Efficient Classical Simulation of Many-body Systems with Local Integrals of Motion
summary
Claim: a complete set of strictly local integrals of motion lets one build a spectral matrix product operator that encodes every eigenstate as choices of extra indices; in 1D the projector MPO is exact and local expectation values cost only O(N) to evaluate, and time evolution from any MPS-representable initial state is accessible via perfect sampling of eigenstate weights so arbitrarily large times are reachable; in higher D the spectral PEPS exists but contraction becomes nonprovable; if one also has local conjugate variables then all tasks become efficiently solvable in any dimension.
AI-written summary · about
chapters (8)
- 0:00Introduction
- 0:45Motivation
- 4:48Localization
- 22:07Efficient Classical Simulation
- 24:17Spectral Tensor Network
- 30:57Maximum Entropy
- 38:27Locality
- 43:37Representation
related talks
55mFinding Eigenvalues in Exponential Size Space:...
58mUniversality of Approximate Message Passing on Semi-random Matrices
49mApproximate Message Passing Algorithms For Orthogonally Invariant Models
01h 11mOptimization and Sampling Under Symmetry: Part 1 -- Examples
01h 10mAn Introduction to Hamiltonian Monte Carlo Method for Sampling
31mThe Convergence of Hamiltonian Monte Carlo
59mEquivariant Machine Learning Structured Like Classical Physics
36mTo Be (Hard) or Not Be:...
