Hitting Sets and Reconstruction for Dense Orbits in VP_{e} and ΣΠΣ Circuits

Authors Dori Medini, Amir Shpilka



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Dori Medini
  • StarkWare Industries Ltd., Netanya, Israel
Amir Shpilka
  • Blavatnik School of Computer Science, Tel Aviv University, Israel

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Dori Medini and Amir Shpilka. Hitting Sets and Reconstruction for Dense Orbits in VP_{e} and ΣΠΣ Circuits. In 36th Computational Complexity Conference (CCC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 200, pp. 19:1-19:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.CCC.2021.19

Abstract

In this paper we study polynomials in VP_{e} (polynomial-sized formulas) and in ΣΠΣ (polynomial-size depth-3 circuits) whose orbits, under the action of the affine group GL^{aff}_n(𝔽) (the action of (A,b) ∈ GL^{aff}_n(𝔽) on a polynomial f ∈ 𝔽[x] is defined as (A,b)∘f = f(A^Tx+b)), are dense in their ambient class. We construct hitting sets and interpolating sets for these orbits as well as give reconstruction algorithms. Specifically, we obtain the following results:  
1) For C_n(ℓ_1(x),…,ℓ_n(x)) ≜ Trace(\begin{pmatrix} 𝓁₁(x) & 1 \\ 1 & 0 \end{pmatrix} ⋅ … ⋅ \begin{pmatrix} 𝓁_n(x) & 1 \\ 1 & 0 \end{pmatrix}), where the 𝓁_is are linearly independent linear functions, we construct a polynomial-sized interpolating set, and give a polynomial-time reconstruction algorithm. By a result of Bringmann, Ikenmeyer and Zuiddam, the set of all such polynomials is dense in VP_e [Karl Bringmann et al., 2018], thus our construction gives the first polynomial-size interpolating set for a dense subclass of VP_e. 
2) For polynomials of the form ANF_Δ(𝓁₁(x),…,𝓁_{4^Δ}(x)), where ANF_Δ(x) is the canonical read-once formula in alternating normal form, of depth 2Δ, and the 𝓁_is are linearly independent linear functions, we provide a quasipolynomial-size interpolating set. We also observe that the reconstruction algorithm of [Ankit Gupta et al., 2014] works for all polynomials in this class. This class is also dense in VP_e. 
3) Similarly, we give a quasipolynomial-sized hitting set for read-once formulas (not necessarily in alternating normal form) composed with a set of linearly independent linear functions. This gives another dense class in VP_e. 
4) We give a quasipolynomial-sized hitting set for polynomials of the form f(𝓁₁(x),…,𝓁_{m}(x)), where f is an m-variate s-sparse polynomial. and the 𝓁_is are linearly independent linear functions in n ≥ m variables. This class is dense in ΣΠΣ. 
5) For polynomials of the form ∑_{i=1}^{s}∏_{j=1}^{d}𝓁_{i,j}(x), where the 𝓁_{i,j}s are linearly independent linear functions, we construct a polynomial-sized interpolating set. We also observe that the reconstruction algorithm of [Neeraj Kayal and Chandan Saha, 2019] works for every polynomial in the class. This class is dense in ΣΠΣ.  As VP = VNC², our results for VP_{e} translate immediately to VP with a quasipolynomial blow up in parameters. If any of our hitting or interpolating sets could be made robust then this would immediately yield a hitting set for the superclass in which the relevant class is dense, and as a consequence also a lower bound for the superclass. Unfortunately, we also prove that the kind of constructions that we have found (which are defined in terms of k-independent polynomial maps) do not necessarily yield robust hitting sets.

Subject Classification

ACM Subject Classification
  • Theory of computation → Algebraic complexity theory
Keywords
  • Algebraic complexity
  • VP
  • VNP
  • algebraic circuits
  • algebraic formula

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References

  1. Manindra Agrawal, Neeraj Kayal, and Nitin Saxena. Primes is in p. Ann. of Math, 2:781-793, 2002. Google Scholar
  2. Manindra Agrawal, Chandan Saha, Ramprasad Saptharishi, and Nitin Saxena. Jacobian hits circuits: Hitting sets, lower bounds for depth-d occur-k formulas and depth-3 transcendence degree-k circuits. SIAM J. Comput., 45(4):1533-1562, 2016. URL: https://doi.org/10.1137/130910725.
  3. A. Alder. Grenzrang und Grenzkomplexität aus algebraischer und topologischer Sicht. PhD thesis, Universität Zürich, Philosophische Fakultät II, 1984. Google Scholar
  4. Eric Allender and Fengming Wang. On the power of algebraic branching programs of width two. Computational Complexity, 25(1):217-253, 2016. URL: https://doi.org/10.1007/s00037-015-0114-7.
  5. Matthew Anderson, Michael A. Forbes, Ramprasad Saptharishi, Amir Shpilka, and Ben Lee Volk. Identity testing and lower bounds for read-k oblivious algebraic branching programs. ACM Trans. Comput. Theory, 10(1):3:1-3:30, 2018. URL: https://doi.org/10.1145/3170709.
  6. Matthew Anderson, Dieter van Melkebeek, and Ilya Volkovich. Deterministic polynomial identity tests for multilinear bounded-read formulae. Computational Complexity, 24(4):695-776, 2015. URL: https://doi.org/10.1007/s00037-015-0097-4.
  7. Amos Beimel, Francesco Bergadano, Nader H. Bshouty, Eyal Kushilevitz, and Stefano Varricchio. Learning functions represented as multiplicity automata. J. ACM, 47(3):506-530, 2000. URL: https://doi.org/10.1145/337244.337257.
  8. Michael Ben-Or and Richard Cleve. Computing algebraic formulas using a constant number of registers. SIAM J. Comput., 21(1):54-58, 1992. URL: https://doi.org/10.1137/0221006.
  9. Michael Ben-Or and Prasoon Tiwari. A deterministic algorithm for sparse multivariate polynominal interpolation (extended abstract). In Janos Simon, editor, Proceedings of the 20th Annual ACM Symposium on Theory of Computing, May 2-4, 1988, Chicago, Illinois, USA, pages 301-309. ACM, 1988. URL: https://doi.org/10.1145/62212.62241.
  10. Vishwas Bhargava and Sumanta Ghosh. Improved hitting set for orbit of roabps. Electron. Colloquium Comput. Complex., 28:62, 2021. URL: https://eccc.weizmann.ac.il/report/2021/062/.
  11. Vishwas Bhargava, Shubhangi Saraf, and Ilya Volkovich. Reconstruction of depth-4 multilinear circuits. In Shuchi Chawla, editor, Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, SODA 2020, Salt Lake City, UT, USA, January 5-8, 2020, pages 2144-2160. SIAM, 2020. URL: https://doi.org/10.1137/1.9781611975994.132.
  12. Dario Bini, Milvio Capovani, Francesco Romani, and Grazia Lotti. O(n^2.7799) complexity for n × n approximate matrix multiplication. Information Processing Letters, 8(5):234-235, 1979. URL: https://doi.org/10.1016/0020-0190(79)90113-3.
  13. Markus Bläser and Christian Ikenmeyer. Introduction to geometric complexity theory. https://pcwww.liv.ac.uk/~iken/teaching_sb/summer17/introtogct/gct.pdf, 2019.
  14. Karl Bringmann, Christian Ikenmeyer, and Jeroen Zuiddam. On algebraic branching programs of small width. J. ACM, 65(5):32:1-32:29, 2018. URL: https://doi.org/10.1145/3209663.
  15. Daoud Bshouty and Nader H. Bshouty. On interpolating arithmetic read-once formulas with exponentiation. J. Comput. Syst. Sci., 56(1):112-124, 1998. URL: https://doi.org/10.1006/jcss.1997.1550.
  16. Nader H. Bshouty, Thomas R. Hancock, and Lisa Hellerstein. Learning arithmetic read-once formulas. SIAM J. Comput., 24(4):706-735, 1995. URL: https://doi.org/10.1137/S009753979223664X.
  17. Peter Bürgisser. The complexity of factors of multivariate polynomials. Found. Comput. Math., 4(4):369-396, 2004. URL: https://doi.org/10.1007/s10208-002-0059-5.
  18. Peter Bürgisser, Michael Clausen, and Mohammad A Shokrollahi. Algebraic complexity theory, volume 315. Springer Science & Business Media, 2013. Google Scholar
  19. Chi-Ning Chou, Mrinal Kumar, and Noam Solomon. Hardness vs randomness for bounded depth arithmetic circuits. In Rocco A. Servedio, editor, 33rd Computational Complexity Conference, CCC 2018, June 22-24, 2018, San Diego, CA, USA, volume 102 of LIPIcs, pages 13:1-13:17. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018. URL: https://doi.org/10.4230/LIPIcs.CCC.2018.13.
  20. Rafael Mendes de Oliveira, Amir Shpilka, and Ben lee Volk. Subexponential size hitting sets for bounded depth multilinear formulas. Computational Complexity, 25(2):455-505, 2016. URL: https://doi.org/10.1007/s00037-016-0131-1.
  21. Zeev Dvir and Amir Shpilka. Locally decodable codes with two queries and polynomial identity testing for depth 3 circuits. SIAM Journal on Computing, 36(5):1404-1434, 2007. Google Scholar
  22. Zeev Dvir, Amir Shpilka, and Amir Yehudayoff. Hardness-Randomness Tradeoffs for Bounded Depth Arithmetic Circuits. SIAM J. Comput., 39(4):1279-1293, 2009. URL: https://doi.org/10.1137/080735850.
  23. Stephen A. Fenner, Rohit Gurjar, and Thomas Thierauf. A deterministic parallel algorithm for bipartite perfect matching. Commun. ACM, 62(3):109-115, 2019. URL: https://doi.org/10.1145/3306208.
  24. Michael A. Forbes. Some concrete questions on the border complexity of polynomials. https://www.youtube.com/watch?v=1HMogQIHT6Q, 2016.
  25. Michael A. Forbes, Ramprasad Saptharishi, and Amir Shpilka. Hitting sets for multilinear read-once algebraic branching programs, in any order. In David B. Shmoys, editor, Symposium on Theory of Computing, STOC 2014, New York, NY, USA, May 31 - June 03, 2014, pages 867-875. ACM, 2014. URL: https://doi.org/10.1145/2591796.2591816.
  26. Michael A. Forbes and Amir Shpilka. A PSPACE construction of a hitting set for the closure of small algebraic circuits. 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 1180-1192. ACM, 2018. URL: https://doi.org/10.1145/3188745.3188792.
  27. Michael A. Forbes, Amir Shpilka, Iddo Tzameret, and Avi Wigderson. Proof complexity lower bounds from algebraic circuit complexity. In Ran Raz, editor, 31st Conference on Computational Complexity, CCC 2016, May 29 to June 1, 2016, Tokyo, Japan, volume 50 of LIPIcs, pages 32:1-32:17. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2016. Full version at http://arxiv.org/abs/1606.05050. URL: https://doi.org/10.4230/LIPIcs.CCC.2016.32.
  28. Michael A. Forbes, Amir Shpilka, and Ben Lee Volk. Succinct hitting sets and barriers to proving lower bounds for algebraic circuits. Theory of Computing, 14(1):1-45, 2018. URL: https://doi.org/10.4086/toc.2018.v014a018.
  29. Joshua A. Grochow. Unifying known lower bounds via geometric complexity theory. Computational Complexity, 24(2):393-475, 2015. URL: https://doi.org/10.1007/s00037-015-0103-x.
  30. Joshua A. Grochow, Mrinal Kumar, Michael E. Saks, and Shubhangi Saraf. Towards an algebraic natural proofs barrier via polynomial identity testing. CoRR, abs/1701.01717, 2017. URL: http://arxiv.org/abs/1701.01717.
  31. Zeyu Guo and Rohit Gurjar. Improved explicit hitting-sets for roabps. In Jaroslaw Byrka and Raghu Meka, editors, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2020, August 17-19, 2020, Virtual Conference, volume 176 of LIPIcs, pages 4:1-4:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. URL: https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2020.4.
  32. Zeyu Guo, Mrinal Kumar, Ramprasad Saptharishi, and Noam Solomon. Derandomization from algebraic hardness: Treading the borders. In David Zuckerman, editor, 60th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2019, Baltimore, Maryland, USA, November 9-12, 2019, pages 147-157. IEEE Computer Society, 2019. URL: https://doi.org/10.1109/FOCS.2019.00018.
  33. Ankit Gupta, Pritish Kamath, Neeraj Kayal, and Ramprasad Saptharishi. Arithmetic circuits: A chasm at depth 3. SIAM J. Comput., 45(3):1064-1079, 2016. URL: https://doi.org/10.1137/140957123.
  34. Ankit Gupta, Neeraj Kayal, and Satya Lokam. Reconstruction of depth-4 multilinear circuits with top fan-in 2. In Proceedings of the forty-fourth annual ACM symposium on Theory of computing, pages 625-642, 2012. Google Scholar
  35. Ankit Gupta, Neeraj Kayal, and Youming Qiao. Random arithmetic formulas can be reconstructed efficiently. Computational Complexity, 23(2):207-303, 2014. URL: https://doi.org/10.1007/s00037-014-0085-0.
  36. Johan Håstad. Tensor rank is NP-complete. J. Algorithms, 11(4):644-654, 1990. URL: https://doi.org/10.1016/0196-6774(90)90014-6.
  37. Joos Heintz and Claus-Peter Schnorr. Testing polynomials which are easy to compute (extended abstract). In Raymond E. Miller, Seymour Ginsburg, Walter A. Burkhard, and Richard J. Lipton, editors, Proceedings of the 12th Annual ACM Symposium on Theory of Computing, April 28-30, 1980, Los Angeles, California, USA, pages 262-272. ACM, 1980. URL: https://doi.org/10.1145/800141.804674.
  38. Valentine Kabanets and Russell Impagliazzo. Derandomizing polynomial identity tests means proving circuit lower bounds. Computational Complexity, 13(1-2):1-46, 2004. URL: https://doi.org/10.1007/s00037-004-0182-6.
  39. Kyriakos Kalorkoti. A lower bound for the formula size of rational functions. SIAM J. Comput., 14(3):678-687, 1985. URL: https://doi.org/10.1137/0214050.
  40. Zohar S Karnin and Amir Shpilka. Black box polynomial identity testing of generalized depth-3 arithmetic circuits with bounded top fan-in. In 2008 23rd Annual IEEE Conference on Computational Complexity, pages 280-291. IEEE, 2008. Google Scholar
  41. Zohar Shay Karnin and Amir Shpilka. Reconstruction of generalized depth-3 arithmetic circuits with bounded top fan-in. In Proceedings of the 24th Annual IEEE Conference on Computational Complexity, CCC 2009, Paris, France, 15-18 July 2009, pages 274-285. IEEE Computer Society, 2009. URL: https://doi.org/10.1109/CCC.2009.18.
  42. Neeraj Kayal. Affine projections of polynomials. In Proceedings of the forty-fourth annual ACM symposium on Theory of computing, pages 643-662, 2012. Google Scholar
  43. Neeraj Kayal, Vineet Nair, and Chandan Saha. Average-case linear matrix factorization and reconstruction of low width algebraic branching programs. Computational Complexity, 28(4):749-828, 2019. URL: https://doi.org/10.1007/s00037-019-00189-0.
  44. Neeraj Kayal, Vineet Nair, Chandan Saha, and Sébastien Tavenas. Reconstruction of full rank algebraic branching programs. ACM Transactions on Computation Theory (TOCT), 11(1):1-56, 2018. Google Scholar
  45. 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. Full version at https://eccc.weizmann.ac.il/report/2018/191. URL: https://doi.org/10.1145/3313276.3316360.
  46. Neeraj Kayal, Chandan Saha, and Sébastien Tavenas. An almost cubic lower bound for depth three arithmetic circuits. In Ioannis Chatzigiannakis, Michael Mitzenmacher, Yuval Rabani, and Davide Sangiorgi, editors, 43rd International Colloquium on Automata, Languages, and Programming, ICALP 2016, July 11-15, 2016, Rome, Italy, volume 55 of LIPIcs, pages 33:1-33:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2016. URL: https://doi.org/10.4230/LIPIcs.ICALP.2016.33.
  47. Adam R. Klivans and Amir Shpilka. Learning restricted models of arithmetic circuits. Theory of Computing, 2(10):185-206, 2006. URL: https://doi.org/10.4086/toc.2006.v002a010.
  48. Adam R Klivans and Daniel Spielman. Randomness efficient identity testing of multivariate polynomials. In Proceedings of the thirty-third annual ACM symposium on Theory of computing, pages 216-223, 2001. Google Scholar
  49. Mrinal Kumar. On the power of border of depth-3 arithmetic circuits. ACM Trans. Comput. Theory, 12(1):5:1-5:8, 2020. URL: https://doi.org/10.1145/3371506.
  50. Mrinal Kumar and Ramprasad Saptharishi. Hardness-Randomness tradeoffs for algebraic computation. Bull. EATCS, 129, 2019. URL: http://bulletin.eatcs.org/index.php/beatcs/article/view/591/599.
  51. Joseph M. Landsberg. Geometry and Complexity Theory. Cambridge Studies in Advanced Mathematics. Cambridge University Press, 2017. URL: https://doi.org/10.1017/9781108183192.
  52. Thomas Lehmkuhl and Thomas Lickteig. On the order of approximation in approximative triadic decompositions of tensors. Theor. Comput. Sci., 66(1):1-14, 1989. URL: https://doi.org/10.1016/0304-3975(89)90141-2.
  53. Dori Medini and Amir Shpilka. Hitting sets and reconstruction for dense orbits in vpdollar_edollar and dollarbackslashsigmabackslashpibackslashsigmadollar circuits. Electron. Colloquium Comput. Complex., 28:14, 2021. URL: https://eccc.weizmann.ac.il/report/2021/014.
  54. Daniel Minahan and Ilya Volkovich. Complete derandomization of identity testing and reconstruction of read-once formulas. ACM Transactions on Computation Theory (TOCT), 10(3):1-11, 2018. Google Scholar
  55. Ketan Mulmuley and Milind A. Sohoni. Geometric complexity theory I: an approach to the P vs. NP and related problems. SIAM J. Comput., 31(2):496-526, 2001. URL: https://doi.org/10.1137/S009753970038715X.
  56. Ketan Mulmuley and Milind A. Sohoni. Geometric complexity theory II: towards explicit obstructions for embeddings among class varieties. SIAM J. Comput., 38(3):1175-1206, 2008. URL: https://doi.org/10.1137/080718115.
  57. Ran Raz. Elusive functions and lower bounds for arithmetic circuits. Theory of Computing, 6(1):135-177, 2010. URL: https://doi.org/10.4086/toc.2010.v006a007.
  58. Ran Raz and Amir Shpilka. Deterministic polynomial identity testing in non-commutative models. Computational Complexity, 14(1):1-19, 2005. URL: https://doi.org/10.1007/s00037-005-0188-8.
  59. Chandan Saha, Ramprasad Saptharishi, and Nitin Saxena. The power of depth 2 circuits over algebras. In Ravi Kannan and K. Narayan Kumar, editors, IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2009, December 15-17, 2009, IIT Kanpur, India, volume 4 of LIPIcs, pages 371-382. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2009. URL: https://doi.org/10.4230/LIPIcs.FSTTCS.2009.2333.
  60. Chandan Saha and Bhargav Thankey. Hitting sets for orbits of circuit classes and polynomial families. Electron. Colloquium Comput. Complex., 28:15, 2021. URL: https://eccc.weizmann.ac.il/report/2021/015.
  61. Ramprasad Saptharishi. A survey of lower bounds in arithmetic circuit complexity. Github survey, 2015. Available at URL: https://github.com/dasarpmar/lowerbounds-survey.
  62. Nitin Saxena. Progress on polynomial identity testing. Bull. EATCS, 99:49-79, 2009. Google Scholar
  63. Nitin Saxena. Progress on Polynomial Identity Testing-II, volume 26 of Progress in Computer Science and Applied Logic, pages 131-146. Birkhäuser Basel, 2014. URL: http://arxiv.org/abs/1401.0976.
  64. Nitin Saxena and C. Seshadhri. Blackbox Identity Testing for Bounded Top-Fanin Depth-3 Circuits: The Field Doesn't Matter. SIAM J. Comput., 41(5):1285-1298, 2012. URL: https://doi.org/10.1137/10848232.
  65. Amir Shpilka. Interpolation of depth-3 arithmetic circuits with two multiplication gates. SIAM Journal on Computing, 38(6):2130-2161, 2009. Google Scholar
  66. Amir Shpilka and Ilya Volkovich. Read-once polynomial identity testing. Computational Complexity, 24(3):477-532, 2015. Google Scholar
  67. Amir Shpilka and Amir Yehudayoff. Arithmetic circuits: A survey of recent results and open questions. Found. Trends Theor. Comput. Sci., 5(3-4):207-388, 2010. URL: https://doi.org/10.1561/0400000039.
  68. Gaurav Sinha. Reconstruction of real depth-3 circuits with top fan-in 2. In Ran Raz, editor, 31st Conference on Computational Complexity, CCC 2016, May 29 to June 1, 2016, Tokyo, Japan, volume 50 of LIPIcs, pages 31:1-31:53. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2016. URL: https://doi.org/10.4230/LIPIcs.CCC.2016.31.
  69. Ola Svensson and Jakub Tarnawski. The matching problem in general graphs is in quasi-nc. In Chris Umans, editor, 58th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2017, Berkeley, CA, USA, October 15-17, 2017, pages 696-707. IEEE Computer Society, 2017. URL: https://doi.org/10.1109/FOCS.2017.70.
  70. Joseph Swernofsky. Tensor rank is hard to approximate. In Eric Blais, Klaus Jansen, José D. P. Rolim, and David Steurer, editors, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2018, August 20-22, 2018 - Princeton, NJ, USA, volume 116 of LIPIcs, pages 26:1-26:9. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018. URL: https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2018.26.
  71. 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. URL: https://doi.org/10.1137/0212043.
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