Applied Physics · Cross-listed from cond-mat.mes-hall
Induced nonlinear phase shift of forward volume spin waves in magnetic films and one-dimensional magnonic crystals
Alexey B. Ustinov, Roman V. Haponchyk, Anton P. Burovikhin et al. (+2 more)
A differential phase shift of a low-power
spin wave (SW) induced by a high-power pumping wave co-propagating at different frequencies in perpendicularly magnetized
magnetic films has been studied. We find that this effect for forward volume SWs propagating in yttrium iron garnet (YIG) films is stronger than that for surface SWs propagating in tangentially magnetized films. The results show that the induced nonlinear phase shift up to 180{\deg} takes place for pumping wave power of a few milliwatts. The phenomenon paves the way for fast and energy-efficient control of one-dimensional
magnon transport.
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All authors Alexey B. Ustinov, Roman V. Haponchyk, Anton P. Burovikhin, Mitsuteru Inoue, Taichi Goto
Instrumentation and Detectors
The relative interfacial thermal contraction as a possible origin of the low-energy excess in cryogenic calorimeters
Vanessa Zema and Pasquale Pavone
Low threshold cryogenic calorimeters are a key technology for the advancement of rare-event searches. However, since a few years their sensitivity reach is challenged by the presence of a rising spectrum at low energies named low-energy excess (LEE), ascribed to an unknown background. In this work, we describe the LEE as absorber events induced by the relative thermal-contraction coefficient mismatch between the absorber and the SiO$_2$ amorphous layer underneath the transition-edge sensors (TESs), present for example in the case of CRESST detectors. The relative contraction in processes with temperature changes, such as during sensor fabrication and cooldown from room temperature to the temperature of operation, can induce surface dislocation nucleation. Other interfaced materials with thermal-expansion mismatch can also generate dislocations during temperature-variation processes. We formulate a simple elastic model to bridge this solid-state effect and the LEE observations. Double-TES modules have been designed to provide surface background rejection. We highlight that the presence of the LEE in the coincident event band of double-TES modules does not exclude the explanation given in this work. Exemplary, we discuss the role of the thermal boundary resistance between absorber and sensor as explanation for the presence of the LEE in the coincident-event band. We propose detector designs to test these hypotheses and mitigate the LEE.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts
Fanny Lehmann, Firat Ozdemir, Yun Cheng et al. (+4 more)
While AI weather models excel at short-to-medium range forecasts (up to 15 days), they frequently suffer from ill-defined "instabilities" when rolled out over longer horizons. This work addresses the lack of a formal taxonomy by categorizing these failures into three distinct regimes: blow-up, drift, and loss of seasonality, through year-long rollouts of nine state-of-the-art AI weather models. Our analysis reveals that stability hinges on the treatment of small spatio-temporal scales: unstable models amplify high-frequency energy, while stable models act as denoisers when noise is added to their inputs. Far from reducing these models to mere
stochastic parrots, our findings highlight that stable models generate unique weather trajectories, conditioned on the initial state. We verify our findings through ablation studies on architectural design choices, conducted using state-of-the-art
Vision Transformer (ViT) AI weather model architectures.
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All authors Fanny Lehmann, Firat Ozdemir, Yun Cheng, Torsten Hoefler, Sebastian Schemm, Benedikt Soja, Siddhartha Mishra
Applied Physics
More than just light management – The multiple advantages of nano- and micro-textures in perovskite solar cells
Guillermo Martínez-Denegri and Christiane Becker
Perovskite-based
solar cells have undergone rapid improvements over the last decade enabling highest power conversion efficiencies of single-junction and multi-junction devices. The implementation of nano- or micro-textures has played a major role in this development due to their ability to minimize reflection losses, maximize light trapping, and hence increase light harvesting in the active layer. In the slipstream of these advances, it has become apparent that nano- and micro-textures can also have many other collateral benefits beyond light management. In this article, very recently reported texture-related benefits for perovskite-based
solar cells different from light management are reviewed. These are namely (1) improved film wetting from perovskite-solution, (2) enhanced perovskite crystallinity in terms of grain size,
crystal orientation and phase homogeneity, (3) enhanced carrier extraction leading to higher open-
circuit voltages, and potentially (4) increased mechanical stability upon bending in flexible devices and reduced residual stress. This survey helps to understand textures as a holistic concept to further improve perovskite-based
solar cells, photodetectors and light emitting diodes.
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Medical Physics · Cross-listed from cs.CE
A Lumped-Element Electrical Model of the Human Head for Brain-Oriented Applications
Angelo Faccia, Ermanno Citraro and Francesco P. Andriulli
In this work, we present a compact surrogate
circuit for electro-quasi-static (EQS) head modeling. A three-shell geometry (
brain, skull, scalp) is considered, and each layer is modeled through radial and tangential pathways, implemented as RC branches. Frequency-dependent tissue conductivity and permittivity are mapped into dispersive resistive and capacitive elements. The model is validated against a semi-analytical spherical-harmonics reference solution over multiple geometrical configurations and operating frequencies, demonstrating good agreement. Neglecting dispersion and capacitive pathways can lead to an overestimation of scalp potentials over the considered frequency range, highlighting the need for dispersive RC
circuit modeling.
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Chemical Physics · Cross-listed from quant-ph
Tunneling phase diagram: A machine-learning framework for multidimensional kinetic isotope effects
Xinrui Yang and Zhigang Wang
The kinetic isotope effect (KIE) is the conventional probe for
quantum tunneling, yet its composite nature conflates tunneling with zero-point energy and classical kinetics. Here, we introduce the tunneling phase diagram, a machine-learning framework that decouples true tunneling strength by decoding the nonlinear relationship between KIE and the tunneling factor (ąppa}). With exceptional fidelity (R^2 > 0.98, RMSE = 0.21), this framework reveals an anomalous high KIE-low ąppa} spanning 300-600 K, thereby defining a paradigm for the quantitative assessment of
quantum tunneling.
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Optics · Cross-listed from cs.NE
Deep Binarized Photonic Reservoir Computing for Ultrafast Multimedia Signal Processing
Muhammad Waqar Iqbal, Mohamad Alassir, Nicolas Marsal et al. (+1 more)
We present a deep photonic neural network architecture based on ultrafast binary optical modulation from a digital micro-mirror device (DMD), optical scattering in random medium, high-speed photodetection with a CMOS sensor, and time-multiplexed deep layer structure. Operating at Gigabit-per-second (Gb/s) processing rates, our system based on the reservoir computing (RC) framework achieves state-of-the-art performance across various multimedia tasks, including
video, image and
speech recognition. We show that the careful optimization of key physical intra- and inter-layer hyper-parameters can significantly enhance the deep photonic RC system ability to extract relevant temporal and spatial features via balancing
memory retention and dynamical response of individual layers. This approach paves the way for highly scalable hierarchical photonic reservoir computing systems for high-throughput real-time multimedia signal processing.
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All authors Muhammad Waqar Iqbal, Mohamad Alassir, Nicolas Marsal, Damien Rontani
Fluid Dynamics
The Role of Interfacial Tension in Direct Numerical Simulations of Drop-Film Interaction for Immiscible Fluids
Rishi Dhar, David Gösele, Paul Saumet et al. (+2 more)
Many experimental studies have reported variations in interfacial tension. Isolating all the
geometric and fluid material parameters and varying the interfacial tension can be useful to check their influence. Numerical investigations using Free Surface 3D (FS3D), have been conducted to compare varying values of interfacial tension and evaluate the sensitivity. A grid independence study compared the compound crown height of a splash to determine the required resolution for validation. A qualitative validation showed FS3D could correctly capture the impact morphology while varying the viscosity ratio of the drop and film
liquid when compared to the experimental results. A quantitative validation for a water drop impacting onto an oil film shows a good match for the crown heights of the numerical and experimental data. The same setup was then extended to study the variation of interfacial tension, where the deviation of the overall compound crown height and spreading diameter of the internal crowns was compared. Results revealed minor changes in the compound crown height and spreading diameter of the drop
liquid, but the internal crown composition showed significant differences. In order to run FS3D efficiently on the new supercomputer Hunter, which has a new APU architecture-based system, extensive work had to be done. To adapt to the new hardware architecture, large parts of FS3D have been ported to utilise the AMD Instinct MI300A accelerated processing units (APUs) at HLRS using OpenMP. Implementation of Umpire
memory pools improved performance for larger workloads per APU. The GPU-accelerated code achieves a 4 times speedup compared to CPU-only execution on the same hardware. Strong and weak scaling tests have been conducted, showing good strong scaling for up to 4 APUs, and linear weak scaling for up to 512 APUs, resulting in a total of 4096**3
cells for the first time.
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All authors Rishi Dhar, David Gösele, Paul Saumet, Bernhard Weigand, Kathrin Schulte
Fluid Dynamics
Two-way coupling of gravity waves and wind farm wakes: a reduced-order boundary-layer model
Hossein A. Kafiabad and Majid Bastankhah
This paper develops a reduced-order numerical framework for modelling the two-way coupling between
gravity waves and turbulent wakes in large-scale wind farms. Starting with the non-hydrostatic Boussinesq equations and introducing simplifications appropriate to the boundary layer and the overlying stratified free atmosphere yield separate governing equations for the two regions. These are coupled through a dynamic boundary condition at the capping inversion, which directly captures the feedback of
gravity waves on the boundary-layer flow. A mixed pseudo-spectral finite-difference discretisation yields a computationally efficient model while retaining vertical boundary-layer structure. For the semi-infinite wind farm considered here, a complete solution is obtained in a matter of seconds on a standard laptop. Comparisons with large-eddy simulations (LES) confirm the model successfully reproduces both internal wind-farm flow and large-scale
gravity-wave effects. It captures the upstream blockage induced by adverse pressure gradients, as well as the accelerated wake recovery within and downwind of the farm, driven by favourable pressure gradients.
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Plasma Physics
Propagation of waves in weakly ionized two-fluid plasmas. II. Nonlinear Alfvénic waves
David Martínez-Gómez
Weakly ionized
plasmas can be found in the lower layers of the
solar and
stellar atmospheres and in structures such as prominences and spicules. A variety of density perturbations and bulk flows detected in these environments have been explained as the result of the ponderomotive force generated by nonlinear Alfvénic waves. In addition, the dissipation of the energy carried by these waves leads to heating of the
plasma. Here, we use a two-fluid model to study the combined influence of
Hall's current and elastic collisions between ions and neutrals on the propagation of linearly and circularly polarized transverse waves in weakly ionized
plasmas. We derive analytical expressions for the damping and heating rates, showing their dependence on the strength of the collisional coupling and on the polarization state. We also perform numerical simulations to investigate the nonlinear generation of density perturbations and bulk flows related to the ponderomotive force and the energy dissipation by the ion-neutral interaction. We find that the nonlinear perturbations associated with the circularly polarized eigenmodes do not show the oscillatory motions typically caused by linearly polarized eigenmodes, but they retain the non-oscillatory bulk flows. We also briefly discuss how in weak coupling conditions the nonlinear dynamics of the neutral fluid is mainly driven by the wave energy dissipation while the ponderomotive force only directly acts on the charged fluid, resulting in different amplitudes of the longitudinal motions and the perturbations of density and temperature.
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Optics
Observation of Electrically Tunable Chirality Inversion in a Slow-Light Waveguide
Xuchao Chen, Savvas Germanis, Nicholas J. Martin et al. (+8 more)
We identify
chiral inversion points in slow-light, glide-plane-symmetric, photonic-
crystal waveguides, defined as fixed locations where the local optical chirality changes sign over a narrow wavelength range. We experimentally access this behaviour using a waveguide-embedded InAs/InGaAs
quantum dot. The slow-light spectral region is determined from time-integrated and time-resolved photoluminescence, and the dot
exciton is electrically tuned across the slow-light bandwidth via the
quantum-confined Stark effect. As the emission wavelength is swept through the slow-light region, the directional emission contrast shows a strong wavelength dependence and a sign reversal, consistent with the identified
chiral inversion point. Numerical simulations attribute the switching primarily to the pronounced spectral variation of the local optical chirality for emitters displaced from the waveguide center. These results demonstrate on-demand electrical switching of
chiral light-matter coupling in nanophotonic waveguides and enable tunable
chiral interfaces for integrated
quantum photonic devices.
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All authors Xuchao Chen, Savvas Germanis, Nicholas J. Martin, Hamidreza Siampour, René Dost, Dominic J. Hallett, Ian Farrer, Akshay Kumar Verma, Maurice S. Skolnick, Luke R. Wilson, A. Mark Fox
Accelerator Physics
Advanced Externally Seeded FEL Schemes for High-Repetition-Rate Operation at SHINE
Hanxiang Yang, Nanshun Huang, Zheng Qi et al. (+3 more)
Externally seeded free-electron
lasers (FELs) are promising approaches for generating fully coherent soft-X-ray radiation. Their extension to shorter wavelengths and MHz-level repetition rates is, however, constrained by the limited availability of high-repetition-rate seed
lasers with sufficient energy modulation. Recent self-amplification and direct-amplification experiments at the Shanghai Soft X-ray FEL facility have significantly relaxed the peak-power requirement for high-gain harmonic generation (HGHG) and opened a practical path toward echo-enabled harmonic generation (EEHG). Using the SHINE bypass line, three compatible high-repetition-rate seeded-FEL configurations are explored: self-modulation cascaded HGHG, self-modulation EEHG, and direct-amplification-driven EEHG. Numerical simulations indicate that these schemes can provide flexible routes toward MHz-level operation with harmonic generation beyond the 30th order. A common modulator-chicane layout is proposed to preserve compatibility among the candidate modes and to support future optimization and experimental implementation at SHINE.
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All authors Hanxiang Yang, Nanshun Huang, Zheng Qi, Tao Liu, Haixiao Deng, Bo Liu
Physics and Society
Spatial equity and decentralization trade-offs in deep decarbonization of the European power system
Kristoffer Hedegaard Aden and Alexander Kies
Standard EU energy system modelling approaches optimize for least-cost, leading to highly centralized systems, in conflict with political feasibility and physical security concerns. This paper incorporates decentralisation as a constraint in a European energy system model using a novel, linear load-weighted renewable capacity constraint, the K-parameter, which scales with total system renewable capacity to avoid interference with decarbonisation targets. The model is a 37-node electricity-only brownfield system based on the PyPSA-EUR framework, with projected 2050 loads and technology costs. A total of 105 optimized scenarios are analyzed at 14 levels of decarbonization and 8 levels of decentralization. Full decarbonization leads to an 80% cost increase due to, among other factors, a 78% increase in energy generation capacity. Without decentralisation constraints, system equity initially improves but collapses at high decarbonisation levels due to concentration in regions with optimal renewable resources. Moderate decentralization of K=7 achieves 76% of the equity benefits at only a 9% cost increase compared to K=1. This indicates that moderate decentralization can be a viable strategy to balance societal preferences and cost-efficiency in the European energy transition.
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Optics
Nanoscopic Multiplexing Optical Data Storage via Chip Fabrication
Junyu Guan, Quanshen Shen, Bowen Tong et al. (+8 more)
The accelerating growth of global data demands storage technologies combining high capacity, long lifetime and low energy consumption. Optical storage is attractive for archival applications, but conventional optical writing is constrained by diffraction-limited resolution and scalability, while thermal accumulation limits high-speed writing. Here we shift optical data writing from a serial optical process to a fabrication-defined process, in which lithographic masks govern where material modification occurs. Using patterned resist masks and ion implantation, we create fluorescent information voxels with nanoscale control over millimeter-scale areas. The platform supports multilevel and multidimensional encoding by independently encoding information in fluorescence intensity and wavelength. A machine-learning-assisted super-resolution reconstruction protocol is developed to recover information beyond conventional optical resolution for information readout. Overall, the framework reaches an areal storage capacity of 1.1 Tbit within the area of a standard 120-mm optical disc, approximately fivefold that of a conventional single-layer Blu-ray disc. This architecture establishes a micro/nanofabrication-compatible route to scalable optical
memory and opens a pathway to wafer-scale archival storage.
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All authors Junyu Guan, Quanshen Shen, Bowen Tong, Hanzhi Wang, Zeyu Gao, Hanyu Zhang, Jingyang Zhou, Zihua Chai, Dong Liu, Ya Wang, Kangwei Xia
Medical Physics · Cross-listed from cs.CE
A Lumped RC Equivalent Circuit of Head Tissues for Dispersive Neuro-Electromagnetic Modeling
Angelo Faccia, Ermanno Citraro and Francesco P. Andriulli
Accurate modeling of electric potential and current distribution in head tissues is crucial for the design and evaluation of neuro-sensing and neuro-stimulation systems operating in the sub-megahertz frequency range. Numerical methods are widely employed in electromagnetic simulations, however their computational cost can limit their applicability to rapid prototyping, real-time simulations, and
circuit-level integration. In this work, we introduce a lumped RC equivalent
circuit model that reproduces the electrical behavior of a canonical three-layer spherical head geometry over a frequency range up to 50 kHz. The model accounts for frequency-dependent tissue conductivity and permittivity to capture dispersive effects, employing complex conductivity in the electro-quasi-static (EQS) regime. The
circuit topology uses a minimal set of impedance elements in order to represent the essential mechanisms of electric signal propagation. Validation was performed using a dipolar
brain source configuration for scalp voltage peak estimation, showing close agreement with semi-analytical solutions across different skull thicknesses and dipole eccentricities. In addition, the impact of tissue dispersion and capacitive branches on the model predictions was quantitatively assessed, showing their contribution to the overall fidelity of the proposed approach.
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Optics
Four-wave mixing and secondary radiations generated by nonharmonic two-color filaments in air: Influence of the Kerr and plasma nonlinearities
V. Tamulienė, P. David, V. Vaičaitis et al. (+4 more)
Four-wave mixing (FWM) is an efficient source of light waves emitted at various frequencies, usually associated with third-order optical nonlinearities. Whereas
attention has mostly been paid in the past to the generation of Stokes (e.g., visible) modes by mixing two nonharmonic frequencies in degenerate FWM, the present work aims to analyze the weaker components, i.e., the anti-Stokes (resp. mid-IR) radiation and cascaded satellites, and characterize their conversion efficiency and tunability. Here we report the production of tunable mid-infrared radiation around 3.3 $\mu$m delivered by two-color femtosecond filaments in air combining $\sim 800$ nm fundamental and $\sim 1.3$ $\mu$m seed waves. Although the Kerr response of air plays a key role in creating both visible and mid-IR radiations, we show that
plasma nonlinearities also contribute by broadening and mixing the pump frequencies. Two experimental setups are exploited to focus, separately, on the production of FWM modes and cascaded satellites - called secondary radiations. A first filamentation setup employing different focal lengths for the two colors displays an ionization-induced broadening of the mid-IR radiation during the
plasma stage. A second setup focusing the two pump components over equal propagation distances allows us to unveil the secondary radiations emerging at lower intensity levels when
plasma occurs. We examine which player, among the
plasma- or Kerr-induced FWM, is the most active in the conversion process. Numerical simulations based on a local-current model and a unidirectional solver highlight the role of the Kerr stage in amplifying the FWM radiations prior to the development of the weaker satellites in
plasma regime. Their results, agreeing well with the experimental data, demonstrate that a broad visible emission is needed to trigger secondary radiations.
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All authors V. Tamulienė, P. David, V. Vaičaitis, M. Rebarz, S. J. Espinoza, F. Catoire, L. Bergé
Atmospheric and Oceanic Physics
Evaluating Skill and Stability of ArchesWeather and ArchesWeatherGen under Multi-Decadal Climate Simulations
Renu Singh, Robert Brunstein, Antonia Jost et al. (+5 more)
We evaluate the
climate simulation capabilities of ArchesWeather and ArchesWeatherGen, two machine learning models originally trained for weather
forecasting and evaluated up to a 10-day lead time. ArchesWeather is a deterministic model, while ArchesWeatherGen is a probabilistic flow-matching model leveraging ArchesWeather's forecasts, enabling ensemble-based uncertainty quantification. In this work, we adapt these models to act as forced atmospheric models by using additional conditioning on the monthly mean sea surface temperature (SST) and sea ice cover (SIC) as boundary conditions. In particular, we follow the AI Model Intercomparison Project (AIMIP) Phase 1 protocol, which, analogous to the Atmospheric Model Intercomparison Project (AMIP), proposes a standardized experimental setup to evaluate the
climate skill of ML-based forced atmospheric models. We present a comprehensive evaluation of both models under these conditions, including comparison against numerical
climate models, ablation studies that examine key design choices in the extension, and an analysis of forced versus unforced configurations. Despite being originally developed for weather
forecasting, we demonstrate that forced configurations of ArchesWeather and ArchesWeatherGen produce stable long-term
climate simulations, have a stable annual cycle, and capture the drift of many
climate variables. The models faithfully reproduce ERA5's climatology, large-scale circulations and interannual variability, and they capture the tails of the distributions.
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All authors Renu Singh, Robert Brunstein, Antonia Jost, Yana Hasson, Thomas Rackow, Claire Monteleoni, Christian Lessig, Guillaume Couairon
Physics and Society
Data-Driven Crowd Dynamics using Kinetic Theory and Ensemble-based Data Assimilation
Santiago Rosa, Manuel Pulido, Orlando Billoni et al. (+2 more)
Understanding pedestrian dynamics is critical for mitigating crowd-related risks and improving public safety. In this work, we propose a data-driven mesoscopic modeling framework that combines the kinetic theory of active particles with data assimilation techniques. The framework uses an ensemble Kalman filter to sequentially estimate the time-dependent spatial distribution of pedestrians and model parameters by fusing observations with the mesoscopic forward model state. Through a series of twin experiments, we show that the panic factor – a key behavioral parameter – is identifiable within this framework. We also evaluate the robustness of the approach by assimilating synthetic observations generated by an
agent-based model (ABM). This setup introduces structural model error because the ABM is governed by microscopic rules that differ fundamentally from the mesoscopic kinetic equations. Despite this discrepancy, the ensemble Kalman filter, through the observation-based innovation term, successfully drives the kinetic model to track the observed pedestrian density while simultaneously recovering the panic factor. In this framework, observations act as a physical constraint on the
evolution of the kinetic model. Crowd-dynamics models, including ABMs and kinetic models, often rely on phenomenological terms to describe social interactions, with parameters that are highly uncertain. Our findings indicate that in such systems, free-running simulations inevitably may diverge from the true state, whereas an online data-driven approach effectively constrains the system's trajectory to its underlying dynamical
manifold.
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All authors Santiago Rosa, Manuel Pulido, Orlando Billoni, Juan Martín Guerrieri, Juan Pablo Agnelli
Biological Physics · Cross-listed from cond-mat.soft
Synergistic approach to probing the dynamics and mechanics of patchy soft matter
Md Mozakker H. Shojib, Asier C. Monasterio, Emanuele Locatelli et al. (+3 more)
Tailoring microscopic details to tune bulk rheology is a key paradigm in soft matter physics, yet the vast parameter space associated with constituent interactions precludes a fully systematic approach. To address this, we have designed a synergistic strategy to explore the parameter space that comprises simulations, experimental rheology, and machine learning. As a case study, we choose DNA-based self-assembled fluids whose viscoelastic response can be fine-tuned by manipulating the base sequencing of the constituent nucleic acid nanostars. We use coarse-grained simulations, benchmarked against experimental data, to obtain the rheology of the DNA fluids, which feeds forward to a framework of Gaussian Process Regression and active learning. The latter is then used to explore the rheological design space with high predictive precision. The pipeline is designed to be deployed iteratively for the rational design and accelerated discovery of generic soft matter suspensions.
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All authors Md Mozakker H. Shojib, Asier C. Monasterio, Emanuele Locatelli, Pascal Friederich, Christopher Ness, Iliya D. Stoev
Applied Physics
Reconfigurable Multistate MRAM Synapses with Vortex STNO based Neurons for Scalable In-Memory Convolutional Neural Networks
Ravish Kumar Raj, Simon N. Richter, Saeed Baghaee Ivriq et al. (+9 more)
Magnetic tunnel junction (MTJ)-based
magnetic random-access
memory (MRAM) is a promising platform for neuromorphic and in-
memory computing owing to its non-
volatility, high endurance, fast switching dynamics and CMOS compatibility. However, conventional
spin-transfer torque and
spin-orbit torque MRAM implementations for neural networks often suffer from high critical switching currents, large latency, thermal instability and significant read-write overheads. Here, we demonstrate a unified multistate MRAM-
spin-torque nano-oscillator (STNO) architecture that integrates synapses and
neurons on a single chip for convolutional neural network (CNN) applications. The system employs 1x8 multistate MRAM arrays as programmable synapses coupled with a
vortex-based STNO
neuron, enabling both individual and collective programming through fieldline-driven write channels. Multiple configurable resistance states are achieved by tuning internal and external
magnetic fields together with bias currents, allowing quantized positive and negative synaptic weights for configurable kernel and pooling operations. The proposed architecture is evaluated through simulation on MNIST, SVHN, CIFAR-10, Google
Speech Commands (GSC) and RadioML
datasets, achieving accuracy of 99.76%, 87.93%, 78.14%, 87.96% and 56.46% respectively. Based on fabricated device dimensions, the complete architecture occupies ~6171.2 {\mu}m2 with an average energy consumption of 200.08 pJ per training and inference cycle for MNIST, highlighting its potential for scalable low-power neuromorphic computing
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All authors Ravish Kumar Raj, Simon N. Richter, Saeed Baghaee Ivriq, Oliver Fridorf, Darío Fernández-Khatiboun, Yasser Rezaeiyan, Luana Benetti, Tim Boehnert, Ricardo Ferreira, Hooman Farkhani, Sonal Shreya, Farshad Moradi
Atomic Physics
Restoring Velocity Immunity via Dynamic Mirror Compensation in a Large-Area Dual-Atom-Interferometer Gyroscope
Jie Gu, Yin-fei Mao, Zhan-Wei Yao et al. (+10 more)
We propose and demonstrate a dynamical mirror compensation scheme to restore velocity immunity in a large-area dual-atom-interferometer gyroscope. In an ideal Mach-Zehnder configuration, the phase shift is inherently immune to atomic velocity, but this property is broken by the Earth's rotation via the Coriolis effect. We overcome this by actively rotating the Raman mirrors during the pulse sequence to cancel the time-dependent angular offset. The implementation relies on a decouplable calibration-compensation chain to remove rotation-induced time-dependent terms. The scheme is validated on a dual-atom-interferometer gyroscope with an interference area of 21.1 cm^2. After compensation, the phase's dependence on atomic velocity is reduced 40-fold, and the velocity contribution to scale-factor stability is evaluated to be 0.13 ppm. The sensor achieves a rotation sensitivity of 1.3\times10^{-8} rad/s/Hz^{1/2} and a stability of 1.9\times10^{-10} rad/s at 4500 s integration, together with a common-mode noise rejection ratio of up to 459, demonstrated in a seismic event. This work removes a key obstacle to scale-factor stabilization in atom-interferometer gyroscopes and paves the way for their applications in inertial
navigation and geophysics.
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All authors Jie Gu, Yin-fei Mao, Zhan-Wei Yao, An-qing Zhang, Si-Bin Lu, Shao-kang Li, Min Jiang, Xiao-Li Chen, Min Ke, Xi Chen, Run-Bing Li, Jin Wang, Ming-Sheng Zhan
Chemical Physics
Diagrammatic Multiplet-Sum Method (MSM) Density-Functional Theory(DFT): III. Inclusion of Relaxation and Application to LiH
Mark E Casida, Abraham Ponra, Gadzikano Munyuki et al. (+1 more)
Ideal density-functional approximations (DFAs) should account for dynamic, static, and nondynamic correlation. While common DFAs struggle with the latter two, the Ziegler-Rauk-Baerends-Daul multiplet sum method (MSM) provides a pragmatic way to include static correlation. In this article, we use diagrammatic MSM density-functional theory (diag MSM DFT) using the two-orbital two-electron model (TOTEM) to extend MSM DFT to include nondynamic correlation without relying on
symmetry arguments. Building on previous formulations [A. Ponra, C. Bakasa, A.J. Etindele,and M.E. Casida, J. Chem. Phys. 159, 244306 (2023); M.E. Casida, A. Ponra, C. Bakasa, and A.J.Etindele, J. Chem. Phys. 162, 144317 (2025)] that lacked relaxation effects, this article incorporates relaxation via nonorthogonal configuration interaction (NOCI). We demonstrate that this modified diag MSM DFT produces an accurate ground-state potential energy curve (PEC) for lithium hydride (LiH), even at the ionic-to-open-shell-singlet avoided crossing characterized by significant charge transfer. This encouraging result suggests that the model can be extended to (at least) other singly and multiply-bonded diatomic molecules, while providing insight into a novel way to include strong correlation in DFT.
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All authors Mark E Casida, Abraham Ponra, Gadzikano Munyuki, Bharathi Natarajan
Fluid Dynamics
Revisit the simplified lattice Boltzmann method: dissipation, dispersion and stability
Zhengwei He and Zhen Chen
The simplified
lattice Boltzmann method (SLBM) is a recent development in the
lattice Boltzmann method (LBM) community, addressing the intrinsic limitations of the traditional LBM by directly evolving macroscopic quantities and maintaining numerical stability in high-Reynolds-number simulations. However, fundamental understanding of the numerical dissipation and dispersion of SLBM is still lacking, and the origin of its good numerical stability is not fully resolved. In this work, a generalized formulation is developed, revealing that the SLBM recovers modified macroscopic equations containing both intrinsic physical deviations and numerical truncation errors. To remove these deviations, the macroscopic equation derived from the standard Bhatnagar–Gross–Krook
lattice Boltzmann method (BGK-LBM) is adopted as a reference model and solved by the predictor-corrector strategy, which constitutes the reformulated SLBM. The proposed method uses the generalized SLBM formulation in the predictor step with tunable high-order parameters, while the corrector step is realized by the finite-difference discretization. Linear stability analysis, together with linear-wave validation, clarifies the roles of these parameters in controlling numerical dissipation and dispersion, which is then examined in more complicated numerical examples. It is demonstrated that the reformulated SLBM preserves the second-order accuracy, improves the dispersion-dissipation performance, remains stable in under-resolved cases, and resolves fine
vortex structures on relatively coarse grids. Thus, the proposed method combines improved numerical properties with the simplicity of SLBM, offering a high-fidelity and stable scheme for incompressible flow simulations.
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Optics
Symmetry restoration through chaotic hysteresis in a non-Hermitian optical trimer
Johanne Hizanidis and Konstantinos G. Makris
We investigate
symmetry restoration and spatially localized dynamics in a non-Hermitian optical trimer composed of three lossy waveguides with complex-valued couplings. Extending our previous analysis of the system's global bifurcation structure, we adopt a site-resolved perspective in order to uncover how collective nonlinear dynamics emerge and reorganize across the individual waveguides. We show that the transition from asymmetric to symmetric states is mediated by a chaotic hysteretic regime involving the coexistence of asymmetric, periodic-symmetric, and chaotic-symmetric attractors. Within this regime, chaotic dynamics become spatially localized predominantly at the edge waveguides, while the central waveguide retains partial spectral coherence. Following
symmetry restoration, the system develops multifrequency dynamics through a spatial period-doubling process, where the middle waveguide oscillates at twice the dominant frequency of the edge sites. These results reveal how Kerr nonlinearity and complex coupling organize
symmetry restoration, chaos localization, and frequency differentiation in minimal non-Hermitian photonic
lattices.
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Fluid Dynamics · Cross-listed from cond-mat.soft
Microfluidic Oscillatory Rheology of Transported Soft Particles
Matteo Milani, Joshua D. McGraw, Anke Lindner et al. (+1 more)
Microfluidic channels have emerged as useful tools to control dynamic forcing on transported microscale objects, as encountered in emulsions, biological flows, and other soft matter systems. Tailored channel designs enable precise interfacial and bulk rheological measurements of complex materials over a wide range of forcing timescales. After a brief overview of recent experiments illustrating these techniques, we discuss perspectives for future research in this direction, including the study of lubrication films in highly confined droplets, the measurement of fast relaxation dynamics of complex interfaces, and the high-throughput rheological characterization of microscopic soft matter systems ranging from single macromolecules to
cells.
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All authors Matteo Milani, Joshua D. McGraw, Anke Lindner, Stefano Aime
Data Analysis and Statistics · Cross-listed from math.ST
The Topological Stability Index: A Variance-Based Measure for Persistence Barcodes
Joris Kirchner and Ioannis Diamantis
We introduce the Topological Stability Index (TSI), a variance-based scalar measure for persistence barcodes that quantifies the dispersion of persistence lifetimes. Unlike persistent
entropy, which depends only on normalized weights, the TSI captures absolute variability and is sensitive to heterogeneous feature scales. We establish fundamental properties of the TSI, including its scaling behavior, invariance under lifetime translation and explicit update formulas under insertion and deletion of bars. We also consider a complementary first-moment-type quantity, the Topological Signal Index (TSigI), which captures the typical scale of persistence lifetimes and provides additional interpretability alongside the TSI. We further introduce a normalized version, $cv\text{TSI}$, which is scale invariant and admits an explicit algebraic relation to the Rényi
entropy of order two. In particular, $cv\text{TSI}$ is an affine function of the collision probability $\sum_i p_i^2$, and therefore a monotone reparametrization of the Rényi
entropy, providing a direct link between variance-based and
entropy-based summaries in topological data analysis. Numerical experiments on synthetic data and
stochastic time series demonstrate that the TSI captures structural variability complementary to
entropy: it is relatively insensitive to deterministic trends, while responding strongly to
stochastic fluctuations and variations in persistence magnitude.
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Applied Physics · Cross-listed from eess.IV
Absorption and Phase-Contrast Microtomography Using Direct X-Ray Detection With Commercial Off-The-Shelf CMOS Sensors
Damian L. Corzi, Jose Lipovetzky, Fabricio Alcalde Bessia et al. (+5 more)
This work presents high-resolution X-ray microtomography based on commercial off-the-shelf (COTS) CMOS image sensors as direct detectors. The system uses a microfocus X-ray source in cone-beam geometry, enabling both absorption-contrast imaging, thanks to the sensor s intrinsic resolution, and phase-contrast imaging, by adjusting the object-to-sensor distance. A dynamic flat-field correction
algorithm mitigates radiation-induced sensor degradation during long acquisitions. The setup provides voxel sizes from 3.9 microns to 5.2 microns, with an effective spatial resolution (FWHM) as fine as 9.6 microns in magnified phase-contrast mode (1.33x) and 21 microns in non-magnified absorption-contrast mode. Phase contrast enhances visualization of soft tissue boundaries that are difficult to visualize using absorption-contrast imaging in the same experimental configuration.
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All authors Damian L. Corzi, Jose Lipovetzky, Fabricio Alcalde Bessia, German Mato, Andres Cicuttin, Maria L. Crespo, Martin Perez, Mariano Gomez Berisso
Accelerator Physics
Updates on Impedance Studies for the FCC-ee High Energy Booster
Keon Hee Kim, Adnan Ghribi, Santiago Martinez et al. (+10 more)
Following the Future Circular
Collider (FCC) Feasibility Study completion, the impedance model for the FCC-ee High-Energy Booster (HEB) has been significantly expanded beyond the initial copper
vacuum pipe resistive wall analysis. This paper presents a comprehensive impedance and wake budget incorporating RF cavities, bellows, and beam position monitors, evaluated through 3D electromagnetic simulations and analytical methods. The updated model provides the basis for future beam dynamics studies, including transverse coupled bunch instability analyses and single bunch tracking simulations. The present work focuses on the construction and comparison of the main impedance and wake contributions, identifying the dominant sources and the components requiring further investigation. These results will be used to refine the HEB collective effects studies and to support future assessments of instability margins and mitigation requirements.
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All authors Keon Hee Kim, Adnan Ghribi, Santiago Martinez, Quentin Bruant, Antoine Chance, Barbara Dalena, Chiara Antuono, Dora Gibellieri, Carlo Zannini, Frank Zimmermann, Ahmad Mashal, Mauro Migliorati, Mikhail Zobov
Computational Physics · Cross-listed from nlin.CD
Complex network topological and spectral determinants of extreme events
Christian Hechler, Timo Bröhl, Ulrike Feudel et al. (+1 more)
We study the impact of the coupling
topology on the ability of various networked dynamical systems to generate extreme events. By determining the coupling strength that is necessary to generate an extreme event in the collective dynamics of a given system, we observe a power-law-like relationship between this coupling threshold and both topological (edge density) and spectral (algebraic connectivity) properties of various coupling
topologies. Interestingly, this relationship appears to be largely independent of both the investigated system and the underlying mechanism to generate extreme events. This may indicate that the observed relationship is primarily mediated by aspects of the coupling
topology.
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All authors Christian Hechler, Timo Bröhl, Ulrike Feudel, Klaus Lehnertz
Instrumentation and Detectors
Thin single-crystal perovskite detector for high-energy charged particles
Z. Chubinidze, M. Auf der Maur, F. Matteocci et al. (+9 more)
The organometal halide perovskites (OMHP) semi-conductors have shown recently a strong potential as radiation detectors, beside the well-known success in photovoltaics and as photo-detectors. Many studies have been published on X-rays detection, and a few studies about detection of alpha, beta-particles and
protons. Less literature is present for high energy charged particles. OMHP-based devices for tracking and real-time monitoring for high energy particles may offer many advantages. OMHPs can be directly grown on pixelated electronics, even on curved substrates, without the need of complex and expensive bump-bonding procedures. Moreover, OMHPs have shown self-healing features after radiation exposure, which makes them attractive for high-flux applications. In this paper we report a device based on a thin single OMHP
crystal, about 150 mum thick, directly grown on a patterned substrate through dewetting technique, able to detect high-energy charged particles in a high dynamic range of incident fluxes. A dedicated electronics
circuit has been developed to match the expected time characteristics of the OMHP
crystals. This is the first demonstration of thin OMHP single
crystals being able to detect high energy charged particles of hundreds of MeV.
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All authors Z. Chubinidze, M. Auf der Maur, F. Matteocci, I. Viola, J. Endrizzi, L. Pancheri, A. Khan, G. Papalino, G. Felici, A. De Santis, G. Tinti, M. Testa