معرفی
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.
