Fluid Dynamics
Wind-Informed Rapid Flight-Planning in Complex Urban Topologies via Machine Learning and Experimental Validation
Peter I. Renn, Alejandro A. Stefan-Zavala, Julian Humml et al. (+8 more)
Advanced air mobility operations hold the potential to enhance and expand regional transportation of both people and goods in populated areas. However, hazardous flight conditions arising from interactions between wind and the built environment remain a significant challenge for aerial vehicles in urban settings. This work proposes a novel framework towards safe flight planning of aerial vehicles in windy urban environments. A learning-based surrogate model is trained to rapidly predict flow fields from readily available information such as building geometry and incident wind. This surrogate prediction is used to calculate a volumetric flight challenge scalar field based on critical flow parameters and proximity to structures. A safe, flow-informed flight trajectory is then identified through a cost-minimizing pathfinder. The complete system is demonstrated experimentally through flight tests of a micro aerial vehicle through a model urban geometry placed in a large fan-array wind tunnel. Comparing this approach to trajectories generated without knowledge of the wind field, we find the flow-informed approach reduces undesired vehicle displacement and improves flight stability. This work is among the first practical demonstrations of safe, wind-aware methodologies for advanced air mobility in urban environments.
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All authors Peter I. Renn, Alejandro A. Stefan-Zavala, Julian Humml, Sabera Talukder, Aysha AlMazrouei, Kresna Aji, Debashisha Mishra, Emanuele Panizio, Jennifer Simonjan, Yisong Yue, Morteza Gharib
Optics
What should a linear optical frontend compute? Assessing the role of meta-optics, nonlocality, and coherence in hybrid inference systems
Nicholas Behrens, Yandong Li and Francesco Monticone
Hybrid inference systems that pair an optical frontend with a digital backend offer a route to offload computation to the physical layer. Yet what the optics should compute, and when this is beneficial, has remained unclear. Here, we show that, for classification tasks, a well-designed optical frontend reshapes the statistics of the sensor intensity readout to improve class separability, quantified by the Bhattacharyya distance. This training-free metric predicts downstream accuracy and reveals that much of the discriminative information resides in inter-pixel correlations. We then identify the roles of coherence and different forms of nonlocality. Because the sensor measures intensity, a linear frontend produces features that are quadratic in the input field; however, only nonlocal, coherent optical systems can exploit the associated information. Such systems can yield significant performance gains, surpassing the best trained linear preprocessor. These results provide physical insights and new design principles for optimal optical–electronic inference systems.
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Fluid Dynamics
SA-AI (Spalart-Allmaras with Autogenous Inception) Technical Summary
Qiqi Wang
Natural transition from laminar to turbulent flow can be modeled by using only the Spalart-Allmaras (SA) working variable. The variable serves as its own transition indicator, in a one-equation Reynolds-averaged Navier-Stokes (RANS) closure. Its sub-O(1) range is dynamically inert in the baseline model. That range becomes a Tollmien-Schlichting amplification factor. A blended production term then drives the SA transport equation through laminar instability growth and turbulent eddy-viscosity production. Computations with this formulation on a zero-pressure-gradient flat plate, the NLF(1)-0416 and Eppler 387 airfoils, a two-element section, a circular cylinder through the drag crisis, the Daedalus human-powered-aircraft wing, and a 6:1 prolate spheroid are compared with experimental data and with other transition models.
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Geophysics
Ground-to-Cable Strain Transfer in Unburied DAS on Earth and the Moon
Simone Probst, Olav Cornelius, Marc Serra Garcia et al. (+2 more)
Distributed acoustic sensing (DAS) cables are typically buried to ensure good coupling and reduce unwanted atmospheric noise. Unburied deployments are attractive for rapid response applications and for missions to the Moon, where burial is impractical. Unburied DAS, however, suffers from degraded signal quality due to poor strain transfer. Here we quantify bending stress relief as a mechanism behind this loss: cable segments suspended between ground contact points accommodate ground strain by bending, so less axial strain reaches the fiber. We derive the strain transfer of such a segment analytically, compare it to numerical models, and validate it on 56 laboratory configurations of different cable types and lengths. The efficiency is governed by a single dimensionless parameter $\Theta$, set by the ratio of the segment's sag to the cable radius. Keeping the loss below 3% requires a sag below about a quarter of the cable radius. The prediction is quasi-static, holding below the fundamental resonance of the segments. The sag is dominated by the
curvature the cable retains from spooling and handling rather than by gravitational sagging, so $\Theta$ has to be measured and not computed from cable specifications. Because the gravitational contribution is small, the criterion applies equally to deployment on the Moon. Lunar
gravity does reduce the friction available to resist slip at the contact points, but a force balance indicates that slip remains unlikely for natural moonquakes.
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All authors Simone Probst, Olav Cornelius, Marc Serra Garcia, Johan O. A. Robertsson, Carly M. Donahue
Instrumentation and Detectors
Position Resolution of a Scintillator Hodoscope Employing Triangular Counters with Embedded Wavelength Shifting Fibers
E. Craig Dukes, Ralf Ehrlich, Daniel Lee et al. (+4 more)
Scintillator counters employing embedded wavelength-shifting fibers have been used in particle physics experiments for several decades. Such counters have been produced with square, rectangular, and triangular profiles. An advantage of arrays of triangular counters is that their position resolution can be greatly enhanced by interpolation between adjacent counters using their relative light yields. We report here on a testbeam study of the position resolution of such a scintillator hodoscope and compare the results to a simulation. We find an order of magnitude improvement in the position resolution over that found by simply using the fiber separation.
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All authors E. Craig Dukes, Ralf Ehrlich, Daniel Lee, Luke Watson, Alan Bross, Sten Hansen, Paul Rubinov
Atmospheric and Oceanic Physics
Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation
Elynn Wu, James P. C. Duncan, Troy Arcomano et al. (+11 more)
We present a
stochastic coupled emulator of E3SM version 3, built on the SamudrACE framework, which couples an atmosphere emulator (ACE2) with a full-depth ocean emulator (Samudra). We replace the deterministic atmosphere emulator with its
stochastic counterpart, ACE2S, and fine-tune the coupled system with a probabilistic objective, so that the atmosphere acts as a source of internal variability for the ocean. Trained on 105 years of a pre-industrial control simulation and evaluated on an independent 400 years, the emulator reproduces E3SMv3's mean
climate state with biases much smaller than existing model-to-observation differences. Relative to a deterministic baseline,
stochastic training maintains internal variability across timescales, most notably in the ENSO power spectrum, eddy-rich SST anomalies, and sea ice variability in the marginal ice zone. The emulator captures daily precipitation accurately up to the 99.99th percentile, but underestimates the rarest tropical extremes. These results show that
stochastic coupled emulators can reproduce long-timescale variability with high fidelity, while extrapolation to unseen extremes remains a key challenge.
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All authors Elynn Wu, James P. C. Duncan, Troy Arcomano, Jeremy McGibbon, Oliver Watt-Meyer, Christopher S. Bretherton, Naser Mahfouz, Claudia Tebaldi, Luke Van Roekel, Andrew Roberts, Wuyin Lin, Finn Rebassoo, Jean-Christophe Golaz, Peter M. Caldwell
Applied Physics · Cross-listed from cs.ET
Unsupervised Detection of Groundwater Storage Anomalies in Ghana Using GRACE Satellite Data
George Yamoah Afrifa, Theophilus Ansah-Narh and Marcellin Atemkeng
Groundwater variability in Ghana remains poorly characterized due to limited long-term in-situ observations. This study investigates groundwater storage anomalies using GRACE-derived data from 2004-2024 combined with statistical analysis and unsupervised machine learning. Groundwater anomalies were standardized using Z-scores, while an ensemble-based Isolation Forest framework was applied for anomaly detection. The results revealed substantial temporal variability, with persistent groundwater deficits during 2004-2009 followed by increasing positive anomalies after 2018. A total of 12 anomalous months were identified, comprising 5 deficit and 7 surplus events, with the strongest anomalies associated with groundwater deficits. Spatial analysis showed more frequent deficit anomalies in northern Ghana and stronger surplus occurrence in southern regions. Comparison with statistical thresholds further indicated that the machine learning framework captured additional subtle deviations beyond conventional threshold-based methods. Overall, the integration of GRACE observations with unsupervised anomaly detection provides a practical framework for groundwater monitoring in data-scarce environments.
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Applied Physics
A Concept of LNA with Low Input Impedance Using Common Base BJT for Low-Field MRI
Aleksei A. Nasonov, Mikhail V. Murzin, Nikolay V. Anisimov et al. (+4 more)
Purpose: In
magnetic resonance imaging (MRI), preamplifier decoupling is used to improve the signal-to-noise ratio of a multichannel receive coil array. In low-field and ultra-low-field MRI, low-noise amplifier (LNA) solutions with low input impedance (LII) are poorly represented and consist mostly of field-effect transistors. We propose a low-cost LNA based on a common-base
circuit with bipolar transistors to achieve LII (<5 Ohm), a low noise figure (<1.3 dB), and high gain (>30 dB). Methods: The proposed LNA
circuits were simulated, fabricated, and tested at frequencies of 3 MHz and 21.2 MHz. The decoupling capabilities of the proposed LNA were experimentally evaluated, and MR imaging was performed in a 0.5T MRI scanner alongside a comparative study with a commercial LNA. At 3 MHz, the LNA was evaluated by analyzing free induction decay signals. Results: Proposed LNA solutions demonstrate a low noise figure below 1.3 dB with an input impedance of 3 Ohm. It was also shown that the presented LNA
circuit enables high SNR values in MR imaging. The developed amplifiers demonstrate superior performance compared to available commercial options within the selected HF band. Conclusion: Due to the availability and cost-effectiveness of the selected transistors, the proposed LNA
circuit is highly suitable for low-field MRI applications.
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All authors Aleksei A. Nasonov, Mikhail V. Murzin, Nikolay V. Anisimov, Vasily S. Severikov, Anna A. Dyatlovich, Anna A. Hurshkainen, Georgiy A. Solomakha
Computational Physics · Cross-listed from math.NA
A Volumetrically Stabilized Mixed Formulation of the Finite Element Immersed Boundary Method for Fluid Structure Interaction with Fully Incompressible Hyperelastic Solids
Abhishek Mishra and Paul T. Bauman
The finite element immersed boundary method (FE IBM) with a distributed Lagrange multiplier is an attractive framework for fluid structure interaction (FSI) because it couples an Eulerian description of an incompressible fluid to a Lagrangian description of an immersed solid on two independent, nonconforming meshes, avoiding the costly remeshing required by body fitted arbitrary Lagrangian Eulerian methods. When the immersed solid is modelled as a fully incompressible hyperelastic material, however, a direct finite element discretization of the deviatoric solid stress fails to enforce the Lagrangian incompressibility constraint, and the computed structure exhibits spurious volumetric instabilities and locking. In this work we present a mixed formulation of the distributed Lagrange multiplier FEIBM that restores volumetric stability. Following the theory of nearly incompressible hyperelasticity, we augment the solid stress with a volumetric contribution derived from a dilatational strain energy and introduce an additional solid pressure field, enforced weakly, that plays the role of the Lagrange multiplier for the Lagrangian incompressibility constraint J = 1. The resulting formulation is discretized in space by finite elements and in time by an unconditionally stable semi implicit scheme, and is implemented as a reusable Immersed Boundary physics kernel within the GRINS multiphysics framework, built on the libMesh finite element library. The method is verified on three FSI
benchmarks, an elliptically displaced thick ring returning to
equilibrium, a radially stretched incompressible ring, and a disk falling under
gravity in a viscous fluid, for which the mixed formulation removes the volumetric failure observed with the unstabilized formulation and reproduces the analytical terminal velocity of the falling disk to within 1%.
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Optics
Active Electronic Terahertz Imaging for Industrial Applications: From Hardware to the Paradigm Shift by Artificial Intelligence
Aparajita Bandyopadhyay, Hui Yuan, Willie J. Padilla et al. (+2 more)
Imaging with terahertz (THz) radiation (0.3-10 THz) benefits from a unique combination of attributes: penetration through dry, non-polar packaging materials; variations of dielectric functions to provide contrast; the existence of spectral fingerprint resonances for some classes of materials; non-ionizing
photon energies that are safe for use around humans; and - viewed from the low-frequency side - an extension of the capabilities of microwave radar to higher frequencies and thus to substantially better spatial resolution, at wavelengths which still permit direct measurement of the complex-valued radiation field. This review concentrates on active THz imaging with electronic sources combined with power detectors or coherent receivers - the system class most likely to deliver fast (ideally real-time), cost-effective and deployable solutions for a wide range of industrial applications such as quality control, non-destructive testing, security screening and ranging for situational awareness. Such systems should be deployable on robotic and emerging autonomous platforms. We review the state of the art of compact
semiconductor detector arrays, of imaging modalities ranging from focused-beam raster and frequency-modulated continuous-wave architectures to coherent
Fourier-plane acquisition, and of augmentation techniques such as compressive sensing. Particular
attention is paid to the growing role of artificial intelligence: from convolutional neural networks and physics-informed deep learning for phase
retrieval and image reconstruction, to agentic frameworks for autonomous system design. The bottlenecks of THz imaging - acquisition speed, resolution, contrast and cost - are re-examined in the light of these innovations, and a reference-anchored technology roadmap is derived which projects an order-of-magnitude reduction in the measurement requirements of THz imaging.
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All authors Aparajita Bandyopadhyay, Hui Yuan, Willie J. Padilla, David J. Brady, Hartmut G. Roskos
Geophysics
A micro-continuum physics-based model for cohesive sediment gravity flows across mudslide, mudflow, and turbidity current regimes
Mitchell D. Jans, Cyprien Soulaine, Judy Q. Yang et al. (+1 more)
Gravity driven sediment flows are responsible for a major portion of sediment redistribution within oceans, reservoirs, and lakes, with important implications in coastal erosion, siltation, carbon burial, and contaminant migration in aquatic systems. Despite the ubiquity of this phenomenon, current mechanistic understanding of sediment
gravity flows (SGFs) remains limited. This knowledge gap is particularly acute in the case of cohesive, fine-grained sediments (i.e., muds) due to the complex properties of the clay
matrix, including low permeability, viscoplastic rheology, and flocculation. In this work, we develop a computational fluid dynamics model that accurately predicts key features of cohesive, clay-rich SGFs based on independent measurements of the relation between sediment solid fraction and rheological yield stress. In particular, the model captures the four primary flow regimes (low density turbidity currents, high density turbidity currents, mudflows, and mudslides) observed in lock-exchange experiments with slurries containing smectite or kaolinite clay. The model is validated through comparison with previous experimental observations of sediment flow morphology, speed, and runout distance. Overall, we demonstrate the ability to predict the influence of intrinsic (particle size, grain density, and rheology) and extrinsic sediment properties (sediment topography and solid fraction) in the development of self-sustaining cohesive SGFs.
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All authors Mitchell D. Jans, Cyprien Soulaine, Judy Q. Yang, Ian C. Bourg
Medical Physics · Cross-listed from cs.CV
Motion Artifact-Aware Self-Supervised Representation Learning for 3D Brain MRI Motion Artifact Reduction
Mojtaba Safari, Shansong Wang, Zach Eidex et al. (+4 more)
Patient motion remains a source of image degradation in
brain MRI, leading to signal loss, blurring, and
geometric distortion that compromise quantitative analysis. Existing deep learning methods for motion correction typically rely on paired clean-corrupted data or k-space acquisitions, which are rarely available in clinical settings. We propose SSRL-MAR, a motion artifact-aware unpaired representation learning framework for motion artifact reduction that requires neither paired training data nor explicit motion labels. SSRL-MAR employed a three-stage training strategy: (1) contrastive learning on 3D patches to extract motion representations by contrasting clean and synthetically corrupted images, (2) a motion artifact-aware synthesis network to generate motion artifacts from clean scans, and (3) a motion artifact-aware generator to restore clean volumes using the learned degrader for self-supervised supervision. On in-silico
dataset, SSRL-MAR achieved PSNR 23.81dB, SSIM 91.55%, and NMSE 0.79%. On in-vivo MR-ART
dataset, the pretrained model reduced motion distortion, and unsupervised domain adaptation further improved anatomical fidelity. Against a source-only supervised model trained on the same simulated pairs, SSRL-MAR improved PSNR by up to 2.0 dB on MR-ART after unsupervised domain adaptation, and remained within 0.25-0.47 dB of an oracle supervised model that requires real paired data unavailable in practice. At the milder motion level, volumetric error in structures such as the corpus callosum and ventricular system decreased by more than 50%, confirming improved neuroanatomical consistency. These results indicate that SSRL-MAR provides a robust and scalable image-domain solution for 3D
brain MRI motion correction, enabling reliable structural quantification in large-scale neuroimaging studies without requiring prospectively acquired pairs or acquisition-specific calibration.
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All authors Mojtaba Safari, Shansong Wang, Zach Eidex, Matthew Goette, Tonghe Wang, Zhen Tian, Xiaofeng Yang
History and Philosophy of Physics
Was Schrödinger ever a determinist?
Flavio Del Santo and Nicolas Gisin
Erwin Schrödinger is often portrayed as a reactionary who resisted the indeterminism introduced by
quantum mechanics, but on closer inspection his views on determinism prove to be more complex and more radical.
Optics
Practical Evaluation of FFT-Based Thickness Extraction for Thick-Film Reflectometry
Zimu Zhou, Enrique A. Lopez-Guerra, Michael Kwan et al. (+1 more)
Fast
Fourier transform (FFT) is widely used for thick-film reflectometry because of its simplicity and computational efficiency. However, its performance under practical thick-film measurement conditions has received limited experimental evaluation. In this work, FFT, Linearized Reflectance Zero-Crossing (LRZ), and optical model fitting were compared using reflectometry measurements from a nominal 52 {\mu}m dielectric film acquired on a production wafer, with White-Light Interferometry (WLI) serving as an independent reference. Although FFT exhibited excellent repeatability, it showed systematic deviation from WLI (RMSE = 0.62 {\mu}m), whereas LRZ significantly improved accuracy (RMSE = 0.20 {\mu}m). Simulations and theoretical analysis indicate that the observed systematic deviation is consistent with spectral leakage caused by finite measurement windows and non-integer fringe periodicity. These results demonstrate that excellent repeatability does not necessarily imply high accuracy and highlight the advantages of zero-crossing-based approaches for thick-film thickness metrology.
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All authors Zimu Zhou, Enrique A. Lopez-Guerra, Michael Kwan, Chester Chien
Instrumentation and Detectors
Machine learning methods for spectroscopic information recovery under ultrafast photon pileup
Jayson R. Vavrek, Thomas D. MacDonald and Yue Shi Lai
We present methods for recovering spectroscopic information from multiple concurrent
photon interactions that would normally be lost due to pulse pileup. In particular, we focus on machine learning methods to recover information based on spatial (rather than temporal) energy deposition patterns in position-sensitive detectors. We construct two representative problems, namely (1) recovering the fraction of total energy deposition stemming from a monoenergetic signal vs. a smooth background; and (2) recovering the signal multiplicity, i.e., the number of interacting
photons, in a pure-source-term example. In the signal fraction recovery problem, we use 3D convolutional neural networks (CNNs), fully-connected neural networks (FCNNs), a network based on the PointNet++ architecture, and two non-machine-learning methods to estimate the signal fraction in synthetic data when up to 20 total piled-up
photons are present. The CNN, FCNN, and PointNet++ models reconstruct the signal energy deposition fractions with root mean square errors (RMSEs) of $14.5\%$, $18.8\%$, and $16.8\%$ given training
datasets that fit in-core, while the classical methods perform poorly and will not improve with additional training data. In the multiplicity recovery problem, we demonstrate that, when trained with synthetically-piled-up real Cs-137 data, the 3D CNN architecture can recover the multiplicity with sub-
photon RMSE, outperforming non-ML baselines. These methods can be adapted to future, more specific
photon active interrogation applications, helping to re-enable spectroscopic analyses in those domains.
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Physics and Society · Cross-listed from cs.SI
Ollivier's Ricci Curvature on Complex-weighted Graphs
Yu Tian, Eleanor Wiesler and Melanie Weber
Understanding the geometry of complex networks is critical for effective modeling and analysis across domains. While discrete notions of
Ricci curvature have emerged as powerful tools for characterizing both local and global network structure, existing formulations are largely confined to undirected networks with real-valued weights. This limits the use of
curvature-based analysis of directional and complex-weighted relations that arise naturally in many applications, from social and biological systems to
quantum and signal-processing networks. In this work, we introduce a principled extension of Ollivier's
Ricci curvature to complex-weighted graphs, which encompasses directed graphs as a special case. We establish fundamental theoretical properties of this new notion, including relations to the
magnetic Laplacian and combinatorial upper and lower bounds that relate
curvature to cycle structure in local neighborhoods. We further develop computational methods for
curvature estimation and demonstrate their utility in community detection on directed networks.
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Optics
Degenerate high-order hybrid bound states in the continuum beyond diffraction limit
Ji Tong Wang and Nicolae C. Panoiu
We demonstrate the existence of at-$\Gamma$ degenerate hybrid bound-states in the continuum (BICs) with high-order topological charges and quadratic band degeneracy in periodic photonic structures with $C_{6v}$
symmetry above the diffraction limit. The degenerate BICs are realized by combining
symmetry protection, which suppresses radiation into zeroth-order diffraction channel, with quadratic band degeneracy and parameter tuning to eliminate radiation into first-order diffraction channels. An effective
Hamiltonian is used to investigate the band structure around the degeneracy point, and the topological dynamics in all diffraction channels are characterized. This work reveals a novel mechanism for realizing degenerate BICs above the diffraction limit, opening up opportunities for new physics and applications.
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Plasma Physics
Steady state, core, operational optimization of an ARC-like tokamak via plasma composition and shape
A. Saltzman, P. Rodriguez-Fernandez, A. Ho et al. (+8 more)
Impurity composition,
plasma shape, and pedestal density all provide strong levers on fusion power. Here, we explore the ways in which their variation changes fusion power and seek to find the optimum of these parameters. The key impacts of these variables are through changes in the core turbulent transport, the density of the fuel species, the pedestal pressure, and the
plasma volume. ITG stabilization due to increased amounts of
impurities is observed. The dependence of all of these parameters on the pedestal pressure is especially complicated because of the separate impacts on the peeling and ballooning modes, which can each limit the pedestal. Optimization of this multidimensional operating space is enabled by the use of
Bayesian optimization, resulting in an operating point similar to ARC V3A with ~30% more fusion power and a higher fusion power density. Increased shaping parameters, including elongation, triangularity, and squareness are all beneficial, as is high Zeff. When elongation is also allowed to vary, a ~65% increase in fusion power can be achieved. While not commonly considered, we find squareness is an important lever on fusion power. The
plasma performance is limited by the Greenwald density limit constraint. This workflow developed here and demonstrated with the example of ARC V3A can readily be applied to other tokamak designs.
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All authors A. Saltzman, P. Rodriguez-Fernandez, A. Ho, G. Snoep, J. Han, J. Hall, M.S. Anastopoulos Tzanis, J. Hillesheim, A.J. Creely, P. Snyder, N.T. Howard
Instrumentation and Detectors · Cross-listed from astro-ph.CO
Reconstructing Dark Matter Mass and Discriminating Standard and Non-Standard WIMP-Nucleus Interactions with Paleo-Detectors
Dionysios P. Theodosopoulos, Katherine Freese, Chris Kelso et al. (+1 more)
Paleo-detectors record and retain
crystal damage in ancient minerals from
nuclear recoils induced by dark matter scattering over geological timescales. Previous studies have shown that paleo-detectors can provide sensitivity to a variety of dark matter (DM) scenarios which is complementary to conventional direct-detection experiments. In this paper, we complete the first detailed study of how well paleo-detectors can reconstruct DM parameters or distinguish between different types of DM interactions with
nuclei in the presence of a DM signal, considering both elastic and inelastic DM-
nucleus scattering. For representative
nuclear recoil track read-out scenarios, we demonstrate that weakly interacting massive particle (WIMP) DM masses can be reconstructed for a variety of Non-Relativistic Effective Field Theory (NREFT) interactions between WIMPs and
nuclei. In particular, paleo-detectors are projected to be capable of reconstructing WIMP masses $\lesssim$ 10 GeV, a regime that is challenging for conventional direct-detection experiments; further, we find that paleo-detectors could reconstruct WIMP masses up to 1 TeV for hypothetical signals within their accessible parameter space, extending the mass range over which reconstruction is possible by up to a factor of $\sim 2$ compared with analogous studies of conventional direct-detection experiments. In addition, we demonstrate that paleo-detectors could discriminate between canonical
spin-independent or
spin-dependent NREFT interactions and non-canonical interactions which can depend on the relative velocity or momentum transferred between the WIMP and
nucleus. Specifically, at WIMP masses $\gtrsim$ 10 GeV, we project that canonical NREFT interactions can be excluded by paleo-detectors in the cases of nearly all non-canonical interactions without measurement of
nuclear recoil direction, which conventional experiments typically require.
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All authors Dionysios P. Theodosopoulos, Katherine Freese, Chris Kelso, Patrick Stengel
Atmospheric and Oceanic Physics · Cross-listed from hep-ph
Mysterious Transients in the Palomar Observatory Sky Survey (POSS-1) as profound manifestation of the Dark Matter physics
Ariel Zhitnitsky
Transient
star-like objects of unknown origin have been identified in the first Palomar Observatory Sky Survey (POSS-1) as part of the Vanishing and Appearing Sources during a Century of Observations (VASCO) project. The source of the transients recorded by POSS-1 remains unknown, which is the warrant to coin the observed phenomena as Mysterious Transients (MT). We advocate an idea that the dark matter (DM) in form of the
axion quark nuggets (AQN) made of standard model
quarks (or antiquarks) and
gluons, similar to the old idea of the Witten's strangelets, could simultaneously explain all the observed MT signals (including very short time scale for flash itself, association with
nuclear test timing, observed
alignments of several MT events, correlation with UAP reports, etc) collected or recorded for many years. Essentially we argue that the MT is a cousin of Ball Lightning (BL) events, also observed for centuries, without commonly accepted physics explanation. The basic parameters of this model (such as the typical
baryon charge of the nuggets) had been fixed long ago by explaining the observed excess of radiation at variety of scales: from
galactic to the
solar, to local Earth's environments. In this work we use the same framework with the same set of parameters to study the observed MT phenomena. We also suggest several tests which substantiate or refute our proposal. We also present some suggestions on type of instruments required to study this specific (and well defined) type of the UAP events representing the cousins of BL and MT events in the AQN framework.
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Optics · Cross-listed from cond-mat.quant-gas
Ripple Signatures of Majorana Hybridization across a Topological Quantum Quench
Xin-Xin Wang, Jin-Xin Li, Ya-Wen Tang et al. (+5 more)
The crossover between
topology and nonequilibrium dynamics has emerged as a rich frontier, in which
quantum systems can exhibit unique dynamical phenomena that lie beyond the reach of
equilibrium. Of particular interest are quench dynamics across topological phase, as it may reveal the information about the underlying Majorana zero-energy states. Here, we investigate the fate of Majorana boundary modes in a quenched fermionic superfluid using self-consistent time-dependent Bogoliubov-de Gennes theory. For
quantum quenches within the topological regime, Majorana boundary modes survive but undergo coherent boundary oscillations arising from the nonadiabatic deformation of their wave functions. Furthermore, a pronounced ripple pattern appears in the post-quench density distribution following a sudden
topology-changing quench. Here we identify that these ripple structures originates from the coherent hybridization and interference of the initially separated Majorana boundary states. Our findings establish nonequilibrium boundary dynamics as a new approach for probing Majorana physics, which is complementary to conventional
equilibrium measurements.
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All authors Xin-Xin Wang, Jin-Xin Li, Ya-Wen Tang, Lu Qin, Zun-Lue Zhu, Wu-Ming Liu, Liang-Liang Wang, Xing-Dong Zhao
Chemical Physics
SABRE Hyperpolarization of Unmodified Amino Acids in Partially Aqueous Media: L-[1-13C]-Valine as a Model System
Oksana A. Bondar and Thomas B. R. Robertson
Hyperpolarization techniques enhance the sensitivity of
nuclear magnetic resonance (NMR) and
magnetic resonance imaging (MRI), enabling detection of low concentration metabolites and dynamic processes. Signal Amplification by Reversible Exchange (SABRE) transfers
spin polarization from parahydrogen without permanent chemical modification of the substrate. Here, we demonstrate SABRE-mediated 13C hyperpolarization of unmodified amino acids using L-[1- 13C]-valine as the primary model system and provide preliminary evidence of applicability to glycine. Signal enhancements exceeding 60-fold were observed on a 1.1 T benchtop NMR spectrometer. The dependence of polarization on parahydrogen bubbling time, solvent composition, and substrate-to-catalyst ratio was investigated.
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Computational Physics · Cross-listed from cond-mat.other
Analytic Boundary Terms for Arbitrary Crystal Geometries and Direct-Sum Evaluation of Madelung Constants in Triclinic Lattices
Yang He and Zhonghan Hu
The direct-sum evaluation of Madelung constants is complicated by the conditional convergence of
lattice sums, which gives rise to a shape-dependent boundary term. In this work, we present, for the first time, a closed-form analytic expression for this boundary term that is valid for arbitrary
crystal geometries. For general triclinic
lattices, this boundary term maps exactly onto the electrostatic potential generated by a set of uniformly charged parallelograms. In addition, we demonstrate that the residual finite-size correction for a
crystal of characteristic size $p$ decays as $(2p+1)^{-2}$. Building on these results, we develop a robust direct-sum method for the accurate computation of Madelung constants in arbitrary triclinic
lattices and validate its effectiveness through explicit calculations on representative Bravais
lattices.
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Atomic Physics · Cross-listed from quant-ph
A Quantum Coherence Microscope in the Hubbard Regime
Lin Su, Michal Szurek, Alec Douglas et al. (+2 more)
Quantum coherence underlies collective
quantum phenomena and emerging
quantum technologies.
Quantum gas microscopes have transformed
quantum simulation by providing projective snapshots of many-body states with single-atom resolution, but spatially resolved measurements of off-diagonal correlations have remained elusive. Here, using the Talbot effect, we introduce a
quantum coherence microscope that maps off-diagonal correlations onto site-resolved density signals with near-single-site resolution. We use this technique to locally probe the superfluid-Mott transition in a layer of a three-dimensional optical
lattice and to measure coherence beyond nearest neighbors in an engineered potential landscape. By mapping off-diagonal correlations onto density signals through controlled Talbot
evolution, this work opens new possibilities for accessing observables beyond the density basis through tailored matter-wave
evolution and recapture.
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All authors Lin Su, Michal Szurek, Alec Douglas, Ceren B. Dag, Markus Greiner
Applied Physics · Cross-listed from cond-mat.mtrl-sci
AES-Debye: an Accurate, Efficient, and Scalable Engine for Debye Scattering Calculations
Navid Panchi, Sebastian Kuckuk, Markus Wittmann et al. (+2 more)
Total scattering models are essential for characterizing the structure and disorder of nanoscale materials. The Debye scattering equation (DSE) provides a rigorous route to elastic total scattering, but its direct evaluation is computationally demanding because pairwise contributions must be accumulated at every scattering vector, whereas common acceleration strategies based on binned pair-distance distributions or gridded fast
Fourier transforms can introduce discretization and aliasing artifacts that compromise diffuse-scattering accuracy. Here, we present AES-Debye, an accuracy-preserving DSE framework that aggregates pair distances into a pair distribution function (PDF) using corrected bin centers and numerically robust accumulation to suppress discretization and summation errors. A data-locality-aware parallel design enables efficient execution on CPUs and GPUs. We demonstrate strong scalability by computing a high-resolution total scattering profile for a system of 90 million atoms, $(0.1,\mu\mathrm{m})^{3}$, in minutes on a distributed-
memory CPU platform. These capabilities extend accurate elastic total scattering calculations to large, complex systems while simultaneously providing high-resolution PDFs for downstream structural analysis.
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All authors Navid Panchi, Sebastian Kuckuk, Markus Wittmann, Michael Engel, Alberto Leonardi
Optics
Full-Wave Harmonic Balance Framework for Dispersive Time-Varying Photonic Structures
Mohammad R. Tavakol and Wenshan Cai
Time-varying photonic structures redistribute electromagnetic energy among Floquet harmonics, enabling frequency conversion, nonreciprocity, parametric gain, and dynamic wavefront control. Accurate modeling of realistic platforms remains challenging when temporal modulation occurs in strongly dispersive materials, because each harmonic experiences a distinct material response while remaining coupled to all others through the modulation. This work introduces a full-wave harmonic-balance framework for dispersive time-varying photonic structures. The formulation solves the steady-state Floquet response in the frequency domain by representing modulated components as induced secondary sources: volumetric polarization densities for bulk media and surface current densities for conductive sheets. Material dispersion and radiation operators are evaluated at each harmonic frequency, whereas temporal modulation enters as off-diagonal convolutional coupling in Floquet space. The framework is validated for a parametrically pumped rolled
graphene cylinder, where numerical results agree with an analytical Floquet scattering solution and resolve harmonic-specific scattering, absorption, and near fields. It is further applied to an ITO-based epsilon-near-zero (ENZ) space-time metasurface, enabling shape optimization of a reflective device that converts an optical input into sidebands and redirects them into selected spatial diffraction orders. The approach establishes a general platform for modeling and designing dispersive active photonic structures with harmonic-resolved field, power, absorption, and diffraction observables.
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Optics · Cross-listed from quant-ph
Surface passivation for narrowing optical linewidth of silicon T centers in nanophotonic devices
Fariba Islam, Chang-Min Lee, Kyu-Young Kim et al. (+4 more)
Silicon T centers are promising
spin-
photon interfaces in solid-state platforms for telecom-compatible, scalable
quantum information technologies. A major challenge for T centers in nanophotonics is spectral
diffusion, where fluctuations in the local electric-field environment from surface and bulk charge states broaden the optical transition and reduce
photon indistinguishability. Strategies that directly suppress spectral
diffusion are therefore critical for improving T-center-based
quantum photonic devices. Here, we use atomic-layer-deposited Al2O3 to passivate the silicon surface and demonstrate a systematic narrowing of T center optical linewidths. Across our measurements, Al2O3 passivation reduces the T center emission linewidth by up to 57%. Complementary above-bandgap illumination and spectral hole burning measurements show that the remaining linewidth contains a significant spectral-
diffusion component caused by adjacent charge traps, while placing an upper bound of approximately 75 MHz on the homogeneous linewidth. This work provides a CMOS-compatible path toward generating indistinguishable
photons from silicon T centers for scalable
quantum photonic applications.
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All authors Fariba Islam, Chang-Min Lee, Kyu-Young Kim, Sorah Fischer, Purbita Purkayastha, Amirehsan Alizadehherfati, Edo Waks
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Spatially resolved elastic strain and lattice rotation at threading dislocations in HgCdTe/CdZnTe epilayers by dark-field X-ray microscopy
C. Yildirim, A. Benhadjira, P. Ballet et al. (+5 more)
Threading dislocations (TDs) propagating from a Cd$_{1-y}$Zn$_{y}$Te (CZT) substrate into a
liquid-phase-epitaxy Hg$_{1-x}$Cd$_{x}$Te (MCT) epilayer set the minority-carrier lifetime and dark-current floor of mid-wave infrared focal-plane arrays, yet at device-grade densities their local strain fields have been accessible only through topography, which conflates
lattice tilt and elastic strain. We apply dark-field X-ray microscopy in reflection geometry to a \SI{7}{\micro\metre}-thick (111) MCT/CZT epilayer. Shallow Bragg angle and absorption makes the signal layer dominated while the numerical aperture of the objective keeps the layer and substrate rocking curves convolved, so weak-beam images on either side of the rocking curve and their difference image the correlated defects in a single frame: dot-like substrate TDs and the elongated, in-plane island features they nucleate in the layer. Kernel average misorientation resolves each TD as a \SI{7}{\micro\metre} signature, the layer thickness, alongside axial strain lobes of $\pm(4$ to $5)\times10^{-5}$.
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All authors C. Yildirim, A. Benhadjira, P. Ballet, T. N. Tran Caliste, J. Baruchel, C. Detlefs, D. Brellier, M. P. Kabukcuoglu
Computational Physics
Autonomous Lindblad Realizability of Nonunitary Linear Dynamics with a Carleman Lattice Boltzmann Application
Muhammad Idrees Khan
Carleman lifting converts nonlinear
polynomial dynamics into finite linear systems, but the resulting truncations are generally nonunitary and need not correspond to physical
quantum evolution. We prove that a finite linear endpoint admits an autonomous Gorini–Kossakowski–Sudarshan–Lindblad (GKSL) realization on
vacuum coherences if and only if it is invertible and power bounded. The construction is explicit and realizes the nonunitary map directly as open-system dynamics, with no endpoint postselection and with one encoding and one decoding over repeated timesteps. We apply the result to the complete D2Q9 multiple-relaxation-time
lattice Boltzmann (LB) timestep by compiling collision and periodic streaming into a single Carleman endpoint. The resulting GKSL
evolution reproduces the classical Carleman trajectory over multiple timesteps, while the remaining discrepancy from nonlinear LB dynamics is the expected Carleman truncation error. The result establishes a general criterion for autonomous open-
quantum realization of finite nonunitary dynamics, with Carleman–LB dynamics as a concrete example.
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Computational Physics · Cross-listed from q-bio.NC
Graph Analysis of Neuronal-Culture Connectivity Derived from a Reservoir-Computing Model
Ilya Auslender, Giorgio Letti, Yasaman Heydari et al. (+1 more)
Graph-theoretical analysis offers a principled framework for quantifying emergent dynamics in neuronal cultures. Here, we present an analytical pipeline for inferring network-level properties of in vitro cortical cultures from multichannel electrophysiological recordings. The approach builds on a recently proposed Reservoir Computing (RC) framework (Auslender et al., 2025), which enables direct extraction of an Intrinsic Connectivity Map (ICM) from neural activity. We interpret the ICM as an effective adjacency
matrix and apply graph-theoretic centrality measures to quantify node- and edge-level contributions to the culture's collective dynamics. We systematically evaluate both local and global graph metrics and examine their relationships with experimentally measured activity features, including firing rates and network-level descriptors. To validate the inference procedure, we also simulate the experimental environment, enabling controlled benchmarking of the RC-derived connectivity against a known ground-truth adjacency
matrix and assessment of model performance as a function of graph structure. Our results demonstrate statistically robust associations, of varying strength, between graph-theoretic measures and experimentally observed activity patterns. These findings additionally support the validity of the RC-based connectivity inference and establish a scalable, data-driven framework for functional network characterization in neuronal culture systems.
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All authors Ilya Auslender, Giorgio Letti, Yasaman Heydari, Lorenzo Pavesi