Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy

Computational techniques allow breaking the limits of traditional imaging methods, such as time restrictions, resolution, and optics flaws. While simple computational methods can be enough for highly controlled microscope setups or just for previews, an increased level of complexity is instead required for advanced setups, acquisition modalities or where uncertainty is high; the need for complex computational methods clashes with rapid design and execution. In all these cases, Automatic Differentiation, one of the subtopics of Artificial Intelligence, may offer a functional solution, but only if a GPU implementation is available. In this paper, we show how a framework built to solve just one optimisation problem can be employed for many different X-ray imaging inverse problems

Review : Deep learning in electron microscopy

Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applications of deep learning in electron microscopy. Following, we discuss hardware and software needed to get started with deep learning and interface with electron microscopes. We then review neural network components, popular architectures, and their optimization. Finally, we discuss future directions of deep learning in electron microscopy

Temporal contrast-dependent modeling of laser-driven solids: studying femtosecond-nanometer interactions and probing

Establishing precise control over the unique beam parameters of laser-accelerated ions from relativistic ultra-short pulse laser-solid interactions has been a major goal for the past 20 years. While the spatio-temporal coupling of laser-pulse and target parameters create transient phenomena at femtosecond-nanometer scales that are decisive for the acceleration performance, these scales have also largely been inaccessible to experimental observation. Computer simulations of laser-driven plasmas provide valuable insight into the physics at play. Nevertheless, predictive capabilities are still lacking due to the massive computational cost to perform these in 3D at high resolution for extended simulation times. This thesis investigates the optimal acceleration of protons from ultra-thin foils following the interaction with an ultra-short ultra-high intensity laser pulse, including realistic contrast conditions up to a picosecond before the main pulse. Advanced ionization methods implemented into the highly scalable, open-source particle-in-cell code PIConGPU enabled this study. Supporting two experimental campaigns, the new methods led to a deeper understanding of the physics of Laser-Wake eld acceleration and Colloidal Crystal melting, respectively, for they now allowed to explain experimental observations with simulated ionization- and plasma dynamics. Subsequently, explorative 3D3V simulations of enhanced laser-ion acceleration were performed on the Swiss supercomputer Piz Daint. There, the inclusion of realistic laser contrast conditions altered the intra-pulse dynamics of the acceleration process significantly. Contrary to a perfect Gaussian pulse, a better spatio-temporal overlap of the protons with the electron sheath origin allowed for full exploitation of the accelerating potential, leading to higher maximum energies. Adapting well-known analytic models allowed to match the results qualitatively and, in chosen cases, quantitatively. However, despite complex 3D plasma dynamics not being reflected within the 1D models, the upper limit of ion acceleration performance within the TNSA scenario can be predicted remarkably well. Radiation signatures obtained from synthetic diagnostics of electrons, protons, and bremsstrahlung photons show that the target state at maximum laser intensity is encoded, previewing how experiments may gain insight into this previously unobservable time frame. Furthermore, as X-ray Free Electron Laser facilities have only recently begun to allow observations at femtosecond-nanometer scales, benchmarking the physics models for solid-density plasma simulations is now in reach. Finally, this thesis presents the first start-to-end simulations of optical-pump, X-ray-probe laser-solid interactions with the photon scattering code ParaTAXIS. The associated PIC simulations guided the planning and execution of an LCLS experiment, demonstrating the first observation of solid-density plasma distribution driven by near-relativistic short-pulse laser pulses at femtosecond-nanometer resolution.Die Erlangung präziser Kontrolle über die einzigartigen Strahlparameter von laserbeschleunigten Ionen aus relativistischen Ultrakurzpuls-Laser-Festkörper-Wechselwirkungen ist ein wesentliches Ziel der letzten 20 Jahre. Während die räumlich-zeitliche Kopplung von Laserpuls und Targetparametern transiente Phänomene auf Femtosekunden- und Nanometerskalen erzeugt, die für den Beschleunigungsprozess entscheidend sind, waren diese Skalen der experimentellen Beobachtung bisher weitgehend unzugänglich. Computersimulationen von lasergetriebenen Plasmen liefern dabei wertvolle Einblicke in die zugrunde liegende Physik. Dennoch mangelt es noch an Vorhersagemöglichkeiten aufgrund des massiven Rechenaufwands, um Parameterstudien in 3D mit hoher Auflösung für längere Simulationszeiten durchzuführen. In dieser Arbeit wird die optimale Beschleunigung von Protonen aus ultradünnen Folien nach der Wechselwirkung mit einem ultrakurzen Ultrahochintensitäts-Laserpuls unter Einbeziehung realistischer Kontrastbedingungen bis zu einer Pikosekunde vor dem Hauptpuls untersucht. Hierbei ermöglichen neu implementierte fortschrittliche Ionisierungsmethoden für den hoch skalierbaren, quelloffenen Partikel-in-Zelle-Code PIConGPU von nun an Studien dieser Art. Bei der Unterstützung zweier Experimentalkampagnen führten diese Methoden zu einem tieferen Verständnis der Laser-Wake eld-Beschleunigung bzw. des Schmelzens kolloidaler Kristalle, da nun experimentelle Beobachtungen mit simulierter Ionisations- und Plasmadynamik erklärt werden konnten. Im Anschluss werden explorative 3D3V Simulationen verbesserter Laser-Ionen-Beschleunigung vorgestellt, die auf dem Schweizer Supercomputer Piz Daint durchgeführt wurden. Dabei veränderte die Einbeziehung realistischer Laserkontrastbedingungen die Intrapulsdynamik des Beschleunigungsprozesses signifikant. Im Gegensatz zu einem perfekten Gauß-Puls erlaubte eine bessere räumlich-zeitliche Überlappung der Protonen mit dem Ursprung der Elektronenwolke die volle Ausnutzung des Beschleunigungspotentials, was zu höheren maximalen Energien führte. Die Adaptation bekannter analytischer Modelle erlaubte es, die Ergebnisse qualitativ und in ausgewählten Fällen auch quantitativ zu bestätigen. Trotz der in den 1D-Modellen nicht abgebildeten komplexen 3D-Plasmadynamik zeigt die Vorhersage erstaunlich gut das obere Limit der erreichbaren Ionen-Energien im TNSA Szenario. Strahlungssignaturen, die aus synthethischen Diagnostiken von Elektronen, Protonen und Bremsstrahlungsphotonen gewonnen wurden, zeigen, dass der Target-Zustand bei maximaler Laserintensität einkodiert ist, was einen Ausblick darauf gibt, wie Experimente Einblicke in dieses bisher unbeobachtbare Zeitfenster gewinnen können. Mit neuen Freie-Elektronen-Röntgenlasern sind Beobachtungen auf Femtosekunden-Nanometerskalen endlich zugänglich geworden. Damit liegt ein Benchmarking der physikalischen Modelle für Plasmasimulationen bei Festkörperdichte nun in Reichweite, aber Experimente sind immer noch selten, komplex, und schwer zu interpretieren. Zuletzt werden daher in dieser Arbeit die ersten Start-zu-End-Simulationen der Pump-Probe Wechselwirkungen von optischem sowie Röntgenlaser mit Festkörpern mittels des Photonenstreu-Codes ParaTAXIS vorgestellt. Darüber hinaus dienten die zugehörigen PIC-Simulationen als Grundlage für die Planung und Durchführung eines LCLS-Experiments zur erstmaligen Beobachtung einer durch nah-relativistische Kurzpuls-Laserpulse getriebenen Festkörper-Plasma-Dichte, dessen Auflösungsbereich gleichzeitig bis auf Femtosekunden und Nanometer vordrang

Temporal contrast-dependent modeling of laser-driven solids - studying femtosecond-nanometer interactions and probing

Establishing precise control over the unique beam parameters of laser-accelerated ions from relativistic ultra-short pulse laser-solid interactions has been a major goal for the past 20 years. While the spatio-temporal coupling of laser-pulse and target parameters create transient phenomena at femtosecond-nanometer scales that are decisive for the acceleration performance, these scales have also largely been inaccessible to experimental observation. Computer simulations of laser-driven plasmas provide valuable insight into the physics at play. Nevertheless, predictive capabilities are still lacking due to the massive computational cost to perform these in 3D at high resolution for extended simulation times. This thesis investigates the optimal acceleration of protons from ultra-thin foils following the interaction with an ultra-short ultra-high intensity laser pulse, including realistic contrast conditions up to a picosecond before the main pulse. Advanced ionization methods implemented into the highly scalable, open-source particle-in-cell code PIConGPU enabled this study. Supporting two experimental campaigns, the new methods led to a deeper understanding of the physics of Laser-Wakefield acceleration and Colloidal Crystal melting, respectively, for they now allowed to explain experimental observations with simulated ionization- and plasma dynamics. Subsequently, explorative 3D3V simulations of enhanced laser-ion acceleration were performed on the Swiss supercomputer Piz Daint. There, the inclusion of realistic laser contrast conditions altered the intra-pulse dynamics of the acceleration process significantly. Contrary to a perfect Gaussian pulse, a better spatio-temporal overlap of the protons with the electron sheath origin allowed for full exploitation of the accelerating potential, leading to higher maximum energies. Adapting well-known analytic models allowed to match the results qualitatively and, in chosen cases, quantitatively. However, despite complex 3D plasma dynamics not being reflected within the 1D models, the upper limit of ion acceleration performance within the TNSA scenario can be predicted remarkably well. Radiation signatures obtained from synthetic diagnostics of electrons, protons, and bremsstrahlung photons show that the target state at maximum laser intensity is encoded, previewing how experiments may gain insight into this previously unobservable time frame. Furthermore, as X-ray Free Electron Laser facilities have only recently begun to allow observations at femtosecond-nanometer scales, benchmarking the physics models for solid-density plasma simulations is now in reach. Finally, this thesis presents the first start-to-end simulations of optical-pump, X-ray-probe laser-solid interactions with the photon scattering code ParaTAXIS. The associated PIC simulations guided the planning and execution of an LCLS experiment, demonstrating the first observation of solid-density plasma distribution driven by near-relativistic short-pulse laser pulses at femtosecond-nanometer resolution

Pattern Recognition

Pattern recognition is a very wide research field. It involves factors as diverse as sensors, feature extraction, pattern classification, decision fusion, applications and others. The signals processed are commonly one, two or three dimensional, the processing is done in real- time or takes hours and days, some systems look for one narrow object class, others search huge databases for entries with at least a small amount of similarity. No single person can claim expertise across the whole field, which develops rapidly, updates its paradigms and comprehends several philosophical approaches. This book reflects this diversity by presenting a selection of recent developments within the area of pattern recognition and related fields. It covers theoretical advances in classification and feature extraction as well as application-oriented works. Authors of these 25 works present and advocate recent achievements of their research related to the field of pattern recognition

FIAS Scientific Report 2011

In the year 2010 the Frankfurt Institute for Advanced Studies has successfully continued to follow its agenda to pursue theoretical research in the natural sciences. As stipulated in its charter, FIAS closely collaborates with extramural research institutions, like the Max Planck Institute for Brain Research in Frankfurt and the GSI Helmholtz Center for Heavy Ion Research, Darmstadt and with research groups at the science departments of Goethe University. The institute also engages in the training of young researchers and the education of doctoral students. This Annual Report documents how these goals have been pursued in the year 2010. Notable events in the scientific life of the Institute will be presented, e.g., teaching activities in the framework of the Frankfurt International Graduate School for Science (FIGSS), colloquium schedules, conferences organized by FIAS, and a full bibliography of publications by authors affiliated with FIAS. The main part of the Report consists of short one-page summaries describing the scientific progress reached in individual research projects in the year 2010..

Rapid data processing for ultrafast x-ray computed tomography using scalable and modular CUDA based pipelines

Ultrafast X-ray tomography is an advanced imaging technique for the study of dynamic processes basing on the principles of electron beam scanning. A typical application case for this technique is e.g.the study of multiphase flows, that is, flows of mixtures of substances such as gas-liquid flows in pipelines or chemical reactors. At Helmholtz-Zentrum Dresden-Rossendorf (HZDR) a number of such tomography scanners are operated. Currently, there are two main points limiting their application in some fields. First, after each CT scan sequence the data of the radiation detector must be downloaded from the scanner to a data processing machine. Second, the current data processing is comparably time-consuming compared to the CT scan sequence interval. To enable online observations or use this technique to control actuators in real-time, a modular and scalable data processing tool has been developed, consisting of user-definable stages working independently together in a so called data processing pipeline, that keeps up with the CT scanner’s maximal frame rate of up to 8 kHz. The newly developed data processing stages are freely programmable and combinable. In order to achieve the highest processing performance all relevant data processing steps, which are required for a standard slice image reconstruction, were individually implemented in separate stages using Graphics Processing Units (GPUs) and NVIDIA’s CUDA programming language. Data processing performance tests on different high-end GPUs (Tesla K20c, GeForce GTX 1080, Tesla P100) showed excellent performance