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arXiv · 2011.05938

A Feasible Approach for Automatically Differentiable Unitary Coupled-Cluster on Quantum Computers

Jakob S. Kottmann·Abhinav Anand·Alán Aspuru-Guzik
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Abstract

We develop computationally affordable and encoding independent gradient evaluation procedures for unitary coupled-cluster type operators, applicable on quantum computers. We show that, within our framework, the gradient of an expectation value with respect to a parameterized n-fold fermionic excitation can be evaluated by four expectation values of similar form and size, whereas most standard approaches based on the direct application of the parameter-shift-rule come with an associated cost of O(2^(2n)) expectation values. For real wavefunctions, this cost can be further reduced to two expectation values. Our strategies are implemented within the open-source package tequila and allow blackboard style construction of differentiable objective functions. We illustrate initial applications for electronic ground and excited states.

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Jakob S. Kottmann, Abhinav Anand, Alán Aspuru-Guzik. 2020-11-11. A Feasible Approach for Automatically Differentiable Unitary Coupled-Cluster on Quantum Computers. https://doi.org/10.1039/d0sc06627c

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