Optimal parameters for radiation reaction experiments

Arran, Christopher; Cole, J. M.; Gerstmayr, E.; Blackburn, Tom; Mangles, Stuart; Ridgers, C. P.

doi:10.1088/1361-6587/ab20f6

Cited by 20 publications

(14 citation statements)

References 37 publications

(69 reference statements)

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“…( 23); to see stochastic effects, we must consider instead the width of the distribution [59,61,62]. Given electron beams with narrower initial energy spectra, it would be possible to identify stochastic effects (or their absence) by correlating the mean and variance of the final electron energy spectra [177].…”

Section: Recent Resultsmentioning

confidence: 99%

Radiation reaction in electron–beam interactions with high-intensity lasers

Blackburn

2020

Rev. Mod. Plasma Phys.

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123

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Charged particles accelerated by electromagnetic fields emit radiation, which must, by the conservation of momentum, exert a recoil on the emitting particle. The force of this recoil, known as radiation reaction, strongly affects the dynamics of ultrarelativistic electrons in intense electromagnetic fields. Such environments are found astrophysically, e.g. in neutron star magnetospheres, and will be created in laser-matter experiments in the next generation of high-intensity laser facilities. In many of these scenarios, the energy of an individual photon of the radiation can be comparable to the energy of the emitting particle, which necessitates modelling not only of radiation reaction, but quantum radiation reaction. The worldwide development of multi-petawatt laser systems in large-scale facilities, and the expectation that they will create focussed electromagnetic fields with unprecedented intensities > 10 23 Wcm −2 , has motivated renewed interest in these effects. In this paper I review theoretical and experimental progress towards understanding radiation reaction, and quantum effects on the same, in high-intensity laser fields that are probed with ultrarelativistic electron beams. In particular, we will discuss how analytical and numerical methods give insight into new kinds of radiation-reaction-induced dynamics, as well as how the same physics can be explored in experiments at currently existing laser facilities.

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Section: Recent Resultsmentioning

confidence: 99%

Radiation reaction in electron–beam interactions with high-intensity lasers

Blackburn

2020

Rev. Mod. Plasma Phys.

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123

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“…As the best choice of model depends on the intensity, relaxing the requirement that one must be assumed a priori means that our method provides strong evidence that a particular intensity range has been reached. This is particularly useful for experiments intended to distinguish between radiation reaction models, as this becomes feasible in a reduced number of successful collisions if a 0 can be measured independently [33]. The quantities necessary to use eq.…”

Section: Discussionmentioning

confidence: 99%

Model-independent inference of laser intensity

Blackburn,

Gerstmayr,

Mangles

et al. 2019

Preprint

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An ultrarelativistic electron beam passing through an intense laser pulse emits radiation around its direction of propagation into a characteristic angular profile. Here we show that measurement of the variances of this profile in the planes parallel and perpendicular to the laser polarization, and the mean initial and final energies of the electron beam, allows the intensity of the laser pulse to be inferred in way that is independent of the model of the electron dynamics. The method presented applies whether radiation reaction is important or not, and whether it is classical or quantum in nature, with accuracy of a few per cent across three orders of magnitude in intensity. It is tolerant of electron beams with broad energy spread and finite divergence. In laser-electron beam collision experiments, where spatiotemporal fluctuations cause alignment of the beams to vary from shot to shot, this permits inference of the laser intensity at the collision point, thereby facilitating comparisons between theoretical calculations and experimental data.

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“…The scheme of the numerical experiment is close to the one used in Ref. [ 16 ]. Initially, the electrons in the bunch have the energy

, where

is the relativistic Lorentz-factor.…”

Section: Problem Statementmentioning

confidence: 99%

ML-Based Analysis of Particle Distributions in High-Intensity Laser Experiments: Role of Binning Strategy

Rodimkov

Efimenko

Volokitin

et al. 2020

Entropy

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When entering the phase of big data processing and statistical inferences in experimental physics, the efficient use of machine learning methods may require optimal data preprocessing methods and, in particular, optimal balance between details and noise. In experimental studies of strong-field quantum electrodynamics with intense lasers, this balance concerns data binning for the observed distributions of particles and photons. Here we analyze the aspect of binning with respect to different machine learning methods (Support Vector Machine (SVM), Gradient Boosting Trees (GBT), Fully-Connected Neural Network (FCNN), Convolutional Neural Network (CNN)) using numerical simulations that mimic expected properties of upcoming experiments. We see that binning can crucially affect the performance of SVM and GBT, and, to a less extent, FCNN and CNN. This can be interpreted as the latter methods being able to effectively learn the optimal binning, discarding unnecessary information. Nevertheless, given limited training sets, the results indicate that the efficiency can be increased by optimizing the binning scale along with other hyperparameters. We present specific measurements of accuracy that can be useful for planning of experiments in the specified research area.

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Optimal parameters for radiation reaction experiments

Cited by 20 publications

References 37 publications

Radiation reaction in electron–beam interactions with high-intensity lasers

Radiation reaction in electron–beam interactions with high-intensity lasers

Model-independent inference of laser intensity

ML-Based Analysis of Particle Distributions in High-Intensity Laser Experiments: Role of Binning Strategy

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