Data-driven Science and Machine Learning Methods in Laser-Plasma Physics

Döpp, A.; Eberle, Christoph; Howard, Sunny; Irshad, Faran; Lin, Jingquan; Streeter, Matthew

doi:10.48550/arxiv.2212.00026

Cited by 3 publications

(4 citation statements)

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“…Inspired by recent progress in machine-learning-based laser science [13] , here we present the concept for a singleshot method that utilizes compressed sensing (CS) to resolve the wavefront in both the spectral and spatial domains. The paper is structured as follows.…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral compressive wavefront sensing

Howard

Esslinger²,

Wang³

et al. 2023

High Pow Laser Sci Eng

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Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot. A deep unrolling algorithm is utilised for the snapshot compressive imaging reconstruction due to its parameter efficiency and superior speed relative to other methods, potentially allowing for online reconstruction. The algorithm's regularisation term is represented using neural network with 3D convolutional layers, to exploit the spatio-spectral correlations that exist in laser wavefronts. Compressed sensing is not typically applied to modulated signals, but we demonstrate its success here. Furthermore, we train a neural network to predict the wavefronts from a lateral shearing interferogram in terms of Zernike polynomials, which again increases the speed of our technique without sacrificing fidelity. This method is supported with simulation-based results. While applied to the example of lateral shearing interferometry, the methods presented here are generally applicable to a wide range of signals, including Shack-Hartmann-type sensors. The results may be of interest beyond the context of laser wavefront characterization, including within quantitative phase imaging.

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Section: Introductionmentioning

confidence: 99%

Hyperspectral compressive wavefront sensing

Howard

Esslinger²,

Wang³

et al. 2023

High Pow Laser Sci Eng

Self Cite

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“…A particularly popular method for the optimization of laser-plasma accelerators is Bayesian optimization (BO) [12][13][14]. BO is a global optimization method based on searching optima in a probabilistic surrogate model that is updated iteratively as the experiment progresses.…”

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confidence: 99%

“…While it would appear to the optimizer that this particular position in the input space X produced stable electron beams at 350 MeV, the spectrum is quite unstable, with most charge contained in a beam with fluctuating energy between 200 MeV and 350 MeV. To separate the signal of individual bunches from the overall electron spectrum, we use a Gaussian mixture model (GMM) [12]. The GMM is an efficient and robust way to decompose the electron spectrum into its constituent parts, which can then be analyzed separately.…”

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confidence: 99%

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Pareto Optimization of a Laser Wakefield Accelerator

Irshad¹,

Eberle²,

Foerster³

et al. 2023

Preprint

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Measuring spatio-temporal couplings using modal spatio-spectral wavefront retrieval

Weisse¹,

Esslinger²,

Howard³

et al. 2023

Opt. Express

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Knowledge of spatio-temporal couplings such as pulse-front tilt or curvature is important to determine the focused intensity of high-power lasers. Common techniques to diagnose these couplings are either qualitative or require hundreds of measurements. Here we present both a new algorithm for retrieving spatio-temporal couplings, as well as novel experimental implementations. Our method is based on the expression of the spatio-spectral phase in terms of a Zernike-Taylor basis, allowing us to directly quantify the coefficients for common spatio-temporal couplings. We take advantage of this method to perform quantitative measurements using a simple experimental setup, consisting of different bandpass filters in front of a Shack-Hartmann wavefront sensor. This fast acquisition of laser couplings using narrowband filters, abbreviated FALCON, is easy and cheap to implement in existing facilities. To this end, we present a measurement of spatio-temporal couplings at the ATLAS-3000 petawatt laser using our technique.

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Data-driven Science and Machine Learning Methods in Laser-Plasma Physics

Cited by 3 publications

References 0 publications

Hyperspectral compressive wavefront sensing

Hyperspectral compressive wavefront sensing

Pareto Optimization of a Laser Wakefield Accelerator

Measuring spatio-temporal couplings using modal spatio-spectral wavefront retrieval

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