TY - JOUR A1 - Franz, Maja A1 - Wolf, Lucas A1 - Periyasamy, Maniraman A1 - Ufrecht, Christian A1 - Scherer, Daniel D. A1 - Plinge, Axel A1 - Mutschler, Christopher A1 - Mauerer, Wolfgang T1 - Uncovering Instabilities in Variational-Quantum Deep Q-Networks JF - Journal of the Franklin Institute N2 - Deep Reinforcement Learning (RL) has considerably advanced over the past decade. At the same time, state-of-the-art RL algorithms require a large computational budget in terms of training time to converge. Recent work has started to approach this problem through the lens of quantum computing, which promises theoretical speed-ups for several traditionally hard tasks. In this work, we examine a class of hybrid quantumclassical RL algorithms that we collectively refer to as variational quantum deep Q-networks (VQ-DQN). We show that VQ-DQN approaches are subject to instabilities that cause the learned policy to diverge, study the extent to which this afflicts reproduciblity of established results based on classical simulation, and perform systematic experiments to identify potential explanations for the observed instabilities. Additionally, and in contrast to most existing work on quantum reinforcement learning, we execute RL algorithms on an actual quantum processing unit (an IBM Quantum Device) and investigate differences in behaviour between simulated and physical quantum systems that suffer from implementation deficiencies. Our experiments show that, contrary to opposite claims in the literature, it cannot be conclusively decided if known quantum approaches, even if simulated without physical imperfections, can provide an advantage as compared to classical approaches. Finally, we provide a robust, universal and well-tested implementation of VQ-DQN as a reproducible testbed for future experiments. KW - Artificial Intelligence KW - Computer Science KW - Quantum Physics Y1 - 2022 U6 - https://doi.org/10.1016/j.jfranklin.2022.08.021 SN - 0016-0032 N1 - Corresponding author: Maja Franz PB - Elsevier ET - In Press, Corrected Proof ER - TY - CHAP A1 - Schönberger, Manuel A1 - Franz, Maja A1 - Scherzinger, Stefanie A1 - Mauerer, Wolfgang T1 - Peel | Pile? Cross-Framework Portability of Quantum Software T2 - 2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C), 12-15 March 2022, Honolulu, HI, USA N2 - In recent years, various vendors have made quantum software frameworks available. Yet with vendor-specific frameworks, code portability seems at risk, especially in a field where hardware and software libraries have not yet reached a consolidated state, and even foundational aspects of the technologies are still in flux. Accordingly, the development of vendor-independent quantum programming languages and frameworks is often suggested. This follows the established architectural pattern of introducing additional levels of abstraction into software stacks, thereby piling on layers of abstraction. Yet software architecture also provides seemingly less abstract alternatives, namely to focus on hardware-specific formulations of problems that peel off unnecessary layers. In this article, we quantitatively and experimentally explore these strategic alternatives, and compare popular quantum frameworks from the software implementation perspective. We find that for several specific, yet generalisable problems, the mathematical formulation of the problem to be solved is not just sufficiently abstract and serves as precise description, but is likewise concrete enough to allow for deriving framework-specific implementations with little effort. Additionally, we argue, based on analysing dozens of existing quantum codes, that porting between frameworks is actually low-effort, since the quantum- and framework-specific portions are very manageable in terms of size, commonly in the order of mere hundreds of lines of code. Given the current state-of-the-art in quantum programming practice, this leads us to argue in favour of peeling off unnecessary abstraction levels. KW - Computer Science KW - Quantum Physics KW - Software Engineering Y1 - 2022 U6 - https://doi.org/10.1109/ICSA-C54293.2022.00039 N1 - Preprint unter: https://arxiv.org/abs/2203.06289 PB - IEEE ER - TY - CHAP A1 - Mauerer, Wolfgang A1 - Scherzinger, Stefanie T1 - 1-2-3 Reproducibility for Quantum Software Experiments T2 - 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Honolulu, HI, USA, 15-18 March 2022 N2 - Various fields of science face a reproducibility crisis. For quantum software engineering as an emerging field, it is therefore imminent to focus on proper reproducibility engineering from the start. Yet the provision of reproduction packages is almost universally lacking. Actionable advice on how to build such packages is rare, particularly unfortunate in a field with many contributions from researchers with backgrounds outside computer science. In this article, we argue how to rectify this deficiency by proposing a 1-2-3~approach to reproducibility engineering for quantum software experiments: Using a meta-generation mechanism, we generate DOI-safe, long-term functioning and dependency-free reproduction packages. They are designed to satisfy the requirements of professional and learned societies solely on the basis of project-specific research artefacts (source code, measurement and configuration data), and require little temporal investment by researchers. Our scheme ascertains long-term traceability even when the quantum processor itself is no longer accessible. By drastically lowering the technical bar, we foster the proliferation of reproduction packages in quantum software experiments and ease the inclusion of non-CS researchers entering the field. KW - Computer Science KW - Quantum Physics KW - Software Engineering Y1 - 2022 U6 - https://doi.org/10.1109/SANER53432.2022.00148 SP - 1247 EP - 1248 PB - IEEE ER -