Physics Education · Cross-listed from astro-ph.IM
MIRA: a data management and education platform connecting students to robotic telescopes
Peter P. Pedersen, Lionel Garcia, Mahshid Alimi et al. (+3 more)
Hands-on
telescope experience is often used to drive student engagement in astronomy education, but scaling access to larger groups of students is operationally challenging. Consequently, students encounter only a fraction of the professional workflow, rarely engaging with the rigorous peer-review, time-allocation processes, or automated data reduction pipelines that govern modern research facilities. We present the design of MIRA (Mentored Investigations using Robotic Astronomy), a data management and educational platform that connects Swiss secondary school and undergraduate students with operational robotic observatories. MIRA structures the entire observation lifecycle: proposal, review, acceptance/rejection, scheduling, and observation. Following execution, the platform automatically reduces raw FITS frames (including astrometric calibration and photometry) and serves them via a web-accessible archive accompanied by Python-based analysis tutorials. By separating educational front-ends from low-level
telescope controls through Astra and ASCOM Alpaca, MIRA delivers an authentic scientific research workflow that bridges classroom learning with professional observatory operations.
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All authors Peter P. Pedersen, Lionel Garcia, Mahshid Alimi, David Degen, Florian Lienhard, Didier Queloz
Physics and Society · Cross-listed from cond-mat.stat-mech
The distribution of eccentricities in random regular graphs
Dor Lev-Ari, Ofer Biham and Eytan Katzav
We derive a closed-form analytical expression for the distribution of eccentricities (DoE) in random regular graphs (RRGs) that consist of $N$ nodes of degree $c$. The DoE is given by the tail distribution $P(E > \ell) \simeq 1 - \exp \left[ - \exp \left( - \frac{ e^{b \ell} - \mu }{\beta} \right) \right]$, where the distance $\ell$ takes integer values, $b = \ln (c-1)$ is the shape parameter, $\beta = \frac{c-2}{c} N$ is the scale parameter and $\mu = \frac{c-2}{c} N \ln N$ is the location parameter. By providing the full distribution rather than a single characteristic length scale, we present a detailed view of the large-scale structure. In spite of the fact that the degrees of all the nodes are the same, their eccentricities exhibit non-trivial variations. We derive a closed-form expression for the mean eccentricity, which is given by $\langle E \rangle \simeq \frac{\ln N}{\ln (c-1)} + \frac{\ln \ln N}{\ln (c-1)} - \frac{ \ln c - \ln (c-2) }{ \ln (c-1) } + \frac{1}{2}$. We calculate the mode of the DoE, which exhibits a staircase profile as a function of the network size. Interestingly, the mode is given by $E_{\rm mode} ={\rm Round} \left( \langle E \rangle \right)$, where ${\rm Round}( x )$ is the nearest integer to $x$. We also calculate the variance ${\rm Var}(E)$ and show that it exhibits oscillations as a function of the network size $N$. The results presented in this paper may serve as
benchmarks for algorithmic approaches to eccentricity calculations in large sparse networks. The eccentricities are important in practical applications such as broadcasting and global dissemination, where the network performance is determined by the longest delay times.
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Fluid Dynamics
Exploring 2D turbulent properties in anisotropic and disordered Fourier space: Insights into inverse cascades and universal superdiffusion from randomly sampled triadic interaction
Francesco Carbone and Sergio Servidio
Two-dimensional turbulent properties are investigated within a “low-density” Galerkin-truncated system, with a focus on both Eulerian and Lagrangian characteristics. In particular, an ordered pseudo-logarithmic and a disordered distribution of {active (i.e. resonant)} triads has been sampled in
Fourier space, allowing for a tunable degree of anisotropy and “triadic density”, enabling investigation into their effects on the inverse energy cascade and particle pairs
diffusion. Despite the non-uniform and anisotropic mesh in the
Fourier space, this reduced model successfully captures 2D
turbulence scaling laws and maintains integral energy cascade properties. It consistently reveals the classical double-cascade: a $k^{-5/3}$ inverse cascade at large scales and a $k^{-3}$ direct cascade at small scales, observed across all configurations. Furthermore, while anisotropy, controlled via angular sampling, significantly impacts the vorticity field organization and the efficiency of the inverse energy flux, the system's diffusive properties exhibit a Richardson superdiffusive scaling, $\ell^2(t)\sim t^3$, for particle pair separation. The prescribed spectral anisotropy affects the Lagrangian eddy diffusivity, enhancing
diffusion along one direction for short timescales. Conversely, for longer times, particles become uncorrelated, and the separation distance degenerates into the classical Brownian scaling, $\ell^2(t)\sim t$. The observed $t^3$ pair-dispersion indicates that the retained spectral interactions sustain super-ballistic separation, while anisotropy mainly affects the dispersion amplitude without modifying the scaling.
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Instrumentation and Detectors · Cross-listed from hep-ex
Track fitting at the full LHC collision rate
Pierre Billoir, Thomas Boettcher, Michel De Cian et al. (+1 more)
The LHCb experiment at the Large
Hadron Collider underwent a major upgrade before the LHC Run 3 data taking period, employing an all-software approach in its trigger system. Here we present a fast implementation of a Kalman filter, used in the first trigger stage since the 2025 data taking period, allowing to determine parameter estimates of charged-particle trajectories at the full LHCb collision frequency of 30 MHz. This approach replaces computationally expensive
magnetic field map lookups and numerical integration methods with fast analytical parameterisations while maintaining the mathematical framework of Kalman filtering. Implemented on approximately 500 GPUs within the first-level trigger, the
algorithm has replaced the previous partial track fitting
algorithm in the real-time trigger environment at the cost of a 2% increase in processing time. Compared to the previous fitter this parameterised Kalman filter shows a significantly improved momentum resolution, resulting in a factor of two improvement in the invariant mass resolutions for reconstructed D0 and J/{\psi}
hadrons. It additionally demonstrates greater robustness against detector misalignment effects and substantially sharpens the discrimination between genuine particle trajectories and accidental background, more than doubling the rejection of the latter at no cost to genuine-track efficiency, for a standard selection working point.
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All authors Pierre Billoir, Thomas Boettcher, Michel De Cian, Lennart H. Uecker
Data Analysis and Statistics
Inferring Non-Normal Amplification Geometry from Multivariate Time Series
V.R. Saiprasad, V. Troude and D. Sornette
Across hydrodynamics, ecology, neuroscience, network dynamics, non-Hermitian physics, and socio-economic systems, asymptotically stable dynamics can exhibit large transient amplifications that are invisible to
eigenvalue-based analyses. The mechanism is
geometric rather than spectral: perturbations entering along one direction may be expressed transiently along another, allowing asymptotic decay to coexist with strong transient or noise-driven amplification. We introduce non-normal directional response inference, a data-driven method for detecting this geometry from multivariate time series when the governing operator is unknown. A local linear operator is estimated from sliding windows and projected onto the dominant two-dimensional input-response subspace. The reduced dynamics are summarized by the
eigenvalue splitting $\Delta$, eigenvector non-orthogonality $K$, and the scale-free ratio $R=K/K_c(\Delta)$, where $K_c(\Delta)$ is the two-dimensional threshold for transient amplification. Controlled
benchmarks show that the reduced geometry, particularly $R$, can be recovered from finite data even when the full high-dimensional operator is poorly estimated. Tests across sample size, dimension, training horizon, spectral structure, and non-stationarity confirm that the relevant response geometry requires far fewer observations than full-
matrix recovery. Applied in moving windows to electrohysterogram, seizure
EEG, freezing-of-gait, and unstable push-up inertial recordings, the method reveals systematic changes around known physiological or behavioral episodes through shifts in $R$, changes in $\Delta$, or stronger projection of fluctuations onto the inferred response direction. It thus exposes interpretable changes in local response geometry without framing the problem as supervised event detection.
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Physics and Society
Photovoltaics beyond the panel: system-level net energy under grid and firming constraints
Hans Peter Beck
Photovoltaics can exhibit favourable installation-level energy return on investment (EROI), yet electricity must also be delivered when
solar and wind generation are insufficient. This study evaluates how the energy balance changes when the boundary is expanded to reliable electricity supply. A fleet-equivalent
benchmark model includes component turnover, grids, storage, renewable overbuild, dispatchable backup, and fuel supply. It is not a simulation, optimization, or real-system prediction. Photovoltaics provide the accounting reference in an illustrative Central European mix of 80% wind and 20% photovoltaics, while the firming penalties arise more generally from weather-dependent generation. Expanding the boundary is decisive. The unfirmed renewable fleet retains an EROI of 10.7-16.0, but does not provide continuous electricity. Battery load-balancing references decline from 7.1-12.5 for 1h to 0.7-2.3 for 24h. Seasonal hydrogen yields 3.4-7.7; adding a 1h battery reduces the combined range to 2.9-6.8. Pipeline-gas and LNG backup yield only 1.2-2.6 and 1.0-2.2. The lifecycle-carbon advantage narrows accordingly. Under present industrial supply chains, GWP$_{100}$ intensities rise from 38-75 gCO$_2$eq/kWh without firming to 80-289 gCO$_2$eq/kWh for hydrogen and battery-hydrogen firming, and 121-327 gCO$_2$eq/kWh for gas backup. These favourable
benchmarks set orientation, site, curtailment, and delivery factors to unity; real deployment lowers EROI and raises emissions. The results identify firming as a critical energetic constraint: reliable decarbonization requires firm low-carbon generation with sufficient net-energy surplus to sustain a resilient industrial society.
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Optics
Ultraviolet direct absorption microscopy for single particle protein/nucleic acid quantification
C. J. Richards, D. van de Lockand, D. Wolters et al. (+1 more)
Bio-nanoparticles are pivotal to next generation nanotherapeutics, but providing single-particle biomolecular characterization remains a crucial challenge. Herein we present ultra-violet direct absorption microscopy (UV-DAM) to tackle this challenge. UV-DAM is based on a tailored illumination scheme for absorption-only imaging, combined with a custom deep UV light source. Combined, they provide biomolecular specificity with single particle sensitivity. As such, UV-DAM provides rapid, label-free, high resolution, biochemical imaging. Enabled by these capabilities, we implement the classic nucleic acid:
protein absorption assay at the single virus level where we demonstrate UV-DAM's ability to distinguish empty from DNA-loaded viral capsids based on bimolecularly specific absorption fingerprints. UV-DAM presents the translation from bulk UV-visible spectrometry to single-particle assessment, a crucial advancement for nanomedicine characterization where particle loading efficiencies are often heterogenous. Beyond this, UV-DAM is applicable to a wide range of nanomaterials or investigation of biological process with high spatio-temporal resolution and intrinsic molecular contrast.
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All authors C. J. Richards, D. van de Lockand, D. Wolters, M. Liebel
Optics
Empirical verification of principal mode orthogonality and relative phase calibration in photonic lanterns
Adam K. Taras, Barnaby R. M. Norris, Christopher Betters et al. (+6 more)
Photonic lanterns efficiently map input spatial modes to single-mode outputs for applications like high angular resolution imaging and nulling interferometry. However, manufacturing limits prevent full control over the device's mode transfer
matrix at the design stage, making empirical characterisation essential. In this work we further analyse a
dataset of direct measurements of a photonic lantern's principal modes using digital off-axis holography over a 73 nm range near 1550 nm. By analysing the electric field directly, we find that the principal modes are significantly more orthogonal than random vectors in a space of the same size, as expected for near-adiabatic devices. We propose metrics for quantifying this effect, noting that mode converters with orthogonal principal modes provide better conditioned inverse solvers. We also simulate additional measurements that characterisation systems could take, where the orthogonality would be leveraged to determine the relative phase between principal modes.
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All authors Adam K. Taras, Barnaby R. M. Norris, Christopher Betters, Daniel S. Dahl, Nathan Long, Andrew Ross-Adams, Peter G. Tuthill, Jin Wei, Sergio Leon-Saval
Optics
Motion-Based Beamshape Recovery Enables Precision Nanoparticle Sizing
D-Dré K.J.M.J. Braam, Daan Wolters and Matz Liebel
Label-free all-optical nanosizing approaches based on interferometric or darkfield-imaging infer size, composition, or shape from single-particle scattering signals, but these signals are inseparably coupled to the spatially non-uniform illumination profile of the imaging system. Existing normalisation strategies require directly measuring this illumination field, an approach that fails for background-free geometries, such as lightsheet-type illumination, where the field cannot be detected. Here we introduce a self-normalisation method that reconstructs the illumination profile directly from the scattering signals of many freely diffusing nanoparticles, requiring no additional hardware, calibration samples, or direct field measurement. Critically, our approach eliminates the particle-heterogeneity bias that otherwise corrupts such reconstructions, by normalising single-particle trajectories against each other in regions of spatial overlap, where distinct particles necessarily sample identical illumination and detection conditions. We validate this method for gold nanoparticles of various size in two- and three-dimensional geometries, including a 90{\deg} side-illumination configuration in which the illumination field is entirely undetectable by conventional means, and show that reconstructed profiles closely match ground-truth measurements, thus drastically reducing signal variability. Relying solely on the scattering signal already acquired for sizing, our approach is immediately compatible with existing interferometric and darkfield nanoscopy platforms and broadly extendable to other scattering or fluorescent modalities, including light-sheet microscopy.
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Optics
Local Variance-Based Calibration of Programmable Photonic Interferometer Meshes
Gökhan Elmas, Igor A. Litvin and Janis Nötzel
Programmable photonic interferometer meshes enable reconfigurable linear optical transformations, but their performance depends critically on accurate calibration of Mach-Zehnder interferometers and phase shifters. Conventional methods often require node isolation, dedicated routing paths, orthogonal training states, reference channels, or prior phase-voltage characterization, which become increasingly difficult in large thermally tuned meshes. We introduce a local variance-based self-calibration method using intensity-only measurements. Controlled phase perturbations are applied, and calibration points are identified from minima of the measured output-power variance. For Mach-Zehnder interferometers, the variance follows a characteristic |sin(theta)| dependence, allowing bar and cross operating points to be found without conventional node isolation. For phase shifters, balanced interference produces a complementary |cos(phi)| variance signature, enabling quadrature calibration through the same statistical principle. We validate the method experimentally on an 8 x 8 silicon nitride programmable photonic processor using a fully automated two-stage procedure. Starting from random phase settings, all Mach-Zehnder interferometers are calibrated first, followed by phase-shifter calibration under balanced-interference conditions. As a system-level test, we implement an embedded 4 x 4 Hadamard transformation on the 8 x 8 processor using a Clements decomposition. These results establish local output variance as a simple calibration observable for programmable photonic meshes. The method is compatible with discrete random phase ensembles and requires neither conventional node isolation nor orthogonal training fields, making it a practical calibration primitive for scalable self-stabilizing photonic processors.
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Optics
3D scanning microscopy through scattering surfaces using the optical memory effect
Harish Sasikumar, Gerwin Osnabrugge, Kirsten Gerritsma et al. (+2 more)
Wavefront shaping allows light to be focused through scattering objects. However, the wavefront correction found is only valid in a small region called the isoplanatic patch. Here we present a simple approach to extend this isoplanatic patch by shifting and scaling the corrected wavefront appropriately, demonstrating an 8.6-fold increase in the lateral scanning range and a 1.5-fold increase in the axial range through a scattering layer without the need to perform additional wavefront shaping measurements. Our findings agree well with a simple geometrical model that also allows us to extract the effective position of the scattering layer from the measurements.
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All authors Harish Sasikumar, Gerwin Osnabrugge, Kirsten Gerritsma, Bahareh Mastiani, Ivo M. Vellekoop
Plasma Physics
Computational studies of giant edge islands and unpaired X-points in HSX and W7-X by manipulating coil currents
Robert Davies, Dieter Boeyaert, Alexis Wolfmeister et al. (+3 more)
We present
magnetic configurations in the Helically Symmetric eXperiment (HSX) and Wendelstein 7-X (W7-X), in which the edge
magnetic structure is dominated by island chains which are spatially larger than the previously reported configurations. These “
giant" island chains (with rotational transform $\iota=4/3$ or $4/4$ for HSX and $\iota=5/6$, $5/5$ or $5/4$ for W7-X) are obtained by reducing the coil current in main coil 6 for HSX and non-planar coil 5 for W7-X (i.e. the coil nearest the up-down symmetric cross-section $\phi=36^\circ$ for W7-X and $\phi=45^\circ$ for HSX); this appears a sufficient (but not necessary) condition for
giant islands. The
giant islands create relatively straight X-point legs which transport
plasma to the
plasma-facing components (PFCs). In the most extreme cases, the island O-points leave the domain of the field line map and the divertor legs of the remaining “unpaired" X-points do not close around the island. We use the anisotropic heat
diffusion code EMC3-Lite to find “
giant island" W7-X configurations which are promising for PFC heat loads. Coil forces analysis (in addition to other effects such as neoclassical transport and magnetohydrodynamic stability) would also be required but are not explored here. It is not known whether
giant islands are intrinsically favourable for divertor performance but we demonstrate that such regimes, which are far from the ordinary island divertor, are obtainable and can in principle be studied experimentally. This also reveals the flexibility of existing machines for edge studies beyond their original design space.
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All authors Robert Davies, Dieter Boeyaert, Alexis Wolfmeister, Benedikt Geiger, Georg Harrer, Joachim Geiger
Biological Physics · Cross-listed from cond-mat.soft
Amoeboid swimming of active vesicles
Reiner Kree and Annette Zippelius
We investigate the shape dynamics and migration of weakly deflated active vesicles driven by processes acting either directly in the membrane or transmitted by the cytoskeleton. For a force-free vesicle, local membrane incompressibility suppresses rigid-body translation, so that migration arises from time-dependent shape deformations. Assuming small excess area enables a systematic analysis of the coupled deformation and migration dynamics in free space, i.e. in the absence of substrate adhesion or confinement. Depending on the strength and frequency of the activity, the vesicle exhibits several dynamical regimes, including synchronized oscillations, quasiperiodic shape changes, transitions between non-propelling and propelling states, and intermittent motion.
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Optics · Cross-listed from quant-ph
High-rate continuous-variable quantum key distribution coexisting with Tb/s coherent classical transmission in hollow-core fiber
Xitao Ji, Siyu Chen, Peng Li et al. (+7 more)
Quantum key distribution (QKD) can provide secret keys with security rooted in
quantum mechanics, but operation alongside high-capacity classical traffic remains limited by the excess-noise budget of weak
quantum states in conventional solid-core fiber. Here, we combine ultralow-loss anti-resonant hollow-core fiber with residual-carrier-assisted discrete-modulation continuous-variable QKD (DM-CV-QKD) to address both propagation-induced coexistence noise and low-SNR phase recovery. Over a 24.3-km hollow-core link with 3.3-dB end-to-end loss, a dual-polarization 15-Gbaud DM-CV-QKD channel achieves an average asymptotic secret-key rate (SKR) of 153.22 Mb/s and a finite-size SKR of 149.99 Mb/s, while 39 coherent wavelength-division-multiplexed channels deliver an aggregate data rate of 7.6 Tb/s and a net data rate of 7.2 Tb/s. The system can even sustain a positive SKR under a high classical launch power of up to 15 dBm, without an optical bandpass filter (BPF). Finite-size analysis against collective attacks further yields a projected positive secret-key rate at a 100-km-equivalent condition. These results show that an anti-resonant hollow-core fiber, combined with carrier-assisted phase recovery, can greatly extend the operating regime of shared-fiber
quantum-secured coherent links, pointing to a promising approach for integrating high-rate CV-QKD with high-capacity optical networks.
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All authors Xitao Ji, Siyu Chen, Peng Li, Mingming Zhang, Yilun Chen, Jun Gao, Rui Lin, Bacco Davide, Siqi Yan, Ming Tang
Instrumentation and Detectors
Summary of quality control (QC) of ATLAS18 production ITk strip sensors
P. Federičováa, A. Affolder, K. Affolder et al. (+38 more)
To address the demanding operational requirements of the High-Luminosity upgrade of the Large
Hadron Collider (HL-LHC), the ATLAS experiment is replacing its current Inner Detector with a new all-silicon Inner Tracker (ITk). The ITk will feature an active area of 165 m2, with its outer tracking layers populated by approximately 18,000 ATLAS18 n+-in-p silicon strip sensors. The silicon sensors, available in eight geometries tailored to two barrel and six endcap types, respectively, are designed to tolerate fluences of up to 1.6 x 10^15 neq/cm2 and ionizing doses of 66 Mrad. A comprehensive, multi-year Quality Control (QC) program is underway across multiple international institutes to evaluate these ITk strip sensors for mechanical and electrical conformity. The QC process includes IV/CV characterization, full strip tests, long-term current stability monitoring, visual inspection, and metrology tests. To manage the high throughput of about 500 sensors per month, the collaboration has implemented standardized test procedures, software packages for data monitoring and integrity checks, unified data formats, and automated analysis tools. The standardization ensures consistent pass/fail evaluation and centralized data handling that enables effective identification of trends and anomalies at all sites during the production. This contribution presents an overview of the ITk strip sensor production and QC framework, along with key findings throughout the whole production, such as charge-up of sensors, stability of the leakage currents, nonrecoverable IV breakdown, and low inter-strip isolation within wafers. It provides insights into sensor yield, quality trends, and reviews specific case studies, such as p-stop doping non-uniformity. Over 91% of the production, totaling over 590 batches, were tested and accepted. Six batches were rejected. These account for 2.8% of the total tested sensors.
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All authors P. Federičováa, A. Affolder, K. Affolder, A. Awais, G.A. Beck, A. J. Bevan, Z. Chen, J. Dandoy, I. Dawson, V. Fadeyev, J. Fernandez-Tejero, E. C. Hill, S. Hirose, L. Hommels, T. Ivison, C. Jessiman, K. Kariyapperuma, S. Katznelson, J. Keller, C. T. Klein, T. Koffas, I. Kopsalis, J. Kozáková, J. Kroll, M. Kůtová, J. Kvasnička, K. Maeyama, R.R. Marcelo Gregorio, F. Martinez-Mckinney, M. Mikeštíková, P. S. Miyagawa, L. Morelos-Zaragoza, K. Nakamura, Q. Paddock, K. Sato, E. Staats, P. Tůma, M. Ullan, Y. Unno, Y. Zhao, S. C. Zenz
Optics
Vortex-Beam Transient Absorption Microspectroscopy Resolves Ultrafast Free-Exciton and Polaron Diffusion in 2D Perovskites
Ju-Young Kim, Anirban Mondal, Gi Rim Han et al. (+4 more)
Two-dimensional (2D) Ruddlesden Popper perovskites are promising optoelectronic materials with strongly confined excitonic properties; however, probing their ultrafast carrier transport dynamics, particularly the initial nonequilibrium
diffusion regime, remains challenging because conventional transient absorption microscopy requires complex spatial imaging and lacks sufficient temporal sensitivity to resolve early time
diffusion dynamics. Here, we demonstrate a
vortex beam based transient absorption microspectroscopy platform (VTAM) enabling imaging free measurement of carrier transport by encoding spatial
diffusion information into the mode dependent pump probe signal. By employing
vortex probes with different topological charges, VTAM provides mode selective spatial sensitivity to excitonic dynamics with subpicosecond temporal resolution. Using VTAM, we resolved rapid free
exciton (FE)
diffusion followed by relaxation toward a slower steady state transport regime. A theoretically derived time dependent
diffusion model separated transient and steady state transport contributions, yielding a transient
diffusion enhancement (68.84 cm2 per s) and a steady state
diffusion coefficient (1.85 cm2 per s), thus providing an initial
diffusion coefficient (70.69 cm2 per s), and a cooling time of 0.35 ps. Measurements at the
exciton-polaron (EP) resonance revealed strongly suppressed
diffusion with nearly time independent signal ratios, indicating
lattice-coupled EP transport. These parameters were extracted without spatial scanning or image reconstruction, establishing V-TAM as a powerful imaging free platform for investigating carrier transport in perovskites and other
semiconductor systems.
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All authors Ju-Young Kim, Anirban Mondal, Gi Rim Han, Kwang Jin Lee, Jong Min Lim, Myeongsam Jen, Minhaeng Cho
Computational Physics · Cross-listed from cond-mat.supr-con
Spin-fluctuation-mediated unconventional $d_{xy}$-wave superconductivity in ThFeAsN from first-principles
Guang-Yu Guo, Jau-Wen Liu and Mitsuaki Kawamura
Superconducting (SC) pairing mechanism, origin of high $T_c$ and
symmetry of SC order parameter in Fe-based
superconductors are among the important unsolved problems in condensed matter and materials physics. We study the SC properties of ThFeAsN, a Fe-based high $T_c$
superconductor, by ab initio superconducting density functional theory calculations with electron-
phonon coupling, screened static and dynamic electron-electron Coulomb repulsion and
spin fluctuation (SF) mediated pair-interaction fully taken into account. Our calculations reveal that ThFeAsN is a SF-mediated multiband
superconductor with the calculated $T_c$ of 22.4 K and the $d_{xy}$-wave SC order parameter with different signs on different
Fermi surface sheets, in consistent with experiments. We also present distinct SC properties such as quasiparticle density of states and ultrasonic attenuation coefficient which can be immediately verified by experiments.
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Biological Physics
Rate-Independent Epigenetics: a thermodynamically consistent framework for modelling epigenetic response
Jacobo Ayensa-Jiménez and Ignacio ROmero
Epigenetic changes – heritable, long-lived, yet actively reversible modifications of the chromatin state – display
memory, threshold activation and hysteresis, features that are the hallmark of rate-independent dissipative
evolution. We propose a mathematical framework, Rate-Independent Epigenetics, that models epigenetic change within the theory of rate-independent systems and is consistent with two fundamental principles identified with the laws of thermodynamics. In this framework, a model is specified by a state space of epigenetic configurations, a stored-energy functional depending on the state and on an external loading, and a 1-homogeneous dissipation potential encoding the resistance of the epigenetic machinery to change. Assuming an energetic
evolution principle, the governing equations follow, with no further modelling hypotheses. The energy balance is exact energy conservation, and the 1-homogeneity of the dissipation potential forces a non-negative, minimal (economical) dissipation. Under natural coercivity and continuity assumptions we establish existence of energetic solutions and, via vanishing viscosity, of balanced-viscosity solutions that resolve the ambiguity of the energetic formulation at epigenetic switches; uniqueness holds under convexity and, in the scalar case, under a mild finite-multiplicity condition. We then build a variational time integrator, prove its convergence to energetic solutions and a global energy-consistency estimate. The framework is illustrated on the scalar linear play operator, on an example with a double-well energetic potential, showing the ability of the framework to study multi-stability scenarios and catastrophic switches and on a nonlinear problem, proving that the theoretical results hold. The presented framework can be seen as a skeleton for a richer thermodynamically-consistent theory incorporating viscous dissipation features.
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Fluid Dynamics · Cross-listed from astro-ph.SR
Efficiency of Tidal Dissipation in Convective Flow Under Rapid Tidal Forcing
Hongzhe Zhou and Dong Lai
For close binaries and
star-
planet systems,
tidal interactions mediate the energy transfer between the orbital motion and the internal flows of the bodies involved, thus playing a central role in their
evolution. For
equilibrium tides, the associated energy transfer is commonly modeled through an effective viscosity acting on the
tidal flow. However, the scaling of viscous dissipation efficiency with
tidal frequency $\omega_\text{T}$ remains debated, particularly when $\omega_\text{T}$ greatly exceeds the convective eddy turnover frequency $\omega_\text{c}$. Previous numerical studies have addressed this issue by subjecting a turbulent convective flow to an oscillating background shear mimicking
equilibrium tides. In this work, we adopt a novel three-layered convective box – designed to represent a
stellar convection zone sandwiched between two stable layers – driven by an external periodic forcing. We quantify
tidal dissipation efficiency by the forcing power on the flow in steady state. Our results yield a shallower scaling of
tidal power per unit mass with $\omega_\text{T}$ than reported in earlier shear-flow simulations. This scaling is consistent with the prediction by \cite{Terquem2021}, suggesting that the effective turbulent viscosity depends only weakly on $\omega_\text{T}$, although our simulations are restricted to $\omega_\text{T}\lesssim 10\omega_\text{c}$. Moreover, we find no evidence of inverse energy transfer (or “negative viscosity”), a phenomenon observed in some prior shear-flow simulations. We further investigate the influence of rotation within the same local framework. Slow rotation ($\Omega\lesssim \omega_\text{T}$) tends to enhance the
tidal power, whereas fast rotation ($\Omega\gtrsim\omega_\text{T}$) significantly suppresses it. We discuss the limitations of our approach and the broader implications of our findings.
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Physics and Society
Criticality and reduced dynamical resilience in PM2.5 pollution systems
Yuan Chen, Yongwen Zhang, Xu Li et al. (+5 more)
Concentration-based metrics underpin air-quality assessment, while dynamical persistence and recovery describe how rapidly high-PM2.5 episodes dissipate and how strongly they retain
memory. Here we introduce a finite-
memory multiplicative reversion (FMMR) process that links the lognormal concentration backbone of PM2.5 variability with event recurrence, temporal
memory, variance amplification and local dynamical resilience. Across station observations and reanalysis data, elevated PM2.5 regimes show a coherent set of critical signatures: stronger
memory, rising autocorrelation, broader upper tails, amplified variance, reduced resilience and more clustered exceedance events. Together, these co-occurring signals reveal dynamical criticality in PM2.5 pollution systems, with critical slowing down expressed as a loss of restoring capacity under high-pollution conditions. A gridded comparison across populated and emission-influenced regions further shows that areas with similar PM2.5 burden can differ in recovery capacity, while eastern China has shifted toward higher resilience during recent air-quality improvements and India and West Africa occupy lower-resilience states. By identifying where pollution burden and recovery capacity diverge, these findings establish dynamical persistence and resilience as complementary dimensions of PM2.5 risk and provide a quantitative basis for resilience-oriented air-quality assessment.
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All authors Yuan Chen, Yongwen Zhang, Xu Li, Dean Chen, Jingfang Fan, Yosef Ashkenazy, Deliang Chen, Shlomo Havlin
Instrumentation and Detectors
Machine Learning for Complex Instrument Design and Optimization
Barry C. Barish, Jonathan W. Richardson, Evangelos E. Papalexakis et al. (+1 more)
In modern experimental physics, particle accelerators and gravitational-wave observatories enable a wide-range of research at the frontiers of science. These instruments are highly complex consisting of many interacting systems which can face significant operational challenges. Apart from the experiment's main data product, a lot of data about the experimental apparatus and its environment is recorded. Machine learning techniques can analyze this big data at scale and find useful insights into operational faults potentially improving the instrument's performance and achieving the design goals. Speaking of design, machine learning can also accelerate/augment the expensive physics simulations used during the design phase of such large-scale instruments.
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All authors Barry C. Barish, Jonathan W. Richardson, Evangelos E. Papalexakis, Rutuja Gurav
Optics · Cross-listed from cond-mat.supr-con
A programmable superconductor created by light
Viktoria Yursa, Igor Vaskivskyi, Anze Mraz et al. (+7 more)
The quest for superconductivity created by light extends for more than half a century, yet direct evidence of a true zero-resistance state - whose macroscopic
quantum phase coherence is both created and controlled by light - has remained elusive. Here we report for the first time on a complex but robust light-programmable superconducting (LiPS) state at an aluminium-silicon heterojunction that is created and fully controlled with femtosecond
laser pulses. The superconducting critical temperatures - ranging from 1.8 to 8.5 K, can be increased or erased at will by the application of tailored pulse sequences. At low temperatures the LiPS state shows features characteristic of a Berezinski-Kosterlitz-Thouless topological transition, but another distinct state appears at temperatures above 2 K, which shows clear signatures of
quantum phase disorder. In the presence of a
magnetic field we observe behaviour characteristic of
vortex pinning and creep consistent with the 2-dimensional (2D) nature of the phase coherent system. The origin of the LiPS effect is attributed to light pulse control of the Moire-like superlattice of misfit dislocations (MDs) arising from discommensurations between the Al and Si
lattices which is visible by high-resolution electron microscopy. We show how light pulses can be used to control the superlattice periodicity and highlight the appearance of topologically protected
soliton-like kinks along the dislocation lines, important for imparting controllable metastability to the system. The demonstration of LiPS paves the way for designing metastable superconducting devices with controllable phase-coherence, enabling applications such as light-engineered
quantum circuits, local gap tuning in
quantum processors, and optically switchable superconducting devices.
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All authors Viktoria Yursa, Igor Vaskivskyi, Anze Mraz, Damjan Svetin, Sergej Raznjevic, Vinko Srsan, Saso Sturm, Tomaz Mertelj, Mikhail Feigelman, Dragan Mihailovic
Optics
Ultrafast programmable Bragg reflection in photonic integrated circuits
Yunxiang Song, Pawan Ratra, Danxian Liu et al. (+12 more)
Distributed Bragg reflectors (DBRs) are foundational building blocks of classical and
quantum photonic technologies. However, their optical responses are typically fixed upon fabrication, limiting
circuit robustness, reconfigurability, and functionality in applications from high-speed communications to
quantum computing. Here, we demonstrate photonic chip-based programmable DBRs at telecommunications wavelengths, which are formed by electro-optically inducing refractive index contrast between periodic ferroelectric domains in thin-film lithium niobate waveguides. We achieve voltage-controlled Bragg reflection from zero to near-unity, and gigahertz-speed reflectivity modulation. Our results bring DBRs into the ultrafast programmable regime, opening new opportunities in topological photonics, cavity
quantum electrodynamics, integrated
lasers, and optical interconnects. The interplay between nanoscale ferroelectric domain engineering and strong electro-optic nonlinearity establishes a new design strategy for nanophotonic devices, otherwise inaccessible in bulk media.
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All authors Yunxiang Song, Pawan Ratra, Danxian Liu, Jiayu Yang, Zhongshu Liu, Urban Senica, Salma Mohideen, Mingjie Zhang, Xudong Li, Donald Witt, Joshua Mornhinweg, Norman Lippok, Eric Mazur, Federico Capasso, Marko Lončar
Physics and Society · Cross-listed from cs.SI
Overlapping Network Community Detection Using Sparse Backbones
Zihe Zhou and Samin Aref
Community structures are common in real networks, and extracting them provides valuable insight in applications ranging from drug discovery to
market segmentation. Overlapping community detection (OCD) is the task of clustering networked data in which nodes may belong to multiple clusters. Existing OCD
algorithms often struggle to achieve a suitable balance between detection quality and scalability. We, therefore, propose Highway, a scalable OCD
algorithm that exploits the sparse backbone of the input network to perform efficient community inference. We used 728 Lancichinetti-Fortunato-Radicchi
benchmark networks to compare Highway and its ablated version against 10 existing OCD
algorithms. Our results, based on five performance measures, demonstrate a competitive performance for Highway. It ranks first in overlapping normalized mutual information with a 6.9% improvement over the strongest baseline. It also ranks second in all the other four performance measures. These comparative results suggest that Highway coupled with its backbone procedure offers a suitable accuracy-efficiency trade-off. The Highway
algorithm is open-source and available as part of the CDlib library.
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Optics
Right Device, Right Place: Variation-Aware Placement and Design Optimization for Robust Photonic Lattice-Filter Demultiplexers
Zahra Ghanaatian, Edwin K. P. Chong and Mahdi Nikdast
We propose a
Bayesian co-optimization framework for robust integrated photonic
lattice-filter demultiplexers, jointly optimizing device placement and design parameters under fabrication and thermal variations. Results show 75% better spectral matching and 45% lower calibration power.
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Optics
Transverse Optomechanical Interaction Mediated by Mechanically Induced Symmetry Breaking: Hamiltonian Dynamics
Satyam S. Jha and Lev Deych
In cavity optomechanics, the interaction between light and motion is usually introduced via the shift of cavity resonances in response to mechanical displacement. Here we present an analysis of
Hamiltonian dynamics of an optomechanical system with a different form of optomechanical coupling, in which mechanical motion dynamically couples otherwise independent optical modes. In the
language of Schwinger pseudospin operators, the dispersive coupling can be interpreted as "longitudinal" while the mode-coupling mechanism corresponds to a transverse interaction. The latter is well known in cavity and
circuit QED but was given only scarce
attention in cavity optomechanics. Unlike the traditional dispersive/dissipative coupling, the mode-coupling optomechanical interaction generates rich
Hamiltonian dynamics even in the absence of external drive or dissipation. For instance, under certain initial conditions this dynamics is characterized by a
Hamiltonian Hopf bifurcation controlled by the total
photon power injected into the system. Below the bifurcation threshold and for large enough non-linearity, mechanical modulation of optical amplitudes generates a broad spectrum of multiple sidebands covering a frequency interval larger than ten mechanical frequencies. Above the threshold, the frequency of optical oscillations becomes dependent on the mechanical amplitude, while mechanical degrees of freedom return to oscillating at their bare frequency. The scope of this work is limited to the study of purely
Hamiltonian dynamics to demonstrate that the mechanically mediated mode-coupling optomechanical interaction provides an alternative method of coherent control of energy exchange between light and mechanical motion.
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Plasma Physics
Parameter Scan of Multi-Fluid Equilibria in Rotating p-11B Plasmas: Effects on Fusion Power and Bremsstrahlung Losses
Xingyu Li, Huasheng Xie, Lai Wei et al. (+1 more)
We present VEQ-MF, a fast spectral parameter-scan framework for two-dimensional axisymmetric multi-fluid
equilibria with prescribed species-dependent toroidal rotation. The solver couples generalized Boltzmann density responses, quasineutral electrostatic polarization, and a generalized Grad–Shafranov equation, extending reduced-parameter Grad-Shafranov and VEQ formulations to multi-species rotating
equilibria. Rotating $p\text{-}^{11}\text{B}$ spherical-tokamak configurations are used as a demanding test case. Independent scans of the
proton and boron rotation frequencies are performed in EHL-2 and EHL-3B geometries. The computed fields are then post-processed to obtain fusion power from a drift-Maxwellian reaction-rate coefficient and bremsstrahlung power from an analytical radiation model. Three in-range EHL-3B finite-difference
benchmarks give global stored-energy, bremsstrahlung-power, and fusion-power differences of $1.7$–$3.4\%$, while a representative convergence check shows sub-percent sensitivity to increasing the spectral-parameter number and negligible sensitivity to Gaussian-grid refinement. The core
equilibrium solve remains fast for repeated scans, with representative nonzero EHL-3B cases requiring $0.032$–$0.050$~s per point in MATLAB, excluding post-processing, interpolation, plotting, and file export. The scans identify two competing multi-fluid effects. Under iso-rotation, outward boron accumulation increases the volume-integrated $n_e^2$, so the fusion-to-bremsstrahlung power ratio $\mathcal{R}_{\mathrm{fb}}$ decreases with increasing rotation. Species-dependent toroidal rotation weakens centrifugal polarization and lowers bremsstrahlung power, while the relative toroidal flow in the larger EHL-3B geometry raises the drift-Maxwellian reaction-rate coefficient and thereby modifies fusion power.
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All authors Xingyu Li, Huasheng Xie, Lai Wei, Zhengxiong Wang
Plasma Physics
Microwave Resonant Discharges for Spatiotemporally Selective Plasma Breakdown Near Surfaces
Arnav Mohapatra, Joshua K. Goodrich, Usman Humayun et al. (+1 more)
Generating non-
equilibrium plasmas close to surfaces remains a significant challenge for conventional
plasma sources. Existing
plasma generation schemes create volumetric discharges with limited spatial selectivity that lead to inefficient energy deposition and poor coupling between reactive intermediates and nearby surfaces. This work establishes tailored resonant field enhancement as a mechanism for prescribing where
plasma forms near dielectric surfaces through microwave excitation. In this approach, the geometry, refractive index, and packing configuration of dielectric materials define resonant field structures that interfere constructively and amplify electric fields locally.
Plasma forms only within these resonant volumes where the amplified fields exceed the local breakdown threshold, while the surrounding gas remains below breakdown. Microwave pulse shaping then provides dynamic control over these modes and can be used to excite different families of resonances, determine where breakdown occurs, and reconfigure what locations microplasmas occupy from one pulse to the next. We validate this framework through theory, electromagnetic simulations, and experiments using a pair of high-permittivity dielectric resonators. These studies identify multiple resonant mode families, demonstrate dynamic repositioning of microplasmas between prescribed breakdown sites, quantify the ignition characteristics of each mode, and confirm that multiple resonant microplasmas remain confined to localized field-enhancement regions during a microwave pulse. Together, these results establish a framework for designing resonant dielectric materials that localize, reconfigure, and control atmospheric-pressure
plasmas near surfaces.
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All authors Arnav Mohapatra, Joshua K. Goodrich, Usman Humayun, Thomas C. Underwood
Chemical Physics
Full-data accuracy with fewer labels for training and fine-tuning machine-learning force fields
Sheng Bi, Yi-Ze Wang and Jun Cheng
Machine-learning force fields (MLFFs) are reliable only near their training distribution, making efficient construction of diverse training sets a major bottleneck for both train-from-scratch and foundation fine-tuning workflows. Active learning can reduce this cost, but standard model-committee uncertainty is impractical for foundation MLFFs because each committee member requires a separate fine-tuning run. We present an active-learning workflow based on last-layer-projection regression (LLPR), a forward-pass-cheap per-configuration uncertainty
estimator. Across molecular, condensed-phase, and electrolyte systems, LLPR identifies compact, high-value training sets that recover full-data accuracy using only a small fraction of electronic-structure labels. In foundation-model fine-tuning, LLPR-selected configurations approach the practical fine-tuning ceiling with substantially fewer labels than random selection. In iterative electrolyte fine-tuning, LLPR detects unphysical local coordination before new labelling, calibrates uncertainty in force-error units, and supports retrospective convergence monitoring. The resulting models reproduce reference density and Li–O coordination structure, providing a scalable uncertainty-quantification strategy across MLFF training regimes.
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Chemical Physics
How Alkali Metal Cations Affect the Structure and Reactivity of the Hydrated Dielectron
Tatiana Nemirovich, Pavel Jungwirth and Ondrej Marsalek
Hydrated electrons of opposite
spins pair to form dielectrons at sufficiently high concentrations that can be achieved by dissolution of alkali metals in water. While experimental investigations of these systems are challenging due to their vigorous, even explosive, reactivity, simulations open the possibility to characterize the structure and reactivity of hydrated dielectrons and the effects of alkali cations thereon. Here, we present ab initio molecular dynamics simulations of a hydrated dielectron without or with explicit Li$^+$ or Cs$^+$ counterions. While the overall solvation structure is preserved in all these systems, the presence of cations has a distinct effect of increasing the dielectron gyration radius by about 10% and forming cation-specific cation-dielectron arrangements. Moreover, analysis of water bond lengths reveals in all studied systems a substantial elongation of first-shell O-H bonds oriented toward the dielectron, providing a structural explanation for vibrational red-shifts observed in resonance Raman measurements. Finally, at the 10 ps simulation timescale, rare reactive events were observed, albeit only for the system without metal cations, where hydride intermediates stable on picosecond timescales were identified. These observations also suggest that on the investigated timescales, metal cations may suppress hydrated dielectron reactivity.
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