On model reduction for quantum dynamics: symmetries and invariant subspaces

Abstract

Simulation of quantum dynamics is a grand challenge of computational physics. In this work we investigate methods for reducing the demands of such simulation by identifying reduced-order models for dynamics generated by parameterized quantum Hamiltonians. In particular, we first formulate an algebraic condition that certifies the existence of invariant subspaces for a model defined by a parameterized Hamiltonian and an initial state. Following this we develop and analyze two methods to explicitly construct a reduced-order model, if one exists. In addition to general results characterizing invariant subspaces of arbitrary finite dimensional Hamiltonians, by exploiting properties of the generalized Pauli group we develop practical tools to speed up simulation of dynamics generated by certain spin Hamiltonians. To illustrate the methods developed we apply them to several paradigmatic spin models.

26 pages, 2 figures, 3 algorithms. Version 2 is published version and contains new results on stability of invariant subspaces to perturbations

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Cited by in corpus (4)

• Systematic Dimensionality Reduction for Quantum Walks: Optimal Spatial Search and Transport on Non-Regular Graphs
• Quantum System Compression: A Hamiltonian Guided Walk Through Hilbert Space
• Exact Model Reduction for Continuous-Time Open Quantum Dynamics
• Model Reduction for Quantum Systems: Discrete-time Quantum Walks and Open Markov Dynamics