Physics and Society
Clustering in co-evolving opinion dynamics: reduced SPDE models
Sebastian Zimper, Nataša Djurdjevac Conrad, Federico Cornalba et al. (+1 more)
Clustering is a fundamental collective phenomenon in
agent-based models (ABMs) of opinion dynamics. To study clustering in systems with co-evolving social and opinion variables, we derive
stochastic partial differential equation (SPDE) models that describe the
evolution of clusters. Specifically, these SPDE models are reduced in the sense that their domain accounts only for social variables, while opinion variables are instead incorporated in a multiplicative (Eulerian velocity-type) fashion. The model reduction is primarily guided by computational efficiency, as well as model interpretability. We consider two settings: one in which opinions do not affect social interactions, and another one in which a feedback mechanism couples the two. Our approach extends reduced PDE modelling to a
stochastic framework, which is essential for capturing long-term cluster behaviour. Numerical experiments indeed demonstrate that the proposed reduced SPDEs substantially decrease computational cost compared to full-state SPDE models, such as the Dean–Kawasaki equation, while still accurately reproducing the clustering behaviour of the underlying ABM. As a result, these reduced models provide an efficient tool for studying systems with large populations, including those arising in the analysis of real-world data: in particular, we provide an application related to the large-scale General Social Survey (GSS), which comprises opinion and social data of the US population since 1972.
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All authors Sebastian Zimper, Nataša Djurdjevac Conrad, Federico Cornalba, Ana Djurdjevac
Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Calibrating Attribution Proxies for Reward Allocation in Participatory Weather Sensing
Mark C. Ballandies, Michael T. C. Chiu and Claudio J. Tessone
Large-scale IoT weather sensing networks require incentive mechanisms to sustain participation, yet determining how much value individual data contributions bring to the network remains an open problem. Existing approaches address data quality but not data valuation; in operational meteorology, adjoint-based methods derive value from the forecast model itself but require full data assimilation infrastructure. We propose to utilise differentiable AI weather models to fill this gap and characterise gradient-based attribution on gridded GFS analysis inputs as a candidate value signal, evaluating fidelity, calibration, cost, and gaming vulnerability across more than 400 configurations. Attribution captures near-optimal sensor placement utility with monotonically faithful payments, but can be inflated by
adversarial inputs, with detection requiring external baseline data. These findings establish gradient attribution as a computationally validated signal for model-informed reward allocation in participatory weather sensing.
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Optics
Comparison of two laser wavelengths for LIBS bioimaging of plants grown in lunar regolith
T. Vozár, L. Čechová, J. Buday et al. (+8 more)
The colonisation of extraterrestrial
planets requires sustainable food production independent of Earth-based supplies. Due to the high costs and complicated logistics of food transport, in-situ cultivation will be essential. Growing plants directly in regolith offers a practical approach to achieve sustainable long-term human habitation beyond Earth. In this study,
Laser-Induced Breakdown Spectroscopy (LIBS) technique was employed for bioimaging of broccoli (Brassica oleracea) and salad (Lactuca sativa) plants grown in Lunar regolith simulant and control substrate. For this purpose, the potential of the 2090 nm
laser wavelength for bioimaging of plant tissue was studied compared to the conventional 1064 nm. The signal-to-noise ratio (SNR), total emissivity ($\epsilon_{\mathrm{tot}}$), and Mg II / Mg I intensity ratio (ionisation degree) were all higher when using the 2090 nm
laser wavelength compared to 1064 nm. These findings indicate that the 2090 nm
laser produces a hotter and more efficiently ionised
plasma, supporting its feasibility for bioimaging of plant tissues. Additionally, bioimaging with both
laser wavelengths confirmed higher uptake of key plant nutrients such as magnesium (Mg) and calcium (Ca) from Lunar regolith simulant. These results support the potential of LIBS as a diagnostic tool for plant growth monitoring in extraterrestrial environments.
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All authors T. Vozár, L. Čechová, J. Buday, M. Füleky, K. Molnárová, L. Lenža, J. Mužík, Y. Koshiba, M. Smrž, P. Pořízka, J. Kaiser
Biological Physics
Neural Investment as an Entropy-Budget Strategy: A Thermodynamic Derivation of Primate Longevity from the Principle of Biological Time Equivalence
Mesfin Taye
Primates exhibit a robust deviation from canonical allometric scaling: at fixed body mass, their lifespans exceed those of non-primate mammals by factors of two to three. A rhesus macaque (8 kg) lives 25-40 years, whereas a cat of similar mass rarely exceeds 18 years. This statistically significant clade-level excess cannot be explained by standard metabolic or ecological models. We provide a thermodynamic explanation within the Principle of Biological Time Equivalence (PBTE), where lifespan is determined by a finite cycle budget governed by
entropy production. We show that primates reduce
entropy production per physiological cycle through increased neural energy allocation. The neural power fraction acts as a control parameter, extending the effective lifetime cycle count. Three mechanisms, predictive regulation, enhanced repair, and behavioral buffering, jointly suppress dissipation. This yields a quantitative neuro-metabolic multiplier that explains primate longevity and provides testable predictions linking
brain energetics,
entropy production, and lifespan.
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Physics and Society
Scale-freeness under node removal: a finite-size scaling perspective
Yeonsu Jeong, Deok-Sun Lee, Mi Jin Lee et al. (+1 more)
In heterogeneous network systems such as ecological and social networks, structural stability depends on how connectivity changes under node removal, as different removal sequences can trigger distinct modes of systemic collapse. While robustness to random failures and targeted attacks has been extensively studied, most analyses have focused on connectivity loss or degree distribution, rather than on how scale-invariant organization emerges and evolves with system size. Here we examine how scale-free structure evolves under progressive degree-dependent node removal, systematically varying the hub-protection strength $\theta$. Starting from scale-free networks, we apply the recently developed finite-size scaling (FSS) analysis to node-removed networks and compare the results with those from Kullback-Leibler (KL) divergence-based classification. We find that under random ($\theta=0$) and hub-protecting removal ($\theta>0$), the two criteria largely agree, whereas under hub-preferential removal ($\theta<0$), networks may appear scale-free according to the KL criterion while failing the FSS test of scaling collapse. This discrepancy indicates that similarity to a reference degree distribution does not guarantee the persistence of scale-invariant organization across system sizes. The two diagnostics thus probe complementary aspects of network structure, and their joint use provides a more complete characterization of structural degradation.
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All authors Yeonsu Jeong, Deok-Sun Lee, Mi Jin Lee, Seung-Woo Son
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Fragment-Constrained Charge Equilibration for Charge-Aware Machine Learning Potentials at Electrochemical Interfaces
Akhil Reddy Peeketi, Blas P Uberuaga and Travis E Jones
Predictive simulation of electrochemical interfaces requires atomistic models that capture reactive bond rearrangements, long-range electrostatics, and charge distributions reflecting the electronic distinctness of electrode and electrolyte. Existing charge-aware machine-learned interatomic potentials (MLIPs) built on global charge equilibration (QEq) settle electrode and electrolyte at a common electrochemical potential, leaving no room for the interfacial gradient that the double layer requires and admitting spurious charge transfer between electronically disconnected regions. Per-fragment charge equilibration is the established remedy in classical molecular dynamics, but reliance on predefined molecular
topology has confined it to non-reactive systems. We lift this restriction by making fragment identification itself a differentiable function of atomic geometry, yielding soft fragment-constrained charge equilibration (Soft-FQEq) – a solver layer that restores fragment-resolved charge conservation in reactive MLIPs. The layer consumes four scalar MLP readouts from a shared atomic-feature network – per-atom electronegativity, source charge, short-range energy, and a soft bond connectivity – and returns equilibrated charges together with per-fragment chemical potentials. We implement Soft-FQEq as an extension of the hippynn framework on a HIP-NN feature network and train it on DFT energies, forces, and DDEC6 charges for IrO2/H2O/Na+/ClO4- interfaces. The trained model recovers a clear electrode-to-electrolyte gradient in the per-atom electrochemical potential. With the same trained weights but the fragment-constrained solver replaced by global QEq at inference, this gradient collapses to an essentially uniform profile, directly showing that the gradient cannot be sustained within global QEq while the fragment formulation recovers it.
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Optics
Low-cost passive single-shot ultrafast imaging at 685 Gfps
Dilem Eşlik, Bahad{\i}r Utku Kesgin and Uğur Teğin
Capturing ultrafast transient phenomena conventionally requires streak cameras or computational imaging based on compressed sensing, which lead to complex and costly systems. In this Letter, we demonstrate, to the best of our knowledge, the first fully passive single-shot ultrafast imaging architecture assembled entirely from off-the-shelf, low-cost components. A commercial microlens array combined with a stack of standard microscope cover glasses maps temporal information into multiple spatial channels, and a consumer-grade CMOS image sensor records all delayed replicas within a single camera exposure. The proposed system has a total hardware cost below US\$500 and captures the
evolution of a picosecond
laser pulse with a temporal sampling interval of 1.46~ps, an effective frame rate of 685~Gfps, and a sequence depth of ten frames. The temporal fidelity of the system is verified by recovering the expected Gaussian pulse profile, and the spatial resolution is characterized through a point-source measurement with a point spread function of 1.86 and 1.62 pixels full width at half maximum along the horizontal and vertical directions, respectively. The proposed architecture presents an alternative approach to single-shot ultrafast imaging with a simple, low-cost, computation-free, and fully passive design.
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Optics
Second harmonic generation and third harmonic generation in topological insulator-based van der Waals metamaterials
Alessandra Di Gaspare, Sara Ghayeb, Craig Knox et al. (+3 more)
High-order harmonic generation (HHG) in solids - the frequency up-conversion of an optical signal - is governed by
symmetries. At terahertz (THz) frequencies, HHG is a key technology to access high frequency spectral windows that are usually difficult to cover using conventional solid state
laser technologies. This effect has been recently exploited in
graphene where HHG has been demonstrated, albeit only at odd multiples of the driving frequency owing to its inherent centro-
symmetry. In topological
insulators (TIs), the combination of
spin-orbit interaction and time-reversal
symmetry create an insulating bulk state with an inverted band order, inseparably connected with conducting surface states. TIs have been predicted to support unconventional high harmonic generation from the bulk and topological surface, which are usually difficult to be distinguished. However, no experimental results have been provided, so far. Here, we exploit the strong optical field amplification provided by an array of single or double split ring resonators, with embedded Bi2Se3 or (InxBi(1-x))2Se3/ Bi2Se3 van der Waals
heterostructures, to achieve up-conversion in the 6.4 (even) - 9.7 (odd) THz frequency range. This results from bulk centro-
symmetry (odd states) and
symmetry breaking in the topological surface states (odd and even).
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All authors Alessandra Di Gaspare, Sara Ghayeb, Craig Knox, Edmund H. Linfield, Joshua Freeman, Miriam S. Vitiello
Biological Physics
The Lifetime Cardiac-Cycle Invariant in Endothermic Vertebrates: A 230-Species Comparative Dataset, Statistical Validation, and Explicit Falsifiability Criteria
Mesfin Taye
A pygmy shrew (Suncus etruscus, ${\approx}2$\,g) sustains a resting heart rate near $1{,}000$\,beats\,min$^{-1}$ and dies within two years; an African elephant (${\approx}4{,}000$\,kg) beats at $28$\,beats\,min$^{-1}$ and lives seven decades. Their chronological lifespans differ by a factor of 35, yet each accumulates close to $10^9$ cardiac cycles before death – a near-constancy first noted by Rubner~(1908) and quantified by Lindstedt and Calder~(1981)~\cite{lindstedt1981}, but never subjected to multi-clade statistical testing, phylogenetic correction, or explicit falsifiability criteria with a large modern
dataset. We address this gap with a curated 230-species vertebrate
dataset spanning non-primate placentals ($n=43$), primates ($n=18$), marsupials and monotremes ($n=19$), duty-cycle-corrected bats ($n=31$), dive-corrected cetaceans ($n=12$), birds ($n=78$), and Arrhenius-corrected ectotherms ($n=26$), and subject the log-invariant $\ell = \log_{10}(N^{\!\star})$ – where $N^{\!\star} = f_H\,L\times 525{,}960$ cardiac cycles – to four independent tests.
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Instrumentation and Detectors
Optimisation of a silicon-tungsten electromagnetic calorimeter energy response to photons
Yukun Shi and Vincent Boudry
An innovative path for the detectors at future
colliders to achieve higher performances is to use a Particle Flow approach, which requires highly granular calorimeters to image individual showers. The silicon-tungsten electromagnetic calorimeter (SiW-ECAL) aims at fulfilling all the expected physical and technical requirements. SiW-ECAL has been developed by the CALICE and ILD collaborations for more than two decades and is now reaching maturity, for linear machines. However, with the tendency towards circular machines, the progress of electronics and the rapid advancement of machine learning (ML) techniques, the SiW-ECAL design needs to be reoptimised to enhance its performance. This study develops ML-based reconstruction approaches for SiW-ECAL, achieving an approximate 20% improvement in energy resolution in the low-energy range and effectively correcting energy leakage in the high-energy range. Subsequently, the SiW-ECAL design is reoptimized based on this method.
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Fluid Dynamics
Mixing and spreading of gravity currents in heterogeneous porous media
Albert Jiménez-Ramos and Juan J. Hidalgo
We analyze the mixing, migration and spreading of a
gravity current in a heterogeneous porous medium using high-fidelity numerical simulations. Heterogeneity is represented by log-normal permeability fields of varying correlation lengths and variance. Stable and unstable density stratification scenarios are considered through linear and non-monotonic density laws, respectively. Heterogeneity reduces dissolution and increases the speed of the
gravity current proportionally to the Rayleigh number. In the unstable case, heterogeneity accelerates the onset of convection. Convection-driven dissolution slows down the
gravity current and counteracts the dispersive effect of heterogeneity resulting in a narrower interface and higher dissolution than in the stable case. Permeability anisotropy reduces dissolution because of the barrier effect of low permeability regions, except when blobs of buoyant fluid are trapped in low permeability structures and rapidly dissolve. The variance of the log-permeability field enhances dissolution. However, the homogeneous case outperforms heterogeneous cases except when Rayleigh number is small. This suggest an interaction between the size of the instabilities, the correlation length of the permeability field and the dispersive and barrier effects of the permeability field that controls dissolution efficiency.
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Applied Physics
Stabilisation of NV centres in diamond nanopillars at low temperature
Ravi Kumar, Saksham Mahajan, Felix Donaldson et al. (+8 more)
Degradation of near surface nitrogen vacancy (NV) centers in diamond under optical illumination has restricted their deployment in applications such as scanning NV magnetomety, particularly under harsh environment such as low temperatures and
vacuum. Previously, alumina passivation of planar diamond samples has been shown to reduce the degradation of near surface ensemble NV centers in
vacuum. Here, we expand this study to incorporate photonic nanostructures by analyzing the single
photon emission characteristics of NV centers embedded in an array of alumina-coated diamond nanopillars in high
vacuum and low temperature (6K, high
vacuum) environments under non-resonant (522 nm)
laser exposure. We find that, in contrast to the oxygen-terminated diamond nanopillars, NV centers in the alumina-coated nanopillars demonstrate negligible change in the single
photon purity and brightness over the course of
laser exposure in
vacuum. At low temperature, NV centers under alumina termination demonstrate stable single
photon emission, whereas under oxygen termination the single
photon purity degrades under high intensity
laser exposure. Alumina surface passivation is therefore shown as a viable path toward the realization of robust NV-diamond based nanoscale sensing under non-ambient atmospheric environments, including using diamond scanning probes.
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All authors Ravi Kumar, Saksham Mahajan, Felix Donaldson, Leonardo Santoni, Aysha A. Riaz, Gediminas Seniutinas, Felipe Favaro de Oliveira, Anna Regoutz, Fabrizia Foglia, Siddharth Dhomkar, John J.L. Morton
Plasma Physics
Chirp-controlled plasma wake excitation by an exponential laser pulse in underdense plasma
Ajit Kumar Kushwaha, Dinkar Mishra, Shivani Aggarwal et al. (+2 more)
The excitation of
plasma wakefields driven by chirped
laser pulses is investigated using a reduced relativistic fluid Poisson model supported by fully relativistic particle in
cell (PIC) simulations. The study considers exponential, linear, quadratic, and unchirped phase-modulated
laser drivers propagating in an underdense
plasma. Numerical solutions of the governing equations demonstrate that exponential chirping produces enhanced wakefield amplitudes compared to
polynomial and unchirped cases due to nonlinear phase variation across the pulse envelope. The analytical predictions are validated using quasi cylindrical PIC simulations performed under identical
plasma and
laser parameters. The simulations reveal strong chirp dependent wakefield modification, with positively chirped pulses generating peak accelerating fields exceeding 58 GV per m, accompanied by pronounced density compression and enhanced electron momentum gain. These results demonstrate that exponential chirping provides an effective mechanism for controlling wakefield strength and improving
plasma based particle acceleration.
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All authors Ajit Kumar Kushwaha, Dinkar Mishra, Shivani Aggarwal, Saumya Singh, Bhupesh Kumar
Optics
YOSO: single-frame Gerchberg-Saxton phase retrieval with AI-based data augmentation for in-line holography
Julianna Winnik, Adam Walocha, Wojciech Ogonowski et al. (+9 more)
We present YOSO (You Only Shot Once), a single-frame phase
retrieval framework for digital in-line
holographic microscopy (DIHM) in which supervised deep learning is used to numerically generate an additional hologram corresponding to different defocus distance, creating a so-called multi-height
dataset, which is then conventionally processed with a well-established Gerchberg-Saxton (GS)
algorithm. YOSO is trained on computer-generated data derived from natural images, enabling strong generalization. The selected multi-scale ResNet architecture enables rapid training in under two hours on a mid-range workstation, which is done only once, enabling efficient inference thereafter. We further show that YOSO network can process inputs of varying spatial dimensions, allowing training on small inputs and direct inference on full-sized holograms while bypassing patch-and-stitch procedure. A further advantage of YOSO is its physics-consistent hologram padding, which replaces conventional zero or edge-value padding with a physically grounded approach compatible with the GS framework. The YOSO framework is tested on various systems (lens-based and lensless DIHM) and diverse samples: a resolution test target, adherent and suspended biological
cells, and a mouse
brain slice. The results show that YOSO is compatible with 3D objects and correctly recovers defocused object wave features, enabling
holographic postprocessing such as numerical refocusing. The results of this work are available publicly as software for end-to-end implementation.
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All authors Julianna Winnik, Adam Walocha, Wojciech Ogonowski, Wiktor Forjasz, Piotr Arcab, Mikołaj Rogalski, Aleksandra Rutkowska, Marzena Stefaniuk, José Ángel Picazo-Bueno, Vicente Micó, Maciej Trusiak, Maria Cywińska
Optics
Leveraging natural fluctuations for matrix-based aberration correction in photoacoustic imaging
Yevgeny Slobodkin and Ori Katz
Photoacoustic imaging is the leading technique for deep tissue optical imaging, allowing single-shot imaging at depths. However, its resolution may be limited by acoustic aberrations, caused by natural unknown heterogeneities in the tissue speed of sound. In recent years, reflection-
matrix based scattering-compensation techniques have been successfully employed in ultrasound, optics, and seismology, to computationally correct such distortions. However, they have not been adapted to photoacoustic imaging since they rely on multiple acquisitions under different controlled excitations, such as input plane-wave illuminations, which do not result in signal changes in photoacoustics. Here, we introduce a framework that enables the direct application of the state-of-the-art reflection-
matrix based aberration correction techniques to photoacoustic imaging of dynamic targets. Specifically, we show that a covariance
matrix analysis of a conventional set of photoacoustic frames of dynamic targets, such as flowing red blood
cells in blood vessels, yields a virtual reflection-
matrix that is mathematically analogous to a pulse-echo reflection-
matrix, and lends itself to direct processing by conventional reflection-
matrix based scattering-compensation
algorithms. We validate and demonstrate the approach for photoacoustic aberration correction of vessel-mimicking targets containing flowing absorbers in both simulations and experiments.
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Instrumentation and Detectors · Cross-listed from quant-ph
Macroscopic photon counting beating the Poisson noise limit
Timon Schapeler, Fabian Schlue, Isabell Mischke et al. (+4 more)
Photon counting is a cornerstone of
quantum optics. Here, we demonstrate precisely counting from 0 to over 9000
photons, beating the Poisson noise limit by at least $4.1~\mathrm{dB}$ across this range. We achieve sub-single-
photon precision up to 276
photons per pulse. To do so, we multiplex eight intrinsically
photon-number-resolving superconducting nanowire single-
photon detectors across 128 temporal modes. We use a model-informed characterization of each of the 1024 detection bins, for optimal precision. We perform
quantum detector
tomography to reconstruct the positive operator valued measures (POVMs) of the complete device, which consists of $1.38\cdot10^8$
matrix elements. At the repetition rate of our experiment of $80~\mathrm{kHz}$, we can precisely count
photons corresponding to an optical power of approximately $71~\mathrm{pW}$, bridging the gap from single-
photon measurements to high-sensitivity optical power meters. A
photon-number-resolving detector of this size, and the tools used to analyze it, will become increasingly important to characterize large
quantum states, as well as tasks in precision metrology and optical power standards.
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All authors Timon Schapeler, Fabian Schlue, Isabell Mischke, Michael Stefszky, Benjamin Brecht, Christine Silberhorn, Tim J. Bartley
Biological Physics · Cross-listed from cond-mat.soft
On Linear and Non-Linear Mechanics of Cyanobacterial Colonies
Yuri Z. Sinzato, Annemieke M. Drost, Dedmer B. Van de Waal et al. (+4 more)
Toxic cyanobacterial blooms are a growing environmental concern that affects freshwater ecosystems, drinking water supplies, and public health. The cyanobacterium Microcystis is among the most important bloom forming species. It often grows in large colonies, which enhances its flotation, reduces grazing, and improves nutrient regulation. Microcystis
cells are held together by a
matrix of extracellular polymeric substances (EPS), making colony mechanics crucial for bloom formation. However, an analysis of the biomechanical properties of cyanobacterial colonies, and how these properties relate to environmental conditions like nutrient availability, remains largely missing. Here, we use micropipette force sensors to quantify the linear and non-linear mechanical properties of individual colonies at single-
cell resolution. Bulk shear rheology complements these measurements by probing macroscopic properties. The measured tensile strength and yield stress are broadly comparable to those of bacterial biofilms and are far greater than the hydrodynamic stresses typically found in wind-mixed lakes. This implies that cyanobacterial colonies are highly resistant to fragmentation by natural mixing processes. We also show that low nutrient availability, particularly low phosphorus, produced stronger colonies, suggesting structural changes in the EPS. Overall, our results establish mechanical testing as a tool for a more complete and physically grounded understanding of cyanobacterial colony formation.
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All authors Yuri Z. Sinzato, Annemieke M. Drost, Dedmer B. Van de Waal, Robert Uittenbogaard, Petra M. Visser, Jef Huisman, Maziyar Jalaal
Optics
Inverse designed metasurfaces for multi-wavelength full-Stokes polarisation imaging
Sarah E. Dean, Neuton Li, Josephine Munro et al. (+7 more)
Multispectral full-Stokes polarisation imaging has a broad range of applications, from biological
cell imaging to agricultural remote surveying. For such applications, especially involving lightweight unmanned aerial vehicles like drones, it is necessary to have compact, single-shot, efficient optical systems. We present a
topology-optimised metasurface design that diffractively separates a scene into spectral and polarimetric measurements, operating for 532 nm and 700 nm in a single-shot imaging system. The polarisation imaging performance of the design is shown in simulation to be robust to critical performance metrics, matching both spectral and angular bandwidth requirements. We fabricated our metasurface design by nanopatterning a TiO$_2$ thin film, and experimentally demonstrate polarisation reconstruction for two wavelengths with a single metasurface structure.
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All authors Sarah E. Dean, Neuton Li, Josephine Munro, Benjamin Laudert, Thomas Siefke, Gia Quyet Ngo, Robert Sharp, Dragomir N. Neshev, Falk Eilenberger, Andrey A. Sukhorukov
Optics · Cross-listed from hep-th
Keidai Akiba and Naoki Yamamoto
Using the path-integral formalism, we show that
photons possess a nontrivial
quantum metric in momentum space. We derive the semiclassical action and equations of motion by taking into account the
quantum metric. In media with a spatially varying refractive index $n(\mathbf{x})$, the
quantum metric induces a shift in the trajectory of light at second order in derivatives of $n$, which may be regarded as a nonlinear
Hall effect of light. The
quantum metric also gives rise to corrections to gravitational
lensing in curved spacetime at the nonlinear order in wavelength. This gravitational nonlinear
Hall effect results from the interplay between the geometry of position space and that of momentum space.
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Optics
Field-driven helicity in solid-state high-harmonic generation
Carlos Batista, Jean Paul Menotti, Dasol Kim et al. (+4 more)
The polarization state of light plays a central role in strong-field light–matter interactions and is widely used to probe electronic structure in solids via high-order harmonic generation (HHG). In particular, helicity-resolved HHG has been interpreted as a fingerprint of
crystal symmetry and
topology. Here, we demonstrate deterministic and continuous control of harmonic helicity in solids using polarization-crafted beams, formed by two orthogonally polarized pulses with a controlled time delay. By tuning this delay, the polarization state of individual harmonics can be driven from linear to circular, independent of the material under investigation. We show that this behavior is robust across systems with distinct
symmetry and
topology, and originates from the sub-cycle modulation of the light–matter interaction mediated by the dipole coupling. Furthermore, the orthogonal configuration allows to break the dynamical
symmetry of the light-matter interaction which is manifested in the generation of otherwise forbidden harmonics under standard selection rules.. These results establish harmonic helicity as a field-controlled observable rather than a direct material fingerprint.
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All authors Carlos Batista, Jean Paul Menotti, Dasol Kim, Bikash Kumar Das, Wenlong Gao, Alexis Chacón, Camilo Granados
Optics
OAM-mode sorting with a wavefront twister
Suman Karan, Swati Chaudhary, Harshwardhan Wanare et al. (+1 more)
We propose an OAM sorter based on a novel optical element that we refer to as a wavefront twister. It is a generalization of the conventional wavefront rotators such as the Dove prism. However, unlike a Dove prism, which simply rotates a wavefront, the rotation generated by a wavefront twister varies linearly with radial position, resulting in the twisting of the wavefront. We demonstrate that the wavefront twister, followed by a lens, maps each OAM mode to an annulus of distinct radius at the back focal plane of the lens with negligible inter-modal overlap and preserves the circular
symmetry. Thus, the proposed wavefront twister offers a scalable scheme for high-dimensional OAM mode sorting, with important consequences for the practical realization of OAM-based applications.
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All authors Suman Karan, Swati Chaudhary, Harshwardhan Wanare, Anand Kumar Jha
Physics and Society
Crowd Dynamics in Historical Perspective: Reframing the Amritsar Massacre through Agent-Based Modelling and Social Psychology
Mohcine Chraibi, Krisztina Konya and Ezel Üsten
Crowds have long held a paradoxical place in the human imagination, feared for their destructive potential yet essential for collective expression. This tension was tragically manifested in the 1919 Jallianwala Bagh massacre, when British colonial troops opened fire on a peaceful gathering in Amritsar, India. Although officially 379 deaths were recorded, eyewitnesses and historians have long challenged this figure. With this study, we critically revisit the events through the lens of the specific role of the crowd as a phenomenon, both regarding the physical and the socio-psychological dynamics. We show that even under conservative physical assumptions - moderate shooting cadence, crowd-shielding, and constrained escape routes - our
agent-based simulations consistently yield fatality estimates well above the official death count. On the socio-psychological front, we explore how early 20th-century discourses, influenced by Le Bon's theory of crowd psychology, constructed the crowd as an inherently irrational and threatening entity, thus providing a rationale for the application of excessive force. Our findings show that acknowledging the socio-cultural construction of crowds as a relevant factor in how state power engage with and respond to collective gatherings brings to light contemporary parallels and the risks posed by their rhetorical framing. Furthermore, this study highlights the importance of interdisciplinary modelling for both historical accountability and current crowd safety, particularly in an era of growing political unrest, surveillance, and militarised crowd policing.
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Optics
Universal Nano-Bead Emitter Inks for Programmable Nanometric Fluorescent Architectures
Ilya Olevsko, Maria Shehadeh, Dmytro Ohorodniichuk et al. (+5 more)
Fabricating brightly fluorescent layers with nanometric thickness and digitally controlled lateral structuration remains a challenge for next-generation photonic devices, optical calibration standards, and biocompatible interfaces. Here, we introduce Nano-Bead Emitters (NBEs), hydrogel nanoparticles covalently functionalized with fluorophores, as a universal, water-processable ink platform for fabricating programmable nanometric fluorescent architectures. By immobilizing fluorophores within a charged nanohydrogel scaffold, the platform entirely decouples film morphology from dye solubility. This molecule-independent strategy enables spectrally distinct, inherently water-insoluble dyes to be processed using a single, standardized aqueous ink formulation. Combined with
laser-induced forward transfer (LIFT) printing, this additive approach yields highly uniform fluorescent layers (~7 nm thickness, sub-nanometric roughness). This structural invariance produces complex multicolor patterns sharing identical thickness and surface morphology across all spectral channels, a critical requirement for quantitative optical calibration. Furthermore, LIFT printing provides programmable, layer-by-layer control over fluorescence intensity via successive deposition cycles, yielding precisely tunable brightness without aggregation-caused quenching. This maskless technique enables rapid, high-fidelity printing of both monochromatic and multicolor patterns over macroscopic areas with absolute spatial resolution. Finally, these universally compatible NBE inks stably deposit onto diverse substrates (glass,
polymers,
semiconductors, metasurfaces), effectively bridging scalable manufacturing with high-performance integrated photonic systems.
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All authors Ilya Olevsko, Maria Shehadeh, Dmytro Ohorodniichuk, Leonid Weisman, Rotem Golan, Martin Oheim, Gerardo Byk, Adi Salomon
Applied Physics · Cross-listed from cond-mat.soft
Guided elastic waves for soft elastomer characterization: an alternative to conventional rheometry
Samuel Croquette, Pierre Chantelot, Daniel A. Kiefer et al. (+2 more)
Elastic wave propagation is intrinsically sensitive to the mechanical properties of the medium through which it travels. In soft elastomers, this makes guided elastic waves natural probes of viscoelastic and acoustoelastic behavior over a broad frequency range. In this work, we introduce a wave-based mechanical characterization method in which a thin elastomer strip acts as a waveguide supporting multiple in-plane guided modes. By combining stroboscopic measurements of monochromatic wave fields with a theoretical framework that couples frequency-dependent viscoelasticity and elongation-dependent acoustoelasticity, we extract complex-valued dispersion relations for guided modes under controlled static elongation. A dedicated numerical implementation allows these experimental dispersion curves to be quantitatively matched to theory, enabling identification of the material's rheological and hyperelastic parameters. Applied to several commercial silicone elastomers, the method yields mechanical parameters that are consistent with conventional plate-plate rheometry, while extending the accessible frequency range beyond that of conventional techniques. By exploiting the richness of guided-wave dispersion and the sensitivity of waves to both frequency and pre-stress, this approach provides a unified, broadband, and experimentally simple route to the mechanical characterization of soft elastomers.
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All authors Samuel Croquette, Pierre Chantelot, Daniel A. Kiefer, Claire Prada, Fabrice Lemoult
Atmospheric and Oceanic Physics
Physically-Informed Fuzzy Clustering of Vertical Sounding Ionograms
Oleg I.Berngardt and Sergey N.Ponomarchuk
This paper presents a physically-informed fuzzy clustering of vertical sounding ionograms for automatically separating the ionogram into tracks suitable for further interpretation and determining their optimal number. The model is designed for use not only in conditions where the number of tracks is known, but also in disturbed ionospheric conditions where the number of tracks is preliminary unknown. The method is based on an expectation-maximization
algorithm, used for clustering, and on parametrically specified distributions of distances from points to parametrically specified curves. The curves used as track models are close to model tracks in the
parabolic ionospheric layer model. The resulting model of each track has six parameters: three standard ones (the critical frequency, the lower boundary of the layer, and its half-width), and three additional ones to take into account possible underlying layer effects. By sequentially increasing the number of tracks and optimizing their parameters, the model finds the optimal number of tracks on the ionogram by minimizing the modified
Bayesian information criterion. The Sequential Least Squares Quadratic Programming
algorithm is used to find the parameters of a single track. The width of each single track is assumed to be unknown constant found during fitting process. To improve the quality of ionogram clustering, automatic adaptive noise filtering is performed before clustering. This filtering is based on a combination of the DBSCAN and Gaussian Mixture
algorithms. Also, to improve clustering quality on an ionosonde without hardware separation of the ordinary and extraordinary components, a preliminary approximate removal of points belonging to the extraordinary mode is performed.
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Optics · Cross-listed from cond-mat.mes-hall
Size-Limited Room Temperature Single-Photon Emission from Sidewall-Treated Fractional Dimension InGaN Quantum Dots: Determined by Density-of-States-Corrected Ultrafast Carrier Dynamics and Improved Signal-to-Noise Ratio
Pratim K. Saha
Room-temperature single-
photon emission (SPE) resulting from a biexciton-
exciton cascaded decay is demonstrated for the first time from chemically and photoelectrochemically etched site-controlled In0.14Ga0.86N
quantum dots (QDs) embedded in vertical GaN nanowires. Diameter-dependent biexciton-
exciton dynamics are analysed to determine the eligibility of QD as a single-
photon emitter. The signal-to-noise ratio degrades with increasing QD diameter. Background noise
photons pose a bottleneck to achieving SPE. This is also explained from a carrier dynamics perspective. Surface recombination contributes to inhomogeneous broadening at QD diameters larger than 35 nm. Below 35 nm, density-of-states-corrected Auger gradually becomes the principal biexciton-decay route with further reduction in QD diameter, thereby quenching the possibility of thermal broadening and setting a threshold for SPE. Below 9 nm, the Auger recombination rate becomes manyfold of other decay rates, causing multi-
photon suppression via single Auger decay to form an
exciton. Surface recombination probability of this
exciton is minimized while biexciton state filling probability is maximized by reducing sidewall surface states through wet-treatment. These improve biexciton state preparation and enhance the single-
photon purity of the
exciton towards the
exciton Bohr radius (3 nm) regime. Far away from this regime, higher-order autocorrelations to characterize
quantum emission involving multi-
photon events are discussed. This study establishes a generalized physical framework for predetermining SPE probability as a function of QD surface and geometry down to the
exciton Bohr radius regime, with practical implementations. This work shows the pathway to design and develop next-generation
semiconductor QDs for high-purity room-temperature SPE.
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Accelerator Physics
The impact of experimental conditions on the observation of channeling and crystalline undulator radiation
Maykel Marquez-Mijares, German Rojas-Lorenzo, Jesus Rubayo-Soneira et al. (+3 more)
In this study, we present a comprehensive quantitative analysis of the radiation emitted by 855 MeV electrons propagating through an oriented diamond hetero-
crystal. The
crystal consists of two distinct segments: (i) a straight single-
crystal diamond substrate, and (ii) a diamond layer that is periodically doped with boron atoms. The doping profiles were derived from precise experimental measurements of boron concentration obtained during the layer fabrication via Microwave
Plasma Chemical Vapor Deposition (MPCVD). Our study systematically investigates the channelling and the crystalline undulator radiation, accounting for the different doping profiles in the undulating region. The simulations were conducted using the advanced MBNExplorer software package, which enables detailed modeling of particle trajectories and radiation emission. We report on good agreement with experiment and discuss remaining discrepancies providing possible explanations for them. The results obtained show that the radiation intensity is significantly affected by a range of factors, including the angular divergence of the incident beam, its orientation with respect to the target, the direction in which the emitted radiation is detected, and the choice of the doping profiles. These findings are important for optimising the design of crystalline undulators as novel gamma radiation light sources.
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All authors Maykel Marquez-Mijares, German Rojas-Lorenzo, Jesus Rubayo-Soneira, Thu Nhi Tran Caliste, Andrei V. Korol, Andrey V. Solov'yov
Fluid Dynamics
Cahn-Hilliard Phase Field modelling captures nanoscale contact line dynamics on high-friction surfaces
Michele Pellegrino, Parvathy K. Kannan, Gustav Amberg et al. (+3 more)
Incorporating molecular-scale effects in the description of contact line motion is essential for accurately capturing all sources of energy dissipation in wetting dynamics. This holds particularly true in the cases where contact line friction dominates, and hydrodynamics models struggle to achieve regularisation due to the negligible Navier slip. We perform Molecular Dynamics simulations of water/hexane biphasic systems in a two-phase Couette flow configuration. Wetting occurs over a silica-like surface with controllable wettability. The simulation results are reproduced by a Phase Field model (Cahn-Hilliard Navier-Stokes equations), which includes localised contact line slip and contact angle dynamics. The continuous equations are directly parametrized from Molecular Dynamics simulation results, under the numerical sharp interface limit. We demonstrate that the Phase Field model can quantitatively reproduce Molecular Dynamics through a systematic calibration protocol. Critically, we show that contact line friction is the primary physical parameter requiring empirical calibration based on Molecular Dynamics data. Once extracted by matching contact angle dynamics, quantitative agreement across multiple observables is obtained, including interface
curvature, steady contact line displacement, and the structure of streamlines. All other model parameters are determined a posteriori, according to the calculation of independent observables and under numerical constraints. The results presented in this article indicate that Phase Field modelling can capture the net effect of molecular processes on the mobility of contact lines and that the careful calibration of contact line friction based on the reconstruction of contact angle dynamics and interface bending is key to fully reconcile continuous models with Molecular Dynamics.
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All authors Michele Pellegrino, Parvathy K. Kannan, Gustav Amberg, Shervin Bagheri, Outi Tammisola, Berk Hess
Computational Physics · Cross-listed from cond-mat.mtrl-sci
VibroML: an automated toolkit for high-throughput vibrational analysis and dynamic instability remediation of crystalline materials using machine-learned potentials
Rogério Almeida Gouvêa and Gian-Marco Rignanese
While machine-learned interatomic potentials (MLIPs) accelerate
phonon dispersion calculations, merely identifying dynamical instabilities in computationally predicted materials is insufficient; automated pathways to resolve them are required. We introduce VibroML, an open-source Python toolkit driven by foundational MLIPs that shifts the paradigm from stability verification to automated structural remediation. VibroML employs an energy-guided genetic
algorithm that vastly outperforms traditional soft-mode following, efficiently navigating the potential energy surface to uncover diverse, dynamically stable polymorphs. As 0 K harmonic stability does not guarantee macroscopic viability, an automated molecular dynamics workflow evaluates finite-temperature structural retention. VibroML also couples with ProtoCSP, our combinatorial structure prediction engine, to stabilize frustrated
crystal topologies via targeted alloying, successfully rescuing functional perovskite networks like Cs$_2$KInI$_6$ and KTaSe$_3$. Demonstrating broader applicability, we mined the Alexandria database – where ~50% of quaternary and 99.5% of quinary elemental combinations lack any structural entries – to identify thousands of abandoned, high-
symmetry stoichiometries. Deploying ProtoCSP's "cold start"
retrieval and VibroML's evolutionary search on a sample, we successfully identified dynamically stable low-
symmetry candidates. Through integrated structural remediation, thermal validation, and systematic compositional exploration, VibroML enables a comprehensive deep-screening approach, yielding physically sound structural propositions that far surpass standard high-throughput workflows.
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Atmospheric and Oceanic Physics
Quantifying the safe operating space for the Amazon rainforest under climate change and deforestation
Jonathan Krönke, Arie Staal, Jonathan F. Donges et al. (+2 more)
The Amazon rainforest is considered one of the core tipping elements in the
climate system with a potential tipping point from rainforest to savannah between 2 and 6 {\deg}C of global warming. However, ongoing deforestation constitutes an additional major threat to the Amazon rainforest that acts simultaneously to undermine the stability of the rainforest. Both effects could synergistically compound and lower the overall threshold in global warming and deforestation when tipping points may be crossed. Here, we quantify the safe operating space of the Amazon rainforest, which we define as the joint global warming and deforestation conditions where resilience of the system as a whole is preserved. Based on the underlying environmental data from a global
climate model, we use a reduced complexity model and explicitly take into account the adaptive capacities of the forest as well as the atmospheric moisture recycling. We quantify that under current conditions of around 1.4 {\deg}C of global warming and around 17 % of deforestation, more than a third of the Amazon rainforest is at high risk of crossing critical thresholds. We therefore conclude that the Amazon rainforest may have already left its safe operating space. Furthermore, we find that the historic and projected deforestation pattern could be particularly detrimental. Our results support the need for ambitious
climate action to hold the Paris
climate target and also nature protection to end net deforestation.
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All authors Jonathan Krönke, Arie Staal, Jonathan F. Donges, Johan Rockström, Nico Wunderling