arXiv subjects

Eugene Kur

Publications and source records attributed to Eugene Kur.

8 recordsLinked to original sources

arXiv2026

A joint diffusion approach to multi-modal inference in inertial confinement fusion

A combination of physics-based simulation and experiments has been critical to achieving ignition in inertial confinement fusion (ICF). Simulation and experiment both produce a mixture of scalar and images outputs, however only a subset of simulated data are available experimentally. We introduce a generative framework, called JointDiff, which enables predictions of conditional simulation input and output distributions from partial, multi-modal observations. The model leverages joint diffusion to unify forward surrogate modeling, inverse inference, and output imputation into one architecture. We train our model on a large ensemble of three-dimensional Multi-Rocket Piston simulations and demonstrate high accuracy, statistical robustness, and transferability to experiments performed at the National Ignition Facility (NIF). This work establishes JointDiff as a flexible generative surrogate for multi-modal scientific tasks, with implications for understanding diagnostic constraints, aligning simulation to experiment, and accelerating ICF design.

physics.plasm-ph↗

arXiv2026

Near-Unity-Efficiency Gas Gratings for Ultraviolet, Visible, and Infrared High-Power Lasers

Interfering deep ultraviolet (DUV) lasers can induce substantial density modulations in an ozone-doped gas flow via photochemical reactions, creating volume diffraction gratings. These transient optics are immune to target debris and shrapnel and feature orders-of-magnitude higher damage thresholds than conventional solid optics, providing a promising method for efficiently manipulating high-energy lasers. In this work, we describe gas gratings that can efficiently diffract probe beams across a variety of wavelengths and pulse durations, ranging from deep ultraviolet to near-infrared and from nanosecond to femtosecond, achieving a full beam diffraction efficiency up to 99% while preserving the focusability and wavefront quality. In addition, we present a comprehensive characterization of the performance of the gas gratings under various experimental conditions, including imprint fluence, gas composition, and grating geometries, showing significant enhancement of this process with the addition of carbon dioxide. We also demonstrate stable performance over hours of operation. Our results validate a previously developed theoretical model and suggest optimal parameters to efficiently scale gas gratings to high-energy applications.

physics.optics↗

arXiv2024

Photochemically-induced acousto-optics in gases

Acousto-optics consists of launching acoustic waves in a medium (usually a crystal) in order to modulate its refractive index and create a tunable optical grating. In this article, we present the theoretical basis of a new scheme to generate acousto-optics in a gas, where the acoustic waves are initiated by the localized absorption (and thus gas heating) of spatially-modulated UV light, as was demonstrated in Y. Michine and H. Yoneda, Commun. Phys. 3, 24 (2020). We identify the chemical reactions initiated by the absorption of UV light via the photodissociation of ozone molecules present in the gas, and calculate the resulting temperature increase in the gas as a function of space and time. Solving the Euler fluid equations shows that the modulated, isochoric heating initiates a mixed acoustic/entropy wave in the gas, whose high-amplitude density (and thus refractive index) modulation can be used to manipulate a high-power laser. We calculate that diffraction efficiencies near 100% can be obtained using only a few millimeters of gas containing a few percent ozone fraction at room temperature, with UV fluences of less than 100 mJ/cm2, consistent with the experimental measurements. Our analysis suggests possible ways to optimize the diffraction efficiency by changing the buffer gas composition. Gases have optics damage thresholds two to three orders of magnitude beyond those of solids; these optical elements should therefore be able to manipulate kJ-class lasers.

physics.optics↗

arXiv2022

Discrete Gravity with Local Lorentz Invariance

A novel structure-preserving algorithm for general relativity in vacuum is derived from a lattice gauge theoretic discretization of the tetradic Palatini action. The resulting model of discrete gravity is demonstrated to preserve local Lorentz invariance and symplectic structure.

gr-qc↗

arXiv2022

The Delaunay Density Diagnostic

Accurate approximation of a real-valued function depends on two aspects of the available data: the density of inputs within the domain of interest and the variation of the outputs over that domain. There are few methods for assessing whether the density of inputs is \textit{sufficient} to identify the relevant variations in outputs -- i.e., the ``geometric scale'' of the function -- despite the fact that sampling density is closely tied to the success or failure of an approximation method. In this paper, we introduce a general purpose, computational approach to detecting the geometric scale of real-valued functions over a fixed domain using a deterministic interpolation technique from computational geometry. The algorithm is intended to work on scalar data in moderate dimensions (2-10). Our algorithm is based on the observation that a sequence of piecewise linear interpolants will converge to a continuous function at a quadratic rate (in $L^2$ norm) if and only if the data are sampled densely enough to distinguish the feature from noise (assuming sufficiently regular sampling). We present numerical experiments demonstrating how our method can identify feature scale, estimate uncertainty in feature scale, and assess the sampling density for fixed (i.e., static) datasets of input-output pairs. We include analytical results in support of our numerical findings and have released lightweight code that can be adapted for use in a variety of data science settings.

math.NA↗

arXiv2021

Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion

In this paper, we develop a Wasserstein autoencoder (WAE) with a hyperspherical prior for multimodal data in the application of inertial confinement fusion. Unlike a typical hyperspherical generative model that requires computationally inefficient sampling from distributions like the von Mis Fisher, we sample from a normal distribution followed by a projection layer before the generator. Finally, to determine the validity of the generated samples, we exploit a known relationship between the modalities in the dataset as a scientific constraint, and study different properties of the proposed model.

cs.LG↗

arXiv2020

Nonlinear Polarization Transfer and Control of Two Laser Beams Overlapping in a Uniform Nonlinear Medium

A scheme for polarization control using two laser beams in a non-linear optical medium is studied using both co- and counter-propagating beam geometries. In particular, we show that under certain conditions it is possible for two laser beams to exchange their polarization states. A model accounting for a more realistic, 2D propagation geometry is presented. The 2D model produces drastically different results (compared to the 1D propagation geometry), creating difficulties for implementing polarization control in a realistic setting. A proposal for overcoming these difficulties by reducing the non-linear optical medium to a thin slab is presented.

physics.optics↗

arXiv2014

Symplectic and Semiclassical Aspects of the Schläfli Identity

The Schläfli identity, which is important in Regge calculus and loop quantum gravity, is examined from a symplectic and semiclassical standpoint in the special case of flat, 3-dimensional space. In this case a proof is given, based on symplectic geometry. A series of symplectic and Lagrangian manifolds related to the Schläfli identity, including several versions of a Lagrangian manifold of tetrahedra, are discussed. Semiclassical interpretations of the various steps are provided. Possible generalizations to 3-dimensional spaces of constant (nonzero) curvature, involving Poisson-Lie groups and q-deformed spin networks, are discussed.

math-ph↗