Abstract:
This talk offers a practical introduction to tensor networks, bridging the gap between theory and implementation. We'll begin with the basic concepts of Matrix Product States (MPS), including canonical forms and orthogonalization. We'll then explore an implementation of the Time-Evolving Block Decimation (TEBD) algorithm for modeling quantum dynamics. Finally, we'll explore how MPS can be used as a generative model using autoregressive sampling. Participants will gain the foundational skills to apply these powerful methods to their work in machine learning and computational physics.
Language: English
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