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Matthias Koch

Publications and source records attributed to Matthias Koch.

10 recordsLinked to original sources
arXiv2026

From Obligation to Specification: A Survey on Validating EU AI Act Requirements in RE

With the EU AI Act entering into force, organizations developing or operating AI systems face new obligations on transparency, risk management, and traceability. For Requirements Engineering (RE), these obligations must be translated into testable, auditable requirements and verifiable evidence. However, many organizations currently lack systematic processes to achieve this. We hypothesize that LLM-based agentic validation tools can support this translation, thereby helping to close this gap. We present a mixed-method exploratory study with expert interviews (N=10) and an online survey (N=15) to assess organizational preparedness for EU AI Act-oriented RE and perceptions of LLM-based, agentic closed-loop validation tools, with participants spanning RE, data science, development, and compliance roles. Our results show that, although the EU AI Act is viewed as highly relevant, structured mechanisms to capture regulatory obligations, propagate updates into projects, and maintain lifecycle-wide traceability and evidence are often missing. Participants see LLM-based tools as promising for mapping obligations to requirements, assessing coverage, and organizing evidence, but express strong concerns about full automation and stress the need for safeguards. Based on these findings, we outline minimum requirements for an EU AI Act-ready closed-loop approach.

cs.SE↗
arXiv2025

From Requirements to Code: Understanding Developer Practices in LLM-Assisted Software Engineering

With the advent of generative LLMs and their advanced code generation capabilities, some people already envision the end of traditional software engineering, as LLMs may be able to produce high-quality code based solely on the requirements a domain expert feeds into the system. The feasibility of this vision can be assessed by understanding how developers currently incorporate requirements when using LLMs for code generation-a topic that remains largely unexplored. We interviewed 18 practitioners from 14 companies to understand how they (re)use information from requirements and other design artifacts to feed LLMs when generating code. Based on our findings, we propose a theory that explains the processes developers employ and the artifacts they rely on. Our theory suggests that requirements, as typically documented, are too abstract for direct input into LLMs. Instead, they must first be manually decomposed into programming tasks, which are then enriched with design decisions and architectural constraints before being used in prompts. Our study highlights that fundamental RE work is still necessary when LLMs are used to generate code. Our theory is important for contextualizing scientific approaches to automating requirements-centric SE tasks.

cs.SE↗
arXiv2025

Large, ultra-flat optical traps for uniform quantum gases

Ultracold atomic gases with uniform density can be created by flat-bottom optical traps. These gases provide an ideal platform to study many-body physics in a system that allows for simple connections with theoretical models and emulation of numerous effects from a wide range of fields of physics. In Earth-bound laboratories the trap sizes, number of species and states, as well as the range of physical effects are largely restricted by the adopted levitation technique. Homogeneous ultracold gases in microgravity simulators and space however offer an interesting perspective which is actively being pursued. To exploit the full potential of any gravity-compensated laboratory the box potentials created need to be as large as possible. By using two orthogonally aligned acousto-optic deflectors, we create large time-averaged optical potentials with trapping volumes a thousandfold larger than conventional setups, described by power-law scalings with exponents of up to $152$. We verify the performance of our setup by simulating the mean-field behaviour of a quantum gas ground state in conjunction with dynamical excitations due to the realistic time-dependent painting potentials. The implementation of this setup may open new directions at the interface with condensed matter, few-body Efimov physics or the exploration of critical, non-equilibrium phenomena.

cond-mat.quant-gas↗
arXiv2025

A5/1 is in the Air: Passive Detection of 2G (GSM) Ciphering Algorithms

This paper investigates the ongoing use of the A5/1 ciphering algorithm within 2G GSM networks. Despite its known vulnerabilities and the gradual phasing out of GSM technology by some operators, GSM security remains relevant due to potential downgrade attacks from 4G/5G networks and its use in IoT applications. We present a comprehensive overview of a historical weakness associated with the A5 family of cryptographic algorithms. Building on this, our main contribution is the design of a measurement approach using low-cost, off-the-shelf hardware to passively monitor Cipher Mode Command messages transmitted by base transceiver stations (BTS). We collected over 500,000 samples at 10 different locations, focusing on the three largest mobile network operators in Germany. Our findings reveal significant variations in algorithm usage among these providers. One operator favors A5/3, while another surprisingly retains a high reliance on the compromised A5/1. The third provider shows a marked preference for A5/3 and A5/4, indicating a shift towards more secure ciphering algorithms in GSM networks.

cs.NI↗
arXiv2025

Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints

While classical convolutional neural networks (CNNs) have revolutionized image classification, the emergence of quantum computing presents new opportunities for enhancing neural network architectures. Quantum CNNs (QCNNs) leverage quantum mechanical properties and hold potential to outperform classical approaches. However, their implementation on current noisy intermediate-scale quantum (NISQ) devices remains challenging due to hardware limitations. In our research, we address this challenge by introducing an encoding scheme that significantly reduces the input dimensionality. We demonstrate that a primitive QCNN architecture with 49 qubits is sufficient to directly process $28\times 28$ pixel MNIST images, eliminating the need for classical dimensionality reduction pre-processing. Additionally, we propose an automated framework based on expressibility, entanglement, and complexity characteristics to identify the building blocks of QCNNs, parameterized quantum circuits (PQCs). Our approach demonstrates advantages in accuracy and convergence speed with a similar parameter count compared to both hybrid QCNNs and classical CNNs. We validated our experiments on IBM's Heron r2 quantum processor, achieving $96.08\%$ classification accuracy, surpassing the $71.74\%$ benchmark of traditional approaches under identical training conditions. These results represent one of the first implementations of image classifications on real quantum hardware and validate the potential of quantum computing in this area.

quant-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↗
arXiv2021

Optimising Rolling Stock Planning including Maintenance with Constraint Programming and Quantum Annealing

We propose and compare Constraint Programming (CP) and Quantum Annealing (QA) approaches for rolling stock assignment optimisation considering necessary maintenance tasks. In the CP approach, we model the problem with an Alldifferent constraint, extensions of the Element constraint, and logical implications, among others. For the QA approach, we develop a quadratic unconstrained binary optimisation (QUBO) model. For evaluation, we use data sets based on real data from Deutsche Bahn and run the QA approach on real quantum computers from D-Wave. Classical computers are used to evaluate the CP approach as well as tabu search for the QUBO model. At the current development stage of the physical quantum annealers, we find that both approaches tend to produce comparable results.

cs.AI↗
arXiv2006

Enumeration of generalized polyominoes

As a generalization of polyominoes we consider edge-to-edge connected nonoverlapping unions of regular $k$-gons. For $n\le 4$ we determine formulas for the number $a_k(n)$ of generalized polyominoes consisting of $n$ regular $k$-gons. Additionally we give a table of the numbers $a_k(n)$ for small $k$ and $n$ obtained by computer enumeration. We finish with some open problems for $k$-polyominoes.

math.CO↗