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arXiv:quant-ph/0511013

Bounded-Error Quantum State Identification and Exponential Separations in Communication Complexity

Gavinsky, Dmytro, Julia Kempe, Oded Regev, Ronald de Wolf

Published Nov 2, 2005• 1 citation
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Abstract

We consider the problem of bounded-error quantum state identification: given either state α_0 or state α_1, we are required to output `0', `1' or `?' ("don't know"), such that conditioned on outputting `0' or `1', our guess is correct with high probability. The goal is to maximize the probability of not outputting `?'. We prove a direct product theorem: if we're given two such problems, with optimal probabilities a and b, respectively, and the states in the first problem are pure, then the optimal probability for the joint bounded-error state identification problem is O(ab). Our proof is based on semidefinite programming duality and may be of wider interest. Using this result, we present two exponential separations in the simultaneous message passing model of communication complexity. Both are shown in the strongest possible sense. First, we describe a relation that can be computed with O(log n) classical bits of communication in the presence of shared randomness, but needs Omega(n^{1/3}) communication if the parties don't share randomness, even if communication is quantum. This shows the optimality of Yao's recent exponential simulation of shared-randomness protocols by quantum protocols without shared randomness. Second, we describe a relation that can be computed with O(log n) classical bits of communication in the presence of shared entanglement, but needs Omega((n/log n)^{1/3}) communication if the parties share randomness but no entanglement, even if communication is quantum. This is the first example in communication complexity of a situation where entanglement buys you much more than quantum communication does.

DOI
10.48550/arxiv.quant-ph/0511013

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We consider the following problem of bounded-error quantum state identification: Given either state α0\alpha_0α0​ or state α1\alpha_1α1​, we are required to output “0”, “1”, or “?” (“don't know"), such that conditioned on outputting “0” or “1”, our guess is correct with high probability. The goal is to maximize the probability of not outputting “?”. We prove the following direct product theorem: If we are given two such problems, with optimal probabilities a and b, respectively, and the states in the first problem are pure, then the optimal probability for the joint bounded-error state identification problem is O(ab)O(ab)O(ab). Our proof is based on semidefinite programming duality. Using this result, we present two exponential separations in the simultaneous message passing model of communication complexity. First, we describe a relation that can be computed with O(log⁡n)O(\log n)O(logn) classical bits of communication in the presence of shared randomness, but needs Ω(n1/3)\Omega(n^{1/3})Ω(n1/3) communication if the parties don't share randomness, even if communication is quantum. This shows the optimality of Yao's recent exponential simulation of shared-randomness protocols by quantum protocols without shared randomness. Combined with an earlier separation in the other direction due to Bar-Yossef, Jayram, and Kerenidis, this shows that the quantum simultaneous message passing (SMP) model is incomparable with the classical shared-randomness SMP model. Second, we describe a relation that can be computed with O(log⁡n)O(\log n)O(logn) classical bits of communication in the presence of shared entanglement, but needs Ω((n/log⁡n)1/3)\Omega((n/\log n)^{1/3})Ω((n/logn)1/3) communication if the parties share randomness but no entanglement, even if communication is quantum. This is the first example in communication complexity of a situation where entanglement buys much more than quantum communication.
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Abstract. We give the first exponential separation between quantum and bounded-error randomized one-way communication complexity. Specifically, we define the Hidden Matching Problem HMn: Alice gets as input a string x ∈ {0,1} n, and Bob gets a perfect matching M on the n coordinates. Bob’s goal is to output a tuple 〈i, j, b 〉 such that the edge (i,j) belongs to the matching M and b = xi ⊕ xj. We prove that the quantum one-way communication complexity of HMn is O(logn), yet any randomized one-way protocol with bounded error must use Ω ( √ n) bits of communication. No asymptotic gap for one-way communication was previously known. Our bounds also hold in the model of Simultaneous Messages (SM), and hence we provide the first exponential separation between quantum SM and randomized SM with public coins. For a Boolean decision version of HMn, we show that the quantum one-way communication complexity remains O(logn) and that the 0-error randomized one-way communication complexity is Ω(n). We prove that any randomized linear one-way protocol with bounded error for this problem requires Ω ( 3 √ nlog n) bits of communication.
Computing many instances jointly can reduce communication per instance. We ask whether such savings occur in the simultaneous-message-passing (SMP) model and how they depend on quantum messages and shared resources. For every finite total function fff and fixed error 0≤ε<10\le\varepsilon<10≤ε<1, we prove that the optimal worst-case communication per instance for fnf^nfn converges to D∥(f)=log⁡∣Row(f)∣+log⁡∣Col(f)∣, D^\parallel(f)=\log|\mathrm{Row}(f)|+\log|\mathrm{Col}(f)|, D∥(f)=log∣Row(f)∣+log∣Col(f)∣, where Row(f)\mathrm{Row}(f)Row(f) and Col(f)\mathrm{Col}(f)Col(f) are the sets of distinct rows and columns of the table (f(x,y))x,y(f(x,y))_{x,y}(f(x,y))x,y​. This holds for classical and quantum SMP without shared entanglement, with or without shared randomness. Thus, transmitting row and column indices is asymptotically optimal, even with bounded error, joint computation, and quantum messages. In particular, the exponential advantage of quantum fingerprinting for a single instance of equality without shared randomness disappears in the asymptotic rate. We also prove that the same threshold governs an exponential strong converse: every fixed worst-case communication rate below it forces the probability of computing all nnn outputs correctly to decay as 2−Ω(n)2^{-Ω(n)}2−Ω(n), even on average under a fixed product input distribution. With shared randomness, the optimal expected communication rate is (1−ε)D∥(f)(1-\varepsilon)D^\parallel(f)(1−ε)D∥(f). Entanglement shared between each sender and the referee halves both rates; arbitrary tripartite entanglement gives no further reduction. The results extend to a class of total relations and yield one-way characterizations with D∥(f)D^\parallel(f)D∥(f) replaced by log⁡∣Row(f)∣\log|\mathrm{Row}(f)|log∣Row(f)∣. Our proof reduces SMP to one-way communication and relates successful computation to sampling based on quantum min-entropy; we also give a simpler proof of the key lemma using the pretty-good measurement.
We study the simultaneous message passing (SMP) model of communication complexity, for the case where one party is quantum and the other is classical. We show that in an SMP protocol that computes some function with the first party sending q qubits and the second sending c classical bits, the quantum message can be replaced by a randomized message of O(qc) classical bits, as well as by a deterministic message of O(q c log q) classical bits. Our proofs rely heavily on earlier results due to Scott Aaronson. In particular, our results imply that quantum-classical protocols need to send Omega(sqrt{n/log n}) bits/qubits to compute Equality on n-bit strings, and hence are not significantly better than classical-classical protocols (and are much worse than quantum-quantum protocols such as quantum fingerprinting). This essentially answers a recent question of Wim van Dam. Our results also imply, more generally, that there are no superpolynomial separations between quantum-classical and classical-classical SMP protocols for functional problems. This contrasts with the situation for relational problems, where exponential gaps between quantum-classical and classical-classical SMP protocols are known. We show that this surprising situation cannot arise in purely classical models: there, an exponential separation for a relational problem can be converted into an exponential separation for a functional problem.