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Documents authored by Lagarde, Guillaume

Document
DOI: 10.4230/LIPIcs.STACS.2020.24
Lower Bounds for Arithmetic Circuits via the Hankel Matrix

Authors: Nathanaël Fijalkow, Guillaume Lagarde, Pierre Ohlmann, and Olivier Serre

Published in: LIPIcs, Volume 154, 37th International Symposium on Theoretical Aspects of Computer Science (STACS 2020)

Abstract
We study the complexity of representing polynomials by arithmetic circuits in both the commutative and the non-commutative settings. To analyse circuits we count their number of parse trees, which describe the non-associative computations realised by the circuit. In the non-commutative setting a circuit computing a polynomial of degree d has at most 2^{O(d)} parse trees. Previous superpolynomial lower bounds were known for circuits with up to 2^{d^{1/3-ε}} parse trees, for any ε > 0. Our main result is to reduce the gap by showing a superpolynomial lower bound for circuits with just a small defect in the exponent for the total number of parse trees, that is 2^{d^{1 - ε}}, for any ε > 0. In the commutative setting a circuit computing a polynomial of degree d has at most 2^{O(d log d)} parse trees. We show a superpolynomial lower bound for circuits with up to 2^{d^{1/3 - ε}} parse trees, for any ε > 0. When d is polylogarithmic in n, we push this further to up to 2^{d^{1 - ε}} parse trees. While these two main results hold in the associative setting, our approach goes through a precise understanding of the more restricted setting where multiplication is not associative, meaning that we distinguish the polynomials (xy)z and x(yz). Our first and main conceptual result is a characterization result: we show that the size of the smallest circuit computing a given non-associative polynomial is exactly the rank of a matrix constructed from the polynomial and called the Hankel matrix. This result applies to the class of all circuits in both commutative and non-commutative settings, and can be seen as an extension of the seminal result of Nisan giving a similar characterization for non-commutative algebraic branching programs. Our key technical contribution is to provide generic lower bound theorems based on analyzing and decomposing the Hankel matrix, from which we derive the results mentioned above. The study of the Hankel matrix also provides a unifying approach for proving lower bounds for polynomials in the (classical) associative setting. We demonstrate this by giving alternative proofs of recent lower bounds as corollaries of our generic lower bound results.
Cite as

Nathanaël Fijalkow, Guillaume Lagarde, Pierre Ohlmann, and Olivier Serre. Lower Bounds for Arithmetic Circuits via the Hankel Matrix. In 37th International Symposium on Theoretical Aspects of Computer Science (STACS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 154, pp. 24:1-24:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{fijalkow_et_al:LIPIcs.STACS.2020.24,
  author =	{Fijalkow, Nathana\"{e}l and Lagarde, Guillaume and Ohlmann, Pierre and Serre, Olivier},
  title =	{{Lower Bounds for Arithmetic Circuits via the Hankel Matrix}},
  booktitle =	{37th International Symposium on Theoretical Aspects of Computer Science (STACS 2020)},
  pages =	{24:1--24:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-140-5},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{154},
  editor =	{Paul, Christophe and Bl\"{a}ser, Markus},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2020.24},
  URN =		{urn:nbn:de:0030-drops-118859},
  doi =		{10.4230/LIPIcs.STACS.2020.24},
  annote =	{Keywords: Arithmetic Circuit Complexity, Lower Bounds, Parse Trees, Hankel Matrix}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2020.72
Trade-Offs Between Size and Degree in Polynomial Calculus

Authors: Guillaume Lagarde, Jakob Nordström, Dmitry Sokolov, and Joseph Swernofsky

Published in: LIPIcs, Volume 151, 11th Innovations in Theoretical Computer Science Conference (ITCS 2020)

Abstract
Building on [Clegg et al. '96], [Impagliazzo et al. '99] established that if an unsatisfiable k-CNF formula over n variables has a refutation of size S in the polynomial calculus resolution proof system, then this formula also has a refutation of degree k + O(√(n log S)). The proof of this works by converting a small-size refutation into a small-degree one, but at the expense of increasing the proof size exponentially. This raises the question of whether it is possible to achieve both small size and small degree in the same refutation, or whether the exponential blow-up is inherent. Using and extending ideas from [Thapen '16], who studied the analogous question for the resolution proof system, we prove that a strong size-degree trade-off is necessary.
Cite as

Guillaume Lagarde, Jakob Nordström, Dmitry Sokolov, and Joseph Swernofsky. Trade-Offs Between Size and Degree in Polynomial Calculus. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 151, pp. 72:1-72:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{lagarde_et_al:LIPIcs.ITCS.2020.72,
  author =	{Lagarde, Guillaume and Nordstr\"{o}m, Jakob and Sokolov, Dmitry and Swernofsky, Joseph},
  title =	{{Trade-Offs Between Size and Degree in Polynomial Calculus}},
  booktitle =	{11th Innovations in Theoretical Computer Science Conference (ITCS 2020)},
  pages =	{72:1--72:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-134-4},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{151},
  editor =	{Vidick, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2020.72},
  URN =		{urn:nbn:de:0030-drops-117573},
  doi =		{10.4230/LIPIcs.ITCS.2020.72},
  annote =	{Keywords: proof complexity, polynomial calculus, polynomial calculus resolution, PCR, size-degree trade-off, resolution, colored polynomial local search}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2017.41
Lower Bounds and PIT for Non-Commutative Arithmetic Circuits with Restricted Parse Trees

Authors: Guillaume Lagarde, Nutan Limaye, and Srikanth Srinivasan

Published in: LIPIcs, Volume 83, 42nd International Symposium on Mathematical Foundations of Computer Science (MFCS 2017)

Abstract
We investigate the power of Non-commutative Arithmetic Circuits, which compute polynomials over the free non-commutative polynomial ring F<x_1,...,x_N>, where variables do not commute. We consider circuits that are restricted in the ways in which they can compute monomials: this can be seen as restricting the families of parse trees that appear in the circuit. Such restrictions capture essentially all non-commutative circuit models for which lower bounds are known. We prove several results about such circuits. - We show explicit exponential lower bounds for circuits with up to an exponential number of parse trees, strengthening the work of Lagarde, Malod, and Perifel (ECCC 2016), who prove such a result for Unique Parse Tree (UPT) circuits which have a single parse tree. - We show explicit exponential lower bounds for circuits whose parse trees are rotations of a single tree. This simultaneously generalizes recent lower bounds of Limaye, Malod, and Srinivasan (Theory of Computing 2016) and the above lower bounds of Lagarde et al., which are known to be incomparable. - We make progress on a question of Nisan (STOC 1991) regarding separating the power of Algebraic Branching Programs (ABPs) and Formulas in the non-commutative setting by showing a tight lower bound of n^{Omega(log d)} for any UPT formula computing the product of d n*n matrices. When d <= log n, we can also prove superpolynomial lower bounds for formulas with up to 2^{o(d)} many parse trees (for computing the same polynomial). Improving this bound to allow for 2^{O(d)} trees would yield an unconditional separation between ABPs and Formulas. - We give deterministic white-box PIT algorithms for UPT circuits over any field (strengthening a result of Lagarde et al. (2016)) and also for sums of a constant number of UPT circuits with different parse trees.
Cite as

Guillaume Lagarde, Nutan Limaye, and Srikanth Srinivasan. Lower Bounds and PIT for Non-Commutative Arithmetic Circuits with Restricted Parse Trees. In 42nd International Symposium on Mathematical Foundations of Computer Science (MFCS 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 83, pp. 41:1-41:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{lagarde_et_al:LIPIcs.MFCS.2017.41,
  author =	{Lagarde, Guillaume and Limaye, Nutan and Srinivasan, Srikanth},
  title =	{{Lower Bounds and PIT for Non-Commutative Arithmetic Circuits with Restricted Parse Trees}},
  booktitle =	{42nd International Symposium on Mathematical Foundations of Computer Science (MFCS 2017)},
  pages =	{41:1--41:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-046-0},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{83},
  editor =	{Larsen, Kim G. and Bodlaender, Hans L. and Raskin, Jean-Francois},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2017.41},
  URN =		{urn:nbn:de:0030-drops-81094},
  doi =		{10.4230/LIPIcs.MFCS.2017.41},
  annote =	{Keywords: Non-commutative Arithemetic circuits, Partial derivatives, restrictions}
}
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