Jannes Nys

Dr. Jannes Nys is a researcher at the Professorship for Computational Physics at ETH Zürich. His work bridges computational physics and machine learning, focusing on quantum systems and many-body problems.

Email: jannys@phys.ethz.ch

Research Interests: His research spans computational physics, quantum many-body systems, and machine learning applications in physics. He develops neural network-based quantum states and symmetry-aware algorithms for simulating complex quantum phenomena.

• Quantum Many-Body Systems
• Neural Quantum States
• Ab-initio Simulations
• Quantum Chemistry
• Topological Entanglement
• High Energy Physics

Recent Article Trends: His publications highlight the intersection of machine learning and quantum physics, including neural wavefunction optimization for non-Hermitian systems, symmetry-aware models for electron spectroscopy, and variational methods for real-time quantum dynamics. He also explores exotic hadrons in particle physics and novel quantum Monte Carlo approaches.