Dresden 2026 – scientific programme

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QI: Fachverband Quanteninformation

QI 4: Quantum Manybody Systems (joint session QI/TT)

QI 4.1: Invited Talk

Monday, March 9, 2026, 15:00–15:30, BEY/0245

Reducing Noise, Complexity, and Optimization Barriers in Quantum Simulations of Strongly Correlated Systems — •Werner Dobrautz — Center for Advanced Systems Understanding (CASUS), Görlitz, Germany — Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany — Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, Dresden, Germany — Technical University Dresden, Dresden, Germany

Near-term quantum hardware poses severe constraints for quantum chemistry and quantum many-body simulations due to noise, limited coherence, and challenging optimization landscapes. We present a unifying set of algorithmic strategies to address these bottlenecks, combining transcorrelated Hamiltonians, spin-adapted representations, and advanced variational optimization techniques. By embedding electronic correlations directly into the Hamiltonian, transcorrelated methods yield compact, noise-resilient quantum circuits and improved convergence for both molecular systems and lattice models. Spin-adapted formulations further reduce Hilbert space complexity and enable efficient simulations of correlated spin systems. To enhance robustness and trainability, we introduce multireference error mitigation strategies and qBang, a momentum-aware variational optimization scheme that effectively navigates flat and ill-conditioned energy landscapes. Together, these approaches establish a scalable and hardware-aware framework for accurate quantum simulations of strongly correlated systems on current and near-term quantum devices.

Keywords: Near-term Quantum algorithms; Strongly correlated electrons; Quantum Chemistry; Error Mitigation