Fluid Dynamics
Hydrodynamic loads and vortex evolution from a bio-inspired pectoral fin near a solid body
Xiaowei He and Kenneth Breuer
A fin-body configuration is tested in a water tunnel to study the hydrodynamic loads and
vortex evolution under dynamic fin-flapping motions, which is an idealized approximation of the pectoral fins of fish. The fin flaps about its leading edge, which is attached to the side of the body, at a range of combinations of amplitudes ($0^\circ-30^\circ$) and frequencies ($0.25\,\mathrm{Hz}-2\,\mathrm{Hz}$ or $k=0.16-1.26$), so the Strouhal number ($St=0.013-0.419$). The quasi-steady hydrodynamic loads exhibit significant hysteresis during the upstroke and downstroke phases of the fin flapping. Particle image velocimetry (PIV) measurements show the details of the shear layer and
vortex development in dynamic flapping cases. Orbiting behaviors of the fin tip
vortices are observed in larger Strouhal number cases. PIV results also reveal the influence of
vortices on hydrodynamic loads in terms of lift fluctuations and thrust generation. The strong dependency on the reduced frequency and Strouhal number leads to scalings of the hydrodynamic loads using a data-driven method to select highly correlated terms. The most significant terms selected by the scaling process are quadratic terms of the Strouhal number and its nonlinear combinations with the reduced frequency.
Read the full abstract ▾
Computational Physics
Two-Way Feedback Mechanisms between the Madden-Julian Oscillation and Mesoscale Convective Systems
Haobo Yang and Qiu Yang
The Madden-Julian Oscillation (MJO) is a planetary-scale convective system characterized by large-scale envelopes of enhanced and suppressed convection that contain numerous mesoscale convective systems (MCSs). While MCSs are widely recognized as the fundamental convective elements embedded within the MJO, their relationship with the MJO is intrinsically two-way: the MJO modulates the large-scale dynamical and thermodynamic environment that organizes MCS activity, while the collective upscale impacts of MCSs feed back onto the MJO through the transport of momentum and heat. However, the nature of this bidirectional interaction remains insufficiently quantified from an observational perspective. In this study, we use satellite-based MJO indices together with a long-term, objectively tracked MCS
dataset to investigate the two-way feedback mechanisms between the MJO and MCSs. By compositing MCS activity across different MJO phases and analyzing their environmental conditions, we quantify how the evolving MJO circulation regulates MCS frequency, intensity, and organization. At the same time, we diagnose the aggregate influence of MCS populations on the large-scale MJO circulation through their associated momentum and thermodynamic anomalies. Our results reveal a robust two-way coupling between the MJO and MCSs. Enhanced MCS activity preferentially occurs in specific MJO phases associated with favorable moisture, instability, and vertical shear, indicating strong MJO control on MCS organization. Conversely, periods of enhanced MCS activity are associated with coherent large-scale circulation anomalies consistent with upscale transport of momentum and moisture that reinforce the MJO convective envelope and support its eastward propagation. This feedback suggests that MCSs are not merely passive responses to the MJO environment, but actively contribute to its maintenance and
evolution.
Read the full abstract ▾
Fluid Dynamics · Cross-listed from cond-mat.soft
Orientation Dynamics of Gyrotactic Microswimmers in Turbulent Flows
Suraj Kumar Nayak, Vishwanath Shukla and Akshay Bhatnagar
We study the dynamics of gyrotactic microswimmers suspended in homogeneous and isotropic
turbulence by using direct numerical simulations (DNS). The swimmers are characterized by three non-dimensional parameters: their aspect ratio ($\gamma$), a dimensionless swimming speed ($\phi$), and a dimensionless reorientation time ($\psi$). Strong gyrotaxis (smaller $\psi$) promotes vertical
alignment of the swimmers, while weak gyrotaxis leads to nearly isotropic orientations. At low swimming numbers, the orientation distribution is largely shape-independent with spheres and spheroids showing marginally greater vertical
alignment than rods, whereas at higher activity the peaks of the distributions exhibit largely shape-independent behavior and the tails show a clear dependence on particle shape. However, at large $\psi$ rods exhibit a stronger
alignment along the vertical. We observe that at small $\psi$ the rod-shaped swimmers respond to shear by aligning with the stretching direction of the strain-rate tensor, while at large $\psi$ the
alignment with the vorticity vector is preferred. The orientation autocorrelation is found to decay exponentially, with a decay rate that scales as $1/(2\psi)$. Analysis of the mean-squared displacement (MSD) reveals a transition from a ballistic motion at short times to a diffusive regime at longer times. To assess the efficiency of vertical migration, we compute the probability distributions of vertical displacement over a fixed time interval and the time taken to migrate a specific vertical distance. Furthermore, we use a simplified two-dimensional model for spherical swimmers that qualitatively reproduces the key trends observed in the full three-dimensional (3D) simulations.
Read the full abstract ▾
Computational Physics
Modulation Effects of Atmospheric Environmental Conditions on Mesoscale Convective Systems over Tropical Oceans
Huaiping Wang and Qiu Yang
Mesoscale convective systems MCSs play a central role in tropical rainfall and are closely linked to extreme precipitation and large scale variability. However, a quantitative understanding of their environmental controls remains incomplete. In this study, we construct an observational MCS
dataset by applying an objective tracking
algorithm to satellite and reanalysis data, and examine the climatology of tropical MCSs. We further use a Random Forest model to quantify environmental controls at the monthly scale. The results show pronounced spatial and seasonal variability in tropical MCS activity, closely tied to large scale circulation and moisture availability. Environmental predictors explain up to about 50% of the variance in monthly MCS frequency and associated precipitation. Moisture convergence atmospheric instability and column integrated water vapor emerge as the leading controlling factors. Partial dependence analyses reveal clear nonlinear interactions among key predictors. The relative importance of environmental controls also varies with region and season, with thermodynamic factors dominating in some regimes and dynamic factors such as vertical wind shear playing a larger role in others. Overall, this study provides an observationally constrained quantification of environmental controls on tropical MCSs and offers new insight into their variability and potential response to
climate variability and change.
Read the full abstract ▾
Optics · Cross-listed from cond-mat.str-el
Giant spontaneous Kerr effect and its self-doping dependence in altermagnetic MnTe
Weitung Yang, Choongjae Won, Cory Cress et al. (+9 more)
Altermagnetism, a third class of collinear magnetism with
spin-split bands and vanishing net magnetization, has emerged in hexagonal {\alpha}-MnTe, a promising platform for ultrafast, stray-field-free spintronics. Whether MnTe's macroscopic
symmetry-breaking signatures reflect ideal altermagnetic order or are activated by defects remains open. Here we report
giant spontaneous Kerr rotations of up to 1500 rad in {\alpha}-MnTe single
crystals at the telecommunication wavelength of 1550 nm, onsetting precisely at the Néel temperature TN = 307 K. The signal appears in disjoint macroscopic patches whose amplitude tracks the sample conductivity, and a hole-conducting {\alpha}-MnTe film reproduces this response together with an anomalous
Hall effect. Within a single
crystal, Kerr-active regions are optically distinct from their Kerr-silent surroundings in co-registered reflection maps. These observations indicate that carrier self-doping, rather than ideal altermagnetic order alone, governs the
giant magneto-optical response, and establish telecom-wavelength Kerr imaging as a practical readout for altermagnetic spintronics.
Read the full abstract ▾
All authors Weitung Yang, Choongjae Won, Cory Cress, Weihang Lu, Xiaochen Fang, Shelby Fields, Nicholas Combs, Shaofeng Han, Marshall Zachary Franklin, Steven P. Bennett, Sang-Wook Cheong, Jing Xia
Chemical Physics
Chaos Gated Tunneling Drives Molecular Reactivity in Astrophysical Environments
Saptarshi G. Dastider, K. Prashant, P. Shruti et al. (+2 more)
Accurate modeling of ion-molecule reaction networks is essential for understanding the chemical
evolution of planetary ionospheres, particularly for
giant planets where
proton-transfer chains drive atmospheric composition. However, predicting reaction rates in these ultracold environments remains a challenge due to the non-trivial interplay between vibrational dynamics and
quantum tunneling. In this work we present a chaos-diagnostic framework that integrates multireference electronic structure theory, Adiabatic Gauge Potentials (AGP), and Random
Matrix Theory (RMT) to characterize the microscopic dynamics of
proton transport. Using the formation of H+3 and the
proton-bound cluster H+5 as representative model systems relevant to Jovian atmospheres, we demonstrate that the transition state acts as a dynamical bottleneck where
quantum chaos is notably suppressed, effectively enhancing tunneling probabilities. We introduce a fragility index based on the AGP slope to quantify how specific vibrational modes reintroduce chaos and suppress reactivity. This diagnostic approach offers a generalizable, data-driven metric for identifying vibrationally gated pathways in complex astrochemical networks, providing a theoretical basis for refining kinetic models of planetary and interstellar
plasmas
Read the full abstract ▾
All authors Saptarshi G. Dastider, K. Prashant, P. Shruti, C. Sudheesh, Jobin Cyriac
Fluid Dynamics
Surfactant effect on collective bubble bursting and aerosol emission
Megan Mazzatenta, Samuel M. Koblensky and Luc Deike
Bubbles entrained by breaking waves rise to the ocean surface where they cluster and burst, emitting sea spray aerosols into the atmosphere. Bubble bursting thereby links seawater biogeochemistry and aerosol chemistry, influencing the ability of emitted aerosols to serve as cloud condensation
nuclei or ice nucleating particles. The mechanisms of film drop and jet drop production are modulated by organic material present in seawater, which may affect the size, number, and composition of resulting aerosols. We disentangle the effect of surfactant on collective bursting processes using laboratory experiments with detailed bubble and aerosol measurements down to small sizes, multiple bubble size configurations, and measurements of bubble lifetime. Submicron aerosol emission, linked to film drop production, increased with surfactant up to an optimal concentration, while production of supermicron aerosols emitted through jet drop production was shut down. Our work paves the way to integrate organic composition into sea spray emission functions.
Read the full abstract ▾
Geophysics
Localization of fast and slow slip in fault gouge and fracture energy scaling
Dmitry I. Garagash and Alice-Agnes Gabriel
The localization of slow and fast slip in fault gouges may play a crucial role in understanding the mechanics of earthquakes and slow slip events. Here, we investigate the fracture energy accompanying this localization and the subsequent thermal weakening. We develop an analytical framework, complemented by numerical simulations, for a gouge governed by rate-and-state-dependent friction with flash-heating at high strain rate and thermal pressurization of pore fluids. The model captures the transition from initially distributed shearing to a co-seismic principal slip “surface” at slip $\delta_{\mathrm{loc}} \approx \gamma_c h$, and yields a decomposition of the fracture energy, $G = G_\mathrm{loc}(h) + \Delta G(\delta)$. The minimum, localization-related component $G_\mathrm{loc}$ scales with gouge thickness $h$, which in turn scales linearly with fault size. Flash heating is activated only upon localization for fast earthquake slip, producing an abrupt strength drop, and contributing to the magnitude of $G_\mathrm{loc}$. The post-localization term $\Delta G$ increases with co-seismic slip due to efficient thermal pressurization and is insensitive to $h$. Localization is predicted to occur for both rate-weakening and rate-strengthening gouges because transient state
evolution drives apparent weakening after a slip-rate increase. These results unify field, laboratory, and seismological observations of shear band thickness, critical slip, and fracture-energy scaling, and they clarify why small events can be governed by scale-dependent $G_\mathrm{loc}$ whereas large ruptures become increasingly fault-invariant as $\Delta G$ dominates. Our framework provides testable predictions for the relation of gouge thickness to lower bounds of co-seismic fracture energy, and the mechanics of slow-slip transients and fast earthquakes.
Read the full abstract ▾
Optics
Knotted spacetime electromagnetic vortex unlinking and unknotting with vector and scalar reconnections and field twist compensation
Jordan M. Adams
Optical
vortex knots have been realized in monochromatic
laser beams, but monochromatic fields are stationary and their
topology is frozen. Here we show that knotted spatiotemporal
vortices, whose phase singularities form closed loops in spacetime, undergo
topology changing reconnections with free space propagation. When null lines of different vector components unlink, the electric
spin,
magnetic spin, linear momentum, and electromagnetic helicity densities, each built from a specific pair of field components, twist to exactly compensate the change in linking number. This compensation is enforced by the argument principle where the total for each component pair, combining mutual phase twist,
geometric linking, and open-line threading, vanishes identically and remains exactly zero through all reconnection events.
Read the full abstract ▾
Chemical Physics
Engineering molecular potential energy surfaces using magnetic cavity quantum electrodynamics
Lukas Weber, Leonardo dos Anjos Cunha, Johannes Flick et al. (+1 more)
We investigate the effects of coupling a
quantum-
magnetic cavity field to molecules. Our high-precision auxiliary-field
quantum Monte Carlo calculations capture the effect of the cavity field in the presence of electron correlations, and their interplay and competition. In H$_2$, we find that a strong enough cavity coupling makes the original bound ground state metastable, along with inverting the singlet-triplet gap. In ring molecules (e.g., H$_n$), the
magnetic cavity coupling stabilizes symmetric geometries. As a consequence, open-shell rings such as H$_4$, H$_8$, or C$_4$H$_4$, which would undergo Jahn-Teller distortions outside of the cavity, obtain exotic
spin or ring-current polarized, antiaromatic ground states. These effects are enhanced by increasing the molecule concentration inside the cavity. Our results suggest cavity
quantum electrodynamics beyond the long-wavelength approximation as a promising avenue for cavity-altered chemistry.
Read the full abstract ▾
All authors Lukas Weber, Leonardo dos Anjos Cunha, Johannes Flick, Shiwei Zhang
Data Analysis and Statistics · Cross-listed from hep-ph
Kitchen Sink Anomaly Detection
Ranit Das, Marie Hein, Gregor Kasieczka et al. (+6 more)
An enormous amount of R&D effort has resulted in many new resonant anomaly detection methods being proposed in recent years. However, the vast majority of previous R&D studies have suffered from two limitations: they have focused on a very small set of simulated signal
benchmark models; and they have either used small sets of carefully crafted high-level jet substructure observables, which can be highly performant but are prone to model dependence, or the full
collider event phase space, which is more agnostic but suffers from reduced sensitivity. In this work, we address both limitations: we formulate a number of new simulated signal
benchmarks, which we make publicly available in a format fully compatible with the LHCO R&D
benchmark; and we explore a high-level, yet highly agnostic, observable set consisting of Energy Flow
Polynomials in addition to the usual subjettiness variables. We evaluate this "kitchen sink" observable set for both an idealized anomaly detector and the CWoLa hunting task, along with three baseline observable sets (the Baseline LHC Olympics set, subjettiness observables, and Energy Flow
Polynomials). We find that our kitchen sink approach is the most sensitive to a broad range of signal types. Furthermore, we show that an attribute bagging variant, in which each ensemble member is trained on a random subset of substructure observables, yields comparable anomaly detection performance while significantly reducing training cost.
Read the full abstract ▾
All authors Ranit Das, Marie Hein, Gregor Kasieczka, Michael Krämer, Lukas Lang, Radha Mastandrea, Louis Moureaux, Alexander Mück, David Shih
Plasma Physics
Turbulence Mode Decomposition and Anisotropy in Magnetically Dominated Collisionless Plasmas
Samuel T. Sebastian, Siyao Xu, Yue Hu et al. (+3 more)
We use the 3D fully kinetic simulation to study different
turbulence modes and
turbulence anisotropy of relativistic
turbulence in magnetically dominated collisionless
plasmas. We extend the method developed by Cho & Lazarian (2002) for decomposing non-relativistic magnetohydrodynamic (MHD)
turbulence into Alfvén, fast, and slow modes to the regime of collisionless
plasmas. We find that Alfvén and slow modes are anisotropic, following the Goldreich & Sridhar (1995) scaling, while fast modes are isotropic. We observe a larger kinetic energy fraction of fast modes compared to that in the non-relativistic MHD
turbulence, suggesting a stronger coupling of Alfvén and fast modes in relativistic magnetized
turbulence in collisionless
plasmas. We further examine the dynamic
alignment and find a weaker scale dependence of the
alignment angle than previously proposed. The dominant thermal fluctuations in the kinetic range can cause flattening of the turbulent velocity structure function and weakening of the
turbulence anisotropy and dynamic
alignment near the kinetic scales.
Read the full abstract ▾
All authors Samuel T. Sebastian, Siyao Xu, Yue Hu, Luca Comisso, Saikat Das, Joonas Nättilä
Medical Physics
Deep Reinforcement Learning for Optimizing Angle Selection and Dose Allocation in CT Reconstruction
Tianyuan Wang, Daniël M. Pelt, Felix Lucka et al. (+2 more)
Traditional X-ray computed
tomography (CT) scanning strategies typically select projection angles uniformly and allocate dose equally. In practice, however, CT scans often need to be fast, radiation-efficient, and adaptive. Sparse-view
tomography addresses these requirements by reducing both the number of angles and the total dose budget. Under such constraints, angle selection and dose allocation should be information-driven, with more dose assigned to informative directions. To this end, we propose a dose-aware acquisition and reconstruction framework that combines a PWLS-PnP reconstruction backbone with an RL-based strategy for adaptive angle selection, explicitly accounting for angle-dependent
photon statistics. Numerical experiments show that the proposed approach improves overall reconstruction quality and enhances defect detectability compared with conventional strategies, particularly when only a small number of projections or a constrained dose budget is available.
Read the full abstract ▾
All authors Tianyuan Wang, Daniël M. Pelt, Felix Lucka, Tristan van Leeuwen, K. Joost Batenburg
Optics
Laser electro-optic frequency comb in lithium niobate nanophotonics
Benjamin K. Gutierrez, Yingchu Xu, Nicolas Englebert et al. (+8 more)
Optical frequency combs have revolutionized precision science and technology, yet their nanophotonic implementations have failed to simultaneously achieve high efficiency, power, and coherence. Optically driven microcombs provide broad and stable spectra but low usable power, whereas active comb generators, including mode-locked
lasers, can be efficient yet offer less control over coherence. We introduce the
laser electro-optic (LEO) frequency comb, a comb-generation mechanism in which coherent continuous-wave injection drives a phase-modulated
laser cavity above threshold into a distinct operating regime. Unlike other coherently driven integrated comb sources, the LEO comb generates comb powers that exceed the injected continuous-wave power by an order of magnitude. We realize the LEO comb in a hybrid lithium niobate/III-V nanophotonic
circuit and demonstrate milliwatt-level power per comb line, 1.76-ps pulses, a 4.7-nm background-free spectrum, and linewidths as narrow as 19.6 kHz. By unifying high efficiency, power, and coherence, this architecture establishes a definitive route to chip-scale frequency comb sources that deliver on the promise of scalable, high-performance coherent optical technologies.
Read the full abstract ▾
All authors Benjamin K. Gutierrez, Yingchu Xu, Nicolas Englebert, Rithvik Ramesh, Maximilian Shen, Deven Tseng, Adelynn Tang, Ryoto Sekine, Mahmood Bagheri, Auro M. Perego, Alireza Marandi
Physics and Society
Network exploration by random walks: A large deviation perspective
Sarvesh K. Upadhyay, Trifce Sandev, Sanjay Kumar et al. (+1 more)
We study exploration properties of a random walk on a network. For a fully connected network we find that the problem can be mapped to the well known coupon collector problem, thus allowing us to estimate form of $P(S,t)$: the distribution of number of distinct nodes $S$ visited by the random walk upto time $t$. From a practical point of view, however, both the fully connected network and hops taking place after fixed intervals are an idealization. We solve this problem by introducing the formalism of continuous time random walks wherein the random walk spends a random amount of time a node before hopping to its neighboring node. The formalism allows us to study the large deviation limit of $P(S,t)$ under very mild conditions that the distribution of waiting times $\psi(\tau)$ exhibits analyticity at small times. Furthermore, we find that at small times, the properties of $P(S,t)$ are largely independent of the network
topology, and are governed solely by the waiting time characteristics.
Read the full abstract ▾
All authors Sarvesh K. Upadhyay, Trifce Sandev, Sanjay Kumar, R. K. Singh
Geophysics
The Pc1 geomagnetic pulsations in light of the Cepheid theory
A.V. Guglielmi, A.S. Potapov and F.Z. Feygin
It has been 90 years since the discovery of geomagnetic pulsations in the Pc1 range (0.2-5 Hz), widely known as pearls. In the second half of the last century, the concept of pearls as multiple echoes of a wave packet that propagates along the lines of the geomagnetic field, periodically reflecting off the ionosphere at magnetically conjugate points emerged. This paper proposes an alternative interpretation of the pearls. It is assumed that high above the Earth in the narrow equatorial zone of the outer radiation belt there is a pulsed generator of ion-cyclotron waves. The generator excites a discrete sequence of wave packets, which are recorded in the magnetosphere and on the Earth's surface as a series of pearls. The generator is a Q-modulated ion cyclotron resonator with active filling. The presence of opacity domains adjacent to the resonator's end faces is reminiscent of the opacity layer in the atmosphere of a Cepheid. This association was strengthened by the fact that in both cases the formation of opaque layers is associated with the presence in the medium of ions with different charge-to-mass ratios. Based on this association, the idea of a ponderomotive valve arose, periodically changing the width of the opacity domains, thereby forming a periodic sequence of pearls. The ponderomotive valve in pearl theory is analogous to the Eddington valve in Cepheid theory.
Read the full abstract ▾
Applied Physics
How do sub-bandgap reflectors affect the performance of PV modules?
Klaus Jäger, Jyotirmoy Mandal, Barry P. Rand et al. (+2 more)
Sub-bandgap reflectors (SBR) can reduce the temperature of photovoltaic (PV) modules by reflecting the near-infrared region of the
solar spectrum with
photon energies smaller than the electronic bandgap of the
solar cell absorber material. We consider an ideal SBR, which reflects 100 % of non-harvestable low-energy
photons but does not alter the reflectivity of the PV module for usable high-energy
photons, and estimate how reducing the module temperature with the SBR affects the annual and the cumulative energy yield of silicon PV modules for six locations in North America and Europe. An ideal SBR would increase the annual energy yield between 1.0 % and 1.5 % for open-rack mounted modules and between 1.6 % and 2.4 % for close-roof mounted PV modules. Whether a non-ideal SBR provides a benefit in actual deployments strongly depends on the location and the optical properties of the coating. Beyond effects on the instantaneous power conversion efficiency and hence the annual energy yield, reducing the temperature by a SBR might also reduce the degradation and increase the overall lifetime of the PV module. By describing degradation using a simple Arrhenius approach using typical activation energies between 0.4 eV and 0.8 eV, we find that an ideal SBR increases the cumulative energy yield over 30 years between 2.2 % and 4.0 % for an open-rack mounted PV module in Princeton, New Jersey, USA.
Read the full abstract ▾
All authors Klaus Jäger, Jyotirmoy Mandal, Barry P. Rand, Forrest Meggers, Christiane Becker
Fluid Dynamics
RG-Based Local Hopf Reduction and Slow-Manifold Reconstruction for Nonlinear Aeroelastic Systems
Gelin Chen, Chen Song and Chao Yang
Self-excited limit-cycle oscillations (LCOs) from
Hopf bifurcations are a key feature of nonlinear aeroelasticity and depend sensitively on structural and aerodynamic parameters. Classical center-
manifold and normal-form theory describe this local behavior, but can be cumbersome to apply in large discretized models and standard reduced-order modeling (ROM) workflows. A renormalization-group (RG)-based reduction is developed that directly yields a
Hopf-type amplitude equation on a local invariant
manifold, specialized for
polynomial nonlinearities in tensor-based discretizations and compatible with finite-element-type settings. The method provides explicit coefficients governing the
Hopf threshold, criticality, and leading LCO amplitude/frequency trends, and admits a companion slow-
manifold approximation with selected stable modes retained as static coordinates. Representative nonlinear-aeroelastic examples illustrate how the proposed framework supplies compact, parameter-aware
Hopf/LCO descriptors suitable for local ROM construction near flutter.
Read the full abstract ▾
Optics
High-Fidelity Single-Shot Quantitative Differential Phase Microscopy Using Pseudothermal Sagnac Interferometer
Pawel Goclowski, Hong Mao, Maciek Trusiak et al. (+2 more)
In this letter, a high-fidelity single-shot differential quantitative phase microscopy (dQPM) method is presented to effectively image nearly transparent biological samples. The proposed method is based on a common-path Sagnac interferometric configuration, which provides superior temporal phase stability and robustness against environmental disturbances. The proposed system exploits a pseudothermal source to achieve high spatial sensitivity and generate dense interference fringes for effective single-shot differential quantitative phase imaging. The effectiveness of the proposed system is experimentally demonstrated with various samples, including polystyrene microspheres, a USAF phase target, fixed and live HeLa
cells, and mouse kidney tissue.
Read the full abstract ▾
All authors Pawel Goclowski, Hong Mao, Maciek Trusiak, Balpreet S. Ahluwalia, Azeem Ahmad
Computational Physics · Cross-listed from cs.LG
Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health
Peter Collett, Alexander Johannes Stasik, Simone Casolo et al. (+1 more)
Accurate condition monitoring of industrial equipment requires inferring latent degradation parameters from indirect sensor measurements under uncertainty. While traditional
Bayesian methods like Markov Chain Monte Carlo (MCMC) provide rigorous uncertainty quantification, their heavy computational bottlenecks render them impractical for real-time process control. To overcome this limitation, we propose an AI-driven framework utilizing Simulation-Based Inference (SBI) powered by amortized neural posterior estimation to diagnose complex failure modes in heat exchangers. By training neural density
estimators on a simulated
dataset, our approach learns a direct, likelihood-free mapping from thermal-fluid observations to the full posterior distribution of degradation parameters. We
benchmark this framework against an MCMC baseline across various synthetic fouling and leakage scenarios, including challenging low-probability, sparse-event failures. The results show that SBI achieves comparable diagnostic accuracy and reliable uncertainty quantification, while accelerating inference time by a factor of82$\times$ compared to traditional sampling. The amortized nature of the neural network enables near-instantaneous inference, establishing SBI as a highly scalable, real-time alternative for probabilistic fault diagnosis and digital twin realization in complex engineering systems.
Read the full abstract ▾
All authors Peter Collett, Alexander Johannes Stasik, Simone Casolo, Signe Riemer-Sørensen
Instrumentation and Detectors · Cross-listed from eess.SY
Low-Cost Turntable Designed for RF Phased Array Antenna Active Element Pattern Measurement
Rebekah Edwards, Taylor Martini, Jonathan E. Swindell et al. (+5 more)
Accurate
antenna array calibrations and measurements of aspects such as active element pattern (AEP) are critical for enabling integrated sensing and communication (
ISAC) technologies such as directional modulation. One reliable way of obtaining accurate and repeatable AEP measurements is to
spin the
antenna array on a turntable, but many turntables designed for
antenna array measurements are prohibitively expensive for small labs and may not be designed with RF considerations, such as cable phase stability, in mind. This paper details the design of a motorized 3D printed turntable for use in directional modulation and in-situ measurement experiments that will allow for rotation of an
antenna array around a point, such that the far field of the
antenna pattern can be measured by a stationary receiver.
Read the full abstract ▾
All authors Rebekah Edwards, Taylor Martini, Jonathan E. Swindell, David W. Cox, Adam C. Goad, Austin Egbert, Charles Baylis, Robert J. Marks
Plasma Physics
An analytic formula for surface currents generating prescribed plasma equilibrium fields
Wadim Gerner
Given a
plasma domain $P\subset\mathbb{R}^3$, a
plasma equilibrium field $B$ on $P$ and a coil winding surface $\Sigma$ surrounding $P$, we provide an analytic formula whose output is a surface current distribution $j$ on $\Sigma$ such that $\operatorname{BS}(j)+\operatorname{BS}(\operatorname{curl}(B))=B$ in $P$, i.e. the combination of the
plasma current
magnetic field and the surface current
magnetic field exactly produce the full
plasma equilibrium field. We use this new formula to provide a theoretical explanation of the empirical phenomenon that currents tend to attain their maximal strength at points which correspond to points of highest normal
magnetic curvature on the
plasma boundary. Some discussions regarding aspects of numerical approximations are also included.
Read the full abstract ▾
Instrumentation and Detectors
A 260-Liter Test Stand for Liquid Argon R&D
Yichen Li, Aleksey Bolotnikov, Milind Diwan et al. (+6 more)
We describe the design and performance of a 260-liter
liquid argon (LAr) cryogenic test stand for
liquid argon detector research and development at BNL. The system uses gas-phase argon purification with continuous pump-free circulation, in which boil-off argon gas is purified, recondensed, and returned to the cryostat by
gravity without a mechanical recirculation pump; it also incorporates an upgraded condenser that increases the effective thermal contact area by a factor of 13 relative to the previously developed 20-liter system reported perviously. A
liquid argon purity monitor is installed to measure the electron lifetime directly in LAr, enabling quantitative characterization of charge attenuation due to electronegative
impurities. Under the operating conditions reported here, the demonstrated electron lifetime is 0.5 ms. The system is designed to enable rapid iteration of detector components in complete operational cycles, including pump-down, leak verification, cryogenic fill, stable operation, and warm-up, which can be completed within 7 days. Such a fast turnaround time, together with the medium-scale
liquid volume and direct purity diagnostics, makes the facility well suited for testing and refining detector designs in support of large
liquid argon time projection chamber (LArTPC) experiments.
Read the full abstract ▾
All authors Yichen Li, Aleksey Bolotnikov, Milind Diwan, Jay Hyun Jo, Steven Kettell, Steven Linden, Xin Qian, Matteo Vicenzi, Chao Zhang
Applied Physics
Gradient Residual Stress in Transferred Thin-Film Lithium Niobate and Its Compensation Using Periodically Poled Piezoelectric Bilayers
Byeongjin Kim, Ian Anderson, Tzu-Hsuan Hsu et al. (+1 more)
In this work, we experimentally investigate the gradient stress (sigma1) in 128 deg Y-cut transferred thin film lithium niobate (TFLN) films with thicknesses from 100 to 460 nm using cantilever
curvature analysis. The results reveal a strong dependence of sigma1 on both crystallographic orientation and film thickness, with stress-free orientations at approximately 55 deg and 125 deg for 220-460 nm films, shifting to approximately 20 deg and 160 deg for 100 nm films. The extracted normalized sigma1 ranges from -0.1 to 3.4 MPa/nm (100 nm), -0.8 to 0.34 MPa/nm (220 nm), and -0.12 to 0.08 MPa/nm (460 nm), indicating a pronounced thickness-dependent through-thickness stress gradient. Finite element simulations show excellent agreement with the measurements, validating the
curvature-based extraction method and confirming that sigma1 originates from an orientation-dependent residual stress gradient. To mitigate this effect, a
bilayer TFLN structure with opposite crystallographic orientations, forming a periodically poled piezoelectric film (P3F), is investigated, enabling partial cancellation of sigma1. A 90/110 nm P3F
bilayer reduces the equivalent normalized sigma1 to -0.4 to -0.04 MPa/nm, resulting in significantly reduced deformation. These results establish gradient stress engineering through orientation, thickness, and
bilayer design as an effective strategy for achieving mechanically stable and scalable TFLN microelectromechanical systems (MEMS) devices.
Read the full abstract ▾
All authors Byeongjin Kim, Ian Anderson, Tzu-Hsuan Hsu, Ruochen Lu
Data Analysis and Statistics
Bayesian approach for uncertainty quantification of hybrid spectral unmixing in $\gamma$-ray spectrometry
Dinh Triem Phan, Jérôme Bobin, Cheick Thiam et al. (+1 more)
Identifying and quantifying $\gamma$-emitting radionuclides, considering spectral deformation from $\gamma$-interactions in radioactive source surroundings, present a significant challenge in $\gamma$-ray spectrometry. In that context, a hybrid machine learning method has been previously proposed to jointly estimate the counting and spectral signatures of $\gamma$-emitters under conditions of spectral variability. This paper addresses the uncertainty quantification of the
estimators (i.e., the counting and the variable $\lambda$ which characterizes the spectral signatures) obtained by this spectral unmixing
algorithm. The focus is on the coverage interval, as defined by the GUM, which corresponds closely to a credible interval in the
Bayesian framework. Given the inverse problem and the constraints associated with spectral deformation, two
Bayesian methods - Laplace approximation and Markov Chain Monte Carlo - have been developed for uncertainty quantification to ensure robust decision-making. The Laplace approximation technique approximates the posterior distribution by a Gaussian distribution, while the Markov Chain Monte Carlo technique samples the posterior distribution. This study evaluates these two methods in terms of precision of coverage interval based on repeated Monte Carlo samples using the long-run success rate. Numerical experiments show that both methods yield similar results close to the expected success rate of 95.4$\%$ when constraints related to spectral signatures deformation and counting are inactive. However, when constraints are active or the background counting significantly dominates other radionuclides, the Laplace approximation method deviates from the expected long-run success rate due to the non-Gaussian posterior distribution. In such cases, the Markov Chain Monte Carlo method still provides robust results.
Read the full abstract ▾
All authors Dinh Triem Phan, Jérôme Bobin, Cheick Thiam, Christophe Bobin
Classical Physics
Unidirectional Transverse Scattering in Acoustic Dimers
Mikhail Smagin, Iuliia Timankova, Pavel Pankin et al. (+2 more)
We study unidirectional transverse scattering in a two-dimensional acoustic dimer composed of two circular subwavelength scatterers. Using a coupled multipole model, we show that interparticle coupling enables effective monopole–dipole interference and supports a transverse Kerker effect under plane-wave excitation. In contrast to a single non-absorbing rotationally symmetric particle, where Kerker-type directional scattering is only approached in the weak-scattering limit, the dimer can combine pronounced directionality with strong overall scattering. This regime is promising for compact acoustic beam steering and directional wave routing.
Read the full abstract ▾
All authors Mikhail Smagin, Iuliia Timankova, Pavel Pankin, Yong Li, Mihail Petrov
Optics
Toward nanophotonic platforms for solid-state $^{229}$Th nuclear clocks
Sandro Kraemer, Karen Mamian, Toby Bi et al. (+18 more)
While the $^{229}$Th
nuclear isomer has recently been observed and
laser-excited, converting optical
nuclear manipulation into a chip-scale solid-state frequency standard remains an open challenge. Here, we present a nanophotonic platform to realize an all-solid-state
nuclear clock based on the low-energy isomeric transition of $^{229}$Th embedded in high-$Q$ fluoride photonic resonators. By coupling ensembles of thorium
nuclei to confined optical modes, we show that resonant field build-up in the cavity can substantially enhance the
nuclear excitation rate, enabling optical interrogation at practical
laser intensities. We model the
nuclei-
photon interaction dynamics and outline a technological roadmap toward addressing this challenge, including resonator fabrication in fluoride
crystals, thorium implantation,
nuclear excitation with integrated
lasers, and on-chip detection of
vacuum-ultraviolet
photons. As an initial proof of concept, we implant a crystalline fluoride whispering-gallery-mode resonator with $^{229}$Th and assess the impact of implantation-induced damage on resonator performance. Our platform leverages recent advances in materials integration and nanophotonics to chart a realistic route toward compact and scalable
nuclear frequency standards.
Read the full abstract ▾
All authors Sandro Kraemer, Karen Mamian, Toby Bi, Shun Fujii, Jan de Haan, Harshith Babu, Arno Claessens, Rafael Ferrer Garcia, Fedor Ivandikov, Piet Van Duppen, Andreas Dragoun, Christoph E. Düllmann, Christoph Marquardt, Ulrich Wahl, Bart Kuyken, Thorsten Schumm, Pascal Del'Haye, Lino M. C. Pereira, Georgy A. Kazakov, Kasper Van Gasse, Charles Roques-Carmes
Fluid Dynamics · Cross-listed from cond-mat.soft
Flow-history-dependent orientational relaxation in dilute polydisperse colloidal rod suspensions
Yuto Yokoyama, Vincenzo Calabrese, Fabian Hillebrand et al. (+3 more)
Orientation and relaxation dynamics of rod-like colloids under flow govern the optical and mechanical properties of many emerging soft materials. In polydisperse suspensions, particles of different lengths exhibit distinct rotational
diffusion timescales, yet how this polydispersity influences relaxation following flow cessation remains unclear. In particular, it is not well understood how the pre-shear rate determines the subsequent orientation relaxation dynamics. To address this question, we performed simple shear on dilute cellulose nanocrystal (CNC) suspensions in a narrow-gap Taylor-Couette
cell and measured birefringence relaxation after flow cessation using high-speed polarization imaging. To interpret the experiments, we formulated a polydisperse Fokker-Planck model parameterized by the measured length distribution. As a result, the average orientation relaxation time systematically decreases with increasing pre-shear rate. Moreover, when organized by the Péclet number based on the rotational
diffusion coefficient of the weighted average rod length, the data agree well with the theory over a wide range of shear rates. This trend arises because the rod sub-population contributing most strongly to the orientation shifts from longer rods to shorter rods as the pre-shear rate increases, showing that the flow history governs the orientation relaxation dynamics. In polydisperse systems, the orientation relaxation time is no longer a material-specific constant but is determined by both the flow conditions and the polydispersity. This study provides a quantitative framework for understanding orientation dynamics in polydisperse rod suspensions and for interpreting rheo-optical measurements.
Read the full abstract ▾
All authors Yuto Yokoyama, Vincenzo Calabrese, Fabian Hillebrand, Henry J. London, Simon J. Haward, Amy Q. Shen
Plasma Physics
Attosecond Nonlinear Quantum Electrodynamics in Laser-Driven Plasmas via Two-Photon Synchrotron Emission
Vedin Dewan, Aleksei M. Zheltikov and Julia M. Mikhailova
Ultrafast strong-field
laser–
plasma physics is shown to offer a promising framework for relativistic nonlinear
quantum electrodynamics (QED). As one of its key advantages, this approach to relativistic nonlinear QED does not require an external beam of relativistic particles. Instead, high-energy electrons are produced in this setting as a part of ultrafast strong-field
laser–
plasma interactions. An intense ultrashort
laser pulse generates and accelerates dense electron bunches to relativistic energies, giving rise to
photon-pair emission confined to the nanometer scale in space and the attosecond scale in time. As a lowest-order nonlinear QED process, relativistic electrons in
laser-driven
plasmas are shown to give rise to attosecond bursts of two-
photon emission, providing an ultrabroadband source of correlated
photon pairs. As a physically insightful estimate, the rate of this two-
photon emission is expressed via a product $ \alpha^2 \gamma \omega_{turn}$, where $\alpha$ is the fine-structure constant, $\gamma$ is the Lorentz factor, and $ \omega_{turn}$ is the local relativistic
curvature frequency.
Photon pairs with strongest correlations, providing a resource for
photon entanglement, are emitted at a much lower rate, estimated as $ \alpha^2 \gamma^2 \omega_{turn} E_{\perp} /E_S$, where $E_{\perp}$ is the
laser electromagnetic field, determining the transverse Lorentz force, and $E_S$ is the Schwinger critical field. Our study offers a clear guidance on how
quantum aspects of
laser-driven relativistic
plasma electrodynamics can be isolated from their classical counterparts, enabling a physically justifiable approach to the analysis of nonlinear QED phenomena in complex
laser–
plasma interactions driven by ultrashort high-intensity
laser pulses.
Read the full abstract ▾
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Load-dependent Hardness Prediction for Materials using Machine Learning
Madhubanti Mukherjee, Rampi Ramprasad and Harikrishna Sahu
Superhard materials are critical for wear-resistant and high-stress applications. Conventional approaches correlating hardness with elastic
moduli derived from DFT calculations enable rapid screening but overlook the strong load dependence of hardness. In this work, machine learning (ML) models were developed using a large, curated
dataset of load-dependent experimental Vickers hardness (Hv) measurements. Moderate correlation was observed between experimental and DFT-based Hv values, whereas a single-task ML model trained solely on experimental data outperformed multi-task models that combined experimental and computed data. The superior performance of the single-task model highlights that explicit inclusion of indentation load, along with compositional, electronic, and structural descriptors, is essential and sufficient for accurate hardness prediction, beyond what can be achieved using DFT-accessible bulk and shear
moduli alone (or in tandem with experimental data). These results emphasize the importance of high-quality experimental data and explicit inclusion of measurement conditions, particularly load, in the development of reliable hardness prediction models.
Read the full abstract ▾