LUX -- A Laser-Plasma Driven Undulator Beamline

The LUX beamline is a novel type of laser-plasma accelerator. Building on the joint expertise of the University of Hamburg and DESY the beamline was carefully designed to combine state-of-the-art expertise in laser-plasma acceleration with the latest advances in accelerator technology and beam diagnostics. LUX introduces a paradigm change moving from single-shot demonstration experiments towards available, stable and controllable accelerator operation. Here, we discuss the general design concepts of LUX and present first critical milestones that have recently been achieved, including the generation of electron beams at the repetition rate of up to 5 Hz with energies above 600 MeV and the generation of spontaneous undulator radiation at a wavelength well below 9 nm.Comment: submitte

Chirp mitigation of plasma-accelerated beams using a modulated plasma density

Plasma-based accelerators offer the possibility to drive future compact light sources and high-energy physics applications. Achieving good beam quality, especially a small beam energy spread, is still one of the major challenges. For stable transport, the beam is located in the focusing region of the wakefield which covers only the slope of the accelerating field. This, however, imprints a longitudinal energy correlation (chirp) along the bunch. Here, we propose an alternating focusing scheme in the plasma to mitigate the development of this chirp and thus maintain a small energy spread

Ice nucleation activity of agricultural soil dust aerosols from Mongolia, Argentina, and Germany

Soil dust particles emitted from agricultural areas contain considerable mass fractions of organic material. Also, soil dust particles may act as carriers for potentially ice-active biological particles. In this work, we present ice nucleation experiments conducted in the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) cloud chamber. We investigated the ice nucleation efficiency of four types of soil dust from different regions of the world. The results are expressed as ice nucleation active surface site (INAS) densities and presented for the immersion freezing and the deposition nucleation mode. For immersion freezing occurring at 254 K, samples from Argentina, China, and Germany show ice nucleation efficiencies which are by a factor of 10 higher than desert dusts. On average, the difference in ice nucleation efficiencies between agricultural and desert dusts becomes significantly smaller at temperatures below 247 K. In the deposition mode the soil dusts showed higher ice nucleation activity than Arizona Test Dust over a temperature range between 232 and 248 K and humidities RHice up to 125%. INAS densities varied between 109 and 1011m-2 for these thermodynamic conditions. For one soil dust sample (Argentinian Soil), the effect of treatments with heat was investigated. Heat treatments (383 K) did not affect the ice nucleation efficiency observed at 249 K. This finding presumably excludes proteinaceous ice-nucleating entities as the only source of the increased ice nucleation efficiency.Fil: Steinke, I.. Karlsruhe Institute of Technology; AlemaniaFil: Funk, R.. Leibniz Centre for Agricultural Landscape Research; AlemaniaFil: Busse, J.. Leibniz Centre for Agricultural Landscape Research; AlemaniaFil: Iturri, Laura Antonela. Universidad Nacional de La Pampa; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; ArgentinaFil: Kirchen, S.. Karlsruhe Institute of Technology; AlemaniaFil: Leue, M.. Leibniz Centre for Agricultural Landscape Research; AlemaniaFil: Möhler, O.. Karlsruhe Institute of Technology; AlemaniaFil: Schwartz, T.. Universidad Nacional de La Pampa; ArgentinaFil: Schnaiter, M.. Karlsruhe Institute of Technology; AlemaniaFil: Sierau, B.. Institute for Atmospheric and Climate Science; SuizaFil: Toprak, E.. Karlsruhe Institute of Technology; AlemaniaFil: Ullrich, R.. Karlsruhe Institute of Technology; AlemaniaFil: Ulrich, A.. Leibniz Centre for Agricultural Landscape Research; AlemaniaFil: Hoose, C.. Karlsruhe Institute of Technology; AlemaniaFil: Leisner, T.. Karlsruhe Institute of Technology; Alemania. Heidelberg University; Alemani

Status Report of the 50 MeV LPA-Based Injector at ATHENA for a Compact Storage Ring

Laser-based plasma accelerators (LPA) have successfully demonstrated their capability to generate high-energy electron beams with intrinsically short bunch lengths and high peak currents at a setup with a small footprint. These properties make them attractive drivers for a broad range of different applications including injectors for rf-driven, ring-based light sources. In close collaboration the Deutsches Elektronen-Synchrotron (DESY), the Karlsruhe Institute of Technology (KIT) and the Helmholtz Institute Jena aim to develop a 50 MeV plasma injector and demonstrate the injection into a compact storage ring. This storage ring will be built within the project cSTART at KIT. As part of the ATHENA (Accelerator Technology HElmholtz iNfrAstructure) project, DESY will design, setup and operate a 50 MeV plasma injector prototype for this endeavor. This contribution gives a status update of the 50 MeV LPA-based injector and presents a first layout of the prototype design at DESY in Hamburg

2022 Review of Data-Driven Plasma Science

Data-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma science whose progress is driven strongly by data and data analyses. Plasma is considered to be the most ubiquitous form of observable matter in the universe. Data associated with plasmas can, therefore, cover extremely large spatial and temporal scales, and often provide essential information for other scientific disciplines. Thanks to the latest technological developments, plasma experiments, observations, and computation now produce a large amount of data that can no longer be analyzed or interpreted manually. This trend now necessitates a highly sophisticated use of high-performance computers for data analyses, making artificial intelligence and machine learning vital components of DDPS. This article contains seven primary sections, in addition to the introduction and summary. Following an overview of fundamental data-driven science, five other sections cover widely studied topics of plasma science and technologies, i.e., basic plasma physics and laboratory experiments, magnetic confinement fusion, inertial confinement fusion and high-energy-density physics, space and astronomical plasmas, and plasma technologies for industrial and other applications. The final section before the summary discusses plasma-related databases that could significantly contribute to DDPS. Each primary section starts with a brief introduction to the topic, discusses the state-of-the-art developments in the use of data and/or data-scientific approaches, and presents the summary and outlook. Despite the recent impressive signs of progress, the DDPS is still in its infancy. This article attempts to offer a broad perspective on the development of this field and identify where further innovations are required

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

Erratum to: EuPRAXIA Conceptual Design Report – Eur. Phys. J. Special Topics 229, 3675-4284 (2020), https://doi.org/10.1140/epjst/e2020-000127-8

International audienceThe online version of the original article can be found at http://https://doi.org/10.1140/epjst/e2020-000127-8</A