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Physics Physics

physics Watch Physics

Wednesday 3 December

Optics

Terahertz emission from interdigitated photoconductive antennas based on Ge-on-Si

Dhanashree Chemate, Abhishek Singh, Ruturaj Puranik et al. (+4 more)

An interdigitated photoconductive antenna (i-PCA) for terahertz (THz) emission with a novel metal-insulator-semiconductor interface is designed with the aim of developing compact and scalable THz devices. The photoconductive material is an amorphous germanium (Ge) film deposited using DC magnetron sputtering. The antenna electrodes are composed of gold-germanium (AuGe). With the integration of a silicon dioxide (SiO2) layer that acts as an electrical mask on alternate active areas, we present a simple approach to fabricate a large-area i-PCA. Along with a simplified fabrication compared to other existing designs, our approach increases the electrical robustness of the emitter and reduces the inactive gap area on the device. The i-PCA is capable of THz emission up to 2.5 THz and 36 dB signal-to-noise ratio (SNR), and is promising for applications in CMOS technologies.
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All authors Dhanashree Chemate, Abhishek Singh, Ruturaj Puranik, Utkarsh Pandey, Dipti Gupta, Siddhartha P. Duttagupta, Shriganesh S. Prabhu

Instrumentation and Detectors

Studying the GRAiNITA concept: first test beam results

Sergey Barsuk, Oleg Bezshyyko, Ianina Boiaryntseva et al. (+20 more)

Data collected over a two-day period in June 2024 at the CERN SPS H9 test beam using a small-scale GRAiNITA prototype have been analyzed to characterize the detector's energy resolution performance. The measurements allow for a first estimate of the constant term associated with detector non-uniformity. Although the evaluation is limited by the small prototype size and the use of pion beams, the results indicate that the non-uniformity-related constant term is significantly below 1%. Furthermore, the test-beam data confirm that the contribution to the energy resolution arising from photo-electron statistics is approximately 1%/sqrt(E). These findings validate the expected calorimetric performance of the GRAiNITA concept and provide important input for the design and optimization of future full-scale detectors.
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All authors Sergey Barsuk, Oleg Bezshyyko, Ianina Boiaryntseva, Andrey Boyarintsev, Dominique Breton, Herve Chanal, Alexander M. Dubovik, Larysa Golinka-Bezshyyko, Carlos Dominguez Goncalves, Yingrui Hou, Giulia Hull, Miktat Imre, Denys Klekots, Jacques Lefrancois, Jihane Maalmi, Magali Magne, Bernard Mathon, Stéphane Monteil, Sebastien Olmo, David Picard, Marie-Helene Schune, Irina Tupitsyna, Mykhailo Yeresko

Instrumentation and Detectors · Cross-listed from cond-mat.mtrl-sci

Poly- and single-crystalline diamond nitrogen-induced TLS losses estimation with superconducting lumped elements micro-resonators

Francesco Mazzocchi, Martin Neidig, Hideaki Yamada et al. (+3 more)

Research on diamond has intensified due to its exceptional thermal, optical, and mechanical properties, making it a key material in quantum technologies and high-power applications. Diamonds with engineered nitrogen-vacancy (NV) centers represent a very sensitive platform for quantum sensing, while high-optical quality diamond windows represent a fundamental safety component inside Electron Cyclotron Resonance Heating (ECRH) systems in nuclear fusion reactors. A major challenge is the development of ultra-low-loss, high-optical-quality single-crystal diamond substrates to meet growing demands for quantum coherence and power handling. Traditionally, dielectric losses ($\tan \delta$) in diamonds are evaluated using Fabry-Perot microwave resonators, in which the resonance quality factors Q of the cavity with and without the sample are compared. These devices are limited to resolutions around 10$^{-5}$ by the need to keep the resonator dimensions within a reasonable range. In contrast, superconducting thin-film micro-strip resonators, with Q factors exceeding 10$^6$, are stated to provide higher sensitivity for assessing ultra-low-loss materials. This study examines four diamond samples grown through different processes, analyzing their dielectric losses at extreme low temperatures (sub-Kelvin) within the Two-Level System (TLS) framework. Complementary Raman spectroscopy measurements allowed us not only to associate higher nitrogen content with increased losses, but also to investigate how the different growth process influence the way these defects are incorporated in the crystal lattice.
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All authors Francesco Mazzocchi, Martin Neidig, Hideaki Yamada, Sebastian Kempf, Dirk Strauss, Theo Scherer

Physics and Society

Quantum Simulations of Opinion Dynamics

Xingyu Guo, Xiaoyang Wang and Lingxiao Wang

Consensus formation is a central problem in collective behavior. In this work, we develop quantum models of opinion dynamics that can be exactly solved and implemented on current quantum hardware. By exploiting quantum superposition, measurement-induced state collapse, and entanglement, our framework captures key features of opinion evolution and allows a systematic investigation of how network connectivity shapes consensus formation. We demonstrate our approach using practical quantum circuits and validate representative cases on IBM Quantum devices for the open-chain. These findings pave the way for further exploration into quantum-enhanced social modeling, highlighting the potential of near-term quantum computers for simulating collective behavior in complex systems.
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Physics and Society · Cross-listed from cs.SI

Inaccessibility in Public Transit Networks

Katherine Betz

The study of networks derived from infrastructure systems has received considerable attention, yet the accessibility of such systems, particularly within public transit networks, remains comparatively underexplored. Accessibility encompasses a broad range of considerations, from infrastructure-based features such as elevators and step-free access to spatial factors such as the geographic distribution of accessible stations. In this work, we investigate infrastructure-based accessibility in two major transit systems: the London Underground and the New York City Subway. We construct network models in which nodes represent accessible stations and edges represent adjacency along transit lines. Using tools from network analysis, we examine the structural properties of these accessibility networks, including clustering patterns and the spatial distribution of accessible nodes. We further employ centrality measures to identify stations that serve as major accessible hubs. Finally, we analyze socioeconomic and tourism-related variables to assess the influence of neighborhood wealth and popularity on the prevalence of accessible stations. Our findings highlight significant disparities in accessibility across both systems and demonstrate the utility of mathematical and network-theoretic methods in understanding and improving modern transit infrastructure.
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Fluid Dynamics · Cross-listed from quant-ph

An end-to-end quantum algorithm for nonlinear fluid dynamics with bounded quantum advantage

David Jennings, Kamil Korzekwa, Matteo Lostaglio et al. (+3 more)

Computational fluid dynamics (CFD) is a cornerstone of classical scientific computing, and there is growing interest in whether quantum computers can accelerate such simulations. The existing proposals for fault-tolerant quantum algorithms for CFD have almost exclusively been based on the Carleman embedding method, used to encode nonlinearities on a quantum computer. Here, we first identify several key challenges that must be addressed in order to establish quantum advantage using this method, including Carleman convergence, time-stepping requirements, condition-number scaling, and data extraction. Building on this analysis, we develop a novel algorithm for the incompressible lattice Boltzmann equation that addresses them, and provide its detailed analysis, including all potential sources of algorithmic complexity, as well as gate count estimates. We find that for an end-to-end problem, a modest quantum advantage may be preserved for selected observables in the high-error-tolerance regime. We establish a lower bound for the Reynolds number scaling of our quantum algorithm in dimension $D$ at Kolmogorov microscale resolution with $O(\mathrm{Re}^{\frac{3}{4}(1+\frac{D}{2})} \times q_M)$, where $q_M$ is a multiplicative overhead for data extraction with $q_M = O(\mathrm{Re}^{\frac{3}{8}})$ for the drag force. This upper bounds the scaling improvement over classical algorithms by $O(\mathrm{Re}^{\frac{3D}{8}})$. However, our numerical investigations suggest a lower speedup, with a scaling estimate of $O(\mathrm{Re}^{1.936} \times q_M)$ for $D=2$. Our results give robust evidence that small, but nontrivial, quantum advantages can be achieved in the context of CFD, and motivate the need for additional rigorous end-to-end quantum algorithm development.
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All authors David Jennings, Kamil Korzekwa, Matteo Lostaglio, Richard Ashworth, Emanuele Marsili, Stephen Rolston

Chemical Physics

Real-Time Coupled Electron-Nuclear Dynamics of Chemical Bond Formation: Hydrogen Scattering from a Semiconductor Surface

Jialong Shi, Lingjun Zhu, Florian Nitz et al. (+4 more)

A first-principles coupled electron-nuclear dynamics simulation based on real-time, time-dependent density functional theory and Ehrenfest dynamics quantitatively repro-duces bimodal translational energy loss and angular distributions observed in experiment for hydrogen atom scattering from Ge(111)-c(2*8). The theory elucidates a site-selective mechanism of electronically nonadiabatic energy transfer associated with the formation of different Ge-H bonds. When a hydrogen atom approaches a Ge rest-atom, it is strongly accelerated toward the potential minimum forming a transient Ge-H bond and then re-flected by the repulsive wall. This transient bond formation triggers an ultrafast electron transfer event from the rest-atom to an adjacent Ge-adatom, involving several crossings between valence and conduction bands of the substrate. Electronic equilibration is impos-sible within such a short time (Born-Oppenheimer failure) allowing the H-atom kinetic energy to be converted to inter-band electronic excitation of the substrate. H-atom colli-sions at other Ge atoms also form a transient bond but exhibit no electronic excitation, resulting in distinctly less efficient energy loss in scattered H-atoms. The nucle-ar-to-electronic energy transfer observed in this system reflects the electronic dynamics of covalent bond formation at a semiconductor surface, a mechanism that is quite distinct from previously identified nonadiabatic energy transfer mechanisms at metal surfaces mediated by electronic friction or transient negative ions.
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All authors Jialong Shi, Lingjun Zhu, Florian Nitz, Oliver Bünermann, Alec M. Wodtke, Hua Guo, Bin Jiang

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

Revealing Nanoscale Molecular Organization in Liquid Crystals via Cryogenic Atom Probe Tomography

Kuan Meng, Kang'an Wang, Sebastian Eich et al. (+5 more)

While liquid crystals (LCs) have been extensively studied, obtaining a comprehensive nanoscale picture of their molecular organization remains challenging, as conventional techniques face an intrinsic trade-off between spatial and chemical resolution. Here, cryogenic atom probe tomography (cryo-APT) is introduced as a new analytical approach for LC materials, using 4'-Pentyl-4-cyanobiphenyl (5CB) and 4'-Octyl-4-cyanobiphenyl (8CB) as representative model compounds. This was enabled by a tailored cryogenic focused ion beam (cryo-FIB) protocol optimized for small organic molecules. The method enables controlled field evaporation of both intact molecules and diagnostic fragments, achieving over 90% molecular retention while preserving four characteristic dissociation patterns. By spatially correlating these fragmentation profiles with the local electric field derived from the tip geometry, we reveal field-directed dissociation pathways of CB molecules. In parallel, the distribution of intact molecular ions enables nanoscale visualization of material structure: we resolve homogeneous mixing of 5CB and 8CB in the nematic phase and directly observe the sub-nanometer crystalline layering in a supercooled 8CB sample, with contrast to the surrounding amorphous matrix suggesting the presence of a solid-liquid interface. This work establishes cryo-APT as a new powerful analytical platform for LC research and reveals its broad potential for application in soft matter systems.
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All authors Kuan Meng, Kang'an Wang, Sebastian Eich, Pierre Nacke, Johanna R. Bruckner, Patrick Stender, Frank Giesselmann, Guido Schmitz

Instrumentation and Detectors

Compton suppressed scintillation spectrometer based on a cluster of 9$\times$CeBr$_{3}$-NaI(Tl) phoswich detectors

Mark Povolotskiy, Yuri Sobolev and Sergei Stukalov

Measurements of the characteristics of an Compton suppressed spectrometer consisting of 9$\times$CeBr$_{3}$-NaI(Tl) phoswich detectors surrounded by four CsI(Tl) scintillation detectors intended for suppressing the Compton component of the spectrum have been carried out. Measurements were performed using gamma and neutron radiation sources. Key parameters of the spectrometer have been determined: the suppression factor of the Compton part of the $\gamma$-spectrum, as well as the dependencies of the neutron detection efficiency on their energy at various detection threshold values.
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Optics

Tailoring the morphology of ultrathin bismuth films around percolation for thickness-optimized optical cavities

Fernando Chacon-Sanchez, Johann Toudert and Rosalía Serna

Ultrathin bismuth films (<10 nm) are emerging candidates for advanced applications in photonics. It has been shown that Bi-based subwavelength optical cavities show outstanding features, including broad tuneable resonances for structural color generation and broadband perfect absorption for light harvesting. While current devices are based on continuous Bi films, integrating ultrathin films around the percolation threshold with a tailored morphology promises to enable more compact devices with a wider tunability range and/or enhanced optical response. In this context, we report the tailoring of the morphology and UV-Vis-NIR effective optical dielectric function ( $\varepsilon$= $\varepsilon_1$+i$\varepsilon_2$) of ultrathin Bi films around the percolation threshold. Just below percolation, the films effective optical permittivity $\varepsilon_1$ differs markedly from that of a continuous film, as it turns from negative to positive while its effective optical loss $\varepsilon_2$ is reduced. We showcase the relevance of such dielectric tunability for the design of enhanced subwavelength optical cavities operating in the NIR and visible regions. In particular, we show that discontinuous near-percolation films enable designing optimized cavities for efficient colour generation with a thickness almost 3 times smaller than what was previously achieved for continuous films.
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Computational Physics

Consistent Projection of Langevin Dynamics: Preserving Thermodynamics and Kinetics in Coarse-Grained Models

Vahid Nateghi, Lara Neureither, Selma Moqvist et al. (+3 more)

Coarse graining (CG) is an important task for efficient modeling and simulation of complex multi-scale systems, such as the conformational dynamics of biomolecules. This work presents a projection-based coarse-graining formalism for general underdamped Langevin dynamics. Following the Zwanzig projection approach, we derive a closed-form expression for the coarse grained dynamics. In addition, we show how the generator Extended Dynamic Mode Decomposition (gEDMD) method, which was developed in the context of Koopman operator methods, can be used to model the CG dynamics and evaluate its kinetic properties, such as transition timescales. Finally, we combine our approach with thermodynamic interpolation (TI), a generative approach to transform samples between thermodynamic conditions, to extend the scope of the approach across thermodynamic states without repeated numerical simulations. Using a two-dimensional model system, we demonstrate that the proposed method allows to accurately capture the thermodynamic and kinetic properties of the full-space model.
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All authors Vahid Nateghi, Lara Neureither, Selma Moqvist, Carsten Hartmann, Simon Olsson, Feliks Nüske

Applied Physics · Cross-listed from cond-mat.mes-hall

Spin-flop driven interfacial tunneling magnetoresistance in an antiferromagnetic tunnel junction

Xiaolin Ren, Ruizi Liu, Yiyang Zhang et al. (+6 more)

The utilization of two-dimensional (2D) materials in magnetic tunnel junctions (MTJs) has shown excellent performance and rich physics. As for 2D antiferromagnets, the magnetic moments in different layers respond asynchronously and can be configured at various states under different magnetic fields, showing the possibility of efficient magnetic and electrical tunability. In this report, A-type antiferromagnetic (AFM) material (Fe0.5Co0.5)5GeTe2 (FCGT) works as electrodes to realize full van der Waals magnetic tunnel junctions. Owing to the interfacial effect, the even-layer FCGT, although with zero net magnetization, exhibits spin selectivity in MTJ architecture contributing to a tunneling magnetoresistance (TMR) reaching about 25% at a low operating current 1 nA at 100 K and persists near room temperature. Due to the surface spin-flop (SSF) effect in antiferromagnetic FCGT, the alternation flexibility between the volatile and nonvolatile memory behavior is achieved. The interfacial TMR can be tuned efficiently in amplitude and even sign under different bias currents and temperatures. These findings show precise magnetoelectric manipulation in MTJs based on 2D antiferromagnets and highlight the promise of 2D antiferromagnets for spintronic devices.
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All authors Xiaolin Ren, Ruizi Liu, Yiyang Zhang, Yuting Liu, Xuezhao Wu, Kun Qian, Kenji Watanabe, Takashi Taniguchi, Qiming Shao

Optics

Photonic time stretch fieldoscopy: single-shot electric field detection at near-petahertz bandwidth

Steffen Gommel, Kilian Scheffter, Andreas Herbst et al. (+2 more)

Accessing the electric field of light with petahertz bandwidths in ambient air is a rapidly advancing frontier, essential for probing ultrafast dynamics driven by classical or quantum ultrashort pulses. Near-petahertz fieldoscopy has recently demonstrated sub-cycle access to light-matter interactions, enabling label-free spectro-microscopy of liquids and solids with unprecedented spatiotemporal resolution, detection sensitivity, and dynamic range. However, current implementations still rely on temporal scanning and averaging over many laser pulses. Here, we introduce photonic time-stretch fieldoscopy, enabling single-shot electric-field detection at near-petahertz frequencies. Numerical results demonstrate that integrating fieldoscopy with a nonlinear time lens enables the real-time acquisition of ultrashort optical waveforms with a detection bandwidth approaching petahertz. The resulting large temporal aperture and attosecond resolution allow direct single-shot detection of transient electric fields generated in solid or liquid samples. This concept opens new avenues for petahertz electronics, ultrafast spectro-microscopy, and the study of dynamic, non-repetitive optical phenomena
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All authors Steffen Gommel, Kilian Scheffter, Andreas Herbst, Anchit Srivastava, Hanieh Fattahi

Fluid Dynamics

Linking Aneurysmal Geometry and Hemodynamics Using Computational Fluid Dynamics

Spyridon C. Katsoudas, Konstantina C. Kyriakoudi, Grigorios T. Chrimatopoulos et al. (+8 more)

The development and progression of abdominal aortic aneurysms (AAA) are related to complex flow patterns and wall-shear-driven mechanobiological stimuli, yet the quantitative relationship between aneurysmal geometry and hemodynamics remains poorly defined. In this study, we conducted a comprehensive hemodynamic analysis of 74 patient-specific abdominal aortas, representing one of the largest Computational Fluid Dynamics (CFD) cohorts reported to date. A multiscale framework coupling 0D-1D systemic circulation models with 3D stabilized finite-element simulations is used to generate physiologically consistent boundary conditions and high-fidelity flow fields. From each model, we extract Time Averaged Wall Shear Stress (TAWSS), Oscillatory Shear Index (OSI), Relative Residence Time (RRT) and Local Normalized Helicity (LNH) indicators alongside an extended set of geometric descriptors characterizing diameter, curvature and torsion. This study provides a clear and comprehensive view of how aneurysm shape influences blood-flow behavior, supported by one of the largest systematically analyzed CFD datasets of AAAs to date. Our results show that specific geometric features reliably shape shear-stress patterns, suggesting that these geometry-driven flow signatures could serve as valuable biomarkers for patient-specific risk assessment. Together, these insights highlight the potential of incorporating detailed geometric descriptors into future models that aim to predict AAA growth and rupture.
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All authors Spyridon C. Katsoudas, Konstantina C. Kyriakoudi, Grigorios T. Chrimatopoulos, Panagiotis D. Linardopoulos, Christoforos T. Chrimatopoulos, Anastasios A. Raptis, Konstantinos G. Moulakakis, John D. Kakisis, Christos G. Manopoulos, Michail A. Xenos, Efstratios E. Tzirtzilakis

Biological Physics

V-Reactor Dynamics: Dual Chaotic Systems and Synchronizing Human Defenses with Viral Evolution

Yong-Shou Chen

The COVID-19 pandemic exposed critical gaps in our ability to predict viral emergence and trajectory. Moving beyond sequence-dependent surveillance, we introduce V-Reactor Dynamics, a physics-based framework that models host-virus interaction as a synchronized dual chaotic system. At its core is the reactivity parameter ($\rho$), a measurable quantity derived from viral replication, immune neutralization, and drug interaction cross sections. We show that $\rho$ dictates both intra-host viral load phases, peak ($\rho>0$), plateau ($\rho\approx0$), and clearance ($\rho<0$), and, through a scaling law, the Lyapunov Exponent governing population-level transmission dynamics. Retrospectively, the model correctly differentiates SARS-CoV-2's higher transmissibility from SARS-CoV's lethality, accurately forecasts Omicron waves, and quantifies trade-offs between lockdown intensity and socioeconomic cost. Crucially, V-Dynamics enables pre-outbreak prediction via in vitro measurement of viral reaction cross sections, offering a pathway to proactive pandemic defense. By integrating quantum-mechanical interaction models with chaos theory across scales, this framework provides a quantitative roadmap for anticipating, controlling, and ultimately preempting future viral threats.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG

Conditional updates of neural network weights for increased out of training performance

Jan Saynisch-Wagner and Saran Rajendran Sari

This study proposes a method to enhance neural network performance when training data and application data are not very similar, e.g., out of distribution problems, as well as pattern and regime shifts. The method consists of three main steps: 1) Retrain the neural network towards reasonable subsets of the training data set and note down the resulting weight anomalies. 2) Choose reasonable predictors and derive a regression between the predictors and the weight anomalies. 3) Extrapolate the weights, and thereby the neural network, to the application data. We show and discuss this method in three use cases from the climate sciences, which include successful temporal, spatial and cross-domain extrapolations of neural networks.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG

The promising potential of vision language models for the generation of textual weather forecasts

Edward C. C. Steele, Dinesh Mane, Emilio Monti et al. (+14 more)

Despite the promising capability of multimodal foundation models, their application to the generation of meteorological products and services remains nascent. To accelerate aspiration and adoption, we explore the novel use of a vision language model for writing the iconic Shipping Forecast text directly from video-encoded gridded weather data. These early results demonstrate promising scalable technological opportunities for enhancing production efficiency and service innovation within the weather enterprise and beyond.
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All authors Edward C. C. Steele, Dinesh Mane, Emilio Monti, Luis Orus, Rebecca Chantrill-Cheyette, Matthew Couch, Kirstine I. Dale, Simon Eaton, Govindarajan Rangarajan, Amir Majlesi, Steven Ramsdale, Michael Sharpe, Craig Smith, Jonathan Smith, Rebecca Yates, Holly Ellis, Charles Ewen

Fluid Dynamics

Drag reduction via separation control using plasma actuators on a truck cabin side

Lucas Schneeberger, Stefano Discetti and Andrea Ianiro

We investigate the drag reduction on a heavy-duty vehicle using dielectric-barrier discharge plasma actuators located on the A-pillars. An experimental campaign is carried out on a generalized truck model, the Ground Transportation System (GTS), which is known for its lateral separation bubbles on both sides of the truck's cabin. Measurements are performed for several yaw angles up to $7.5\degree$. Actuation is applied individually on the leeward and windward sides as well as simultaneously. Load cell measurements show that the plasma actuators effectively reduce the axial force on the GTS, with symmetric actuation achieving the highest reduction. Leeward actuation demonstrates greater control authority than the windward one; at large yaw angles the latter has a negligible effect on the axial force. Regarding side force, the leeward actuation produces a drop in its magnitude while windward actuation produces an increase. Interestingly, actuating symmetrically also augments the side force. Particle image velocimetry reveals that the plasma actuator causes a reduction in the length and width of the separation bubble on the cabin side, reducing the apparent frontal area of the truck and thus its drag. Under crosswind conditions, the stronger authority of the leeward actuator is explained by the larger separation bubble. The side force variation is driven by the net lateral suction force, which correlates with the size of the lateral recirculation regions controlled by the actuators.
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Biological Physics · Cross-listed from cond-mat.soft

Hamiltonian Active Particles in Incompressible Fluid Membranes

Sneha Krishnan and Rickmoy Samanta

Active proteins and membrane-bound motors exert force dipole flows along fluid interfaces and lipid bilayers. We develop a Hamiltonian framework for the interactions of pusher and puller dipoles embedded in an incompressible two-dimensional membrane supported by a shallow viscous subphase. Beginning from the Brinkman-regularized Stokes equations of the membrane-subphase system, we construct the near-field and far-field dipolar velocity fields and associated stream functions. For two quenched (fixed orientation) dipoles, we obtain exact analytic solutions in both the near- and far-field regimes. Although generic dipoles reorient under local membrane vorticity, we show that the far-field dipolar flow is vorticity-free; force-free motors therefore retain fixed orientations and obey a position-based Hamiltonian dynamics in which the positions of $N$ dipoles evolve via an effective Hamiltonian built from the dipolar stream function. In the near field, where the flow possesses finite vorticity, a Hamiltonian formulation is recovered in the quenched-orientation limit. For identical dipoles, the far-field Hamiltonian produces rapid clustering from random initial conditions, whereas the near-field Hamiltonian suppresses collapse leading to non-aggregating configurations. The phase portraits reveal that the many-body collapse observed in the time evolution of the far field Hamiltonian arises from angular transport across phase space enabled by the screened hydrodynamic interaction. Our work thus provides a concrete realization of a position-based Hamiltonian formulation for active particles in incompressible fluid membranes and shows that hydrodynamic screening can reorganize both the dynamical phase space and the collective organization of active dipoles.
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Optics

Multi-peak vector soliton families in defocusing Kerr resonators

Pengxiang Wang, Carlos Mas-Arabi, Gian-Luca Oppo et al. (+6 more)

We report the existence of multi-peaked vector soliton families in normally dispersive passive Kerr resonators. Through cross-phase modulation between two orthogonal polarization components, each peak becomes tightly interlocked, enabling robust localization of the entire wave packet in defocusing cavities. Analysis using snakes-and-ladder diagrams demonstrates the diversity of these vector soliton families, which include dark-bright multi-peak solitons, flat-topped solitons, and modulation instability patterns, among others. Furthermore, stability analysis based on the coupled Lugiato-Lefever equations reveals that specific combinations of parameters can sustain stable vector cavity solitons, whose peak numbers can be continuously tuned by adding appropriate perturbations. These findings significantly expand the scope of soliton dynamics and optical frequency comb generation in pumped-dissipative systems, independent of dispersion conditions.
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All authors Pengxiang Wang, Carlos Mas-Arabi, Gian-Luca Oppo, Yiqing Xu, Miro Erkintalo, Stephane Coen, Bertrand Kibler, Julien Fatome, Gang Xu

Fluid Dynamics

Fast directional transport of Leidenfrost droplets on spiked surfaces

Kai-Xin Hu, Dong-Xu Duan, Yin-Jiang Chen et al. (+2 more)

The Leidenfrost effect enables droplets to levitate above a solid surface, significantly reducing the resistance to droplet motion. In this study, a spiked surface is utilized to achieve fast directional transport of Leidenfrost droplets, with a maximum average speed reaching 8.36 m per second over a 10 cm distance,far exceeding the previously reported maximum speeds for droplet transport. When a droplet falls onto a substrate heated above the Leidenfrost temperature, it becomes trapped between spikes and levitates. The sides and bottom surface of the droplet undergo vaporization, creating a gas film between the solid wall and the droplet. However, this gas film is unstable and prone to rupture at certain points, causing the droplet to come into contact with the solid surface. Therefore, the droplets undergo violent boiling, leading to intense compression and bursting into smaller daughter droplets, which are then propelled rapidly along the substrate. Additionally, the asymmetric geometry of the spikes ensures that droplets move unidirectionally along the longitudinal direction. This study proposes a novel droplet self-propulsion mechanism, pioneering new strategies for enhancing droplet transport speed..
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All authors Kai-Xin Hu, Dong-Xu Duan, Yin-Jiang Chen, Dan Wu, Qi-Sheng Chen

Geophysics

Postseismicity of slow-slip doublets discerned on the outermost of the Nankai Trough subduction megathrust

Dye SK Sato, Takane Hori, Takeshi Iinuma et al. (+2 more)

Despite dissimilar slip rates, slow earthquakes are faulting as ordinary earthquakes are. It is therefore physically natural that slow earthquakes also cause postseismic motions similarly to ordinary earthquakes, even though coseismic and postseismic slips remain undifferentiated for slow earthquakes. We pursue the slow-earthquake postseismicity based on the analysis of a fault slip beneath the Bungo Channel, the westernmost region of the Nankai Trough subduction zone in southwestern Japan. Its 2010 long-term slow slip event (SSE) was mispredicted by physics-based models, which concludes that the initial acceleration of this SSE was too abrupt for a slow variant of a fault rupture. We identify that a mispredicted GNSS signal evolves logarithmically in time, preceded by minor signals that evolve exponentially, lasting about two years west and about half a year east. By performing sparse inverse modeling on the GNSS, we have estimated that exponential slips occur at the same depth, bracketing a logarithmic slip that occurs beneath the channel. The regions of exponential slips match repeating slow-slip regions, and deep tremors synchronize exclusively with the logarithmic slip. This source complexity can be explained as a neighboring rupture doublet and its afterslip and aftershocks by the known mechanics of ordinary earthquakes. If slow earthquakes have a dual origin in exponentially nucleating slow rupture and logarithmically decelerating postseismic creep, it is possible to pick the slow earthquake nuclei that could accelerate into megathrust catastrophes.
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All authors Dye SK Sato, Takane Hori, Takeshi Iinuma, Masayuki Kano, Yusuke Tanaka

Optics

Real-Time Control and Automation Framework for Acousto-Holographic Microscopy

Hasan Berkay Abdioğlu, Yağmur Iş{\i}k, Mustafa İsmail İnal et al. (+5 more)

Manual operation of microscopes for repetitive tasks in cell biology is a significant bottleneck, consuming invaluable expert time, and introducing human error. Automation is essential, and while Digital Holographic Microscopy (DHM) offers powerful, label-free quantitative phase imaging (QPI), its inherently noisy and low-contrast holograms make robust autofocus and object detection challenging. We present the design, integration, and validation of a fully automated closed-loop DHM system engineered for high-throughput mechanical characterization of biological cells. The system integrates automated serpentine scanning, real-time YOLO-based object detection, and a high-performance, multi-threaded software architecture using pinned memory and SPSC queues. This design enables the GPU-accelerated reconstruction pipeline to run fully in parallel with the 50 fps data acquisition, adding no sequential overhead. A key contribution is the validation of a robust, multi-stage holographic autofocus strategy; we demonstrate that a selected metric (based on a low-pass filter and standard deviation) provides reliable focusing for noisy holograms where conventional methods (e.g., Tenengrad, Laplacian) fail entirely. Performance analysis of the complete system identifies the 2.23-second autofocus operation-not reconstruction-as the primary throughput bottleneck, resulting in a 9.62-second analysis time per object. This work delivers a complete functional platform for autonomous DHM screening and provides a clear, data-driven path for future optimization, proposing a hybrid brightfield imaging modality to address current bottlenecks.
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All authors Hasan Berkay Abdioğlu, Yağmur Iş{\i}k, Mustafa İsmail İnal, Nehir Serin, Kerem Bayer, Muhammed Furkan Koşar, Taha Ünal, Hüseyin Üvet

Computational Physics · Cross-listed from math.NA

Constraint-Preserving High-Order Compact OEDG Method for Spherically Symmetric Einstein-Euler System

Yuchen Huang, Manting Peng and Kailiang Wu

Numerical simulation of the spherically symmetric Einstein–Euler (EE) system faces severe challenges due to the stringent physical admissibility constraints of relativistic fluids and the geometric singularities inherent in metric evolution. This paper proposes a high-order Constraint-Preserving (CP) compact Oscillation-Eliminating Discontinuous Galerkin (cOEDG) method specifically tailored to address these difficulties. The method integrates a scale-invariant oscillation-eliminating mechanism [M. Peng, Z. Sun, K. Wu, Math. Comp., 94: 1147–1198, 2025] into a compact Runge–Kutta DG framework. By characterizing the convex invariant region of the hydrodynamic subsystem with general barotropic equations of state, we prove that the proposed scheme preserves physical realizability (specifically, positive density and subluminal velocity) directly in terms of conservative variables, thereby eliminating the need for complex primitive-variable checks. To ensure the geometric validity of the spacetime, we introduce a bijective transformation of the metric potentials. Rather than evolving the constrained metric components directly, the scheme advances unconstrained auxiliary variables whose inverse mapping automatically enforces strict positivity and asymptotic bounds without any limiters. Combined with a compatible high-order boundary treatment, the resulting CPcOEDG method exhibits robust stability and design-order accuracy in capturing strong gravity-fluid interactions, as demonstrated by simulations of black hole accretion and relativistic shock waves.
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Computational Physics · Cross-listed from cs.LG

ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms

Juan Diego Toscano, Daniel T. Chen and George Em Karniadakis

Progress in computational science depends on complex numerical workflows that must faithfully encode physical laws, yet translating conceptual insight into reliable code remains a major bottleneck. Although large language models can generate isolated code fragments, they lack the structured reasoning required to design, verify, and iteratively refine complete scientific pipelines. Here we introduce ATHENA, an agentic framework explicitly designed to emulate scientific research modeled as a knowledge-driven contextual bandit process. Its core loop separates conceptual policy from numerical realization through expert-derived conceptual scaffolding, enabling principled diagnosis, reformulation, and repair of computational strategies. Across scientific computing and scientific machine learning tasks, ATHENA autonomously derives and correctly applies exact analytical solutions, constructs stable numerical solvers, diagnoses ill-posed formulations, and orchestrates hybrid symbolic-numeric workflows. Quantitatively, ATHENA matches and frequently surpasses the accuracy of expert-authored reference solutions reported in the literature on canonical benchmarks. By reframing computation as an object of agentic reasoning, our framework enables autonomous orchestration of heterogeneous algorithms across scientific domains.
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Plasma Physics · Cross-listed from astro-ph.SR

Quasi-linear theory of perpendicular ion heating by critically balanced turbulence

Zade Johnston and Jonathan Squire

In collisionless astrophysical plasmas, turbulence mediates the partitioning of free energy among cascade channels and its dissipation into ion and electron heat. The resulting ion heating is often anisotropic, with ions observed to be preferentially heated perpendicular to the local magnetic field; understanding the mechanisms responsible for this heating is a key step in understanding the evolution of such plasmas. In this paper, we use the framework of quasi-linear theory to compute analytically the heating rates of ions interacting with turbulent, large-scale Alfvénic fluctuations. We show how the imbalance of the turbulence (the difference in energies between Alfvénic fluctuations travelling parallel and antiparallel to the magnetic field) modifies the spatiotemporal spectrum of these fluctuations, allowing the heating mechanism to smoothly transition between stochastic heating in balanced turbulence and cyclotron-resonant heating in imbalanced turbulence. The resultant heating rate is found to have a general form regardless of the level of imbalance, exhibiting a suppression related to the conservation of the ions' magnetic moment at small turbulent amplitudes and recovering previous empirical results in a formal calculation. The results of this work help to consolidate our qualitative understanding of ion heating within astrophysical plasmas, as well as yielding specific quantitative predictions to analyse simulations and observations.
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Biological Physics

A novel multiscale modelling for the hemodynamics in retinal microcirculation with an analytic solution for the capillary-tissue coupled system

Chang Lin, Zilong Song, Robert Eisenberg et al. (+2 more)

Mathematical modelling of the microcirculatory hemodynamics in the retina is an essential tool for understanding various diseases of the retina, yet remains challenging due to the multiscale nature of the retinal vasculature and its coupling to surrounding tissue. To address this, we develop a multiscale model that couples retinal vasculature across scales with interstitial tissue. Our model combines the one-dimensional (1D) model for arterioles and venules with the coupled Darcy equations for capillaries and tissue. The model uses an analytic solution for capillary-tissue coupled system that provides a simple interpretation of the results along with much faster computation. The analytic solution implies a dynamic coupling condition that links the capillary bed with upstream arteriolar and downstream venular flows. The model is mathematically robust, demonstrated through analysis of the solution's truncation error and convergence. Its predictive accuracy is validated against experimental data and other models, making it useful in interpreting experimental results. Finally, the role of various parameters in controlling retinal hemodynamics is explored.
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All authors Chang Lin, Zilong Song, Robert Eisenberg, Shixin Xu, Huaxiong Huang

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

Subgrid Mean-field Dynamo Model with Dynamical Quenching in General Relativistic Magnetohydrodynamic Simulations

Hongzhe Zhou, Yosuke Mizuno and Zhenyu Zhu

Large-scale magnetic fields are relevant for a number of dynamical processes in accretion disks, including driving turbulence, reconnection events, and launching outflows. Numerical simulations have indicated that the initial strengths and configurations of the large-scale magnetic fields have a direct imprint on the outcome of an accretion disk evolution. To facilitate future self-consistent simulations that include intrinsic dynamo processes, we derive and implement a subgrid model of a helical large-scale dynamo with dynamical quenching in general-relativistic resistive magnetohydrodynamical simulations of geometrically thin accretion disks. By incorporating previous numerical and analytical results of helical dynamos, our model features only one input parameter, the viscosity parameter $\alpha_\text{SS}$. We demonstrate that our model can reproduce butterfly diagrams seen in previous local and global simulations. With rather aggressive parameter choice of $\alpha_\text{SS}=0.02$ and black hole spin $a_\text{BH}=0.9375$, our thin-disk model launches weak collimated polar outflows with Lorentz factor $\simeq 1.2$, but no polar outflow is present with less vigorous turbulence or less positive $a_\text{BH}$. With negative $a_\text{BH}$, we find the field configurations to appear more similar to Newtonian cases, whereas for positive $a_\text{BH}$, the poloidal field loops become distorted and the cycle period becomes sporadic or even disappears. Moreover, we demonstrate how $\alpha_\text{SS}$ can avoid to be prescribed and instead be determined by the local plasma beta. Such a fully dynamical subgrid dynamo allows for self-consistent amplification of the large-scale magnetic fields.
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Optics · Cross-listed from cond-mat.mtrl-sci

Unconventional Magneto-Optical Effects in Altermagnets

Yongpan Li, Yichen Liu and Cheng-Cheng Liu

The ideal altermagnets are a class of collinear, crystal-symmetry-enforced fully compensated magnets with nonrelativistic spin-split bands, in which contributions from Berry curvature to magneto-optical effects (MOEs) are strictly forbidden by an effective time-reversal symmetry. Here we show that, in such systems, MOEs are exclusively induced by the quantum metric and, in realistic altermagnets, are typically dominated by it. We refer to Berry-curvature-induced MOEs as conventional MOEs and to quantum-metric-dominated MOEs as unconventional MOEs. We derive general formulas that incorporate both Berry curvature and quantum metric for unconventional MOEs in altermagnets, enabling a quantitative evaluation of their respective contributions. Through symmetry analysis, we prove that ideal altermagnets are constrained to exhibit only unconventional MOEs. Using the three-dimensional canonical altermagnet MnTe and the emerging two-dimensional bilayer twisted altermagnet CrSBr as illustrative examples, we demonstrate that unconventional MOEs are prevalent in altermagnets. Our results establish altermagnets as a natural platform for quantum-metric-driven optical phenomena, substantially broadening the scope of MOEs and providing concrete predictions that can be tested in future experimental studies.
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Chemical Physics

Zero-Waste Biorefinery: Pyrolysis of Fermentation Residues into Catalytic Biochar for Circular Biohydrogen Systems

Muhammad Shahzaib

This study presents a closed-loop biorefinery strategy that thermochemically upcycles fermentation residues (FRs) from photo-fermentative biohydrogen production (PFHP) into functional biochar catalysts, thereby enhancing the efficiency of the initial PFHP process. Four FRs derived from hydrothermal and ethylene glycol-pretreated corn stover were pyrolyzed at 700{\deg}C. Multi-model kinetic analyses revealed diffusion-controlled mechanisms with activation energies ranging from 157 to 278 kJ/mol, while thermodynamic profiling highlighted the influence of feedstock composition on reaction spontaneity and entropy. Pyrolysis effectively restored porosity compromised during fermentation, yielding biochar with tailored properties: microporous BC3 (185 m2/g) from oxygen-rich precursors and mesoporous BC4 (76.58 m2/g) from graphitized residues. When reintroduced into PFHP, BC3 maximized cumulative hydrogen yield (570 mL) via pH buffering, and BC4 achieved the highest production rate (14.91 mL/h) through electron shuttle mechanisms. The integrated process concurrently generated syngas, bio-oil, and catalytic biochar, enabling waste valorization, renewable energy output, and process enhancement within a circular bioeconomy framework.
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