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Physics Physics

physics Watch Physics

Tuesday 29 September

Chemical Physics

Ionization-Driven Dehydrogenation and Molecular Growth in Gas-Phase Adamantane Clusters

Sumit Srivastav, Per Eng-Johnsson, Raimund Feifel et al. (+4 more)

We investigate fragmentation and molecular growth induced by keV ions in initially neutral gas-phase adamantane clusters, the simplest diamondoid molecule (Ad, C$_{10}$H$_{16}$). Using time-of-flight mass spectrometry in combination with quantum-chemical calculations, we find that intact cluster cations undergo extensive dehydrogenation. We also observe a distinct distribution of singly charged products with masses predominantly between those of the adamantane monomer and dimer cations. We attribute these species to ion-induced growth products and interpret their formation considering the smallest cluster cation, [Ad]$_2^+$, using quantum-chemical calculations. Our results demonstrate that ionization strongly reorganizes the dimer geometry, facilitating H$_2$ elimination and intermolecular covalent C–C bond formation. Weakly bound adamantane clusters are thereby transformed into covalently bound carbonaceous species with a strong preference for specific molecular structures. These findings provide new insight into ionization-driven molecular growth in saturated hydrocarbon systems contributing to the understanding of molecular complexification, with implications for chemical physics and astrochemistry.
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All authors Sumit Srivastav, Per Eng-Johnsson, Raimund Feifel, Alicja Domaracka, Patrick Rousseau, Dariusz G. Piekarski, Sylvain Maclot

Biological Physics · Cross-listed from q-bio.NC

An adaptive fractional state links circuit mechanisms to cortical dynamics across the visual hierarchy

Brendan Harris and Pulin Gong

Cortical circuits must respond flexibly to new inputs while integrating information about the past, yet the way in which neural activity reconciles these competing demands remains unclear. Combining Neuropixels recordings from six mouse visual areas with mechanistic circuit modeling, we identify a dynamical regime in which heavy-tailed superdiffusive fluctuations coexist with long-range temporal dependence and oscillations. We formalize this regime as the adaptive fractional (AF) state, using an effective mean-field theory in which spatial and temporal fractional derivatives capture heavy-tailed excursions and long-range memory, respectively. We find that dynamical exponents characterizing the AF state vary systematically across the visual hierarchy: higher visual areas exhibit weaker superdiffusion and stronger temporal memory. In the circuit model, this hierarchical shift emerges from a progressive weakening of effective inhibition. These findings extend the classical hierarchy of timescales to a hierarchy of dynamical regimes and suggest that the AF state allows cortical areas to jointly express rapid responses and long-term temporal integration.
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Atomic Physics · Cross-listed from quant-ph

A magnetic-field insensitive gate set for trapped-ion nuclear spin qubits

Jonathan Paul Home, Jeremy Flannery, Matteo Mazzanti et al. (+2 more)

We outline a complete set of operations for manipulating nuclear spin qubits of trapped-ions stored in high magnetic fields such as required for Penning trapping, where the nuclear and electron spins are largely decoupled due to the dominance of the external field Hamiltonian. The reduced nuclear magnetic moment results in insensitivity to external magnetic fields compared to the use of an electron spin, but also makes the nuclear spin hard to manipulate on fast timescales. To maintain speed, we propose a two-qubit phase gate technique which utilizes the electron spin, but for which the qubit remains protected from magnetic fields through retaining the nuclear encoding. This method works for magnetic-field insensitive qubits at lower fields as well as for both microwave and laser field gradients.
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All authors Jonathan Paul Home, Jeremy Flannery, Matteo Mazzanti, Jan Apolin, Shreyans Jain

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

Vapor phase growth and characterization of van der Waals BiSbTeSe platelets on semiconducting MoS2

M. Zhezhu, V. Torosyan, V. Mehrabyan et al. (+1 more)

Three dimensional topological insulators of the tetradymite family, such as BiSbTeSe (BSTS), are attractive for spintronic and quantum device applications because of their compensated, bulk-insulating character. Nanostructured BSTS platelets are promising for practical TI based devices. However, their growth often requires complex equipment, organometallic precursors, or electrically insulating substrates. Simple growth on technologically relevant semiconducting substrates remains largely unexplored. Here, we report the vapor phase growth of van der Waals BSTS platelets directly on semiconducting MoS2 using a presynthesized BiSbTe1.5Se1.5 crystal as the source material. The grown BSTS platelets exhibit thicknesses ranging from 4 nm to 246 nm, with an average lateral size of 1.4 mkm for individual platelets. Raman spectra of platelets, acquired in correlation with AFM thickness measurements, reveal contributions from both BSTS and the underlying MoS2 substrate. Among the characteristic BSTS modes, A21g mode shows the highest sensitivity to platelet thickness and local composition. EDS analysis reveals a systematic thickness dependence of the platelet composition, with an apparent crossover around 49 nm that coincides with a change in the thickness dependence of the low-wavenumber component of the E2g Raman band. This correlation suggests a composition-related origin of the Raman behavior, with the compositional variations tentatively attributed to the differential volatility of the constituent elements during growth. These results demonstrate that MoS2 is a promising van der Waals platform for BSTS deposition and provide a structural and compositional baseline for future studies of BSTS-MoS2 heterostructures.
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All authors M. Zhezhu, V. Torosyan, V. Mehrabyan, A. Vasilev

Optics

Scanless quantum Fourier-transform mid-infrared spectroscopy for solids and surface analysis

Paul Gattinger, Michela Conti, Franziska Dietz et al. (+4 more)

Quantum infrared (IR) spectroscopy is a novel technique based on nonlinear interferometry and quantum sensing with undetected photons. In this approach, spectrally far-separated correlated photon pairs are used for detection and probing, respectively. Hence, the probing wavelength domain (mid-IR) is substantially different from the detection spectral range (near-IR), which enables shot-noise-limited and cost-effective sensing schemes attractive for applied metrology. In this paper, we implement and employ a custom-built scanless quantum Fourier-transform mid-IR (sQFTIR) microspectrometer for chemical characterization and analysis of solids and interfaces. The sQFTIR system employs spectral-domain acquisition, without the need to scan the optical delay. This results in enhanced sensitivity and short measurement times and therefore enables rapid spectral acquisitions in 100~ms spanning a spectral band from 3000 cm$^{-1}$ - 2400 cm$^{-1}$. The capabilities of our approach are demonstrated for hyperspectral mid-IR imaging of dried pharmaceuticals (insulin on a gold surface) and investigation of a security feature on a banknote. Furthermore, we demonstrate hyperspectral imaging and spectroscopy through a turbid ceramic medium.
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All authors Paul Gattinger, Michela Conti, Franziska Dietz, Andrei N. Halangescu Moldovan, Andreas W. Schell, Markus Brandstetter, Ivan Zorin

Plasma Physics

Rectification of plasma-powered active matter into macroscopic work

Ting-yu Yao, Shuo Wang, Shao-peng Li et al. (+3 more)

Plasmas sustain strong energy and momentum flux, yet this activity is typically treated as a dissipative loss channel rather than a usable resource, and its conversion into macroscopic work remains challenging. Here we demonstrate a plasma-powered active engine by coupling self-propelled micromotors to ratchet rectification. Dielectric microspheres in the plasma sheath spontaneously develop asymmetric surface charging and undergo a Quincke rotational instability, forming fast micromotors that extract energy directly from the plasma. Their stochastic impacts are rectified by a sawtooth rotor into a directed angular-momentum flux that drives steady rotation, while an outer asymmetric gear organizes the active bath into coherent circulation to amplify torque transfer. Operating in an inertia-relevant regime, the engine achieves orders-of-magnitude enhancements in both power output and end-to-end efficiency compared with liquid-phase active engines, and remains functional down to the single-micromotor limit. More broadly, our results establish a general route to rectify nonequilibrium plasma activity for macroscopic work.
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All authors Ting-yu Yao, Shuo Wang, Shao-peng Li, Ming-hang Zhao, Bao-quan Ai, Ya-feng He

Fluid Dynamics

Vortex rings as hydrodynamic dispersants for mitigating underwater oil spills

Siddhant Jain, Saini Jatin Rao and Saptarshi Basu

The usage of chemical dispersant to promote the breakup of oil droplets remains one of the crucial response strategy towards controlling the rapidly rising droplets during an underwater oil spillage disaster like the Deepwater horizon. However, the detrimental effects of dispersant on the marine life are now well recognized. Here, we demonstrate that vortex ring presents an environmental friendly alternative to the debatable usage of chemical dispersant that primarily aids droplet break-up. We propose two mitigating strategies through the application of vortex rings: (i) atomization of large oil droplets into smaller droplets, which enhances natural dispersion and biodegradation (ii) targeted relocation of spilled oil droplets from ecologically sensitive regions to safer remote locations during minor spill events. This proof-of-concept study demonstrates that vortex rings can efficiently atomize underwater oil droplets while simultaneously transporting them over long distances. The efficiency strongly depends on the droplet size distribution and the strength of the vortex ring. Using time scale analysis and force balances arguments, we propose droplet response and atomization criteria by a traversing vortex ring. Beyond atomization and droplet transport which are center to many engineering processes, the work finds high relevance in the area of bubble turbulence, agricultural industry, multiphase reactors, combustion process, atmospheric fluid dynamics and oil extraction from rocks, to name a few.
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Optics

Silicon nitride nanophotonics for low-redundancy 3D convolution

Shuai Hu, Jingcheng Li, Qichao Ding et al. (+5 more)

Three-dimensional (3D) convolution extracts correlations in high-dimensional data, but overlapping receptive fields introduce substantial redundant data movement. Here, we demonstrate a silicon nitride 3D optical convolution accelerator (3D-OCA) that reconstructs receptive fields through coordinate-aware wavelength-to-group-delay mapping. A deterministically serialized input tensor is broadcast onto multiple wavelength channels, and a chirped waveguide Bragg grating (CWBG) compensates the temporal offsets associated with 3D kernel coordinates. This arrangement continuously forms neighboring receptive fields without repeatedly rearranging and loading their shared input samples. The integrated CWBG provides a differential group delay of 2691 ps and a dispersion of 124.8 ps/nm. At 20 Gbaud, spatial-spectral processing of Indian Pines data yields convolution agreement with a coefficient of determination up to 0.997 and 97.9% classification accuracy, compared with 98.9% digitally. At 10 Gbaud, the optical convolution layer preserves spatiotemporal features and achieves 92.5% accuracy on a four-class KTH video-recognition task. These results establish low-redundancy streaming 3D convolution across spectral and temporal data dimensions using the same optical delay architecture.
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All authors Shuai Hu, Jingcheng Li, Qichao Ding, Hongli Wang, Hailong Zhou, Chi Zhang, Jianji Dong, Xinliang Zhang

Optics

Photonic sequential logic circuits for stateful intelligence

Jingcheng Li, Wenkai Zhang, Jialong Zhang et al. (+6 more)

By virtue of its high energy efficiency and ultra-low latency, optical computing is regarded as a highly promising computing paradigm in the post-Moore era. However, constructing a Turing-complete optical computing for next-generation AI paradigms, from large language models (LLMs) to real-time autonomous systems, requires not only stateless function mapping units, but also sequential logic circuits capable of storing historical states and processing dynamic data streams. Current photonic processors lack this temporal memory, and the state-of-the-art optical sequential schemes remain impractical due to signal attenuation and the absence of programmable clock control. Here, we propose a photonic sequential logic circuits (PSLC) to resolve this fundamental challenge. Leveraging a uniquely designed active optoelectronic feedback network, we construct a complete family of photonic sequential logic devices, comprehensively encompassing set-reset latches, D latches, and edge-triggered master-slave D flip-flops. We further construct photonic sequence detectors and asynchronous counters, verifying the capability of the architecture to execute both synchronous and asynchronous sequential tasks, alongside its system-level scalability. Ultimately, by combining the constructed PSLC with stateless function mapping units, we establish a universal hardware paradigm for stateful intelligence. We validate this paradigm by executing highly reliable real-time drone obstacle avoidance in the physical domain, alongside Shakespearean-style text generation in the symbolic domain. This work provides the crucial missing piece of the puzzle for optical computing to achieve stateful computing, establishing a definitive hardware foundation for advancing toward Turing-complete optical computing.
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All authors Jingcheng Li, Wenkai Zhang, Jialong Zhang, Bo Wu, Qichao Ding, Hongli Wang, Hailong Zhou, Jianji Dong, Xinliang Zhang

Plasma Physics

Laser-Polarization Dependence of Betatron X-Ray Production and Angular Collection in Laser-Wakefield Acceleration

Andrei Ciprian Berceanu, Vojtěch Horný, Dan Stutman et al. (+1 more)

Laser polarization affects both the production of betatron x rays and their angular distribution, which together determine the photon yield collected within a fixed angular acceptance. We investigate these effects using particle-in-cell simulations of laser-wakefield acceleration with linearly polarized (LP) and circularly polarized (CP) pulses of equal energy in helium–nitrogen targets of two different lengths. In the longer target, CP produces more photons early in propagation, whereas LP produces more later. For 20–60-keV photons transmitted through 2 mm of aluminum, the LP/CP yield ratio before angular selection changes from 0.88 early on to 1.91 in a late stage. Late-emitting LP electrons develop pronounced transverse oscillations along the laser polarization direction, accompanied by angular broadening of the radiation. This broadening largely removes the late LP production advantage within a central $\pm5$-mrad acceptance, where the two yields are nearly equal. Integrated over the full interaction, however, LP supplies more central photons, while CP provides more uniform illumination. In the shorter target, the extracted charges above 100 MeV are nearly equal, yet transport through a quadrupole triplet delivers 750 pC for LP and 500 pC for CP in the 350–500-MeV energy band within a radius of 5 mm. Collected photon and electron yields are thus shaped by propagation length and collection acceptance.
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All authors Andrei Ciprian Berceanu, Vojtěch Horný, Dan Stutman, Paolo Tomassini

Plasma Physics

Cold atmospheric plasma decontaminates Arabidopsis thaliana seeds and remodels seedling fungal microbiota

Lena Taras, Nicole Chaumont, Caroline Kunz et al. (+2 more)

Seed-associated microorganisms influence seed quality, seedling establishment, and plant health and also constitute a major source of seed-borne pathogens. Cold atmospheric plasma (CAP) has emerged as a promising alternative to chemical seed treatments because of its antimicrobial activity, although its effects on fungal communities associated with developing seedlings remain poorly understood. Here, Arabidopsis thaliana seeds from two ecotypes (Columbia and Landsberg erecta) were exposed to CAP for 5 or 15 min. Seed decontamination efficiency was assessed by culturing on malt extract agar and nephelometric analyses, while fungal communities associated with seedlings derived from treated and untreated seeds were characterized by ITS1 amplicon sequencing. CAP efficiently reduced fungal contamination without affecting seed germination. CAP altered the composition of fungal communities associated with developing seedlings, but the magnitude of these changes depended on seed batch and ecotype. Dominant taxa markedly declined after treatment, whereas several low-abundance taxa increased in relative abundance. These findings demonstrate that CAP is an effective pesticide-free technology for seed decontamination and can also reshape fungal communities associated with developing seedlings, highlighting broader ecological consequences of plasma-based seed treatments.
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All authors Lena Taras, Nicole Chaumont, Caroline Kunz, Thierry Dufour, Christophe Bailly

Geophysics

Finite-Horizon Triggering Cores of Earthquake Sequences

Didier Sornette and Giuseppe Petrillo

Models of triggered seismicity commonly aggregate the contributions of all past earthquakes into a total predicted rate. This aggregation does not distinguish a forecast dominated by one recent earthquake from an equal-rate forecast supported by many events distributed across a longer history, even though these configurations can have different persistence and sensitivity to catalog and parameter uncertainties. We introduce the finite-horizon triggering core size \(N_{p,T}(t)\), defined as the minimum number of past earthquakes whose expected contributions account for a fraction \(p\) of the total triggering potential over the future interval \([t,t+T]\). The definition applies to any triggering model that assigns nonnegative event-specific expected contributions over a specified future window. We develop its theory for marked Hawkes and epidemic-type aftershock sequence processes, where the weights are the expected numbers of direct offspring produced by individual past earthquakes. The finite horizon makes the observable well defined for every normalized Omori kernel with exponent \(\theta>0\), including the long-memory regime in which the corresponding infinite-horizon quantity diverges. We derive continuum and marked-Poisson benchmarks, an exact representation of the marked-Poisson distribution, and high-\(p\) distributional laws. For finite-horizon Omori memory, the triggering core grows as \((1-p)^{-1/\theta}\) with a realization-dependent amplitude controlled by the total triggering weight; for exponential memory, the growth is logarithmic.[...]
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Fluid Dynamics

Probabilistic Symbolic-Distillation Model of Droplet Collision for Spray Simulation at High Ambient Pressures

Weiming Xu, Tao Yang and Peng Zhang

Droplet collision governs droplet population dynamics in many chemical engineering processes, such as spray drying, spray cooling, agricultural spraying, and combustion. Existing analytical models impose deterministic, pairwise boundaries between collision outcomes, whereas machine-learning classifiers lack the explicit functional form required of analytical collision submodels. In this study, we develop a probabilistic symbolic-distillation model using nearly forty thousand experimental events spanning eight regimes and five dimensionless parameters, including over five thousand data for ambient pressure up to 50 atm. A machine-learning teacher learns the joint outcome-probability landscape from these data, and symbolic regression subsequently distils it into eight class-specific expressions that jointly define a coupled analytical model. The resulting analytical field replaces abrupt regime switching with finite-width fuzzy boundaries. It outperforms the evaluated conventional analytical boundary models and reveals that their main limitation is the inability of zero-width boundaries to represent gradual probability transitions. The "biased-dice" sampling scheme provides a statistically consistent and practically convenient model implementation for Eulerian-Lagrangian spray simulation.
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Computational Physics · Cross-listed from cond-mat.stat-mech

Accurate ground-state entropies from population Monte Carlo: The antiferromagnetic Ising model on the Shastry-Sutherland lattice

Denis Gessert, Wolfhard Janke and Martin Weigel

We demonstrate how the population annealing Monte Carlo simulation method can be used to compute the ground-state entropy to high precision. This approach is tested for the classical antiferromagnetic Ising model on the Shastry-Sutherland lattice with diagonal couplings chosen twice as strong as the nearest-neighbor interactions. In the absence of an external magnetic field, the model is known to be disordered at all temperatures, with a macroscopically degenerate ground state. We find the ground-state entropy to be $0.458\,777\,78(10)$ per site, which is in good agreement with the estimate of a recent study using the corner transfer matrix renormalization group method. The sampled ground-state configurations are analyzed by considering the bond configurations, the local-energy configurations, and the spin-spin correlations. While all observations are consistent with the disordered nature of the ground state, the numerical data suggest a power-law decay of the size distribution of clusters of sites with local energies different from the ground-state level.
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Chemical Physics

Adaptive Expansions of the Optimized Effective Potential in Physically Motivated Response Spaces

Gabriel Chirchir, Aditi Singh, Yan Lukashevich et al. (+4 more)

The optimized effective potential (OEP) method provides an exact framework for incorporating orbital-dependent exchange within Kohn-Sham (KS) density-functional theory (DFT). Its practical implementation requires representing the exchange-response potential in a suitable auxiliary space, yet conventional choices are not necessarily adapted to the physical structure of the OEP response. Here, we introduce a general response-space strategy in which physically motivated response functions from existing model exchange potentials are repurposed as adaptive auxiliary directions for the OEP equation. Specifically, response functions associated with the Becke-Johnson (BJ), R"as"anen-Pittalis-Proetto (RPP), Gritsenko-van Leeuwen-van Lenthe-Baerends (GLLB), Krieger-Li-Iafrate (KLI), and localized Hartree-Fock (LHF) constructions are incorporated into compact auxiliary spaces, while their coefficients are determined directly from the projected OEP equation rather than fixed by the underlying model potentials. This establishes a systematic connection between model exchange potentials and finite-basis OEP: model potentials provide physically informed response directions, while OEP determines their system-dependent amplitudes. The framework encompasses one- and multidimensional response spaces, including occupied-orbital and occupied-pair representations, without modifying the underlying OEP condition. We show that these physically adapted spaces capture the dominant spatial structures of the OEP exchange response with substantially fewer degrees of freedom than conventional auxiliary expansions. The proposed approach therefore provides a general route to compact, adaptive representations of exchange-only OEP potentials and a systematic framework for developing low-dimensional OEP approximations from physically motivated model response functions.
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All authors Gabriel Chirchir, Aditi Singh, Yan Lukashevich, Igor Sawicki, Bogumiła Jezierska, Subrata Jana, Szymon Śmiga

Optics

Optically-Induced Modulation and Programming of Diamond Photonic Cavities

Yuchun Zhu, Amirali Arabmoheghi, Nicolas Le Thomas et al. (+3 more)

Single-crystal diamond combines exceptional optical, thermal, and mechanical properties while hosting optically addressable and spin-coherent colour centres, making it a promising platform for integrated quantum and nonlinear photonics. However, practical post-fabrication mechanisms for dynamically controlling and tuning monolithic diamond photonic circuits remain limited. Here, we demonstrate all-optical modulation and long-lived tuning of suspended diamond Fabry–Perot nanobeam cavities containing nitrogen-vacancy centres. Under 532~nm illumination, the infrared (1000 to 1100~nm) cavity response is governed by two competing contributions: a well-understood thermo-optic red-shift, and a novel charge-mediated blue-shift that we attribute to the free-carrier plasma dispersion effect. With 10~mW of 20~kHz-modulated green light, we achieve an infrared modulation depth of approximately 45% of the available reflection contrast. Green illumination also produces quasi-permanent photo-refractive resonance blue-shifts, with a maximum observed tuning of 3.15~nm (0.87~THz), without measurable degradation of the cavity linewidth or contrast. Achieving the same cavity shift in a lithium-niobate Pockels modulator would require 200 to 500~V across a \(5~\mu\mathrm{m}\) electrode gap. These results establish a monolithic diamond nanophotonic platform combining agile and reversible modulation with long-lived optical reconfiguration, two key ingredients in photonic technologies.
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All authors Yuchun Zhu, Amirali Arabmoheghi, Nicolas Le Thomas, Niels Quack, Valentin Goblot, Christophe Galland

Optics · Cross-listed from cond-mat.quant-gas

Second-order coherence properties of ultrafast polariton dynamics in plasmonic lattices

Evgeny A. Mamonov, Lukas Freter, Sioneh Eyvazi et al. (+2 more)

The first-order coherence properties of strongly coupled systems supporting polariton lasing and Bose-Einstein condensation (BEC) have been thoroughly studied and show consistent results. In contrast, second-order coherence properties have been found to vary for different systems, and the second-order coherence function can deviate from the value of one, typical for atomic BEC, revealing super-Poissonian fluctuations even above the BEC/polariton lasing threshold. This calls for a deeper understanding of the emission statistics and dynamics in light-based condensates, especially in the non-equilibrium regime. Here we demonstrate a coherent state of polariton emission from a plasmonic lattice measured as the second-order coherence function value separately for $\mathrm{\Gamma}$- and non-$\mathrm{\Gamma}$-point radiation (ground state and high-energy tail). We observe a high degree of coherence with the value $g^{(2)}(\tau=0)-1<10^{-4}$. We also demonstrate the ultrafast ($>$1 THz) nature of the dynamics. The process can be interpreted as a BEC with ultrafast, sub-50-fs thermalization, but we also suggest an alternative explanation as superradiance in a system where the emitters have vibrational degrees of freedom.
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All authors Evgeny A. Mamonov, Lukas Freter, Sioneh Eyvazi, Elliot W. Lloyd, Päivi Törmä

Accelerator Physics

Input to the SCAC Facilities Subcommittee from the U.S. Muon Collider Collaboration

S.Jindariani, T.Holmes, P.Meade et al. (+5 more)

This document presents input from the U.S. Muon Collider Collaboration to the SCAC Facilities Subcommittee. It outlines the scientific motivation for a future Muon Collider, the R&D and demonstration program needed to establish its feasibility, and its relevance to U.S. facilities planning for 2026-2036. It also discusses opportunities for leveraging existing U.S. capabilities, developing the accelerator workforce, and building synergies with other DOE programs and international efforts.
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All authors S.Jindariani, T.Holmes, P.Meade, K.DiPetrillo, K.Kennedy, L.Lee, S.Pagan Griso, D.Stratakis

Biological Physics · Cross-listed from cond-mat.stat-mech

Thermodynamics of the space of trajectories governed by a combination of two additive boundary functionals

V. V. Ryazanov

This paper extends the formalism of stochastic path-space thermodynamics by systematically expanding the space of thermodynamic variables with a spectrum of boundary and relative functionals of random processes. Generalizing the approaches introduced in preprints arXiv:2607.24078 and arXiv:2609.08477, we investigate the fluctuation statistics of a one-dimensional Ornstein-Uhlenbeck process with an asymmetric linear drift and a step penalty potential at the origin, which models the waiting phase of a molecular Brownian motor. Utilizing the Feynman-Kac formalism and the parabolic cylinder theory, a numerical scheme based on matching logarithmic derivatives via the secant method is constructed. A high-precision eigenvalues of the effective Hamiltonian is obtained, which define the cumulant generating function. We formulate a modified path-space fluctuation theorem of the Gallavotti-Cohen type for the conjugate drift current at a fixed integral occupation time of the system in the dissipative half-plane. The physical and thermodynamic significance of the new variables is elucidated. A combination of "residence time" and "integral current" functionals is applied to describe an ion channel sensitive to mechanical or electrical stimuli.
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Chemical Physics · Cross-listed from quant-ph

Minimal building blocks for molecular quantum circuits with exact spin symmetry

Mengwei Liu and Zhenyu Li

Preserving particle number and spin helps quantum circuits target molecular electronic states, but does not guarantee access to every state with the required quantum numbers. We determine which additional operations, combined with spin-independent orbital rotations connecting all spatial orbitals, generate every real state-space rotation within each complete subspace of fixed particle number $N$, total spin $S$, and spin projection $M_S$. We consider spin-free molecular calculations in real orbitals, without an additional spatial-symmetry restriction, and continuously tunable operations that preserve particle number, full spin symmetry, and real amplitudes. Below the maximal-spin limits set by the electron and hole numbers, repeated singlet-pair transfer between any two fixed spatial orbitals is sufficient. On nontrivial maximal-spin boundaries, pair transfer vanishes, and an additional generator built from one- and two-electron terms is sufficient exactly when its action in the target subspace is not a linear combination of orbital-rotation generators. The minimum number of spatial orbitals needed by one additional generator is two in the interior and three on nontrivial boundaries, even when terms involving more than two electrons are allowed. Both minima are attained using only one- and two-electron terms. The three-orbital optimum rotates two orbitals according to the occupation of a third, and its unitary factors exactly into eight commuting Pauli rotations. Molecular benchmarks show that this operation removes the observed boundary energy-error plateaus, while sparse interior constructions attain the prescribed energy accuracy with fewer compiled CNOT gates in selected fixed-orbital comparisons.
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Computational Physics · Cross-listed from hep-ex

Trace isotopes set the neutron horizon of liquid argon

Yasser Maghrbi

Near 57 keV, destructive interference makes argon-40 almost transparent to neutrons. The 0.4% of argon-36 and argon-38 in natural argon then supply over 90% of its opacity, amplified 230-fold. Published transmission data rule out the argon-36 evaluation FLUKA uses by default, even with every other isotope made transparent, and bound its cross section in the window to 2-11 b. In a DUNE-scale detector, switching to the data-consistent evaluations moves the fiducial fraction of argon-41 calibration captures by 9-13% while the total yield changes by only 2%: the effect is on where captures occur, not how many.
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Atomic and Molecular Clusters · Cross-listed from cond-mat.quant-gas

Finite-momentum trimers and Cooper quartets in a one-dimensional Fermi gas with coexistent $s$- and $p$-wave interactions

Yixin Guo

We study finite-momentum trimers and Cooper quartets in a one-dimensional two-component Fermi gas with coexistent $s$- and $p$-wave interactions, regularized in the relative momentum of each pair so that they remain Galilean invariant. Pauli blocking alone then makes the trimer dispersion deviate from free center-of-mass motion, so the trimer energy can be lowest at finite total momentum. Allowing this motion expands the $abb$ region among pairs and trimers and removes the region where an odd-wave pair is lowest. The $aabb$ quartet lies below all these branches at every sampled coupling, and in a strip starting on the crossing of the two dimer-pair channels its lowest breakup channel is a moving $abb$ trimer and an atom. At weak interspecies attraction, a variational bound shows that two odd-wave Cooper pairs bind into a quartet, whose binding exceeds that of the coexisting trimer by orders of magnitude as the attraction weakens. At stronger interspecies attraction, the quartet binding relative to two unlike-species dimers disappears when the odd-wave interaction is switched off, although the even-wave interaction dominates the interaction energy. Relative to the in-vacuum case, the Fermi sea enhances the weak-coupling quartet binding, and at fixed scattering lengths the quartet binding grows with density while the coexisting trimer becomes much shallower. These results show that neither the most strongly bound pair nor the dominant interaction energy alone determines whether the quartet binds.
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Physics and Society

An LLM-powered Agent Framework for Heterogeneous Evacuation Behavior Modeling under a Moving Threat in a Public Plaza

Jian Ma, Runxin Yu, Tianyu Tang et al. (+1 more)

Modeling heterogeneous evacuation behavior under a moving threat is difficult because human perception, memory, and evidence evaluation are not well captured by fixed rules. We propose a novel LLM-powered agent-based framework to represent these internal decision processes. Each pedestrian agent perceives a private symbolic ASCII view, maintains a Memory-based Knowledge Graph derived solely from individual observations, and makes decisions through persona-conditioned prompts under a common sampling configuration. A compressed decision context with stateless memory preserves trial-and-error experience across turns while excluding reasoning traces, and a validation engine separates behavioral choice from physical feasibility by executing routes only over observed terrain. We evaluated eight personality compositions in eight paired randomized blocks within a simulated public plaza. Usable-exit knowledge was strongly associated with evacuation success: 89.5% of agents possessing such knowledge evacuated, compared with 1.05% of those without it. Personality compositions also differed in their evaluation of remembered threat evidence: the proportion of danger assessments varied by 0.265, while high-urgency, low-directness decisions ranged from 11.41% to 34.33%. After direct threat sightings, responses converged, with 99.6% of assessments classifying the situation as dangerous. Movement was selected in 99.8% of decisions. Overall, evacuation outcomes were strongly associated with information access, while evacuation time was jointly associated with spatial geometry, information, and affect. The framework provides an auditable approach to generating endogenous behavioral heterogeneity through persona-conditioned LLM agents in crowd-evacuation simulations.
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All authors Jian Ma, Runxin Yu, Tianyu Tang, Xiaolian Li

Fluid Dynamics

Rheotaxis of a Microswimmer in Poiseuille Flow

Baopi Liu, Peng Wang, Xu-Ming Wang et al. (+1 more)

We investigate the motion of a spherical microswimmer in a planar Poiseuille flow using analytical calculations and numerical simulations. Our results show that the microswimmer's orientation undergoes periodic oscillations governed by pendulum-like dynamics. The oscillation period is proportional to the channel width and to the complete elliptic integral of the first kind evaluated at the maximum orientation angle, and inversely proportional to the square root of the product of the maximum flow speed and the self-propulsion speed. Based on the net displacement along the flow direction within one oscillation period and the signs of the maximum and minimum velocities, we identify five motion states: upstream, oscillatory upstream, zero-drift oscillatory, oscillatory downstream, and downstream motion. The net displacement is jointly determined by the ratio of the self-propulsion speed to the maximum flow speed and the complete elliptic integrals of the first and second kinds. The signs of the maximum and minimum velocities are determined by the speed ratio and the cosine of the orientation angle. Flow nonuniformity promotes upstream migration, whereas inertial lift produces negligible radial displacement during one oscillation period. These findings identify the key parameters governing the motion of spherical microswimmers and provide significant implications for understanding microorganism motility and designing microrobots with prescribed motion states.
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All authors Baopi Liu, Peng Wang, Xu-Ming Wang, Bing Miao

Computational Physics

From Bellissard's gap labeling to atomistic quasiperiodic bilayers

Thomas D. Kühne, Vladislav Efremkin and Emil Prodan

Bellissard's framework uses covariant observables to describe aperiodic solids. We examine how butterfly-like spectra in twisted bilayers can be related to bulk gap labels and topological response. A bulk gap permits a spectral projector and an integrated density of states. A topological response requires an additional pairing of that projector. In an illustrative finite honeycomb bilayer, an exact second-moment identity isolates the interlayer contribution to spectral variance. Angle-resolved spectra, finite state counts, an uncoupled reference, and size and broadening checks show how coupling redistributes spectral weight without assigning a bulk gap label. We then examine the requirements for atomistic electronic-structure calculations, including nonorthogonal orbitals, projected densities of states, and basis functions that move during relative sliding. The resulting framework specifies the steps needed to connect atomistic spectra with bulk state counting and topological response.
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Plasma Physics

Electron Rephasing in a Truncated Tunable Plasma Channel

Arujash Mohanty, Santhosh Krishnamurthy, Yinren Shou et al. (+6 more)

We report the acceleration of stable electron beams with energies up to 1.5 GeV using a 50 TW laser pulse guided in a preformed plasma channel generated by an axiparabola-focused heater pulse. Varying the channel length changes the plasma density beyond the channel end and produces distinct electron spectra. A short channel causes a large decrease in bubble size after the truncated channel, leaving only part of the electron bunch in the accelerating phase and resulting in a quasi-monoenergetic peak. For a longer channel ending near the target density down-ramp, the smaller density increase rephases and further accelerates a larger fraction of the bunch, producing a continuous high-charge spectrum. Hydrodynamic and particle-in-cell simulations reproduce the observed spectral evolution. Together, the measurements and simulations identify channel length as a key control parameter in guided laser-wakefield acceleration.
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All authors Arujash Mohanty, Santhosh Krishnamurthy, Yinren Shou, Sheroy Tata, Anton Golovanov, Anda-Maria Talposi, Aaron Liberman, Eyal Kroupp, Victor Malka

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

Deep Learning GW Quasiparticle Hamiltonians for Many-Body Excited-State Electronic Structure at Scale

Xiaoxun Gong, Zechen Tang, Woochang Kim et al. (+4 more)

Accurate quasiparticle electronic structures are the foundation for understanding excited-state properties of materials and explaining optoelectronic, quantum, and transport phenomena. First-principles GW calculations nevertheless remain computationally intensive for large or configurationally complex systems. Here we introduce DeepH-GW, a deep-learning framework that predicts an effective GW quasiparticle Hamiltonian directly from atomic structure. Building on the local, equivariant message-passing architecture of DeepH, DeepH-GW is trained on high-fidelity plane-wave GW calculations through a real-space Hamiltonian-reconstruction interface. This approach combines the systematic accuracy and broad chemical applicability of plane-wave methods with linear-scaling neural-network inference. Across the systems examined, DeepH-GW reproduces quasiparticle band structures with errors on the order of a few meV. Moreover, we show that, despite the intrinsic nonlocality of many-body interactions, DeepH-GW exhibits strong cross-scale transferability from relatively small training structures to substantially larger supercells. We demonstrate that the framework can accurately capture GW-level electron-phonon band-gap renormalization through predictions in supercells with thermal displacements, illustrating the power of the approach. DeepH-GW therefore provides a practical route toward large-scale many-body simulations and foundation models for excited-state electronic structure.
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All authors Xiaoxun Gong, Zechen Tang, Woochang Kim, Yang Li, Wenhui Duan, Yong Xu, Steven G. Louie

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

Ohm's law for information revealed by a skyrmion Maxwell's demon

Soma Miki, Yoshishige Suzuki, Ryo Ishikawa et al. (+10 more)

Reducing the energy cost of computation-a pressing issue in the age of AI-requires a framework for circuit design based on information thermodynamics. By extending non-equilibrium statistical mechanics to information thermodynamics, it has been shown that a probability flow carrying information-hereinafter referred to as an 'information current'-is driven by its conjugate thermodynamic force, namely 'information affinity'. Since information affinity plays a role analogous to that of voltage in an electrical circuit, it is suggested that information transport also follows a linear response relationship analogous to Ohm's law. However, despite this theoretical prediction, experimentally establishing an Ohm-like constitutive relation for information transport remains an important unsolved problem. Here, we realise an information engine consisting of two magnetic skyrmions undergoing Brownian motion at room temperature. We demonstrate that the resulting information current is proportional to the information affinity generated by Maxwell's demon over a relatively wide range, establishing Ohm's law for information. Furthermore, we clarify that, in real information circuits, both Ohm's law for information and Kirchhoff's voltage law must be slightly modified to account for interactions between information carriers and the scattering of the information current.
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All authors Soma Miki, Yoshishige Suzuki, Ryo Ishikawa, Yuki Hibino, Shunya Morishita, Hiroto Imanishi, Keigo Adachi, Yoichi Shiota, Takayuki Nozaki, Minori Goto, Hikaru Nomura, Shigemi Mizukami, Eiiti Tamura

Chemical Physics

A systematic comparison of hard- and soft-constrained physics-informed molecular machine learning with the Clapeyron equation

Jan Pavšek, Jan G. Rittig and Alexander Mitsos

In molecular machine learning (ML), significant progress has been made on integrating fundamental thermodynamic relations into ML models. Such physics-informed approaches can be categorized as hard-constrained, where the thermodynamic relations are embedded in the model architecture, and soft-constrained, where relations are included in the training loss. While both approaches have been applied to various property prediction tasks, a systematic comparison on experimental data is lacking. We herein compare hard- and soft-constrained approaches on a numerically challenging case study: the prediction of vapor pressure, saturated liquid and vapor molar volumes, and enthalpy of vaporization as functions of temperature for single-species vapor-liquid equilibrium, related by the exact Clapeyron equation. Furthermore, soft-constrained approaches in molecular ML typically balance data and physics losses with a fixed weighting factor, requiring careful tuning. To overcome this, we investigate the augmented Lagrangian method (ALM), well established in constrained optimization. We find that for the soft-constrained approach, using the ALM improves prediction performance in terms of constraint satisfaction by factor 2 and reduces training epochs compared to using a fixed penalty by 30%. Hence, in the soft-constrained approach, the use of the ALM is always recommended. The hard-constrained approach, which entails additional architectural design choices, can reach on par accuracy with the soft-constrained approach, at even higher thermodynamic consistency, reaching 12 orders of magnitude closer approximation of the Clapeyron equation. Overall, the hard-constrained approach is most promising when thermodynamic consistency is critical, yet requires tailoring the ML model architecture to the respective thermodynamic relation.
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Physics and Society

NuPaD: A Generative AI Framework for Fostering Deep Learning in Subatomic Physics

Chong Qi

The rapid adoption of generative artificial intelligence (GenAI) in higher education has introduced a critical pedagogical paradox: while these systems possess extraordinary capacity for information retrieval and synthesis, their default operational mode of supplying immediate, unprompted answers actively undermines the cognitive processes upon which genuine scientific understanding is built. This paper presents NuPaD (Nuclear & Particle Physics – Deep Learning Tutor), a novel pedagogical framework designed for the graduate-level subatomic physics curriculum. For such advanced courses, instruction naturally shifts toward inquiry-driven, problem-based learning, making it an ideal environment to use GenAI to explore complex, open-ended physical questions rather than merely querying established facts. The framework consists of three tightly coupled and easy-to-use components: a primary agent instruction file that enforces a structured problem-based learning protocol, a purpose-built textbook optimized for precise parsing by privacy-preserving local GenAI, and a concise companion file that bridges the knowledge gap between the textbook and GenAI, alongside a comprehensive dynamic skill set for specialized tasks. We explain in detail the architectural principles of the modular NuPaD framework, the design philosophy of the Markdown-native textbook format, and the underlying GenAI regulation principles. By redefining the interaction loop between student and model, this framework transforms GenAI from a passive answer engine into an active, personalized tutor, ensuring that it accelerates rather than bypasses the development of deep learning and scientific reasoning.
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