arXiv subjects

Oliver Anton

Publications and source records attributed to Oliver Anton.

5 recordsLinked to original sources

arXiv2026

Quantum Deep Learning: A Comprehensive Review

Quantum deep learning (QDL) explores the use of both quantum and quantum-inspired resources to determine when deep learning's core capabilities, such as expressivity, generalization, and scalability, can be enhanced based on specific resource constraints. Distinct from broader quantum machine learning, QDL emphasizes compositional depth at the pipeline level and the integration of quantum or quantum-inspired components within end-to-end workflows. This review provides an operational definition of QDL and introduces a taxonomy comprising four primary paradigms: hybrid quantum-classical models, quantum deep neural networks, quantum algorithms for deep learning primitives, and quantum-inspired classical algorithms. Theoretical principles are connected to advanced architectures, software toolchains, and experimental demonstrations across superconducting, trapped-ion, photonic, semiconductor spin, and neutral-atom systems, as well as quantum annealers. Claims of quantum advantage are critically assessed by distinguishing provable complexity-theoretic separations from empirical observations. The analysis characterizes trade-offs between model expressivity, trainability, and classical simulability, while systematically detailing the bottlenecks imposed by optimization landscapes, input-output access models, and hardware constraints. Applications are surveyed in domains encompassing image classification, natural language processing, scientific discovery, quantum data processing, and quantum optimal control, underscoring fair benchmarking against optimized classical counterparts and a comprehensive assessment of resource requirements. This review serves as a tutorial entry point for graduate students while guiding readers to specialized literature. It concludes with a verification-aware roadmap to transition QDL from near-term demonstrations to scalable and fault-tolerant implementations.

quant-ph↗

arXiv2024

Micro-integrated crossed-beam optical dipole trap system with long-term alignment stability for mobile atomic quantum technologies

Quantum technologies extensively use laser light for state preparation, manipulation, and readout. For field applications, these systems must be robust and compact, driving the need for miniaturized and highly stable optical setups and system integration. In this work, we present a micro-integrated crossed-beam optical dipole trap setup, the $μ$XODT, designed for trapping and cooling $^{87}\text{Rb}$. This fiber-coupled setup operates at $1064\,\text{nm}$ wavelength with up to $2.5\,\text{W}$ optical power and realizes a free-space crossed beam geometry. The $μ$XODT precisely overlaps two focused beams ($w_0 \approx 33\,μ\text{m}$) at their waists in a $45^\circ$ crossing angle, achieving a position difference $\leq 3.4\,μ\text{m}$ and 0.998 power ratio between both beams with long-term stability. We describe the design and assembly process in detail, along with optical and thermal tests with temperatures of up to $65\,^\circ C$. The system's volume of $25\,\text{ml}$ represents a reduction of more than two orders of magnitude compared to typically used macroscopic setups, while demonstrating exceptional mechanical robustness and thermal stability. The $μ$XODT is integrated with a $^{87}\text{Rb}$ 3D MOT setup, trapping $3 \times 10^5$ atoms from a laser-cooled atomic cloud, and has shown no signs of degradation after two years of operation.

physics.atom-ph↗

arXiv2023

Review and experimental benchmarking of machine learning algorithms for efficient optimization of cold atom experiments

The generation of cold atom clouds is a complex process which involves the optimization of noisy data in high dimensional parameter spaces. Optimization can be challenging both in and especially outside of the lab due to lack of time, expertise, or access for lengthy manual optimization. In recent years, it was demonstrated that machine learning offers a solution since it can optimize high dimensional problems quickly, without knowledge of the experiment itself. In this paper we present results showing the benchmarking of nine different optimization techniques and implementations, alongside their ability to optimize a Rubidium (Rb) cold atom experiment. The investigations are performed on a 3D $^{87}$Rb molasses with 10 and 18 adjustable parameters, respectively, where the atom number obtained by absorption imaging was chosen as the test problem. We further compare the best performing optimizers under different effective noise conditions by reducing the Signal-to-Noise ratio of the images via adapting the atomic vapor pressure in the 2D+ MOT and the detection laser frequency stability.

physics.atom-ph↗

arXiv2023

A Dual-Species Atom Interferometer Payload for Operation on Sounding Rockets

We report on the design and the construction of a sounding rocket payload capable of performing atom interferometry with Bose-Einstein condensates of $^{41}$K and $^{87}$Rb. The apparatus is designed to be launched in two consecutive missions with a VSB-30 sounding rocket and is qualified to withstand the expected vibrational loads of 1.8 g root-mean-square in a frequency range between 20 - 2000 Hz and the expected static loads during ascent and re-entry of 25 g. We present a modular design of the scientific payload comprising a physics package, a laser system, an electronics system and a battery module. A dedicated on-board software provides a largely automated process of predefined experiments. To operate the payload safely in laboratory and flight mode, a thermal control system and ground support equipment has been implemented and will be presented. The payload presented here represents a cornerstone for future applications of matter wave interferometry with ultracold atoms on satellites.

physics.atom-ph↗

arXiv2019

ZERODUR based optical systems for quantum gas experiments in space

Numerous quantum technologies make use of a microgravity environment e.g. in space. Operating in this extreme environment makes high demands on the experiment and especially the laser system regarding miniaturization and power consumption as well as mechanical and thermal stability. In our systems, optical modules consisting of ZERODUR based optical benches with free-space optics are combined with fiber components. Suitability of the technology has been demonstrated in the successful sounding rocket missions FOKUS, KALEXUS and MAIUS-1. Here, we report on our toolkit for stable optical benches including mounts, fixed and adjustable mirrors as well as polarization maintaining fiber collimators and couplers made from ZERODUR. As an example, we present the optical modules for the scientific rocket payload of MAIUS-2, a quantum gas experiment performing dual-species atom interferometry with Bose-Einstein condensates. The modules are used on the one hand to stabilize the laser frequencies and on the other hand to distribute, overlap and switch the laser beams. This includes the overlap and joint fiber coupling of beams at 767nm and 780nm in the same polarization state to cool and manipulate atoms of both species simultaneously. Future projects include the development of a platform for experiments with cold atoms onboard the International Space Station. The laser system again involves ZERODUR based optical benches in conjunction with fiber optical components. The experiment is planned as multi-user facility and currently in the design phase. The next step is to build the training, test and flight hardware.

physics.atom-ph↗