Variational Quantum Computation of Excited States
1Riverlane, 3 Charles Babbage Road, Cambridge CB3 0GT
2Department of Physics and Astronomy, University College London, London, WC1E 6BT
3Joint Center for Quantum Information and Computer Science, University of Maryland, College Park, MD 20742
Published: | 2019-07-01, volume 3, page 156 |
Eprint: | arXiv:1805.08138v5 |
Doi: | https://doi.org/10.22331/q-2019-07-01-156 |
Citation: | Quantum 3, 156 (2019). |
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Abstract
The calculation of excited state energies of electronic structure Hamiltonians has many important applications, such as the calculation of optical spectra and reaction rates. While low-depth quantum algorithms, such as the variational quantum eigenvalue solver (VQE), have been used to determine ground state energies, methods for calculating excited states currently involve the implementation of high-depth controlled-unitaries or a large number of additional samples. Here we show how overlap estimation can be used to deflate eigenstates once they are found, enabling the calculation of excited state energies and their degeneracies. We propose an implementation that requires the same number of qubits as VQE and at most twice the circuit depth. Our method is robust to control errors, is compatible with error-mitigation strategies and can be implemented on near-term quantum computers.

Popular summary
The algorithm we have developed - variational quantum deflation - uses a hybrid of both quantum and classical resources to determine the excited state energies of quantum systems. We achieve this at almost no extra cost over the most promising hybrid method for determining ground state energies - the variational quantum eigensolver - by first finding the ground state and then energetically exciting it, allowing the first excited state to be found as the ground state of the new modified system. By repeating this procedure and incorporating techniques to mitigate device errors, our method can determine multiple excited states even on imperfect hardware. Our algorithm is therefore a promising candidate for useful near-term quantum-enhanced computation.
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