Difference between revisions of "Open Problems:77"

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Here are two interesting candidate communication classes (both of these classes are subsets of \mathbf{AM}, a well-known frontier class in communication complexity).  
 
Here are two interesting candidate communication classes (both of these classes are subsets of \mathbf{AM}, a well-known frontier class in communication complexity).  
  
a) The communication analog of non-interactive statistical zero knowledge proofs (\mathbf{NISZK}). This model can be defined as follows. For a given function f(x, y) \to \{0, 1\}, Alice and Bob engage in a (private coin) randomized communication protocol in which they exchange at most k bits, at the end of which Bob outputs a string in \{0, 1\}^k. If f(x, y)=1 (respectively, f(x, y)=0), then the distribution of Bob's output string must have statistical distance at most 1/3 (respectively, at least 2/3) from uniform. The cost of the protocol is k.  
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# The communication analog of non-interactive statistical zero knowledge proofs (\mathbf{NISZK}). This model can be defined as follows. For a given function f(x, y) \to \{0, 1\}, Alice and Bob engage in a (private coin) randomized communication protocol in which they exchange at most k bits, at the end of which Bob outputs a string in \{0, 1\}^k. If f(x, y)=1 (respectively, f(x, y)=0), then the distribution of Bob's output string must have statistical distance at most 1/3 (respectively, at least 2/3) from uniform. The cost of the protocol is k.
 +
# The communication complexity class \mathbf{OIP}_+^{[2]}, which is the two-party communication analog of 2-message streaming interactive proofs {{cite|ChakrabartiCMTV-15}}. This model involves three parties: Alice, Bob, and Merlin. Alice knows x, Bob knows y, and Merlin knows both x and y.  At the start of the protocol, Alice sends a randomized message to Bob (not seen by Merlin). Then Bob sends a message to Merlin, who sends a single message back to Bob. Bob then outputs 0 or 1. If f(x, y)=1, then there must be a Merlin strategy that convinces Bob to output 1 with probability at least 2/3. If f(x, y)=0, then for every Merlin strategy, Bob must output 0 with probability at least 2/3. The cost of the protocol is the sum of the length of all three messages sent (Alice to Bob, Bob to Merlin, Merlin to Bob).
  
b) The communication complexity class \mathbf{OIP}_+^{[2]}, which is the two-party communication analog of 2-message streaming interactive proofs {{cite|ChakrabartiCMTV-15}}. This model involves 3 parties, Alice, Bob, and Merlin. Alice knows x, Bob knows y, and Merlin knows both x and y.  At the start of the protocol, Alice sends a randomized message to Bob (not seen by Merlin). Then Bob sends a message to Merlin, who sends a single message back to Bob. Bob then outputs 0 or 1. If f(x, y)=1, then there must be a Merlin strategy that convinces Bob to output 1 with probability at least 2/3. If f(x, y)=0, then for every Merlin strategy, Bob must output 0 with probability at least 2/3. The cost of the protocol is the sum of the length of all three messages sent (Alice to Bob, Bob to Merlin, Merlin to Bob).
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{{cite|BoulandCHTV-16}} showed that both \mathbf{NISZK} and \mathbf{OIP}_+^{[2]} can, with logarithmic cost, compute (promise) problems outside of \mathbf{UPP}.  So the open question is to exhibit an explicit function, such as '''Disjointness''' or '''Inner-Product-Mod-2''', that cannot be computed by logarithmic cost \mathbf{NISZK} or \mathbf{OIP}_+^{[2]} protocols.
 
+
As far as we know, this is open even for 1-way \mathbf{NISZK}, in which Alice sends a single message to Bob of length k, after which Bob outputs a string in \{0, 1\}^k that must be either close or far from uniform depending on whether f(x, y)=1. (This model is also a special case of \mathbf{OIP}_+^{[2]}.) Even this model can, with logarithmic cost, compute functions outside \mathbf{UPP}, yet as far as we know it is possible that '''Index''' does not have a logarithmic cost protocol in this model.
{{cite|BoulandCHTV-16}} showed that both \mathbf{NISZK} and \mathbf{OIP}_+^{[2]} can, with logarithmic cost, compute (promise) problems outside of \mathbf{UPP}.  So the open question is to exhibit an explicit function, such as Disjointness or Inner Product Mod 2, that cannot be computed by logarithmic cost \mathbf{NISZK} or \mathbf{OIP}_+^{[2]} protocols.
 
 
 
As far as we know, this is open even for 1-way \mathbf{NISZK}, in which Alice sends a single message to Bob of length k, after which Bob outputs a string in \{0, 1\}^k that must be either close or far from uniform depending on whether f(x, y)=1. (This model is also a special case of \mathbf{OIP}_+^{[2]}). Even this model can, with logarithmic cost, compute functions outside \mathbf{UPP}, yet as far as we know it is possible that Index does not have a logarithmic cost protocol in this model.
 
  
 
==Notes==
 
==Notes==
 
<references />
 
<references />

Revision as of 02:35, 28 April 2017

Suggested by Justin Thaler
Source Banff 2017
Short link https://sublinear.info/77

In the \mathbf{UPP} communication model, two parties execute a (private coin) randomized communication protocol, and must output the correct answer with probability strictly greater than 1/2. Forster [Forster-01] proved a linear lower bound on the \mathbf{UPP} communication complexity of Inner Product Mod 2. \mathbf{UPP} is essentially the most powerful two-party communication model against which we know how to prove lower bounds.[1]

The (informal) open question is to prove a superlogarithmic lower bound for any natural communication complexity class that can compute problems outside of \mathbf{UPP}.

Here are two interesting candidate communication classes (both of these classes are subsets of \mathbf{AM}, a well-known frontier class in communication complexity).

  1. The communication analog of non-interactive statistical zero knowledge proofs (\mathbf{NISZK}). This model can be defined as follows. For a given function f(x, y) \to \{0, 1\}, Alice and Bob engage in a (private coin) randomized communication protocol in which they exchange at most k bits, at the end of which Bob outputs a string in \{0, 1\}^k. If f(x, y)=1 (respectively, f(x, y)=0), then the distribution of Bob's output string must have statistical distance at most 1/3 (respectively, at least 2/3) from uniform. The cost of the protocol is k.
  2. The communication complexity class \mathbf{OIP}_+^{[2]}, which is the two-party communication analog of 2-message streaming interactive proofs [ChakrabartiCMTV-15]. This model involves three parties: Alice, Bob, and Merlin. Alice knows x, Bob knows y, and Merlin knows both x and y. At the start of the protocol, Alice sends a randomized message to Bob (not seen by Merlin). Then Bob sends a message to Merlin, who sends a single message back to Bob. Bob then outputs 0 or 1. If f(x, y)=1, then there must be a Merlin strategy that convinces Bob to output 1 with probability at least 2/3. If f(x, y)=0, then for every Merlin strategy, Bob must output 0 with probability at least 2/3. The cost of the protocol is the sum of the length of all three messages sent (Alice to Bob, Bob to Merlin, Merlin to Bob).

[BoulandCHTV-16] showed that both \mathbf{NISZK} and \mathbf{OIP}_+^{[2]} can, with logarithmic cost, compute (promise) problems outside of \mathbf{UPP}. So the open question is to exhibit an explicit function, such as Disjointness or Inner-Product-Mod-2, that cannot be computed by logarithmic cost \mathbf{NISZK} or \mathbf{OIP}_+^{[2]} protocols. As far as we know, this is open even for 1-way \mathbf{NISZK}, in which Alice sends a single message to Bob of length k, after which Bob outputs a string in \{0, 1\}^k that must be either close or far from uniform depending on whether f(x, y)=1. (This model is also a special case of \mathbf{OIP}_+^{[2]}.) Even this model can, with logarithmic cost, compute functions outside \mathbf{UPP}, yet as far as we know it is possible that Index does not have a logarithmic cost protocol in this model.

Notes

  1. Jump up Let us ignore the example of Parity-P, which can compute Inner Product Mod 2 with constant communication, yet a linear lower bound on the Parity-P communication complexity of Equality follows from a matrix rank argument.