Quantum mixed state compiling
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- Univ. of Southern California, Los Angeles, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Lancaster Univ. (United Kingdom)
- Louisiana State Univ., Baton Rouge, LA (United States)
- Louisiana State Univ., Baton Rouge, LA (United States); Cornell Univ., Ithaca, NY (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Quantum Science Center, Oak Ridge, TN (United States)
- Quantum Science Center, Oak Ridge, TN (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ecole Polytechnique Fédérale de Lausanne (EPFL) (Switzerland)
The task of learning a quantum circuit to prepare a given mixed state is a fundamental quantum subroutine. We present a variational quantum algorithm (VQA) to learn mixed states which is suitable for near-term hardware. Our algorithm represents a generalization of previous VQAs that aimed at learning preparation circuits for pure states. We consider two different ansätze for compiling the target state; the first is based on learning a purification of the state and the second on representing it as a convex combination of pure states. In both cases, the resources required to store and manipulate the compiled state grow with the rank of the approximation. Thus, by learning a lower rank approximation of the target state, our algorithm provides a means of compressing a state for more efficient processing. As a byproduct of our algorithm, one effectively learns the principal components of the target state, and hence our algorithm further provides a new method for principal component analysis. We investigate the efficacy of our algorithm through extensive numerical implementations, showing that typical random states and thermal states of many body systems may be learnt this way. Additionally, we demonstrate on quantum hardware how our algorithm can be used to study hardware noise-induced states.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Quantum Science Center (QSC)
- Sponsoring Organization:
- National Science Foundation (NSF); USDOE; USDOE Office of Science (SC)
- Grant/Contract Number:
- 89233218CNA000001; SC0020347
- OSTI ID:
- 1968358
- Report Number(s):
- LA-UR-22-28240
- Journal Information:
- Quantum Science and Technology, Journal Name: Quantum Science and Technology Journal Issue: 3 Vol. 8; ISSN 2058-9565
- Publisher:
- IOP PublishingCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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