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Documents authored by Shastri, Pratik


Document
Lower Bounds for Noncommutative Circuits with Low Syntactic Degree

Authors: Pratik Shastri

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)


Abstract
Proving lower bounds on the size of noncommutative arithmetic circuits is an important problem in arithmetic circuit complexity. For explicit n variate polynomials of degree Θ(n), the best known general bound is Ω(n log n) [Strassen, 1973; Walter Baur and Volker Strassen, 1983]. Recent work of Chatterjee and Hrubeš [Chatterjee and Hrubeš, 2023] has provided stronger (Ω(n²)) bounds for the restricted class of homogeneous circuits. The present paper extends these results to a broader class of circuits by using syntactic degree as a complexity measure. The syntactic degree of a circuit is a well known parameter which measures the extent to which high degree computation is used in the circuit. A homogeneous circuit computing a degree d polynomial can be assumed, without loss of generality, to have syntactic degree exactly equal to d [Fournier et al., 2024]. We generalize this by considering circuits that are not necessarily homogeneous but have low syntactic degree. Specifically, for an explicit n variate, degree n polynomial f we show that any circuit with syntactic degree O(n) computing f must have size Ω(n^{1+c}) for some constant c > 0. We also show that any circuit with syntactic degree o(nlog n) computing the same f must have size ω(nlog n). We further analyze the circuit size required to compute f based on the number of distinct syntactic degrees appearing in the circuit. Our analysis yields an ω(nlog n) size lower bound for all but a narrow parameter regime where an improved bound is not obtained. Finally, we observe that low syntactic degree circuits are more powerful than homogeneous circuits in a fine grained sense: there exists an n variate, degree Θ(n) polynomial that has a circuit of size O(nlog ²n) and syntactic degree O(n) but any homogeneous circuit computing it requires size Ω(n²).

Cite as

Pratik Shastri. Lower Bounds for Noncommutative Circuits with Low Syntactic Degree. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 115:1-115:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{shastri:LIPIcs.ITCS.2026.115,
  author =	{Shastri, Pratik},
  title =	{{Lower Bounds for Noncommutative Circuits with Low Syntactic Degree}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{115:1--115:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.115},
  URN =		{urn:nbn:de:0030-drops-254028},
  doi =		{10.4230/LIPIcs.ITCS.2026.115},
  annote =	{Keywords: Noncommutative Circuits, Lower Bounds, Circuit Complexity, Algebraic Complexity}
}
Document
On the Hardness of Order Finding and Equivalence Testing for ROABPs

Authors: C. Ramya and Pratik Shastri

Published in: LIPIcs, Volume 360, 45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025)


Abstract
The complexity of representing a polynomial by a Read-Once Oblivious Algebraic Branching Program (ROABP) is highly dependent on the chosen variable ordering. Bhargava et al. [Bhargava et al., 2024] prove that finding the optimal ordering is NP-hard, and provide some evidence (based on the Small Set Expansion hypothesis) that it is also hard to approximate the optimal ROABP width. In another work, Baraskar et al. [Baraskar et al., 2024] show that it is NP-hard to test whether a polynomial is in the GL_n orbit of a polynomial of sparsity at most s. Building upon these works, we show the following results: first, we prove that approximating the minimum ROABP width up to any constant factor is NP-hard, when the input is presented as a circuit. This removes the reliance on stronger conjectures in the previous work [Bhargava et al., 2024]. Second, we show that testing if an input polynomial given in the sparse representation is in the affine GL_n orbit of a width-w ROABP is NP-hard. Furthermore, we show that over fields of characteristic 0, the problem is NP-hard even when the input polynomial is homogeneous. This provides the first NP-hardness results for membership testing for a dense subclass of polynomial sized algebraic branching programs (VBP). Finally, we locate the source of hardness for the order finding problem at the lowest possible non-trivial degree, proving that the problem is NP-hard even for quadratic forms.

Cite as

C. Ramya and Pratik Shastri. On the Hardness of Order Finding and Equivalence Testing for ROABPs. In 45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 360, pp. 49:1-49:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{ramya_et_al:LIPIcs.FSTTCS.2025.49,
  author =	{Ramya, C. and Shastri, Pratik},
  title =	{{On the Hardness of Order Finding and Equivalence Testing for ROABPs}},
  booktitle =	{45th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2025)},
  pages =	{49:1--49:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-406-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{360},
  editor =	{Aiswarya, C. and Mehta, Ruta and Roy, Subhajit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2025.49},
  URN =		{urn:nbn:de:0030-drops-251296},
  doi =		{10.4230/LIPIcs.FSTTCS.2025.49},
  annote =	{Keywords: ROABP, Order Finding, Equivalence Testing, NP-hardness, Hardness of Approximation}
}
Document
RANDOM
Efficient Polynomial Identity Testing over Nonassociative Algebras

Authors: Partha Mukhopadhyay, C. Ramya, and Pratik Shastri

Published in: LIPIcs, Volume 353, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)


Abstract
We design the first efficient polynomial identity testing algorithms over the nonassociative polynomial algebra. In particular, multiplication among the formal variables is commutative but it is not associative. This complements the strong lower bound results obtained over this algebra by Hrubeš, Yehudayoff, and Wigderson [Pavel Hrubes et al., 2010] and Fijalkow, Lagarde, Ohlmann, and Serre [Fijalkow et al., 2021] from the identity testing perspective. Our main results are the following: - We construct nonassociative algebras (both commutative and noncommutative) which have no low degree identities. As a result, we obtain the first Amitsur-Levitzki type theorems [A. S. Amitsur and J. Levitzki, 1950] over nonassociative polynomial algebras. As a direct consequence, we obtain randomized polynomial-time black-box PIT algorithms for nonassociative polynomials which allow evaluation over such algebras. - On the derandomization side, we give a deterministic polynomial-time identity testing algorithm for nonassociative polynomials given by arithmetic circuits in the white-box setting. Previously, such an algorithm was known with the additional restriction of noncommutativity [Vikraman Arvind et al., 2017]. - In the black-box setting, we construct a hitting set of quasipolynomial-size for nonassociative polynomials computed by arithmetic circuits of small depth. Understanding the black-box complexity of identity testing, even in the randomized setting, was open prior to our work.

Cite as

Partha Mukhopadhyay, C. Ramya, and Pratik Shastri. Efficient Polynomial Identity Testing over Nonassociative Algebras. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 353, pp. 56:1-56:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{mukhopadhyay_et_al:LIPIcs.APPROX/RANDOM.2025.56,
  author =	{Mukhopadhyay, Partha and C. Ramya and Shastri, Pratik},
  title =	{{Efficient Polynomial Identity Testing over Nonassociative Algebras}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)},
  pages =	{56:1--56:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-397-3},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{353},
  editor =	{Ene, Alina and Chattopadhyay, Eshan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2025.56},
  URN =		{urn:nbn:de:0030-drops-244224},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2025.56},
  annote =	{Keywords: Polynomial identity testing, nonassociative algebra, arithmetic circuits, black-box algorithms, white-box algorithms}
}
Document
Lower Bounds for Planar Arithmetic Circuits

Authors: C. Ramya and Pratik Shastri

Published in: LIPIcs, Volume 287, 15th Innovations in Theoretical Computer Science Conference (ITCS 2024)


Abstract
Arithmetic circuits are a natural well-studied model for computing multivariate polynomials over a field. In this paper, we study planar arithmetic circuits. These are circuits whose underlying graph is planar. In particular, we prove an Ω(nlog n) lower bound on the size of planar arithmetic circuits computing explicit bilinear forms on 2n variables. As a consequence, we get an Ω(nlog n) lower bound on the size of arithmetic formulas and planar algebraic branching programs computing explicit bilinear forms. This is the first such lower bound on the formula complexity of an explicit bilinear form. In the case of read-once planar circuits, we show Ω(n²) size lower bounds for computing explicit bilinear forms. Furthermore, we prove fine separations between the various planar models of computations mentioned above. In addition to this, we look at multi-output planar circuits and show Ω(n^{4/3}) size lower bound for computing an explicit linear transformation on n-variables. For a suitable definition of multi-output formulas, we extend the above result to get an Ω(n²/log n) size lower bound. As a consequence, we demonstrate that there exists an n-variate polynomial computable by n^{1 + o(1)}-sized formulas such that any multi-output planar circuit (resp., multi-output formula) simultaneously computing all its first-order partial derivatives requires size Ω(n^{4/3}) (resp., Ω(n²/log n)). This shows that a statement analogous to that of Baur, Strassen[Walter Baur and Volker Strassen, 1983] does not hold in the case of planar circuits and formulas.

Cite as

C. Ramya and Pratik Shastri. Lower Bounds for Planar Arithmetic Circuits. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 91:1-91:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{ramya_et_al:LIPIcs.ITCS.2024.91,
  author =	{Ramya, C. and Shastri, Pratik},
  title =	{{Lower Bounds for Planar Arithmetic Circuits}},
  booktitle =	{15th Innovations in Theoretical Computer Science Conference (ITCS 2024)},
  pages =	{91:1--91:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-309-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{287},
  editor =	{Guruswami, Venkatesan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2024.91},
  URN =		{urn:nbn:de:0030-drops-196199},
  doi =		{10.4230/LIPIcs.ITCS.2024.91},
  annote =	{Keywords: Arithmetic circuit complexity, Planar circuits, Bilinear forms}
}
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