Atomic Physics
Observation of multiphoton entanglement in resonance fluoresce
Xiao-Long Zhou, Jian Wang, Ze-Min Shen et al. (+8 more)
Resonance fluorescence, the process in which a single two-level
quantum emitter interacts with a near-resonant coherent light, is a cornerstone of
quantum optics as a paradigmatic light-matter interaction.
Quantum phenomena in resonance fluorescence have been accounted for in terms of one- and two-
photon processes; however, the physical processes arising from the interaction of a single two-level atom with higher
photon numbers remain unexplored experimentally. Here we experimentally reveal the multiphoton scattering nature of resonance fluorescence, which intrinsically gives rise to multiphoton
entanglement. By accessing
quantum fluctuations in the field emitted from a cavity-
quantum electrodynamics system, we resolve third- and fourth-order
photon scattering events from a single two-level atom. In the three-
photon component, the scattered
photons are shown to be genuinely energy-time entangled, as verified by a violation of Svetlichny's inequality. As a demonstration of an application, a
quantum secret sharing protocol (QSS) is implemented using this entangled
photon source. Our study refines the descriptive framework of resonance fluorescence and broadens the scope of its investigation. It also establishes a fundamentally simple route for generating multiphoton entangled states for
quantum information processing and
quantum metrology.
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All authors Xiao-Long Zhou, Jian Wang, Ze-Min Shen, Dong-Yu Huang, Si-Jian He, Qi-Yang Huang, Yi-Jia Liu, Yu-Shu Chen, Quan Jiang, Chuan-Feng Li, Guang-Can Guo
Optics
Aberration sensing in fluorescence microscopy using quantum correlations
Shay Elmalem, Shaurya Aarav, Allard K. F. Hübler et al. (+2 more)
Widefield fluorescence microscopy is an essential biological imaging tool, yet its penetration depth is fundamentally restricted by tissue-induced aberrations. Correcting these requires precise characterization of the point spread function (PSF), but existing wavefront sensing techniques rely either on often-unavailable guide
stars, or on computationally heavy indirect phase
retrieval methods, that could struggle in low-contrast regions. Here, we show that the PSF can be mapped directly and non-invasively by exploiting
quantum correlations between
photons. Standard fluorophores inherently exhibit
photon antibunching, effectively acting as sources of “missing”
photon pairs. By capturing these correlation statistics across a wide field of view using a single-
photon avalanche diode (SPAD) array imager, we extract the local PSF autocorrelation directly from the fluorescence emission itself. This approach bypasses the limitations of classical intensity measurements, requiring no iterative or complex numerical optimization. We demonstrate widefield direct PSF
retrieval in a second or less, paving the way for real-time operation. By translating
quantum optical concepts to conventional fluorescent probes, this technique provides a robust, direct pathway to deep-tissue adaptive optics in life sciences.
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All authors Shay Elmalem, Shaurya Aarav, Allard K. F. Hübler, Hugo Defienne, Dan Oron
Space Physics · Cross-listed from astro-ph.EP
Widespread plasma jets in the Martian magnetosheath revealed by dual-spacecraft observations
Abigail Tadlock, Chuanfei Dong, Chi Zhang et al. (+4 more)
Plasma jets in planetary magnetosheaths are transient, high dynamic pressure structures capable of strongly perturbing downstream magnetospheres and modulating solar wind energy transfer. Although recently identified at Mars, their formation mechanisms and global occurrence remain poorly constrained. Using dual-spacecraft observations from Mars Atmosphere and Volatile
EvolutioN (MAVEN) and Tianwen-1, we show that magnetosheath jets occur throughout the Martian magnetosheath, in striking contrast to Earth where jet occurrence is strongly controlled by interplanetary
magnetic field orientation and largely confined to quasi-parallel shock regions. We propose that this widespread distribution is linked to Mars' extended hydrogen corona, which generates pickup ions that drive
proton-cyclotron waves upstream of the bow shock. Because this mechanism is generic to any body with an extended corona (or exosphere) embedded in a stellar wind, this finding bears on solar-wind interactions at comets and other small bodies, and on the space environments of unmagnetized terrestrial
exoplanets. These results indicate that magnetosheath jet formation can be governed not only by external solar wind forcing but also by intrinsic planetary properties, pointing to a previously unrecognized pathway for solar wind-
planet coupling at unmagnetized worlds.
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All authors Abigail Tadlock, Chuanfei Dong, Chi Zhang, Savvas Raptis, Hongyang Zhou, Xinmin Li, Jiawei Gao
Optics · Cross-listed from cs.LG
Learning-Based Reconstruction of Optical Properties in Bilayered Media from Single-distance Time-Resolved Reflectance Measurements
Caterina Amendola, Giulia Maffeis, Lorenzo Buffoni et al. (+8 more)
The inverse problem of reconstructing optical properties, specifically absorption and scattering coefficients, in layered biological media from time-domain reflectance measurements remains a significant challenge for traditional analytical models. Inverse solvers based on the
diffusion equation often struggle with structural heterogeneity, frequently yielding poor accuracy for superficial absorption and deep-layers scattering. In this work, we propose a machine learning framework as an alternative approach to reconstruct the optical properties of a bilayered medium, benchmarking its efficiency and accuracy against model-based
algorithms. To overcome the intrinsic approximations of
diffusion theory and inverse reconstruction, we generated a robust synthetic
dataset of forward DTOF using exact Monte Carlo simulations at multiple source-detector distances. A machine learning pipeline was then trained on this
dataset and validated against state-of-the-art model-based reconstruction methods. Besides the significant reconstruction speed-up, the machine learning approach achieves higher accuracy than model-based inverse solvers, further providing an estimate of the parameter space dimensionality without requiring any a priori information about the number of layers in the investigated geometry. Further enhancements in the reconstruction accuracy can be expected in future extensions of this work, by training the pipeline over multiple DTOF curves from the same medium, in a joint multi-distance reconstruction approach.
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All authors Caterina Amendola, Giulia Maffeis, Lorenzo Buffoni, Lorenzo Chicchi, Francesco Coghi, Duccio Fanelli, Raffaele Marino, Fabrizio Martelli, Riccardo Paoli, Lorenzo Pattelli, Lorenzo Spinelli
Optics
Rapidity-Coupled Spin Dynamics in Pulsed Laser Fields from Physics-Informed Neural Networks
N. S. Akintsov, A. P. Nevecheria, S. N. Andreev et al. (+1 more)
Carrier-envelope-phase (CEP) stabilized few-cycle pulses make the sub-cycle field structure a control parameter for
laser-driven polarized electron sources, yet
spin solvers for such pulses are rarely tested against exact results. We show that for an electron initially at rest in a linearly polarized plane-wave pulse the rest-frame polarization angle follows the instantaneous vector potential, $\Sigma = 2\arctan(a_x/2) + a_e a_x$ with $a_e$ the electron anomaly: the net rotation vanishes for every CEP, while the peak intra-pulse angle varies over the CEP by 3.02 degrees for a two-cycle and by 0.22 degrees for an eight-cycle pulse. The result follows from the Volkov orbit in longitudinal and transverse rapidities. We use it to validate a light-front reference integrator and a physics-informed neural network trained only on the light-front equations, which reaches $4\times10^{-5}$ in the
spin sector and carries over to elliptical polarization, for which no closed-form solution is known. This gives validated tools for CEP-resolved
spin dynamics in intense fields.
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All authors N. S. Akintsov, A. P. Nevecheria, S. N. Andreev, Qing-Hua Qin
Plasma Physics
Indirect-Drive Fusion Target Design for Commercial Fusion Energy
C. R. Weber, A. L. Kritcher, S. Bhandarkar et al. (+26 more)
This paper presents the physics basis for commercially relevant
laser indirect-drive (LID) (radiation-driven) inertial fusion energy (IFE) using a 10 MJ
laser driver. To date, this approach, proven at the National Ignition Facility (NIF), remains the first and only controlled fusion method to demonstrate the key physics required for fusion energy production, including a self-sustained burning
plasma, substantially de-risking the path to commercial fusion energy. Building directly on these results, we present scaled designs to larger target sizes and fusion gains relevant for commercial power generation ($G\sim 26$–$43$). The designs remain close to experimentally demonstrated ignition physics, modifying target components to improve scalability, manufacturability, and cost-effectiveness for fusion energy applications while preserving ignition-relevant implosion physics and fusion power plant compatibility. The baseline platform retains a high-density carbon ablator and clean cryogenic DT fuel layering while extending ignition platforms to substantially larger fuel masses (exceeding 10 times that of current ignition experiments at the NIF) and higher burn fractions ($\sim$40%) with total areal densities at stagnation of $\sim$3~g/cm$^2$. Benchmarked simulations anchored to NIF ignition experiments (using HYDRA and LASNEX) predict that these designs achieve robust ignition and propagating burn at substantially higher fusion yields (265–427~MJ) with significant ignition margin (2–4$\times$ relative to NIF) against hydrodynamic instabilities and representative power-plant non-idealities, including low-mode asymmetry, polycrystalline DT ice roughness, HDC ablator voids, and target-support and fill-hole perturbations. We also show that implosion
symmetry and
laser-
plasma interactions (LPI) can be controlled with our novel multi-beam configuration using thousands of
laser beam-lines.
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All authors C. R. Weber, A. L. Kritcher, S. Bhandarkar, T. Briggs, T. Chapman, T. M. Fears, B. A. Hammel, D. D.-M. Ho, O. Hurricane, B. Kozioziemski, J. Milovich, A. Nikroo, A. Oudin, W. Riedel, A. Wray, N. Alexander, G. Cearley, M. Dunne, J. Gaffney, D. Hammond, J. Kilkenny, R. Lau, J. Lawson, J. Ludwig, B. MacGowan, R. Peterson, V. Smalyuk, R. Toro, Inertia Collaboration
Optics
Voltage-Current-Emission Framework of Time-Resolved Electroluminescence
Hui Bao, Longjia Wu, Yanan Guo et al. (+3 more)
Time-resolved electroluminescence has been a central methodology in the development of LED devices. However, it still lacks quantitative theoretical descriptions of time-resolved electroluminescence. By combining the equivalent
circuit models of
semiconductor devices and the carrier dynamics of electroluminescence processes, we here developed a Voltage-Current-Emission framework to illustrate time-resolved electroluminescence from the pulse voltage as input, to injection current and finally generate electroluminescence as output. The features of different LED devices can be quantitatively interpreted, confirming the universal applicability across LEDs with different materials and device structures. Importantly, the curves of time-resolved electroluminescence can be simulated to quantitatively describe the dynamics of current and carriers of LED operation. In all, the Voltage-Current-Emission framework offers theoretical guidance for achieving advanced LED devices for AI technology.
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All authors Hui Bao, Longjia Wu, Yanan Guo, Jianchang Yan, Ying Wang, Haizheng Zhong
Instrumentation and Detectors
Design and characterization of large-size monolithic layers of 3D-segmented plastic scintillator
Jon Berisha, Xingyu Zhao, Andrey Boyarintsev et al. (+10 more)
Three-dimensional fine-grained plastic scintillator detectors are extensively used in high-energy physics experiments where particle tracking, identification, calorimetry and sub-nanosecond timing information are required. Moreover, the low cost of plastic scintillator makes, in principle, the scalability to multi-tonne detectors possible. In order to circumvent the difficulties related to the long production time and the challenging assembly of millions of tiny independent scintillating voxels, a new technology consisting of gluing a few thousand $9 \times 9 \times 9$ mm$^3$ plastic scintillator cubes in a single large monolithic layer with machining precision, while ensuring an efficient optical separation, was developed and demonstrated. In this work we demonstrate that such technology can be reliably extended to a monolithic layer of $48 \times 48$ optically-isolated scintillating cubes, the size required for future ton-scale detectors, fulfilling the requirements of future
neutrino detectors and sampling calorimeters.
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All authors Jon Berisha, Xingyu Zhao, Andrey Boyarintsev, Sebastien Cap, Diogo Di Calafiori, Maksim Kiktev, Umut Kose, Anzhelika Kuzmina, Natalia Leskina, André Rubbia, Tetiana Sibilieva, Tim Weber, Davide Sgalaberna
Fluid Dynamics
Experimental study of the impact dynamics of polymeric hollow droplets
Mohammad Mahdi Nasiri, Mohammad Reza Daneshvar Garmroodi, Damian Vadillo et al. (+1 more)
The impact dynamics of hollow droplets, while influential in applications such as coating and spraying, remain less explored than their dense counterparts. In particular, the impact dynamics of viscoelastic hollow droplets have yet to be fully explored. This study presents an experimental investigation into the impact of hollow Newtonian (water) and viscoelastic (polymeric solution) droplets on a solid surface at different impact velocities and
polymer concentrations. We demonstrate two hallmark features of hollow droplet flattening: the formation of a central counter-jet and the final deposition, both associated with the entrapped air bubble. For Newtonian droplets, the counter-jet exhibits rapid growth and breakup due to capillary instabilities. Introducing
polymer additives fundamentally alters this behavior: viscoelasticity affects the counter-jet's height and velocity, delays bubble rupture, and inhibits droplet detachment. Crucially, we observe the emergence of beads-on-a-string structures during filament thinning, a signature of the competition between elastic and capillary forces. By systematically varying the
polymer concentration and impact velocity, we identify the conditions under which three distinct outcomes occur: deposition, partial deposition, and detachment. Our results show how inertia, viscosity, capillarity, and elasticity together govern the splashing morphology of hollow non-Newtonian droplets.
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All authors Mohammad Mahdi Nasiri, Mohammad Reza Daneshvar Garmroodi, Damian Vadillo, Moussa Tembely
Instrumentation and Detectors
Proposing, never assigning: fair allocation of control-room shifts in experimental particle physics collaborations from ranked wishes under institutional quotas
Kamal Benslama
Experimental particle physics collaborations staff their detectors around the clock with members drawn from dozens of institutions. The established practice is a credit system with self-sign-up: institutions owe a quota of credit, and people take the seats they want when booking opens. This paper describes a method in which seats are instead allocated from ranked wishes under institutional quotas, the result is issued as offers that each person accepts or declines, and an independent checker recomputes every rule before anything is published: the platform proposes, never assigns, and proves that it kept the rules. The credit and quota model is inherited from current practice. Around that core the paper adds a quota rule that keeps indivisible blocks fair to institutions whose share of a period is smaller than one block, and four rules that make
fairness visible beyond the count: shares of owl, weekend and holiday blocks, seats shown in the laboratory's clock and the institution's own, reachable pools for institutions that cannot travel, and booking order by balance. On a synthetic collaboration of 48 institutions and 256 eligible members, the method allocates 70 to 72 of 72 seats per period in two rounds, with a mean rank satisfaction of 84 to 95% and no rule broken; after a year of running every institution of four members or more is within 13% of its cumulative share, and the smallest institutions, which one block overshoots by arithmetic, are brought within the same range by pooling in pairs. The method is stated completely enough to be reimplemented; a reference implementation exists and is available to collaborations under license. It applies as it stands to any scientific collaboration that staffs a facility in blocks of shifts under institutional quotas.
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Fluid Dynamics
Well-posedness of neural turbulence closures and tangent dissipation
Zhen Zhang and George Em Karniadakis
A neural
turbulence closure defines a new boundary-value problem, $R(U)=N(U)+F(U)=0$, with a coupled Jacobian $J(U)=N'(U)+F'(U)$, where $N$ is the original mean-flow operator and $F$ the learned closure. We establish two consequences of global tangent dissipation. For a monotone original operator, a positive uniform margin supplied by the original operator and closure together guarantees existence, uniqueness and a global inverse-sensitivity bound relating a posteriori solution error to the a priori residual. For a general original operator, a dissipative closure cannot worsen tangent dissipation, but this alone does not guarantee uniqueness. Tangent dissipation depends on both
diffusion and reaction. We study two complementary ways to promote it: (1) an exact-integral construction enforcing non-negative tangent
diffusion while leaving reaction unconstrained, and (2) a penalty on tangent-reaction violations at sampled states. Tangent
diffusion enters the Jacobian, and non-negative secant eddy viscosity alone does not control its coercivity. We conduct tests with channel flow at $Re_\tau=180$–$5200$, which provides a strongly monotone baseline. Both constrained closures reach accurate solutions in all 50 training-seed/Reynolds-number cases. At $Re_\tau=1000$, we conduct tests with 10,000 starts for one fixed network per closure and we find one root for each constrained closure and multiple roots for the other closures. Although this does not prove uniqueness, it provides strong empirical evidence for uniqueness of the tested constrained closures. At $Re_\tau=5200$, the construction and penalty reduce the reported inverse sensitivity relative to the original operator by approximately $372\times$ and $11\times$, respectively.
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Geophysics
The Brittle-Plastic Transition in Quartz-Albite Mixtures: New Insights From Shear Deformation Experiments at Mid-to-Lower Crustal Depth Conditions
M. Furukawa, B.A. Verberne, S. Sawa et al. (+4 more)
Crustal strength is often characterized using a strength-depth profile where laboratory-derived friction and flow laws are connected at depth (i.e., the so-called Christmas Tree diagram). Large, destructive earthquakes frequently nucleate within the transition zone from a frictional-to-viscous deformation regime, which represents the strongest part of the crust. However, microscale deformation mechanisms controlling bulk frictional-to-viscous transitional behavior remain unclear. To investigate the deformation mechanisms, we conducted shear experiments on room-dry, powdered quartz-albite mixtures under upper- to mid-crustal pressure-temperature conditions using a Griggs-type deformation apparatus. We simulated depth conditions in the range 7-30 km, by varying temperatures and confining pressures (210-900 C and 185-870 MPa, respectively, by assuming 30 C/km and 2,700 kg/m3). To assess the rate dependence and stability of shear deformation, we sequentially stepped shear strain rates between 10^-3/s and 10^-4/s. At shallower depth conditions, friction coefficients follow Byerlee's law, while at greater depth conditions they deviate from it and strain weakening is observed. Post-mortem microstructures indicate changing deformation mechanisms with increasing simulated depths. The samples deformed at shallower depth conditions (<18 km) show a predominance of cataclastic grain comminution. At greater depth conditions (>24 km), nano-grains are observed, as well as polygonal quartz grains at the greatest depth condition (30 km). These results indicate that the controlling deformation mechanisms at the frictional-viscous transition zone are grain boundary sliding and dynamic recrystallization. We conclude that nano-scale deformation mechanisms govern the frictional-viscous transitional deformation in the upper crust, and propose their importance for understanding seismic rupture processes there.
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All authors M. Furukawa, B.A. Verberne, S. Sawa, H. Nagahama, M. Takahashi, O. Pluemper, J. Muto
Fluid Dynamics · Cross-listed from cond-mat.soft
Viscoelastocapillary extensional De-Oh or VE-DeOh stringiness of unentangled polymer solutions
Louis B. Edano and Vivek Sharma
Characterization, control, and calibration of stringiness, the propensity to form long, thin, persistent threads, are key to the design and application of
polymer solutions and formulations transferred to substrates by dropwise dispensing, jetting, spraying, or coating, and are used in manufacturing fibers, membranes, or spray-dried products. For Newtonian fluids, enhancing shear viscosity translates into increasing stringiness as can be easily perceived during dripping of water vs. sugar syrups or glycerol-water mixtures. In contrast, even
polymer solutions with comparable shear viscosity can display a significant contrast in extensional rheology and apparent stringiness. However, there are no quantitative maps, formulas, or scales for stringiness, which motivates this study. In this contribution, we contrast the stringiness for a series of aqueous
polymer solutions by determining the filament lifespan using dripping-onto-substrate (DoS) rheometry and filament length and lifespan in using dripping-into-air (DiA). We investigate the influence of
polymer chemistry and molecular weight on stringiness and rely on DoS rheometry to characterize pinching dynamics and extensional rheology response. We show that an increase in stringiness correlates with steady, terminal extensional viscosity, and extensional relaxation time, respectively. Lastly, we provide a framework, which compares the stringiness of different
polymer solutions through an extensional Ohnesorge-Deborah ($Oh-De$) plot or $Oh_E-De_E$ map, by computing the two dimensionless groups $Oh_E$ using steady, terminal extensional viscosity and $De_E$ using extensional relaxation time, respectively
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Physics and Society
Geography as the Organizing Grammar of Geospatial Models
Rajiv Ranjan and Shashank Tamaskar
GeoAI increasingly produces reusable Earth representation s, physical forecasts,
multimodal systems, and
reasoning a gents. Their progress exposes two distinct limitations. Geo graphic completeness asks whether the represented world ex tends beyond readily observed land surfaces and atmospher ic fields to oceans, biogeography, economies, institutions, and human agency. Geographic intelligence asks whether model outputs preserve place, scale, relations, process, un certainty, and the limits of valid inference. The first con cerns what exists in a model; the second concerns what may responsibly be claimed about it. This critical integrative review argues that geography provides the organizing gram mar that connects these dimensions. Seven structural gaps, propositions, and corresponding review questions translate the argument into testable requirements. The resulting re search agenda advances Living Geospatial Models as federat ed, continually updated systems that couple specialist Earth and human-domain models through shared geographic iden tity, support, relations, provenance, and uncertainty. The objective is not a single universal network, but geospatial intelligence that can explain connections and change, antic ipate plausible futures, and support accountable decisions across places and scales.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Hydrogen Reorganization in Hot Dense Ammonia
Yu Tao, Jingyi Liu and Li Lei
Hydrogen is known to form stable compounds with a variety of simple molecular solids under high pressure. However, ammonia hydride has not been experimentally observed. Here, through a series of
laser-heating diamond anvil
cell (LHDAC) experiments, we observed the transparent ionic ammonia transformed into an opaque phase above 150 GPa and 1000 K. Raman spectroscopy reveals a pronounced structural change, accompanied by the emergence of two distinct asymmetric H$_2$ vibrons ($\nu_1$ and $\nu_2$). A new ionic phase produced following thermally induced dissociation and hydrogen reorganization in hot dense ammonia. The combination of experimental results and first-principles calculations identify this phase as the theoretically predicted ionic $P4_12_12$ phase of NH$_7$ , which consists of NH$_4^+$, H$^-$and H$_2$ units. Our results suggest that the formation of ammonia hydrides follows a thermodynamic pathway distinct from those of other H$_2$-containing mixtures, revealing a new ionic transformation pathway driven by hydrogen reorganization in hot dense ammonia.
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Chemical Physics
Efficient tensorized evaluation of permutation invariant polynomials for representing potential energy surfaces
Junhong Li, Kaisheng Song, Hua Guo et al. (+1 more)
Permutation invariant
polynomials (PIPs), together with related
polynomial-based invariant descriptors such as fundamental invariants (FIs), are widely used in constructing high-fidelity global potential energy surfaces (PESs) of molecules that contain identical atoms. Although the monomial symmetrization approach (MSA) enables fast evaluation of PIPs through recursive factorization, it leads to deeply nested computational graphs that may require large
memory and are inefficient in modern automatic differentiation frameworks. In this work, we introduce JaxPIP, a JAX-based implementation that reformulates PIP/FI evaluation into tensorized linear
algebra operations. By replacing recursive factorization with dense
matrix operations combined with log-exp transformation and segmented summation, the evaluation becomes regular and GPU-friendly. This allows efficient execution with just-in-time compilation and enables large-scale batch evaluation of energies and forces (as well as higher-order derivatives). The resulting architecture supports ensemble simulations such as quasi-classical trajectory (QCT), path-integral molecular dynamics (PIMD), and
diffusion Monte Carlo (DMC) in a fully vectorized manner. As demonstrated in examples, JaxPIP provides a practical route for efficient simulations of molecular systems with scalable GPU execution.
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All authors Junhong Li, Kaisheng Song, Hua Guo, Jun Li
Optics
Limits on the free-space group velocity of optical wave packets incorporating angular dispersion. Part~II, non-differentiable angular dispersion: tutorial
Layton A. Hall and Ayman F. Abouraddy
In Part~I of this tutorial, we showed that introducing angular dispersion (AD) into a collimated optical pulse allows for tuning the wave packet group velocity in free space. In principle, the group velocity can take on arbitrary values, whether superluminal, subluminal, or even negative. However, any significant deviation of the group velocity from $c$ (the speed of light in
vacuum) necessitates propagation at large angles with respect to the optical axis in the non-paraxial regime. In Part~II of this tutorial, we describe the recent discovery of a new form of AD we refer to as `non-differentiable AD', which circumvents the limits imposed by conventional (differentiable) AD. Non-differentiable AD does not refer to an AD profile that is discontinuous, contains a kink, or features a singularity. Rather, a non-differentiable AD profile is continuous, smooth, and is differentiable everywhere except for one wavelength at which the derivative is not defined. We show that salutary features follow from this non-differentiability with respect to tuning the group velocity of a pulsed beam in free space; namely, significant deviations in the group velocity away from $c$ are achievable in the paraxial regime while remaining free of group-velocity dispersion and all higher-order dispersive effects. This tutorial presents an outline of these recent results for tuning the group velocity of a wave packet via non-differentiable AD, connecting them with the corresponding results associated with conventional AD – as outlined in Part~I. Moreover, we show that non-differentiable AD undergirds the unique characteristics of propagation-invariant space-time wave packets, thus unifying a large swathe of results in a single conceptual framework.
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Optics
Limits on the free-space group velocity of optical wave packets incorporating angular dispersion. Part~I, conventional angular dispersion: tutorial
Layton A. Hall and Ayman F. Abouraddy
A plane-wave optical pulse travels in free space at a group velocity $c$ (the speed of light in
vacuum) measured along its propagation axis. It is sometimes thought that spatially structuring the field in free space reduces the group velocity below $c$ because – intuitively – the oblique wave vectors undergirding the wave packet increase the average group delay. Here we show that spatiotemporally structuring a pulsed optical beam (or wave packet) can yield – in principle – arbitrary group velocities in free space in contradistinction to this commonly held intuition. We devote our
attention here to pulses endowed with angular dispersion (AD) where the propagation angle is wavelength dependent. This class of wave packets is particularly pertinent because their group velocity is constant over the transverse field profile and along the propagation axis, thereby yielding an unambiguous group delay. However, significant deviation of the AD-induced group velocity in free space from~$c$ inevitably requires a large numerical aperture that lies deep in the non-paraxial regime, and such wave packets experience AD-induced group-velocity dispersion. The formulation presented here captures a broad range of results, connecting them in a single framework. In Part~II of this tutorial, we describe recently identified `non-differentiable AD' (associated with propagation-invariant space-time wave packets) that helps circumvent the limits associated with conventional (differentiable) AD as outlined here.
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Plasma Physics
Efficient laser ion acceleration in near-critical density plasmas in the picosecond pulse regime
Joshua Luoma, Andreas Kemp, Andrew Longman et al. (+2 more)
Kilojoule-class short-pulse (< 10 ps)
lasers are excellent tools for generating relativistic ion beams, but achieving high
laser-to-ion conversion efficiency remains an open challenge. Recent experiments show a significant increase in conversion efficiency when leveraging targets with an average
plasma density approaching the relativistic-critical limit. We present an analytical model that explains this increase by extending the theory of target-normal sheath acceleration (TNSA) to include
laser penetration of relativistic-critical density targets, enabling energy transfer to the ion front by heating the expanding electron sheath. This physical process increases the sheath field strength and significantly improves ion cutoff energy and
laser-to-ion conversion efficiency relative to classical TNSA. The model predicts a maximum ion conversion efficiency of 37% by optimizing
laser transmission and target areal density. Key scalings of the model agree with particle-in-
cell (PIC) simulations and published experimental data. A series of 2D and 3D simulations of hydrocarbon
plasmas confirm the robustness of the acceleration process, demonstrating a path for maximizing ion yields using relativistic-critical targets.
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All authors Joshua Luoma, Andreas Kemp, Andrew Longman, Dean Rusby, Gennady Shvets
Optics
Automatic Optical Alignment Using Projective Geometry
Bowen Li, Lukas Palm, Xin Wei et al. (+5 more)
Aligning and maintaining complex optical beam paths is a central challenge across experimental science, because it is a high-dimensional task with strong cross-coupling between controls, often in systems with limited physical access. We present an automated hardware-software framework that resolves this
alignment challenge using low-cost, retro-fittable motorized mounts driven by projective-geometry models and a photodiode-fed optimizer. A compact forward model describes the beam path to paraxial order with only the physical mirror angles left free, so it can be rapidly ($\sim$ms) numerically inverted to return the required mirror angles for a desired beam trajectory. A photodiode-fed optimizer then fine-tunes this
geometric starting point, and converged mirror settings are tabulated for
retrieval in milliseconds and actuation in seconds. We experimentally demonstrate the performance of this approach on a retro-reflected
lattice atom-transport system, yielding improvements in both speed and precision over manual
alignment. This framework reduces the manual effort required to align complex beam paths, enables programmable optical control in experiments with limited physical access, and enhances the scalability of complex optical architectures.
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All authors Bowen Li, Lukas Palm, Xin Wei, Marius Jürgensen, Zeyang Li, Yiming Cady Feng, Abhishek V. Karve, Jon Simon
Computational Physics
Mollified-sharp decomposition: a probabilistic regularization of parametric POD for shock-bearing flows
Oliver T. Schmidt
This paper introduces the mollified-sharp decomposition, a probabilistic regularization of moving shocks in parametric reduced-order models. Each detected shock location is treated as a random variable with a prescribed probability density. Averaging over this artificial distribution replaces the localized pressure change by a smooth transition whose spatial extent is set by the density width, rather than by direct filtering of the pressure field. Each snapshot is decomposed exactly into a regularized mollified field and a local sharp correction that restores the shock. This probabilistic construction and exact additive split define the general method; the detector, kernel, treatment of multiple shocks,
alignment coordinates, and regression are implementation choices. In the present realization, a calibrated indicator detects shocks, a compactly supported Wendland kernel mollifies them, and a peak-normalized and, where necessary, partitioned weight derived from each shock-location probability density defines the centroid, principal axes, and scales of its local
alignment domain. Separate POD-GPR models represent the mollified field and aligned corrections, with additional regressions for shock presence and
alignment. The method is demonstrated on the transonic airfoil pressure data of Catalani et al. (2023) and compared with a standard POD-GPR model constructed from the same data and POD-energy criterion. The mollified-sharp model reduces the mean test-set relative $L^2$ pressure error by 31.2% and the mean test-set surface-pressure-coefficient error by 33.2%, while also improving the predicted shock locations and pressure changes; the trade-off is a median online evaluation time 2.24 times as long. The construction is applicable in principle to other parameter-dependent fields with moving sharp features, such as moving material interfaces in multiphase flows.
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Atmospheric and Oceanic Physics · Cross-listed from stat.ME
Spatial Aggregation of ROC and Precision-Recall Curves
Romain Pic, Zhongwei Zhang, Sebastian Engelke et al. (+1 more)
Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves are widely used to assess the discrimination ability of forecasts for binary events, such as threshold exceedances or warnings of extreme events. In weather forecasting, forecasts are provided as spatial fields, yielding location-wise ROC and PR curves that are often aggregated to facilitate comparison. However, the effect of the aggregation strategy on performance assessment remains poorly understood. We investigate how different aggregation strategies for ROC and PR curves affect the assessment of discrimination ability. In particular, we identify conditions under which aggregation strategies satisfy two desirable properties for fair comparison: preservation of dominance between forecasts and preservation of concavity or achievability of the curves. We obtain sufficient conditions and propose two strategies satisfying them. They are compared with existing strategies from the literature, and we analyze their properties and highlight potential pitfalls that may lead to misleading interpretations. Based on these findings, we provide practical guidelines for the interpretation of aggregated ROC and PR curves. The proposed framework is illustrated with AI-based global weather forecasts, showing how different aggregation strategies can yield different rankings of competing forecasts.
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All authors Romain Pic, Zhongwei Zhang, Sebastian Engelke, Johanna Ziegel
Geophysics
Continental-scale probabilistic resistivity imaging of Australia using deep learning: Implications for geology, groundwater, and critical minerals
Sihong Wu, Jiajia Sun and Jiefu Chen
Electrical resistivity is a fundamental physical property that provides powerful constraints on subsurface structure, lithology, fluid distribution, and mineralization. We present a continental-scale electrical resistivity model of Australia's shallow crust with quantified uncertainty, extending to depths of up to ~650 m. The model is derived from probabilistic inversion of more than 26.6 million airborne electromagnetic (AEM) soundings acquired along 352,600 line-kilometers from the AusAEM program. We develop a deep learning-based probabilistic inversion framework using invertible neural networks (INNs). To accommodate differences among AEM surveys, we trained 11 networks using a common set of synthetic resistivity models and the same training strategy, enabling consistent integration of inversion results across Australia. The entire inversion was completed in only 4.37 GPU hours, overcoming long-standing computational barriers to continental-scale probabilistic geophysical imaging. The resulting resistivity model exhibits clear spatial patterns that closely align with Australia's major geological provinces, sedimentary basins, aquifer and mineralizing systems. We further define the depth of investigation using posterior resistivity distributions to support uncertainty-informed geological interpretation. The resistivity model together with quantified uncertainty provides new physical constraints on regolith thickness, basin architecture, paleochannel and mineralized systems across Australia, serving as a foundation for interpreting continental-scale electrical structure and its geological, hydrological, and mineral system implications.
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