arXiv subjects

Jens Viefhaus

Publications and source records attributed to Jens Viefhaus.

14 recordsLinked to original sources

arXiv2025

Offset Finding of Beamline Parameters on the METRIXS Beamline at BESSY II Using Machine Learning

Beamline alignment is challenging as the beamline components must be set up ideally so that the rays follow the desired optical path. Automated methods using a digital twin allow for faster diagnostics and improved beam properties compared to manual tuning. We introduce an automated method of finding the offsets to improve this digital twin model. These offsets represent the unknown but constant differences between the beamline parameter positions as set up at the physical beamline and the corresponding parameter positions of its digital twin. Our method assumes the capability to execute precise relative movements with a known step size for these parameters, although the absolute position information is unknown. By combining the surrogate model with a global optimizer, we successfully determine offsets for 34 beamline parameters on a simulated METRIXS beamline at the BESSY II synchrotron radiation source in Berlin.

physics.acc-ph↗

arXiv2025

Inverse Surrogate Model of a Soft X-Ray Spectrometer using Domain Adaptation

In this study, we present a method to create a robust inverse surrogate model for a soft X-ray spectrometer. During a beamtime at an electron storage ring, such as BESSY II, instrumentation and beamlines are required to be correctly aligned and calibrated for optimal experimental conditions. In order to automate these processes, machine learning methods can be developed and implemented, but in many cases these methods require the use of an inverse model which maps the output of the experiment, such as a detector image, to the parameters of the device. Due to limited experimental data, such models are often trained with simulated data, which creates the challenge of compensating for the inherent differences between simulation and experiment. In order to close this gap, we demonstrate the application of data augmentation and adversarial domain adaptation techniques, with which we can predict absolute coordinates for the automated alignment of our spectrometer. Bridging the simulation-experiment gap with minimal real-world data opens new avenues for automated experimentation using machine learning in scientific instrumentation.

physics.ins-det↗

arXiv2025

Reconstructing Time-of-Flight Detector Values of Angular Streaking Using Machine Learning

Angular streaking experiments enable for experimentation in the attosecond regions. However, the deployed Time-of-flight detectors are susceptible to noise and failure. These shortcomings make the outputs of the Time-of-flight detectors hard to understand for humans and further processing, such as for example the extraction of beam properties. In this article, we present an approach to remove high noise levels and reconstruct up to three failed Time-of-flight detectors from an arrangement of 16 Time-of-flight detectors. Due to its fast evaluation time, the presented method is applicable online during a running experiment. It is trained with simulation data, and we show the results of denoising and reconstruction of our method on real-world experiment data.

physics.data-an↗

arXiv2023

Artificial intelligence for online characterization of ultrashort X-ray free-electron laser pulses

X-ray free-electron lasers (XFELs) as the world's brightest light sources provide ultrashort X-ray pulses with a duration typically in the order of femtoseconds. Recently, they have approached and entered the attosecond regime, which holds new promises for single-molecule imaging and studying nonlinear and ultrafast phenomena such as localized electron dynamics. The technological evolution of XFELs toward well-controllable light sources for precise metrology of ultrafast processes has been, however, hampered by the diagnostic capabilities for characterizing X-ray pulses at the attosecond frontier. In this regard, the spectroscopic technique of photoelectron angular streaking has successfully proven how to non-destructively retrieve the exact time-energy structure of XFEL pulses on a single-shot basis. By using artificial intelligence techniques, in particular convolutional neural networks, we here show how this technique can be leveraged from its proof-of-principle stage toward routine diagnostics even at high-repetition-rate XFELs, thus enhancing and refining their scientific accessibility in all related disciplines.

physics.data-an↗

arXiv2022

Unsupervised real-world knowledge extraction via disentangled variational autoencoders for photon diagnostics

We present real-world data processing on measured electron time-of-flight data via neural networks. Specifically, the use of disentangled variational autoencoders on data from a diagnostic instrument for online wavelength monitoring at the free electron laser FLASH in Hamburg. Without a-priori knowledge the network is able to find representations of single-shot FEL spectra, which have a low signal-to-noise ratio. This reveals, in a directly human-interpretable way, crucial information about the photon properties. The central photon energy and the intensity as well as very detector-specific features are identified. The network is also capable of data cleaning, i.e. denoising, as well as the removal of artefacts. In the reconstruction, this allows for identification of signatures with very low intensity which are hardly recognisable in the raw data. In this particular case, the network enhances the quality of the diagnostic analysis at FLASH. However, this unsupervised method also has the potential to improve the analysis of other similar types of spectroscopy data.

physics.data-an↗

arXiv2022

Electronic Quantum Coherence in Glycine Molecules Probed with Ultrashort X-ray Pulses in Real Time

Quantum coherence between electronic states of a photoionized molecule and the resulting process of ultrafast electron-hole migration have been put forward as a possible quantum mechanism of charge-directed reactivity governing the photoionization-induced molecular decomposition. Attosecond experiments based on the indirect (fragment ion-based) characterization of the proposed electronic phenomena suggest that the photoionization-induced electronic coherence can survive for tens of femtoseconds, while some theoretical studies predict much faster decay of the coherence due to the quantum uncertainty in the nuclear positions and the nuclear-motion effects. The open questions are: do long-lived electronic quantum coherences exist in complex molecules and can they be probed directly, i.e. via electronic observables? Here, we use x-rays both to create and to directly probe quantum coherence in the photoionized amino acid glycine. The outgoing photoelectron wave leaves behind a positively charged ion that is in a coherent superposition of quantum mechanical eigenstates lying within the ionizing pulse spectral bandwidth. Delayed x-ray pulses track the induced coherence through resonant x-ray absorption that induces Auger decay and by the photoelectron emission from sequential double photoionization. Sinusoidal temporal modulation of the detected signal at early times (0 - 25 fs) is observed in both measurements. Advanced ab initio many-electron simulations, taking into account the quantum uncertainty in the nuclear positions, allow us to explain the first 25 fs of the detected coherent quantum evolution in terms of the electronic coherence.

physics.chem-ph↗

arXiv2022

Optimizing a Superconducting Radiofrequency Gun Using Deep Reinforcement Learning

Superconducting photoelectron injectors are a promising technique for generating high brilliant pulsed electron beams with high repetition rates and low emittances. Experiments such as ultra-fast electron diffraction, experiments at the Terahertz scale, and energy recovery linac applications require such properties. However, optimization of the beam properties is challenging due to the high amount of possible machine parameter combinations. In this article, we show the successful automated optimization of beam properties utilizing an already existing simulation model. To reduce the amount of required computation time, we replace the costly simulation by a faster approximation with a neural network. For optimization, we propose a reinforcement learning approach leveraging the simple computation of the derivative of the approximation. We prove that our approach outperforms common optimization methods for the required function evaluations given a defined minimum accuracy.

physics.acc-ph↗

arXiv2021

Measurement of spin dynamics in a layered nickelate using x-ray photon correlation spectroscopy: Evidence for intrinsic destabilization of incommensurate stripes at low temperatures

We study the temporal stability of stripe-type spin order in a layered nickelate with X-ray photon correlation spectroscopy and observe fluctuations on time scales of tens of minutes over a wide temperature range. These fluctuations show an anomalous temperature dependence: they slow down at intermediate temperatures and speed up both upon heating and cooling. This behavior appears to be directly connected with spatial correlations: stripes fluctuate slowly when stripe correlation lengths are large and become faster when spatial correlations decrease. A low-temperature decay of nickelate stripe correlations, reminiscent of what occurs in cuprates due to a competition between stripes and superconductivity, hence occurs via loss of both spatial and temporal correlations.

cond-mat.str-el↗

arXiv2019

Direct Visualization of Spatial inhomogeneity of Spin Stripes Order in La1.72Sr0.28NiO4

In several strongly correlated electron systems, defects, charge and local lattice distortions are found to show complex inhomogeneous spatial distributions. There is growing evidence that such inhomogeneity plays a fundamental role in unique functionality of quantum complex materials. La1.72Sr0.28NiO4 is a prototypical strongly correlated material showing spin striped order associated with lattice and charge modulations. In this work we present the spatial distribution of the spin organization by applying micro X-ray diffraction to La1.72Sr0.28NiO4, mapping the spin-density-wave order below the 120K onset temperature. We find that the spin-density-wave order shows the formation of nanoscale puddles with large spatial fluctuations. The nano-puddle density changes on the microscopic scale forming a multiscale phase separation extending from nanoscale to micron scale with scale-free distribution. Indeed spin-density-wave striped puddles are disconnected by spatial regions with different stripe orientation or negligible spin-density-wave order. The present work highlights the complex nanoscale phase separation of spin stripes in nickelate perovskites and opens the question of the energetics at domain interfaces

cond-mat.mes-hall↗

arXiv2018

Photophysics of indole upon x-ray absorption

A photofragmentation study of gas-phase indole (C$_8$H$_7$N) upon single-photon ionization at a photon energy of 420 eV is presented. Indole was primarily inner-shell ionized at its nitrogen and carbon $1s$ orbitals. Electrons and ions were measured in coincidence by means of velocity map imaging. The angular relationship between ionic fragments is discussed along with the possibility to use the angle-resolved coincidence detection to perform experiments on molecules that are strongly oriented in their recoil-frame. The coincident measurement of electrons and ions revealed fragmentation-pathway-dependent electron spectra, linking the structural fragmentation dynamics to different electronic excitations. Evidence for photoelectron-impact self-ionization was observed.

physics.atm-clus↗

arXiv2017

Near L-Edge Single and Multiple Photoionization of Singly Charged Iron Ions

Absolute cross sections for m-fold photoionization (m=1,...,6) of Fe+ by a single photon were measured employing the photon-ion merged-beams setup PIPE at the PETRA III synchrotron light source, operated by DESY in Hamburg, Germany. Photon energies were in the range 680-920 eV which covers the photoionization resonances associated with 2p and 2s excitation to higher atomic shells as well as the thresholds for 2p and 2s ionization. The corresponding resonance positions were measured with an uncertainty of +- 0.2 eV. The cross section for Fe+ photoabsorption is derived as the sum of the individually measured cross-sections for m-fold ionization. Calculations of the Fe+ absorption cross sections have been carried out using two different theoretical approaches, Hartree-Fock including relativistic extensions and fully relativistic Multi-Configuration Dirac Fock. Apart from overall energy shifts of up to about 3 eV, the theoretical cross sections are in good agreement with each other and with the experimental results. In addition, the complex deexcitation cascades after the creation of inner-shell holes in the Fe+ ion have been tracked on the atomic fine-structure level. The corresponding theoretical results for the product charge-state distributions are in much better agreement with the experimental data than previously published configuration-average results. The present experimental and theoretical results are valuable for opacity calculations and are expected to pave the way to a more accurate determination of the iron abundance in the interstellar medium.

astro-ph.IM↗

arXiv2017

Field-free deterministic ultra fast creation of skyrmions by spin orbit torques

Magnetic skyrmions are currently the most promising option to realize current-driven magnetic shift registers. A variety of concepts to create skyrmions were proposed and demonstrated. However, none of the reported experiments show controlled creation of single skyrmions using integrated designs. Here, we demonstrate that skyrmions can be generated deterministically on subnanosecond timescales in magnetic racetracks at artificial or natural defects using spin orbit torque (SOT) pulses. The mechanism is largely similar to SOT-induced switching of uniformly magnetized elements, but due to the effect of the Dzyaloshinskii-Moriya interaction (DMI), external fields are not required. Our observations provide a simple and reliable means for skyrmion writing that can be readily integrated into racetrack devices.

cond-mat.mtrl-sci↗

arXiv2016

High-dynamic-range water window ptychography

Ptychographic imaging with soft X-rays, especially in the water window energy range, suffers from limited detector dynamic range that directly influences the maximum spatial resolution achievable. High-dynamic-range data can be obtained by multiple exposures. By this approach we have increased the dynamic range of a ptychographic data set by a factor of 76 and obtained diffraction signal till the corners of the detector. The real space half period resolution was improved from 50 nm for the single exposure data to 18 nm for the high-dynamic-range data.

physics.optics↗

arXiv2015

Water Window Ptychographic Imaging with Characterized Coherent X-rays

We report on a ptychographical coherent diffractive imaging experiment in the water window with focused soft X-rays at $500~\mathrm{eV}$. An X-ray beam with high degree of coherence was selected for ptychography at the P04 beamline of the PETRA III synchrotron radiation source. We measured the beam coherence with the newly developed non-redundant array method. A pinhole $2.6~\mathrm{μm}$ in size selected the coherent part of the beam and was used for ptychographic measurements of a lithographically manufactured test sample and fossil diatom. The achieved resolution was $53~\mathrm{nm}$ for the test sample and only limited by the size of the detector. The diatom was imaged at a resolution better than $90~\mathrm{nm}$.

physics.bio-ph↗