activity
20002022
most citedAdaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces

47 citations · 91 across the 9 of their papers we have counts for

collaborators

11 papers

physics.ins-det2022★ 2 cited

Detection of MeV electrons using a charge integrating hybrid pixel detector

E. Fröjdh, F. Baruffaldi, A. Bergamaschi +13

Electrons are emerging as a strong complement to X-rays for diffraction based studies. In this paper we investigate the performance of a JUNGFRAU detector with 320 um thick silicon…

physics.acc-ph2022★ 20 cited

European Strategy for Particle Physics -- Accelerator R&D Roadmap

C. Adolphsen, D. Angal-Kalinin, T. Arndt +133

The 2020 update of the European Strategy for Particle Physics emphasised the importance of an intensified and well-coordinated programme of accelerator R&D, supporting the design a…

physics.acc-ph2021★ 6 cited

Electron beam transverse phase space tomography using nanofabricated wire scanners with submicrometer resolution

Benedikt Hermann, Vitaliy A. Guzenko, Orell R. Hürzeler +4

Characterization and control of the transverse phase space of high-brightness electron beams is required at free-electron lasers or electron diffraction experiments for emittance m…

physics.acc-ph2019★ 5 cited

Nano-Fabricated Free-Standing Wire-Scanners with Sub-Micrometer Resolution

G. L. Orlandi, C. David, E. Ferrari +10

Diagnostics of the beam transverse profile with ever more demanding spatial resolution is required by the progress on novel particle accelerators - such as laser and plasma driven…

cs.LG2019★ 47 cited

Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces

Johannes Kirschner, Mojmír Mutný, Nicole Hiller +2

Bayesian optimization is known to be difficult to scale to high dimensions, because the acquisition step requires solving a non-convex optimization problem in the same search space…

physics.acc-ph2018

Opportunities in Machine Learning for Particle Accelerators

Auralee Edelen, Christopher Mayes, Daniel Bowring +10

Machine learning (ML) is a subfield of artificial intelligence. The term applies broadly to a collection of computational algorithms and techniques that train systems from raw data…

physics.acc-ph2018

Generation and Measurement of Sub-Micrometer Relativistic Electron Beams

Simona Borrelli, Gian Luca Orlandi, Martin Bednarzik +6

The generation of low-emittance electron beams has received significant interest in recent years. Driven by the requirements of X-ray free electron lasers, the emittance of photoca…

physics.acc-ph2017★ 1 cited

Energy efficiency studies for dual-grating dielectric laser-driven accelerators

Yelong Wei, Mark Ibison, Javier Resta-Lopez +7

Dielectric laser-driven accelerators (DLAs) can provide high accelerating gradients in the GV/m range due to their having higher breakdown thresholds than metals, which opens the w…

physics.ins-det2017

Realtime Tomography of Gas-Jets with a Wollaston Interferometer

A. Adelmann, B. Hermann, R. Ischebeck +4

A tomographic gas-density diagnostic using a single-beam Wollaston interferometer able to characterise non-symmetric density distributions in gas jets is presented. A real-time tom…

physics.ins-det2016★ 1 cited

Design and Test of Wire-Scanners for SwissFEL

G. L. Orlandi, M. Baldinger, H. Brands +14

The SwissFEL light-facility will provide coherent X-rays in the wavelength region 7-0.7 nm and 0.7-0.1 nm. In SwissFEL, view-screens and wire-scanners will be used to monitor the t…

physics.acc-ph2000★ 9 cited

Test Results on the Silicon Pixel Detector for the TTF-FEL Beam Trajectory Monitor

S. Hillert, R. Ischebeck, U. C. Müller +11

Test measurements on the silicon pixel detector for the beam trajectory monitor at the free electron laser of the TESLA test facility are presented. To determine the electronic noi…