Reducing circuit depth in adaptive variational quantum algorithms via effective Hamiltonian theories

• URL: http://arxiv.org/abs/2201.09214v1
• Date: Sun, 23 Jan 2022 09:38:46 GMT
• Title: Reducing circuit depth in adaptive variational quantum algorithms via effective Hamiltonian theories
• Authors: Jie Liu and Zhenyu Li and Jinlong Yang
• Abstract summary: We introduce a new transformation in the form of a product of a linear combination of excitation operators to construct the effective Hamiltonian with finite terms. The effective Hamiltonian defined with this new transformation is incorporated into the adaptive variational quantum algorithms to maintain constant-size quantum circuits.
• Score: 8.24048506727803
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Electronic structure simulation is an anticipated application for quantum computers. Due to high-dimensional quantum entanglement in strongly correlated systems, the quantum resources required to perform such simulations are far beyond the capacity of current quantum devices. To reduce the quantum circuit complexity, it has been suggested to incorporate a part of the electronic correlation into an effective Hamiltonian, which is often obtained from a similarity transformation of the electronic Hamiltonian. In this work, we introduce a new transformation in the form of a product of a linear combination of excitation operators to construct the effective Hamiltonian with finite terms. To demonstrate its accuracy, we also consider an equivalent adaptive variational algorithm with this transformation and show that it can obtain an accurate ground state wave function. The effective Hamiltonian defined with this new transformation is incorporated into the adaptive variational quantum algorithms to maintain constant-size quantum circuits. The new computational scheme is assessed by performing numerical simulations for small molecules. Chemical accuracy is achieved with a much shallower circuit depth.

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