Charged particle motion and radiation in strong electromagnetic fields
The dynamics of charged particles in electromagnetic fields is an essential component of
understanding the most extreme environments in our Universe. In electromagnetic fields of …
understanding the most extreme environments in our Universe. In electromagnetic fields of …
Machine learning for design and control of particle accelerators: A look backward and forward
Particle accelerators are extremely complex machines that are challenging to simulate,
design, and control. Over the past decade, artificial intelligence (AI) and machine learning …
design, and control. Over the past decade, artificial intelligence (AI) and machine learning …
Laboratory realization of relativistic pair-plasma beams
Relativistic electron-positron plasmas are ubiquitous in extreme astrophysical environments
such as black-hole and neutron-star magnetospheres, where accretion-powered jets and …
such as black-hole and neutron-star magnetospheres, where accretion-powered jets and …
A hybrid, asymmetric, linear Higgs factory based on plasma-wakefield and radio-frequency acceleration
The construction of an electron–positron collider'Higgs factory'has been stalled for a decade,
not because of feasibility but because of the cost of conventional radio-frequency (RF) …
not because of feasibility but because of the cost of conventional radio-frequency (RF) …
Perspectives on relativistic electron–positron pair plasma experiments of astrophysical relevance using high-power lasers
The study of relativistic electron–positron pair plasmas is both of fundamental physics
interest and important to understand the processes that shape the magnetic field dynamics …
interest and important to understand the processes that shape the magnetic field dynamics …
Adaptive machine learning for time-varying systems: low dimensional latent space tuning
Abstract Machine learning (ML) tools such as encoder-decoder convolutional neural
networks (CNN) can represent incredibly complex nonlinear functions which map between …
networks (CNN) can represent incredibly complex nonlinear functions which map between …
Stable positron acceleration in thin, warm, hollow plasma channels
Hollow plasma channels are attractive for lepton acceleration because they provide intrinsic
emittance preservation regimes. However, beam breakup instabilities dominate the …
emittance preservation regimes. However, beam breakup instabilities dominate the …
Electron polarization in ultrarelativistic plasma current filamentation instabilities
Plasma current filamentation of an ultrarelativistic electron beam im**ing on an overdense
plasma is investigated, with emphasis on radiation-induced electron polarization. Particle-in …
plasma is investigated, with emphasis on radiation-induced electron polarization. Particle-in …
Energy spread minimization in a beam-driven plasma wakefield accelerator
Next-generation plasma-based accelerators can push electron bunches to gigaelectronvolt
energies within centimetre distances,. The plasma, excited by a driver pulse, generates …
energies within centimetre distances,. The plasma, excited by a driver pulse, generates …
[HTML][HTML] Physics-constrained 3D convolutional neural networks for electrodynamics
We present a physics-constrained neural network (PCNN) approach to solving Maxwell's
equations for the electromagnetic fields of intense relativistic charged particle beams. We …
equations for the electromagnetic fields of intense relativistic charged particle beams. We …