TY - GEN
T1 - Strengths and weaknesses of quantum fingerprinting
AU - Gavinsky, Dmitry
AU - Kempe, Julia
AU - De Wolf, Ronald
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2006
Y1 - 2006
N2 - We study the power of quantum fingerprints in the simultaneous message passing (SMP) setting of communication complexity. Yao recently showed how to simulate, with exponential overhead, classical shared-randomness SMP protocols by means of quantum SMP protocols without shared randomness (Q∥ -protocols). Our first result is to extend Yao's simulation to the strongest possible model: every many-round quantum protocol with unlimited shared entanglement can be simulated, with exponential overhead, by Q| -protocols. We apply our technique to obtain an efficient Q∥ -protocol for a function which cannot be efficiently solved through more restricted simulations. Second, we tightly characterize the power of the quantum fingerprinting technique by making a connection to arrangements of homogeneous halfspaces with maximal margin. These arrangements have been well studied in computational learning theory, and we use some strong results obtained in this area to exhibit weaknesses of quantum fingerprinting. In particular, this implies that for almost all functions, quantum fingerprinting protocols are exponentially worse than classical deterministic SMP protocols.
AB - We study the power of quantum fingerprints in the simultaneous message passing (SMP) setting of communication complexity. Yao recently showed how to simulate, with exponential overhead, classical shared-randomness SMP protocols by means of quantum SMP protocols without shared randomness (Q∥ -protocols). Our first result is to extend Yao's simulation to the strongest possible model: every many-round quantum protocol with unlimited shared entanglement can be simulated, with exponential overhead, by Q| -protocols. We apply our technique to obtain an efficient Q∥ -protocol for a function which cannot be efficiently solved through more restricted simulations. Second, we tightly characterize the power of the quantum fingerprinting technique by making a connection to arrangements of homogeneous halfspaces with maximal margin. These arrangements have been well studied in computational learning theory, and we use some strong results obtained in this area to exhibit weaknesses of quantum fingerprinting. In particular, this implies that for almost all functions, quantum fingerprinting protocols are exponentially worse than classical deterministic SMP protocols.
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U2 - 10.1109/CCC.2006.39
DO - 10.1109/CCC.2006.39
M3 - Conference contribution
AN - SCOPUS:34247496907
SN - 0769525962
SN - 9780769525969
T3 - Proceedings of the Annual IEEE Conference on Computational Complexity
SP - 288
EP - 295
BT - Proceedings - Twenty-First Annual IEEE Conference on Computational Complexity, CCC 2006
T2 - 21st Annual IEEE Conference on Computational Complexity, CCC 2006
Y2 - 16 July 2006 through 20 July 2006
ER -