Natural Quantum Monte Carlo Computation of Excited States
- URL: http://arxiv.org/abs/2308.16848v2
- Date: Mon, 12 Feb 2024 10:14:32 GMT
- Title: Natural Quantum Monte Carlo Computation of Excited States
- Authors: David Pfau and Simon Axelrod and Halvard Sutterud and Ingrid von Glehn
and James S. Spencer
- Abstract summary: We present a variational Monte Carlo algorithm for estimating the lowest excited states of a quantum system.
We show that it works well in conjunction with recent work on using neural networks as variational Ansatze for many-electron systems.
We expect this technique will be of great interest for applications of variational quantum Monte Carlo to atomic, nuclear and condensed matter physics.
- Score: 5.356944479760105
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We present a variational Monte Carlo algorithm for estimating the lowest
excited states of a quantum system which is a natural generalization of the
estimation of ground states. The method has no free parameters and requires no
explicit orthogonalization of the different states, instead transforming the
problem of finding excited states of a given system into that of finding the
ground state of an expanded system. Expected values of arbitrary observables
can be calculated, including off-diagonal expectations between different states
such as the transition dipole moment. Although the method is entirely general,
it works particularly well in conjunction with recent work on using neural
networks as variational Ansatze for many-electron systems, and we show that by
combining this method with the FermiNet and Psiformer Ansatze we can accurately
recover vertical excitation energies and oscillator strengths on molecules as
large as benzene. Beyond the examples on molecules presented here, we expect
this technique will be of great interest for applications of variational
quantum Monte Carlo to atomic, nuclear and condensed matter physics.
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