Literature DB >> 28788967

Method for computationally efficient design of dielectric laser accelerator structures.

Tyler Hughes, Georgios Veronis, Kent P Wootton, R Joel England, Shanhui Fan.   

Abstract

Dielectric microstructures have generated much interest in recent years as a means of accelerating charged particles when powered by solid state lasers. The acceleration gradient (or particle energy gain per unit length) is an important figure of merit. To design structures with high acceleration gradients, we explore the adjoint variable method, a highly efficient technique used to compute the sensitivity of an objective with respect to a large number of parameters. With this formalism, the sensitivity of the acceleration gradient of a dielectric structure with respect to its entire spatial permittivity distribution is calculated by the use of only two full-field electromagnetic simulations, the original and 'adjoint'. The adjoint simulation corresponds physically to the reciprocal situation of a point charge moving through the accelerator gap and radiating. Using this formalism, we perform numerical optimizations aimed at maximizing acceleration gradients, which generate fabricable structures of greatly improved performance in comparison to previously examined geometries.

Year:  2017        PMID: 28788967     DOI: 10.1364/OE.25.015414

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  3 in total

1.  Inverse-Designed Narrowband THz Radiator for Ultrarelativistic Electrons.

Authors:  Benedikt Hermann; Urs Haeusler; Gyanendra Yadav; Adrian Kirchner; Thomas Feurer; Carsten Welsch; Peter Hommelhoff; Rasmus Ischebeck
Journal:  ACS Photonics       Date:  2022-03-16       Impact factor: 7.077

2.  Predicting in vivo MRI Gradient-Field Induced Voltage Levels on Implanted Deep Brain Stimulation Systems Using Neural Networks.

Authors:  M Arcan Erturk; Eric Panken; Mark J Conroy; Jonathan Edmonson; Jeff Kramer; Jacob Chatterton; S Riki Banerjee
Journal:  Front Hum Neurosci       Date:  2020-02-20       Impact factor: 3.169

3.  Intelligent nanophotonics: merging photonics and artificial intelligence at the nanoscale.

Authors:  Kan Yao; Rohit Unni; Yuebing Zheng
Journal:  Nanophotonics       Date:  2019-01-25       Impact factor: 8.449

  3 in total

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