the water window and is shorter than the atomic unit of time (24.2 as). The pulse is supported by a spectrum centred at 243 eV, extending up to 390 eV, and crossing the carbon K-edge with record
photon flux: 4.8x10$^10$
photons per second overall and 4.1x10$^9$
photons per second in a 10% bandwidth at the carbon K-shell edge (284 eV). Such an extremely short soft X-ray pulse combines extreme temporal resolution with a coherent ultrabroadband soft X-ray spectrum, opening new opportunities to study electron dynamics in atoms, molecules, and solids, disentangle many-body interactions in correlated systems, and follow non-adiabatic energy flow in molecular complexes. Our results establish a new
benchmark for table-top attosecond technology and lay the foundation for its widespread application in science and technology.
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All authors Fernando Ardana-Lamas, Seth L. Cousin, Juliette Lignieres, Jens Biegert
Optics · Cross-listed from quant-ph
Non-Markovian protection of states from decay in quasi-PT-symmetric systems
T. T. Sergeev, E. S. Andrianov and A. A. Zyablovsky
We consider a quasi-PT-symmetric system of two resonators, one of which interacts with a finite-size environment. The interaction with the environment leads to energy losses in the resonators, and the finite size of the environment leads to a non-Markovian dynamics of the relaxation process. We demonstrate that non-Markovian processes in the quasi-PT-symmetric system can make the states of the system infinitely living, loss-protected states, even in the absence of gain. There is a critical value of the interaction between the resonator and the environment below which any state of the system is loss-protected. When the interaction magnitude is greater than the critical value, depending on the coupling strength between the resonators, either one or both states are unprotected. We show that the boundaries of regions with different numbers of protected states are determined by the relaxation rates in the quasi-PT-symmetric system, calculated in the Markovian approximation. By changing the coupling strength between the resonators and the interaction magnitude between the resonator and the environment, the system switches between modes with two, one, or no loss-protected states. This makes it possible to realize stable PT-symmetric devices based on purely dissipative systems. The obtained results are applicable to
quantum systems with single excitations, allowing the concept of PT
symmetry to be extended to such systems.
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Applied Physics
Ultralong Octupole Moment Switching Driven by Twin Topological Spin
Shijie Xu, Zhizhong Zhang, Yan Huang et al. (+10 more)
Spintronics has emerged as a revolutionary frontier in the pursuit of faster, more energy-efficient, and technologically advanced electronics.
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All authors Shijie Xu, Zhizhong Zhang, Yan Huang, Tianyi Wang, Bingqian Dai, Yinchang Ma, Mang Yang, Meng Tang, Houyi Cheng, Kang L. Wang, Weisheng Zhao, Yue Zhang, Xixiang Zhang
Instrumentation and Detectors
A borehole muon detector with SiPM-on-tile technology
Miguel Arratia, Jiajun Huang, Sean Preins et al. (+3 more)
We developed a compact and rugged
muon detector designed for deployment in boreholes. The detector uses a SiPM-on-tile approach in which silicon photomultipliers are directly coupled to scintillator tiles, thereby eliminating the need for wavelength-shifting fibers and long scintillator bars. The modular design is based on a 64-channel unit, 140~cm in length and 80~mm in diameter, composed of $5 \times 5$~cm$^{2}$ scintillator tiles coupled to SiPMs, powered and read out using off-the-shelf electronics. The detector has an average
muon detection efficiency above 95% and acceptance over 5$^\circ$–60$^\circ$ in zenith and 0$^\circ$–360$^\circ$ in azimuth. Simulations indicate that reconstruction combining hit positions and energy deposits achieves a zenith resolution of 1.5–4.0$^\circ$ across most of the zenith range. This work demonstrates a compact, rugged, and cost-effective borehole
muon detector based on the SiPM-on-tile approach, offering a new alternative for
muon tomography.
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All authors Miguel Arratia, Jiajun Huang, Sean Preins, Sebastian Ritter, Christian P. Romero, Sebastian Tapia
Atmospheric and Oceanic Physics · Cross-listed from cs.AI
Zephyrus: An Agentic Framework for Weather Science
Sumanth Varambally, Marshall Fisher, Jas Thakker et al. (+14 more)
Foundation models for weather science are pre-trained on vast amounts of structured numerical data and outperform traditional weather
forecasting systems. However, these models lack
language-based
reasoning capabilities, limiting their utility in interactive scientific workflows. Large
language models (LLMs) excel at understanding and generating text but cannot reason about high-dimensional meteorological
datasets. We bridge this gap by building the first agentic framework for weather science. Our framework includes a Python code-based environment for
agents (ZephyrusWorld) to interact with weather data, featuring tools including a WeatherBench 2
dataset indexer, geolocator for geocoding from natural
language, weather
forecasting,
climate simulation capabilities, and a climatology module for querying precomputed climatological statistics (e.g., means, extremes, and
quantiles) across multiple timescales. We design Zephyrus, a multi-turn LLM-based weather
agent that iteratively analyzes weather
datasets, observes results, and refines its approach through conversational feedback loops. We accompany the
agent with a new
benchmark, ZephyrusBench, with a scalable data generation pipeline that constructs diverse question-answer pairs across weather-related tasks, from basic lookups to advanced
forecasting, extreme event detection, and counterfactual
reasoning. Experiments on this
benchmark demonstrate the strong performance of Zephyrus
agents over text-only baselines, outperforming them by up to 44 percentage points in correctness. However, the hard tasks are still difficult even with frontier LLMs, highlighting the challenging nature of our
benchmark and suggesting room for future development. Our codebase and
benchmark are available at https://github.com/Rose-STL-Lab/Zephyrus.
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All authors Sumanth Varambally, Marshall Fisher, Jas Thakker, Yiwei Chen, Zhirui Xia, Yasaman Jafari, Ruijia Niu, Manas Jain, Veeramakali Vignesh Manivannan, Zachary Novack, Luyu Han, Srikar Eranky, Salva Rühling Cachay, Taylor Berg-Kirkpatrick, Duncan Watson-Parris, Yi-An Ma, Rose Yu
Instrumentation and Detectors · Cross-listed from cs.IR
The LCLStream Ecosystem for Multi-Institutional Dataset Exploration
David Rogers, Valerio Mariani, Cong Wang et al. (+7 more)
We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications – AI training, extremely high-rate X-ray time-of-flight analysis,
crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique contribution to the DOE Integrated Research Infrastructure (IRI) landscape. By creating a flexible, API-driven data request service, we address a significant need for high-speed data streaming sources for the X-ray science data analysis community. With the combination of data request API, mutual authentication web security framework, job queue system, high-rate data buffer, and complementary nature to facility infrastructure, the LCLStreamer framework has prototyped and implemented several new paradigms critical for future generation experiments.
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All authors David Rogers, Valerio Mariani, Cong Wang, Ryan Coffee, Wilko Kroeger, Murali Shankar, Hans Thorsten Schwander, Tom Beck, Frédéric Poitevin, Jana Thayer