Applied Physics · Cross-listed from cond-mat.mtrl-sci
Tracking visible pulsed laser annealing of Hf$_{0.5}$Zr$_{0.5}$O$_2$ heterostructures with in situ transmission electron microscopy
Aida Amini, Shruti Verma, Katharina Kohlmann et al. (+4 more)
Laser annealing offers a promising route to back end of the line fabrication of ferroelectric thin film transistors based on hafnium-zirconium
oxide (HZO). Due to the wide band gap of this material, previous reports have studied the crystallization of HZO using ultraviolet or infrared light. In contrast, we monitor its crystallization in a Si$_3$N$_4$/TiN/Hf$_{0.5}$Zr$_{0.5}$O$_2$ thin film
heterostructure upon irradiation with visible nanosecond
laser pulses. This geometry mimics the structure of CMOS devices and harnesses the absorption of TiN in the visible regime to generate the heat necessary for the transformation. Through a series of local in situ measurements using a modified transmission electron microscope, we quantify the relationship between the HZO film thickness, critical
laser energy density and the ferroelectric HZO phase fraction, finding a sharp threshold behavior in the
laser pulse energy necessary to crystallize HZO. The optimal condition of irradiating an 8-nm HZO film with a single
laser pulse with an energy density of 177 mJ/cm$^2$ is found to produce 86% of the ferroelectric orthorhombic phase. Heat transfer dynamics within the
heterostructure during
laser annealing are revealed by finite element simulations, where the partial melting of the silicon nitride substrate is found to play an important role limiting the temperature to 1900 {\deg}C. This finding as well as the observed
laser pulse energy threshold behavior support a kinetic crystallization pathway involving the tetragonal phase. More generally, these findings show how
laser-driven phase engineering can lead to scalable design and enhanced performance of ferroelectric materials in advanced electronic applications.
Read the full abstract ▾
All authors Aida Amini, Shruti Verma, Katharina Kohlmann, Sebastian Obernberger, Jean-Christof Lamanque, Andreas Rüdiger, Kenneth R. Beyerlein
Plasma Physics
Theory of Relativistic Surface Plasmon Excitation on Smooth Surface by High-Intensity Laser
Bifeng Lei, Bin Qiao, Matt Zepf et al. (+2 more)
We present a classical theory of relativistic surface plasmon (RSP) excitation at a smooth
plasma-
vacuum interface driven by either a ponderomotive force or an electric field of an intense
laser pulse. Starting from Maxwell equations coupled to a cold-fluid
plasma response, we derive a general driven wave equation for the RSP and solve it analytically. We show that an infinite planar surface enforces conservation of the in-plane wavevector. A finite longitudinal interaction length or axial modulation supplies a finite kz spectrum, while cylindrical
curvature replaces one continuous transverse in-plane wavenumber by a discrete azimuthal mode index m. This partially relaxes the planar in-plane constraint, while axial phase matching remains controlled by the longitudinal spectrum of the drive. The excitation strength is controlled by the overlap between the drive and the surface eigenfield, which is determined by the surface geometry. This provides a general principle for controlling RSP excitation. We also show that relativistic effects can substantially modify the dielectric response and can be preliminarily verified by particle-in-
cell simulations. Within the local relativistic dielectric model, the overlap-normalised planar source saturates at large a0, and cylindrical
curvature partially alleviates this reduction before strong surface softening develops. The role of surface geometry is analysed. A cylindrical surface can sustain an on-axis accelerating field, enabling highly nonlinear wakefield generation for particle acceleration. In addition, the cylindrical geometry imposes a precise mode-selection rule that provides intrinsic control over RSP excitation. Axisymmetric ponderomotive drive selects fundamental mode m=0. A linearly polarised
laser field selects a superposition of m=+1 and m=-1 modes, and a circularly polarised
laser field selects a single helical mode.
Read the full abstract ▾
All authors Bifeng Lei, Bin Qiao, Matt Zepf, Guoxing Xia, Carsten Welsh
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Discovering physical mechanisms from experiment-simulation mismatches
Yue Li, Penghui Yang, Yushan Xiao et al. (+7 more)
Scientific discovery often begins where observation and prediction disagree. As computation and machine learning survey chemical space, experiment-simulation mismatches are exposed at scale, while tracing them to physical mechanisms remains expert-led. Here we present eXplainable DFT (XDFT), a self-evolving
agent that turns this process into an executable search. XDFT formalizes candidate mechanisms as executable hypotheses, adjudicates their consequences against experiment and distils trajectories into priors for later searches. This couples a solving loop from mismatch to mechanism with a learning loop through which solving changes the solver. Across 112 source-audited cases in which standard calculations predict a metal whereas experiments find a
semiconductor, XDFT resolved 105 with evidence-supported mechanisms within a single-GPU envelope. After 60 cases, the resolving mechanism ranked among the first three hypotheses for 80% of held-out cases, up from 7% under the initial expert prior. XDFT also returned evidence-graded mechanisms for seven expert-curated questions about physical mechanisms. These results establish experiment-simulation mismatches as tractable starting points for scientific
agents that discover physical mechanisms while learning how to find the next.
Read the full abstract ▾
All authors Yue Li, Penghui Yang, Yushan Xiao, Zhonghan Zhang, Jianguo Huang, Yuhao Lu, Cuntai Guan, Bo An, Bijun Tang, Zheng Liu
Fluid Dynamics
Compartment Modelling of Multiphase Reactors using Unsupervised Clustering
Michael Mitterlindner, Maximilian Graber, Regina Kratzer et al. (+2 more)
Detailed Computational Fluid Dynamics (CFD) simulations are too computationally expensive for the real-time control and design optimization of multiphase flow reactors. To address these limitations, we introduce CLARA, a software toolbox that automates the generation of Compartment Models (CM) via the unsupervised clustering of CFD data. Unlike previous studies, our toolbox enables the modelling of multiphase phenomena and interphase mass transfer within each compartment. CLARA employs unsupervised clustering
algorithms, graph reassignment, and optimization routines to ensure mass conservation and spatial connectivity across all compartments. Verification studies utilizing analytical
benchmarks and reactive multiphase CFD simulations demonstrate that the CMs produced by CLARA accurately reproduce reactor performance and spatial species distributions. The significantly reduced computational demand of CMs compared to full CFD models enables the optimal control of multiphase reactors and facilitates their rational design and optimization.
Read the full abstract ▾
All authors Michael Mitterlindner, Maximilian Graber, Regina Kratzer, Markus Reichhartinger, Stefan Radl
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Emergent surface resonance from charge density wave symmetry breaking in TiSe2
Turgut Yilmaz, Yi Sheng Ng, Muhammad Awais Fiaz et al. (+13 more)
Surface confined electronic states provide a fertile ground for discovering emergent phenomena that have no counterpart in the bulk, offering new routes to manipulate correlations,
symmetry breaking, and dimensionality at the atomic scale. Here, we show that charge density wave (CDW)
symmetry breaking can yield a surface states in 1T-TiSe2. Micro angle resolved photoemission spectroscopy resolves a sharp, two dimensional surface resonant state (SRS) that emerges within the CDW reconstructed low energy spectrum. The SRS exhibits notable temperature dependence and its spectral weight collapses around 160 K, while CDW transition temperature TCDW is commonly reported as 202 K. Slab DFT+U calculations reproduce a surface localized resonance when CDW folding brings valence and conduction states into near degeneracy, suggesting a correlation tuned, surface selective origin. These results point to a form of correlation-tuned surface resonance in a layered CDW compound and suggest a framework for engineering low dimensional
quantum states in van der Waals materials via
symmetry breaking and electronic structure tuning.
Read the full abstract ▾
All authors Turgut Yilmaz, Yi Sheng Ng, Muhammad Awais Fiaz, Anil Rajapitamahuni, Asish K. Kundu, Shawna M. Hollen, Polina M. Sheverdyaeva, Paolo Moras, Ivana Vobornik, Jun Fujii, Shinichiro Ideta, Kenya Shimada, Boris Sinkovic, Elio Vescovo, Hui-Qiong Wang, Jin-Cheng Zheng
Fluid Dynamics
Wave Vortices Around Oscillating Subwavelength Holes: Water-Wave Observation
Junyi Ye, Zheyi Li, Alexey Y. Nikitin et al. (+4 more)
We consider a two-dimensional wave system containing a subwavelength hole, such as an aperture in an interface supporting surface electromagnetic or acoustic waves, or an island in a fluid surface sustaining
gravity-capillary waves. Recent studies have revealed the emergence of pronounced wave
vortices around such structures, termed type-II
vortices, in contrast to conventional (type-I)
vortices associated with phase singularities and intensity nulls. A striking natural manifestation of type-II
vortices occurs in ocean tides around islands such as New Zealand, Madagascar, and Iceland, where the
tidal phase increases by $\pm 2\pi$ around the island. Although this phenomenon is usually associated with the Coriolis effect from the rotation of the Earth, here we demonstrate the controlled generation of type-II
vortices using a minimal and tunable setup: a dipole-oscillating subwavelength hole and a single incident plane wave. Using laboratory
gravity-capillary waves and an oscillating subwavelength `island', we directly measure the resulting phase structure, topological charge, and wave angular momentum. We show that the emergence and handedness of the
vortices can be precisely controlled via the relative phase between the dipolar source and the incident wave. Our results offer a simple and versatile mechanism for engineering subwavelength wave
vortices, with potential applications in a variety of two-dimensional wave systems.
Read the full abstract ▾
All authors Junyi Ye, Zheyi Li, Alexey Y. Nikitin, Franco Nori, Wenzhe Liu, Konstantin Y. Bliokh, Lei Shi
Optics · Cross-listed from eess.IV
Circular Phase Representation and Geometry-Aware Optimization for Ptychographic Image Reconstruction
Carson Yu Liu, Jun Cheng, Chien-Chun Chen et al. (+1 more)
Traditional iterative reconstruction methods are accurate but computationally expensive, limiting their use in high-throughput and real-time ptychography. Recent deep learning approaches improve speed, but often predict phase as a Euclidean scalar despite its $2\pi$ periodicity, which can introduce wrapping artifacts, discontinuities at $\pm\pi$, and a mismatch between the loss and the underlying signal geometry. We present a deep learning framework for ptychographic reconstruction that models phase on the unit circle using cosine and sine components. Phase error is optimized with a differentiable geodesic loss, which avoids branch-cut discontinuities and provides bounded gradients. The network further incorporates saturation-aware dual-gain input scaling, parallel encoder branches, and three decoders for amplitude, cosine, and sine prediction, together with a composite loss that promotes circular consistency and structural fidelity. Experiments on synthetic and experimental
datasets show consistent improvements in both amplitude and phase reconstruction over existing deep learning methods. Frequency-domain analysis further shows better preservation of mid- and high-frequency phase content. The proposed method also provides substantial speedup over iterative solvers while maintaining physically consistent reconstructions.
Read the full abstract ▾
All authors Carson Yu Liu, Jun Cheng, Chien-Chun Chen, Steve F. Shu
Medical Physics
Simulation of complex DNA damage enhancement and biological effect validation for Proton-CAT
Lang Dong, Dechao An, Junxiang Wu et al. (+10 more)
Proton therapy has been rapidly advancing due to its excellent conformal index, but its relatively low relative biological effect (RBE) has somewhat limited its therapeutic efficacy for certain tumors. To address this, we previously proposed a nitrogen-targeting
Proton-Carbon-Alpha-Therapy (
Proton-CAT) enhancement method. In this letter, we present combined multi-scale DNA damage simulations and in vitro
cell experiments, further investigating the mechanism of the
Proton-CAT. It has been show that $^{15}$N enrichment significantly enhances complex DNA damage induced by high linear energy transfer(LET) particles within tumor regions. Under 30% $^{15}$N conditions, $\alpha$ and $^{12}$C particle induced DSB++ increased by 175.19% and 52.94%, respectively. Furthermore, in vitro
cell experiments using $^{15}$N-glutamine ($^{15}$N-Glu) as the $^{15}$N carrier indicated that high concentrations of $^{15}$N-Glu did not bring about significant cytotoxicity. Following 2 Gy irradiation, the
cell viability in the 500 $\mu$g/mL $^{15}$N-Glu treated group exhibited a net reduction of about 15.41% compared to the control group.This indicates that the enhanced effect of
Proton-CAT primarily stems from increased complex DNA damage. This work provides a theoretical basis and multi-scale research framework for the development of the
Proton-CAT.
Read the full abstract ▾
All authors Lang Dong, Dechao An, Junxiang Wu, Tianle Wang, Zhao Sun, Jiajun Kang, Xianliang Wang, Lintao Li, Shun Lu, Tianli Qiu, Da Zhang, Zhencen He, Zhimin Hu
Applied Physics
Inverse Design of Cellular Composites for Targeted Nonlinear Mechanical Response via Multi-Fidelity Bayesian Optimisation
Hirak Kansara, Leo Guo and Wei Tan
The rise of machine learning and additive manufacturing has enabled the design of architected materials with tailored properties that surpass those of natural materials. Inverse design offers a data-efficient alternative to trial-and-error methods, yet most existing approaches depend on either large
datasets or scarce high-fidelity data from simulations and experiments. These requirements pose a particular challenge for architected materials with nonlinear mechanical responses, where capturing complex deformation modes requires expensive evaluations. To address this, a Multi-Fidelity
Bayesian Optimisation (MFBO) framework for the inverse design of cellular composites that directly targets their full nonlinear response is introduced. By integrating information from multiple fidelity sources and scalarising the response using a similarity score, the framework enables efficient exploration of the design space while reducing reliance on costly evaluations. As a proof of concept, the method is applied to spinodoid cellular composites using finite element models, validated with compression tests on short carbon-fibre reinforced PET-G composites. Four target responses were considered, with three multi-fidelity strategies benchmarked against a standard single-fidelity approach. Across all cases, MFBO achieved higher similarity scores and consistently recovered the targeted responses, outperforming the single-fidelity baseline under the same evaluation budget, while also successfully recovering all targeted responses. These results demonstrate the effectiveness of MFBO for inverse design of
stochastic architected materials, where high-quality data is scarce but lower-cost proxies exist. By efficiently navigating complex design spaces, MFBO enables the creation of cellular composites with precisely tailored nonlinear mechanical behaviour.
Read the full abstract ▾
Atomic Physics
Development of a compact cryogenic Penning trap with permanent magnets: An intermediate step toward the Shanghai Penning Trap
Tianhang Zhang, Jiawei Wang, Jialin Liu et al. (+11 more)
Penning traps, renowned for their unparalleled precision in determining fundamental properties such as mass and
magnetic moments, are cornerstone instruments in modern physics. Their applications span from
nuclear structure studies to stringent tests of
quantum electrodynamics and CPT invariance. Although Penning traps have been demonstrated for fundamental studies, often employing superconducting magnets, their high cost and operational complexity remain challenges. In this work, we report the development of a compact cryogenic Penning trap that utilizes a permanent magnet to provide a confining
magnetic field, offering a more economical and flexible alternative. We have successfully demonstrated all core functionalities of this system, including ion generation, transport, confinement, manipulation, and signal detection. This compact trap not only serves as a vital technical testbed for the development of the Shanghai Penning Trap, but also establishes a cryogenic Penning-trap experiment platform for ion trapping and cooling applications as well as envisaged spectroscopic studies applications.
Read the full abstract ▾
All authors Tianhang Zhang, Jiawei Wang, Jialin Liu, Jingtian Wei, Jiaxuan Ji, Jifei Wu, Zichen Su, Yiming Xie, Liangyu Huang, Ke Yao, Yang Shen, Yaming Zou, Baoren Wei, Bingsheng Tu
Chemical Physics
Effect of reaction temperature on nascent carbonaceous particles from toluene shock-tube pyrolysis: Insights from FTIR and Raman spectroscopy
Meysam K. Rezaeian, Can Shao, Jürgen Herzler et al. (+3 more)
The transition from gaseous precursors to nascent solid particles and their subsequent structural maturation were investigated in single-pulse shock-tube experiments using ex situ
Fourier-transform infrared (FTIR) and Raman spectroscopy of sampled products. A mixture of 2% toluene in argon was pyrolyzed at around 2.0 bar with temperature plateau times of 2.0 ms over the 1450-1800 K reaction temperature range. In situ
laser extinction measurements indicate the onset of particle formation at 1570 K. At this temperature, Raman spectra exhibit emerging D and G bands, and transmission electron microscopy (TEM) reveals the disappearance of poorly defined structures, identifying 1570 K as the phase-transition reaction temperature. Approaching this reaction temperature, Raman spectra show a rapid disappearance of sp hybridized triple carbon bonds. At 1670 K reaction temperature, a maximum in primary particle diameter and a decrease in structural disorder inferred from Raman spectroscopy are observed, defining the ordering threshold. Deconvolution of the FTIR spectra enables separation of in ring double carbon bond stretching vibrations from isolated and ring-conjugated side-chain double carbon bond modes. The in-ring double carbon band is used to normalize aliphatic and aromatic C-H vibrations. FTIR analysis reveals ring-edge structures associated with electron-localization sites, including bay regions, five-membered ring defects, and benzylic positions, indicating a radical-rich environment below the phase-transition temperature. Between the phase-transition and ordering-threshold temperatures, K-regions and armchair structures associated with electron delocalization and thermal stability increase. The emergence of these electronic and structural characteristics highlights the critical role of radicals in soot inception and early structural ordering.
Read the full abstract ▾
All authors Meysam K. Rezaeian, Can Shao, Jürgen Herzler, Mustapha Fikri, Greg J. Smallwood, Christof Schulz
Optics
Spectral window engineering for temporal leakage of synthetic gain waveform
Fuxin Guan, Nanyu Chen, Zemeng Lin et al. (+4 more)
Arbitrary waveform generation enables precise engineering of optical fields. As an alternative, the synthetic wave approach has been proposed to generate virtual-gain waveforms for loss compensation. However, the achievable synthetic gain is severely limited by the finite spectral bandwidth available in realistic experiments. This imposes a rectangular spectral window, causing abrupt spectral truncation and inducing severe temporal leakage in the time domain synthetic response. Here, we introduce spectral window engineering to fundamentally resolve this limitation. By employing smooth-edged spectral filters, such as the Hann and Blackman windows, temporal leakage is pushed deeply into the late-time regime, yielding a significantly extended effective lifetime and reduced residual damping. Using a coupled plasmonic resonator platform, we experimentally validate that our windowed approach suppresses residual damping by more than a factor of two compared to the standard rectangular baseline. Our findings establish a practical and robust spectral filtering strategy to realize high efficiency synthetic gain, with promising prospects for nanodetection and advanced spectroscopy.
Read the full abstract ▾
All authors Fuxin Guan, Nanyu Chen, Zemeng Lin, Wange Song, Shining Zhu, Tao Li, Shuang Zhang
Fluid Dynamics
A hybrid framework integrating physics-informed neural operators with conventional methods for turbulence
Sunan Zhao, Yunpeng Wang, Boyu Fan et al. (+3 more)
We develop large-eddy simulation nets (LESnets), a hybrid framework that integrates physics-informed neural operators with conventional computational methods for accurate and efficient simulation of wall-bounded
turbulence. LESnets incorporates the large-eddy simulation (LES) equations into the training of the factorized
Fourier neural operator (F-FNO), requiring no labeled training data and accommodating flexible time horizons during training. Boundary conditions are enforced as hard constraints and a wall model based on the law of the wall is incorporated to improve physical consistency and enable reliable coarse-grid simulations at high Reynolds numbers. Furthermore, the immersed boundary method (IBM) is embedded in the physics-informed loss function to accommodate complex geometries with boundaries that are not aligned with the computational grid. In addition, the subgrid-scale (SGS) model coefficient is optimized during training using a single flow snapshot. The framework is evaluated on turbulent channel flows at friction Reynolds numbers $Re_{\tau} \approx 180$, $590$, $1000$, and $2000$ and turbulent flows over periodic hills at Reynolds numbers $Re_h \approx 5600$ and $10595$. Numerical results show that LESnets achieves predictive accuracy and computational efficiency comparable to those of the implicit U-Net enhanced
Fourier neural operator (IUFNO) and F-FNO, while attaining accuracy comparable to that of conventional LES with greater computational efficiency. These results support the integration of physics-informed neural operators with established computational methods as a promising approach to accurate and efficient simulation of wall-bounded
turbulence.
Read the full abstract ▾
All authors Sunan Zhao, Yunpeng Wang, Boyu Fan, Huiyu Yang, Zhihong Guo, Jianchun Wang
Optics
Linking extended vector wave fields with momentum space topology
A. Neuhaus, P. Gessler, P. Dreher et al. (+10 more)
Topology describes properties of physical systems that remain constant under continuous deformations. For infinite vector waves, global topological invariants in position space are typically associated with periodic patterns. We demonstrate that even for aperiodic Helmholtz-decomposable wave fields, possessing only the wave's intrinsic periodicity, a topological invariant can be found in momentum space. This invariant, the linking number, represents a Berry phase. By utilizing electromagnetic and hydrodynamic surface waves, we confirm the robustness of the linking number against deformations, and experimentally observe discrete transitions between distinct topological sectors. The linking number captures the
topology of vector wave fields across both continuous and discrete momentum spaces. Our work introduces a unified topological framework for vector wave fields, enabling their classification via a global invariant.
Read the full abstract ▾
All authors A. Neuhaus, P. Gessler, P. Dreher, D. Janoschka, A. Rödl, M. Manten, Th. Bauer, M. Azhar, B. Frank, T. J. Davis, H. Giessen, K. Everschor-Sitte, F. Meyer zu Heringdorf
Geophysics · Cross-listed from astro-ph.SR
36Cl Concentrations from Polar Ice Cores Set New Constraints on the Carrington Event
F. Mekhaldi, C. I. Paleari, A. M. Smith et al. (+12 more)
The Carrington event of 1859 CE is considered as one of the largest geomagnetic storms of the observational era, and often used as a
benchmark for a worst-case scenario. Yet, there exists no robust evidence of an associated
solar energetic particle event of a significant magnitude, based on measurements of cosmogenic radionuclides 10Be and 14C from ice cores and tree rings, respectively. In this study, we present two 36Cl records from Greenland with 2-year and 4-year resolution from the EGRIP and NGRIP ice-core sites, together with semi-annual 10Be data from EGRIP, as well as annual 10Be and 36Cl concentrations from the Dome Summit Site, Law Dome, East Antarctica. We observe no significant 36Cl concentration increase around 1859 CE in the three records. This allows us to rule out an extreme
solar energetic particle event hitting Earth associated with the Carrington event in terms of fluence above 30 MeV. Based on these ice core 36Cl measurements, we can suggest two scenarios: i) a soft SEP event with a maximum fluence above 30 MeV up to three times larger than any Space Age event or, ii) the possibility that there was no Earth-bound SEP event.
Read the full abstract ▾
All authors F. Mekhaldi, C. I. Paleari, A. M. Smith, A. Aldahan, J. Beer, M. Christl, C. Vockenhuber, H. Hayakawa, M. Curran, T. Erhardt, C. Plummer, K. Simon, K. Wilcken, M. Zheng, R. Muscheler
Atmospheric and Oceanic Physics
Multiscale Decomposition Reveals Predictable Interannual Variability and Climate Trends in Antarctic Sea Ice Loss
Peter Yatsyshin, Karl Lapo, Jonathan Smith et al. (+4 more)
Antarctic sea ice has undergone unprecedented changes in recent years, raising questions about how this key geophysical system is responding to
climate change. Decades of slow expansion were replaced by a precipitous decline in 2014-2017, a subsequent apparent recovery, and a renewed collapse from 2022 to the present. We diagnosed sea ice concentration (SIC) from satellite observations with a hierarchical decomposition method based on Dynamic Mode Decomposition (DMD) that finds coherent spatiotemporal modes. We find that the 2014-2017 decline and apparent recovery are the result of interacting interannual modes and that a
climate change signal emerges in 2012, which becomes unambiguous by 2022 when it dominates over interannual variability. These rapid changes underscore the need for seasonal-to-annual forecasts of SIC. However, existing forecasts are subject to limited prediction horizons combined with high computational costs. Our predictive DMD model (IceDMD) is regularised to prioritize the stationary spatiotemporal modes found by the decomposition. The predictive model can forecast SIC anomalies in 2023-2024 up to two years in advance, outperforming all existing approaches with the additional benefits of physical interpretability and extremely cheap computational cost. Finally, this framework for regularising predictive DMD models can be generalized to a range of multi-scale systems.
Read the full abstract ▾
All authors Peter Yatsyshin, Karl Lapo, Jonathan Smith, Oliver Strickson, Louisa van Zeeland, J. Scott Hosking, J. Nathan Kutz
Applied Physics · Cross-listed from cs.LG
PiGGO: Physics-Guided Learnable Graph Kalman Filters for Virtual Sensing of Nonlinear Dynamic Structures under Uncertainty
Marcus Haywood-Alexander, Gregory Duthé and Eleni Chatzi
Digital twins provide a powerful paradigm for diagnostic and prognostic tasks in the monitoring and control of engineered systems; however, their deployment for complex structures remains challenged by model-form uncertainty, arising from unknown nonlinear dynamics, and by sparse sensing. These limitations hinder reliable online state estimation using either purely physics-based or purely data-driven approaches. This work introduces the Physics-Guided Graph Neural ODE (PiGGO) framework, a physics-informed, graph-based
Bayesian state estimation approach in which a learned graph neural ordinary differential equation (GNODE) serves as the continuous-time state-transition model within an extended Kalman filter. The graph representation explicitly defines the system state-space, while physics-guided inductive biases encode known structural relationships and constrain the learning of nonlinear dynamics. By integrating graph-native learned dynamics with recursive
Bayesian filtering, the proposed PiGGO framework enables online virtual sensing and uncertainty-aware state estimation for nonlinear systems with unknown model form, while maintaining generalisation across topologically similar structures. Numerical case studies demonstrate improved robustness to model uncertainty and measurement noise, outperforming both open-loop graph neural models and conventional filtering approaches in online prediction tasks.
Read the full abstract ▾
Optics
Low peak-power pulse compression in gas-filled Herriott cells in the 2 {\mu}m wavelength range
Johann Gabriel Meyer, Felix Ritzkowsky, Fatemehsadat Ghaffari et al. (+5 more)
At
laser wavelengths longer than the prominent 1 {\mu}m range of high-power ytterbium-doped
lasers, nonlinear phase shifts produced in nonlinear media for spectral broadening and subsequent pulse compression decrease drastically. Consequently, at the 2 {\mu}m wavelength range, the threshold of the applicable peak power for pulse compression in gas-filled multipass
cells increases. The common approach of choosing a Herriott multipass
cell configuration close to the concentric resonator does not necessarily lead to the highest total nonlinear phase shift, due to a restriction of the total number of reflections on the
cell mirrors of a given size. Therefore, an analytical approach is presented here to maximize the nonlinear phase shift for a given set of mirrors, considering lossless and dispersionless propagation. Furthermore, to achieve pulse compression with gas-filled multipass
cells for relatively low peak powers at wavelengths around 2 {\mu}m, we developed a high-pressure gas
cell and demonstrated experimentally pulse compression in the negative- and positive dispersion regimes, with achieved pulse durations of around 40 fs and 55 fs respectively.
Read the full abstract ▾
All authors Johann Gabriel Meyer, Felix Ritzkowsky, Fatemehsadat Ghaffari, Kevin Schwarz, Nazar Kovalenko, Christian Franke, Andrea Trabattoni, Oleg Pronin
Atomic Physics · Cross-listed from quant-ph
Addressable Rydberg excitation in arrays of single neutral atoms with a strongly focused flat-top beam
I. V. Iukhnovets, M. Y. Goloshchapov, A. P. Gordeev et al. (+4 more)
We present a method for generating a
laser beam with flat intensity and phase profiles in the focal region where the beam interacts with neutral $^{87}$Rb atoms in an array of optical dipole traps. We synthesize the beam as a superposition of Hermite–Gaussian or Laguerre–Gaussian modes. Then we give analytical expressions for the coefficients of such a superposition, an analysis of beam propagation along the $z$ axis in the vicinity of the waist, and several other related theoretical issues. Rydberg two-
qubit dynamics driven by this flat-top profile are analyzed through numerical solutions of the Lindblad master equation using our in-house Julia package. Beam preparation is demonstrated on a neutral-atom experimental platform. Measurements reveal a difference in the visibility of Rabi oscillations for addressed atoms compared with neighboring ones, confirming the effective spatial selectivity provided by the flat-top beam profile.
Read the full abstract ▾
All authors I. V. Iukhnovets, M. Y. Goloshchapov, A. P. Gordeev, O. V. Bychkova, I. B. Bobrov, G. I. Struchalin, S. S. Straupe
Chemical Physics · Cross-listed from cs.LG
Advancing multi-site emission control: A physics-informed transfer learning framework with mixture of experts for carbon-pollutant synergy
Yuxuan Ying, Hanqing Yang, Kaige Wang et al. (+6 more)
Municipal solid waste incineration (MSWI) converts urban waste to energy but simultaneously emits carbon dioxide, carbon monoxide and multiple regulated air pollutants whose formation is tightly coupled within a single combustion system. Controlling these emissions across a network of diverse facilities poses a fundamentally different challenge from optimising a single plant: data-driven models trained at one site capture local statistical patterns that rarely survive transfer to another, because they lack the physical constraints and regime-level structure needed to generalise. Here we show that shared emission-control relationships can be identified across heterogeneous MSWI plants when physical conservation laws, operating-regime heterogeneity and carbon-pollutant coupling are treated jointly. We develop a carbon-pollutant mixture-of-experts (CPMoE) model that routes process observations through regime-specific expert networks under conservation-based regularisation, and combine it with physics-informed transfer learning to adapt a reference model to new facilities. Across 13 plants, CPMoE predicts six major pollutants and a composite system-level risk index with source-domain R2 of 0.668-0.904 and 0.666-0.970, respectively; after transfer to 12 target plants these values remain 0.661-0.842 and 0.610-0.841. Expert-utilisation patterns show that adaptation proceeds through structured regime re-weighting rather than re-learning from scratch.
Embedding the transferred model in an offline digital twin and screening candidate operating adjustments against historical process records yields consistent risk-index reductions of 3.6-6.3% with simultaneous pollutant co-reductions in 94-100% of evaluated samples. These findings suggest a practical route toward transferable, system-level decision support for carbon-pollutant co-control in heterogeneous waste-to-energy networks.
Read the full abstract ▾
All authors Yuxuan Ying, Hanqing Yang, Kaige Wang, Yu Hu, Zhiming Zheng, Yunliang Jiang, Xiaoqing Lin, Xiaodong Li, Jun Chen
Chemical Physics
Physics-based modeling of cyclic and calendar aging of LIBs with Si-Gr composite anodes
Micha C. J. Philipp, Lukas Köbbing, Alexander Karger et al. (+3 more)
Higher energy density and longer lifetime are the requirements for next-generation lithium-ion batteries. A promising anode material is silicon, which offers high specific capacity, but its significant volume change during lithiation and delithiation enormously reduces battery lifetime. A physical understanding of the processes degrading the battery is key to mitigate this effect and advance in the field. We develop a physics-based model to describe degradation during battery cycling under various protocols and storage conditions, with varying check-up (CU) frequencies. The model can disentangle basic degradation mechanisms, such as the growth of the Solid-Electrolyte Interphase (SEI), from silicon mechanisms, such as particle cracking, SEI growth on cracks, and loss of active material (LAM). We investigate the impact of CUs on the observed storage degradation and the reason behind the increased degradation in batteries, including silicon in the anode. Additionally, we relate the observed degradation to operating conditions, enabling future optimization of battery use and design.
Read the full abstract ▾
All authors Micha C. J. Philipp, Lukas Köbbing, Alexander Karger, Andreas Jossen, Arnulf Latz, Birger Horstmann
Instrumentation and Detectors
A cm-wave quantum noise limited resonant superconducting parametric amplifier
V. Gilles, T. Sweetnam, B. Mohammadian et al. (+2 more)
Superconducting Parametric Amplifiers (SPAs) have seen great interest in recent years due to their high gain and
quantum limited noise performance. Among these amplifiers, resonant SPAs have been widely developed for experiments where ultra low-noise narrow-band amplification is of interest, such as the search for
Axion dark matter in particle physics and the detection of spectroscopic lines in astrophysics, while also finding applications in
quantum computing. This work presents an amplifier based on a Complementary Split Ring Resonator (CSRR), patterned on a NbTi coated sapphire substrate embedded within a waveguide, designed to work at a set of four narrow frequency bands throughout K band (18-27 GHz) using the kinetic inductance of the superconducting film. The S-parameters measured at 400 mK, using a sorption cooler, show the four resonances between 23.3 and 26.3 GHz at 1 GHz spacing, with a maximum transmission on resonance of -1 dB. Four-wave mixing has been observed with each resonance, and a maximum signal gain of 30 dB has been measured, corresponding to 29 dB of insertion gain. The noise performance of the amplifier has been measured, showing an added noise of 1.2 half quanta at 400 mK. These results are relevant to high-frequency
Axion dark matter experiments and help motivate the exploration of higher frequencies in
quantum technologies.
Read the full abstract ▾
All authors V. Gilles, T. Sweetnam, B. Mohammadian, M. A. McCulloch, L. Piccirillo
Computational Physics · Cross-listed from cs.GR
GMT: A Geometric Multigrid Transformer Solver for Microstructure Homogenization
Yu Xing, Yang Liu, Tianyang Xue et al. (+1 more)
Lattice metamaterials enable lightweight, multifunctional structures, yet homogenization-based evaluation of their effective properties remains computationally expensive. Neural surrogates offer speed but often lack the accuracy and stability required for engineering-grade simulations. We introduce GMT, a
Geometric Multigrid
Transformer – a neural solver with high numerical fidelity for fast and reliable
lattice homogenization. GMT achieves architectural
alignment with
Geometric Multigrid (GMG) by restructuring Point
Transformer V3 to operate across sparse GMG hierarchies, capturing long-range dependencies and cross-level interactions essential for multigrid convergence. To enforce physical consistency, GMT incorporates physics-aware positional encoding for strict enforcement of periodicity and predicts both the finest-level solution and multi-level residual corrections. These predictions deliver a spectrally-aligned initialization, enabling end-to-end training under physics-informed and solver-aware losses and requiring only a single GMG V-cycle refinement to reach convergence. This fusion of neural prediction and numerical rigor achieves relative residual errors of $10^{-5}$ with a $160\times$ speedup over state-of-the-art GPU-based solvers at equivalent accuracy – particularly at high resolutions (e.g. $512^3$), where traditional methods become most costly. We validate GMT across mechanical and thermal domains, demonstrate robust generalization to unseen geometries and non-periodic settings, and showcase scalability to high resolutions – enabling real-time design iteration, multi-scale simulations, high-throughput material discovery, and inverse design.
Read the full abstract ▾
All authors Yu Xing, Yang Liu, Tianyang Xue, Lin Lu
Optics
Microsecond-resolved electro-optic dual-comb spectroscopy in the 10~12.5 $\mu$m fingerprint region for radical kinetics
Pei-Ling Luo and I-Yun Chen
Dual-comb spectroscopy enables broadband, high-resolution measurements with microsecond temporal resolution, but extending this capability to the 10~12.5 $\mu$m molecular fingerprint region remains technically challenging, particularly for transient radical kinetics. Here, we demonstrate microsecond-resolved dual-comb spectroscopy in this spectral range using electro-optic combs and difference-frequency generation in an orientation-patterned gallium phosphide
crystal. Operation near a turning-point quasi-phase-matching condition at approximately 140 $^\circ$C reduces the wavelength sensitivity of the nonlinear conversion, enabling robust tuning of the idler comb over 83 cm$^{-1}$, corresponding to approximately 1.2 $\mu$m near 12 $\mu$m, by adjusting only the signal-comb center wavelength while keeping the pump wavelength and
crystal temperature fixed. As a demonstration, we perform high-resolution, microsecond-resolved spectroscopy of transient chlorine monoxide (ClO) near 12 $\mu$m. Time-resolved dual-comb spectra capture the temporal
evolution of ClO produced by the Cl + O$_3$ reaction with a temporal resolution of 1.5 $\mu$s, enabling quantitative determination of the ClO formation rate coefficient. These results establish this dual-comb platform as a promising tool for quantitative, microsecond-resolved studies of short-lived radicals, particularly atmospherically relevant halogen
oxides.
Read the full abstract ▾
Plasma Physics
Plasma dechirper and lens for electron beams from laser wakefield acceleration in a tailored density profile
T.L. Steyn, A. Panchal, O. Vasilovici et al. (+16 more)
Achieving high-quality electron beams from
laser wakefield accelerators critically relies on density tailoring to control electron dynamics during injection, acceleration, and extraction. We report on the experimental observation of electron beam acceleration and shaping, in transverse momentum and longitudinal phase space, controlled by
plasma density tailoring in a gas
cell. Electron beams with a FWHM charge of 40 pC at an energy of 190 MeV, 3.4% energy spread and an rms divergence of 0.46 mrad, corresponding to a transverse momentum spread of 0.2 $m_e c$, have been measured. These beams have a peak spectral brightness of up to 8 pC/MeV/mrad. Simulations using experimental parameters as input show that acceleration in the
plasma plateau leads to chirped electron beams which then undergo transverse momentum spread reduction in a
plasma down-ramp followed by dechirping in a 10~mm long
plasma tail, leading to the measured peaked spectra. %\textcolor{blue}{A control experiment with and without the LPT confirms these results.} The comparison of experimental results with and without long
plasma tail confirms this analysis.
Read the full abstract ▾
All authors T.L. Steyn, A. Panchal, O. Vasilovici, F.M. Herrmann, S. Schöbel, P. Ufer, O. Khomyshyn, Y.-Y. Chang, I. Moulanier, M. Masckala, M. Samir, C. Ballage, M. LaBerge, P. Désesquelles, F. Massimo, S. Dobosz Dufrénoy, U. Schramm, A. Irman, B. Cros
Fluid Dynamics
A Provably Robust Multi-Jet Framework applied to Active Flow Control of an Airfoil in Weakly Compressible Flow
Rohan Kaushik, Anna Schwarz and Andrea Beck
Reinforcement learning has by now become well established in finding excellent flow control strategies for a variety of scenarios. Existing literature has focused on using a simple two-jet solution (and variants there-of) or a straightforward mean-centered multi-jet setup. This mean-centering approach is however non-injective in nature, such that distinct action predictions by the actor network can lead to the same implemented jet-intensities. Thus, the potential of true multi-jet setups still remains unexplored. To this end, in this study we first theoretically analyze multi-jet setups, highlighting the aforementioned pitfall and offer a viable alternative. We also derive upper-bounds on the running costs of these setups, and find the proposed approach to have a jet-count-independent maximum running cost (compared to a near-linear scaling for the traditional setup). The mean-centered and proposed multi-jet setups are applied to a variety of flow-configurations, to test performance and learning capabilities. The new formulation proves effective in learning more complex flow-control strategies, coordinating the jets in a sophisticated manner so as to produce favorable outcomes at minimal actuation cost. For the cylinder-in-channel case, this results in drag and total-force suppression to beyond an idealized symmetric case, whereas for the airfoil the separation region is minimized and significant improvements in aerodynamic efficiency are observed (from 53% up to 73% depending on jet configuration). Additionally, we also incorporate some best practices from traditional RL literature to show fast, reproducible and reliable learning, thereby bringing down the upfront training costs. This study thus provides a robust and mathematically grounded approach to multi-jet design and closes a hitherto overlooked theoretical gap.
Read the full abstract ▾
Fluid Dynamics
A conservative low-order model for Boussinesq baroclinic fronts
Nadav Yovel and Eyal Heifetz
The internal dynamics of baroclinic fronts are governed by a fundamental interplay: turbulent eddies systematically act to disrupt thermal wind balance, with baroclinic eddies flattening isopycnals and barotropic momentum fluxes intensifying the primary jet, while the ageostrophic overturning circulation acts to restore it. In quasi-balanced models, this restorative adjustment is assumed instantaneous, locking the flow onto a balanced
manifold. To conceptually track this mechanism when the adjustment takes a finite time, we construct a low-order model that spans from $\mathcal{O}(1)$ Rossby numbers down to the quasi-balanced limit. Formulated from the continuous Boussinesq equations under a $Ro^2 Ri \sim 1$ scaling, which constrains the horizontal length scale to the Rossby deformation radius, the derivation yields a closed, nonlinear five-dimensional ODE system. The degrees of freedom consist of the domain-averaged along-front vertical shear, the cross-frontal overturning vorticity, the horizontal and vertical buoyancy gradients, and the total eddy energy. We identify two constants of motion that constrain the
evolution of the mean flow: the total energy (kinetic energy of the along- and cross-frontal flows, mean potential energy, and eddy energy) and the magnitude of the domain-averaged cross-frontal density gradient. Notably, while the system is energetically conservative, the parameterized turbulent closure renders the dynamics strictly non-
Hamiltonian. Bounded by these invariants, the adiabatic adjustment of the front physically reduces to a continuous rotation of the density gradient's slope. By explicitly resolving the inertial lag of the secondary circulation, this framework isolates the individual mechanisms governing frontal adjustment and tracks their continuous dynamic interplay.
Read the full abstract ▾
Classical Physics · Cross-listed from cond-mat.soft
Linear poroelastic response of thin permeable gel films
Caroline Kopecz-Muller, Joshua D Mcgraw and Thomas Salez
When a hydrophilic and deformable porous material is immersed in a bath, it may absorb the solvent and expand by several times its volume, thus forming a highly soft and porous hydrogel. A stress applied on the soft hydrogel surface deforms it and forces the absorbed solvent to move by flowing through the network of pores. This coupled phenomenon sets the framework of poroelasticity. Moreover, polymeric gels are often used in ultra-thin coatings to tune surface properties. Together with the characteristic poroelastic coupling, this thinness challenges the modelling of their response. In this article, we derive the point-force mechanical response of a thin, permeable and poroelastic layer bounded to a rigid substrate. We show that the gel surface is only deformed around the indentation point, within a radius on the order of the layer thickness. The obtained Green's function can be directly used to predict the space- and time-dependent surface deformation of the gel. Our findings are relevant for a broad range of applications, such as indentation experiments on swollen gels, thin membranes or soft and living systems, as well as lubrication problems involving a soft and porous wall, for instance in microfluidics.
Read the full abstract ▾
Fluid Dynamics
A Hybrid Gas-Kinetic Scheme and Discrete Velocity Method for Continuum and Rarefied Flows
Hangkong Wu, Yuze Zhu, Yajun Zhu et al. (+1 more)
The gas-kinetic scheme (GKS) provides high computational efficiency and accuracy for continuum flow simulations but is unable to reliably capture rarefaction effects. In contrast, although the discrete velocity method (DVM) is better suited for rarefied flows, it exhibits reduced accuracy and slow convergence when applied to continuum regimes. To overcome these limitations, this work proposes a hybrid GKS-DVM method that integrates the strengths of both approaches. The hybrid approach balances the
equilibrium distribution function in GKS with the upwind-reconstructed non-
equilibrium distribution function in DVM through a numerical collision time. This balancing strategy ensures to recover Navier-Stokes solutions in the continuum limit (asymptotic preserving), while naturally capturing free molecular flows in the rarefied limit. Moreover, the introduction of a numerical collision time significantly enhances robustness in shock capturing for continuum flow applications. To further reduce computational cost of the hybrid approach, several adaptive strategies based on the local Knudsen number and Mach number have been proposed. The effectiveness and accuracy of the proposed hybrid method are systematically assessed through four representative test cases: a flat-plate boundary layer, a lid-driven cavity flow, shock structures, and flow past a semi-cylinder. The first case is subjected to continuum conditions, while the latter two span a broad range of Knudsen numbers. The results demonstrate that the proposed method achieves high solution accuracy and computational efficiency across both continuum and rarefied flow regimes.
Read the full abstract ▾
All authors Hangkong Wu, Yuze Zhu, Yajun Zhu, Kun Xu
Optics
Geometric-Configuration Modulation: A Novel Free-Space Optical Communication Paradigm for $D/r_{0}\sim 5$ Turbulence Resistance
Yu-Ming Bai, Ming-Han Ding, Yu-Xuan Liu et al. (+1 more)
We propose
Geometric-Configuration Modulation (GM), a novel AO-free FSO paradigm utilizing multi-source
geometric configuration encoding and active correlative decoding. GM demonstrates exceptional resistance to strong atmospheric
turbulence ($D/r_{0}\sim 5$) over a 1.2 m link in preliminary experiments.
Read the full abstract ▾
All authors Yu-Ming Bai, Ming-Han Ding, Yu-Xuan Liu, Jun-Lin Li