TL;DR
This paper provides a comprehensive characterization of quantum space-bounded computation, establishing complete problems and equivalences with classical complexity classes, and exploring implications for quantum algorithms and state preparation.
Contribution
It introduces two complete problems for quantum space-bounded classes, improves space-efficient quantum algorithms, and shows PreciseQMA equals PSPACE, advancing understanding of quantum computational complexity.
Findings
Approximate matrix inverse is complete for quantum space class.
Estimating minimum eigenvalue is complete for the same class.
PreciseQMA equals PSPACE, with eigenvalue estimation being PSPACE-complete.
Abstract
Motivated by understanding the power of quantum computation with restricted number of qubits, we give two complete characterizations of unitary quantum space bounded computation. First we show that approximating an element of the inverse of a well-conditioned efficiently encoded matrix is complete for the class of problems solvable by quantum circuits acting on qubits with all measurements at the end of the computation. Similarly, estimating the minimum eigenvalue of an efficiently encoded Hermitian matrix is also complete for this class. In the logspace case, our results improve on previous results of Ta-Shma [STOC '13] by giving new space-efficient quantum algorithms that avoid intermediate measurements, as well as showing matching hardness results. Additionally, as a consequence we show that PreciseQMA, the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
A complete characterization of unitary quantum space· youtube
