arXiv subjects

Daniel Fischer

Publications and source records attributed to Daniel Fischer.

13 recordsLinked to original sources

arXiv2026

Kernel-based learning of manifold-to-manifold maps from scattered data

We describe and analyze new methods for approximating manifold-to-manifold maps using only scattered data information. To this end, we first study kernel-based approximation methods for scalar-valued functions defined on a manifold and derive a new sampling inequality and error estimates for functions from Sobolev spaces. After that, these methods are combined with a closest point projection to reconstruct manifold-to-manifold maps. The new methods are analyzed and error estimates are derived. Finally, numerical examples are given to verify the theoretical findings.

math.NA↗

arXiv2026

A delay-programmable two-color femtosecond source for multiphoton ionization studies based on chirped-seed NOPA

We demonstrate a delay-programmable two-color femtosecond source based on a chirped-seed noncollinear optical parametric amplifier. Introducing controlled dispersion into the seed enables spectral selection through pump-seed delay, allowing flexible generation of two independently tunable pulse components with adjustable relative timing at high repetition rate. The temporal and spectral properties are characterized using nonlinear optical cross-correlation and dispersion-scan measurements. As a benchmark application, the source is employed in a COLTRIMS-based multiphoton ionization experiment on trapped Li atoms, revealing delay-dependent ionization pathways and demonstrating its suitability for bichromatic ultrafast spectroscopy.

physics.atom-ph↗

arXiv2025

Time-resolved 3D momentum spectroscopy in continuous wave atomic photoionization

An experimental continuous-wave (cw) pump-probe scheme is demonstrated by investigating the population and photoionization dynamics of an atomic system. Specifically, $^6$Li atoms are initially prepared in optically pumped $2^{2}S_{1/2}$ and $2^{2}P_{3/2}$ states before being excited via multi-photon absorption from a tunable femtosecond laser. The subsequent cascade back to the ground state is analyzed by ionizing the atoms in the field of a cw optical dipole trap laser. Conventional spectroscopic methods such as standard cold-target recoil-ion momentum spectroscopy (COLTRIMS) or velocity map imaging (VMI) cannot provide simultaneous momentum and time-resolved information on an event-by-event basis for the system investigated here. The new approach overcomes this limitation by leveraging electron-recoil ion coincidences, momentum conservation, and the cyclotron motion of the photoelectron in the magnetic spectrometer field. This enables the reconstruction of ionization times and time-of-flight of the charged target fragments with nanosecond resolution. As a result, not only can three-dimensional photoelectron momentum vectors be determined, but the (incoherent) population dynamics of the atomic system also become accessible. Future applications exploring coherent atomic dynamics on the nanosecond timescale would not only expand the scope of time-resolved spectroscopy but can also aid in developing coherent control schemes for precise atomic manipulation.

physics.atom-ph↗

arXiv2025

A Continuous Pump-Probe Experiment to Observe Zeeman Wave Packet Dynamics

In this work, we study the coherent dynamics of an atomic Zeeman wave packet using a continuous pump--probe scheme. A polarized wave packet is generated via few-photon excitation by a femtosecond laser pulse, creating a state with a magnetic moment tilted relative to an external magnetic field. The subsequent Larmor precession of the atoms is probed by continuous ionization in the field of an optical dipole trap (ODT) laser. Photoelectrons and photoions are detected in coincidence using a cold target recoil ion momentum spectrometer (COLTRIMS). While the addition of the ODT enables further cooling of the atomic ensemble, it removes the pulsed timing reference typically used to extract photoelectron momentum distributions in COLTRIMS. Here, we present a method that extends the standard COLTRIMS technique by exploiting redundancy in the measured data to reconstruct the time of ionization. The resulting time-dependent ionization signal reflects the coherent precession of the atomic magnetic moment, enabling real-time access to atomic dynamics on nanosecond timescales.

physics.atom-ph↗

arXiv2024

Demystifying Reinforcement Learning in Production Scheduling via Explainable AI

Deep Reinforcement Learning (DRL) is a frequently employed technique to solve scheduling problems. Although DRL agents ace at delivering viable results in short computing times, their reasoning remains opaque. We conduct a case study where we systematically apply two explainable AI (xAI) frameworks, namely SHAP (DeepSHAP) and Captum (Input x Gradient), to describe the reasoning behind scheduling decisions of a specialized DRL agent in a flow production. We find that methods in the xAI literature lack falsifiability and consistent terminology, do not adequately consider domain-knowledge, the target audience or real-world scenarios, and typically provide simple input-output explanations rather than causal interpretations. To resolve this issue, we introduce a hypotheses-based workflow. This approach enables us to inspect whether explanations align with domain knowledge and match the reward hypotheses of the agent. We furthermore tackle the challenge of communicating these insights to third parties by tailoring hypotheses to the target audience, which can serve as interpretations of the agent's behavior after verification. Our proposed workflow emphasizes the repeated verification of explanations and may be applicable to various DRL-based scheduling use cases.

cs.AI↗

arXiv2024

TattTRN: Template Reconstruction Network for Tattoo Retrieval

Tattoos have been used effectively as soft biometrics to assist law enforcement in the identification of offenders and victims, as they contain discriminative information, and are a useful indicator to locate members of a criminal gang or organisation. Due to various privacy issues in the acquisition of images containing tattoos, only a limited number of databases exists. This lack of databases has delayed the development of new methods to effectively retrieve a potential suspect's tattoo images from a candidate gallery. To mitigate this issue, in our work, we use an unsupervised generative approach to create a balanced database consisting of 28,550 semi-synthetic images with tattooed subjects from 571 tattoo categories. Further, we introduce a novel Tattoo Template Reconstruction Network (TattTRN), which learns to map the input tattoo sample to its respective tattoo template to enhance the distinguishing attributes of the final feature embedding. Experimental results with real data, i.e., WebTattoo and BIVTatt databases, demonstrate the soundness of the presented approach: an accuracy of up to 99% is achieved for checking at most the first 20 entries of the candidate list.

cs.CV↗

arXiv2022

Reliable Detection of Doppelg\"angers based on Deep Face Representations

Doppelg\"angers (or lookalikes) usually yield an increased probability of false matches in a facial recognition system, as opposed to random face image pairs selected for non-mated comparison trials. In this work, we assess the impact of doppelg\"angers on the HDA Doppelg\"anger and Disguised Faces in The Wild databases using a state-of-the-art face recognition system. It is found that doppelg\"anger image pairs yield very high similarity scores resulting in a significant increase of false match rates. Further, we propose a doppelg\"anger detection method which distinguishes doppelg\"angers from mated comparison trials by analysing differences in deep representations obtained from face image pairs. The proposed detection system employs a machine learning-based classifier, which is trained with generated doppelg\"anger image pairs utilising face morphing techniques. Experimental evaluations conducted on the HDA Doppelg\"anger and Look-Alike Face databases reveal a detection equal error rate of approximately 2.7% for the task of separating mated authentication attempts from doppelg\"angers.

cs.CV↗

arXiv2020

Morphing Attack Detection -- Database, Evaluation Platform and Benchmarking

Morphing attacks have posed a severe threat to Face Recognition System (FRS). Despite the number of advancements reported in recent works, we note serious open issues such as independent benchmarking, generalizability challenges and considerations to age, gender, ethnicity that are inadequately addressed. Morphing Attack Detection (MAD) algorithms often are prone to generalization challenges as they are database dependent. The existing databases, mostly of semi-public nature, lack in diversity in terms of ethnicity, various morphing process and post-processing pipelines. Further, they do not reflect a realistic operational scenario for Automated Border Control (ABC) and do not provide a basis to test MAD on unseen data, in order to benchmark the robustness of algorithms. In this work, we present a new sequestered dataset for facilitating the advancements of MAD where the algorithms can be tested on unseen data in an effort to better generalize. The newly constructed dataset consists of facial images from 150 subjects from various ethnicities, age-groups and both genders. In order to challenge the existing MAD algorithms, the morphed images are with careful subject pre-selection created from the contributing images, and further post-processed to remove morphing artifacts. The images are also printed and scanned to remove all digital cues and to simulate a realistic challenge for MAD algorithms. Further, we present a new online evaluation platform to test algorithms on sequestered data. With the platform we can benchmark the morph detection performance and study the generalization ability. This work also presents a detailed analysis on various subsets of sequestered data and outlines open challenges for future directions in MAD research.

cs.CV↗

arXiv2016

REPPlab: An R package for detecting clusters and outliers using exploratory projection pursuit

The R-package REPPlab is designed to explore multivariate data sets using one-dimensional unsupervised projection pursuit. It is useful in practice as a preprocessing step to find clusters or as an outlier detection tool for multivariate numerical data. Except from the package tourr that implements smooth sequences of projection matrices and rggobi that provides an interface to a dynamic graphics package called GGobi, there is no implementation of exploratory projection pursuit tools available in R especially in the context of outlier detection. REPPlab is an R interface for the Java program EPPlab that implements four projection indices and three biologically inspired optimization algorithms. The implemented indices are either adapted to cluster or to outlier detection and the optimization algorithms have at most one parameter to tune. Following the original software EPPlab, the exploration strategy in REPPlab is divided into two steps. Many potentially interesting projections are calculated at the first step and examined at the second step. For this second step, different tools for plotting and combining the results are proposed with specific tools for outlier detection. Compared to EPPlab, some of these tools are new and their performance is illustrated through some simulations and using some real data sets in a clustering context. The functionalities of the package are also illustrated for outlier detection on a new data set that is provided with the package.

stat.CO↗

arXiv2016

Computing the Oja Median in R: The Package OjaNP

The Oja median is one of several extensions of the univariate median to the multivariate case. It has many nice properties, but is computationally demanding. In this paper, we first review the properties of the Oja median and compare it to other multivariate medians. Afterwards we discuss four algorithms to compute the Oja median, which are implemented in our R-package OjaNP. Besides these algorithms, the package contains also functions to compute Oja signs, Oja signed ranks, Oja ranks, and the related scatter concepts. To illustrate their use, the corresponding multivariate one- and $C$-sample location tests are implemented.

stat.CO↗

arXiv2014

Electron and recoil ion momentum imaging with a magneto-optically trapped target

A reaction microscope (ReMi) has been combined with a magneto-optical trap (MOT) for the kinematically complete investigation of atomic break-up processes. With the novel MOTReMi apparatus, the momentum vectors of the fragments of laser-cooled and state-prepared lithium atoms are measured in coincidence and over the full solid angle. %Earlier attempts to realize this combination failed due to intrinsic incompatibilities of the magnetic fields required for MOT and ReMi. The first successful implementation of a MOTReMi could be realized due to an optimized design of the present setup, a nonstandard operation of the MOT, and by employing a switching cycle with alternating measuring and trapping periods. The very low target temperature in the MOT ($2mK$) allow for an excellent momentum resolution. Optical preparation of the target atoms in the excited Li $2^2P_{3/2}$ state was demonstrated providing an atomic polarization of close to 100\percent. While first experimental results were reported earlier, in this work we focus on the technical description of the setup and its performance in commissioning experiments involving target ionization in $266nm$ laser pulses and in collisions with projectile ions.

physics.atom-ph↗

arXiv2014

Polar State in Freestanding Strontium Titanate Nanoparticles

Monodispersed strontium titanate nanoparticles were prepared and studied in detail. It is found that ~10 nm as-prepared stoichiometric nanoparticles are in a polar structural state (with possibly ferroelectric properties) over a broad temperature range. A tetragonal structure, with possible reduction of the electronic hybridization is found as the particle size is reduced. In the 10 nm particles, no change in the local Ti-off centering is seen between 20 and 300 K. The results indicate that nanoscale motifs of SrTiO3 may be utilized in data storage as assembled nano-particle arrays in applications where chemical stability, temperature stability and low toxicity are critical issues.

cond-mat.mtrl-sci↗

arXiv2012

Molecular beam growth of graphene nanocrystals on dielectric substrates

We demonstrate the growth of graphene nanocrystals by molecular beam methods that employ a solid carbon source, and that can be used on a diverse class of large area dielectric substrates. Characterization by Raman and Near Edge X-ray Absorption Fine Structure spectroscopies reveal a sp2 hybridized hexagonal carbon lattice in the nanocrystals. Lower growth rates favor the formation of higher quality, larger size multi-layer graphene crystallites on all investigated substrates. The surface morphology is determined by the roughness of the underlying substrate and graphitic monolayer steps are observed by ambient scanning tunneling microscopy.

cond-mat.mtrl-sci↗