Instrumentation and Detectors
Characterization of p-stop isolation implants in silicon sensors using MOSFET structures
Thomas Bergauer, Suman Chatterjee, Marko Dragicevic et al. (+2 more)
Metal-
oxide-
semiconductor field-effect transistor (MOSFET) test structures are investigated to characterize p-stop isolation implants between n-type electrodes in p-type silicon sensors. The device transfer characteristics are measured as a function of the voltage applied to the backside to extract the threshold voltage, which quantifies inter-electrode isolation, and the field-dependent mobility parameters. We present a methodology to reconstruct depth-dependent doping profiles from the threshold voltage characteristics, accounting for the localized space-charge effects and electric-field screening induced by the p-stop implants. The study evaluates the sensitivity of this technique to various p-stop geometries and doping concentrations across different wafer types. The results demonstrate the potential of MOSFET-based structures as a non-destructive diagnostic for monitoring p-stop consistency and inter-electrode isolation properties in silicon detectors.
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All authors Thomas Bergauer, Suman Chatterjee, Marko Dragicevic, Ioannis Kopsalis, Veronika Kraus
Optics
Calibration of systematic distortions in quantum emitter localization microscopy for deterministic nanophotonic fabrication
Chenxi Ma, Maximilian Heller, Timon Handrup et al. (+10 more)
Quantum photonic technologies greatly benefit from
quantum light emitters with high brightness, indistinguishability, and reliable polarization characteristics. Achieving optimal performance relies on the accurate localization of emitters and their deterministic integration into tailored photonic structures with nanometer-scale accuracy. Although marker-based photoluminescence imaging techniques can achieve statistical fitting uncertainties below 10 nm, the ultimate integration yield is often limited by uncorrected systematic distortions in custom cryo-optical setups that compromise metrological accuracy. Here, we present an in situ calibration protocol that uses lithographically defined gold nanodisk arrays as references to calibrate optical distortions with a Zernike vector-field model. On held-out validation patterns beyond the calibration
dataset, this correction reduces the residual systematic bias to 5.3 nm with a 2D scatter of 24.6 nm across the analyzed field of view. Furthermore, we demonstrate that applying this correction to the deterministic fabrication of circular mesa structures around
semiconductor quantum dots reduces the variance in emission polarization by 49%, indicating improved registration accuracy. This calibration strategy offers a practical route to high-yield deterministic integration of
quantum emitters into scalable
quantum photonic
circuits.
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All authors Chenxi Ma, Maximilian Heller, Timon Handrup, Yiteng Zhang, Tobias M. Krieger, Thomas Oberleitner, Zenghui Jiang, Xian Zheng, Eddy P. Rugeramigabo, Folke Dencker, Armando Rastelli, Fei Ding, Michael Zopf
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Data-driven atomistic modelling of hybrid halide perovskite passivation
Laura-Bianca Paşca, Henry J. Snaith and Volker L. Deringer
Molecular passivation of surface defects is key to improving the optoelectronic performance of hybrid halide perovskite materials, but the underlying atomistic mechanisms are incompletely understood. While machine-learned interatomic potentials are now widely used to simulate complex molecular and crystalline systems, their application to experimentally-realistic scenarios - such as molecules coordinating to perovskite surfaces - is still far from trivial. Here, we describe a multistep training pipeline, resembling continuous fine-tuning used for large
language models, to underpin atomistic modelling and computational experiments in this domain. Our protocol involves two components: (i) a large, curated, and open
dataset of diverse metal and hybrid halide perovskite structures ('hyP-26'); and (ii) a small, specialised
dataset for an amino-silane molecule passivating the surface, providing highly specific information for fine-tuning. We apply this approach to explore collective behaviour at a mixed-composition halide perovskite surface passivated with a varying coverage of amino-silane molecules, revealing an
evolution of interactions with increasing molecular surface coverage.
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Biological Physics
Energetic Protection, Monotonicity and Switching Far from Equilibrium
Uğur Çetiner
At
equilibrium, the ratio of two steady-state probabilities is a Boltzmann factor, set by a free-energy difference. Such ratios are the natural, normalization-independent readouts of both thermodynamics and information processing, and are often used as a measure of fidelity in biophysical systems. What becomes of these ratios once a system is driven from
equilibrium, where the Boltzmann factor no longer holds? Representing Markov processes as graphs and their steady states as averages over a distribution on spanning trees, the arboreal distribution, we track the ratio $\pi_i/\pi_j$ under driving along energetic edges, where detailed balance is broken, relative to its
equilibrium value. Our central finding is that a chosen ratio can stay exactly locked to its
equilibrium value arbitrarily far from
equilibrium, a phenomenon we call energetic protection, whenever an algebraic equality between spanning-tree weights holds. Just as detailed balance constrains rates around cycles, energetic protection constrains weights across trees, providing a new mechanism for robustness against fluctuations in the driving force, such as variations in ATP concentration. Away from this equality, single-edge driving collapses the response onto two arboreal coefficients and forces it to be monotonic, so nonmonotonic single-edge control is impossible at any strength. With two energetic edges, protection and monotonicity combine into a thermodynamic switch that holds a function at its
equilibrium value for as long as desired and releases it sharply.
Equilibrium is known for the limits it places on information processing. We show that new constraints, both no-go principles and exact invariances, survive far from
equilibrium. These results reveal how the localization of energy expenditure governs the functional logic of nonequilibrium systems in physics and biology.
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Fluid Dynamics · Cross-listed from astro-ph.SR
The steady incompressible ideal free-boundary flows of a hydromagnetic star
B. C. Low and S. W. McIntosh
This self-contained theoretical study treats incompressible, free-boundary flows in a gravitating, ideal hydromagnetic
star abutting
vacuum, centered on the steady field-aligned flows of Chandrasekhar, Prendergast and Tsinganos, together with a novel family of steady cross-field flows, all as solutions of the axisymmetric Tsinganos equation. In the absence of compressive waves and shocks, an incompressible fluid evolves by its frozen-in
magnetic field propagating as transverse Alfvèn waves along the field lines, with pressure reacting instantly in place. The origin of the steady flows rests on the Parker theory that everywhere-continuous flows are the exception rather than the rule because of a basic propensity for tangential field/flow discontinuities. Astrophysical viscosity and electrical resistivity are not zero but are significant only over scales much smaller than macroscopic scales. Such near-ideal fluids have the same propensity for tangential discontinuities but the near-discontinuities readily dissipate by small-scale, viscous-resistive
magnetic reconnections. The study treats the strictly ideal fluid separately in its own right, to construct a conceptual understanding of the turbulent creation of a steady flow in a self-organizing near-ideal fluid via irrepressible energy loss and field-
topology changes as episodic reconnections run out of free energy. The study suggests that metastable storage of steady
vortices and twisted fields is a natural product of the
solar internal dynamo, to explain a recent, multi-instrument observation of
solar-coronal eruptions persisting coherently in preferred longitudinal locations over
solar-rotational timescales.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci
Phase-field modeling of elastically driven abnormal grain growth
Yazhuo Liu, Yin Zhang, Kunqing Ding et al. (+6 more)
Grain-refined metals typically exhibit high strength, yet their engineering applications are often constrained by grain coarsening under thermo-mechanical loading. Recent experiments have revealed abnormal grain growth (AGG) in ultrafine-grained Ni thin films subjected to cyclic loading at room temperature. Unlike conventional AGG, which generally requires significant plastic deformation or high temperatures, this phenomenon occurs within the regime of macroscopic elastic deformation. This AGG is characterized by the preferential growth of grains with an in-plane <100> orientation aligned with the loading direction. Here, we investigate the underlying physical mechanisms by combining phase-field simulations with micromechanical analysis. The results indicate that elastic energy reduction provides a thermodynamically plausible driving force for this orientation-selective grain growth. Phase-field simulations reveal the
evolution kinetics of AGG and confirm that local grain geometry and stress states play critical roles in determining the grain growth pathway. By applying this framework to systems with varying elastic anisotropy, we establish a general approach for investigating elastically driven AGG in polycrystalline materials.
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All authors Yazhuo Liu, Yin Zhang, Kunqing Ding, Yichen Yang, Alejandro Barrios, Xavier Maeder, Olivier Pierron, Xing Liu, Ting Zhu
Instrumentation and Detectors · Cross-listed from astro-ph.IM
Trigger system for the Payload for Ultrahigh Energy Observations (PUEO) balloon-borne neutrino detector
Q. Abarr, J. Alfaro, P. Allison et al. (+67 more)
The Payload for Ultrahigh Energy Observations (PUEO) is a NASA balloon-borne instrument for the detection of ultra-high energy (UHE)
neutrinos with energies above $10^{17.5}~\textrm{eV}$ via either the Askaryan effect or geomagnetic emissions from an upward-going air shower. The main instrument trigger system for PUEO is a fully digital supersample rate beamformer based on 24 Xilinx
Radio Frequency System-on-a-Chip (RFSoC) digitizers sampling 192 channels operating at $3~\textrm{GSa/s}$ and a system clock frequency of $375~\textrm{MHz}$. The trigger implements frequency band conditioning, dynamic
radio-frequency interference (RFI) rejection, and matched filtering, with significant emphasis on optimization to reduce both the power and resource usage while maintaining sensitivity. The system implements 48 total synthetic
antenna beams with up to 8
antennas each, covering a $\sim25^\circ$ range in zenith and $\sim60^\circ$ range in azimuth. Preflight testing demonstrated a trigger performance of a minimum signal-to-noise ratio (SNR) of $\sim1.5$ using simulated signals while consuming between $5-7~\textrm{W}$ in the trigger logic.
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All authors Q. Abarr, J. Alfaro, P. Allison, J. Alvarez-Muñiz, T. Anderson, H. Barnett, A. Basharina-Freshville, J. J. Beatty, L. Beaufore, D. Z. Besson, M. Betts, R. Bose, D. Braun, B. Chamanbahar, P. Chen, Y. Chen, J. M. Clem, T. Coakley, A. Connolly, K. Couberly, L. Cremonesi, A. Cummings, P. Dasgupta, C. Deaconu, J. Flaherty, C. Godden, P. W. Gorham, C. Hornhuber, J. Hoffman, K. Hughes, A. Hynous, A. Jung, A. M. Kofman, Y. Ku, D. Kullgren, C.-Y. Kuo, P. Linton, L. Lisalda, T. C. Liu, W. Luszczak, S. C. Mackey, Z. Martin, K. McBride, C. Miki, J. Nam, R. J. Nichol, A. Novikov, A. Nozdrina, E. Oberla, S. Prohira, H. Pumphrey, D. Radomski, B. F. Rauch, R. Scrandis, D. Seckel, M. F. H. Seikh, J. Shiao, G. Simburger, J. Tutt, A. G. Vieregg, S.-H. Wang, D. Washington, C. Welling, P. Windischhofer, S. A. Wissel, C. Xie, J. Yao, R. Young, E. Zas, A. Zeolla
Optics
Photon-conserving Raman soliton attractors in focusing and defocusing Kerr media
Weiye Huang, Junhong Yang, Tao Sun et al. (+6 more)
The sign of the Kerr nonlinear coefficient has long been regarded as irrelevant to the direction of the Raman-induced
soliton self-frequency shift. Yet the standard generalized nonlinear Schrödinger equation (GNLSE) predicts a frequency shift that depends on the sign of the nonlinearity, which leads to an unphysical blue shift in the defocusing case. We resolve this inconsistency by deriving the time-domain form of the
photon-conserving GNLSE (pcGNLSE) from its established frequency-domain counterpart. The derivation reveals that
photon-number conservation imposes two sign modifications relative to the standard GNLSE: the Raman-shift coefficient acquires the absolute value of the Kerr nonlinear coefficient in place of its signed counterpart, and the self-steepening-Raman dissipation term likewise carries an absolute-value prefactor rather than a signed one. These two modifications jointly guarantee a universal spectral
redshift and monotonically decreasing pulse energy during propagation, irrespective of the signs of the Kerr nonlinear coefficient and its frequency derivative. Applying the method of moments to the time-domain pcGNLSE with appropriate chirped ansätze, we derive closed-form
evolution equations for five pulse parameters and establish explicit attractor conditions under which bright or dark Raman
solitons propagate with constant peak power. Direct numerical integration of the pcGNLSE confirms all analytical predictions and demonstrates that the standard GNLSE fails qualitatively, predicting unphysical energy growth and spectral blueshift in the negative-nonlinearity regime. The results provide a rigorous analytical framework for Raman
soliton dynamics in materials with negative third-order susceptibility, with direct implications for
soliton-based devices in emerging
semiconductor waveguide and microresonator platforms.
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All authors Weiye Huang, Junhong Yang, Tao Sun, Qian Gao, Peilong Yang, Jintao Fan, Günter Steinmeyer, Jinhui Yuan, Chao Mei
Biological Physics · Cross-listed from cond-mat.soft
Swimming-limited aggregation of bacteria in liquid crystals
Guillaume Sintès, Martyna Goral, Teresa López-León et al. (+2 more)
Aggregation and fragmentation processes are widespread in engineering and the natural world. Here, we investigate a distinct colloidal aggregation mechanism in an active system of motile bacteria in highly anisotropic environments. Specifically, we examine Escherichia coli bacteria swimming in one-dimensional confinement within nematic
liquid crystals and observe long-lived chains of bacteria swimming along the nematic director. Crucially, we find that longer chains swim faster, in apparent contradiction to fundamental force-balance models that predict the swimming speed to be independent of chain length, as chains should swim at the average speed of their individual components. The seeming discrepancy is resolved by recognizing that chains do not form randomly but self-organize due to the relative velocities between bacteria. To elucidate the physical mechanism behind this active aggregation process, we combine our experimental findings with a minimal model of nearest-neighbour aggregation and
agent-based simulations of active particles aggregating in one dimension. Consistent with experimental observations, our
agent-based simulations reveal a positive correlation between the length and speed of dynamically self-assembled chains of active particles, with the correlation depending on the variance of the individual speed distribution and diminishing over time. Together, our experiments and theoretical models indicate a distinct regime of swimming-limited aggregation whose
evolution is constrained by the intrinsic speed distribution of active
agents, providing new insight into bacterial self-organization.
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All authors Guillaume Sintès, Martyna Goral, Teresa López-León, Anke Lindner, Maria Tătulea-Codrean
Atomic Physics
Fast Pulses for High-Fidelity Circularization of Interacting Rydberg atoms
Matthias Hüls, Aurore A. Young, Clément Sayrin et al. (+6 more)
Circular states in Rydberg atoms offer a promising platform for
quantum computation,
quantum simulation and
quantum sensing. However, the final step of their preparation - termed as circularization, a process that involves the transfer of a large amount of angular momentum quanta to the valence electron by means of
radio-frequency (RF) pulses - remains as a major bottleneck for all technological applications based on interacting circular Rydberg atoms. Even though successfully implemented to circularize an atom cloud in the dilute regime, previous efforts to speed up the circularization process have focused on the single-atom case, thereby neglecting the interactions which constitute one of the main resources for
quantum simulation and computation. In this theoretical work we show how interactions between two atoms disturb the efficiency of pulses designed for single atoms and identify shifts induced by the interactions on relevant transition energies as the dominant disturbance. We demonstrate that the initial efficiency of single-atom pulses can be restored by adapting them to these shifts. Our approach is based on a simple functional form depending only on two linear parameters, which we derive analytically. The adapted pulses prepare two $^{87}$Rb atoms after $65 \,$ns in a $n=52$ circular state with a fidelity of at least $95\,\%$ for interatomic distances down to $6.5\,\mu$m and for all angular configurations, while also complying experimental amplitude and frequency constraints. Finally, we show that when combining our adapted pulses with Krotov's pulse-shaping
algorithm we obtain high-fidelity pulses for any pair arrangement with interatomic distances larger than $5.9\,\mu$m. This work demonstrates that fast RF pulses can circularize interacting Rydberg atoms, paving the way toward their technological application.
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All authors Matthias Hüls, Aurore A. Young, Clément Sayrin, Michel Brune, Jean-Michel Raimond, Tommaso Calarco, Felix Motzoi, Robert Zeier, Eloisa Cuestas
Data Analysis and Statistics · Cross-listed from astro-ph.SR
The Recurrent Nova TCrB: A Method for Predicting the Next Eruptive Event in Nova Cycles
Stefano Sello
The symbiotic recurrent nova (SyRNe) TCrB (T-Coronae Borealis) is perhaps the most famous example of the group of known four symbiotic nova systems, for which at least two previous nova eruptions are known and accurately recorded: in 1866 and 1946. B.E. Schaefer (2023) has identified the dates of two other previous eruptive events: in 1787 and 1217. Its peak magnitude V was found to be 2.50+-0.10, making it the brightest of its class. In its quiescent phase, TCrB is the brightest of all known novae, with a mean magnitude of 9.8. Careful studies, especially photometric ones, have led to different predictions for the next nova eruption, taking into account the recurrence times extrapolated from previous eruptions, which an average value about 80 years. Schaefer, in particular, has produced various forecasts, including one made in 2023 based on B and V light curves for the period: 1842-2022, which predicts the next nova eruption should occur in 2025.5+-1.3 and is therefore still valid today. Using the Schaefer's remarkable work in accurately determining the key physical parameters that drive the dynamics of the TCrB symbiotic system, we propose here a new semi-empirical method to derive the variations in the nova recurrence time, Trec, and thus obtain a forecast estimate for the next eruption for the date: 26-Feb-2027, which is currently compatible and consistent with the observed behavior and would also justify the supposed "delay" for the next event of this nova as commented by various authors.
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Chemical Physics
cQED-iCIPT2: A Near-Exact Method for Polaritonic Chemistry
Ning Zhang and Wenjian Liu
Strong light-matter coupling in optical cavities provides a versatile platform for modulating chemical structure, reactivity, and spectroscopy, and hence motivates the development of ab initio cavity
quantum electrodynamics (cQED) methods that can treat the electronic and photonic degrees of freedom on an equal footing. We present such a method, cQED-iCIPT2, by combining the near-exact iCIPT2 (iterative configuration interaction with selection and second-order perturbation theory) with the cQED
Hamiltonian in two ways, cQED-PN-iCIPT2 and cQED-CS-iCIPT2. The former works directly in the
photon-number representation, whereas the latter employs a coherent-state transformation that restores origin invariance of the cQED
Hamiltonian and avoids artificially strong coupling in charged systems. To efficiently handle the tensor-product structure of the electron-
photon wavefunction, we introduce a graded configuration space organized by
photon numbers and decompose the key computational steps (selection, diagonalization, and perturbation correction) into intra- and inter-subspace steps, so as to maximize the reuse of the existing infrastructure in the MetaWave platform (J. Phys. Chem. A 2025, 129, 5170). The selection step enables automatic determination of the optimal number of
photons without a priori truncation. The efficacy of the methods is showcased dissociation of N2, torsion of ethylene,
proton transfer reactions in malonaldehyde and aminopropenal, and low-lying excited states of polyacenes. The results provide numerically accurate reference data and meanwhile reveal how the cavity can fine-tune reaction barriers, alter potential energy surfaces, and induce state crossings. As such, this work establishes a robust near-exact framework for polaritonic chemistry in the presence of both strong electron correlation and strong light-matter coupling.
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Biological Physics · Cross-listed from cond-mat.stat-mech
Semi-Markovian switching in a fluctuating harmonic trap: An age-structured formulation
Derek Frydel
We study a Brownian particle in a harmonic trap whose stiffness switches between two values with arbitrary waiting-time statistics, generating semi-Markovian dynamics. To treat the resulting temporal
memory, we formulate the problem in an enlarged age-structured state space, restoring Markovianity and yielding a local Fokker–Planck description. Within this framework, we derive exact steady-state integral equations for the spatial and birth distributions and obtain exact expressions for stationary moments, injected power, and potential energy. In the second part of the paper, we analyze the
stochastic-resetting limit, corresponding to a particle alternately released and trapped. By representing the stationary spatial distribution as a superposition of Gaussian states with fluctuating variance, the problem can be reformulated as a switching process in variance space. This yields exact integral equations for the variance distributions and leads to a simplified description amenable to direct analytical treatment.
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Biological Physics
Biophysics of the Pyrenoid
Charley Schaefer and Mark Leake
Phase-separated
liquid droplets organize molecules in
cells, but the underlying physical principles differ from abiotic mixing and quantitative rules in living systems remain poorly understood. The pyrenoid – a
liquid-like organelle that enhances photosynthetic carbon fixation in algae and hornworts – provides an unusually tractable model system. Here, we review recent advances in our understanding of pyrenoids from the perspective of biophysics. We highlight how reaction-
diffusion models connect compartment architecture to catalytic performance, how soft matter theories link molecular interactions to condensate assembly, and how modern experimental methods enable these predictions to be tested quantitatively. Recent studies suggest that pyrenoid function may be described by a small number of effective transport and reaction processes, while condensate assembly can be understood through molecular design parameters and thermodynamic constraints. Together, these findings establish the pyrenoid as a powerful system for investigating catalytic compartmentalization, biomolecular self-organization and the emergence of effective physical descriptions in living systems.
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Optics
Torsional selection rule for the spin–orbit conversion of light
Edilberto O. Silva
Standard Pancharatnam-Berry and linear-birefringent media convert optical
spin into orbital angular momentum (OAM) through an anisotropy director, a rank-two, headless field, and therefore obey the selection rule $\Delta\ell=2q$ per unit texture charge $q$. We show that a medium with
geometric torsion, the continuum limit of a screw-dislocation array, can convert
spin to OAM through the contortion of its material connection, which enters the effective paraxial dynamics as a rank-one vector field. The resulting selection rule is $\Delta\ell=q$. Its winding is fixed by geometry and
symmetry, not by a Pancharatnam–Berry director, and the process conserves the screw charge $\tilde J_z=L_z+(q/2)\sigma_z$ while exchanging $(2-q)\hbar$ of angular momentum per converted
photon with the defect
lattice. Paraxial simulations confirm the rule: a circular Gaussian input develops a stable, topologically quantized $\ell=+q$
vortex in the reversed helicity, with $83\%$ conversion over three Rayleigh ranges and no fine-tuning. We propose a polarization-resolved photonic-
lattice discriminator in which the slope of the measured OAM versus the independently written texture charge, one for torsion, two for birefringence, separates the two mechanisms.
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Physics Education
Measurement of the effect of member performances on team outcomes in two-stage exams
Hyewon Jang
Two-stage exams have been used in physics classrooms, yet no empirical study has examined the effect of individual member performances on team performance. Using direct measures of individual and team performances in two-stage physics exams, we study the effect of member performances on team outcomes. Our data reveal three results of interest. First, either the best or the mean of member performances significantly affects team performance, whereas the standard deviation of member performances has a weak effect. Second, member performances explain less than half the variance in team performances, indicating that team outcomes in two-stage exams are not determined simply by individual performances. Third, cross-validation shows that the best predictor of team performance is the best member's performance, highlighting the need to form balanced teams with high-scoring individuals distributed evenly throughout teams before team exams are conducted. As the first empirical analysis built on the input-process-output framework, this study provides researchers of two-stage exams with insight into how to investigate factors that can make team problem-solving more productive in the team round.
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Plasma Physics
SoPlasmaFoam: an OpenFOAM-based solver for streamer and dielectric barrier discharges with adaptive mesh refinement
R. Pasolari and K. Kourtzanidis
SoPlasmaFoam is an open-source, multi-region
plasma-dielectric solver built on OpenFOAM, integrated with the PETSc linear-
algebra suite (CPU and GPU back-ends), the blastAMR adaptive-mesh-refinement library (hexahedral and polyhedral meshes), and the ROUND family of high-resolution convective schemes. It solves drift-
diffusion-reaction transport for charged species, coupled self-consistently to Poisson's equation explicitly or semi-implicitly, with
plasma and dielectric regions joined by a monolithic multi-domain coupling for arbitrary curved interfaces. This work makes three contributions. First, a systematic assessment of convective schemes on a stiff scalar-advection problem and the positive-streamer
benchmark shows that Scharfetter-Gummel is stable but excessively diffusive on coarse meshes, while ROUNDF outperforms all tested TVD limiters and is recommended for streamer transport. Second, an analysis of Poisson-transport coupling shows that fixed-point correction loops critically control accuracy, that a semi-implicit Poisson formulation does not remove this requirement, and that coupling must be tightened even when Courant and dielectric-relaxation numbers are well below unity. Third, a drift-robust wall boundary condition acting on discretized
matrix coefficients is introduced, remaining accurate in the drift-dominated limit where conventional mixed-boundary mappings fail. The solver is validated against a low-pressure DC glow discharge and the positive-streamer
benchmark, and its multi-region capability is demonstrated on a nanosecond surface dielectric barrier discharge. Performance analysis confirms
memory-bound finite-volume scaling and shows that with AMR the solver is competitive with the fastest reported
plasma codes. The framework provides a modular foundation for multiphysics simulations in
plasma-assisted combustion,
plasma processing, and
plasma-based flow control.
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Fluid Dynamics
An SO(3) Gauge Theory of Turbulence with Spontaneous Symmetry Breaking
Ahmed Farooq
Fully developed isotropic
turbulence exhibits a dual nature: a continuous, scale-invariant energy cascade coexists with discrete, intense
vortex filaments. We show that this duality arises from a spontaneously broken SO(3) gauge
symmetry. By identifying the specific angular momentum $\mathbf{L} = \mathbf{r}\times\mathbf{u}$ as a non-Abelian gauge connection and the radial velocity $u_r$ as a
Higgs field, the turbulent
vacuum is described by the SO(3) Georgi-Glashow model. When the radial strain condenses, the
symmetry breaks SO(3) $\to$ U(1), generating a topological mass gap $M_W = gv$. This gap partitions the energy into a massless U(1) sector (the solenoidal background) that sustains the Kolmogorov cascade, and a massive SO(3)/U(1) sector that is confined to
vortex filaments. Using high-resolution DNS data (JHTDB, $Re_\lambda\approx433$), we empirically verify three key predictions: (i) the energy spectra obey a strict 1:2 equipartition over the inertial range, with a sharp divergence at $M_W \approx 40$; (ii) the radial
Higgs field extracted around isolated
vortex cores follows the exact BPS monopole profile $H(r)=\coth(r/\eta)-\eta/r$ with $\eta = 0.0093$ domain units and the VEV $v = 0.338$, identifying the ubiquitous "worms" as macroscopic 't Hooft-Polyakov monopoles; (iii) the Wilson loop computed from the velocity field exhibits a clean area law $\langle W_C \rangle \sim e^{-\sigma A}$ with string tension $\sigma = 0.303 \pm 0.009$, directly confirming the confining nature of the turbulent
vacuum.
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Optics
Two Photon excitation microscopy of individual Single-Walled Carbon Nanotubes
Nasim Akhtar, Marc Tondusson, Benjamin Flavel et al. (+2 more)
Two-
photon fluorescence imaging achieves deep-tissue penetration through long excitation wavelengths and nonlinear excitation confinement. The 1700 nm transparency window is particularly attractive, as it optimally balances tissue scattering and absorption. However, efficient fluorophores for two-
photon excitation in this window remain limited. Moreover the weak near-infrared emission of individual emitters, and the low
photon detection efficiency, has so far precluded single-particle imaging. Here, we characterize the two-
photon excitation properties of chirality-sorted pristine and
quantum color center-functionalized single-walled carbon nanotubes under 1700 nm excitation. By measuring and comparing their two-
photon action cross-sections, we identify
quantum color center-functionalized (6,5) nanotubes emitting at 1140 nm, as the most promising emitter, with an exceptionally large cross-section of (57 \pm 2).103 GM. Leveraging these favorable photophysical properties, we image individual nanotubes under 1700 nm excitation, to our knowledge the first demonstration of single-particle imaging at this wavelength. These results establish
quantum color center-functionalized (6,5) nanotube as a strong candidate for long-wavelength two-
photon imaging and lay the groundwork for deep-tissue single-particle imaging.
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All authors Nasim Akhtar, Marc Tondusson, Benjamin Flavel, Stéphane Bancelin, Laurent Cognet
Chemical Physics
Physically-Relevant Information Learning in High-Dimensional Time-Derivatives Spaces
Domiziano Doria, Matteo Becchi and Giovanni M. Pavan
Understanding the physics of many-body complex dynamical systems may be a non-trivial task. High-dimensional analysis approaches are often deemed necessary to prevent losing important information. Typically, these use order parameters or descriptors capturing information related to, e.g., relative positions,
symmetries, etc., of the units in the studied system. However, in many cases, gaining information related to the relative positions of the constitutive units (or their velocities) alone may be insufficient, and to reach a more complete physical knowledge, one should ideally learn and correlate with each other both structure and dynamics. Here we demonstrate how to achieve such a goal efficiently by building and navigating high-dimensional Time-Derivatives (TiDe) spaces. A TiDe space can be generated for virtually any type of system/phenomenon from the time-series data collected along its observation over time. Each TiDe's dimension corresponds to a growing-order time-derivative of the extracted data, thus containing information related to different physical phenomena/events, which can be easily extracted via unsupervised approaches. We demonstrate how, by definition, TiDes can be directly analyzed without a need for prior dimensionality reduction, providing results that are intrinsically intuitive to interpret. We show the potential of the method by analyzing two prototypical example
datasets extracted from molecular dynamics simulations or experimental tracking of different types of complex dynamical systems. Our results demonstrate how efficiently one can navigate and learn in information-rich TiDe spaces, which provide a robust general framework for data analysis and for studying complex dynamical systems from the data collected along their observation over time.
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Atmospheric and Oceanic Physics
AIFS-SUBS: Extending Data-Driven Forecasting to Sub-Seasonal Timescales
Jakob Schloer, Steffen Tietsche, Christopher D. Roberts et al. (+6 more)
Data-driven models now rival numerical weather prediction in the medium range, but extending them to sub-seasonal lead times raises challenges absent at shorter horizons. Errors accumulate over long autoregressive rollouts, systematic biases grow with lead time, and several years of data must be held out for independent verification, even though machine-learning models otherwise benefit from longer training records. To address these challenges, we adapt ECMWF's AIFS-CRPS medium-range model. AIFS-SUBS adopts a 24h autoregressive time step to reduce error accumulation, adds stratospheric levels and top-of-atmosphere thermal radiation as predictors, and reserves 2007–2011 as an independent verification window. We evaluate two config-durations: AIFS-SUBS, fine-tuned on operational analyses, and AIFS-SUBS-ERA5, trained on ERA5 alone. Across weeks 2–6, AIFS-SUBS matches the operational Integrated
Forecasting System (IFS) in probabilistic skill while reducing systematic biases. For the convective (OLR) component of the Madden–Julian Oscillation (MJO), AIFS-SUBS extends skilful forecasts (correlation > 0.5) by eight days relative to the IFS, while matching or exceeding the IFS for the full multivariate RMM index. AIFS-SUBS also reproduces the observed MJO modulation of tropical cyclone activity comparably. Stratospheric skill is particularly strong with AIFS-SUBS reproducing sudden stratospheric warming (SSW) frequency and surface impact. In the AI Weather Quest, AIFS-SUBS-ERA5 attains a variable-averaged ranked probability skill score slightly ahead of the IFS at weeks 3 and 4. At inference, AIFS-SUBS uses about 200 times less energy than the IFS, opening the door to much larger real-time ensembles. AIFS-SUBS is ECMWF's first machine-learning model targeted at sub-seasonal time-scales.
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All authors Jakob Schloer, Steffen Tietsche, Christopher D. Roberts, Lorenzo Zampieri, Simon Lang, Gert Mertes, Gareth Jones, Matthew Chantry, Frederic Vitart
Atmospheric and Oceanic Physics
A Real-Time Remote-Sensing-Guided Decision-Support Framework for Cloud-Seeding Operations: A Field Demonstration Using Himawari-9 and C-band Phased Array Weather Radar
Shunji Kotsuki, Kazuaki Yasunaga, Atsushi Hamada et al. (+11 more)
This study proposes a real-time remote-sensing-guided decision-support framework for cloud-seeding operations using high frequency geostationary satellite and ground weather radar observations. The framework integrates cloud assessment, human-in-the-loop decision support, and aircraft operation to translate high-frequency remote-sensing information into actionable guidance for seeding aircraft. We demonstrate the framework using 2.5-min Himawari-9 geostationary satellite observations and 60-s C-band phased-array weather radar (C-PAWR) observations during the preliminary dry-ice cloud-seeding field campaign conducted over Toyama Bay, Japan, in January 2026. In the 13 January case, the framework enabled the ground team to identify a developing cumulus cloud with a lifetime of approximately 20 min, communicate guidance to the aircraft, and conduct seeding immediately before the cloud began to dissipate naturally. Candidate seedable clouds were identified from Himawari-9 infrared indices, and their selection was supported by near-real-time C-PAWR observations of precipitation echoes. Because the released dry-ice amount was limited to 30 kg, this study does not attempt to attribute subsequent cloud
evolution to seeding effects. Instead, the results demonstrate that rapid-scan satellite and ground radar observations can support real-time target selection and aircraft guidance for responsible, operationally feasible weather-intervention field experiments.
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All authors Shunji Kotsuki, Kazuaki Yasunaga, Atsushi Hamada, Kazuhiro Yoshimi, Kenta Shiraishi, Akira Takeshima, Yoshiki Terashima, Kaya Kanemaru, Yusuke Hiraga, Takuya Funatomi, Hiroyuki Kubo, Kohei Suzuki, Masanao Ohashi, Tadashi Tsuyuki
Applied Physics
Experimental Realization of Type-II Quadrupole Topological Insulator
Yuan Liu, Yangkai Liu, Cheng Lin et al. (+4 more)
The discovery of quadrupole topological
insulators (QTIs) has spurred extensive research into higher-order topological phases. Recently proposed type-II QTIs exhibit unconventional topological behaviors with 1/2 edge polarization \operatorname{p}_x and zero edge polarization \operatorname{p}_y, due to the inequivalence between Wannier-band and edge-spectrum gap closures, yet their experimental realization remains challenging owing to the long-range and complex off-site hopping terms in their tight-binding model (TBM). Here, we circumvent this difficulty via an optimized Householder tridiagonalization (OHT) mapping that reduces the complex two-dimensional
lattices to one-dimensional chains with only negative-real-valued nearest-neighbor hopping terms, greatly facilitating experimental sample fabrication. Using this strategy, we experimentally verify the type-II QTI phase, type-I QTI phase and trivial phase in elastic wave platforms via simple aperiodic plate-beam chain structures, where the plates reflect the on-site potential terms and beams correspond to the off-site hopping terms in the TBM. Our approach provides a versatile route for experimentally exploring more complex and richer topological phenomena based on TBM.
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All authors Yuan Liu, Yangkai Liu, Cheng Lin, Jiao Shen, Yifan Zhu, Haiyan Fan, Hui Zhang
Atmospheric and Oceanic Physics
On the Genealogy of Machine Learning Weather Prediction
Mohammad Hassan Erfani
Modern machine-learning weather prediction (MLWP) has largely inherited the initial-value-problem (IVP) framing of numerical weather prediction (NWP). This inheritance leads to a dominant paradigm of learned autoregressive time-stepping and constrains how the learning problem is defined and architectures are favored. In this study we make the inheritance explicit, contrast two philosophical traditions: "scientific surrogate modeling," where machine learning (ML) is embedded within a physical system and must respect its structural constraints, and "free-form data-driven modeling," where atmospheric fields are treated as spatiotemporal sequences and models learn latent dynamics without explicit physical constraints. By reviewing the governing primitive equations, surveying recent literature, and analyzing concrete physical examples, we map each modeling paradigm to either a state-conditioned or
evolution operator formulation. We conclude that principled model selection requires explicitly aligning architecture and training objectives with either the physical system structure or the statistical structure of the data.
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Optics
Surface-exciton enhanced SHG response in few-layer 2H-TMDC
H. Hübschmann, G. Berth, M. Groll et al. (+6 more)
We explore the nonlinear optical properties of few-layer MoS2 by means of polarization and
laser-power-dependent measurements as well as ab initio techniques. While for even layer samples a weak second-harmonic (SH) signal can be attributed to the presence of surface defects or interface effects, our measurements resolve a layer-number dependent signal for odd-layer samples. For the excitation energy of 780 nm, we find that the SH intensity decreases steadily with the layer number. Our simulations demonstrate that this effect cannot be purely attributed to modifications of the band structure, but requires the inclusion of excitonic effects and can be explained by the increasing delocalization of
excitons with increasing sample thickness.
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All authors H. Hübschmann, G. Berth, M. Groll, K. Burgholzer, A. Bonanni, K. D. Jöns, U. Gerstmann, W. G. Schmidt, A. Bocchini
Atmospheric and Oceanic Physics
A Mutual Information-Based Ensemble Kalman Filter
Tadashi Tsuyuki and Shunji Kotsuki
Ensemble Kalman filters (EnKFs) are widely used for data assimilation in geophysical systems. Among various implementations, the local ensemble transform Kalman filter (LETKF) has gained popularity because of its computational efficiency. However, the deterministic EnKF such as the LETKF is known to be less robust than the
stochastic EnKF in strongly nonlinear regimes. We generalize the LETKF such that it contains a
stochastic term and includes the
stochastic EnKF within it. We adaptively optimize the parameter that determines the weight of the
stochastic term based on an identity of mutual information, which is satisfied by the Kalman filter in linear Gaussian systems. As the analysis perturbation equations of EnKFs are decomposed into a system of equations for modes that are uncorrelated with each other, the application of mutual information is easily achieved. The generalized LETKF thus optimized is named the mutual information-based ensemble Kalman filter (MI-EnKF). The MI-EnKF indirectly uses the third- and fourth-order moments of the forecast ensemble through
entropy. To speed up calculations of
entropy, we create a lookup table based on maximum
entropy distributions. We conduct data assimilation experiments using the Lorenz-96 model to confirm the validity of the optimization method of MI-EnKF. When the observation operator is linear, the ML-EnKF shows the same analysis accuracy as the LETKF. When the observation operator is strongly nonlinear, the MI-EnKF is more accurate than both LETKF and
stochastic EnKF regardless of ensemble size. Optimizing just the first mode can lead to significant improvements, but positive impacts of increasing the number of optimized modes are not observed unless the ensemble size is large. The optimized parameter values indicate that the optimal EnKF lies between the deterministic EnKF and the
stochastic EnKF.
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Instrumentation and Detectors · Cross-listed from astro-ph.IM
The Atacama Large Aperture Submillimeter Telescope (AtLAST): enabling large-scale sub-mm science beyond 2030
Claudia Cicone, Tony Mroczkowski, Evanthia Hatziminaoglou et al. (+38 more)
AtLAST is designed to be the largest (sub-)mm single-dish astronomical observatory and the first
climate-neutral modern research infrastructure. It offers a unique combination of large aperture (50 m), large field of view (>1 deg), fast scanning speed (up to 3 deg/s), and high surface accuracy (20micron nighttime half wavefront error) that allows >=50% Ruze efficiency up to 1 THz. The design features a rocking chair mount with an active main reflector surface, a high precision closed-loop metrology system, and the space to house six major instruments. Instruments will be periodically updated as spectroscopic focal plane array, detector, coherent amplifier, and
semiconductor technologies used in readout and backend electronics will advance over the next decades. AtLAST will be a multi-purpose facility that will produce transformational results in nearly all fields of Astrophysics, such as Astrochemistry,
Galactic and Extragalactic Astronomy, Cosmology, Planetary science,
Stellar and
Solar Physics, High energy astrophysics, and Time domain astronomy. Its unrivalled throughput of 6170 m^2 deg^2 will enable wide-field unbiased surveys. These will overcome extragalactic confusion noise and enable the detection of normal
galaxy populations out to z=7. AtLAST will reveal and characterise the missing
baryons in the Universe, by mapping the elusive, low surface brightness gas within and around
galaxies across
cosmic time. AtLAST will be the first green off-grid observatory, powered by a bespoke renewable energy system and reusing its braking energy thanks to a cutting-edge energy recovery system. By sharing surplus power and technological know-how with local communities, AtLAST will contribute to energy justice in Chile. AtLAST's new bold
vision of a sustainable pursuit of breakthrough astronomy is an exceptional opportunity to shape the future of scientific research infrastructures. [abridged]
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All authors Claudia Cicone, Tony Mroczkowski, Evanthia Hatziminaoglou, Matthias Reichert, Sabrina Sartori, Amelie Saintonge, Pamela Klaassen, Francisco Montenegro-Montes, Martin Timpe, Aleksej Kiselev, Danilo Koeltzsch, Carlos De Breuck, Pamela Pizarro, Eelco van Kampen, Tinus Stander, Dirk Muders, Yiqing Song, Kotaro Kohno, Sergio Poppi, Yoichi Tamura, Stefan Thoms, Hans Kaercher, Sven Wedemeyer, Alessandro Attoli, Stephen Molyneux, Bruno Silva, Guillermo Valenzuela Venegas, Paola Velasco-Herrejon, Marianne Zeyringer, Yogesh Kumar Yadav, Mark Booth, Carlos Alberto Duran, Lars-Ake Nyman, Serni Ribo, Francisca Kemper, Manuel Groh, Leandro Aggio, Mathias Hudoba de Badyn, Benjamin Magnelli, Mats Kirkaune, Akira Endo
History and Philosophy of Physics · Cross-listed from gr-qc
Emergent cosmology and gravity from quantum time?
Ovidiu Cristinel Stoica
Macroscopic observables allow the recovery of intrinsic dynamics from stationary
quantum states. I show that, by interpreting the squared amplitude as the probability density for each definite value of intrinsic time, a
curvature emerges in the time direction. For example, from the perspective of intrinsic
quantum time, the Friedmann-Lemaître-Robertson-Walker cosmological model emerges from spherically symmetric stationary solutions in four-dimensional Euclidean space, without presupposing
gravity. If there is no unique direction of time,
curvature emerges in all spacetime dimensions, without presupposing
gravity, from the variable amplitude of the stationary wavefunction alone. This opens a new possibility that general relativity or some modification of it emerges from intrinsic time observables.
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Computational Physics
Watts per event: evaluating Sustainability of HEP Event Generators beyond the LHC era
Szabolcs Molnár, Gábor Bíró, Gábor Papp et al. (+1 more)
The development, tuning and operation of Monte Carlo event generators beyond the LHC era require vast amount of resources. In this study we investigate the sustainability of these software with a containerized set of tools (named 77rev/propripy), by benchmarking the HIJING++ heavy-ion Monte Carlo event generator. We analyze the performance of various CPU architectures and show that by choosing the level of multithreading properly, the cost of event generation can be optimized. The presented approach can reduce the energy footprint of high-energy physics event generators and therefore alleviate the ever-increasing, ubiquitous computational challenges.
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All authors Szabolcs Molnár, Gábor Bíró, Gábor Papp, Gergely Gábor Barnaföldi
Computational Physics
dpti: An Automated Thermodynamic Integration Workflow for Phase Diagram Calculations with Machine Learning Interatomic Potentials
Fengbo Yuan, Xin Zhong, Donghao Zheng et al. (+4 more)
Thermodynamic integration (TI) is a widely used approach for computing free energies and phase diagrams. However, TI calculations driven by machine learning interatomic potentials (MLIPs) remain technically challenging because they require careful design of reversible integration paths and many closely related molecular dynamics (MD) tasks for each phase and state point. To address these challenges, we present dpti, an open-source Python package that automates TI workflows for phase diagram calculations with MLIPs. dpti connects reference systems with analytically known free energies to MLIP-described atomic and molecular solids and
liquids through reversible integration paths. Given JSON input files, dpti generates and runs the required MD tasks, computes free energy contributions, estimates errors, and propagates coexistence points into phase boundaries. We demonstrate the usage of dpti with two examples driven by Deep Potential models: a silica phase diagram involving beta-quartz, coesite, and melt, and the ice Ih-
liquid water phase boundary. dpti provides a useful tool for automated phase diagram calculations of materials modeled by MLIPs.
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All authors Fengbo Yuan, Xin Zhong, Donghao Zheng, Jinzhe Zeng, Linfeng Zhang, Han Wang, Yifan Li