Photoelectron circular dichroism of chiral molecules studied with a continuum-state-corrected strong-field approximation

Motivated by recent experiments on circular dichroism in the photoelectron momentum distributions from strong-field ionization of chiral molecules [C. Lux, Angew. Chem. Int. Ed. 51, 5001 (2012)1433-785110.1002/anie.201109035; C. S. Lehmann, J. Chem. Phys. 139, 234307 (2013)JCPSA60021-960610.1063/1.4844295], we investigate the origin of this effect theoretically. We show that it is not possible to describe photoelectron circular dichroism with the commonly used strong-field approximation due to its plane-wave nature. We therefore apply the Born approximation to the scattering state and use this as a continuum-state correction in the strong-field approximation. We obtain electron distributions for the molecules camphor and fenchone. In order to gain physical insight into the process, we study the contributions of individual molecular orientations. © 2014 American Physical Society.DFG/EXC/QUES

Deep-learning continuous gravitational waves : Multiple detectors and realistic noise

The sensitivity of wide-parameter-space searches for continuous gravitational waves is limited by computational cost. Recently it was shown that deep neural networks (DNNs) can perform all-sky searches directly on (single-detector) strain data [C. Dreissigacker, Phys. Rev. D 100, 044009 (2019)PRVDAQ2470-001010.1103/PhysRevD.100.044009], potentially providing a low-computing-cost search method that could lead to a better overall sensitivity. Here we expand on this study in two respects: (i) using (simulated) strain data from two detectors simultaneously, and (ii) training for directed (i.e., single sky-position) searches in addition to all-sky searches. For a data time span of T=105 s, the all-sky two-detector DNN is about 7% less sensitive (in amplitude h0) at low frequency (f=20 Hz), and about 51% less sensitive at high frequency (f=1000 Hz) compared to fully-coherent matched-filtering (using weave). In the directed case the sensitivity gap compared to matched-filtering ranges from about 7%-14% at f=20 Hz to about 37%-49% at f=1500 Hz. Furthermore we assess the DNN's ability to generalize in signal frequency, spin down and sky-position, and we test its robustness to realistic data conditions, namely gaps in the data and using real LIGO detector noise. We find that the DNN performance is not adversely affected by gaps in the test data or by using a relatively undisturbed band of LIGO detector data instead of Gaussian noise. However, when using a more disturbed LIGO band for the tests, the DNN's detection performance is substantially degraded due to the increase in false alarms, as expected. © 2020 authors

Absorbing boundaries in the mean-field approximation

Absorbing boundaries in the mean-field approximation are investigated and applied to small systems interacting with strong laser fields. Two types of calculations are considered: (i) a variational approach with a complex absorbing potential included in the full Hamiltonian and (ii) the inclusion of a complex absorbing potential in the single-particle equations. It is elucidated that the second approach outperforms the variational approach for small grids. © 2010 The American Physical Society.DFG/EXC/QUES

Adiabaticity in the lateral electron-momentum distribution after strong-field ionization

By solving the time-dependent Schrödinger equation for atoms in short laser pulses of different polarizations, it is shown that in strong-field ionization without rescattering, the lateral width of the electron-momentum distribution corresponds adiabatically to the instantaneous laser field on a sub-laser-cycle time scale, as expected in pure tunneling ionization. In contrast to the distributions along the polarization direction, the width is affected little by depletion or Coulomb effects. © 2012 American Physical Society.DF

Power-to-Heat in thermischen Hochtemperatur-Feststoffspeichern zur Erhöhung der Speicherdichte und Systemflexibilität

Die zukünftige Energieversorgung wird wesentlich durch eine effiziente und bedarfsgerechte Wandlung primärer, überwiegend regenerativer Energieträger zu sekundären Energieträgern wie Strom, Wärme und Kraftstoffe bestimmt. Forschung und Entwicklung stehen daher vor der Herausforderung bei sich ändernden Marktbedingungen kosteneffiziente und flexibel umsetzbare Prozesse zu entwickeln, mit denen die räumlichen und zeitlichen Fluktuationen sowohl bei den Erzeugern als auch bei den Verbrauchern nachhaltig beherrscht werden können. Zur Untersuchung zukünftiger Lösungsoptionen wird im Rahmen des national geförderten Projektes Energy Lab 2.0 ein energietechnischer Anlagenverbund realisiert. Die entstehende Forschungsinfrastruktur ermöglicht es wichtige Energieprozessketten miteinander zu verknüpfen und im Hinblick auf ihr Potenzial zur Erhöhung der Effizienz und Flexibilität des Gesamtsystems zu untersuchen. Eine zentrale Komponente innerhalb des Anlagenverbundes beinhaltet einen lastflexiblen thermischen Hochtemperatur-Feststoffspeicher mit integrierter Elektrobeheizung. Damit wird die anfallende elektrische Leistung aus Anlagenverbund und Netz mit einem hohen Wirkungsgrad in Hochtemperaturwärme umgewandelt, effizient gespeichert und flexibel wieder in den Verbund eingekoppelt. Wesentliches Ziel bei der Entwicklung dieser Speicherkomponente ist es daher, leistungsstarke Konzepte zur elektrischen Beheizung auszuarbeiten, effiziente und betriebsflexible Entwurfslösungen auf Basis von elektrothermischen Studien zu identifizieren und durch experimentelle Arbeiten im Labormaßstab zu unterstützen. Der Beitrag fokussiert die Konzeptentwicklung von elektrisch beheizten Feststoffspeichern, elektro-thermische Simulationsstudien zur Identifizierung eines leistungsstarken, effizienten und betriebsflexiblen Designs. Dazu werden Ergebnisse zur Dimensionierung und zum Integrationsort der Elektrobeheizung vorgestellt

More Security, less Harm? Exploring the Link between Security Measures and Direct Costs of Cyber Incidents within Firms using PLS-PM

As one of the first articles to empirically explore the direct costs of cyber incidents, our research provides novel and significant insights into the structural links between cyber incidents, exposure, and security within firms, as well as the related technical consequences. We employ an explorative approach, which is based on the causal information/cyber risk models proposed by Cohen et al. and Woods & Böhme, as well as PLS-modeling to analyze data from 493 firms that have incurred direct costs from their most severe cyber incident in the last 12 months. These data are part of a larger dataset, based on a representative and stratified random sample of 5,000 organizations that participated in a survey in 2018/19. Based on our model, we discuss the results and derive implications that are highly relevant to the alignment of IT (security) strategy and management. Furthermore, we identify gaps to be assessed in future research

Emission times in high-order harmonic generation

We calculate the emission times of the radiation in high-order harmonic generation using the Gabor transform of numerical data obtained from solving the time-dependent Schrödinger equation in one, two, and three dimensions. Both atomic and molecular systems, including nuclear motion, are investigated. Lewenstein model calculations are used to gauge the performance of the Gabor method. The resulting emission times are compared against the classical simple man's model as well as against the more accurate quantum orbit model based on complex trajectories. The influence of the range of the binding potential (long or short) on the level of agreement is assessed. Our analysis reveals that the short-trajectory harmonics are emitted slightly earlier than predicted by the quantum orbit model. This partially explains recent experimental observations for atoms and molecules. Furthermore, we observe a distinct signature of two-center interference in the emission times for H2 and D2. © 2010 The American Physical Society

Deep-learning continuous gravitational waves

We present a first proof-of-principle study for using deep neural networks (DNNs) as a novel search method for continuous gravitational waves (CWs) from unknown spinning neutron stars. The sensitivity of current wide-parameter-space CW searches is limited by the available computing power, which makes neural networks an interesting alternative to investigate, as they are extremely fast once trained and have recently been shown to rival the sensitivity of matched filtering for black-hole merger signals [D. George and E. A. Huerta, Phys. Rev. D 97, 044039 (2018)10.1103/PhysRevD.97.044039; H. Gabbard, M. Williams, F. Hayes, and C. Messenger, Phys. Rev. Lett. 120, 141103 (2018)10.1103/PhysRevLett.120.141103]. We train a convolutional neural network with residual (shortcut) connections and compare its detection power to that of a fully coherent matched-filtering search using the Weave pipeline [K. Wette, S. Walsh, R. Prix, and M. A. Papa, Phys. Rev. D 97, 123016 (2018)10.1103/PhysRevD.97.123016]. As test benchmarks we consider two types of all-sky searches over the frequency range from 20 to 1000 Hz: an "easy" search using T=105 s of data, and a "harder" search using T=106 s. The detection probability pdet is measured on a signal population for which matched filtering achieves pdet=90% in Gaussian noise. In the easiest test case (T=105 s at 20 Hz) the DNN achieves pdet∼88%, corresponding to a loss in sensitivity depth of ∼5% versus coherent matched filtering. However, at higher frequencies and for longer observation times the DNN detection power decreases, until pdet∼13% and a loss of ∼66% in sensitivity depth in the hardest case (T=106 s at 1000 Hz). We study the DNN generalization ability by testing on signals of different frequencies, spindowns and signal strengths than they were trained on. We observe excellent generalization: only five networks, each trained at a different frequency, would be able to cover the whole frequency range of the search. © 2019 authors. Published by the American Physical Society

Power-to-heat integration in regenerator storage: Enhancing thermal storage capacity and performance,

Electrically heated regenerator storage is an energy- and cost-efficient solution for converting excess electricity and storing it as high-temperature heat. We introduce a transient model to describe the thermodynamic behavior of this hybrid storage system with the fewest number of dimensionless parameters. These characteristic parameters are used to derive key performance indicators for the thermodynamic assessment of the power-to-heat integration in regenerator storage. The results obtained from simulation studies indicate the energy-efficient location of electric heating elements inside the storage tank and provide designs with significantly improved thermal storage capacity and performance. These benefits from power-to-heat extension are particularly evident in the increased cost efficiency and operational flexibility

The Realization of Redistribution Layers for FOWLP by Inkjet Printing

The implementation of additive manufacturing technology (e.g., digital printing) to the electronic packaging segment has recently received increasing attention. In almost all types of Fan-out wafer level packaging (FOWLP), redistribution layers (RDLs) are formed by a combination of photolithography, sputtering and plating process. Alternatively, in this study, inkjet-printed RDLs were introduced for FOWLP. In contrast to a subtractive method (e.g., photolithography), additive manufacturing techniques allow depositing the material only where it is desired. In the current study, RDL structures for different embedded modules were realized by inkjet printing and further characterized by electrical examinations. It was proposed that a digital printing process can be a more efficient and lower-cost solution especially for rapid prototyping of RDLs, since several production steps will be skipped, less material will be wasted and the supply chain will be shortened.EC/H2020/737487/EU/(Ultra)Sound Interfaces and Low Energy iNtegrated SEnsors/SILENS