Computational Physics
High-Accuracy Numerical Solutions of Particle Motion in Static Magnetic Fields
Heather Jiles and Robert Weigel
The Parker-Sochacki (PS) method is investigated as an alternative to Runge-Kutta (RK) methods for solving the Lorentz equations of motion for a charged particle in a static
magnetic field. Traditional methods, including fixed-time-step fourth-order RK, adaptive Dormand-Prince RK, and Gauss-Legendre Runge-Kutta (RKG), advance the solution by sampling derivative estimates at selected points to approximate the solution over a time increment. In contrast, the PS method uses a power series expansion in time that is specific to the system of equations, which is a fundamentally different approach. We assess the accuracy and long-term stability of the RK, RKG, and PS methods for three static
magnetic fields: uniform,
hyperbolic tangent, and dipole, with the RKG method included only for the dipole problem. The PS method results in a 4 to 13 orders-of-magnitude improvement in kinetic energy conservation over the RK methods. When the methods are compared at matched target kinetic energy error, the PS method was substantially faster than RK4, the method with the shortest runtime under identical fixed-time-step conditions. For the dipole field problem, the PS method had the lowest kinetic energy error and had runtimes 4 to 5 times shorter than RKG when using the same fixed time step for
proton runs. The PS method was the only method in this study to maintain accuracy and stability for all problems for both
protons and electrons; the RKG method failed on all electron runs in the dipole problem. We further show that, over sufficiently long integrations in inhomogeneous
magnetic fields, the
symplectic RKG may exhibit secular growth in energy error. Overall, these results indicate that the PS method provides a computationally efficient and highly accurate alternative to the
symplectic RKG and standard RK methods.
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Biological Physics · Cross-listed from cond-mat.soft
Spectral origin of conformal invariance in active nematic turbulence
Rithvik Redrouthu
Zero-vorticity contours in the collective flows of living
cells obey Schramm-Loewner
evolution with diffusivity $\kappa = 6$ and thus fall in the universality class of critical percolation. This observation is surprising because the underlying vorticity field has long-range correlations that, according to the Weinrib-Halperin criterion, should alter the universality class. Here we propose a spectral explanation for this apparent paradox in two-dimensional active nematic
turbulence. The universal energy spectrum $E(q) \sim q^{-1}$ implies sign-field correlations whose decay exponent $a = 3/2$ matches the Weinrib-Halperin marginal threshold $2/\nu_0 = 3/2$ for two-dimensional percolation. At this marginal point the long-range correlations are irrelevant under renormalization, so the system flows to the uncorrelated percolation fixed point. Gaussian surrogate fields with the same spectrum confirm $a = 3/2$ to three significant figures, and left-passage analysis of their zero-vorticity interfaces yields $\kappa = 5.98 \pm 0.08$, consistent with SLE_6.
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Instrumentation and Detectors
Frequency & Radiative Analysis of Random Yagi-UHF/VHF Phased Array
Luis M. Bres, Luis A. Hernandez and Teviet D. Creighton
This paper investigates a phased array ground station capable of tracking multiple sources, multi-beamforming, electronic steering, easy scaling, and low cost. The project will develop a 20-pair dual-polarized yagi-UHF/VHF phased array with a pseudo-random layout, comparing parameters of random and uniform distributions. We will present several analyses: general analysis for side lobes across both elevation and azimuth, analysis of scaling with number of elements ("element sweep"), electronic beam steering analysis, mechanical beam steering analysis, electro-mechanical beam steering analysis, array density analysis, and reception/transmission spectra analysis.
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Chemical Physics · Cross-listed from quant-ph
After 100 Years of Quantum Mechanics: Toward a Constructive Observation-Centered Perspective
Timothy Stroschein and Markus Reiher
Quantum mechanics owes much of its extraordinary success to a Hilbertian program of mathematical formalization. Yet, the formalism remains poorly aligned with the practical limitations of computations in finite dimensions and under finite accuracy. In this perspective, we argue that this mismatch points to the need for a new mathematical program: a rigorous constructive theory for effective descriptions to identify essential degrees of freedom. We propose an observation-centered point of view in which signals are treated as the primary objects of analysis, while wave functions and
Hamiltonians are reconstructed as auxiliary structures to rationalize the observed data. Our starting point is a signal-based spectral equation that reformulates frequency analysis as an operator problem. We connect this point of view to results on prolate
Fourier theory, spectral analysis with finite observation time, and short-time
quantum simulation. We highlight a sharp accuracy transition relating necessary observation time to the effective spectral density of a signal for achieving accurate resolution. The resulting framework integrates approximation as a fundamental necessity more directly into the foundations of
quantum mechanics and points toward a broader program for the effective description of complex
quantum systems, such as those found in the molecular sciences.
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Fluid Dynamics
Unified scaling laws for turbulent boundary layers across flow regimes
Gonzalo Arranz and Adrian Lozano-Duran
We discover unified scaling laws for the mean wall shear stress and the mean velocity profile in turbulent boundary layers subject to favorable and adverse mean pressure gradients-including flows with separation and reattachment. We use the information-theoretic irreducible error
theorem to identify, among all dimensionally consistent combinations, the dimensionless groups with maximal predictive power, without assuming any functional form. Two dimensionless variables suffice to describe the mean wall shear stress, while three characterize the mean velocity profile. The scaling laws depend exclusively on variables defined at a fixed streamwise location, demonstrating that judiciously chosen combinations of local quantities implicitly encode upstream history without requiring global parameters. The results are validated against a rich collection of cases and are shown to collapse mean quantities across flow regimes previously thought to require distinct treatments.
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Data Analysis and Statistics · Cross-listed from cs.LG
Vestibular reservoir computing
Smita Deb, Shirin Panahi, Mulugeta Haile et al. (+1 more)
Reservoir computing (RC) is a computational framework known for its training efficiency, making it ideal for physical hardware implementations. However, realizing the complex interconnectivity of traditional reservoirs in physical systems remains a significant challenge. This paper proposes a physical RC scheme inspired by the biological vestibular system. To overcome hardware complexity, we introduce a designed uncoupled
topology and demonstrate that it achieves performance comparable to fully coupled networks. We theoretically analyze the difference between these
topologies by deriving a
memory capacity formula for linear reservoirs, identifying specific conditions where both configurations yield equivalent
memory. These analytical results are demonstrated to approximately hold for nonlinear reservoir systems. Furthermore, we systematically examine the impact of reservoir size on predictive statistics and
memory capacity. Our findings suggest that uncoupled reservoir architectures offer a mathematically sound and practically feasible pathway for efficient physical reservoir computing.
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All authors Smita Deb, Shirin Panahi, Mulugeta Haile, Ying-Cheng Lai
Instrumentation and Detectors
Cherenkov and scintillation light separation in BGO and BSO crystals coupled to SiPMs for dual-readout electromagnetic calorimetry at future colliders
M. Alviggi, B. Argiento, E. Auffray et al. (+29 more)
We report on the separation of Cherenkov and scintillation light in BGO and BSO
crystals read out with silicon photomultipliers (SiPMs). The two light components are disentangled on an event-by-event basis by combining optical filtering with waveform template fitting, exploiting their distinct spectral and temporal characteristics. Measurements were carried out using high-energy
muon and positron beams at the CERN SPS North Area, demonstrating Cherenkov yields of up to $\sim$150 ph.e./GeV in electromagnetic showers. This work provides the first demonstration of Cherenkov-scintillation separation in BGO and BSO
crystals with SiPM readout, supporting the use of this technology as a building block for a dual-readout electromagnetic calorimeter, as foreseen in the IDEA detector concept for a future $e^+e^-$
Higgs factory.
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All authors M. Alviggi, B. Argiento, E. Auffray, A. Benaglia, M. Biasini, V. Bisignani, D. Boccanfuso, L. Borriello, M. Campajola, C. Cecchi, F. Cirotto, F. Conventi, A. D'Avanzo, J. Delenne, G. De Nardo, C. Di Fraia, A. D'Onofrio, L. Favilla, M. Francesconi, G. Gaudino, A. O. M. Iorio, V. Izzo, M. T. Lucchini, E. Manoni, M. Mirra, S. Moneta, P. Paolucci, S. Perna, B. Rossi, E. Rossi, J. Scamardella, G. Sekhniaidze
Data Analysis and Statistics · Cross-listed from stat.AP
Blume-Capel model: Estimation of a three stable state network for $-\bf 1$, $\bf 0$ and $\bf +1$ data
Lourens Waldorp, Jonas Dalege, Maarten Marsman et al. (+3 more)
An extension of the Ising model is proposed as a viable alternative for data with values $-1$, $0$ and $+1$ in the inverse problem, i.e., estimation of the parameters. This model is called the Blume-Capel (BC) model, adapted from physics for small networks. The advantage of the BC model is not only the fact that it is possible to have a neutral (centrist) position on the response scale, but also that this model allows for three stable states. We illustrate magnetisation properties of the BC model using simulations and mean field results. For estimation of the BC parameters, we show that the BC model is part of the exponential family of distributions and show that the model is identified, except for the (inverse) temperature. We then show that combining pseudo-likelihood with lasso yields accurate parameter recovery for the BC model, even in small networks. Moreover, confidence intervals with good coverage properties can be obtained using the desparsified lasso together with sandwich and shrinkage techniques. We apply the methods to data obtained from the online platform Stemwijzer, intended to aid people in deciding for whom to vote.
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All authors Lourens Waldorp, Jonas Dalege, Maarten Marsman, Adam Finnemann, Irene Ferri, Han L. J. van der Maas
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
How Does Intercalation Reshape Layered Structures? A First-Principles Study of Sodium Insertion in Layered Potassium Birnessite
Adriana Lee Punaro, Daniel Maldonado-Lopez, Jorge L. Cholula-Díaz et al. (+2 more)
This study presents a first-principles study at the level of hybrid-level density functional theory of the sodium intercalation process in a layered potassium birnessite (a layered manganese dioxide, {\delta}-MnO2). Understanding the intercalation processes of {\delta}-MnO2 is a vital step in advancing its potential innovative applications. Through a formation energy formalism, we analyze the stability of the structure as sodium ions (Na+) are intercalated between layers. Simulated Raman spectra allow us to find relationships between the vibrational and structural properties of the material, i.e. we identify the most important vibrational modes and related them to the structural/geometrical change. The
diffusion of Na+ and K+ ions in birnessite is studied by transition state theory, determining the energy barriers to ion displacement in the interlayer. The
symmetry and planar density of the system are characterized by simulated X-ray diffraction and geometrical analysis of the optimized structures. Through binding energy analysis, we also find that the Na+ ions are more loosely bound to the
lattice as they reach the saturation limit. Finally, the electronic properties are studied via
spin-polarized densities of states. As intercalants are added, the electronic properties are profoundly modified, resulting from modification of Mn oxidation states,
lattice distortions, and
symmetry effects. Moreover, some of the intercalated structures behave as bipolar
magnetic semiconductors with potential applications in spintronics devices. In other words, the band gaps and
magnetic behavior of the system can be controlled by intercalation. This work provides an overarching analysis of intercalated birnessite and describes the essential properties of potassium birnessite and co-intercalation with Sodium as a next-generation energy, electronic, and spintronic material.
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All authors Adriana Lee Punaro, Daniel Maldonado-Lopez, Jorge L. Cholula-Díaz, Marcelo Videa, Jose L. Mendoza-Cortes
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Ultrasonic characterization of generally anisotropic elasticity implementing optimal zeroth-order elastic bounds and a wave-fitting approach
Diego Cowes, Juan I. Mieza and MArtín P. Gómez
The elastic behavior of materials is of critical importance for the design, fabrication, and testing of industrial and structural components. The ease with which the wave angle of incidence can be varied makes ultrasonic techniques well suited for the characterization of anisotropic materials, whose properties are direction-dependent. This work aims to develop an ultrasonic goniometry method in which a wave is transmitted through a sample while scanning over spherical coordinates. A plane-wave model is formulated that accounts for fluid-solid interfaces and is applicable to a wide range of sample thicknesses. The model assumes general anisotropy, enabling the characterization of materials with
symmetries up to triclinic, and does not require precise sample
alignment. Specially designed transducers support the plane-wave approximation, thereby avoiding the need for more computationally expensive finite-beam models. Furthermore, implementation of the forward model on GPU architectures significantly reduces the computational cost associated with the numerous evaluations required during the waveform fitting inversion. The introduction of optimal zeroth-order bounds is used to tightly delimit the search space, and an isotropic self-consistent solution is shown to provide an effective initial guess. Finally, measurements on plate-like samples are compared with the literature and diffraction-based methods.
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Optics
Interference Limited Absorption in Dense Molecular Nanolayers Near Reflecting Surfaces
Zeyu Zhou, Maxim Sukharev, Abraham Nitzan et al. (+1 more)
We investigate linear resonant absorption by a dense ensemble of molecules confined to a subwavelength layer in two geometries: (i) a free-standing film in homogeneous space and (ii) the same film placed at a controlled distance from a reflecting surface. In both cases, increasing the effective light-matter coupling (via molecular density/oscillator strength) produces a non-monotonic response: absorption rises to an optimum and then decreases as the film becomes increasingly radiatively bright and reflective. Finite-difference time-domain simulations and analytical transfer-
matrix calculations agree quantitatively and yield compact ridge conditions for the optimum. We interpret the trends using a scattering/port picture: the isolated film is a symmetric two-port system (reflection and transmission), which bounds single-sided resonant absorption to 50% in the ultrathin limit (reflecting transition saturation), whereas adding a mirror suppresses transmission and converts the structure into an effectively one-port absorber. In the mirror-backed geometry, interference can cancel reflection and unity absorption is obtained at critical coupling, when radiative leakage is balanced by intrinsic molecular loss. These results clarify fundamental limits and design rules for collective absorption in dense molecular layers near dielectric or metallic boundaries.
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All authors Zeyu Zhou, Maxim Sukharev, Abraham Nitzan, Joseph E. Subotnik
History and Philosophy of Physics · Cross-listed from quant-ph
Discovery of the Solution to the "Einstein-Podolsky-Rosen Paradox"
Roman Schnabel
In 1935, Albert Einstein, Boris Podolsky and Nathan Rosen (EPR) published a thought experiment that is entirely correct, has been demonstrated in real experiments, and is now the most famous in
quantum physics. Their pioneering work described, for the first time,
quantum correlations and can be regarded as a very early glimpse into today's 'deep'
quantum technologies, by which I mean those that enhance functionality by making use of
quantum correlations. However, their work also contains a paradox that Erwin Schroedinger had already recognised as such in 1935 and which has since been cemented by the so-called Bell experiments. Here, I am now able to pinpoint the origin of the paradox within the chain of
reasoning, which ultimately resolves the paradox.
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Optics
High bandwidth traveling wave electro-optic modulator at 1{\mu}m on thin-film lithium tantalate
Ayed Al Sayem, Shiekh Zia Uddin, Ting-Chen Hu et al. (+4 more)
We present the first experimental demonstration of a high-bandwidth thin-film lithium tantalate (TFLT) electro-optic modulator operating at 1 {\mu}m, with a V{\pi} of 2.4 V, and less than 2 dB electro-optic roll-off up to 50 GHz and stable DC bias operation.
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All authors Ayed Al Sayem, Shiekh Zia Uddin, Ting-Chen Hu, Alaric Tate, Mark Cappuzzo, Rose Kopf, Mark Earnshaw
Instrumentation and Detectors · Cross-listed from hep-ex
Particle transformers for identifying Lorentz-boosted Higgs bosons decaying to a pair of W bosons
CMS Collaboration
A novel deep neural network classifier, a “Particle
transformer” (PaRT), is introduced for the identification of highly Lorentz-boosted resonances reconstructed as single, multipronged jets in measurements and searches performed by the CMS Collaboration at the CERN LHC. Based on a self-
attention mechanism that allows the model to weigh the importance of different particles, PaRT is trained on a wide variety of
topologies, notably demonstrating strong performance for the first time on jets originating from boosted
Higgs boson decays to W
bosons. The PaRT
algorithm achieves a tagging efficiency of more than 50% for such jets at a background efficiency of 1%, while maintaining decorrelation from the jet mass. A calibration is performed in
proton-
proton collision data collected by CMS at a center-of-mass energy of 13 TeV, with a data set corresponding to a total luminosity of 138 fb$^{-1}$. Data-to-simulation selection efficiency scale factors are measured to be in the 0.9$-$1.0 range, with relative uncertainties between 7 and 23%. The tagging capability of PaRT enhances the sensitivity of standard model measurements and searches for beyond-the-standard-model resonances decaying to hadronic diboson systems.
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Medical Physics
A Conjugate Bayesian Framework for Fast 3D Positronium Lifetime Estimation with a Partial System Matrix
Berkin Uluutku, Giulianno Gasparato, Manish Das et al. (+7 more)
Background: Positronium lifetime imaging extends conventional positron emission
tomography by using the time interval between positron emission and annihilation as an additional contrast mechanism. Voxel-wise lifetime estimation in fully three-dimensional settings is computationally difficult because the number of feasible detector-time channels grows rapidly, whereas only a small subset is observed in practice. We developed a scalable statistical framework for three-dimensional positronium lifetime estimation based on a time-of-flight-aware partial system
matrix restricted to observed detector-time channels, combined with posterior event-to-voxel weighting and a conjugate Gamma–Exponential update for closed-form voxel-wise effective-rate estimation. Results: Restricting the forward model to observed detector-time channels reduced
memory and computational requirements while preserving the Poisson data model for retained detected triple coincidences. In simulated data with 4056 voxels, the analytic
Bayesian estimator required 2.76 s versus 74.46 s for 10 L-BFGS-B iterations on the same CPU while accurately recovering the effective-rate map. In a triple-coincidence
dataset acquired with a J-PET prototype scanner and a NEMA image-quality phantom, a 234 375-voxel effective-rate map was estimated in approximately 3 s from about $3.64\times10^5$ retained events. Conclusions: Restricting the system
matrix to observed detector-time channels makes fully three-dimensional positronium lifetime estimation computationally practical for sparse triple-coincidence data. The proposed posterior-weighted conjugate update provides a fast and stable single-component surrogate
estimator of voxel-wise effective lifetime for large-scale three-dimensional positronium lifetime imaging.
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All authors Berkin Uluutku, Giulianno Gasparato, Manish Das, Jarosław Choiński, Anand Pandey, Sushil Sharma, Paweł Moskal, Ewa Stępień, Chien-Min Kao, Hsin-Hsiung Huang
Applied Physics · Cross-listed from quant-ph
Resist-free shadow deposition using silicon trenches for Josephson junctions in superconducting qubits
Tathagata Banerjee, Stephen Daniel Funni, Saswata Roy et al. (+2 more)
Superconducting
qubit fabrication innovations continue to be explored to achieve higher performance. Despite improvements to base layer fabrication and processing, resist-based Josephson junction (JJ) schemes have largely remained unchanged. The
polymer mask during deposition causes chemical contamination and limits in situ and ex situ surface preparation, junction materials, and scalability. Here, we demonstrate a resist-free approach to junction fabrication based on etched silicon trenches that is CMOS compatible and easily integrated into existing innovations in
qubit base layer fabrication and chemical processing. We fabricate Al-AlOx-Al JJs and
qubits using this method, measuring median energy relaxation times up to 184 microseconds. We find minimal contamination at the substrate-metal interface and fluctuations of energy relaxation on a 35 hour timescale that are narrow and normally distributed. The method widens the process window for substrate preparation and new materials platforms.
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All authors Tathagata Banerjee, Stephen Daniel Funni, Saswata Roy, Judy J. Cha, Valla Fatemi
Computational Physics
Differentiable free energy surface: a variational approach to directly observing rare events using generative deep-learning models
Shuo-Hui Li, Chen Chen, Yao-Wen Zhang et al. (+1 more)
Rare events are central to the
evolution of complex many-body systems, characterized as key transitional configurations on the free energy surface (FES). Conventional methods require adequate sampling of rare event transitions to obtain the FES, which is computationally very demanding. Here we introduce the variational free energy surface (VaFES), a
dataset-free framework that directly models FESs using tractable-density generative models. Rare events can then be immediately identified from the FES with their configurations generated directly via one-shot sampling of generative models. By extending a coarse-grained collective variable (CV) into its reversible equivalent, VaFES constructs a latent space of intermediate representation in which the CVs explicitly occupy a subset of dimensions. This latent-space construction preserves the physical interpretability and transparent controllability of the CVs by design, while accommodating arbitrary CV formulations. The reversibility makes the system energy exactly accessible, enabling variational optimization of the FES without pre-generated simulation data. A single optimization yields a continuous, differentiable FES together with one-shot generation of rare-event configurations. Our method can reproduce the exact analytical solution for the bistable dimer potential and identify a chignolin native folded state in close
alignment with the experimental NMR structure. Our approach thus establishes a scalable, systematic framework for advancing the study of complex statistical systems.
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All authors Shuo-Hui Li, Chen Chen, Yao-Wen Zhang, Ding Pan
Biological Physics · Cross-listed from cond-mat.mtrl-sci
Heterogeneous Molecular Signatures of Human Odor Perception
P. Zanineli, E. V. C. Lopes, G. R. Schleder et al. (+3 more)
Understanding how molecular structure gives rise to odor perception remains a long-standing challenge, with ongoing debate over whether olfaction is primarily governed by molecular shape, vibrational properties, or their interplay at the level of olfactory receptors. Here, we ask whether different odors rely on common molecular determinants or instead emerge from distinct physicochemical regimes. Using interpretable machine-learning models trained on molecular descriptors derived from first-principles calculations that span electronic, vibrational, and structural properties, we analyze feature contributions for odor categories and their associated receptors. We find that no single descriptor class universally dominates odor prediction; instead, different odors exhibit strongly odor-specific patterns of feature importance, with substantial variability across physicochemical domains. This heterogeneity is consistent across different models, suggesting that a universal encoding scheme does not capture odor perception but reflects receptor- and odor-dependent structure-odor relationships. Our results provide statistical constraints on competing olfactory theories and offer a data-driven framework for organizing odor space.
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All authors P. Zanineli, E. V. C. Lopes, G. R. Schleder, L. N. Lemos, F. Crasto de Lima, A. Fazzio
Optics · Cross-listed from cs.LG
Integrated electro-optic attention nonlinearities for transformers
Luis Mickeler, Kai Lion, Alfonso Nardi et al. (+5 more)
Transformers achieve state-of-the-art performance in
language processing and computer
vision. Their computation increasingly depends on hardware that can keep pace not only with large
matrix multiplications, but also with nonlinear operations like Softmax within the core
attention mechanism. On digital accelerators, Softmax accounts for only a small fraction of total operations, yet it can disproportionately impact overall inference latency. Here, we use thin-film lithium niobate Mach-Zehnder modulators (MZM) as analog computing elements for low-latency
Transformer attention. Our high-speed nonlinearities based on the intrinsic sinusoidal MZM response achieve performance close to digital baselines in
Vision Transformers and GPT-2, even under 4-bit input and output quantization. We experimentally characterize the electro-optic response at symbol rates up to 10 GBaud and assess model robustness under corresponding noise conditions. Accounting for the full signal chain, our analysis indicates more than an order of magnitude lower latency relative to previous custom electronic and photonic Softmax implementations. These results establish analog electro-optic devices as nonlinear function units well suited for integration into emerging co-packaged electronic-photonic hardware, offering a path toward high-speed
Transformer inference.
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All authors Luis Mickeler, Kai Lion, Alfonso Nardi, Jost Kellner, Pierre Didier, Bhavin J. Shastri, Niao He, Rachel Grange
Atmospheric and Oceanic Physics
On the Methodology for Assessing Vegetation Impacts on the Atmospheric Branch of the Hydrological Cycle
A. M. Makarieva, A. V. Nefiodov, A. D. Nobre et al. (+3 more)
China has undertaken unprecedented, state-driven vegetation restoration on a continental scale. This large-scale land-surface intervention offers a rare opportunity to assess how deliberate biospheric change influences
climate-relevant processes, especially the hydrological cycle. Of particular interest is how increased water use by additional vegetation affects terrestrial water availability, including streamflow that sustains both ecosystems and human society. Here we evaluate the methodological basis for addressing this question in light of recently available data on hydrological change in China. Revisiting the atmospheric branch of the hydrological cycle, we argue that water yield depends fundamentally on vegetation-induced changes in atmospheric circulation. When the effects of vegetation on atmospheric dynamics are neglected, as in moisture-recycling-based approaches, the analysis is predisposed by construction toward diagnosing a negative effect of additional vegetation on water yield. Given the nonlinear dependence of precipitation on atmospheric moisture, we further suggest that streamflow reductions associated with added vegetation in dry regions reflects a transient phase of early ecological succession rather than a long-term outcome. As ecosystems mature and regional moisture regimes evolve, this relationship may reverse, generating a positive feedback between vegetation cover and water availability. We briefly discuss recent observational evidence consistent with this interpretation. We conclude that robust assessment of vegetation impacts on water yield requires frameworks that explicitly couple vegetation change, atmospheric processes, and hydrological responses. Such an approach is essential for distinguishing short-term trade-offs from longer-term system trajectories and for informing sustainable land management under continued ecosystem restoration and conservation.
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All authors A. M. Makarieva, A. V. Nefiodov, A. D. Nobre, L.A. Cuartas, F. Pasini, D. Andrade
Fluid Dynamics
Early onset of half-power scaling laws in turbulent thermomagnetic convection
Paolo Capobianchi
Scaling laws for turbulent thermomagnetic convection are derived through a theoretical approach supported by direct numerical simulations in a two-dimensional square cavity filled with a high-$\mathrm{Pr}$
magnetic fluid. A transport regime consistent with half-power scalings, $\mathrm{Nu} \sim \mathrm{Ra}_m^{1/2}$ and $\mathrm{Re} \sim \mathrm{Ra}_m^{1/2}$, emerges at the early onset of the laminar-to-turbulent transition and persists over the entire range investigated. Energy-budget and thermo-fluid analyses indicate that this behavior originates from the coupling between thermal and
magnetic gradients, which enhances
magnetic-force-driven plume ejection and vertical advection across the fluid bulk.
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Fluid Dynamics
Enhancing the accuracy of under-resolved numerical simulations of atmospheric flows with super resolution
Armin Sheidani, Michele Girfoglio, Annalisa Quaini et al. (+1 more)
Super-resolution (SR) techniques based on deep learning have recently emerged as a promising approach to enhance the spatial resolution of computational fluid dynamics simulations while containing computational cost. In this paper, we investigate several SR architectures to improve coarse-grid simulations of mesoscale atmospheric flows, with training data generated from simulations of the weakly compressible Euler equations. We compare a baseline convolutional neural network (CNN), an
attention-enhanced CNN, a multi-scale CNN designed to capture flow structures across different spatial scales, and a
diffusion-based SR model. The methods are evaluated on two standard atmospheric
benchmarks: the rising thermal bubble and the density current. Results show that the baseline CNN can accurately reconstruct simpler flow features, while more complex flows require multi-scale architectures. Overall, SR based on the multi-scale CNN provides the best balance of accuracy, robustness, and computational efficiency, outperforming even a state-of-the-art
diffusion-based approach. We also analyze the sensitivity of the models to the size of the training
dataset, highlighting limitations and trade-offs of the proposed SR strategies.
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All authors Armin Sheidani, Michele Girfoglio, Annalisa Quaini, Gianluigi Rozza
Fluid Dynamics · Cross-listed from math.AP
A nonlocal curve evolution for an immersed elastic filament: global existence and convergence to resistive force theory
Laurel Ohm
We consider a nonlocal curve
evolution belonging to a hierarchy of models for the dynamics of an inextensible elastic filament in a 3D Stokes fluid. This model captures the principal part of a full free boundary problem for an elastic filament in Stokes flow. The fluid effects on the filament
evolution are encoded in a pseudodifferential force-to-velocity operator which may be regarded as an interpolation between resistive force theory at low wavenumbers and a Stokes boundary value problem at high wavenumbers. Here the curve is considered to be the centerline of a 3D filament with constant cross sectional radius $\epsilon>0$. We show global well-posedness for the curve
evolution in the natural energy space. This loosely suggests that the full
evolution may be globally well-posed if the large-scale geometry is controlled. Furthermore, we prove convergence to resistive force theory dynamics as $\epsilon\to 0$, which illustrates how resistive force theory emerges from more detailed models.
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Atomic Physics
Characterization of rf field-induced a.c. Zeeman shift in multi-level highly charged ions
Shuying Chen, Lukas J. Spieß, Alexander Wilzewski et al. (+3 more)
Characterization of the trap rf induced a.c. Zeeman shift is essential for achieving high accuracy in optical ion clocks. In this work, we demonstrate the experimental characterization of this shift using highly charged $\mathrm{Ca}^{14+}$. The transverse component of the a.c.
magnetic field is measured using the Autler-Townes splitting of the equally-spaced Zeeman components of the $^{3}\mathrm{P}_1$ when the Zeeman splitting is close to resonance with the trap rf drive frequency. We observe the resulting modulation by performing
quantum logic spectroscopy using the co-trapped $\mathrm{Be}^{+}$. The longitudinal component is measured from probing the $\mathrm{Be}^{+}$
magnetic field-insensitive hyperfine transition $|F=2,m_F=0 \rangle \rightarrow | F=1,m_F=0 \rangle$. We confirm the small influence of the a.c. Zeeman shift in highly charged ions. The employed techniques can easily be transferred to other multi-level atomic systems.
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All authors Shuying Chen, Lukas J. Spieß, Alexander Wilzewski, Malte Wehrheim, José R. Crespo López-Urrutia, Piet O. Schmidt
Fluid Dynamics
Revisit eddy viscosity in pressure-driven wall turbulence at high Reynolds number
Ben-Rui Xu and Ao Xu
We investigate eddy-viscosity distributions in pressure-driven wall
turbulence for three canonical configurations: plane closed-channel flow, open-channel flow with a free-slip surface, and pipe flow. Using direct numerical simulation (DNS) databases spanning friction Reynolds numbers $Re_{\tau}=$ 2000–12000, we infer the eddy viscosity from one-point statistics through the Boussinesq relation. The DNS-inferred eddy viscosity displays configuration-dependent behavior in the outer region, indicating that a single full-depth expression is not uniformly accurate for all three configurations. Building on the interpretation of eddy viscosity as the product of a velocity scale and a length scale, we extend the log-law scaling into the outer region. Specifically, we adopt a stress-based velocity scale and introduce an outer correction function to capture the remaining dependence on the outer coordinate. We then embed a compact parametric form of this correction into a Cess-type framework with van Driest near-wall damping, yielding a full-depth eddy-viscosity model. We assess the model using eddy-viscosity profiles, the log-law indicator function, and skin friction. The results show that the proposed model yields noticeable improvement for open-channel flow while remaining comparable to the classical Cess model for closed-channel flow and pipe flow. These findings underscore the role of outer boundary conditions in shaping the outer-region eddy viscosity and, consequently, mean-flow predictions.
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