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Track A: Algorithms, Complexity and Games

DOI: 10.4230/LIPIcs.ICALP.2024.16

NP-Hardness of Testing Equivalence to Sparse Polynomials and to Constant-Support Polynomials

Authors: Omkar Baraskar, Agrim Dewan, Chandan Saha, and Pulkit Sinha

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)

Abstract

An s-sparse polynomial has at most s monomials with nonzero coefficients. The Equivalence Testing problem for sparse polynomials (ETsparse) asks to decide if a given polynomial f is equivalent to (i.e., in the orbit of) some s-sparse polynomial. In other words, given f ∈ 𝔽[𝐱] and s ∈ ℕ, ETsparse asks to check if there exist A ∈ GL(|𝐱|, 𝔽) and 𝐛 ∈ 𝔽^|𝐱| such that f(A𝐱 + 𝐛) is s-sparse. We show that ETsparse is NP-hard over any field 𝔽, if f is given in the sparse representation, i.e., as a list of nonzero coefficients and exponent vectors. This answers a question posed by Gupta, Saha and Thankey (SODA 2023) and also, more explicitly, by Baraskar, Dewan and Saha (STACS 2024). The result implies that the Minimum Circuit Size Problem (MCSP) is NP-hard for a dense subclass of depth-3 arithmetic circuits if the input is given in sparse representation. We also show that approximating the smallest s₀ such that a given s-sparse polynomial f is in the orbit of some s₀-sparse polynomial to within a factor of s^{1/3 - ε} is NP-hard for any ε > 0; observe that s-factor approximation is trivial as the input is s-sparse. Finally, we show that for any constant σ ≥ 6, checking if a polynomial (given in sparse representation) is in the orbit of some support-σ polynomial is NP-hard. Support of a polynomial f is the maximum number of variables present in any monomial of f. These results are obtained via direct reductions from the 3-SAT problem.

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Omkar Baraskar, Agrim Dewan, Chandan Saha, and Pulkit Sinha. NP-Hardness of Testing Equivalence to Sparse Polynomials and to Constant-Support Polynomials. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 16:1-16:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{baraskar_et_al:LIPIcs.ICALP.2024.16,
  author =	{Baraskar, Omkar and Dewan, Agrim and Saha, Chandan and Sinha, Pulkit},
  title =	{{NP-Hardness of Testing Equivalence to Sparse Polynomials and to Constant-Support Polynomials}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{16:1--16:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.16},
  URN =		{urn:nbn:de:0030-drops-201598},
  doi =		{10.4230/LIPIcs.ICALP.2024.16},
  annote =	{Keywords: Equivalence testing, MCSP, sparse polynomials, 3SAT}
}

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DOI: 10.4230/LIPIcs.STACS.2024.9

Testing Equivalence to Design Polynomials

Authors: Omkar Baraskar, Agrim Dewan, and Chandan Saha

Published in: LIPIcs, Volume 289, 41st International Symposium on Theoretical Aspects of Computer Science (STACS 2024)

Abstract

An n-variate polynomial g of degree d is a (n,d,t) design polynomial if the degree of the gcd of every pair of monomials of g is at most t-1. The power symmetric polynomial PSym_{n,d} : = ∑_{i = 1}ⁿ x^d_i and the sum-product polynomial SP_{s,d} : = ∑_{i = 1}^{s}∏_{j = 1}^{d} x_{i,j} are instances of design polynomials for t = 1. Another example is the Nisan-Wigderson design polynomial NW, which has been used extensively to prove various arithmetic circuit lower bounds. Given black-box access to an n-variate, degree-d polynomial f(𝐱) ∈ 𝔽[𝐱], how fast can we check if there exist an A ∈ GL(n, 𝔽) and a 𝐛 ∈ 𝔽ⁿ such that f(A𝐱+𝐛) is a (n,d,t) design polynomial? We call this problem "testing equivalence to design polynomials", or alternatively, "equivalence testing for design polynomials". In this work, we present a randomized algorithm that finds (A, 𝐛) such that f(A𝐱+𝐛) is a (n,d,t) design polynomial, if such A and 𝐛 exist, provided t ≤ d/3. The algorithm runs in (nd)^O(t) time and works over any sufficiently large 𝔽 of characteristic 0 or > d. As applications of this test, we show two results - one is structural and the other is algorithmic. The structural result establishes a polynomial-time equivalence between the graph isomorphism problem and the polynomial equivalence problem for design polynomials. The algorithmic result implies that Patarin’s scheme (EUROCRYPT 1996) can be broken in quasi-polynomial time if a random sparse polynomial is used in the key generation phase. We also give an efficient learning algorithm for n-variate random affine projections of multilinear degree-d design polynomials, provided n ≥ d⁴. If one obtains an analogous result under the weaker assumption "n ≥ d^ε, for any ε > 0", then the NW family is not VNP-complete unless there is a VNP-complete family whose random affine projections are learnable. It is not known if random affine projections of the permanent are learnable. The above algorithms are obtained by using the vector space decomposition framework, introduced by Kayal and Saha (STOC 2019) and Garg, Kayal and Saha (FOCS 2020), for learning non-degenerate arithmetic circuits. A key technical difference between the analysis in the papers by Garg, Kayal and Saha (FOCS 2020) and Bhargava, Garg, Kayal and Saha (RANDOM 2022) and the analysis here is that a certain adjoint algebra, which turned out to be trivial (i.e., diagonalizable) in prior works, is non-trivial in our case. However, we show that the adjoint arising here is triangularizable which then helps in carrying out the vector space decomposition step.

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Omkar Baraskar, Agrim Dewan, and Chandan Saha. Testing Equivalence to Design Polynomials. In 41st International Symposium on Theoretical Aspects of Computer Science (STACS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 289, pp. 9:1-9:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{baraskar_et_al:LIPIcs.STACS.2024.9,
  author =	{Baraskar, Omkar and Dewan, Agrim and Saha, Chandan},
  title =	{{Testing Equivalence to Design Polynomials}},
  booktitle =	{41st International Symposium on Theoretical Aspects of Computer Science (STACS 2024)},
  pages =	{9:1--9:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-311-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{289},
  editor =	{Beyersdorff, Olaf and Kant\'{e}, Mamadou Moustapha and Kupferman, Orna and Lokshtanov, Daniel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2024.9},
  URN =		{urn:nbn:de:0030-drops-197193},
  doi =		{10.4230/LIPIcs.STACS.2024.9},
  annote =	{Keywords: Polynomial equivalence, design polynomials, graph isomorphism, vector space decomposition}
}

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Documents authored by Baraskar, Omkar

NP-Hardness of Testing Equivalence to Sparse Polynomials and to Constant-Support Polynomials

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Testing Equivalence to Design Polynomials

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