Fabian Müller
During my previous studies, I theoretically investigated and optimized quantum optical and measurement systems using tools from quantum information theory. Since 2025, I have been a PhD student in physics at Charles University in Prague, where my theoretical research focuses on fast and reliable quantum state tomography. My work emphasizes developing and implementing improved methods that enable efficient tomography even for high‑dimensional systems.
Session
Quantum computing, communication, and sensing technologies rely on precise knowledge of quantum states. Quantum states cannot be directly measured. Quantum state tomography (QST) reconstructs these states from indirect measurements, similar to how CT imaging combines multiple 2D projections into a 3D model. In QST, the goal is to minimize the statistical discrepancy between experimentally observed data and predictions from quantum theory. This optimization problem is nonlinear and subject to physical constraints on the states. We present a Julia implementation that efficiently and robustly minimizes this statistical distance while enforcing these constraints. Our work provides a practical, extensible toolkit for QST and a comparative guide to choosing optimizer based on accuracy, speed, and robustness.