Self-consistent Quantum Iteratively Sparsified Hamiltonian method (SQuISH): A new algorithm for efficient Hamiltonian simulation and compression
Diana B. Chamaki, Stuart Hadfield, Katherine Klymko, Bryan O'Gorman,, Norm M. Tubman

TL;DR
SQuISH is a novel quantum algorithm that iteratively creates a resource-efficient, truncated Hamiltonian using both the Hamiltonian and an approximate ground state, significantly reducing quantum resource requirements.
Contribution
The paper introduces SQuISH, a new iterative method combining Hamiltonian and wavefunction information to efficiently simulate quantum systems with reduced resource needs.
Findings
Successfully applied to small molecules and larger systems
Reduces gate complexity for ground state calculations
Handles systems requiring over 200 qubits on quantum hardware
Abstract
It is crucial to reduce the resources required to run quantum algorithms and simulate physical systems on quantum computers due to coherence time limitations. With regards to Hamiltonian simulation, a significant effort has focused on building efficient algorithms using various factorizations and truncations, typically derived from the Hamiltonian alone. We introduce a new paradigm for improving Hamiltonian simulation and reducing the cost of ground state problems based on ideas recently developed for classical chemistry simulations. The key idea is that one can find efficient ways to reduce resources needed by quantum algorithms by making use of two key pieces of information: the Hamiltonian operator and an approximate ground state wavefunction. We refer to our algorithm as the (SQuISH). By performing our scheme…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Cloud Computing and Resource Management · Quantum Information and Cryptography
