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Toward Quantum-Centric Simulations of Extended Molecules: Sample-Based Quantum Diagonalization Enhanced with Density

Akhil Shajan^1,2, Danil Kaliakin¹, Abhishek Mitra¹

¹Center for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, Ohio 44106, United States.

Journal of Chemical Theory and Computation

|July 8, 2025

Summary

Quantum embedding methods, like Density Matrix Embedding Theory (DMET) combined with Sample-based Quantum Diagonalization (SQD), accurately compute molecular ground-state properties. This hybrid approach scales quantum computations for larger molecules on near-term quantum devices.

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Area of Science:

Quantum computing
Computational chemistry
Electronic structure theory

Background:

Computing molecular ground-state properties is crucial for chemistry and materials science.
Quantum embedding methods offer a hybrid approach, combining quantum and classical computing for efficient calculations.
Density Matrix Embedding Theory (DMET) is a powerful quantum embedding method.

Purpose of the Study:

To present the first Density Matrix Embedding Theory (DMET) simulations combined with Sample-based Quantum Diagonalization (SQD).
To compute ground-state properties of molecular systems using the novel DMET-SQD formalism.
To demonstrate the potential of quantum-centric simulations for accurate electronic structure calculations.

Main Methods:

Implementation of the DMET-SQD formalism for quantum embedding.
Application to compute the ground-state energy of an 18-hydrogen atom ring.
Calculation of relative energies for cyclohexane conformers using active-region simulations on quantum hardware (ibm_cleveland).

Main Results:

Successful computation of ground-state energy for a ring of 18 hydrogen atoms.
Accurate determination of relative energies for cyclohexane conformers.
Validation of DMET-SQD results against established classical methods.
Demonstration of decomposing large quantum simulations into smaller, manageable active-region simulations (27- and 32-qubit).

Conclusions:

DMET-SQD represents significant progress in tackling larger active regions on near-term quantum computers.
This work showcases the potential of quantum-centric simulations for accurate electronic structure calculations of large molecules.
The ultimate goal is to apply these methods to complex systems like peptides and proteins.