Atmospheric and Oceanic Physics · Cross-listed from cs.LG
AFDBench: A Reasoning-First AI Scientist for NationalWeather Service Forecast Discussions
Manmeet Singh, Somnath Luitel, Prabhjot Singh et al. (+3 more)
Large
language models (LLMs) hallucinate numerical values when generating high-stakes meteorological text, posing risks for weather communication. We present AFDBench, an AI meteorologist that generates professional Area Forecast Discussions (AFDs) by
reasoning through structured AI weather forecast data from Google's WeatherNext 2. We introduce AFDBench, the first
benchmark for evaluating generative meteorological
reasoning, comprising 7,732 expert written discussions from 13 National Weather Service (NWS) offices paired with real AI weather forecast inputs, and three complementary metrics: Met-Align (numerical accuracy), Style-Align (professional dialect adherence), and Input-Grounding (fidelity to source weather data). Zero-shot evaluations reveal that open-source LLMs achieve low Style-Align (~0.33) and moderate Input-Grounding (~0.88), failing to write in the professional NWS register or faithfully use their input data. We apply Group Relative Policy Optimization (GRPO) with domain-specific rewards targeting temperature accuracy, synoptic correctness, and format compliance. On 1,033 held-out samples from two unseen NWS offices, GRPO nearly doubles Style-Align from 0.318 to 0.619 and improves Input-Grounding from 0.881 to 0.940, demonstrating that reinforcement learning teaches a 7B-parameter model to write like a professional meteorologist and faithfully interpret AI weather data.
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All authors Manmeet Singh, Somnath Luitel, Prabhjot Singh, Manraaj Banga, Naveen Sudharsan, Josh Durkee
Fluid Dynamics
Ice melting in an oscillatory flow
Sofía Angriman, Tobias de Buck, Roberto Verzicco et al. (+1 more)
We investigate the melting dynamics of an ice disk subjected to an external oscillatory flow using two-dimensional direct numerical simulations, in the absence of buoyancy, varying the flow amplitude and its oscillation frequency. We identify two distinct regimes governed by the interplay between advection and
diffusion within the boundary layer. For slow oscillations, the melting process is well described by an effective steady flow, where a description based on classical forced convection is applicable. For fast oscillations the melting time increases significantly and approaches the
diffusion limit regime, as a result of the oscillatory flow being unable to renew the fluid within the oscillating boundary layer, causing cold meltwater to accumulate near the interface and reducing heat transfer.
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All authors Sofía Angriman, Tobias de Buck, Roberto Verzicco, Sander G. Huisman
Data Analysis and Statistics · Cross-listed from hep-ex
Binary Hypothesis Testing: A Robust Framework Against the Look Elsewhere Effect
Han Zhang, Xue-feng Ding, Yu-Feng Li et al. (+3 more)
In particle physics, discovery claims conventionally require an observed significance exceeding $5\sigma$. However, the interpretation of a $5\sigma$ result depends critically on the testing procedure, namely whether the hypothesis is tested at a single pre-specified point in parameter space or by scanning over a range of possible signal locations. This distinction gives rise to the look-elsewhere effect, a concept that is widely used but often interpreted as a simple penalty for scanning. In this work, we reinterpret the look-elsewhere effect as a correction for procedural inconsistency arising when the null distribution is generated under one procedure while the test statistic is evaluated under another. Within the framework of hypothesis testing, we examine its implications and clarify the distinct roles of the look-elsewhere effect in binary and peak-search scenarios. In particular, we show that binary test is robust against the look-elsewhere effect, whereas peak searches require an explicit correction for the search over signal locations. Using a moderate trial factor of approximately 26, calibrated from the ATLAS
Higgs search, we show that a $3\sigma$ global significance of peak search can correspond to approximately $4\sigma$ significance of the binary test for the same value of the observed test statistic. This reformulation provides a clearer statistical interpretation of the look-elsewhere effect and offers a more coherent framework for understanding significance claims in particle physics.
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All authors Han Zhang, Xue-feng Ding, Yu-Feng Li, Yi-fang Wang, Liang-jian Wen, Liang Zhan
Chemical Physics
Dynamical Consequences of Nontrivial Topology of Molecular Conical Intersections
Indranil Ghosh, Kush Banker and Gregory S. Engel
The
topology of the electronic structure for an avoided crossing and a conical intersection (CI) is different and is characterized by the presence of the
geometric phase in the electronic wavefunction in the latter. Using the linear Jahn-Teller model, we show that an avoided crossing can be created from the conical intersection while preserving the nontrivial
topology of the latter by adding a Pauli $\sigma_y$ term to the
Hamiltonian. Analogously to solid state systems, we derive a half-integer topological invariant as the integral of the Berry
curvature over the CI
nuclear branching space. We investigate the influence of electronic
topology on chemical dynamics by conducting fewest-switches surface hopping simulations and find distinct hopping rates on identical eigensurfaces but with different
topologies. Our work extends the influence of
topology on molecular excited state dynamics beyond the Berry phase that can be practically realized through electron-
nuclear and
spin-orbit coupling.
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Optics · Cross-listed from cond-mat.mtrl-sci
Predicting THz Generation Capability of Organic Crystals through Data Mining and Crystal Nonlinearity Models
Sin Hang Ho, Ashton Roma, Connor Barlow et al. (+5 more)
We report the use of DFT computation and mathematical models to predict the nonlinear dielectric polarization (P^{NL}) and nonlinear susceptibility coefficients (\chi^{(2)}_{IJK}) of organic materials based on their
crystal structures. We apply this computation approach on single-component
crystals, co-
crystals and ionic
crystals found through data mining the Cambridge Structural Database. We verify these computational results with experimental terahertz (THz) generation efficiencies for known THz generators, demonstrating consistency between the measurements and the computed values. Several mined structures show similar or larger PNL values compared to state-of-the-art THz generation
crystals DAST, OH1 and BNA, suggesting great potential for their use in nonlinear optical (NLO) applications. Importantly, we also compared the resulting model of nonlinear optical tensor components with commonly-used simplifications of nonlinearity, showing that the comprehensive approach should be the standard method to evaluate the nonlinear optical properties of single-crystalline materials.
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All authors Sin Hang Ho, Ashton Roma, Connor Barlow, Matthew Lutz, Natalie Green, Stacey Smith, David Michaelis, Jeremy A Johnson
Fluid Dynamics
Effects of pressure on the chemical sooting structure of equi-diffusive counterflow diffusion flames
Rajat Sawanni and Ömer L. Gülder
The effects of pressure on the chemical sooting structure of equi-diffusive soot formation (SF) in a counterflow
diffusion flame (CDF) are explored in a combined experimental and numerical study over pressures ranging from 1 bar to 6 bar. Experiments preserve the diffusive flame structure and carbon flux at increasing pressures and utilize measurements of soot concentrations, dispersion exponents and soot production rates. Numerical simulations are completed in OpenSMOKE++ with detailed \ce{C1}-\ce{C16} chemistry, lumped PAH consideration up to \ce{C160}, sectional soot model and tracking of the C/H ratio in particulates. Network-based tools are utilized to study the organization and
evolution of carbon routing pathways. Results show that for equi-diffusive flames, soot concentration increases with residence time and pressure, whereas soot production rates are influenced only by pressure. Soot C/H ratio is observed to increase with pressure using numerical and experimental methods, but numerical solutions underestimate the increase in hydrogen abstraction reactions. The soot-forming network undergoes a percolation-like organization of its pathways before soot inception. The network then continues to grow by adding connections through its influential nodes. Acetylene is identified as a highly influential node in the carbon transfer graph, with its influence increasing with pressure.
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Atomic Physics · Cross-listed from cond-mat.quant-gas
Roton Instability in Quantum Droplets with Finite-Range Soft-Core Interaction
Avra Banerjee
We investigate the emergence of roton instability in self-bound
quantum droplets interacting via a finite-range soft-core potential modeled by a Heaviside step interaction. The ground-state properties are obtained by solving the extended Gross-Pitaevskii equation including Lee-Huang-Yang corrections with a nonlocal interaction term. The collective excitation spectrum reveals the formation and progressive softening of a roton minimum as the interaction strength and range increase. When the roton energy approaches zero, the system becomes unstable, signaling the onset of density modulation. The rotonic behavior is further characterized through the static structure factor, which exhibits pronounced peaks at the roton momentum.
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Optics
Effects of Quantum Noise and Source Blurring on Dark-Field Signal Retrieval in X-ray Speckle-Based Imaging
Hunwoo Lee, Jingcheng Yuan and Mini Das
X-ray speckle-based dark-field imaging offers high sensitivity to sub-pixel structural features, yet its quantitative reliability in clinical and preclinical settings remains constrained by low
photon flux and finite focal spot sizes. However, how hardware-induced noise and source blurring propagate through
retrieval algorithms to degrade signal integrity is not fully understood. Here, we systematically evaluate
algorithm robustness quantified by signal linearity, sensitivity, and bias under
photon starvation and source blurring across two mathematically distinct frameworks: differential-based intrinsic tracking (Low-Coherence System, LCS) and patch-wise explicit tracking (X-ray Speckle-Tracking Speckle-Vector-Tracking, XST-XSVT). Our experimental results demonstrate that input speckle pattern distortions propagate through
retrieval algorithms in fundamentally different ways depending on
algorithm architecture. As an example, using our setup, under severe
photon starvation, derivative noise amplification in LCS causes its dark-field signal linearity and sensitivity to drop precipitously, while sharply elevating baseline bias. In contrast, XST-XSVT restricts these losses for sensitivity while maintaining a stable baseline, as its patch-wise variance calculation inherently suppresses
stochastic noise. Similarly, under blur-limited conditions , source blurring washes out the speckle pattern, directly reducing dark-field sensitivity for both LCS and XST-XSVT. This characterization establishes operational boundaries for low-power and low-coherence X-ray systems, guiding
algorithm selection and framework optimization to realize quantitative dark-field imaging in preclinical and clinical applications.
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Chemical Physics · Cross-listed from cond-mat.stat-mech
Kinetic Turnover in the Early-Stage Nucleation of Multi-Shell Condensed Clusters
Kaicheng Zhu and Haibin Su
Nucleation is a key rate-limiting process in phase transition and phase separation. Recent studies highlight a significant discrepancy between experimentally measured nucleation rates and theoretical predictions, particularly when dynamic structural reordering occurs along multi-step pathways. To bridge this gap, we develop a multi-shell model with a space-time-dependent order-parameter field to describe the reordering-nucleation process, where structural reorganization couples with the early growth of condensed clusters. Through
stochastic simulations, we track the time-resolved
evolution of heterogeneous structural order inside growing clusters. Path analysis of the first-passage problem in early-stage nucleation demonstrates that shifting the reordering rate alters the nucleation rate by several orders of magnitude. Furthermore, as the coupling strength increases, the relationship between the mean first-passage time and reordering susceptibility shifts from monotonic to non-monotonic, exhibiting a turnover effect. We quantitatively rationalize these behaviors with an effective nucleation barrier that accounts for non-
equilibrium properties. Our findings elucidate the mechanisms behind multi-step nucleation and offer a predictive framework for future studies.
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Plasma Physics
Physics Attention Transformer Surrogate for Rapid Vertical Instability Growth Rate Prediction: Alcator C-Mod to SPARC
Arunav Kumar, Cesar Clauser, Theodore Golfinopoulos et al. (+5 more)
In this work, we investigate rapid prediction of the dominant $n{=}0$ vertical instability growth rate in C-Mod and SPARC
equilibria, where nonrigid free boundary response models are too slow for control cycle use. Using a Physics
Attention Transformer trained on MEQ-FGE-L labels, we predict both the scalar growth rate and the associated two dimensional perturbed toroidal current density. We find mean absolute errors of 5.4~s$^{-1}$ on held out C-Mod
equilibria and 12.7~s$^{-1}$ on synthetic SPARC cases, with spatial eigenfunction errors near 5%. We also compared PAT with operator based ML models : FNO2D and DeepONet, where we found PAT predicts a much lower normalised growth rate error and improved spatial reconstruction. These results indicate that PAT can reproduce MEQ-FGE-L outputs at control relevant latency and could support future studies of growth rate headroom monitoring and proximity aware shape control.
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All authors Arunav Kumar, Cesar Clauser, Theodore Golfinopoulos, Cristina Rea, Francesco Capersene, Dan Boyer, SPARC Team, Alcator C-Mod Team
Plasma Physics · Cross-listed from astro-ph.SR
Calculation of Field Line Slippage Rates in Coronal Simulations
Valentin Aslanyan, David MacTaggart, Roger B. Scott et al. (+6 more)
We present the Universal Slippage calculator (USlip), an extension of the Universal Fieldline Tracer (UFiT), that computes
magnetic field line slippage rates from an input
magnetic field defined on a structured grid. The slippage rate provides a local, physically grounded diagnostic of non-ideal
evolution, directly quantifying departures from ideal frozen-in motion. We outline the theoretical formulation and describe an efficient numerical implementation. The method is validated against analytical solutions and applied to simulations using three coronal codes treating varying spatial scales, all of which are standard inputs for USlip. In all the examples considered, the slippage rate not only identifies where
magnetic connectivity changes occur, but also accurately reproduces the observed direction of field-line slippage. The consistency of the results across analytical tests and multiple simulation platforms demonstrates that USlip is a robust and versatile tool for diagnosing three-dimensional reconnection in dynamically evolving systems.
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All authors Valentin Aslanyan, David MacTaggart, Roger B. Scott, Chloe P. Wilkins, David I. Pontin, Anthony R. Yeates, Peter F. Wyper, Karen A. Meyer, Spiro K. Antiochos
Atomic Physics · Cross-listed from quant-ph
Geometry-controlled correlated electric-field noise in enclosed ion traps from billiard return spectra
Ayush Nadiger
We ask how passive conducting geometry determines the spatial structure of electric-field noise seen by trapped ions. From a boundary-potential covariance and the Dirichlet Green function we construct the $N$-ion electric-field cross-spectral
matrix and its blockwise motional Kossakowski generator. In a parallel slab, billiard unfolding turns the electrostatic response into a return-depth measure and yields an exact return-pair functional for arbitrary stationary surface spectra. For every finite equal-height ion array, the passive cover increases the normal-field covariance
matrix in the positive-semidefinite ordering and decreases the tangential-field covariance
matrix in the same ordering: all collective normal-field coordinates acquire more absolute noise, while all collective tangential coordinates acquire less. At $h=2d$ the local-noise single-ion ratios are exactly $\zeta(3)$ and $\eta(3)$. Diagonalizing the equal-frequency covariance identifies collective environmental noise eigenchannels and a geometry-dependent noise rank; within a degenerate frequency block these become the Lindblad jump channels. In a ten-ion example, closing the cover to $h=2d$ lowers the participation rank from 5.61 to 5.11 while increasing the leading channel's share from 23.7% to 28.6%; a primitive Mølmer-Sørensen calculation shows how the projected covariance sets the weak-heating gate exposure. Beyond parallel walls, specular paths emerge as large-$q_z$ saddles of the screened boundary operator. Across 16 curved covers, the fitted electrostatic decay exponent correlates at 0.9991 with the independently computed shortest specular excess length, while separate tests resolve focusing and competing saddles.
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Space Physics · Cross-listed from astro-ph.SR
Photospheric index of geomagnetic activity
Ismo Tähtinen, Timo Qvick, Timo Asikainen et al. (+1 more)
Geomagnetic indices quantify the disturbances of the Earth's
magnetic field. They form an important space weather and space
climate record that tracks
solar-terrestrial effects on the Earth. Although geomagnetic activity has its origins in the photospheric
magnetic fields, the two have so far not been directly related. We develop a photospheric index of geomagnetic activity (PIGA) that measures the geoeffectiveness of the Sun based on photospheric
magnetic field as presented in synoptic magnetograms. We construct the PIGA from synoptic magnetograms of Wilcox
Solar Observatory by relating the equatorial and axial dipole components of the photospheric
magnetic field to the geomagnetic Kp index by means of linear regression. PIGA captures well the
evolution of the geomagnetic activity over the past 50 years at the resolution of
solar rotation, having linear correlation of 0.71 with the geomagnetic Kp index. PIGA makes it straightforward to measure the geoeffectiveness of the Sun using the dominant structure of the global
solar magnetic field. PIGA can for example be used to study the geoeffectiveness of the Sun using historical simulations or the predicted
solar magnetic field. PIGA also allows to use observed geomagnetic activity as an additional constraint for the early
magnetic field reconstructions of the
solar magnetic field.
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All authors Ismo Tähtinen, Timo Qvick, Timo Asikainen, Kalevi Mursula
Biological Physics · Cross-listed from q-bio.PE
Global geometry of the genotype-phenotype map illuminates a trade-off between penetrance and mutational adaptability
Yutaro Ikeda, Kunihiko Kaneko and Tetsuhiro S. Hatakeyama
Evolution in changing environments requires both reliable expression of the currently favored phenotype, as quantified by penetrance, and the capacity to reach alternative phenotypes through mutation. Previous studies suggest that high penetrance may restrict such mutational access. However, because these studies focus on evolved genotypes and local mutational neighborhoods, they cannot determine whether this local constraint limits mutational adaptability under environmental change. Such adaptability depends on a genotype's position relative to high-fitness regions for other environments. Addressing this question requires reconstructing the full probability distribution over phenotypes for every genotype and the resulting environment-specific fitness landscapes across genotype space. Such reconstruction is generally infeasible because genotype and phenotype spaces grow combinatorially. Here, an abstract model of
stochastic genotype-phenotype mapping, inspired by interacting
spins in statistical physics, permits exhaustive reconstruction of the map. We find that high-penetrance genotypes tend to occupy the interior of environment-specific high-fitness regions and are mutationally robust, whereas lower-penetrance genotypes tend to lie near their boundaries and have greater mutational access to high-fitness regions for alternative environments. This global geometry generates a trade-off between penetrance and mutational adaptability. In evolutionary simulations, stronger phenotypic noise in a fixed environment increases the selective advantage of reliable expression, thereby favoring high penetrance and mutational robustness. Frequent environmental change instead favors mutational accessibility at the expense of penetrance. Thus, penetrance and adaptability are opposing consequences of the same global geometry, with environmental conditions determining their evolutionary balance.
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Applied Physics
Imaging atomic scale stochasticity: noise in the nearly commensurate charge density wave of 1T-TaS$_2$ for leaky-integrator-and-fire neuromorphic emulator
Michael Verhage
Low-dimensional materials are promising materials for emulating
neuron-like firing were understanding of the atomic-scale origin of this behavior can benefit integration into neurormophic hardware. Using scanning tunneling microscopy (STM) as a highly local probe of correlations in the charge density wave (CDW), we study atomic-scale CDW noise in $1T\text{-}\mathrm{TaS}_2$ at room temperature. We statistically analyze the tunnel-junction noise and, to explain the temporally correlated current bursts, introduce a mesoscopic model in which the fractal structure and reorganization of CDW discommensurations are related. This noise mimics leaky-integrate-and-fire
neuron dynamics. Our results show that atomic-scale current bursts in the tunnel junction can act as effective nonlinear elements in spiking neural emulators, enabling bioinspired processing through rich CDW dynamics at room temperature and supporting the miniaturization of spiking devices.
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Chemical Physics
Collective intermolecular Coulombic decay beyond Coulomb
Alan G. Falkowski and Lorenz S. Cederbaum
Intermolecular Coulombic decay (ICD) is a widely spread phenomenon in nature and laboratory in which the excess energy of a donor is utilized to ionize a nearby acceptor. If the excess energy is insufficiently large to enable ICD, two (or more) donors can collectively transfer their combined excess energy to ionize the acceptor. Experiments show that this collective ICD is, surprisingly, operative in gases. Recently, it has been demonstrated that standard ICD can efficiently take place at large distances between the donors and acceptors due to retardation. Here, we derive the theory of collective ICD including retardation.
Quantum electrodynamics (QED) perturbation theory is used and it is shown that the theory can be substantially simplified and the process also made more amenable to interpretation by introducing two-body interaction potentials which include retardation. Explicit formulas for the rate of collective ICD are derived and interpreted by expressing the rate in terms of measurable quantities and
geometric factors. It is demonstrated that the change of the permanent dipole moments of the species upon excitation is a relevant ingredient in collective ICD.
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Computational Physics · Cross-listed from astro-ph.CO
Chebyshev interpolation in Einstein-Boltzmann codes
Herman Sletmoen
Einstein-Boltzmann codes compute theoretical predictions of cosmological models and rely heavily on interpolation in their independent variables: time $\tau$, wavenumber $k$ and multipole $\ell$. We give a practical summary of interpolation with Chebyshev
polynomials, which converges rapidly for smooth functions and thus pairs naturally with approximation-free Einstein-Boltzmann codes. By solving the perturbations and line-of-sight integrals at Chebyshev nodes in $k$ and $\ell$, we show that Chebyshev
polynomials interpolate to higher precision than traditional cubic splines from fewer explicit solutions. On a set of example spectra for matter and the
cosmic microwave background (CMB), we find up to four orders of magnitude lower interpolation error using the same number of points. For a typical CMB temperature spectrum computed with interpolation in both $k$ and $\ell$, Chebyshev
polynomials converge to $10^{-4}$-$10^{-5}$ relative error with only 50-80 points per variable, while cubic splines approach $10^{-4}$ error with 200 points, translating to a $2.5\times$-$4\times$ speedup. The exact improvement depends on the target function and is generally more dramatic at high precision levels. Standard Chebyshev $\ell$-interpolation needs line-of-sight integrals generalized to non-integer $\ell$, but we show a way to avoid this by rounding the nodes to integers. Chebyshev interpolation is implemented in SymBoltz, which is available at https://github.com/hersle/SymBoltz.jl.
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Chemical Physics
Efficient, precise DFT calculations of NMR shieldings: Revisiting the finite field approach
Xiao Liu, Kaushik D. Nanda, Jiashu Liang et al. (+1 more)
Absolute
nuclear magnetic shielding constants and relative chemical shifts are second-derivative response properties that underpin the interpretation of
Nuclear Magnetic Resonance (NMR) spectra and provide critical insights into the structural and electronic environments of diverse chemical systems. However, their accurate computation is often constrained by the need for method-specific, analytical response implementation, and therefore is particularly challenging for non-variational, correlated wavefunction methods where analytical second derivatives are frequently unavailable. Here we present a scalable framework that computes NMR shielding tensors through finite
magnetic field differentiation of complex-valued, gauge-including atomic-orbital (GIAO) based self-consistent field (SCF) calculations. By combining hybrid MPI and OpenMP parallelization and resolution-of-identity (RI) approximation-based Coulomb (J) and Exchange (K) implementation and mixed numerical/analytical derivatives computational scheme, we achieve very good efficiency for hybrid density functional theory (DFT) NMR shielding, relative to existing state-of-the-art analytic implementations across realistic chemical systems of various sizes. Forward differentiation with optimal step sizes derived from rigorous error analysis retains favorable numerical errors much smaller than experimental uncertainty or intrinsic DFT errors. The results demonstrate that RI-accelerated finite
magnetic field calculations can obtain DFT-level NMR shielding constants very precisely, providing a scalable foundation for extensions to more advanced
quantum chemistry methods in future work.
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All authors Xiao Liu, Kaushik D. Nanda, Jiashu Liang, Martin Head-Gordon
Atmospheric and Oceanic Physics
AICON: An operational global machine learning weather forecasting model
Tobias Goecke, Marek Jacob, Florian Prill et al. (+9 more)
We introduce AICON, a global machine learning weather prediction (MLWP) model which generates forecasts at 13 km spatial resolution with a 3-hour time step, trained on the high-resolution, non-hydrostatic ICON-DREAM
dataset. AICON is in full operational use at Deutscher Wetterdienst since 2nd of March 2026. The model employs a graph neural network (GNN) architecture with an encoder-processor-decoder structure, where node updates are performed using a graph
attention mechanism. A key feature of AICON is its use of an icosahedral multi-mesh derived from the native grid of the ICON model, ensuring consistency with the training data. ICON's terrain-following vertical SLEVE coordinate is one of the major distinctions from existing emulators. AICON's training strategy prioritizes small-scale fidelity by avoiding autoregressive multi-step rollout and longer forecast horizons during training, a design choice motivated by the hypothesis that this approach preserves fine-scale features often damped in models optimized for longer-range forecasts. We describe the prognostic and diagnostic variables used for training, the transfer learning protocol employed to accelerate convergence, and the model's performance across a range of evaluation metrics. An extensive evaluation, including routine verification against observation, a tropical cyclone case and spectral analysis reveal the strengths and limitations in the representation of atmospheric variability across scales. Routine verification against observations demonstrates competitive skill relative to the operational ICON model, particularly for near-surface variables in the short to medium forecast range.
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All authors Tobias Goecke, Marek Jacob, Florian Prill, Michael Denhard, Felix Fundel, Jan Keller, Roland Potthast, Hendrik Reich, Britta Seegebrecht, Sven Ulbrich, Arianna Valmassoi, Sabrina Wahl
Optics
Ultrafast tuning of the focusing efficiency of a nonlinear atomically thin lens
Rahil Rezwan, Bernardo Dias, Tom Hoekstra et al. (+10 more)
Control over light focusing is paramount for optical and imaging systems. However, its implementation in active and integrated nanophotonic devices is hindered by the bulky and static nature of standard lenses. Here, we show that Fresnel Zone Plate Lenses (FZPL) based on a monolayer Transitional Metal Dichalcogenide are a viable solution to the challenges of miniaturization, integration, and active control of the focusing efficiency, featuring both ultrafast and large modulation depth. Using a monolayer $WSe_2$ FZPL, we demonstrate all-optical ultrafast ($\sim$ ps) modulation of the focusing efficiency close to $\sim$30%, that we achieve by exploiting the nonlinear
exciton-resonant enhancement and modulation of second harmonic generation.
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All authors Rahil Rezwan, Bernardo Dias, Tom Hoekstra, Mehmet At{\i}f Durmuş, Bauke van der Vorm, Till Weickhardt, Omid Ghaebi, Zhuoyuan Lu, Devapriyo Mithun, Carsten Ronning, Yuerui Lu, Jorik van de Groep, Giancarlo Soavi
Computational Physics · Cross-listed from cs.LG
Delayed Optimizer-State Transport Shapes Short-Horizon Training Decisions
Jinhui Guo
Adaptive optimizers retain gradient history in moment variables, allowing a local change in loss weighting to alter later updates. We examine whether this delayed transport is large enough to change prospective short-horizon decisions. On committed future-minibatch sequences, we differentiate eight-step AdamW trajectories through the complete model–optimizer state and select exposure-matched Math–Code loss schedules before independent evaluation. Across 12 unused 0.3M
Transformer histories, full transport lowers
token-disjoint loss relative to an optimizer-aware immediate derivative in 10/12 histories (mean benefit $4.71\times10^{-4}$; exact one-sided sign test, $p=0.0193$). The two controllers act equally often but select different schedules in 60/96 windows. Crossed checkpoint–future-path tests attribute this reordering to the interaction between optimizer state and near-future data, while an independent Ising–CNN experiment shows that deleting moment-state transport destroys accurate response prediction. Full-transport scores also concentrate exact-rollout winners in larger candidate libraries, focusing finite-amplitude evaluation on a shortlist. On these committed short paths, optimizer
memory and near-future data order are therefore actionable components of the training state, providing a mechanism-based criterion for when finite-horizon rather than one-step intervention is required.
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Fluid Dynamics · Cross-listed from cond-mat.soft
Phoretic interactions in two-medium wedge geometries
Abdallah Daddi-Moussa-Ider
We investigate the diffusiophoretic motion of a chemically isotropic active colloid in a three-dimensional wedge formed by two distinct fluid media, in the limit of vanishing Péclet and Reynolds numbers. The concentration field is obtained using the
Fourier-Kontorovich-Lebedev transform, yielding an exact representation for arbitrary wedge opening angles and interfacial contrasts. We introduce the interfacial parameter $\Gamma=(1-\lambda\ell)/(1+\lambda\ell)$, where $\lambda$ denotes the diffusivity contrast and $\ell$ the solute partition coefficient. For $\Gamma=\pm1$ and commensurate wedge angles, the solution reduces to finite image constructions, with distinct structures for even and odd commensurability. The general solution also recovers the planar-interface and semi-infinite-interface limits. The leading-order translational phoretic velocity is derived from the concentration field, revealing a strong interplay between wedge geometry and interfacial properties that governs both the magnitude and direction of particle motion. This work provides a framework for understanding and controlling phoretic transport in confined multiphase environments and offer a basis for extensions to finite-size geometries and mixed fluid–fluid and solid boundary conditions. Our results may find applications in the control of active-particle transport in confined multiphase environments, where interfacial properties and geometry can be exploited to tune phoretic motion.
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Instrumentation and Detectors
Fabrication and validation of a MEMS Electron Monochromator
M.J. Adriaans, J.P. Hoogenboom and A. Mohammadi-Gheidari
Electron monochromators are essential components for many applications in electron microscopy but are often large and complex to operate instruments. In prior work, we presented a concept for monochromation using the fringe fields around miniature electrostatic elements. This concept could be realized with a compact monochromator design that requires tuning of only 7 power supplies. In this manuscript, we present the fabrication using MEMS technology and experimental testing of such a miniaturized monochromator. The fabrication scheme involves Bosch deep reactive ion etching to shape lens and deflector electrodes and focused ion beam milling to create nanoscale apertures in a silicon nitride membrane. All elements are then coated, precisely aligned and, after stacking, wire bonded to connect to external power supplies. We use the assembled prototype to measure the electron-beam energy spread in a scanning electron microscope demonstrating the energy filtering capability of the device. These results highlight the possibilities for making miniaturized electron optics instruments using
alignment and stacking of different MEMS fabricated elements, representing an important step towards the development of compact, lightweight, high performance electron-beam instrumentation.
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Physics and Society
Why fragmented parliaments stop passing legislation: Opposition discipline and representation across four democratic institutions
Fuad Ali
Parliamentary systems pass more bills than presidential systems at baseline, but collapse to near-zero passage under party-system fragmentation. The literature offers three competing micro-explanations: coalition-formation failure, party discipline, and committee gatekeeping. These operate simultaneously in any real legislature, so observational studies struggle to separate their contributions. We present an
agent-based model that compares four democratic institutions: pure parliamentary, pure republican/presidential, premier-presidential (France), and president-parliamentary (Russia). Across four scenarios and N=200 seeds per
cell we report bootstrap confidence intervals, Morris screening, Sobol variance decomposition, mechanism ablations, and a hung-parliament variant comparison. Three findings emerge. First, government formation failure alone does not halt legislation: when a fragmented parliament reverts to personal voting, parliamentary passage (46.4%) is statistically indistinguishable from the presidential
benchmark (44.8%); collapse requires cohesive opposition obstruction, which drives passage to 0.05%. Second, disabling discipline restores fragmented passage to 46.7%, and the rescue magnitude is monotone across the four institutions in a pattern that survives varying the common discipline level. Third, the passage-representation tradeoff is a single spectrum: parliamentary maximises throughput at the cost of representational fidelity; republican maximises fidelity via the presidential veto; semi-presidential variants split the difference.
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Instrumentation and Detectors
Calibration of the discriminator threshold of the Amplifier-Shaper-Discriminator Chip for the Upgrade of the ATLAS Muon Drift-Tube Chambers for the High-Luminosity LHC
Oliver Kortner, Nick Meier and Julia Okfen
The read-out electronics of the ATLAS
muon drift-tube chambers will be upgraded for operation at the High-Luminosity Large
Hadron Collider. Part of the upgrade is the introduction of new amplifier-shaper-discriminator chips. This note presents the calibration of the discriminator threshold of the new chip in terms of primary electron signals using data from small-diameter
muon drift-tube chambers operated in a monoenergetic, high-energy
muon beam. The discriminator threshold intended for use in the ATLAS
muon spectrometer corresponds to the signal of 20 primary electrons.
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Computational Physics · Cross-listed from math.NA
Randomized Block Davidson Eigensolvers for Plane-Wave Density-Functional Theory
Moritz Gubler, Taejun Park, Augustin Bussy et al. (+4 more)
Iterative diagonalization is the dominant cost of plane-wave density-functional theory (DFT), with search-space orthogonalization scaling particularly quickly with problem size and the number of target states. We present a randomized block Davidson-type eigensolver that replaces Euclidean orthogonalization with randomized Gram-Schmidt in a sketched inner product, requiring only a single pass over the basis while keeping its conditioning bounded independently of the input vectors. This modification changes only the Rayleigh-Ritz step, which becomes a definite generalized Hermitian eigenproblem. Ritz extraction remains exact, preserving true Ritz pairs and the interlacing property that makes each band energy an upper bound on the true one. The method is implemented in mixed precision for CPUs and GPUs from a single Julia code, interfaces
matrix-free with DFTK, and is released in the open-source RandESC library. On sparse test problems with a fixed number of eigenpairs, the sketched solver overtakes its deterministic counterpart beyond
matrix dimensions of about $2\times 10^4$ and is $25\%$ faster at $5\times 10^5$. In full self-consistent field DFT calculations, however, both Davidson variants outperform the locally optimal block preconditioned conjugate gradient (LOBPCG) reference only by $5$ to $11\%$ in total time, while the additional benefit of sketching is limited. As the number of requested states grows with system size, orthogonalization savings are offset by the generalized eigenproblem. Therefore, the regime in which sketching pays off is set by how the number of wanted states scales with the problem dimension, not by the eigensolver as such.
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All authors Moritz Gubler, Taejun Park, Augustin Bussy, Johannes Laute, Nicola Marzari, Iurii Timrov, Laura Grigori
Optics
Phase-controlled super-modes in a `lossy' tri-waveguide coupled micro-ring resonator system
Tianrui Li, Max Goodwin, Matthew P. Halsall et al. (+1 more)
In coupled micro-ring resonator (MRR) systems, the coupling process plays a critical role in determining the optical response, yet models of these structures typically assume this process to be either lossless, or dissipative with either purely real or purely imaginary coupling rate, respectively. Dissipative coupling is contingent on having appropriately phase engineered structures with intricate coupling geometries, but systems exhibiting `lossy coupling', i.e., characterized by complex-valued coupling rates, have received comparatively little
attention. In this work, we investigate the effect of such `lossy' coupling, by modelling the optical response of a tri-waveguide coupled MRR system, using Temporal Coupled-Mode Theory (TCMT). The `lossy' coupling occurs via a common bus waveguide, positioned between a pair of MRRs, leading to the emergence of a pair of intrinsic resonances, whose frequency and linewidth may be tailored by controlling the respective coupling rates from either MRR. We develop these ideas, and by connecting the input (driving) waveguides, using a 3dB y-splitter, demonstrate a novel, coherently driven, lossy-coupled MRR, which exhibits either an absorptive or transparent resonance peak on demand by phase-controlled super-modes.
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All authors Tianrui Li, Max Goodwin, Matthew P. Halsall, Iain F. Crowe
Optics
AlGaAs nanowires as a universal platform for GaAs, InGaAs, and InAs quantum dots
Rohan Radhakrishnan, Rodion Reznik, Gilles Patriarche et al. (+5 more)
Optical
quantum dots (QDs) are central to photonic
quantum technologies, with fabrication approaches tailored to different spectral ranges. A key challenge, however, is the realization of a unified platform$\unicode{x2014}$a single growth method combined with a host material offering a designable architecture$\unicode{x2014}$enabling wavelength tunability across the full emission range and co-integration of multiple
quantum dots. Here, we introduce AlGaAs nanowires as a universal host for GaAs, InGaAs, and InAs QDs. Building on our previous demonstration of high-quality GaAs QDs, we realize InGaAs QDs with tunable emission by varying the growth duration from 2 to 5 s, achieving emission at 780 and 920 nm. We further showcase the platform's versatility for multi-
quantum-dot devices by co-integrating two InGaAs QDs, as well as GaAs and InGaAs QDs within a single nanowire. Finally, we initiate a first step toward pure InAs QDs by growing a pristine InAs segment on AlGaAs nanowires, demonstrating material compatibility.
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All authors Rohan Radhakrishnan, Rodion Reznik, Gilles Patriarche, Igor Ilkiv, Konstantin Kotlyar, Anna Andreeva, George Cirlin, Nika Akopian
Space Physics
Comprehensive solar eruption analyses enabled by the tools of the SOLER project
Nina Dresing, Jan Gieseler, Markus Baumgartner-Steinleitner et al. (+26 more)
Solar eruptions comprise of a multitude of phenomena such as
flares, coronal mass ejections (CMEs), large-scale coronal waves,
radio bursts, and energetic particles traveling through interplanetary space. These phenomena are observed with a variety of instrumentation, including remote sensing and in-situ detectors. Obtaining a global understanding of a
solar eruption often requires the analysis of various of these different
datasets, including a multitude of analysis and modeling tools and a wide range of expertise. Usually, such a comprehensive analysis can only be achieved by a skilled and broad team. The Energetic
Solar Eruptions: Data and Analysis Tools (SOLER) project aims at creating a comprehensive analysis platform for the study of
solar eruptions that allows a single user to easily apply analysis methods addressing various counterparts of the
solar event. Therefore, each partner of the project developed Python-based software, including interfaces in the form of Jupyter Notebooks, which provides application examples and concise step-to-step documentation. In this paper we introduce the comprehensive
solar-eruption-analysis infrastructure developed within the SOLER project. We explain where to find the software, how to use it, and give dedicated use-case examples of how to employ selected tools in a combined manner.
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All authors Nina Dresing, Jan Gieseler, Markus Baumgartner-Steinleitner, Carine Briand, Karin Dissauer, Annamaria Fedeli, Robert Jarolim, Jaclyn T. Lang, Diana E. Morosan, Jake A. J Mitchell, Christian Palmroos, Jens Pomoell, Jinge Zhang, Otso Santala, Astrid M. Veronig, Laura Vuorinen, Alexander Warmuth, Oliver Flor, Myrthe Flossie, Emilia K. J. Kilpua, Werner Pötzi, Daniel J. Price, Antonio Gomes, Emil J. Hotti, Ruth A. Hyndman, M. Liebel, Amaia Razquin, Song Tan, Ramio Vainio
Fluid Dynamics
Feedback control of vortex shedding using data-driven modelling
Jack Proudfoot, Chris J. Nicholls, Brian M. T. Tang et al. (+1 more)
This paper details the data-driven modelling and feedback control of
vortex shedding past a circular cylinder at a Reynolds number of Re = 1000. We study the effect of varying the order of the reduced model for control design purposes and demonstrate that higher orders can lead to lower suppression of
vortex shedding. We use the Bode integral
theorem and a frequency-domain interpretation to show that this drop in performance is, in part, due to the classical “waterbed effect”, which increases sensitivity in frequency bands of unmodelled dynamics. Training data from 2D unsteady simulation is used to obtain linear reduced-order state-space models of the system via dynamic mode decomposition with control. Using only lift measurement, we show that at least a 4th-order model is required for an LQG controller to suppress
vortex shedding, with the best performance achieved with as few as 9 modes, whilst higher-order (>14) controllers show a significant decrease in performance. We study the influence of external disturbances, noise rejection, and parameter uncertainty on controller performance. A 28.6 dB reduction in lift coefficient variance is achieved, resulting in a 26% reduction in drag. We further show that, for control design purposes with practical actuation bandwidth, the closed-loop control delivers a significant 13.7% drag reduction within 3D DDES, despite having been trained with 2D URANS and therefore argue that 2D URANS simulation is sufficient for reduced-order model generation and control design.
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All authors Jack Proudfoot, Chris J. Nicholls, Brian M. T. Tang, Marko Bacic