Lightning Talk: Simulating Quantum Systems with PyTorch - Pierre Guilmin, Alice & Bob
Lightning Talk: Simulating Quantum Systems with PyTorch - Pierre Guilmin, Alice & Bob
In this talk, I propose to explain why simulating quantum systems is a formidable challenge, and how leveraging modern hardware and software can result in notable performance improvement. PyTorch is ideally suited for this task, first because running solvers on GPUs results in a significant speed-up, and second because numerous tasks related to the calibration and control of quantum systems require the computation of gradients based on the time-evolved quantum state. The emerging research effort to develop quantum computers heavily relies on such tools. The dynamiqs library (https://github.com/dynamiqs/dynamiqs) is a Python library powered by PyTorch, designed to address this challenge. It provides differentiable solvers for the Schrödinger Equation which governs closed quantum systems, the Lindblad Master Equation for open quantum systems and the Stochastic Master Equation for continuously measured quantum systems. Gradients can be computed with PyTorch’s automatic differentiation, or using a constant memory cost method. The library is being developed by several PhD students in physics, most of whom have substantial experience in software development.
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