Space Physics
LEVITAS: Levitodynamics for Accurate Individual Particle Sensing in Space
Rafal Gajewski, Ravindra T Desai, James Bateman et al. (+3 more)
Accurately observing the rarefied media of the upper atmosphere, exosphere, and planetary and
solar system environments and beyond requires highly sensitive metrological techniques. We present the operating concept and architecture of an in-situ sensing solution based on the dynamics of a levitated nanoparticle (levitodynamics). It can detect and measure impacts of individual particles in rarefied media. Dubbed `LEVITAS', our sensor consists of a dispenser of dielectric nanoparticles and optical trapping of a single nanoparticle in the focus of a
laser beam. The trapped nanoparticle constitutes a harmonic oscillator at frequencies in the kilohertz range whose position can be tracked at the standard
quantum limit by interferometric detection of the
laser photons it scatters. Here, we simulate microcanonical impacts on the nanoparticle and show that the density, velocity, temperature, and composition of the surrounding medium can be estimated accurately. We illustrate the performance of LEVITAS in circumstances ranging from low Earth orbit out to exospheric distances, across which individual impacts can be detected at favourable rates. Furthermore, LEVITAS may be employed to accurately measure highly rarefied neutral distributions within vastly different areas of momentum space. This we demonstrate by simulating the measurement of high-velocity neutral gas particles from the interstellar medium penetrating the heliosphere and flowing through our
solar system.
Read the full abstract ▾
All authors Rafal Gajewski, Ravindra T Desai, James Bateman, Bengt Eliasson, Daniel K L Oi, Animesh Datta
Fluid Dynamics
Characterisation and extension of a rigid body dynamics solver coupled with OpenFOAM for flight performance analysis of flapping-wing drones
Romain Poletti, Emanuele Bombardi, Lilla Koloszar et al. (+2 more)
The extraordinary aerial agility of hummingbirds and insects continues to inspire the design of flapping-wing drones. To replicate and analyze such flight, computational fluid dynamics (CFD) simulations that couple flow solvers with rigid body dynamics are essential. While OpenFOAM offers tools for these multiphysics simulations, two key limitations remain: (1) a lack of thorough verification and performance characterization, and (2) the reliance on torque-based control for wing motion, which is impractical for parametric studies and real-time control. The developments are tested with a four and a five degrees of freedom flapping-wing drone equipped with a rigid, semi-elliptical wing. Ascending flight motions are simulated using the overset method, a moving background grid, and an LES model. Parametric studies demonstrate the independence of the grid and integration schemes, while profiling analyses identify the overset method as the computational bottleneck. The drone trajectories are compared with those from a literature quasi-steady model, and the body-wing interaction is analyzed in detail.
Read the full abstract ▾
All authors Romain Poletti, Emanuele Bombardi, Lilla Koloszar, Miguel Alfonso Mendez, Joris Degroote
Geophysics · Cross-listed from eess.SP
Heuristic Quality Coefficients for Interferometric Phase Linking
Magnus Heimpel, Irena Hajnsek and Othmar Frey
In multitemporal InSAR, phase linking (PL) refers to the estimation of a single-reference interferometric phase history for distributed scatterers (DS) from the information contained in the sample coherence
matrix. Because the phase information in this
matrix is typically inconsistent, DS processing needs practical reliability indicators to decide whether a pixel's PL estimate is sufficiently supported by the data for subsequent deformation analysis. For maximum-likelihood estimation, uncertainty can be quantified via Fisher-information-based covariance estimates, but no analogous, generally applicable uncertainty quantification is available for the broad range of non-ML methods. We propose three heuristic quality coefficients within a unified mathematical framework that covers common PL methods: (1) a method-specific goodness-of-fit coefficient that normalizes the achieved PL objective between a method-consistent upper bound and an empirically modeled noise floor level; (2) a closure phase coefficient computed from the sample coherence
matrix in advance; and (3) an ambiguity coefficient that compares the obtained PL estimate with the best alternative in its orthogonal complement in the solution space. All coefficients are normalized to the interval $[0,1]$, where 1 indicates maximum reliability and 0 matches the behavior expected under pure noise. Simulations under exponential and seasonal decorrelation models show that the goodness-of-fit coefficient tracks the normalized absolute phase error most consistently, whereas the closure phase coefficient provides an a priori indicator for pre-screening. Experiments on a TerraSAR-X stack over Visp, Switzerland, reveal plausible spatial patterns across urban and vegetated areas and show that the ambiguity coefficient provides complementary information, especially in regions with temporally varying scattering mechanisms.
Read the full abstract ▾
Optics
Anisotropic Hot Carrier Relaxation and Coherent Phonon Dynamics in Type-II Weyl Semimetal TaIrTe4
Zheng Zhu, Jingwen Wang, Hao Yu et al. (+5 more)
The unique energy band and
crystal structure of the layered type-II Weyl semimetal TaIrTe4 hold great promise for high-performance broadband anisotropic optoelectronic devices. Therefore, gaining an in-depth understanding of the interactions between internal microscopic particles is of vital importance. Here, we employ a two-color pump-probe system to reveal the anisotropic electron-
phonon coupling (EPC) and coherent
phonon dynamics in bulk TaIrTe4. The carrier relaxation exhibits a four-exponential decay process, with strong dependence on polarization of probe pulse, indicating that EPC strength is closely related to the
crystal axes (a/b-axes). In addition, we observe three coherent
phonon modes in bulk TaIrTe4: 38.5 GHz, 0.44 THz and 1.29 THz. Their oscillation amplitudes and dephasing times also show anisotropic responses to the probe polarization. We also investigate the in-plane cross-directional thermal conductivity coefficient of TaIrTe4 by beam-offset frequency-domain thermal reflection (FDTR). The thermal conductivity coefficient along the a-axis and b-axis directions are ka=14.4 W/mK and kb=3.8 W/mK, respectively. This represents a significant in-plane anisotropy. Our work not only reveals the key role of anisotropic EPC in controlling the thermal and optical properties of TaIrTe4, but also provides insights into designing polarization-sensitive optoelectronic devices based on topological semimetals.
Read the full abstract ▾
All authors Zheng Zhu, Jingwen Wang, Hao Yu, Jialin Lu, Tianshu Lai, Peng Yu, Tianran Jiang, Ke Chen
Computational Physics · Cross-listed from cond-mat.dis-nn
Deep-Learning-Empowered Programmable Topolectrical Circuits
Hao Jia, Shanglin Yang, Jiajun He et al. (+9 more)
Topolectrical
circuits provide a versatile platform for exploring and simulating modern physical models. However, existing approaches suffer from incomplete programmability and ineffective feature prediction and control mechanisms, hindering the investigation of physical phenomena on an integrated platform and limiting their translation into practical applications. Here, we present a deep learning empowered programmable topolectrical
circuits (DLPTCs) platform for physical modeling and analysis. By integrating fully independent, continuous tuning of both on site and off site terms of the
lattice Hamiltonian, physics graph informed inverse state design, and immediate hardware verification, our system bridges the gap between theoretical modeling and practical realization. Through flexible control and adiabatic path engineering, we experimentally observe the boundary states without global
symmetry in higher order topological systems, their adiabatic phase transitions, and the flat band like characteristic corresponding to Landau levels in the
circuit. Incorporating a physics graph informed mechanism with a generative AI model for physics exploration, we realize arbitrary, position controllable on board Anderson localization, surpassing conventional random localization. Utilizing this unique capability with high fidelity hardware implementation, we further demonstrate a compelling cryptographic application: hash based probabilistic information encryption by leveraging Anderson localization with extensive disorder configurations, enabling secure delivery of full ASCII messages.
Read the full abstract ▾
All authors Hao Jia, Shanglin Yang, Jiajun He, Shuo Liu, Haoxiang Chen, Ce Shang, Shaojie Ma, Peng Han, Ching Hua Lee, Zhen Gao, Yun Lai, Tie Jun Cui
Physics and Society
Pair Approximation Meets Reality: Diffusion of Innovation in Organizational Networks within the biased-independence q-Voter Model
Angelika Abramiuk-Szurlej and Katarzyna Sznajd-Weron
Collective adaptation, whether in innovation adoption, pro-environmental or organizational change, emerges from the interplay between individual decisions and social influence.
Agent-based modeling provides a useful tool for studying such processes. Here, we introduce the biased-independence $q$-voter model, a generalization of the $q$-voter model with independence, one of the most popular
agent-based models of opinion dynamics. In our model, individuals choose between two options, adopt or not adopt, under the competing influences of conformity and independent choice. Independent choice between two options is determined by an engagement parameter, inspired by earlier
agent-based model of eco-innovation
diffusion. When the engagement parameter equals $0.5$, the model reduces to the original $q$-voter model with independence; values different from $0.5$ break the
symmetry between the two options. To place our study in a broader context, we briefly review asymmetric versions of the $q$-voter model proposed to date. The novelty of this work goes beyond introducing a generalized model: we develop the pair approximation (PA) for an asymmetric $q$-voter model and, for the first time, validate it on empirical organizational networks. Our results show that the interplay of social influence, independence, and option preference generates discontinuous phase transitions and irreversible hysteresis, reflecting path-dependent adoption dynamics. Surprisingly, the PA agrees well with Monte Carlo simulations on some empirical networks, even small ones, highlighting its potential as a computationally efficient bridge between individual decision-making and collective actions.
Read the full abstract ▾
Instrumentation and Detectors · Cross-listed from cond-mat.mtrl-sci
Noise Estimation and Suppression in Quantitative EMCD Measurements
Hitoshi Makino, Bernd Rellinghaus, Sebastian Schneider et al. (+2 more)
Quantitative electron
magnetic circular dichroism (EMCD) in transmission electron microscopy (TEM) enables the measurement of
magnetic moments with elemental and atomic site sensitivity, but its practical application is fundamentally limited by noise. This study presents a comprehensive methodology for noise estimation and suppression in EMCD measurements, demonstrated on Ti-doped barium hexaferrite lamellae. By employing a classical three-beam geometry and long-term acquisition of electron energy-loss spectra, we systematically analyze the signal-to-noise ratio (SNR) across individual energy channels using bootstrap statistics. A robust energy
alignment procedure based on the neighboring Ba-M4,5 edges with an adequate energy upsampling is introduced to minimize systematic errors from energy misalignment. The impact of detector noise, particularly from CMOS-based EELS cameras, is evaluated through variance-to-mean analysis and described by the noise amplification coefficients, revealing that detector-amplified shot noise is the dominant noise source. We recommend a stricter SNR threshold for reliable EMCD detection and quantification, ensuring that critical spectral features such as the Fe-L2,3 peaks meet the requirements for quantitative analysis. The approach also provides a framework for determining the minimum electron dose necessary for valid measurements and can be generalized to scintillator-based or direct electron detectors. This work advances the reliability of EMCD as a quantitative tool for
magnetic characterization at the nanoscale with unknown
magnetic structures. The proposed procedures lay the groundwork for improved error handling and SNR optimization in future EMCD studies.
Read the full abstract ▾
All authors Hitoshi Makino, Bernd Rellinghaus, Sebastian Schneider, Axel Lubk, Darius Pohl
Instrumentation and Detectors
ASTAROTH: A Novel Detector for Dark Matter Direct Detection Using Cryogenic SiPMs
Edoardo Martinenghi, Valerio Toso, Fabrizio Bruno Armani et al. (+12 more)
The DAMA experiment's long-standing claim of dark matter detection remains a key open issue in astroparticle physics. Independent verification requires NaI(Tl)-based detectors with enhanced low-energy sensitivity. Current detectors rely on photomultiplier tubes (PMTs) which features limited detection efficiency, intrinsic radioactivity, and high noise at keV energies. ASTAROTH is an R&D project that developed a proof of concept NaI(Tl) detector where siliconphotomultipliers (SiPMs) have been used instead of PMTs, offering higher
photon detection efficiency, negligible radioactivity, and, most of all, a reduction of two orders of magnitude in the dark noise. The setup includes a custom cryostat operating at approximately 80 K. We report the first characterization of an approximately 360 g NaI(Tl)
crystal coupled to a 5 x 5 cm SiPM
matrix, yielding 4.5 photoelectrons\keV after crosstalk correction. This promising result demonstrates the feasibility of SiPM-based readout for NaI(Tl) and paves the way for future large-scale dark matter experiments.
Read the full abstract ▾
All authors Edoardo Martinenghi, Valerio Toso, Fabrizio Bruno Armani, Andrea Castoldi, Giuseppe Di Carlo, Luca Frontini, Niccolò Gallice, Chiara Guazzoni, Valentino Liberali, Lorenzo Rutigliani, Alberto Stabile, Krzysztof Szczepaniec, Valeria Trabattoni, Andrea Zani, Davide D'Angelo
Classical Physics
Analytic Harmonic Tunable Closed Orbits of Trapped N-Body Systems
Joseph West
The motion of each particle in an N body system of identical masses interacting via an attractive or repulsive pairwise linear force law, the "Swarm," and with an external attractive or repulsive linear force law, the "Trap," is considered. In all Swarm and Trap combinations the motion of all N particles is completely separable and positions are found as a function of time in simple analytic form. in all attractive Traps the center of mass of the Swarm is bound to the center of the trap. For attractive or weakly repulsive Swarms in an attractive Trap the particles are bound to the center of mass of the Swarm and an infinite set of Swarm to Trap force constant ratios result in every particle executing a closed periodic orbit. Figures are provided of trajectories for various combinations of Swarm and Trap force constants. The derivations are suitable for the advanced undergraduate classroom.
Read the full abstract ▾
Atomic Physics
Comprehensive Inclusion of Higher-order Ca$^+$ Isotope Shifts in the King's Plot Yields an Order Improvement on the $e^-$-$n$ Coupling Limit
Vaibhav Katyal, A. Chakraborty and B. K. Sahoo
By critically evaluating higher-order nonlinear effects to the isotope shifts (ISs) in the low-lying transition frequencies of the singly charged calcium ion, stringent constraint on the electron-
neutron coupling due to a hypothetical
boson describing physics beyond the Standard Model is inferred. It shows an order magnitude difference compared to the previously reported limit demonstrating importance of higher-order effects in the analysis of nonlinearity in the King's plot. The first-order IS parameters and enhancement factor ($D$) were evaluated using two complementary approaches in the relativistic coupled-cluster theory framework: namely finite-field (FF) and analytical response (AR) approaches. Extraction of the second-order IS parameters in the FF approach show numerical instabilities, so they are determined in the AR approach. Comparison of these factors with previous calculation shows substantial differences in the magnitudes. However, $D$ values from both the FF and AR approaches display excellent agreement. We also show explicitly roles of electron correlation effects in the evaluation of $D$ values accurately.
Read the full abstract ▾
Optics
Fluorescence intensity correlations enable 3D imaging without sample rotations
Robert G. Radloff, Felix F. Zimmermann, Siqi Li et al. (+23 more)
Lensless X-ray imaging provides element-specific nanoscale insights into thick samples beyond the reach of conventional light and electron microscopy. Coherent diffraction imaging (CDI) methods, such as ptychographic
tomography, can recover three-dimensional (3D) nanoscale structures but require extensive sample rotation, adding complexity to experiments. X-ray elastic-scattering patterns from a single sample orientation are highly directional and provide limited 3D information about the structure. In contrast to X-ray elastic scattering, X-ray fluorescence is emitted mostly isotropically. However, first-order spatial coherence has traditionally limited nanoscale fluorescence imaging to single-crystalline samples. Here, we demonstrate that intensity correlations of X-ray fluorescence excited by ultrashort X-ray pulses contain 3D structural information of non-periodic, stationary objects. In our experiment, we illuminated a vanadium foil within a sub-200 nm X-ray
laser beam focus. Without changing the sample orientation, we recorded 16 distinct specimen projections using detector regions covering different
photon incidence angles relative to the X-ray free-electron
laser (FEL) beam. The projections varied systematically as the fluorescing volume was translated along an astigmatism, confirming that FEL-induced fluorescence reflects real-space structural changes. Our results establish a new approach for lensless 3D imaging of non-periodic specimens using fluorescence intensity correlations, with broad implications for materials science, chemistry, and nanotechnology.
Read the full abstract ▾
All authors Robert G. Radloff, Felix F. Zimmermann, Siqi Li, Stephan Kuschel, Anatoli Ulmer, Yanwen Sun, Takahiro Sato, Peihao Sun, Johann Haber, Diling Zhu, Miklós Tegze, Gyula Faigel, Matthew R. Ware, Jordan T. O'Neal, Jumpei Yamada, Taito Osaka, Robert Zierold, Carina Hedrich, Dimitrios Kazazis, Yasin Ekinci, Makina Yabashi, Ichiro Inoue, Andrew Aquila, Meng Liang, Agostino Marinelli, Tais Gorkhover
Plasma Physics
Physics-Gated Visual Prediction of MARFE on the HL-3 Tokamak
Qianyun Dong, Rongpeng Li, Zongyu Yang et al. (+5 more)
The Multifaceted Asymmetric Radiation From the Edge (MARFE) is a critical
plasma instability that often precedes density-limit disruptions in tokamaks, posing a significant risk to machine integrity and operational efficiency. We develop a physics-gated, continuous MARFE monitor for the HL-3 tokamak that outputs a per-frame intensity probability every $2$\,ms, which can potentially be used by the shape-target controller in the
plasma control system. Our framework integrates two core innovations: (1) a physics-scored, weighted Expectation-Maximization (EM) pipeline that refines noisy visual labels using $(n_e, T_e, f_G, t)$ as a
Bayesian prior, and (2) a continuous-time, physics-gated Neural Ordinary Differential Equation (Neural ODE) backbone whose dynamics are modulated by a sigmoid gate on $f_G$ and $T_e$. Meanwhile, the Neural ODE adopts a $40$\,ms forward
forecasting horizon to accommodate the actuator-response budget. On a frozen $140$-shot held-out test set, the proposed method yields a median label-aligned lead time of $+36$\,ms, close to this design horizon. Against a Bi-LSTM baseline trained under the matched protocol, the proposed Neural ODE attains Area Under the Curve (AUC) $=0.981$ and sample-level $F_1=0.840$, compared with AUC $=0.960$ and sample-level $F_1=0.779$ for the baseline. The deployed inference service runs within a $1$-ms control-cycle budget, while new diagnostic samples are generated at the $2$-ms frame cadence.
Read the full abstract ▾
All authors Qianyun Dong, Rongpeng Li, Zongyu Yang, Niannian Wu, Fan Xia, Liang Liu, Zhifeng Zhao, Wulyu Zhong
Chemical Physics
Regularised density-potential inversion for periodic systems: application to exact exchange in one dimension
Oliver M. Bohle, Maryam Lotfigolian, Andre Laestadius et al. (+1 more)
A detailed convex analysis-based formulation of density-functional theory for periodic systems in arbitrary dimensions is presented. The electron-electron interaction is taken to be of Yukawa type, harmonising with underlying function spaces for densities and wave functions. Moreau–Yosida regularisation of the underlying non-interacting density functionals is then considered, allowing us to recast the Hohenberg–Kohn mapping in a form that is insensitive to perturbations (non-expansiveness) and lends itself to numerical implementation. The general theory is exemplified with a numerical Hartree–Fock implementation for one-dimensional systems. We discuss in particular the challenge of self-consistent field optimisation in calculations related to the regularised noninteracting Hohenberg–Kohn map. The implementation is used to demonstrate that it is practically feasible to recover local Kohn–Sham potentials reproducing the effects of exact exchange within this scheme, which provides a proof-of-principle for recovering the exchange-correlation potential at more accurate levels of theory. Error analysis is performed for the regularised inverse Kohn–Sham
algorithm by quantifying, both theoretically and numerically, how perturbations of the input ground-state density propagate through the regularised density-to-potential map.
Read the full abstract ▾
All authors Oliver M. Bohle, Maryam Lotfigolian, Andre Laestadius, Erik I. Tellgren
Biological Physics
Motility-Driven Viscoelastic Control of Tissue Morphology in Presomitic Mesoderm
Sahil Islam, Mohd. Suhail Rizvi and Anupam Gupta
Embryonic tissues deform across broad spatial and temporal scales and relax stress through active rearrangements. A quantitative link between
cell-scale activity, spatial forcing, and emergent tissue-scale mechanics remains incomplete. Here, we use a vertex-based tissue model with active force fluctuations to study how motility controls viscoelastic response. After validation against experimental presomitic mesoderm relaxation dynamics, we extract intrinsic mechanical timescales using stress relaxation and oscillatory shear. The model captures motility-dependent shifts between elastic and viscous behavior and the coexistence of fast relaxation with long-lived residual stress. When subjected to spatially patterned, temporally pulsed forcing, tissues behave as mechanical filters: long-wavelength inputs are accumulated, whereas short-wavelength,
cell-scale perturbations are rapidly erased, largely independent of motility. Simulations with localized motility hotspots, motivated by spatially confined FGF signaling reported in vertebrate limb development, produce sustained protrusive tissue deformations consistent with experimentally observed early bud-like morphologies. Together, these results establish a minimal framework linking motility-driven activity to wavelength-selective mechanical
memory and emergent tissue patterning.
Read the full abstract ▾
Physics and Society
Structural Vulnerability Assessment in Urban Transport Networks: A Network-Wide Geometric Approach Using Gromov-Wasserstein
Iman Seyedi, Antonio Candelieri, Enza Messina et al. (+1 more)
Urban transportation networks are inherently vulnerable to disruptions that affect connectivity and passenger mobility. Traditional graph_theoretic metrics, such as betweenness and degree centrality, offer insights into local network structure but often fail to capture global structural distortions resulting from link failures. On the other hand, global indices, such as those based on spectral analysis of the networks graph, fail in identifying critical elements. This study proposes to quantify the structural modifications implied by the disruption of single elements in a transportation network through the Gromov-Wasserstein distance. Specifically, we iteratively remove one single edge from the original network to simulate a disruptive event and then compute the Gromov-Wasserstein distance between the original network and the disrupted one. Finally, edges are ranked depending on the observed Gromov-Wasserstein distance: the higher the value of the distance, the more critical the edge is in terms. Two transportation networks from Berlin are considered in the experiments, namely Berlin Friedrichshain Center (BFC) and Berlin Tiergarten (BT). Results reveal that Gromov-Wasserstein is largely uncorrelated with edge betweenness (rho<0.1), proving its ability to capture vulnerability aspects overlooked by local network measures. Moreover, Gromov-Wasserstein exhibits an almost perfect correlation (rho=0.9999) against a proxy measure of the transportation service level, that is, the increase in the maximum shortest path. As a result, the Gromov-Wasserstein distance can be used to rank edges depending on their criticality with respect to their individual impact on the overall infrastructure and level, allowing for prioritizing maintenance, emergency planning, and enhancing the resilience of the urban transport network.
Read the full abstract ▾
All authors Iman Seyedi, Antonio Candelieri, Enza Messina, Francesco Archetti
Geophysics
Numerical Modeling of Effective Thermal Conductivity for Polymineralic Rocks using Lattice Element Method
Nima Haghighat, Amir S. Sattari, Hem B. Motra et al. (+1 more)
Accurate prediction of rock thermal conductivity under in-situ conditions is essential for characterizing subsurface heat flow. This study presents a numerical framework based on the
Lattice Element Method (LEM) for simulating the effective thermal conductivity of polymineralic rocks under coupled pressure-temperature conditions. The model resolves interactions among heat transfer, grain contacts, and mechanical deformation within a microstructure-representative
lattice. The methodology enables consistent treatment of heat conduction, nonlinear contact
evolution, and thermally induced intergranular fracturing. Heterogeneity is introduced through a
stochastic, volume-fraction-constrained discretization that preserves the measured mineral composition and porosity, while mineral anisotropy and fracture behavior are captured through element-level constitutive laws. The framework is evaluated using experimental data for two dry sandstones under ambient and elevated pressures and temperatures. Effective thermal conductivity is computed over the same pressure-temperature ranges and compared directly with the measurements. The results indicate that the predictions are capable of reproducing the characteristic trends and absolute levels. The close agreement between experimental observations and model predictions confirms that the thermo-mechanical coupled LEM provides a physically grounded and transferable approach for modeling heat transport in heterogeneous, polymineralic media.
Read the full abstract ▾
All authors Nima Haghighat, Amir S. Sattari, Hem B. Motra, Frank Wuttke
History and Philosophy of Physics
Cosmology and Philosophy
Daniel Parrochia
Scientific cosmology has now reached its period of maturity with the establishment of a standard model, which is the theory of an expanding universe. The question of whether this expansion resolves itself, in the past, into a singularity identifiable with an absolute beginning, or whether the universe in which we are is only one of the multiple possible universes existing either in space or in time, is still under debate. Moreover, the assimilation of the beginning of the universe to a "creation" has often been contested by theology, which, since Thomas Aquinas, if not since the Fathers of the Church, tends to carefully distinguish the two. In the following article, after briefly summarizing some points in the recent history of scientific cosmology, we will attempt to present in broad outline the standard model that scientists have arrived at. Then, we will undertake to study some of the problems it raises as well as the alternative theories that can be opposed to it. Finally, we will discuss the problematic links that scientific cosmology continues to maintain with philosophy and theology, notably the thorny question of creation from nothing (creatio ex nihilo).
Read the full abstract ▾
Optics · Cross-listed from quant-ph
Christof Wetterich
Wave guides for classical electromagnetic fields can realize the discrete
quantum evolution of the wave function for a system of
qubits. Phase shifts, switches and beam splits allow for the construction of arbitrary
quantum gates. They can act at once on a large number of
qubits. For this correlation based photonic
quantum computer the channels of the wave guides represent basis states of a multi-
qubit system rather than individual
qubits. With probabilistic initial conditions for a large number of channels the classical fields in wave guides realize the density
matrix for a probabilistic
quantum computer obeying the von Neumann equation.
Read the full abstract ▾
Optics
Dual-Bus Resonator for Multi-Port Spectral Engineering
Taewon Kim, Mehedi Hasan, Yu Sung Choi et al. (+2 more)
Microresonators are essential in integrated photonics, enabling optical filters, modulators, sensors, and frequency converters. Their spectral response is governed by bus-to-resonator coupling, typically classified as under-, critical-, or over-coupling. Conventional single-bus designs inevitably link the conditions for critical coupling, a transmission zero, and maximum intra-cavity power, preventing independent control of these phenomena and restricting the ability to engineer coupling regimes and resonance lineshapes. Here we propose and experimentally demonstrate a dual-bus racetrack resonator that breaks this constraint. Our design demonstrates complementary channel-specific coupling regimes and enables wavelength-dependent Lorentzian-to-Fano lineshaping. We model the device using three-waveguide coupled-mode theory and pole-zero analysis, which reveals that transmission zeros are decoupled from cavity-defined critical coupling and maximum intra-cavity power. Furthermore, the dual-bus scheme operates broadband, spanning visible to mid-infrared across all four transmission channels, highlighting its spectral richness and platform independence. These results establish a general framework for multi-port spectral engineering in integrated photonics, with broad implications for tunable filters, modulators, sensors, and nonlinear optical systems.
Read the full abstract ▾
All authors Taewon Kim, Mehedi Hasan, Yu Sung Choi, Jae Woong Yoon, Sangsik Kim
Atmospheric and Oceanic Physics
Forecasting precipitation in the Arctic using probabilistic machine learning informed by causal climate drivers
Madhurima Panja, Dhiman Das, Tanujit Chakraborty et al. (+6 more)
Understanding and
forecasting precipitation events in the Arctic maritime environments, such as Bear Island and Ny-Ålesund, is crucial for assessing
climate risk and developing early warning systems in vulnerable marine regions. This study proposes a probabilistic machine learning framework for modeling and predicting the dynamics and severity of precipitation. We begin by analyzing the scale-dependent relationships between precipitation and key atmospheric drivers (e.g., temperature, relative humidity, cloud cover, and air pressure) using wavelet coherence, which captures localized dependencies across time and frequency domains. To assess joint causal influences, we employ Synergistic-Unique-Redundant Decomposition, which quantifies the impact of interaction effects among each variable on future precipitation dynamics. These insights inform the development of data-driven
forecasting models that incorporate both historical precipitation and causal
climate drivers. To account for uncertainty, we employ the conformal prediction method, which enables the generation of calibrated non-parametric prediction intervals. Our results underscore the importance of utilizing a comprehensive framework that combines causal analysis with probabilistic
forecasting to enhance the reliability and interpretability of precipitation predictions in Arctic marine environments.
Read the full abstract ▾
All authors Madhurima Panja, Dhiman Das, Tanujit Chakraborty, Arnob Ray, R. Athulya, Chittaranjan Hens, Syamal K. Dana, Nuncio Murukesh, Dibakar Ghosh
Instrumentation and Detectors
Development and Flight Trial of a UAV-based Gamma Ray and Neutron Detection System for Large-Area Radioactivity Mapping and Source Activity Estimation
Lysander Miller, Airlie Chapman, James Kennedy et al. (+2 more)
Advances in scintillation
crystal and Silicon PhotoMultiplier (SiPM) technologies have enabled the development of compact, lightweight, and low-power radiation detectors that are suitable for integration with Unmanned Aerial Vehicles (
UAVs). This integration enables efficient and cost-effective large-area radiation monitoring while minimising occupational exposure. In this work, a SiPM-based NaIL scintillation detection payload was developed, characterised, and mounted on a multirotor
UAV for gamma ray and
neutron source localisation and activity estimation applications. To support these capabilities, an analytic radionuclide detection efficiency model was developed and used to estimate radioactivity on the ground from aerial energy spectrum measurements. The analytic expression for the detection efficiency incorporated physical phenomena, including the branching ratio, detector solid angle, air attenuation, and intrinsic peak efficiency, leading to agreement within 10% of experimental radionuclide detection efficiencies. The
UAV-based radiation detection system was physically validated through a controlled indoor live radioactive source demonstration at 1.5 m, 3 m, and 4.5 m flight heights. Using the developed ground-level radioactivity estimation method, Cs-137 and Co-60 sources were successfully localised within 0.5 m, and their activities were estimated with errors on the order of 10% or less.
Read the full abstract ▾
All authors Lysander Miller, Airlie Chapman, James Kennedy, Richard Hebden, Jeremy M. C. Brown
Classical Physics
Tracking the normal modes of an overpass highway bridge using Distributed Acoustic Sensing
E. Diego Mercerat, Martijn P.A. van den Ende, Anthony Sladen et al. (+6 more)
Distributed Acoustic Sensing (DAS) of ambient vibrations is a promising technique in the context of structural health monitoring of civil engineering structures. The methodology uses Rayleigh backscattered light from small deformations at different locations of the sensed fiber-optic cable, turning it into a large array of equally distributed strain sensors. In this paper, we demonstrate the feasibility of using DAS technology to record dynamic strain used for modal identification through the Operational Modal Analysis (OMA) of a strut-frame bridge overpassing the A8 highway in southeastern France. Modal identification using DAS data is successful despite its predominantly axial sensitivity (along fiber), though the help of three-component seismometers is useful for discriminating the main motion direction of each identified mode. The identification of 1 bridge's normal modes with unprecedented spatial resolution is obtained from the lowest (transverse and longitudinal) modes to high-order modes that present significant vertical motion. In addition, strong seasonal effects are observed in both the absolute frequency values and the modal shapes of the first transverse and longitudinal modes of the bridge, comparing ambient vibration testing and DAS surveys carried out in the summer and winter periods.
Read the full abstract ▾
All authors E. Diego Mercerat, Martijn P.A. van den Ende, Anthony Sladen, Vanessa Carrillo-Barra, Julián Pelaez-Quiñones, Daniel Mata Flores, Philippe Langlaude, Destin Nziengui Bâ, Olivier Coutant
Optics
ME-FIRST: A Metasurface-Enhanced Fingerprint InfraRed Spectroscopic Tool for Fluid Analytes
Xiangyu Zhao, Yuqing Liu, Jingzhu Shao et al. (+2 more)
Infrared (IR) spectroscopy has emerged as a pivotal tool in biomedical diagnostics, offering label-free spectral biomarkers for the detection of numerous diseases, particularly in the fingerprint region. However, the lack of rapid and sensitive IR spectroscopic techniques for analyzing complex fluid analytes remains a critical challenge in clinical practice. To address this limitation, we present a Metasurface-Enhanced Fingerprint InfraRed Spectroscopic Tool (ME-FIRST) that enhances light-matter interactions in sub-wavelength volumes through plasmonic resonances across the entire fingerprint range from $1900 cm^{-1}$ to $1000 cm^{-1}$. Numerical simulations reveal confined and enhanced electric near-field, with an average probing depth of ~100 nm and enhancement factor $|E/E_0|$ of ~60-fold at resonant peaks. The ME-FIRST device is further experimentally fabricated and validated, and as a proof of concept, we demonstrate the sensing of molecular vibrational modes with a considerable sensitivity in L-lysine over the full fingerprint IR spectral range. The proposed ME-FIRST presents a promising platform for high-sensitivity IR spectroscopy of fluid analytes, paving the way for clinical applications of infrared spectroscopy in biofluid analysis and pathological scenarios.
Read the full abstract ▾
All authors Xiangyu Zhao, Yuqing Liu, Jingzhu Shao, Longsheng Fang, Chongzhao Wu
Fluid Dynamics
High-energy droplet collisions in multi-interacting hollow cone sprays
Narendra Dev, Varun Kulkarni and Sivakumar Deivandren
Droplets collide in several complex spray environments ranging from sea sprays to combustion chambers, altering their size and velocity characteristics. The present work offers a systematic investigation of such collisions within the interacting region formed by three hollow-cone sprays, termed the combined spray, at two elevated
liquid sheet Weber numbers (Wel). The integrated analysis employs Phase Doppler Interferometry (PDI) and microscopic high-speed backlight imaging to characterize the collision dynamics. PDI indicates a notable reduction (11-15%) in Sauter mean diameter (SMD) at the onset of the interaction region. Images reveal frequent and high-energy droplet collisions, capturing structures associated with binary collision outcomes, namely reflexive and stretching separations, splashing, fingering, and stretching with digitations, along with complex multi-droplet collisions. These collisions produce numerous smaller satellite droplets at the expense of larger parent droplets, leading to a decrease in local SMD. Increasing Wel elevates the frequency of these outcomes, particularly highlighting stretching separation as the dominant mechanism. Furthermore, joint probability density functions from PDI and image-based analysis confirm that most satellite droplets predominantly exhibit axial motion, in contrast to the initial trajectories of parent droplets. The satellite droplets continue to move downstream, colliding with others and resulting in a cascade effect that produces finer droplets. Rescaled droplet size distributions, normalized by mean droplet diameter, are broader in the combined spray due to enhanced size reduction from collisions. These distributions are well captured by the compound gamma distribution, reflecting ligament-mediated breakup dynamics.
Read the full abstract ▾
Chemical Physics
From Nucleobases to DNA: Clustering-Triggered Emission and Pressure-Induced Emission Enhancement
Yijing Cui, Yu Song Cai, Xuchen Wang et al. (+8 more)
The photophysical properties of deoxyribonucleic acid (DNA) are fundamental to life sciences and biophotonics. While previous studies have generally been restricted to fluorescence, attributing it to pi-pi* transitions and charge transfer within nucleobases in dilute solution, these understandings fail to explain the pronounced visible emission in physiological and aggregated states, and moreover, ignore the possible phosphorescence. Addressing this critical gap, we systematically investigate native DNA across its structural hierarchy, from nucleobases to single-stranded chains, under varying states. We demonstrate that DNA exhibits excitation-dependent emission in aggregates and moreover room-temperature phosphorescence (RTP) in the solid state. These behaviors are rationalized by the clustering-triggered emission (CTE) mechanism, where nucleobases and electron-rich nonaromatic moieties like sugar and phosphate synergistically contribute to DNA photophysics. High-pressure experiments reveal a 207-fold luminescence enhancement for nucleotides at 26 GPa, largely retained after decompression, underscoring the precise control of emission by intermolecular interactions. This study not only elucidates the intrinsic luminescence mechanism of DNA and but also establishes pressure modulation as a versatile approach for developing new nucleic acid-inspired luminescent materials.
Read the full abstract ▾
All authors Yijing Cui, Yu Song Cai, Xuchen Wang, Xiang Chen, Junhao Duan, Guangxin Yang, Zhipeng Zhao, Yuhao Zhai, Guanjun Xiao, Bo Zou, Wang Zhang Yuan
Instrumentation and Detectors
Design and characterization of a photosensor system for the RELICS experiment
Jijun Yang, Ruize Li, Chang Cai et al. (+45 more)
In this paper, we present the design and characterization of a photosensor system developed for the RELICS experiment. An extended dynamic range base was designed to mitigate photomultiplier tube (PMT) saturation caused by intense
cosmic muon backgrounds in the surface-level RELICS detector. The system employs dual readout from the anode and the seventh dynode to extend the linear response range of the PMT. In particular, our characterization and measurements of Hamamatsu R8520-406 PMTs confirm stable operation under positive high-voltage bias, extending the linear response range by more than an order of magnitude. Furthermore, a model of PMT saturation and recovery was developed to evaluate the influence of
cosmic muon signals in the RELICS detector. The results demonstrate the system capability to detect coherent elastic
neutrino-
nucleus scattering signals under surface-level
cosmic backgrounds, and suggest the potential to extend the scientific reach of RELICS to MeV-scale interactions.
Read the full abstract ▾
All authors Jijun Yang, Ruize Li, Chang Cai, Guocai Chen, Jiangyu Chen, Huayu Dai, Rundong Fang, Fei Gao, Jingfan Gu, Xiaoran Guo, Jiheng Guo, Gaojun Jin, Fali Ju, Yanzhou Hao, Yang Lei, Kaihang Li, Meng Li, Minhua Li, Shengchao Li, Siyin Li, Tao Li, Qing Lin, Jiajun Liu, Sheng Lv, Guang Luo, Kangwei Ni, Chuanping Shen, Mingzhuo Song, Lijun Tong, Jun Wang, Xiaoyu Wang, Wei Wang, Xiaoping Wang, Zihu Wang, Yuehuan Wei, Liming Weng, Xiang Xiao, Lingfeng Xie, Litao Yang, Long Yang, Jingqiang Ye, Jiachen Yu, Qian Yue, Yuyong Yue, Bingwei Zhang, Yuming Zhang, Yifei Zhao, Chenhui Zhu
Fluid Dynamics
Overshoot-resolved transition modeling based on field inversion and symbolic regression
Lei Wu and Zuoli Xiao
Overshoot of high-speed transitional skin-friction and heat-transfer values over their fully turbulent levels is well documented by numerous direct numerical simulations (DNS) and experimental studies. However, this high-speed-specific overshoot phenomenon remains a longstanding challenge in Reynolds-averaged Navier-Stokes (RANS) transition models. In this paper, field inversion and symbolic regression (FISR) methodologies are adopted to explore a generalizable and interpretable augmentation for resolving the missing overshoot characteristic. Specifically, field inversion is implemented on our previous high-speed-improved $k$-$\omega$-$\gamma$-$\widetilde{Re}_{\theta \rm{t}}$ transition-
turbulence model. Then symbolic regression is employed to derive an analytical map from RANS mean flow variables to the pre-defined and inferred corrective field $\beta(\mathbf{x})$. Results manifest that the excavated expression faithfully reproduces the overshoot phenomena of transition region over various test cases while does not corrupt model behavior in transition location and length. Based on its transparent functional form, mechanistic investigations are conducted to illustrate the underlying logic for accurate capture of overshoot phenomenon. In addition, importance of protect function in $\beta(\mathbf{x})$, feasibility of a more concise expression for $\beta(\mathbf{x})$, and reliable performance of $\beta(\mathbf{x})$ in low-speed transitional flows are emphasized.
Read the full abstract ▾
Chemical Physics
TRIDS: AI-native molecular docking framework for accelerating high-throughput virtual screening with physically valid binding poses
Xuhan Liu, Baohua Zhang, Yue Xue et al. (+7 more)
Molecular docking is a cornerstone of drug discovery for unveiling the mechanism of ligand-receptor interactions. With the recent advances of deep learning (DL), AI-powered molecular docking methods have achieved higher accuracy for binding pose prediction and virtual screening compared with classical physics-based methods. However, there is still a scarcity of approaches to strike a balance among accuracy, computational efficiency, and rigorous physical validity of the output conformations. In the previous two versions of DSDP, we demonstrated the effectiveness of guiding conformation sampling with the gradient of an analytic scoring function. As the third version, TRIDS was devised as an AI-native docking framework that expand the similar strategy to unify conformation sampling and docking processes with DL-based model for improving accuracy of docking and screening. Furthermore, it is tailored for seamless cooperation of AI and physics to guarantee the physical validity of predicted binding poses. Being user-friendly, TRIDS predicts the binding site, parses multiple file formats, and supports Python programming and PyMOL graphical interaction. It improves docking accuracy and passes physical validation with high computational efficiency, i.e. a single docking task is done in a fraction of second while maintaining a highly lightweight GPU
memory footprint of merely hundreds of megabytes, facilitating high-throughput virtual screening in reality. As a proof of concept, TRIDS allowed us to obtain hit compounds with novel scaffolds for tumor necrosis factor-alpha (TNF{\alpha}) inhibitor through a large-scale virtual screening.
Read the full abstract ▾
All authors Xuhan Liu, Baohua Zhang, Yue Xue, Yize Hao, Tiejun Bing, Lili Chai, Tanfeng Zhao, Lijiang Yang, Hong Zhang, Yi Qin Gao
Fluid Dynamics · Cross-listed from cond-mat.soft
Vector Nematodynamics with Symmetry-driven Energy Exchange
L. M. Pismen
We review inadequacy of existing nematodynamic theories and suggest a novel way of establishing relations between nematic orientation and flow based on the local
symmetry between simultaneous rotation of nematic
alignment and flow, which establishes energy exchange between the the two without reducing the problem to near-
equilibrium conditions and invoking Onsager's relations. This approach, applied in the framework of the vector-based theory with a variable modulus, involves antisymmetric interactions between nematic
alignment and flow and avoids spurious instabilities in the absence of an active inputs.
Read the full abstract ▾
Chemical Physics
Effects of Hydrogen Transport on the Kinetic Regimes of 4-Nitrophenol Reduction by Sodium Borohydride
Tatiana Nizkaia, Philipp Groppe, Valentin Müller et al. (+3 more)
The reduction of 4-nitrophenol (4-NiP) with sodium borohydride is widely used to
benchmark heterogeneous catalysts, yet its kinetics are commonly oversimplified as pseudo-first-order. In reality, borohydride hydrolysis and hydrogenation by dissolved hydrogen proceed concurrently, making hydrogen transport a decisive factor in shaping apparent activity. Re-examining data on Pt-SiO2 supraparticles with different pore structures, we attribute contrasting kinetic behavior to distinct regimes of hydrogen transport: diffusive transport sustains pseudo-first-order kinetics, while bubble-mediated escape causes hydrogen loss and incomplete conversion. We propose a kinetic model that captures this transition and enables consistent interpretation of experimental data. More broadly, our analysis shows that apparent differences in activity during 4-NiP benchmarking can arise from hydrogen transport rather than intrinsic properties of the catalyst, underscoring the need to account for transport effects when comparing catalyst performance.
Read the full abstract ▾
All authors Tatiana Nizkaia, Philipp Groppe, Valentin Müller, Jens Harting, Susanne Wintzheimer, Paolo Malgaretti