Quantum Computing in Pharma: A Multilayer Embedding Approach for Near Future Applications
Robert Izsak, Christoph Riplinger, Nick S. Blunt, Bernardo de Souza,, Nicole Holzmann, Ophelia Crawford, Joan Camps, Frank Neese, Patrick Schopf

TL;DR
This paper introduces a multilayer embedding approach for quantum computing applications in pharma, focusing on selecting active spaces for simulating chemical systems relevant to drug development, using quantum algorithms like QPE and VQE.
Contribution
It presents an automatic active space selection scheme combined with quantum algorithms, applicable to large systems beyond classical computational limits.
Findings
Successful quantum phase estimation on F$_2$ molecule.
Active space selection based on localized orbitals and perturbation theory.
Application to pharmaceutical molecules like [Fe] hydrogenase and temoporfin.
Abstract
Quantum computers are special purpose machines that are expected to be particularly useful in simulating strongly correlated chemical systems. The quantum computer excels at treating a moderate number of orbitals within an active space in a fully quantum mechanical manner. We present a quantum phase estimation calculation on F in a (2,2) active space on Rigetti's Aspen-11 QPU. While this is a promising start, it also underlines the need for carefully selecting the orbital spaces treated by the quantum computer. In this work, a scheme for selecting such an active space automatically is described and simulated results obtained using both the quantum phase estimation (QPE) and variational quantum eigensolver (VQE) algorithms are presented and combined with a subtractive method to enable accurate description of the environment. The active occupied space is selected from orbitals…
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