Low-Depth Arithmetic Circuit Lower Bounds: Bypassing Set-Multilinearization

Low-Depth Arithmetic Circuit Lower Bounds: Bypassing Set-Multilinearization

Authors Prashanth Amireddy, Ankit Garg, Neeraj Kayal, Chandan Saha, Bhargav Thankey



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Author Details

Prashanth Amireddy
  • Harvard University, Cambridge, MA, USA
Ankit Garg
  • Microsoft Research, Bangalore, India
Neeraj Kayal
  • Microsoft Research, Bangalore, India
Chandan Saha
  • Indian Institute of Science, Bangalore, India
Bhargav Thankey
  • Indian Institute of Science, Bangalore, India

Acknowledgements

We would like to thank the anonymous reviewers for their valuable feedback.

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Prashanth Amireddy, Ankit Garg, Neeraj Kayal, Chandan Saha, and Bhargav Thankey. Low-Depth Arithmetic Circuit Lower Bounds: Bypassing Set-Multilinearization. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 12:1-12:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/LIPIcs.ICALP.2023.12

Abstract

A recent breakthrough work of Limaye, Srinivasan and Tavenas [Nutan Limaye et al., 2021] proved superpolynomial lower bounds for low-depth arithmetic circuits via a "hardness escalation" approach: they proved lower bounds for low-depth set-multilinear circuits and then lifted the bounds to low-depth general circuits. In this work, we prove superpolynomial lower bounds for low-depth circuits by bypassing the hardness escalation, i.e., the set-multilinearization, step. As set-multilinearization comes with an exponential blow-up in circuit size, our direct proof opens up the possibility of proving an exponential lower bound for low-depth homogeneous circuits by evading a crucial bottleneck. Our bounds hold for the iterated matrix multiplication and the Nisan-Wigderson design polynomials. We also define a subclass of unrestricted depth homogeneous formulas which we call unique parse tree (UPT) formulas, and prove superpolynomial lower bounds for these. This significantly generalizes the superpolynomial lower bounds for regular formulas [Neeraj Kayal et al., 2014; Hervé Fournier et al., 2015].

Subject Classification

ACM Subject Classification
  • Theory of computation → Algebraic complexity theory
Keywords
  • arithmetic circuits
  • low-depth circuits
  • lower bounds
  • shifted partials

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References

  1. Manindra Agrawal and V. Vinay. Arithmetic Circuits: A Chasm at Depth Four. In 49th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2008, October 25-28, 2008, Philadelphia, PA, USA, pages 67-75. IEEE Computer Society, 2008. Google Scholar
  2. Prashanth Amireddy, Ankit Garg, Neeraj Kayal, Chandan Saha, and Bhargav Thankey. Low-depth arithmetic circuit lower bounds via shifted partials. Electron. Colloquium Comput. Complex., TR22-151, 2022. URL: https://eccc.weizmann.ac.il/report/2022/151.
  3. Suryajith Chillara, Nutan Limaye, and Srikanth Srinivasan. Small-depth multilinear formula lower bounds for iterated matrix multiplication with applications. SIAM J. Comput., 48(1):70-92, 2019. Conference version appeared in the proceedings of STACS 2018. URL: https://doi.org/10.1137/18M1191567.
  4. Michael A. Forbes, Mrinal Kumar, and Ramprasad Saptharishi. Functional lower bounds for arithmetic circuits and connections to boolean circuit complexity. In 31st Conference on Computational Complexity, CCC 2016, May 29 to June 1, 2016, Tokyo, Japan, pages 33:1-33:19, 2016. Google Scholar
  5. Lance Fortnow and Adam R. Klivans. Efficient learning algorithms yield circuit lower bounds. J. Comput. Syst. Sci., 75(1):27-36, 2009. Google Scholar
  6. Hervé Fournier, Nutan Limaye, Guillaume Malod, and Srikanth Srinivasan. Lower Bounds for Depth-4 Formulas Computing Iterated Matrix Multiplication. SIAM J. Comput., 44(5):1173-1201, 2015. Conference version appeared in the proceedings of STOC 2014. Google Scholar
  7. Ankit Garg, Neeraj Kayal, and Chandan Saha. Learning sums of powers of low-degree polynomials in the non-degenerate case. In Sandy Irani, editor, 61st IEEE Annual Symposium on Foundations of Computer Science, FOCS 2020, Durham, NC, USA, November 16-19, 2020, pages 889-899. IEEE, 2020. Google Scholar
  8. Fulvio Gesmundo and Joseph M. Landsberg. Explicit polynomial sequences with maximal spaces of partial derivatives and a question of k. mulmuley. Theory Comput., 15:1-24, 2019. URL: https://doi.org/10.4086/toc.2019.v015a003.
  9. Ankit Gupta, Pritish Kamath, Neeraj Kayal, and Ramprasad Saptharishi. Approaching the Chasm at Depth Four. J. ACM, 61(6):33:1-33:16, 2014. Conference version appeared in the proceedings of CCC 2013. Google Scholar
  10. Ankit Gupta, Pritish Kamath, Neeraj Kayal, and Ramprasad Saptharishi. Arithmetic Circuits: A Chasm at Depth 3. SIAM J. Comput., 45(3):1064-1079, 2016. Conference version appeared in the proceedings of FOCS 2013. Google Scholar
  11. Nikhil Gupta, Chandan Saha, and Bhargav Thankey. A super-quadratic lower bound for depth four arithmetic circuits. In Shubhangi Saraf, editor, 35th Computational Complexity Conference, CCC 2020, July 28-31, 2020, Saarbrücken, Germany (Virtual Conference), volume 169 of LIPIcs, pages 23:1-23:31. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. URL: https://doi.org/10.4230/LIPIcs.CCC.2020.23.
  12. Pavel Hrubes and Amir Yehudayoff. Homogeneous formulas and symmetric polynomials. Comput. Complex., 20(3):559-578, 2011. URL: https://doi.org/10.1007/s00037-011-0007-3.
  13. Neeraj Kayal. An exponential lower bound for the sum of powers of bounded degree polynomials. Electronic Colloquium on Computational Complexity (ECCC), 19:81, 2012. URL: http://eccc.hpi-web.de/report/2012/081.
  14. Neeraj Kayal, Nutan Limaye, Chandan Saha, and Srikanth Srinivasan. An Exponential Lower Bound for Homogeneous Depth Four Arithmetic Formulas. SIAM J. Comput., 46(1):307-335, 2017. Conference version appeared in the proceedings of FOCS 2014. Google Scholar
  15. Neeraj Kayal, Vineet Nair, and Chandan Saha. Separation Between Read-once Oblivious Algebraic Branching Programs (ROABPs) and Multilinear Depth-three Circuits. ACM Trans. Comput. Theory, 12(1):2:1-2:27, 2020. Conference version appeared in the proceedings of STACS 2016. Google Scholar
  16. Neeraj Kayal and Chandan Saha. Lower Bounds for Depth-Three Arithmetic Circuits with small bottom fanin. Computational Complexity, 25(2):419-454, 2016. Conference version appeared in the proceedings of CCC 2015. Google Scholar
  17. Neeraj Kayal and Chandan Saha. Multi-k-ic depth three circuit lower bound. Theory Comput. Syst., 61(4):1237-1251, 2017. The conference version appeared in the proceedings of STACS, 2015. URL: https://doi.org/10.1007/s00224-016-9742-9.
  18. Neeraj Kayal and Chandan Saha. Reconstruction of non-degenerate homogeneous depth three circuits. In Moses Charikar and Edith Cohen, editors, Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, STOC 2019, Phoenix, AZ, USA, June 23-26, 2019, pages 413-424. ACM, 2019. Google Scholar
  19. Neeraj Kayal, Chandan Saha, and Ramprasad Saptharishi. A super-polynomial lower bound for regular arithmetic formulas. In Symposium on Theory of Computing, STOC 2014, New York, NY, USA, May 31 - June 03, 2014, pages 146-153, 2014. Google Scholar
  20. Neeraj Kayal, Chandan Saha, and Sébastien Tavenas. An Almost Cubic Lower Bound for Depth Three Arithmetic Circuits. In 43rd International Colloquium on Automata, Languages, and Programming, ICALP 2016, July 11-15, 2016, Rome, Italy, pages 33:1-33:15, 2016. Google Scholar
  21. Neeraj Kayal, Chandan Saha, and Sébastien Tavenas. On the size of homogeneous and of depth four formulas with low individual degree. In Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2016, Cambridge, MA, USA, June 18-21, 2016, pages 626-632, 2016. Google Scholar
  22. Pascal Koiran. Arithmetic circuits: The chasm at depth four gets wider. Theor. Comput. Sci., 448:56-65, 2012. Google Scholar
  23. Mrinal Kumar and Ramprasad Saptharishi. The computational power of depth five arithmetic circuits. SIAM J. Comput., 48(1):144-180, 2019. URL: https://doi.org/10.1137/18M1173319.
  24. Mrinal Kumar and Shubhangi Saraf. The limits of depth reduction for arithmetic formulas: it’s all about the top fan-in. In Symposium on Theory of Computing, STOC 2014, New York, NY, USA, May 31 - June 03, 2014, pages 136-145, 2014. Google Scholar
  25. Mrinal Kumar and Shubhangi Saraf. Superpolynomial lower bounds for general homogeneous depth 4 arithmetic circuits. In Automata, Languages, and Programming - 41st International Colloquium, ICALP 2014, Copenhagen, Denmark, July 8-11, 2014, Proceedings, Part I, pages 751-762, 2014. Google Scholar
  26. Mrinal Kumar and Shubhangi Saraf. On the Power of Homogeneous Depth 4 Arithmetic Circuits. SIAM J. Comput., 46(1):336-387, 2017. Conference version appeared in the proceedings of FOCS 2014. Google Scholar
  27. Deepanshu Kush and Shubhangi Saraf. Improved low-depth set-multilinear circuit lower bounds. In Shachar Lovett, editor, 37th Computational Complexity Conference, CCC 2022, July 20-23, 2022, Philadelphia, PA, USA, volume 234 of LIPIcs, pages 38:1-38:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. URL: https://doi.org/10.4230/LIPIcs.CCC.2022.38.
  28. Guillaume Lagarde, Nutan Limaye, and Srikanth Srinivasan. Lower Bounds and PIT for Non-commutative Arithmetic Circuits with Restricted Parse Trees. Computational Complexity, 28(3):471-542, 2019. Google Scholar
  29. Nutan Limaye, Srikanth Srinivasan, and Sébastien Tavenas. Superpolynomial Lower Bounds Against Low-Depth Algebraic Circuits. In 62nd IEEE Annual Symposium on Foundations of Computer Science, FOCS 2021, Denver, CO, USA, February 7-10, 2022, pages 804-814. IEEE, 2021. A full version of the paper can be found at URL: https://eccc.weizmann.ac.il/report/2021/081.
  30. Nutan Limaye, Srikanth Srinivasan, and Sébastien Tavenas. On the partial derivative method applied to lopsided set-multilinear polynomials. In Shachar Lovett, editor, 37th Computational Complexity Conference, CCC 2022, July 20-23, 2022, Philadelphia, PA, USA, volume 234 of LIPIcs, pages 32:1-32:23. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. URL: https://doi.org/10.4230/LIPIcs.CCC.2022.32.
  31. Noam Nisan. Lower Bounds for Non-Commutative Computation (Extended Abstract). In Cris Koutsougeras and Jeffrey Scott Vitter, editors, Proceedings of the 23rd Annual ACM Symposium on Theory of Computing, May 5-8, 1991, New Orleans, Louisiana, USA, pages 410-418. ACM, 1991. Google Scholar
  32. Noam Nisan and Avi Wigderson. Lower Bounds on Arithmetic Circuits Via Partial Derivatives. Computational Complexity, 6(3):217-234, 1997. Conference version appeared in the proceedings of FOCS 1995. Google Scholar
  33. Ran Raz. On the Complexity of Matrix Product. SIAM J. Comput., 32(5):1356-1369, 2003. Conference version appeared in the proceedings of STOC 2002. Google Scholar
  34. Ran Raz. Separation of Multilinear Circuit and Formula Size. Theory of Computing, 2(6):121-135, 2006. Conference version appeared in the proceedings of FOCS 2004. Google Scholar
  35. Ran Raz. Tensor-Rank and Lower Bounds for Arithmetic Formulas. J. ACM, 60(6):40:1-40:15, 2013. Conference version appeared in the proceedings of STOC 2010. Google Scholar
  36. Ran Raz and Amir Yehudayoff. Lower Bounds and Separations for Constant Depth Multilinear Circuits. Computational Complexity, 18(2):171-207, 2009. Conference version appeared in the proceedings of CCC 2008. Google Scholar
  37. Bruce Reznick. Sums of even powers of real linear forms. Memoirs of the AMS, 96:463, 1992. Google Scholar
  38. Amir Shpilka and Avi Wigderson. Depth-3 arithmetic circuits over fields of characteristic zero. Computational Complexity, 10(1):1-27, 2001. Conference version appeared in the proceedings of CCC 1999. Google Scholar
  39. Sébastien Tavenas. Improved bounds for reduction to depth 4 and depth 3. Inf. Comput., 240:2-11, 2015. Conference version appeared in the proceedings of MFCS 2013. Google Scholar
  40. Leslie G. Valiant. Completeness Classes in Algebra. In Proceedings of the 11h Annual ACM Symposium on Theory of Computing, April 30 - May 2, 1979, Atlanta, Georgia, USA, pages 249-261, 1979. Google Scholar
  41. Leslie G. Valiant, Sven Skyum, S. Berkowitz, and Charles Rackoff. Fast Parallel Computation of Polynomials Using Few Processors. SIAM J. Comput., 12(4):641-644, 1983. Google Scholar
  42. Ilya Volkovich. A Guide to Learning Arithmetic Circuits. In Proceedings of the 29th Conference on Learning Theory, COLT 2016, New York, USA, June 23-26, 2016, pages 1540-1561, 2016. Google Scholar
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