Instrumentation and Detectors · Cross-listed from eess.SP
Multi-Channel Soil Moisture Measurement: High Accuracy and Low Crosstalk Through Optical-Semiconductor Based Differential Sensing
Thomas Maier, Charlotte Rohleder, Lukas Kamm et al. (+3 more)
Soil moisture measurement plays a key role in irrigation and environmental management. Yet it remains unreliable due to heterogeneous soils, limited sensing volumes, temperature drift, and parasitic inter-channel coupling. This work presents a compact multi-depth capacitive probe that extends a parallel-plate geometry from previous work with differential activation to suppress stray capacitances and improve accuracy. An equivalent-
circuit model quantifies parasitic effects, and optically coupled transistor bridges isolate each sensing layer. Raw capacitance is converted to volumetric water content and plant-available water using established calibration models. Laboratory results show a fourfold reduction in temperature sensitivity, strong confinement of the sensing volume, and improved repeatability in heterogeneous soils. Field validation against reference sensors demonstrates high accuracy and precision comparable to widely used instruments, enabling a practical and scalable solution for agricultural and urban soil-moisture monitoring.
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All authors Thomas Maier, Charlotte Rohleder, Lukas Kamm, Philipp Dauner, Jan Pinski, Bjoern M. Eskofier
Geophysics
Surface Crevasse Evolution Observed Using Matched Field Processing and Source Relocation at Hansbreen, Svalbard
Wojciech Gajek, Ugo Nanni, Ali Gholami et al. (+3 more)
Crevasses control glacier dynamics through fracture and meltwater routing, yet their propagation rates remain observationally scarce and poorly constrained across brittle-to-viscous regimes. Cryoseismology offers a powerful means to capture dynamic processes within glacial ice, with recent advances in novel processing methods like Matched Field Processing (MFP) applicable to dense seismic arrays. However, precise localisation of cryoseismic sources remains challenging in sparse or irregular seismic arrays. We propose a two-step workflow for metres-scale resolution mapping of glacial seismic activity that integrates MFP and discrete arrival times relocation under a limited instrumentation constraint. We apply this approach to analyse seismic activity at the ice surface on the Hansbreen glacier, Svalbard. Using MFP, we detect surface icequakes and characterise meltwater noise regardless of the limited instrumentation. The relocation procedure increases the accuracy of surface icequakes localisation and reveals ongoing crevasse opening episodes. The precise locations of the icequakes allow for the estimation of the crevasse propagation rate and the determination of the
diffusion coefficients of 0.47 to 0.55 m2 per s. Based on the obtained results, we discuss brittle-to-viscous regime transfer and interpret the crevassing mechanism as sustained subcritical crack propagation, where viscous stress relaxation governs rates of orders of magnitude below elastic limits.
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All authors Wojciech Gajek, Ugo Nanni, Ali Gholami, William D. Harcourt, Danni M. Pearce, Louise Steffensen Schmidt
Optics
Event-based Scheimpflug LiDAR for Ultra-Fast Laser-Scanned Rangefinding
Nathan Meraz, Alisha Whitehead, Suet Ying Chan et al. (+3 more)
Frame-based ranging systems are constrained by frame rate and provide no intrinsic mechanism for background rejection, limiting utility in high-throughput or cluttered environments. We present eSCHORTY, a Scheimpflug
LiDAR integrating an event-based sensor with a modulated continuous-wave line
laser to enable dense 3D point clouds, generated from over one million megaevents per second. We demonstrate that
laser modulation provides a trade-off between event-space feature detection and localization, and that logarithmic event encoding suppresses the reflectance-induced centroid artifact demonstrated in intensity-based ranging. Reconstructions of natural scenes confirm spatially coherent depth recovery, with the Scheimpflug geometry supporting adaptation from millimeter- to kilometer-scale applications.
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All authors Nathan Meraz, Alisha Whitehead, Suet Ying Chan, Ronan Taneja, Gabriella Mayrend, Joseph L. Greene
Instrumentation and Detectors
Feasibility demonstration of continuous signal-based neutron noise measurements by experiments and simulations
Máté István Boros, Máté Szieberth, Gergely Klujber et al. (+4 more)
Neutron noise methods are used to determine kinetic parameters such as the
prompt neutron decay constant, but traditional pulse-counting suffers from dead-time and pile-up at high detection rates. Recent theory shows that analysing the continuous detector current can avoid these limitations if pulse-shape effects are properly treated. This work presents a feasibility study of continuous-signal
neutron noise analysis based on simulations and experiments performed at two research reactors. The
stochastic model of the detector current is applied to derive Rossi- and Feynman-type formulations, and pulse-shape distortions are mitigated using detector pairs or by deconvolving the average pulse-shape through inverse
Fourier and Wiener filtering. Simulations demonstrate accurate $\alpha$-parameter estimation at count rates where pulse-counting becomes unusable, and enable evaluation of significantly higher $\alpha$ values. Measurements at KUCA and BME TR confirm that continuous and deconvolved signals provide unbiased results despite dead-time and electronic artifacts, establishing the method as a practical alternative for high-rate reactor noise diagnostics.
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All authors Máté István Boros, Máté Szieberth, Gergely Klujber, Imre Pázsit, István Barth, Yasunori Kitamura, Tsuyoshi Misawa
Computational Physics · Cross-listed from cs.CE
A Constrained Natural-Language Interface for Variational Multi-Physics Finite Element Simulations in FEniCS
Nilay Upadhyay and Wesley F. Reinhart
Large
language models can reduce the manual effort required to set up finite element simulations, but they introduce reliability risks when generated solver code lies on the critical path. We present a constrained natural-
language interface for multi-physics finite element analysis in which the LLM is limited to front-end tasks: parsing
prompts into structured JSON, generating Gmsh code only for non-catalog geometries, and using retry feedback for those stages. It never writes FEniCS solver templates, derives weak forms, or writes the numerical solver core. A deterministic dispatcher maps the validated specification to five human-written FEniCS/UFL templates: linear elasticity, hyperelasticity, elastoplasticity, thermo-mechanical coupling, and phase-field fracture. We validate this deterministic template layer against analytical solutions and published 2D/3D
benchmarks. Smooth cases reach sub-percent agreement on adequate meshes, while harder nonlinear cases reach the 2-5 percent range. We also evaluate the LLM-facing front end directly. In a 15-
prompt parser
benchmark, first-pass valid parses were obtained for 9 cases, and all remaining cases were repaired after retry, giving a final valid parse rate of 100.0 percent, 100.0 percent problem-class accuracy, and 97.1 percent field-extraction accuracy. In a 10-case custom-geometry
benchmark routed through the real LLM-to-Gmsh path, first-pass and final success were both 90.0 percent, with one unrecovered invalid-geometry failure. These results show that the parser and constrained
prompt/validation design are effective on these
benchmarks. As an end-to-end demonstration, the system generates and analyzes a 3D elastoplastic L-bracket with a fillet and bolt hole from one natural-
language prompt. The contribution is a measured architecture for natural-
language-driven variational simulation, not open-ended autonomous code generation.
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Fluid Dynamics
Topological origin of flow distributions in disordered porous media
Jose Arnal, Guillem Sole-Mari and Tomás Aquino
We investigate steady Stokes flow through porous media composed of two-dimensional disordered arrays of circular obstacles. We develop a theory for the statistics of flow rates based on a pore-network model that captures local flow correlations. We show that the flow rate distribution across the ensemble of pore bodies follows a Gamma distribution, and that the flow rate distribution through pore throats is fully determined in terms of it. Furthermore, this Gamma distribution can be directly linked to simple geometrical properties such as the coefficient of variation of pore throat widths, rendering the model parameterisable from minimal medium information. The resulting predictions agree closely with computational fluid dynamics simulations and show markedly better agreement than prior mean-field models that neglect local flow-rate correlations, clarifying how local splitting and merging shape flow in disordered porous networks.
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Computational Physics · Cross-listed from cs.CE
Non-linear mechanical field reconstruction coupling recurrent neural networks with physics-informed graph neural networks
Manuel Ricardo Guevara Garban, Yves Chemisky, Étienne Prulière et al. (+3 more)
Reconstructing local stress fields in heterogeneous microstructures under non-linear, history-dependent loading remains a major computational bottleneck in multi-scale simulations. We propose a coupled LSTM-GNN framework that links the temporal and spatial aspects of local stress field reconstruction. A Long Short-Term
Memory network encodes macroscopic stress-strain sequences into a compact hidden state that captures the path-dependent constitutive response, while a physics-informed Graph Neural Network reconstructs the spatially-resolved stress field at each time step. We introduce a relative weighting strategy with linear warm-up to balance the data-driven reconstruction loss and a discrete divergence-based
equilibrium penalty. This resolves the scale mismatch that prevents fixed-weight formulations from converging in the elasto-plastic regime. The model is trained on 10,000 non-proportional loading paths applied to a periodic plate-with-a-hole microstructure and von Mises elasto-plasticity. The model achieves three orders of magnitude speedup over finite element simulations and generalizes to loading sequences twice the training length, with 1.9% cumulative error. Because the graph relies on mesh connectivity instead of the specific element type, one trained surrogate can be applied directly without retraining to meshes with different element types and to both coarser and finer resolutions, while in all cases reproducing the high-fidelity quad-element FE field used during training. Indeed, the message passing characteristics inherent to GNN and MeshGraphNet architecture render the model mesh-agnostic. Analysis of the LSTM hidden states suggests a low-dimensional structure related to the internal state variables of the constitutive model.
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All authors Manuel Ricardo Guevara Garban, Yves Chemisky, Étienne Prulière, Michaël Clément, Martin Abendroth, Björn Kiefer
Optics
A single-step lithography process for reconfigurable SiN photonics with TiN heaters and Al interconnects
Leonardo Limongi, Rachele Favaretto, Lorenzo Baldessarini et al. (+6 more)
Thermo-optic phase shifters are key building blocks in Silicon and Silicon Nitride-based reconfigurable photonic integrated
circuits. They enable manipulating the phase of an optical signal by means of electrically-driven heating of an optical waveguide. Conventional fabrication schemes typically require dedicated lithographic steps to separately define the resistive heaters, the current transmission lines, and the electrical contact pads. This increases the process complexity and slows the standard complementary metal-
oxide-
semiconductor (CMOS) fabrication flows. In this work, we present a single-step lithographic process for the realization of Titanium Nitride thermo-optic phase shifters and Aluminum interconnects integrated on a Silicon Nitride photonic platform. A detailed electro-optical characterization, performed on two platforms operating at 810 nm and 1550 nm, revealed $\pi$-shift powers of 92 $\pm$ 2 mW and 120 $\pm$ 10 mW, respectively. Alongside, modulation bandwidths of 8.5 $\pm$ 0.3 kHz and 3.83 $\pm$ 0.03 kHz were extracted from combined frequency- and time-domain analyses. Our results demonstrate that the proposed single-step lithographic metal definition process represents a robust, viable and cost-efficient route towards CMOS-compatible reconfigurable Silicon Nitride photonics.
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All authors Leonardo Limongi, Rachele Favaretto, Lorenzo Baldessarini, Martino Bernard, Yong Kwon, Gioele Piccoli, Alina Samusenko, Georg Pucker, Mher Ghulinyan
Medical Physics
Flow-Mediated Regulation of Pathogen Survival in the Human Stomach
Sharun Kuhar, Jung-Hee Seo and Rajat Mittal
Foodborne diseases remain a major public-health burden, and the gastric acid barrier serves as the body's primary chemical defense against ingested microbes. Yet experimentally investigating pathogen survival within this environment is highly challenging. Although recent computational stomach models have provided insights into gastric disorders, none have coupled fluid flow, acid transport, and pathogen population kinetics in a realistic stomach to assess gastric acid barrier function. Here, we develop an imaging-based stomach model that tracks 10,000 massless particles representing pathogen colonies ingested with a
liquid meal as they are advected through a dynamic, spatially heterogeneous pH field. The model incorporates acid secretion, peristaltic mixing, and gastric tone-driven emptying. Using this framework, we quantify how hypomotility and altered gastric tone influence pathogen survival. Motility emerges as the dominant factor governing pathogen fate. The hypomotile stomach exhibits weaker mixing, retaining nearly 50% of the initial pathogen population alive 6 minutes after ingestion, compared with less than 30% in healthy cases. It also produces broader acid-dose distributions and more heterogeneous survival outcomes. Counterintuitively, among healthy-motility cases, increased gastric tone delivers the highest concentration of viable pathogens into the duodenum, revealing a trade-off between transport and acid-mediated inactivation. These findings demonstrate that conventional metrics such as average pH or gastric emptying rate are insufficient for assessing gastric sterilization. Instead, the present flow-transport-kinetics framework provides new mechanistic insights into pathogen survival and gastric infection risk.
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Instrumentation and Detectors · Cross-listed from eess.IV
Low-Dose 3D Bonding Mapping Through "Soft" Core-Loss EELS Tomography and Unsupervised Deep Learning
Mario Pelaez-Fernandez, Daniel del-Pozo-Bueno, Adrien Teurtrie et al. (+10 more)
Resolving the 3D chemical configuration of beam-sensitive nanomaterials at high spatial resolution remains a persistent frontier in scanning transmission electron microscopy (STEM). The main limitation lies in the trade-off between high electron dose required for analytical signals and the large number of projections needed for tomographic reconstruction. Here, we achieve dose-efficient 3D bonding mapping of FeO/Fe$_3$O$_4$ core-shell nanocubes with high resolution via electron energy loss spectroscopy (EELS). Our approach relies on two developments. First, a standardless "soft" core-loss EELS methodology exploiting Fe-M$_{2,3}$ edges provides ${\sim}50\times$ higher dose efficiency than conventional Fe-L$_{2,3}$ edges, using the latter only as a source of FeO and Fe$_3$O$_4$ standards. Second, we introduce multi-channel deep image prior with total variation regularization (DIPm-TV), an unsupervised method for spectroscopic
tomography that jointly reconstructs multiple channels by exploiting spatial correlations under sparse-view and low-dose conditions. Using simulated
datasets, high-quality reconstructions are obtained from as few as nine projections over $-70^\circ$ to $+70^\circ$, without HAADF-STEM signal or
symmetry constraints. Applied to FeO/Fe$_3$O$_4$ nanocubes, Fe-M$_{2,3}$ EELS maps show improved SNR and spatial resolution, revealing a thin outer FeO shell surrounding the magnetite shell. DIPm-TV yields ${\sim}1$ nm isotropic resolution oxidation-state volumes preserving cubic morphology, recovering the outer FeO shell, and revealing a small internal void, features not accessible with conventional reconstruction methods. This work establishes a pathway for low-dose 2D and 3D analytical mapping of beam-sensitive materials using shallow core-loss edges, enabling orders-of-magnitude dose reduction while maintaining spectral fidelity and reliable 3D information.
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All authors Mario Pelaez-Fernandez, Daniel del-Pozo-Bueno, Adrien Teurtrie, Serge Brosset, Maya Marinova, Phillipe Ciuciu, Marta Estrader, German Salazar-Alvarez, Francesca Peiró, Raul Arenal, Sonia Estradé, Zineb Saghi, Francisco De la Peña
Chemical Physics · Cross-listed from astro-ph.EP
First detection of HDO ice in a protoplanetary disk
Alexey Potapov, Piyush Kalambkar, Jeroen Bouwman et al. (+4 more)
Protoplanetary disks are the birthplace of
planets and planetary systems. Investigating the molecular inventory of disks is key to linking the chemical
evolution of the interstellar medium and the makeup of
planets and their atmospheres. In particular, tracing the history of the deuterium enrichment of water along the journey from interstellar clouds through protoplanetary disks to planetary systems provides critical insights into the chemical inheritance. We aim to investigate the chemical composition of ices in protoplanetary disks; specifically, the presence of HDO ice that ought to be present, but has not been detected in disks thus far. We analyzed JWST/NIRSpec observations of the 132-1832 edge-on disk located in the Orion Nebula Cluster using the ENIIGMA fitting tool and unique laboratory data. We report on the first detections of HDO ice in a protoplanetary disk. The estimated upper limit for the HDO/H$_2$O ratio for 132-1832 is much higher, compared to HDO/H$_2$O ratios obtained for chondrites, comets, and embedded young
stellar objects. In the disk ices, beyond HDO, we detected H$_2$O, CO$_2$, $^{13}$CO$_2$, CO, OCN$^-$, and OCS, species, whose presence has also been detected in other disks. The HDO ice detection may point to the efficient ice processing in the disk and confirm the findings of laboratory experiments on deuterated ices.
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All authors Alexey Potapov, Piyush Kalambkar, Jeroen Bouwman, Christiaan Boersma, Hiroshi Terada, Will R. Rocha, Hendrik Linz
General Physics
Belief in thermodynamics has provoked false thermodynamics of superconductors
A.V. Nikulov
Belief in thermodynamics has forced superconductivity experts to forget basics of thermodynamics due to a contradiction of superconductivity phenomena to laws of thermodynamics. Because of this belief no one drew reader's
attention during many years that the conventional theory of superconductivity contradicts to the second law of thermodynamics. The common belief that the superconducting transition occurs when the free energy of the superconducting state becomes less than of the normal state has provoked a false claim that a power source of a solenoid creates the energy of magnetization rather than of
magnetic field. The authors of only a few books on superconductivity, mostly future Nobel prize winners, did not follow this false claim. No one for many years has noticed that the equality of free energies at the superconducting transition in the critical
magnetic field cannot be obtained without contradicting the second law of thermodynamics. The Meissner effect violates the second law of thermodynamics because of the negative surplus work performed in the closed Gorter cycle. The desire to avoid contradiction of superconductivity phenomena with the second law of thermodynamics provoked the false thermodynamics of
superconductors, contradicting the law of conservation of energy.
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Biological Physics
Spontaneous polarization for protrusion-driven cell crawling
Pierre Recho
We propose a minimal one-dimensional continuum model for the spontaneous initiation of protrusion-driven
cell crawling on a rigid substrate. The
cell cytoskeleton is represented as a viscous actin meshwork that turns over in the bulk and polymerizes at two moving
cell edges.
Symmetry breaking arises from the feedback between
cell motion, an external chemical regulator of actin nucleation, and actin polymerization at the
cell fronts. When the
cell moves, the regulator becomes polarized around the moving boundaries, thereby imposing different actin nucleation densities at the two edges. This generates unequal protrusive rates, which in turn reinforce motion and sustain the chemical polarization. Above a critical protrusive activity, the static symmetric state loses stability and the system undergoes a bifurcation toward a motile polarized state. Depending on how the external cue controls actin nucleation, the transition can be either supercritical or subcritical, leading in the latter case to coexistence between static and motile states. Using parameter values appropriate for keratocyte
cells, the model predicts realistic crawling speeds and actin-density profiles, including asymmetric edge-localized density peaks. These results identify a generic mechanism by which external biochemical regulation of actin nucleation can trigger spontaneous motility along a one-dimensional track without requiring molecular motors, specific adhesion dynamics, deformable substrates, or pre-existing polarity.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Efficient analytic continuation approach to Bethe-Salpeter excitation spectra in selected energy windows
Ivan Duchemin and Xavier Blase
We explore the merits of building the Bethe-Salpeter absorption spectrum in a specific energy range using analytic continuation techniques. Specifically, we calculate iteratively a few $\bar{\bar \alpha}(z_k)$ polarizability tensors for a coarse set of $(z_k)$ frequencies in the complex-plane. These data allow constructing a continued-fraction representation for $\bar{\bar{\alpha}}(z)$ that is used to calculate the absorption spectrum close to the real energy axis in the desired energy range. The number and location of these sampling complex frequencies are discussed. The importance of building a continued-fraction representation of the full polarizability tensor with
matrix-valued coefficients is emphasized. We show how to extract the poles of the continued fraction as a tool for analyzing the resulting spectra. We study as examples the valence excitations of a paradigmatic dipeptide, the C$_{60}$ fullerene and its PCBM derivative, together with the description of the surface plasmon resonance of the Ag$_{20}$ silver cluster. Further, the high-energy C$_{60}$ X-ray absorption spectrum is explored.
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Fluid Dynamics
Data-driven surrogate models for forecasting experimentally measured fluid flows
Peter I. Renn, Emily H. Palmer, Cong Wang et al. (+1 more)
Data-driven modeling shows significant promise for faster-than-real-time
forecasting of fluid flows. For real-world engineering applications (e.g., flow control), models must contend with limited, imperfect, and incomplete experimental measurements. In this work, we present an analysis of data-driven surrogate models trained to forecast the time-
evolution of experimentally measured cylinder wakes in the subcritical
vortex shedding regime. Using a
dataset of two-dimensional, two-component particle image velocimetry measurements, we train fully convolutional neural networks, U-Nets,
Fourier neural operators, and dynamic mode decomposition-based models to forecast the development of experimentally measured velocity fields. To characterize data-driven approaches contending with transient flow features and limited, imperfect observations, the development of predictions over extended forecast horizons is examined at a fixed Reynolds number (Re = 590). Next, models are trained at a range of Reynolds numbers (Re = 230 to Re = 2920) to investigate the impact of increasingly turbulent and three-dimensional flow phenomena, and the challenges associated with measuring them, on forecast quality. We find that experimentally trained surrogate models can provide meaningful predictions over short time horizons, propagate low-frequency dynamics over longer forecast periods, and achieve faster-than-real-time evaluation. However, the data-driven models struggle to preserve transient flow features and high-frequency energy content when faced with noisy measurements and incomplete state observations. This emphasizes the underlying challenges that remain for data-driven modeling approaches to effectively contend with fluid dynamics in real-world engineering applications, where observations are often imperfect and limited.
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All authors Peter I. Renn, Emily H. Palmer, Cong Wang, Morteza Gharib
Geophysics
Supershear Rupture Indicator in Near-fault Particle Motion
Suli Yao, Hongfeng yang, Harsha S. Bhat et al. (+1 more)
Earthquake rupture propagation speed is an essential source parameter that fundamentally controls hazard and risk. In this paper, we develop and demonstrate the capability of near-fault seismic records in delineating rupture speeds of strike-slip earthquakes through inspecting displacement particle motion. We apply the new method on near-fault strong-motion data in global M7+ strike-slip earthquakes and identify diverse particle motion signatures associated with sustaining subshear rupture, sustaining supershear rupture, supershear transition, oblique slip, initial rupture expanding process, and multiple rupture fronts. This study highlights the superior application of near-fault observations in rapid rupture speed determination.
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All authors Suli Yao, Hongfeng yang, Harsha S. Bhat, Hideo Aochi
Atomic Physics
Enhanced nondipole momentum offsets in triple ionization of atoms driven by mid-infrared laser fields
Samuel James Praill, Georgios Petros Katsoulis, Daria Romero Torres et al. (+1 more)
We investigate the dependence on wavelength of nondipole effects in triple ionization of Ne driven by intense infrared and mid-infrared
laser pulses using a three-dimensional semiclassical model that fully accounts for nondipole effects and the Coulomb singularity in the electron-core interaction. We find in triple ionization of strongly driven Ne a large positive average momentum offset along the direction of
laser propagation, which vanishes in the dipole approximation. This positive momentum offset significantly increases with increasing wavelength of the
laser pulse. This increase is present for all triple ionization events as well as for the main direct and delayed pathways of triple ionization. We attribute the increase of the momentum offset to the contribution of the effect of the
magnetic field of the
laser pulse on the bound electrons. This contribution counterbalances the decrease of electron-electron correlation in recollisions with increasing wavelength. We find that 1200 nm is an ideal wavelength for experimentally measuring the momentum offset related to correlated three-electron escape.
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All authors Samuel James Praill, Georgios Petros Katsoulis, Daria Romero Torres, Agapi Emmanouilidou
Computational Physics
Bounding the Null Space: Interval-Based Uncertainty Quantification for Non-Identifiable Groundwater Models
Maximilian Ramgraber and Ksenia Bestuzheva
Groundwater models are routinely non-identifiable: sparse subsurface observations leave many combinations of parameters, states, and boundary conditions equally consistent with the available data. Existing uncertainty quantification (UQ) methods address this by exploring a finite set of model realizations, but incomplete exploration can systematically underestimate the true range of admissible solutions. We propose a fundamentally different approach based on Optimization-based Bound Tightening (OBBT), which represents uncertainty directly as intervals and tightens them by extremizing variables over a constraint system encoding physical laws and observations. This yields guaranteed outer bounds on all uncertain variables without sampling, side-stepping the exploration problem entirely. To apply OBBT to groundwater flow, we discretize Darcy's law using a finite-volume scheme and handle the resulting bilinear terms through McCormick relaxations. We show that these relaxations can break the sign coupling between fluxes and head gradients, permitting non-physical rotational flow and failing to provide sufficient information for effective bound tightening. We identify flow sign prescription and irrotationality constraints as effective remedies and characterize their respective strengths and limitations. We demonstrate the framework on three numerical examples - a 1D steady-state model, a 2D steady-state model across four experimental configurations, and a 2D transient model on a hexagonal grid - and discuss computational performance, scalability, and directions for future research. OBBT offers a conservative, deterministic, and physically grounded alternative to ensemble-based UQ, with natural connections to null space theory and data assimilation.
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Biological Physics · Cross-listed from cond-mat.soft
NANOG assembles into self-limiting aging micelles that drive a sol-gel transition and modulate DNA dynamics
Amandine Hong-Minh, Yair Augusto Gutierrez Fosado, Abbie Guild et al. (+4 more)
Proteins and nucleic acids form non-Newtonian
liquids with complex rheological properties that contribute to their function in vivo. Here we investigate the rheology of the transcription factor NANOG, a key
protein to maintain embryonic stem
cell pluripotency. We find that at high concentrations, NANOG forms macroscopic aging gels that are dependent on its intrinsically disordered domain. By combining molecular dynamics simulations, mass photometry and Cryo-EM, we also discover that – in contrast with unbounded condensates formed by other intrinsically disordered
proteins – NANOG forms self-limiting micelles with exposed DNA-binding domains. We show that these micelles can stabilize DNA entanglements and in turn modulate DNA dynamics. Based on our findings, we
conjecture that NANOG may contribute to regulate gene expression by creating local gel-like environments that restrict genome dynamics and that its aging may ingrain mechanical
memory in gene regulatory networks.
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All authors Amandine Hong-Minh, Yair Augusto Gutierrez Fosado, Abbie Guild, Nicholas Mullin, Laura Spagnolo, Ian Chambers, Davide Michieletto
Medical Physics · Cross-listed from cs.CV
DD-INR: Dynamics-Driven Implicit Neural Representation for Accelerated Whole-Brain Functional MRI Reconstruction
Qiaoxin Li, Caini Pan, Pierre-Antoine Comby et al. (+2 more)
Accelerated acquisition of fMRI enables enhanced detection of neurovascular (BOLD) activity in the
brain, but image reconstruction becomes challenging with high k-space undersampling: Task-evoked BOLD signals are small in magnitude, which traditional anatomical MRI reconstruction methods fail to recover, as they favor spatial accuracy over temporal fidelity. We present DD-INR, a Dynamics-Driven Implicit Neural Representation framework tailored for accelerated fMRI that benefits from incoherent time-varying sampling and a tailored spatiotemporal prior, outperforming traditional methods, demonstrated in simulation and in-vivo acquisition, both in terms of image quality and
retrieval of activation patterns. DD-INR achieves this by splitting the fMRI data into a static background and a temporally varying dynamic component, representing only the dynamics with a dedicated INR, thereby focusing the model's capacity on activation-relevant changes while remaining compact. In general, DD-INR provides a promising framework for accelerated fMRI reconstruction, with the potential to improve the sensitivity and robustness of fMRI studies within practical scan time limits. The source code is available at https://github.com/JoosenLi/DD-INR.
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All authors Qiaoxin Li, Caini Pan, Pierre-Antoine Comby, Chaithya Giliyar, Philippe Ciuciu
Applied Physics · Cross-listed from cond-mat.soft
Spontaneous translation of charged droplets during evaporation on dry surfaces
Riming Xu, Yanbo Li, Jiawen Zhang et al. (+2 more)
Evaporating sessile droplets are usually treated as capillary objects, but droplets generated by routine handling can carry tens to hundreds of picocoulombs of electric charge. Here we combine Faraday-cup charge measurements with optical imaging to determine how such charge evolves as water droplets evaporate on dry
polymer substrates. A zero-time protocol shows that a reproducible initial charge is preserved on poly(methylpentene) (PMP), whereas PDMS, SOCAL-coated surfaces, and polystyrene either exchange, dissipate, or inject charge on contact. On PMP, ensemble-resolved measurements reveal two regimes: the charge remains nearly constant during early evaporation and then decreases abruptly once the droplet reaches a small-volume state. This charge collapse coincides with spontaneous lateral translation rather than jetting or breakup. A Rayleigh-normalized analysis, including a spherical-cap stress correction and measured contact-angle retention scale, shows that motion occurs only after evaporation drives the droplet into a high electro-pinning state. High-speed imaging and kinematic analysis support a picture in which the subsequent motion is governed by repeated contact-line depinning and re-pinning: the total distance traveled is strongly affected by dry-surface pinning, whereas the peak translational velocity serves as a more robust indicator of the discharge strength. These results identify a dry-substrate mode of evaporation-driven electrostatic relaxation, distinct from Coulomb fission on lubricated surfaces, in which substrate electrostatic passivity enables charge retention, droplet geometry selects the instability onset, and whole-droplet translation provides the charge-release pathway.
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All authors Riming Xu, Yanbo Li, Jiawen Zhang, Jin Wang, Yikai Li
Medical Physics · Cross-listed from cs.CV
Patient-Level Diagnosis of Acute Myeloid Leukemia via Deep Learning Analysis of Bone Marrow Smear
Yuqi Ma, Tianyi Wang, Weihua Meng et al. (+6 more)
Bone marrow smear review remains important for acute myeloid leukemia (AML) assessment, but manual single-
cell interpretation is labor-intensive and patient-level diagnosis requires aggregation of many cellular observations. We present a
cell-to-patient deep learning pipeline for AML-assisted diagnosis from bone marrow smear images. The study included 258 patients from six anonymized centers, including a main cohort of 169 patients from Centers 1-3 and an external validation cohort of 89 patients from Centers 4-6. A 16-category
cell annotation vocabulary was used to describe the global cellular composition, including granulocytic, monocytic, erythroid, lymphoid, eosinophilic, and other
cells. Rather than identifying strict AML blasts or leukemic blasts, the model targets an expert-defined composite category termed Composite Blast-like
Cells (CBLC), comprising N, N1, M, M1, R, R1, J, and J1 according to the project-wide morphological standard. A fixed YOLO-based
segmentation module detected
cells, predicted contours were matched to expert polygon annotations by contour IoU, and standardized single-
cell crops were generated. An EfficientNet-B0 classifier was trained through a two-stage GT-to-YOLO and YOLO-to-YOLO strategy with class-imbalance correction, center-border regularization, and morphology-assisted supervision.
Cell-level predictions were aggregated into patient-level CBLC ratios for AML-oriented diagnostic support. The pipeline achieved stable internal validation and maintained external generalization, with ensemble weighted F1-scores of 0.9076, 0.8696, and 0.9124 on Centers 4, 5, and 6, respectively.
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All authors Yuqi Ma, Tianyi Wang, Weihua Meng, Hongru Chen, Fajin Tao, Qunxian Lu, Lin An, Xiaodong Mo, Gen Yang
Optics
Length-dependent SWIR upconversion spectral response of noncritically phase-matched KTP crystals
Xiao-Hua Wang, Chang-Hao Min, Yin-Hai Li et al. (+2 more)
Noncritically phase-matched (NCPM) KTP
crystals support large-aperture bulk operation, avoid spatial walk-off, and relax angular-
alignment requirements, making them attractive for short-wave infrared upconversion detection. To guide
crystal selection for different detection requirements, we quantitatively characterize how
crystal length affects the coverage and profile of their external upconversion spectral responses. A calibrated Czerny–Turner monochromator is used to measure the responses of 0.5, 1.0, and 2.0 mm
crystals and compare them with theoretical
quantum-efficiency spectra calculated from the phase-matching model. With increasing
crystal length, the response evolves from a broad profile with weak peak separation to a more distinct double-peak structure, accompanied by reduced coverage bandwidth. A representative pump-power measurement further yields the system-level external
quantum-efficiency slope. These results clarify the trade-off between spectral coverage and wavelength selectivity for different
crystal lengths and can be used to choose the
crystal length for SWIR upconversion detection systems.
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All authors Xiao-Hua Wang, Chang-Hao Min, Yin-Hai Li, Zhi-Yuan Zhou, Bao-Sen Shi
Computational Physics
An adaptive framework for the axisymmetric pulsar magnetosphere using physics-informed Kolmogorov-Arnold networks
Spyros Rigas, Ioannis Contopoulos, Georgios Alexandridis et al. (+1 more)
The
pulsar magnetosphere has only recently been addressed using Physics-Informed Neural Networks (PINNs), by deploying a domain-decomposition approach and treating the separatrix and equatorial current sheet as infinitesimally thin discontinuities. However, this baseline requires extensive manual hyperparameter tuning, achieves limited final accuracy and demands several hours of training. We refine this framework by introducing domain-specific neural architectures based on Kolmogorov-Arnold networks, an automated adaptive training pipeline and a physics-based convergence criterion that eliminate the need for manual calibration. The proposed methodology delivers self-consistent axisymmetric magnetosphere solutions with mean squared errors of the PDE residuals at O(1e-6) in double precision - an improvement of two orders of magnitude over the baseline - while achieving convergence in under 20 minutes in single precision. Importantly, the method reliably resolves
stellar radii reduced by up to 80% compared to the baseline, overcoming the severe spatial scale disparities that also challenge traditional solvers. Furthermore, by varying the flux that opens to infinity, we provide a correction to the equation that connects it to the equatorial T-point's position. The complete framework is released as the open-source library PulsarX.
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All authors Spyros Rigas, Ioannis Contopoulos, Georgios Alexandridis, Antonios Nathanail
Plasma Physics
A Comprehensive Study on the Line Profiles and Stark Widths of Ionic Transitions from Laser Produced Aluminum Plasma
B R Geethika, Judhishtir Shamal, Renjtih Kumar et al. (+2 more)
We present a systematic spectroscopic investigation of
laser-produced aluminum
plasma to address inconsistencies in Stark broadening parameters and establish a self-consistent reference
datasets for electron density diagnostics. Optical line emissions of Al II and Al III in the visible wavelength range were recorded from
plasmas having different electron densities and temperatures, however, with the same experimental configuration, only by varying the background pressure, spatial positions, and delay time. The Stark width parameter of Al III lines, which shows consistency across different earlier studies, is used for standardizing the Al II transition from the highest energy level, which is abundant in the emission spectra. This reference spectrum is then used to estimate the Stark parameters of other Al II transitions to obtain a self-consistent database for Al II transitions. This approach significantly reduces the uncertainty in the estimated
plasma electron density using Stark parameters of multiple emission lines. We also report the spatial and temporal
evolution of
plasma density and Stark shift as well as asymmetry in spectral lines. This work addresses the uncertainty in Stark parameters of Al II transitions in the visible range through a unified approach in estimating these parameters simultaneously.
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All authors B R Geethika, Judhishtir Shamal, Renjtih Kumar, Hem Chandra Joshi, Jinto Thomas
Chemical Physics · Cross-listed from quant-ph
Equilibrating continuous-variable open quantum systems using stochastic classical trajectories in path-integral space
William H. D. Moore and Stuart C. Althorpe
Beyond the weak-coupling limit, open
quantum systems equilibrate to a highly entangled thermal state. For continuous-variable systems, this state can be written explicitly as an imaginary-time phase-space path integral, in which the positions are directly entangled with the bath, and the momenta are correlated with the positions through a phase term. Here, we ask to what extent this state can be reached by propagating
stochastic classical trajectories in path-integral phase space. Surprisingly, we find that the trajectories equilibrate to the exact
quantum equilibrium state, recovering the purely imaginary momentum-position correlation in the phase term. The trajectories are generated using a recently derived Matsubara generalized Langevin equation, which produces the imaginary correlations by evolving the
stochastic variables into the complex plane. This makes the dynamics numerically unstable, but we are nonetheless able to demonstrate the equilibration of a quartic oscillator coupled to a white-noise bath. These unexpected findings could lead to new approximate methodologies for simulating continuous-variable open
quantum systems.
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Fluid Dynamics
Far-field approximations for multi-timescale microswimmers near a boundary
Sara Drummond-Curtis, Mohit P. Dalwadi and Benjamin J. Walker
Hydrodynamic interactions with boundaries can significantly affect the trajectories of microscale swimmers. In simple swimmer models, a common assumption is that swimmer shape remains constant, essentially averaging over the rapid oscillations in geometry and associated fluid flows that often are the source of propulsion. Previous work in minimal force-dipole models has shown how the inclusion of time-dependent swimmer changes can lead to a fundamentally wider class of behaviours than for their classic (implicitly averaged) counterparts. However, since force dipole models correspond to the leading-order term in the far-field description of the swimmer-induced flow, they break down as the swimmer approaches a boundary and predictions can become qualitatively inaccurate. Here, we extend the minimal force-dipole model by incorporating higher order flow singularities, systematically accounting for rapid oscillations in shape and singularity strength through a multiscale analysis. We demonstrate that the inclusion of time-dependence into these higher order models significantly expands the reachable parameter space, in particular by increasing its dimensionality. In these extended dynamics, we observe three distinct behaviours: crashing, escaping and hovering. Notably, hovering states are absent from the dynamics predicted by the simplest models, but are observed in more complex models.
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Accelerator Physics
RF Power Transport for Accelerators
Eric Montesinos
This paper reviews the main types of
radio-frequency power transport systems which may be used in accelerators. It gives essentials on rectangular waveguides and coaxial lines. Basics of combining systems, splitting systems and transmission lines are discussed.
Atmospheric and Oceanic Physics · Cross-listed from cs.LG
PhysMetrics.Weather: An Evaluation Framework for Physical Consistency in ML Weather Models
Emma Kasteleyn, Timo Maier, Axel Lauer et al. (+3 more)
Machine learning weather prediction (MLWP) models have achieved impressive
forecasting performance at a small fraction of the computational costs required for traditional physics-based methods. However, they are primarily (1) data-driven and (2) evaluated using pixel-wide error metrics (e.g., RMSE), so there are no guarantees that their forecasts are consistent with known physical laws. We introduce PhysMetrics$.$Weather, an evaluation framework that assesses the physical realism of MLWP models across three types of metrics: conservation, spectral, and dynamical. By quantifying physical realism, this tool guides the development of physics-informed architectures and helps evaluate whether MLWP models are reliable for operational use. Our framework is available on Github at https://github.com/Emmakast/PhysMetrics.Weather.
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All authors Emma Kasteleyn, Timo Maier, Axel Lauer, Veronika Eyring, Pierre Gentine, Ana Lucic
Atomic Physics
Quantum study of ultracold atom-ion excitation exchange
Tibor Jónás, Romain Vexiau, Nadia Bouloufa-Maafa et al. (+3 more)
The
quantum dynamics of ultracold collisions between rubidium atoms and excited metastable strontium ions is treated in the laboratory frame, enlightening the importance of the coupling between internal angular momenta of the particles and their mutual rotation. The study reveals a subtle competition between electronic excitation exchange and fine structure quenching, with no charge exchange, which is found to be very sensitive to the details of ion-atom interactions. The rate constant for electronic excitation exchange is found in agreement with the experimental results of Ben-Shlomi et al. (Phys. Rev. A 102, 031301(R) (2020)), while the rate for fine structure quenching is predicted to strongly depend on the initial polarization of the reactants.
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All authors Tibor Jónás, Romain Vexiau, Nadia Bouloufa-Maafa, Eliane Luc-Koenig, Olivier Dulieu, Andrea Orbán