Tailgating quantum circuits for high-order energy derivatives
Jack Ceroni, Alain Delgado, Soran Jahangiri, Juan Miguel Arrazola

TL;DR
This paper introduces a tailgating technique to enhance variational quantum circuits for calculating high-order energy derivatives, improving accuracy and efficiency in quantum chemistry simulations.
Contribution
The paper proposes an adaptive tailgating method that adds non-optimized gates based on gradient information to improve energy derivative calculations in quantum circuits.
Findings
Supports the validity of the method through theoretical conditions.
Demonstrates advantages via simulations on molecules like beryllium hydride and water.
Achieves accurate second-order energy derivatives efficiently.
Abstract
To understand the chemical properties of molecules, it is often important to study derivatives of energies with respect to nuclear coordinates or external fields. Quantum algorithms for computing energy derivatives have been proposed, but only limited work has been done to address the specific challenges that arise in this context, where calculations are more complicated and involve more stringent requirements on accuracy compared to single-point energy calculations. In this work, we introduce a technique to improve the performance of variational quantum circuits calculating energy derivatives. The method, which we refer to as tailgating, is an adaptive procedure that selects gates based on their gradient with respect to the expectation value of Hamiltonian derivatives. These gates are then added at the end of a quantum circuit originally designed to calculate ground- or excited-state…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum and electron transport phenomena · Spectroscopy and Quantum Chemical Studies
