TIMES-ADAPT: A Quantum algorithm for real-time evolution in low-energy subspaces using fixed-depth circuits
Bharath Sambasivam, Kyle Sherbert, Karunya Shirali, Nicholas J. Mayhall, Edwin Barnes, and Sophia E. Economou

TL;DR
TIMES-ADAPT is a variational quantum algorithm that efficiently simulates real-time evolution within low-energy subspaces using fixed-depth circuits, enabling applications like wave packet dynamics and energy transport in spin systems.
Contribution
The paper introduces TIMES-ADAPT, a novel variational quantum algorithm that constructs fixed-depth circuits for real-time evolution in low-energy subspaces, improving simulation efficiency.
Findings
Successfully benchmarks on Heisenberg XXZ model.
Demonstrates effective wave packet evolution simulation.
Shows potential for energy transport studies.
Abstract
We propose a new variational quantum algorithm, which we refer to as TIMES-ADAPT, that prepares time-evolved states in a low-energy or symmetric subspace of a time-independent Hamiltonian on a quantum computer. Using a specially trained unitary that diagonalizes the Hamiltonian in a subspace, we construct fixed-depth circuits for real-time evolution in the subspace, where time only enters as a circuit parameter. We present two versions of the algorithm depending on whether the initial state is specified in the energy eigenbasis or computational basis. We consider two important applications of our methods: wave packet evolution and energy transport in spin systems. We benchmark our algorithms using variants of the Heisenberg XXZ model.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum many-body systems · Quantum-Dot Cellular Automata
