Learn How Quantum Computing Could Revolutionize Chemistry
Problem Decomposition
The Chemistry Involved
The complex electronic structure of each atom in a quantum system must be taken into account when solving quantum chemistry problems, which quickly becomes intractable with increasing molecular size. Therefore, the efficient simulation of large molecules on quantum devices based on PD techniques used in quantum chemistry has been a long-needed strategy for performing electronic structure calculations. Electronic structure theory in quantum chemistry involves calculating quantum states of electrons, and the forces that exist between the electrons and the nucleus of each atom that make up a given molecule. The forces determine the energies, geometries, and the transitioning states between stable molecular structures. Performing electronic structure and nuclear dynamics calculations is a necessary step in studying the quantum motion of a system.A Novel 1QBit–Dow Framework: The Frozen Natural Orbital Based Method of Increments
A popular type of PD-based approach used in quantum chemistry is the method of increments (MI). The method of increments is based on the many-body expansion of the electron correlation energy in terms of occupied molecular orbitals. The MI approach is used to systematically reduce the occupied orbital space of the molecular system, allowing for easier simulation of the system. A new framework has recently been proposed by 1QBit in collaboration with Dow that uses the frozen natural orbitals (FNO) algorithm to build on the MI approach.4 And, as with the MI approach, FNOs are also obtained using many-body perturbation theory. The FNO algorithm reduces the computing resources needed to perform chemistry simulations by truncating the virtual orbital space of a system. In this way, a new MI-FNO approach is constructed for the systematic reduction of both the occupied space and the virtual space in quantum chemistry simulations, allowing for the scaling up of electronic structure calculations. The MI-FNO framework is independent and transferable, not tied to any particular method of obtaining electron correlation energy. For instance, correlation energy can be computed using any conventional quantum chemistry approach, such as coupled-cluster or full configuration interaction. Alternatively, quantum algorithms such as the variational quantum eigensolver or phase estimation could also be used. For a more detailed discussion on these different conventional and quantum methods, please see the 1QBit paper, “Scaling Up Electronic Structure Calculations on Quantum Computers: The Frozen Natural Orbital Based Method of Increments”.4How Effective is the New Approach?
References
1 A. J. McCaskey, Z. P. Parks, J. Jakowski, et al., “Quantum chemistry as a benchmark for near-term quantum computers”, npj Quantum Inf 5, 99 (2019).
2 J. Olson, Y. Cao, J. Romero, P. Johnson, P-L. Dallaire-Demers, N.Sawaya, P. Narang, I. Kivlichan, M. Wasielewski, and A. Aspuru-Guzik, “Quantum Information and Computation for Chemistry”, arXiv:1706.05413 (2016).
3 T. Yamazaki, S. Matsuura, A. Narimani, A. Saidmuradov, and A. Zaribafiyan, “Towards the Practical Application of Near-Term Quantum Computers in Quantum Chemistry Simulations: A Problem Decomposition Approach”, arXiv:1806.01305 (2018).
4 P. Verma, L. Huntington, M. Coons, Y. Kawashima, T. Yamazaki, and A. Zaribafiyan, “Scaling Up Electronic Structure Calculations on Quantum Computers: The Frozen Natural Orbital Based Method of Increments”, arXiv:2002.07901 (2020).
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