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Optical probing of ultrafast laser-induced solid-to-overdense-plasma transitions

Light(Science & Applications) 2024年第5期13卷 973-984页

作者： Yasmina Azamoum Georg Alexander Becker Sebastian Keppler Guillaume Duchateau Stefan Skupin Mickael Grech Fabrice Catoire Sebastian Hell Issa Tamer Marco Hornung Marco Hellwing Alexander Kessler Franck Schorcht malte christoph kaluza GSI Helmholtzzentrum für Schwerionenforschung Planckstr.164291 DarmstadtGermany. Helmholtz Institute Jena Fröbelstieg 307743 JenaGermany. Institute of Optics and Quantum Electronics Friedrich-SchillerUniversität JenaMax-Wien-Platz 107743 JenaGermany. CEA-CESTA 15 Avenue des SablièresCS6000133116 Le BarpCedexFrance Institut Lumière Matière UMR 5306-CNRSUniversitéde Lyon 169622 VilleurbanneFrance. LULI CNRSCEASorbonne UniversitéInstitut Polytechnique de ParisPalaiseauFrance. Universitéde Bordeaux-CNRS-CEA CELIAUMR 5107 TalenceFrance

Understanding the solid target dynamics resulting from the interaction with an ultrashort laser pulse is a challenging fundamental multi-physics problem involving atomic and solid-state physics,plasma physics,and laser *** of the initial interplay of the underlying processes is essential to many applications ranging from lowpower laser regimes like laser-induced ablation to high-power laser regimes like laser-driven ion *** the properties of the so-called pre-plasma formed as the laser pulse’s rising edge ionizes the target is complicated from the theoretical and experimental point of view,and many aspects of this laser-induced transition from solid to overdense plasma over picosecond timescales are still open *** the one hand,laser-driven ion acceleration requires precise control of the pre-plasma because the efficiency of the acceleration process crucially depends on the target properties at the arrival of the relativistic intensity peak of the *** the other hand,efficient laser ablation requires,for example,preventing the so-called“plasma shielding”.By capturing the dynamics of the initial stage of the interaction,we report on a detailed visualization of the pre-plasma formation and ***-thin diamond-like carbon foils are shown to transition from solid to plasma during the laser rising edge with intensities<10^(16)W/cm^(2).Single-shot near-infrared probe transmission measurements evidence sub-picosecond dynamics of an expanding plasma with densities above 10^(23)cm^(−3)(about 100 times the critical plasma density).The complementarity of a solid-state interaction model and kinetic plasma description provides deep insight into the interplay of initial ionization,collisions,and expansion.

关键词： laser acceleration solid

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A Reinforcement Learning approach for the continuous electricity market ofGermany: Trading from the perspective of a wind park operator

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能源与人工智能(英文) 2022年第2期8卷 67-78页

作者： malte Lehna Björn Hoppmann christoph Scholz RenéHeinrich Fraunhofer Institute for Energy Economics and Energy System Technology(IEE) Königstor 5934119 KasselGermany

With the rising extension of renewable energies, the intraday electricity markets have recorded a growingpopularity amongst traders as well as electric utilities to cope with the induced volatility of the energysupply. Through their short trading horizon and continuous nature, the intraday markets offer the abilityto adjust trading decisions from the day-ahead market or reduce trading risk in a short-term notice. Producersof renewable energies utilize the intraday market to lower their forecast risk, by modifying their providedcapacities based on current forecasts. However, the market dynamics are complex due to the fact that thepower grids have to remain stable and electricity is only partly storable. Consequently, robust and intelligenttrading strategies are required that are capable to operate in the intraday market. In this work, we proposea novel autonomous trading approach based on Deep Reinforcement Learning (DRL) algorithms as a possiblesolution. For this purpose, we model the intraday trade as a Markov Decision Process (MDP) and employ theProximal Policy Optimization (PPO) algorithm as our DRL approach. A simulation framework is introducedthat enables the trading of the continuous intraday price in a resolution of one minute steps. We test ourframework in a case study from the perspective of a wind park operator. We include next to general tradeinformation both price and wind forecasts. On a test scenario of German intraday trading results from 2018,we are able to outperform multiple baselines with at least 45.24% improvement, showing the advantage of theDRL algorithm. However, we also discuss limitations and enhancements of the DRL agent, in order to increasethe performance in future works.

关键词： Deep Reinforcement Learning German intraday electricity trading Deep neural networks Markov Decision Process Proximal Policy Optimization Electricity price forecast

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Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents

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Energy and AI 2023年第4期14卷 283-293页

作者： malte Lehna Jan Viebahn Antoine Marot Sven Tomforde christoph Scholz Fraunhofer Institute for Energy Economics and Energy System Technology(IEE) Germany Kassel University:Intelligent Embedded Systems Germany TenneT TSO BV Netherlands AI Lab Reseau de Transport d’Electricite(RTE)France Kiel University:Intelligent Systems Germany

The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy *** a consequence,active grid management is reaching its limits with conventional *** the context of the Learning to Run a Power Network(L2RPN)challenge,it has been shown that Reinforcement Learning(RL)is an efficient and reliable approach with considerable potential for automatic grid *** this article,we analyse the submitted agent from Binbinchen and provide novel strategies to improve the agent,both for the RL and the rule-based *** main improvement is a N-1 strategy,where we consider topology actions that keep the grid stable,even if one line is ***,we also propose a topology reversion to the original grid,which proved to be *** improvements are tested against reference approaches on the challenge test sets and are able to increase the performance of the rule-based agent by 27%.In direct comparison between rule-based and RL agent we find similar ***,the RL agent has a clear computational *** also analyse the behaviour in an exemplary case in more detail to provide additional ***,we observe that through the N-1 strategy,the actions of both the rule-based and the RL agent become more diversified.

关键词： Deep reinforcement learning Electricity grids Learning to run a power network Topology control Proximal policy optimisation

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Design and Baseline Patient Characteristics of the Prospective, Observational, Multicenter and Multinational Cohort Study Comparing Radiofrequency with Cryoablation for Pulmonary Vein Isolation in Patients with Atrial Fibrillation—The Freeze Cohort Study

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International Journal of Clinical Medicine 2014年第19期5卷 1161-1172页

作者： Ellen Hoffmann Uwe Dorwarth Karl Heinz Kuck Jürgen Vogt malte Kuniss Steffen Schneider Jürgen Tebbenjohanns Kyong Ryul Julian Chun Dietrich Andresen Stefan Spitzer Thorsten Lewalter Stephan Willems Johannes Brachmann christoph Stellbrink Bernhard Rauch Jochen Senges Department of Cardiology Klinikum Bogenhausen Munich Germany Department of Cardiology Asklepios Klinik St. Georg Hamburg Germany Ruhr University Bochum Bad Oeynhausen Germany Department of Cardiology Kerckhoff Klinik Bad Nauheim Germany Stiftung Institut für Herzinfarktforschung Ludwigshafen am Rhein Germany Klinikum Hildesheim Hildesheim Germany Center for Cardiology and Angiology Frankfurt CCB Frankfurt am Main Germany Department of Cardiology Vivantes Klinikum am Urban Berlin Germany Praxisklinik Herz und Gefäße Dresden Germany Department of Cardiology Isar Herzzentrum Munich Germany Department of Cardiology Universit&#228res Herzzentrum Hamburg Hamburg Germany Department of Cardiology Klinikum Coburg Coburg Coburg Department of Cardiology Klinikum Bielefeld Bielefeld Germany

Aims: The FREEZE-cohort study (NCT 01360008) is a prospective observational, multicenter and multinational study to evaluate safety and effectiveness of cryoballoon ablation for pulmonary vein isolation as compared to radiofrequency ablation in patients with paroxysmal or persistent atrial fibrillation (lasting < one year) under the conditions of clinical routine. Methods and Results: The study started in 2011 and anticipates inclusion up to 2000 patients in each of the two treatment groups. A total of 37 centers from 8 countries worldwide, all experienced in at least one of the two ablation techniques, participate in the study. The primary outcome parameter of the study is defined as atrial fibrillation recurrence rate during twelve months of follow-up. Secondary outcome parameters include primary success rates, complication rates in general, specific complications with respect to phrenic nerve palsy and pulmonary vein stenosis, radiation exposure, clinical course including death and repeat ablation. Finally specific procedural aspects will be evaluated in a descriptive manner. Preliminary data of the first 1882 patients show that in clinical practice cryoablation is preferentially performed in patients with paroxysmal atrial fibrillation, whereas application of radiofrequency ablation is equally distributed between patients with persistent and paroxysmal atrial fibrillation. Conclusion: Based on multi-center and multi-national data the FREEZE-cohort study will provide important information on long-term efficacy, clinical effectiveness, complication rates and procedural differences between atrial fibrillation patients treated with either cryoablation or radiofrequency ablation.

关键词： Atrial Fibrillation Catheter Ablation Cryoballoon Ablation Radiofrequency Ablation Registry

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