Abstract
Quantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing. Although universal quantum computers of practical scale may be years away, various approaches are currently being pursued to solve quantum chemistry problems on near-term gate-based quantum computers and quantum annealers by developing the appropriate algorithm and software base. This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer. The approach is based on the matrix formulation, efficiently uses qubit resources based on a power-of-two encoding scheme and is hardware-dominant relying on only one classically optimized parameter. We demonstrate the use of D-Wave hardware for obtaining ground and excited electronic states across a variety of small molecular systems. The approach can be adapted for use by a vast majority of electronic structure methods currently implemented in conventional quantum-chemical packages. The results of this work will encourage further development of software such as qbsolv which has promising applications in emerging quantum information processing hardware and has expectation to address large and complex optimization problems intractable for classical computers.
Highlights
Quantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing
Two overarching statements can be derived from the results reported in the previous section
The first is that the Quantum Annealer Eigensolver (QAE)-based approach to the electronic structure problems is viable
Summary
Quantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing. By manipulating quantum states of matter and taking advantage of their unique features, such as superposition, entanglement and quantum tunneling, quantum computers promise to revolutionize quantum simulations of molecules and solids by bringing down the intractable cost to polynomial scaling[1,2] This can be achieved by using two mathematically equivalent forms of quantum computation[4]: gate-based quantum computing and adiabatic quantum computing, which currently have prototype hardware platforms. The main problem in designing a method to solve the electronic structure on today’s quantum annealers is to find a mapping between the electronic Hamiltonian and classical Ising m odel[21,22], i.e. a model of interacting spins, familiar to many physicists. Finding a mapping of the electronic Hamiltonian to either of these two problem types is a very challenging task
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