Pseudodistributions That Beat All Pseudorandom Generators (Extended Abstract)

Authors Edward Pyne, Salil Vadhan



PDF
Thumbnail PDF

File

LIPIcs.CCC.2021.33.pdf
  • Filesize: 0.73 MB
  • 15 pages

Document Identifiers

Author Details

Edward Pyne
  • Harvard University, Cambridge, MA, USA
Salil Vadhan
  • Harvard University, Cambridge, MA, USA

Acknowledgements

We thank Jack Murtagh and Sumegha Garg for insightful discussions, and Oded Goldreich and the CCC `21 reviewers for feedback that improved our presentation.

Cite As Get BibTex

Edward Pyne and Salil Vadhan. Pseudodistributions That Beat All Pseudorandom Generators (Extended Abstract). In 36th Computational Complexity Conference (CCC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 200, pp. 33:1-33:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.CCC.2021.33

Abstract

A recent paper of Braverman, Cohen, and Garg (STOC 2018) introduced the concept of a weighted pseudorandom generator (WPRG), which amounts to a pseudorandom generator (PRG) whose outputs are accompanied with real coefficients that scale the acceptance probabilities of any potential distinguisher. They gave an explicit construction of WPRGs for ordered branching programs whose seed length has a better dependence on the error parameter ε than the classic PRG construction of Nisan (STOC 1990 and Combinatorica 1992). 
In this work, we give an explicit construction of WPRGs that achieve parameters that are impossible to achieve by a PRG. In particular, we construct a WPRG for ordered permutation branching programs of unbounded width with a single accept state that has seed length Õ(log^{3/2} n) for error parameter ε = 1/poly(n), where n is the input length. In contrast, recent work of Hoza et al. (ITCS 2021) shows that any PRG for this model requires seed length Ω(log² n) to achieve error ε = 1/poly(n).
As a corollary, we obtain explicit WPRGs with seed length Õ(log^{3/2} n) and error ε = 1/poly(n) for ordered permutation branching programs of width w = poly(n) with an arbitrary number of accept states. Previously, seed length o(log² n) was only known when both the width and the reciprocal of the error are subpolynomial, i.e. w = n^{o(1)} and ε = 1/n^{o(1)} (Braverman, Rao, Raz, Yehudayoff, FOCS 2010 and SICOMP 2014).
The starting point for our results are the recent space-efficient algorithms for estimating random-walk probabilities in directed graphs by Ahmadenijad, Kelner, Murtagh, Peebles, Sidford, and Vadhan (FOCS 2020), which are based on spectral graph theory and space-efficient Laplacian solvers. We interpret these algorithms as giving WPRGs with large seed length, which we then derandomize to obtain our results. We also note that this approach gives a simpler proof of the original result of Braverman, Cohen, and Garg, as independently discovered by Cohen, Doron, Renard, Sberlo, and Ta-Shma (these proceedings).

Subject Classification

ACM Subject Classification
  • Theory of computation → Pseudorandomness and derandomization
Keywords
  • pseudorandomness
  • space-bounded computation
  • spectral graph theory

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Rohit Agrawal. Samplers and extractors for unbounded functions. In Dimitris Achlioptas and László A. Végh, editors, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2019, September 20-22, 2019, Massachusetts Institute of Technology, Cambridge, MA, USA, volume 145 of LIPIcs, pages 59:1-59:21. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. URL: https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2019.59.
  2. AmirMahdi Ahmadinejad, Jonathan A. Kelner, Jack Murtagh, John Peebles, Aaron Sidford, and Salil P. Vadhan. High-precision estimation of random walks in small space. In 61st IEEE Annual Symposium on Foundations of Computer Science, FOCS 2020, Durham, NC, USA, November 16-19, 2020, pages 1295-1306. IEEE, 2020. URL: https://doi.org/10.1109/FOCS46700.2020.00123.
  3. Alexander E. Andreev, Andrea E. F. Clementi, and José D. P. Rolim. A new general derandomization method. Journal of the ACM, 45(1):179-213, 1998. URL: https://doi.org/10.1145/273865.273933.
  4. Alexander E. Andreev, Andrea E. F. Clementi, José D. P. Rolim, and Luca Trevisan. Weak random sources, hitting sets, and BPP simulations. SIAM Journal on Computing, 28(6):2103-2116 (electronic), 1999. Google Scholar
  5. Roy Armoni. On the derandomization of space-bounded computations. In Randomization and approximation techniques in computer science (Barcelona, 1998), volume 1518 of Lecture Notes in Comput. Sci., pages 47-59. Springer, Berlin, 1998. Google Scholar
  6. Jaroslaw Blasiok. Optimal streaming and tracking distinct elements with high probability. In Artur Czumaj, editor, Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018, New Orleans, LA, USA, January 7-10, 2018, pages 2432-2448. SIAM, 2018. URL: https://doi.org/10.1137/1.9781611975031.156.
  7. Manuel Blum and Silvio Micali. How to generate cryptographically strong sequences of pseudorandom bits. SIAM Journal on Computing, 13(4):850-864, 1984. URL: https://doi.org/10.1137/0213053.
  8. Andrej Bogdanov, Zeev Dvir, Elad Verbin, and Amir Yehudayoff. Pseudorandomness for width 2 branching programs. Electronic Colloquium on Computational Complexity (ECCC), 16:70, 2009. URL: http://eccc.hpi-web.de/report/2009/070.
  9. Mark Braverman, Gil Cohen, and Sumegha Garg. Hitting sets with near-optimal error for read-once branching programs. In Ilias Diakonikolas, David Kempe, and Monika Henzinger, editors, Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2018, Los Angeles, CA, USA, June 25-29, 2018, pages 353-362. ACM, 2018. URL: https://doi.org/10.1145/3188745.3188780.
  10. Mark Braverman, Anup Rao, Ran Raz, and Amir Yehudayoff. Pseudorandom generators for regular branching programs. In FOCS, pages 40-47. IEEE Computer Society, 2010. URL: https://doi.org/10.1109/FOCS.2010.11.
  11. Harry Buhrman and Lance Fortnow. One-sided two-sided error in probabilistic computation. In STACS 99 (Trier), volume 1563 of Lecture Notes in Comput. Sci., pages 100-109. Springer, Berlin, 1999. Google Scholar
  12. Eshan Chattopadhyay and Jyun-Jie Liao. Optimal error pseudodistributions for read-once branching programs. In Shubhangi Saraf, editor, 35th Computational Complexity Conference, CCC 2020, July 28-31, 2020, Saarbrücken, Germany (Virtual Conference), volume 169 of LIPIcs, pages 25:1-25:27. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. URL: https://doi.org/10.4230/LIPIcs.CCC.2020.25.
  13. Kuan Cheng and William M. Hoza. Hitting sets give two-sided derandomization of small space. In Shubhangi Saraf, editor, 35th Computational Complexity Conference, CCC 2020, July 28-31, 2020, Saarbrücken, Germany (Virtual Conference), volume 169 of LIPIcs, pages 10:1-10:25. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. URL: https://doi.org/10.4230/LIPIcs.CCC.2020.10.
  14. Gil Cohen, Dean Doron, Oren Renard, Ori Sberlo, and Amnon Ta-Shma. Error reduction for weighted prgs against read once branching programs. In 36th Computational Complexity Conference, CCC 2021, July 19-23, 2021, Toronto, Ontario (Virtual Conference), 2021. To appear. Google Scholar
  15. Anindya De. Pseudorandomness for permutation and regular branching programs. In IEEE Conference on Computational Complexity, pages 221-231. IEEE Computer Society, 2011. URL: https://doi.org/10.1109/CCC.2011.23.
  16. Oded Goldreich. A sample of samplers - a computational perspective on sampling (survey). Electronic Colloquium on Computational Complexity (ECCC), 4(20), 1997. URL: http://eccc.hpi-web.de/eccc-reports/1997/TR97-020/index.html.
  17. Oded Goldreich. A primer on pseudorandom generators, volume 55 of University Lecture Series. American Mathematical Society, Providence, RI, 2010. Google Scholar
  18. Oded Goldreich, Salil Vadhan, and Avi Wigderson. Simplified derandomization of bpp using a hitting set generator. In Studies in Complexity and Cryptography. Miscellanea on the Interplay of Randomness and Computation, volume 6650 of Lecture Notes in Computer Science, pages 59-67. Springer, 2011. Google Scholar
  19. Parikshit Gopalan, Raghu Meka, Omer Reingold, Luca Trevisan, and Salil Vadhan. Better pseudorandom generators via milder pseudorandom restrictions. In Proceedings of the 53rd Annual IEEE Symposium on Foundations of Computer Science (FOCS `12). IEEE, 20-23 October 2012. Google Scholar
  20. William M. Hoza, Edward Pyne, and Salil P. Vadhan. Pseudorandom generators for unbounded-width permutation branching programs. In James R. Lee, editor, 12th Innovations in Theoretical Computer Science Conference, ITCS 2021, January 6-8, 2021, Virtual Conference, volume 185 of LIPIcs, pages 7:1-7:20. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. URL: https://doi.org/10.4230/LIPIcs.ITCS.2021.7.
  21. Russell Impagliazzo, Noam Nisan, and Avi Wigderson. Pseudorandomness for network algorithms. In Proceedings of the Twenty-Sixth Annual ACM Symposium on the Theory of Computing, pages 356-364, Montréal, Québec, Canada, 23-25 May 1994. Google Scholar
  22. Daniel M. Kane, Jelani Nelson, and David P. Woodruff. Revisiting norm estimation in data streams. CoRR, abs/0811.3648, 2008. URL: http://arxiv.org/abs/0811.3648.
  23. Michal Koucký, Prajakta Nimbhorkar, and Pavel Pudlák. Pseudorandom generators for group products: extended abstract. In Lance Fortnow and Salil P. Vadhan, editors, STOC, pages 263-272. ACM, 2011. URL: https://doi.org/10.1145/1993636.1993672.
  24. Raghu Meka, Omer Reingold, and Avishay Tal. Pseudorandom generators for width-3 branching programs. In Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, pages 626-637. ACM, 2019. Google Scholar
  25. Noam Nisan. Pseudorandom generators for space-bounded computation. Combinatorica, 12(4):449-461, 1992. Google Scholar
  26. Noam Nisan and Avi Wigderson. Hardness vs randomness. Journal of Computer and System Sciences, 49(2):149-167, October 1994. Google Scholar
  27. Noam Nisan and David Zuckerman. Randomness is linear in space. Journal of Computer and System Sciences, 52(1):43-52, February 1996. Google Scholar
  28. Edward Pyne and Salil Vadhan. Pseudodistributions that beat all pseudorandom generators. ECCC preprint TR21-019, 2021. Google Scholar
  29. Omer Reingold, Luca Trevisan, and Salil Vadhan. Pseudorandom walks in regular digraphs and the RL vs. L problem. In Proceedings of the 38th Annual ACM Symposium on Theory of Computing (STOC `06), pages 457-466, 21-23 May 2006. Preliminary version as ECCC TR05-22, February 2005. Google Scholar
  30. Eyal Rozenman and Salil Vadhan. Derandomized squaring of graphs. In Proceedings of the 8th International Workshop on Randomization and Computation (RANDOM `05), number 3624 in Lecture Notes in Computer Science, pages 436-447, Berkeley, CA, August 2005. Springer. Google Scholar
  31. Michael Saks and Shiyu Zhou. BP_H SPACE(S) ⊆ DSPACE(S^(3/2)). Journal of Computer and System Sciences, 58(2):376-403, 1999. Google Scholar
  32. Jirí Síma and Stanislav Zák. Almost k-wise independent sets establish hitting sets for width-3 1-branching programs. In Alexander S. Kulikov and Nikolay K. Vereshchagin, editors, CSR, volume 6651 of Lecture Notes in Computer Science, pages 120-133. Springer, 2011. URL: https://doi.org/10.1007/978-3-642-20712-9_10.
  33. Thomas Steinke. Pseudorandomness for permutation branching programs without the group theory. Technical Report TR12-083, Electronic Colloquium on Computational Complexity (ECCC), July 2012. URL: http://eccc.hpi-web.de/report/2012/083/.
  34. Salil P Vadhan. Pseudorandomness. Foundations and Trendsregistered in Theoretical Computer Science, 7(1-3):1-336, 2012. Google Scholar
  35. Andrew C. Yao. Theory and applications of trapdoor functions (extended abstract). In 23rd Annual Symposium on Foundations of Computer Science, pages 80-91, Chicago, Illinois, 3-5 November 1982. IEEE. Google Scholar
  36. David Zuckerman. Randomness-optimal oblivious sampling. Random Structures & Algorithms, 11(4):345-367, 1997. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail