pdf icon
Volume 1 (2005) Article 1 pp. 1-28
Limitations of Quantum Advice and One-Way Communication
Received: June 29, 2004
Published: February 9, 2005
Download article from ToC site:
[PDF (309K)] [PS (489K)] [Source ZIP]
Keywords: Quantum Computation, advice, relativized complexity, direct product theorem, nonuniform, BQP, PP, communication, polynomial method, oracle
ACM Classification: F.1.2,F.1.3
AMS Classification: 81P68, 81P05, 68Q10, 68Q15, 42A05

Abstract: [Plain Text Version]

Although a quantum state requires exponentially many classical bits to describe, the laws of quantum mechanics impose severe restrictions on how that state can be accessed. This paper shows in three settings that quantum messages have only limited advantages over classical ones.

First, we show that $\mathsf{BQP/qpoly}\subseteq\mathsf{PP/poly}$, where $\mathsf{BQP/qpoly}$ is the class of problems solvable in quantum polynomial time, given a polynomial-size “quantum advice state” that depends only on the input length. This resolves a question of Buhrman, and means that we should not hope for an unrelativized separation between quantum and classical advice. Underlying our complexity result is a general new relation between deterministic and quantum one-way communication complexities, which applies to partial as well as total functions.

Second, we construct an oracle relative to which $\mathsf{NP}\not \subset \mathsf{BQP/qpoly}$. To do so, we use the polynomial method to give the first correct proof of a direct product theorem for quantum search. This theorem has other applications; for example, it can be used to fix a result of Klauck about quantum time-space tradeoffs for sorting.

Third, we introduce a new trace distance method for proving lower bounds on quantum one-way communication complexity. Using this method, we obtain optimal quantum lower bounds for two problems of Ambainis, for which no nontrivial lower bounds were previously known even for classical randomized protocols.

A preliminary version of this paper appeared in the 2004 Conference on Computational Complexity (CCC).