On Quantum Versions of the Yao Principle
Mart de Graaf, Ronald de Wolf
Abstract
The classical Yao principle states that the complexity Repsilon(f) of an optimal randomized algorithm for a function f with success probability 1-epsilon equals the complexity maxmu Depsilonmu(f) of an optimal deterministic algorithm for f that is correct on a fraction 1-epsilon of the inputs, weighed according to the hardest distribution mu over the inputs. In this paper we investigate to what extent such a principle holds for quantum algorithms. We propose two natural candidate quantum Yao principles, a ``weak'' and a ``strong'' one. For both principles, we prove that the quantum bounded-error complexity is a lower bound on the quantum analogues of max mu Depsilonmu(f). We then prove that equality cannot be obtained for the ``strong'' version, by exhibiting an exponential gap. On the other hand, as a positive result we prove that the ``weak'' version holds up to a constant factor for the query complexity of all symmetric Boolean functions
Create a lesson
Related papers
Gaussian entanglement and quantum communication: geodesic optimization and multimode bounds
Hemant K. Mishra, Mark M. Wilde
On the coincidence of discrete and continuous definitions of Entanglement of Formation
Haobo Ma, Maksim E. Shirokov, Wenlin Zhang
EFI1PRS
Rishabh Batra
Relative-Entropy Geometry and Convergence in Nonconvex Wiretap Optimization
Farzin Salek, Masahito Hayashi
Deterministic and programmable generation of mechanical multipartite entangled states
Isabelle Franzen, Max-Emanuel Kern, Q. Rumman Rahman et al.
Quantum-enhanced mechanical sensing with machine-learning estimation
Finn Müßigbrodt, Andraž Omahen, Q. Rumman Rahman et al.