Separating Deterministic from Nondeterministic NOF Multiparty Communication Complexity

We solve some fundamental problems in the number-onforehead (NOF) k-party communication model. We show that there exists a function which has at most logarithmic communication complexity for randomized protocols with a one-sided error probability of 1/3 but which has linear communication complexity for deterministic protocols. The result is true for k = nO(1) players, where n is the number of bits on each players' forehead. This separates the analogues of RP and P in the NOF communication model. We also show that there exists a function which has constant randomized complexity for public coin protocols but at least logarithmic complexity for private coin protocols. No larger gap between private and public coin protocols is possible. Our lower bounds are existential and we do not know of any explicit function which allows such separations. However, for the 3-player case we exhibit an explicit function which has Ω(log log n) randomized complexity for private coins but only constant complexity for public coins. It follows from our existential result that any function that is complete for the class of functions with polylogarithmic nondeterministic k-party communication complexity does not have polylogarithmic deterministic complexity. We show that the set intersection function, which is complete in the number-in-hand model, is not complete in the NOF model under cylindrical reductions.

[1]  Peter Frankl,et al.  Complexity classes in communication complexity theory (preliminary version) , 1986, IEEE Annual Symposium on Foundations of Computer Science.

[2]  Andrew Chi-Chih Yao,et al.  Some complexity questions related to distributive computing(Preliminary Report) , 1979, STOC.

[3]  Noam Nisan,et al.  Multiparty Protocols, Pseudorandom Generators for Logspace, and Time-Space Trade-Offs , 1992, J. Comput. Syst. Sci..

[4]  Noam Nisan,et al.  Rounds in communication complexity revisited , 1991, STOC '91.

[5]  Toniann Pitassi,et al.  Lower Bounds for Lov[a-acute]sz--Schrijver Systems and Beyond Follow from Multiparty Communication Complexity , 2007, SIAM J. Comput..

[6]  Richard J. Lipton,et al.  Multi-party protocols , 1983, STOC.

[7]  Toniann Pitassi,et al.  Lower bounds for Lov´ asz-Schrijver systems and beyond, using multiparty communication complexity , 2005 .

[8]  Richard Beigel,et al.  On ACC , 1994, computational complexity.

[9]  Fan Chung Graham,et al.  Communication Complexity and Quasi Randomness , 1993, SIAM J. Discret. Math..

[10]  Satyanarayana V. Lokam,et al.  Communication Complexity of Simultaneous Messages , 2003, SIAM J. Comput..

[11]  Toniann Pitassi,et al.  Lower Bounds for Lovász-Schrijver Systems and Beyond Follow from Multiparty Communication Complexity , 2005, ICALP.

[12]  Noam Nisan,et al.  The computational complexity of universal hashing , 1990, STOC '90.

[13]  Ran Raz,et al.  The BNS-Chung criterion for multi-party communication complexity , 2000, computational complexity.

[14]  Ilan Newman,et al.  Private vs. Common Random Bits in Communication Complexity , 1991, Inf. Process. Lett..

[15]  N. Nisan The communication complexity of threshold gates , 1993 .

[16]  William I. Gasarch,et al.  The Multiparty Communication Complexity of Exact-T: Improved Bounds and New Problems , 2006, MFCS.

[17]  Johan Håstad,et al.  On the power of small-depth threshold circuits , 1991, computational complexity.

[18]  Peter Frankl,et al.  Complexity classes in communication complexity theory , 1986, 27th Annual Symposium on Foundations of Computer Science (sfcs 1986).