Bilous, P.; Thirion, L.; Menke, H.; Haverkort, M. W.; Pálffy, A.; Hansmann, P.: Neural-network-supported basis optimizer for the configuration interaction problem in quantum many-body clusters: Feasibility study and numerical proof. arXiv, 2406.00151 (2024), 11 pages, 11 figures pp.

Gu, X.; Krenn, M.: Generation and human-expert evaluation of interesting research ideas using knowledge graphs and large language models. arXiv, 2405.17044 (2024), 10 pages; 5 figures pp.

Schmidt, P.; Marquardt, F.; Mohseni, N.: Transfer learning in predicting quantum many-body dynamics: from physical observables to entanglement entropy. arXiv, 2405.16254 (2024)

Nägele, M.; Olle, J.; Fösel, T.; Zen, R.; Marquardt, F.: Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning. arXiv, 2405.13609 (2024)

Landgraf, J.; Peano, V.; Marquardt, F.: Automated Discovery of Coupled Mode Setups. arXiv, 2404.14887 (2024), 18 pages, 4 figures, 2 figures in the appendix pp.

Wanjura, C. C.; Mayländer, A.; Marti, O.; Blumenfeld, R.: Detailed balance in non-equilibrium dynamics of granular matter: derivation and implications. arXiv, 2404.05059 (2024), 5 pages, 2 figures; Supplementary Material: 3 pages, 3 figures. Comments welcome! pp.

Felski, A.; Beygi, A.; Karapoulitidis, C.; Klevansky, S. P.: Three perspectives on entropy dynamics in a non-Hermitian two-state system. arXiv, 2404.03492 (2024), 12 pages, 6 figures pp.

Wu, Z.; Zen, R. A. M.; Casagrande, H. P.; Bressan, S.; Poletti, D.: Supervised Training of Neural-Network Quantum States for the Next Nearest Neighbor Ising model. arXiv, 2305.03394 (2024)

Gohsrich, J. T.; Fauman, J.; Kunst, F. K.: Exceptional points of any order in a generalized Hatano-Nelson model. arXiv, 2403.12018 (2024)

Montag, A.; Kunst, F. K.: Essential implications of similarities in non-Hermitian systems. arXiv, 2402.18249 (2024)

Zen, R.; Olle, J.; Colmenarez, L.; Puviani, M.; Müller, M.; Marquardt, F.: Quantum Circuit Discovery for Fault-Tolerant Logical State Preparation with Reinforcement Learning. arXiv, 2402.17761 (2024), 32 pages, 18 figures pp.

Schmidt, P.; Arlt, S.; Ruiz-Gonzalez, C.; Gu, X.; Rodríguez, C.; Krenn, M.: Virtual Reality for Understanding Artificial-Intelligence-driven Scientific Discovery with an Application in Quantum Optics. arXiv, 2403.00834 (2024), 12 pages, 6 figures, comments welcome pp.

Gu, X.; Krenn, M.: Forecasting high-impact research topics via machine learning on evolving knowledge graphs. arXiv, 2402.08640 (2024), 8 pages, 6 figures, Comments welcome! pp.

Kasaian, K.; Mazaheri, M.; Sandoghdar, V.: Long-range three-dimensional tracking of nanoparticles using interferometric scattering (iSCAT) microscopy. https://arxiv.org/pdf/2401.12939.pdf (2024)

Belliardo, F.; Zoratti, F.; Marquardt, F.; Giovannetti, V.: Model-aware reinforcement learning for high-performance Bayesian experimental design in quantum metrology. arXiv, 2312.16985 (2023), 42 pages, 9 figures pp.

Puviani, M.; Borah, S.; Zen, R.; Olle, J.; Marquardt, F.: Boosting the Gottesman-Kitaev-Preskill quantum error correction with non-Markovian feedback. arXiv, 2312.07391 (2023), 15 pages, 16 figures pp.

Krenn, M.; Drori, Y.; Adhikari, R. X.: Digital Discovery of interferometric Gravitational Wave Detectors. arXiv, 2312.04258 (2023), 16 pages, 15 figures. Comments welcome! pp.

Nägele, M.; Marquardt, F.: Optimizing ZX-Diagrams with Deep Reinforcement Learning. arXiv, 2311.18588 (2023), 12 pages, 7 figures pp.

Bose, S.; Fuentes, I.; Geraci, A. A.; Khan, S. M.; Qvarfort, S.; Rademacher, M.; Rashid, M.; Toroš, M.; Ulbricht, H.; Wanjura, C. C.: Massive quantum systems as interfaces of quantum mechanics and gravity. arXiv, 2311.09218 (2023), 54 pages, 8 figures. Manuscript prepared for submission to Reviews of Modern Physics. Comments welcome pp.

Olle, J.; Zen, R.; Puviani, M.; Marquardt, F.: Simultaneous Discovery of Quantum Error Correction Codes and Encoders with a Noise-Aware Reinforcement Learning Agent. arXiv, 2311.04750 (2023), 15 pages, 7 figures pp.