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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 S.

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 S.

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 S.

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! S.

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 S.

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 S.

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 S.

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! S.

Wang, Q.; Wanjura, C. C.; Marquardt, F.: Training Coupled Phase Oscillators as a Neuromorphic Platform using Equilibrium Propagation. arXiv, 2402.08579 (2024), 12 pages, 4 figures, comments welcome S.

Musavinezhad, M.; Renger, J.; Zirkelbach, J.; Utikal, T.; Hail, C. U.; Basché, T.; Poulikakos, D.; Götzinger, S.; Sandoghdar, V.: High-resolution Cryogenic Spectroscopy of Single Molecules in Nanoprinted Crystals. https://arxiv.org/abs/2402.07474 (2024)

Puviani, M.: Theory of symmetry-resolved quench-drive spectroscopy: Nonlinear response of phase-fluctuating superconductors. arXiv, 2402.02120 (2024), 14 pages, 9 figures S.

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)

Kashkanova, A.; Albrecht, D.; Kueppers, M.; Blessing, M.; Sandoghdar, V.: Measuring concentration of nanoparticles in polydisperse mixtures using interferometric nanoparticle tracking analysis (iNTA). www.biorxiv.org/content/10.1101/2024.01.09.574819v1 (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 S.