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Pushing Quantum Chemistry Beyond Classical Limitations Using 

Distributed Quantum Computing

Grier M. Jones

            The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ontario, Canada M5S 3G4

Department of Chemical and Physical Sciences, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, Ontario, Canada L5L 1C6

 

In recent years, technological advances in quantum hardware and algorithms have sparked growing interest in quantum computing. Despite the promises of quantum advantage, the applicability of quantum devices has been limited to a few qubits on hardware that experiences decoherence due to noise. One proposed method to get around this challenge is distributed quantum computing (DQC). Like classical distributed computing, DQC aims to increase computational power by spreading the computational processes across many devices, to minimize the noise and circuit depth per quantum device. Additionally, quantum-centric supercomputing, which utilizes classical distributed hardware in combination with quantum processing units (QPUs), has proven to be a successful and practical method for solving the molecular electronic structure problem using the local unitary cluster Jastrow (LUCJ) ansatz. The key limitations in implementing this algorithm arise from the limited number of available qubits per quantum device, which restricts the size of the complete active space (CAS). To bypass this limitation, the LUCJ ansatz can be partitioned across multiple QPUs, within a quantum-centric supercomputing framework, enabling the exploration of the electronic structure of larger chemical systems. We are currently exploring approaches that employ circuit knitting techniques, including local operations and mid-circuit local operations with classical communication. Additionally, we are developing methods to bound the exact solution from above and below using established electronic structure methods, providing mathematical guarantees for our results.

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