Fluid Dynamics
Explainable quantum-compressed machine learning for complex fluid flows
Xiao Xue, Maida Wang, Mingyang Gao et al. (+2 more)
Machine-learning surrogates of physical systems face a paradox: explainable models facing the challenge of expressivity to capture complex nonlinear flows, whereas expressive deep surrogates match high-fidelity simulations only through massive parameterisations that turn the learned dynamics into a black box. Here, we introduce
quantum-compressed machine learning (QCML), which resolves this tension by compressing the latent propagator of a flow surrogate from $524{,}288$ trainable parameters to no more than $8$. This parameter reduction brings the learned dynamical law to the parameter scale of a physical constitutive relation rather than a black-box neural network, making the surrogate directly interpretable and controllable without sacrificing expressivity. The compression is realised by a structured
quantum circuit whose
unitary propagator constrains the latent spectrum to the unit circle exactly and by construction, replacing exponential error growth with linear accumulation over autoregressive rollouts. Classical regularisation only approximates this constraint: even a
quantum-inspired classical baseline penalised towards unitarity collapses within one Lyapunov time on turbulent channel flow, whereas QCML remains stable over the full rollout. Shared phase and coupling angles parameterising the
circuit correspond directly to modal frequencies and inter-mode interactions, giving the learned dynamics a physical interpretation in spectral space. On two patient-specific cardiovascular
benchmarks, the structured QCML propagator matches the predictive accuracy of its classical counterpart on surface pressure spectra, pressure drop, and wall shear stress. These results establish QCML as a working component of scientific machine learning and a concrete contribution towards practical
quantum advantage in real-world prediction.
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All authors Xiao Xue, Maida Wang, Mingyang Gao, Minh Chung, Peter V. Coveney
Accelerator Physics
X-Ray Transition Radiation
Grigor M. Garibian and Chi Yang
The monograph is devoted to theoretical and experimental studies of transition radiation produced by fast charged particles traversing media with interfaces. Particular
attention is paid to X-ray transition radiation (XTR) generated at a single interface as well as in a single plate or in a stack of plates. The foundations of the general theory of transition radiation are presented, and the results of experimental studies of XTR properties are given together with a comparison with theoretical predictions. TRDs of high-energy particles used at modern accelerators and in
cosmic-ray physics are described.
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History and Philosophy of Physics · Cross-listed from astro-ph.SR
Echoes of Star Stories: Integrating Indigenous narratives into modern stellar astrophysics
Dionysios Gakis
Indigenous narratives have long preserved observations of celestial phenomena, offering insights that resonate with modern astrophysical research. Deeply embedded in cultural traditions, these stories describe events such as
stellar variability,
supernovae, eclipses, and planetary
alignments. Indigenous communities have also used the
stars for
navigation and calendar systems, reflecting a sophisticated understanding of celestial patterns. These narratives not only complement historical records but offer human-centric perspectives on
stellar life cycles that often parallel modern models. Drawing from traditions from diverse Indigenous communities - including Aboriginal Australians, Pueblo peoples, Inuit, and Polynesians - this paper highlights the profound connections between Indigenous knowledge and
stellar astrophysics. Integrating these traditions acknowledges their value, safeguards their relevance in the Space Age, and fosters mutual learning through cross-cultural collaboration. We explore how such narratives can enrich education, public engagement, and even inspire scientific hypotheses, bridging cultural heritage and modern astrophysics.
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Physics and Society
Reconstructing the Probability Measure of a Multi-group Curie-Weiss Model with Interacting Groups
Miguel Ballesteros, Gerardo Franco Cordova, Fedro Guillen et al. (+1 more)
We study the problem of reconstructing the probability measure of a multi-group version of the Curie-Weiss or mean-field model of ferromagnetism from a sample of the voting behaviour the population. While originally used to study phase transitions in statistical mechanics, the Curie-Weiss or mean-field model has been applied to study phenomena where many
agents interact with each other, in particular in case of a heterogeneous population with identifiable subpopulations. The degree of social cohesion within social groups manifests in the way the members of the group influence each others' decisions as well as how they behave under outside influence from voters belonging to another group. Contrary to single-group Curie-Weiss models, here we have a larger number of coupling parameters which have to be estimated. While the maximum likelihood
estimator of the coupling parameters has desirable statistical properties in theory, computational challenges make applications to larger populations impractical. Therefore, we analyse an
estimator based on asymptotic approximations to the behaviour of the Curie-Weiss model valid for large populations. Due to the wide applicability of models such as Curie-Weiss, the
estimator is potentially useful in disciplines such as political science, sociology, automated voting, and preference aggregation.
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All authors Miguel Ballesteros, Gerardo Franco Cordova, Fedro Guillen, Gabor Toth
Optics
An integrated all-van der Waals nanobeam laser
Aris Koulas-Simos, Pietro Metuh, Athanasios Paralikis et al. (+7 more)
Transition-metal dichalcogenides offer a promising platform for integrated coherent light sources, yet lasing has largely relied on hybrid photonic architectures without direct
quantum-optical verification. Here, we demonstrate an all-van der Waals (all-vdW) high-$\beta$ nanobeam
laser based on a WS$_2$/MoSe$_2$/WS$_{2}$
heterostructure, with the MoSe$_2$ monolayer directly integrated in the WS$_{2}$-based optical resonator for optimal gain-mode overlap. The devices exhibit efficient
exciton-cavity coupling at cryogenic temperatures, strongly directional and linearly polarized emission, soft nonlinear input-output characteristics and linewidth narrowing, enabling lasing operation with $\beta$ near unity. Excitation-power-dependent
photon-autocorrelation measurements reveal a transition from thermal to Poissonian
photon statistics, with $g_{\mathrm{peak}}^{(2)}(0)$ decreasing from $(1.28\,\pm\,0.09)$ near threshold to $(1.07\,\pm\,0.07)$ above threshold, directly verifying lasing operation. Furthermore, temporal broadening of the autocorrelation uncovers fluctuation-dominated lasing dynamics. These results establish all-vdW
heterostructures as a highly attractive platform for integrated coherent light sources in layered-material photonic architectures and scalable
quantum-photonic
circuits.
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All authors Aris Koulas-Simos, Pietro Metuh, Athanasios Paralikis, Kartik Gaur, Maximilian Klonz, Imad Limame, Bárbara L. T. Rosa, Chirag C. Palekar, Battulga Munkhbat, Stephan Reitzenstein
Atomic Physics · Cross-listed from quant-ph
Strategic Plan for Neutral Atom Quantum Computation
Adrian J. Menssen, Tout Wang, Michael Gullans et al. (+53 more)
We present a strategic plan for neutral atom
quantum computation, bringing together hardware development and theory advancements to achieve the goal of practical
quantum advantage. The concept of practical
quantum advantage is defined, along with how to verify claims of advantage, and approaches to designing
quantum algorithms that deliver practical advantage. Future directions for neutral atom
quantum processor hardware are described: scaling-up system size,
Qubit encodings and atomic platforms, going further below threshold with neutral-atom logical-
qubit performance, continuous reloading of
qubits, and fast readout. We also explore opportunities for scalable integrated photonic control technologies. Alongside hardware advancements, new developments in
quantum error correction and compilation of
quantum circuits are proposed. Finally, we examine the opportunity of networking multiple neutral atom
quantum processors together to perform distributed
quantum computing and overcome possible limitations of a single system.
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All authors Adrian J. Menssen, Tout Wang, Michael Gullans, Tom Manovitz, Jacob M. Taylor, Jason Cong, Josiah Sinclair, Ziv Aqua, Daniel J. Blumenthal, J. Pablo Bonilla Ataides, Johannes Borregaard, Antoine Browaeys, Paola Cappellaro, Soonwon Choi, Alexandre Cooper, Robin Côté, Jacob P. Covey, Alexandre Dauphin, Ivana Dimitrova, Matt Eichenfield, Dirk Englund, Jacob Freedman, Akihisa Goban, Brandon Grinkemeyer, Andi Gu, Ruonan Han, Dominik Hangleiter, Aram W. Harrow, Liang Jiang, Eun-ah Kim, Felix W. Knollmann, Aleksander Kubica, Thierry Lahaye, Lucas Lassabliere, Joonho Lee, Bingzhao Li, Mo Li, Wan-Hsuan Lin, Mikhail D. Lukin, Varun Menon, Thomas Propson, Akbar Safari, Mark Saffman, Pascal Scholl, Alexander Schuckert, Giulia Semeghini, Jonathan Simon, David Spierings, Daniel Bochen Tan, Shai Tsesses, Vladan Vuletic, Hanrui Wang, Hanyu Wang, Susanne Yelin, Johannes Zeiher, Hengyun Zhou
Instrumentation and Detectors
Disentangling mixed neutron fields: multi-source identification from few detected events
David Breitenmoser, William Heriot, Peter Marleau et al. (+2 more)
Identifying
neutron-emitting materials is central to
nuclear nonproliferation, safeguards,
nuclear forensics, and emergency response, yet remains difficult when several sources contribute simultaneously: relevant fission, $(\alpha,\text{n})$, and fusion sources emit broad, strongly overlapping energy distributions, and the associated spectral inversion is severely ill-conditioned. Here we demonstrate quantitative identification of mixed
neutron fields directly from scatter-based (
recoil) spectroscopy measurements, together with simultaneous estimation of the emission rate of each contributing source and a rigorous statistical confidence level for every candidate source combination. Using a compact $21.6\,\mathrm{cm}^3$ organic-glass scintillator spectrometer, we correctly identify Cf-252, a deuterium–deuterium (DD)
neutron generator, and their mixture with decisive statistical support ($>\!4\sigma$), and further resolve a weak deuterium–tritium contaminant in the nominal DD generator field. High-fidelity Monte Carlo simulations spanning exhaustive single-, two-, and three-source mixtures show that identification requires remarkably little information: between $\mathcal{O}(10^1)$ and $\mathcal{O}(10^6)$ detected
recoil events, set primarily by spectral similarity, mixture complexity, and emission-rate imbalance. For the compact spectrometer used here, this corresponds to acquisition times as short as a few minutes. These results substantially extend the operational reach of simple single-volume
neutron spectrometers, enabling rapid, quantitative, and confidence-calibrated attribution of complex
neutron fields in field-deployable instruments.
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All authors David Breitenmoser, William Heriot, Peter Marleau, Shaun D. Clarke, Sara A. Pozzi
Atomic Physics
Experimental realization of a rotating radio-frequency ion trap for precision metrology
Sun Yool Park, Anzhou Wang, Kia Boon Ng et al. (+7 more)
We discuss the experimental realization of the rotating
radio-frequency (rrf) trap, proposed by Hasegawa and Bollinger [Phys. Rev. A 72, 043403 (2005)]. Compared to a traditional linear rf (lrf) Paul trap, the rrf trap is a closer analogy to the popular mechanical lecture demonstration for a Paul trap. In an ion trap with reslistic, non-ideal electrode geometry, the rrf trap averages over angular variations in the effective potential. This averaging provides more uniform confinement and reduces ion loss at equal confinement strength compared with the lrf trap. This feature makes the rrf trap configuration advantageous for precision metrology application, such as electron electric dipole moment (eEDM) measurements.
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All authors Sun Yool Park, Anzhou Wang, Kia Boon Ng, Patricia Hector Hernandez, Addison Hartman, Tuan Anh Nguyen, Rohan Kompella, Michail Athanasakis-Kaklamanakis, Jun Ye, Eric A. Cornell
Chemical Physics
Axel Dieter Becke: Not just the "B" in "B3LYP"
Mark Earl Casida
There is hardly anyone doing electronic structure calculations on molecules who has not used the famous B3LYP functional. Many will even know that the "B" in B3LYP stands for Becke, but how many know the history of the B3LYP functional? Behind this functional, Axel Becke has two of the most highly cited papers in both chemistry and physics—both with several tens of thousands of citations—and many less cited, but arguably equally important accomplishments, that led to B3LYP, as well as continued developments in building ever better density-functional approximatons after the appearance of B3LYP. Axel has received much recognition and many honors for his work. In particular, in 2015, Axel was awarded Canada's highest honor for science and engineering—namely the Gerhard Herzberg Gold Medal. Achievements like this require more than "just" brilliance; they require being the right person in the right place at the right time. I will argue that Axel did indeed fulfill these requirements. At the same time, I will try to give some
flavor of the field of electronic structure as seen through my own eyes and those of a few others during the period from the beginning of Axel's career up until very recent times.
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Atmospheric and Oceanic Physics
Diffusion posterior sampling enables zero shot kilometre scale wind forecasting over complex terrain
Yujiang Cai, Ya Wang, Shuanglei Feng et al. (+6 more)
Reliable prediction of near surface wind over complex terrain is limited by the mismatch between the spatial resolution of operational forecasts and terrain controlled local wind variability. Here, we develop KiloGen, a
diffusion posterior sampling framework for kilometre scale wind forecast enhancement. KiloGen learns a high resolution vector wind prior from Weather Research and
Forecasting (WRF) model simulations and constrains posterior sampling with 25 km forecasts from the European Centre for Medium Range Weather Forecasts (ECMWF) at inference time. This formulation avoids paired ECMWF and WRF training samples and an explicitly learned mapping from coarse to fine resolution. Applied over Shanxi, China, a region with complex mountainous terrain, KiloGen reconstructs terrain organized wind structures and restores high wavenumber variability while retaining the large scale
evolution of the operational forecast. Station verification shows that KiloGen achieves the lowest overall wind speed root mean square error (RMSE) among the evaluated products, with larger benefits at elevated and topographically complex sites. The improvement is strongest under strong wind conditions, reducing RMSE by approximately 10% for observed winds above 20 m s^-1. Across 13 distinct strong wind events, KiloGen improves upon the 0.25 degree ECMWF forecast in all cases and outperforms the 0.1 degree ECMWF forecast in most cases. These results show that
diffusion posterior sampling provides an effective approach for terrain aware kilometre scale wind forecast enhancement.
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All authors Yujiang Cai, Ya Wang, Shuanglei Feng, Bo Wang, Yiming Liu, Hui Yuan, Xinyi Sun, Haijie Li, Shenming Fu
Optics · Cross-listed from quant-ph
Rack-integrated quantum dot-based source of single and entangled photons at telecom C-band
Michal Vyvlecka, Raphael Joos, Benjamin Breiholz et al. (+8 more)
For
quantum light sources in everyday telecommunication networks,
quantum science needs to be fully transformed into
quantum technology. The first necessary step to move outside a well-controlled lab environment requires the use of
quantum light sources operating in the technologically relevant telecom O- and C-band. This can be provided using epitaxial
quantum dots as deterministic sources of
quantum light. Particularly intriguing is that emitters operating at telecom wavelengths are rapidly catching up with their short wavelength counterparts in terms of performances. Here, we make a decisive step forward in the development of
quantum communication networks: a state-of-the-art source of
quantum light, a
semiconductor quantum dot (QD), with record coincidence rate for entangled
photon emission in the telecom C-band, is operated inside an optimized rack-based setup. This setup includes a tunable pulsed
laser for the QD excitation (from quasi- to fully resonant excitation), all optics for the excitation filtering, and QD signal coupling into single-mode fibers. Overall, the setup allows for above $50\%$ transmission for both
exciton and biexciton
photons. These results show that
quantum dots-based telecom light sources can now be transported and integrated into existing fiber infrastructures, an important step to demonstrate the feasibility of the upcoming
quantum internet.
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All authors Michal Vyvlecka, Raphael Joos, Benjamin Breiholz, Emma Marmasse, Anna Friederike Köhler, Ponraj Vijayan, Tobias Huber-Loyola, Sven Höfling, Michael Jetter, Simone Luca Portalupi, Peter Michler
Chemical Physics
Approximating committor functions: Objective functions and training data sampling
Thomas Pigeon, Gabriel Stoltz and Tony Lelièvre
Many molecular dynamics simulations aim at studying transitions between two states (from reactants to products). In this context, the committor function (which gives for a given molecular configuration the probability to reach the product state before the reactant state) is a pivotal quantity, in particular because it is the optimal importance function for rare event simulation methods such as importance sampling or splitting techniques. These methods are used to sample the reactive path ensemble, and estimate for example the transition rate. However, learning such a function is generally a challenging task due to the high dimensionality of the configuration space. In this work, after reviewing the existing methodologies to construct approximate committor functions, a new loss function based on the application of Itō's formula is proposed to learn the committor function with a minimization procedure on the parameters of a neural network. After comparing this novel approach to existing procedures on the Müller–Brown potential, we introduce a coupling strategy with the Adaptive Multilevel Splitting method to better approximate the committor function using a better sampling of the reactive trajectories. This methodology in which the committor function is iteratively learned only requires initially the knowledge of the reactant and product states.
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Computational Physics
Cycle-Consistent and Uncertainty-Aware Neural Surrogates for Tokamak Edge Plasmas
Abdourahmane Diaw, Sebastian De Pascuale, Jae-Sun Park et al. (+3 more)
The boundary and divertor
plasma govern how a tokamak exhausts power and particles, setting heat fluxes, target conditions, and the onset of detachment. Predicting these quantities is essential for operating current and future devices, but edge simulations that resolve them are too slow for parameter scans, optimization, or real-time control. Machine-learning surrogates offer a fast alternative, yet most are forward-only: they cannot recover input parameters from observations or assess the reliability of their predictions. We introduce a cycle-consistent neural surrogate for edge
plasmas, combining a conditional U-Net forward model with an optimization-based inverse method built on the frozen forward network. The forward model maps five control parameters to two-dimensional
plasma-state fields on the SOLPS-ITER mesh; the inverse method enforces consistency between forward and inverse predictions, a self-supervised quality check needing no ground-truth labels at inference. An ensemble of multilayer perceptrons also predicts electron temperature and density profiles at the outboard midplane and divertor targets, with uncertainty estimates that flag where more simulations are needed. The forward model achieves normalized root-mean-square errors below 2.6% and Pearson correlations above 0.95 for all fields. Cycle-consistency regularization raises the average cyclical $R^2$ from 0.59 to 0.99 without degrading forward accuracy and enables recovery of the core fueling rate; all five control parameters are recovered with Pearson $r\ge0.97$. A $k$-d tree warm start yields a database completion rate above 95%, versus roughly 30% outright failures when cold-started. With about $4\times10^6$ parameters, the model produces full 2D predictions in milliseconds, five to six orders of magnitude faster than SOLPS-ITER, enabling real-time control, parameter scans, uncertainty analysis, and digital twins.
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All authors Abdourahmane Diaw, Sebastian De Pascuale, Jae-Sun Park, Ivan Paradela Perez, Jeremy D. Lore, Stefan Dasbach
Chemical Physics
Towards more accurate natural orbital functional approximations: including 4-index cumulant contributions
Valerii Chuiko, Paul W. Ayers and Eduard Matito
Accurate modeling of bond breaking remains a central challenge for reduced density
matrix functional theory (RDMFT). Although some modern functionals can yield reasonably accurate dissociation energies, they often fail to reproduce key properties of the dissociated fragments, such as a vanishing fragment population covariance (also known as the delocalization index) and the correct total
spin angular momentum of each fragment (local
spin). In this work, we revisit the construction of natural orbital functionals by correcting the cumulant contribution produced by the PNOF5 functional. Our method enforces known contributions of the cumulant to local
spin fragments and the delocalization index at the dissociation limit. We obtain the closest cumulant consistent with these physically motivated constraints and subsequently purify the corresponding one- and two-electron reduced density
matrices by imposing the standard $P, Q, \text{and } G$ $N$-representability conditions. The resulting functional yields improved behavior in strongly correlated regimes. Benchmarking on the dissociation of the singlet states of \ce{N2}, \ce{NO+}, \ce{O2}, \ce{S2}, and \ce{CO} shows that in the dissociation regime the energies computed from the updated cumulant exactly reproduce the complete active space self-consistent field (CASSCF) energies. We further analyze the limitations of the approach and identify scenarios in which the current approach performs poorly. This work provides a pathway for systematically improving natural orbital functionals to achieve reliable bond-breaking calculations within RDMFT.
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Chemical Physics
Polaritons of inherently interacting molecules
Gábor J. Halász, Csaba Fábri, Lorenz S. Cederbaum et al. (+1 more)
We investigate the absorption spectra of molecular ensembles strongly coupled to a Fabry-Pérot cavity and establish the microscopic origin of collective polaritonic bands. We show that long-range intermolecular interactions generate a large
manifold of hybrid molecular-photonic states, even without disorder, vibrations, or thermal effects. The observed polariton bands are collective envelopes of these microscopic states, making photonic and molecular spectra strongly dependent on molecular arrangement. Our findings identify long-range intermolecular interactions as a key ingredient of molecular cavity QED.
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All authors Gábor J. Halász, Csaba Fábri, Lorenz S. Cederbaum, Ágnes Vibók
Atmospheric and Oceanic Physics
Flexible generation of daily Earth system model projections across radiative forcing scenarios
Yu Huang, Sebastian Bathiany, Shangshang Yang et al. (+3 more)
Earth system model (ESM) projections of the
climate system's response to anthropogenic forcing are central to assess the impacts of
climate change and inform adaptation and mitigation policies. However, given their high computational cost, projections are only made for a limited set of standardized forcing scenarios with limited temporal extent, such as the Shared Socioeconomic Pathways (SSPs), the spatiotemporal resolution remains too low for direct impact assessments, and uncertainties cannot be comprehensively quantified. Recent data-driven models offer efficient and accurate high-resolution simulations for weather prediction, but cannot extrapolate to future greenhouse gas concentrations because they cannot capture the responses to unprecedented forcing, limiting their value for
climate change projections. Here, we combine response theory with a tailored generative machine learning framework to address this challenge. Our approach extracts the physical forced response to radiative forcing from monthly low-resolution ESM fields, and uses this response to guide a generative model to infer consistent daily global high-resolution temperature and precipitation projections. Our probabilistic approach generalizes across ESMs and provides long-term, bias-corrected responses to radiative forcing at high spatiotemporal resolution. It efficiently generates large ensembles needed for uncertainty quantification, effectively fills the gaps between existing SSPs, and readily extends
climate projections to 2300 and beyond. Our framework hence complements ESM projections by providing efficient, stable, and high spatiotemporal resolution long-term
climate projection ensembles across emission scenarios, enabling detailed impact assessment and exploration of long-term
climate commitment.
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All authors Yu Huang, Sebastian Bathiany, Shangshang Yang, Philipp Hess, Michael Aich, Niklas Boers
Chemical Physics
Graph Neural Network Force Fields (GPTFF-mol) for Organic Molecules from Optimization Trajectories (OpenGEM26)
Yifan Huang, Fankai Xie, Jiangnan Zheng et al. (+3 more)
Density functional theory (DFT) serves as a reliable tool for atomistic molecular simulations, while machine learning potentials have become powerful complements to balance accuracy and efficiency. In this work, we release OpenGEM26 (Open Generated Ensemble of Molecules, 2026), a large-scale
dataset comprising 200,000 unique molecules and 4.4 million conformations composed of H, C, N, O, S and Cl with up to ten heavy atoms. All calculations are carried out at the {\omega}B97X-D/Def2-SVP and Def2-TZVP levels with dispersion corrections, and complete structural optimization trajectories and abundant non-
equilibrium structures are recorded. Statistical analyses confirm that this
dataset covers a broader conformational space than QM9 in terms of energy, bond lengths and bond angles. A graph neural network-based potential GPTFF-mol is trained using the new
dataset, achieving an energy mean absolute error of 16 meV/molecule, which is equivalent to 0.82meV/atom, and superior force prediction performance compared with ANI-2x. Validated by butane rotation and keto-enol tautomerization tests, the model accurately describes molecular dynamical behaviors and reaction barriers at distorted geometries. This work provides a high-quality resource and robust ML potential for efficient simulations of sulfur- and chlorine-containing organic molecules.
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All authors Yifan Huang, Fankai Xie, Jiangnan Zheng, Tenglong Lu, Sheng Meng, Miao Liu
Plasma Physics
Langmuir probe and infrared thermography measurements of wide and narrow heat flux profiles in the ST40 tokamak
T. Brewer, X. Zhang, C. Marsden et al. (+11 more)
Very narrow heat flux profiles have been observed on ST40 with decay lengths in the near scrape-off-layer (SOL) of $\lambda_{q,near}<$~1~mm in H-mode
plasmas. Measurements from divertor Langmuir probes are compared with an infrared (IR) thermography system for upper-single null diverted
plasmas in L-mode and ELM-free H-mode. SOL current to the grounded divertor targets is measured from the Langmuir probes with profiles exhibiting a similar exponential decay to $\lambda_{q,near}$ suggesting the near SOL heat flux is related to enhanced electron current to the divertor. Inclusion of electron current contributions to the heat flux transmission coefficient is crucial in capturing similar narrow profiles to those from the IR thermography system. Ongoing upgrades to ST40 will enable more investigations on SOL power decay lengths on inboard and outboard targets in double and single null configurations.
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All authors T. Brewer, X. Zhang, C. Marsden, A. Scarabosio, J. Bryant, P. F. Buxton, M. Fontana, T. Gray, N. Lopez, L. Martinelli, A. Rengle, E. J. C. Tinacba, E. Vekshina, H. V. Willett
Physics Education
Embodied inquiry with AI as facilitator: an exploratory case study
Eugenio Tufino and Paola Damiani
Generative AI is entering science education at a time when the
embodied education community is asking what such systems cannot do. Rather than asking whether AI can understand the body, this exploratory case study asks where a
language-based AI can stand within an inquiry activity without displacing
embodied experience. University students in a Master's course in physics education investigated the statics of fluids following the ISLE approach (Investigative Science Learning Environment) in a two-phase design: students first built the buoyancy model with their own hands, without AI; a purpose-configured AI assistant then facilitated the application of the model to a new phenomenon. We discuss what a
language-based facilitator cannot reach and the value of a design in which AI complements
embodied inquiry rather than replacing it.
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Instrumentation and Detectors
Front End Amplifiers for Simultaneous Dual Readout of SiPM Sensors
Lucas Finazzi, Felipe Soriano, Leandro Gagliardi et al. (+4 more)
In this work, we present two fully open Analog Front End (AFE) designs for the simultaneous readout of the standard and fast outputs of ONSemi MicroFC-10035 Silicon Photomultipliers and report their main figure-of-merit parameters. The standard output AFE has a 1 p.e. amplitude of $(394 \pm 1)$ mV, which results in a Signal-to-Noise ratio of 30 dB. In addition, the fast AFE has a rise time of $(1.3\pm 0.1)$ ns and a median electronic jitter of $34^{+7}_{-5}$ ps, resulting in an excellent timing performance. Using these amplifiers for simultaneous dual readout, we demonstrate a proof-of-concept application, in which fast output timing information is used to suppress correlated noise events or pileup events present in the standard output charge measurements. This suppression results in a reduction of non-
prompt correlated noise (delayed crosstalks and afterpulses) in dark conditions and an increase up to $\sim$14 in single
photon discrimination under a continuous incident
photon rate of 7.8 MHz/mm$^2$. These results show that dual SiPM readout provides a practical way to remove correlated noise or pileup contamination in standard output charge measurements on an event-by-event basis.
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All authors Lucas Finazzi, Felipe Soriano, Leandro Gagliardi, Alexis Luszczak, Hugo Mériaux, Gabriel Sanca, Federico Golmar
Classical Physics
Spatiotemporal Vortex Rings Induced by Spatiotemporal Coupling
Zhiling Zhou, Wei Zhong, Tong Fu et al. (+4 more)
Vortices and
vortex rings are topological structures that arise in various physical systems. However, the generation of spatiotemporal
vortices (STVs) and
vortex rings (STVRs) has so far relied on complex, often active wavefront modulation. We theoretically and experimentally demonstrate that spatiotemporal coupling can drive unstructured wave packets to form
vortices upon scattering from simple obstacles. The resulting STVs and STVRs possess controllable topological charges and excellent propagation stability. These findings reveal a fundamental mechanism for spatiotemporal singularity formation and provide a universal route to structured-wave generation.
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All authors Zhiling Zhou, Wei Zhong, Tong Fu, Wanyue Xiao, Zhongming Gu, Jie Zhu, Shubo Wang
Fluid Dynamics · Cross-listed from cond-mat.soft
A single length scale rules ballistic aggregation: travels of a droplet train
Nathan Vani, Stefan Kooij, Aritro Mukherjee et al. (+3 more)
Ballistic aggregation is a canonical non-
equilibrium process, relevant across scales from granular gases to planetary
accretion. Collisions are driven by differences in velocities, building up persistent correlations between neighbors. Here, we provide the first experimental realization of one-dimensional ballistic aggregation in a train of droplets formed by the breakup of a
liquid jet. Experiments and simulations confirm the analytically predicted scaling, with the global process shown to be governed by a single length scale. While air drag inverts the sign of neighbor velocity correlations, a 1D ordering constraint protects bulk characteristics of ballistic aggregation such as the scaling exponent and the shape of the large mass tail. More broadly, our results show that Smoluchowski-like mean-field descriptions fail when collisions carry directional
memory – as demonstrated here for jet-generated sprays.
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All authors Nathan Vani, Stefan Kooij, Aritro Mukherjee, Antoine Parrenin, Cees J.M. van Rijn, Daniel Bonn
Plasma Physics · Cross-listed from astro-ph.SR
Collisionless stationary states of a stratified plasma in an expanding magnetic tube with stochastic heating
Luca Barbieri, Pascal Démoulin and Daniel Verscharen
We investigate the collisionless kinetic structure of the upper
solar atmosphere in an expanding
magnetic field. Building on established velocity-filtration models, we extend the
stochastic multi-temperature framework developed in previous works by including
magnetic-field expansion and
magnetic-moment conservation.
Stochastic heating generates a non-Maxwellian boundary distribution through the superposition of particle populations associated with different temperatures. We consider a stationary two-component
plasma confined within an expanding
magnetic flux tube and subject to
gravity, self-consistent electrostatic interactions, the Pannekoek–Rosseland electric field, and
magnetic-moment conservation. Starting from the Vlasov equation, we derive fully analytical expressions for the distribution functions, density, and parallel, perpendicular, and total temperature profiles. The combined conservation of energy and
magnetic moment generates a loss-cone distribution, reducing the density relative to the unmagnetized case and producing temperature anisotropy. For a single-temperature boundary, the competition between
gravity and
magnetic-moment conservation produces a maximum in the parallel temperature, for which we derive and numerically validate analytical scaling laws. With
stochastic heating, gravitational filtering enhances the contribution of hotter populations at coronal heights, while
magnetic-moment conservation amplifies the velocity-space anisotropy. Our analytical solution provides a collisionless
benchmark for future kinetic models incorporating more realistic
magnetic-field geometries, Coulomb collisions, and turbulent particle scattering.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Lifetime effects and satellites in the photoelectron spectrum of platinum metal
Prajna Bhatt, José Julio Gutiérrez Moreno, Laura E. Ratcliff et al. (+9 more)
This work presents a comprehensive investigation of the electronic structure and many-body photoemission effects in metallic platinum using reflection high-energy electron energy-loss spec- troscopy (RHEELS), soft X-ray photoelectron spectroscopy (SXPS), and hard X-ray photoelectron spectroscopy (HAXPES), supported by ab initio calculations. Shallow and deep core state spectra enable the systematic characterisation of intrinsic line-shape asymmetries and satellite structures. Correlation of photoelectron satellites with RHEELS loss features allows the assignment of inter- band transitions, surface and bulk plasmons, plasmonic overtones, and semi-core ionisation losses across the Pt spectrum. Several previously unresolved satellite features and
spin-orbit splittings are identified and discussed. Comparison of experimental valence band spectra with orbital-projected densities of states calculated using ab initio density functional theory (DFT) and G0W0 approaches, with and without
spin-orbit coupling, demonstrates the critical role of relativistic effects in reproducing the Pt valence electronic structure. Together, these results establish a unified, internally consistent spectroscopic reference for metallic platinum, providing a robust framework for interpreting photoelectron spectra of Pt-containing catalysts, electronic materials, and related 5d transition metal systems.
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All authors Prajna Bhatt, José Julio Gutiérrez Moreno, Laura E. Ratcliff, Aysha A. Riaz, Charlotte. M. L. André, Ann S. Y. Lu, Robert G. Palgrave, Andrei Gloskovskii, Christoph Schlueter, Pardeep K. Thakur, Tien-Lin Lee, Anna Regoutz
Computational Physics · Cross-listed from math.NA
An unfitted boundary algebraic equation method with Calderón preconditioning for 2D Stokes flow in irregular geometry
Wenjun Ying and Qing Xia
We present an unfitted boundary algebraic equation method for the two-dimensional exterior/interior Stokes equations on a staggered MAC grid. By constructing an explicit free-space pair of velocity and pressure
lattice Green's functions (LGFs) from free-space Laplace LGFs, we represent homogeneous fields using sources supported exclusively on thin staggered boundary layers. This formulation imposes physical Dirichlet data at cut points via local interpolation, while sampled-normal rank updates remove hydrostatic null modes associated with single or multiple obstacles. The workflow parallels that of classical boundary integral formulations and requires no artificial boundary conditions for exterior flows, but follows a discretize-then-represent route and does not require singular/near-singular quadrature. The resulting dense boundary system is solved via GMRES, utilizing a componentwise discrete Calderón preconditioner built from the scalar Laplace kernel and padded FFTs for fast volume convolutions. Extensive numerical validation, including multiply connected domains, narrow gaps, and Moffatt eddies, confirms discrete incompressibility to solver accuracy and recovers the expected Moffatt eddy scaling. We achieve second-order velocity and pressure convergence and bound maximum discrete divergence within numerical accuracy. The discrete Calderón preconditioner reduces the condition number by orders of magnitude and yields nearly mesh-independent conditioning in exterior configurations, while remaining effective—though more demanding—for narrow-gap and fine-grid interior problems.
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Fluid Dynamics
A general synthetic iterative solver for axisymmetric rarefied gas and electrostatic charged-particle flows
Yifan Wen and Lei Wu
An axisymmetric general synthetic iterative scheme (AxiGSIS) is proposed to simulate rarefied gas flows and charged particle transport under prescribed electrostatic fields. This solver adopts a finite-volume discrete velocity method defined over the two-dimensional axisymmetric meridian plane paired with a three dimensional molecular velocity space. Under the GSIS framework, the kinetic solver computes nonequilibrium stress and heat flux, which are subsequently imported as corrective source terms into the macroscopic synthetic system. Fast iterative updates of low order flow primitive variables are performed on this macroscopic system, whose corrected flow fields are then fed back to the kinetic solver. This bidirectional coupling enables rapid propagation of macroscopic information and substantially accelerates steady state convergence, particularly in near continuum flow regimes. Four
benchmark flows are examined: the Taylor Couette flow, neutral nozzle expansion flow, charged particle flow past an electrostatic sphere, and electrostatically accelerated charged-particle nozzle flow. Results show that AxiGSIS reproduces the reference kinetic solutions and accurately captures axisymmetric flow physics and charged-particle responses to prescribed electrostatic fields. Utilizing fewer spatial
cells and iteration steps, AxiGSIS substantially cuts computational overhead relative to conventional kinetic iterations, particularly for low and moderate Knudsen number flows.
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Chemical Physics
Determination of fundamental properties of nitrogen from first principles. III. Temperature and frequency dependence of the molecular polarizability and magnetic susceptibility
Jakub Lang, Giovanni Garberoglio, Michał Przybytek et al. (+1 more)
This work is the third part of the series of papers that focus on the theoretical determination of the properties of nitrogen that are relevant in metrology. Here we present first-principles calculations of the temperature and frequency dependence of the molecular polarizability and
magnetic susceptibility of the nitrogen molecule (N$_2$). The purely electronic contributions to the static polarizability, Cauchy coefficients (up to sixth order), and isotropic
magnetic susceptibility are computed over a range of internuclear distances using a robust composite scheme combining several electronic structure methods. The temperature dependence, evaluated from $50$~K to $2000$~K, is determined using two independent methods: rovibrational averaging and path integral Monte Carlo (PIMC). The polarizabilities obtained from theory agree with the recent high-precision thermometry measurements, wherever the latter are available, but are significantly less accurate. However, the main usefulness of the theoretical data revolves around combining it with the available experimental results to generate semi-empirical estimates of various quantities that have never been measured thus far. As an example, we determine highly accurate semi-empirical estimates of the static polarizability at key reference temperatures, $\alpha_0(T)=11.735\,962$~a.u.\ at $T=303$~K and $\alpha_0(T)=11.735\,585$~a.u.\ at $T=273.16$~K. Furthermore, we report theoretical values for the
magnetic susceptibility, highlighting the importance of the paramagnetic contribution, and address a significant discrepancy with the experimental data for this quantity.
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All authors Jakub Lang, Giovanni Garberoglio, Michał Przybytek, Michał Lesiuk
Optics · Cross-listed from quant-ph
Space-division multiplexed quantum key distribution exploiting multi-plane light conversion for few-mode fibers
Qian Zhang, Stefan Krause, Felix Kunzmann et al. (+1 more)
As
quantum key distribution (QKD) progresses from laboratory demonstrations toward practical deployment,
quantum communi- cation networks increasingly require higher key rates and the ability to distribute independent secret keys among multiple users and network nodes. In this paper we present a promsing approach with multi-plane light conversion (MPLC) for demultiplexing entangled
photons, transmitted through a few-mode fiber (FMF). We experimentally demonstrated a spatially multiplexed BBM92 QKD scheme. The modes are selectively excited through separate single-mode-fibers and subsequently separated by MPLC into distinct output ports. Unlike high-dimensional QKD based on coherent modal superpositions, our approach exploits distinguishable guided modes as parallel channels while preserving the
entanglement required for QKD. For the multiplexed links, we obtain
quantum bit error rates of $1.9 \pm 0.4\%$ for the channel 1 and $6.8 \pm 0.8\%$ for the channel 2. These results are relevant for scalable
quantum-secured networks, space-division-multiplexed QKD systems, multi-user
entanglement distribution, and future
quantum internet architectures, where parallel
quantum channels must be implemented without compromising the
quantum correlations required for security.
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All authors Qian Zhang, Stefan Krause, Felix Kunzmann, Juergen W Czarske
Optics
Laser Remelting for Reduced Porosity on Additively Manufactured Aluminium Mirrors
Joshua West, Valentina Oyarzun, Marcell Westsik et al. (+17 more)
Additively manufactured (AM) AlSi10Mg mirrors are fabricated through
laser powder bed fusion (LPBF), allowing the use of complex geometries such as
lattices and organic structures that enable high mass reduction while maintaining mechanical stiffness. Micron-sized pores that cause optical scatter may form during LPBF as a consequence of deviations from the optimal processing window, particularly from
laser energy input and scan strategy. This work proposes a
laser remelting strategy aimed at reducing porosity; standard LPBF build steps automatically alternate with
laser remelting passes, where previously deposited material is remelted during fabrication.
Laser remelting is evaluated through fabricating 10 mm proof-of-concept cubes. Following single point diamond turning (SPDT), optical measurements characterised surface roughness and identified surface artefacts. The best-performing AlSi10Mg remelted cube exhibited no pores within sampled regions and achieved 6.4 nm average surface roughness, comparable to a conventionally manufactured RSA 6061 control cube (5.8 nm). Driven by these results, AM 52 mm diameter secondary sandwich mirrors were manufactured using LPBF and
laser remelting. These incorporate an optimised diamond TPMS
lattice to achieve a 50% mass reduction while accommodating design for AM considerations. Unlike the cube study, the optical surface of the remelted mirror after SPDT exhibited residual porosity and 11.8 nm average surface roughness. These results show that while the proof-of-concept confirmed the viability of
laser remelting in reducing porosity within simple geometries, optimisation of the LPBF and SPDT processes are required to translate the benefits of
laser remelting to lightweight AlSi10Mg AM mirrors.
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All authors Joshua West, Valentina Oyarzun, Marcell Westsik, Younes Chahid, Magdalena Kraus, Scott McPhee, William Brzozowski, Samuel Tammas-Williams, Nicola Cayzer, Fraser Laidlaw, Sameer Dayanand Meshram, Daniel Ordnung, Berk Baris Celik, Michel Smet, Mirko Sinico, Wenjuan Sun, Brecht Van Hooreweder, Michael Harris, Stephen James, Carolyn Atkins
Atomic Physics · Cross-listed from quant-ph
Tailoring optical Schrödinger cat states via orientation-dependent high-harmonic generation in $\rm{H}_2^+$
Ziyang Gan, Ahai Chen and Yuhai Jiang
We theoretically demonstrate that the molecular orientation angle $\theta$ provides a structurally intrinsic, continuously tunable control parameter for engineering optical Schrödinger cat states via high-harmonic generation (HHG) in H$_2^+$. Coupling time-dependent Schrödinger equation simulations to the fully quantized HHG framework, we evaluate the Wigner functions of the post-selected harmonic-mode states under two complementary conditioning strategies. Conditioning on resonance-enhanced low-order harmonics exploits the complementary dipole selection rules of the $1\sigma_g\to1\sigma_u$ and $1\sigma_g\to1\pi_u$ transitions, driving a kitten-cat crossover whose direction is opposite in the two channels as $\theta$ is varied. Conditioning on plateau harmonics instead exploits two-center destructive interference, producing a reentrant cat$\to$kitten$\to$cat transition controlled by the order-dependent interference angle $\theta^*(q)$. In both cases the crossover is decoupled from the
laser intensity, focal geometry, and molecular density, offering a degree of control with no counterpart in atomic targets.
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