# Search Results

### Documents authored by Sinhababu, Amit

Document
##### Arithmetic Circuit Complexity of Division and Truncation

Authors: Pranjal Dutta, Gorav Jindal, Anurag Pandey, and Amit Sinhababu

Published in: LIPIcs, Volume 200, 36th Computational Complexity Conference (CCC 2021)

##### Abstract
Given polynomials f,g,h ∈ 𝔽[x₁,…,x_n] such that f = g/h, where both g and h are computable by arithmetic circuits of size s, we show that f can be computed by a circuit of size poly(s,deg(h)). This solves a special case of division elimination for high-degree circuits (Kaltofen'87 & WACT'16). The result is an exponential improvement over Strassen’s classic result (Strassen'73) when deg(h) is poly(s) and deg(f) is exp(s), since the latter gives an upper bound of poly(s, deg(f)). Further, we show that any univariate polynomial family (f_d)_d, defined by the initial segment of the power series expansion of rational function g_d(x)/h_d(x) up to degree d (i.e. f_d = g_d/h_d od x^{d+1}), where circuit size of g is s_d and degree of g_d is at most d, can be computed by a circuit of size poly(s_d,deg(h_d),log d). We also show a hardness result when the degrees of the rational functions are high (i.e. Ω (d)), assuming hardness of the integer factorization problem. Finally, we extend this conditional hardness to simple algebraic functions as well, and show that for every prime p, there is an integral algebraic power series with its minimal polynomial satisfying a degree p polynomial equation, such that its initial segment is hard to compute unless integer factoring is easy, or a multiple of n! is easy to compute. Both, integer factoring and computation of multiple of n!, are believed to be notoriously hard. In contrast, we show examples of transcendental power series whose initial segments are easy to compute.

##### Cite as

Pranjal Dutta, Gorav Jindal, Anurag Pandey, and Amit Sinhababu. Arithmetic Circuit Complexity of Division and Truncation. In 36th Computational Complexity Conference (CCC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 200, pp. 25:1-25:36, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

```@InProceedings{dutta_et_al:LIPIcs.CCC.2021.25,
author =	{Dutta, Pranjal and Jindal, Gorav and Pandey, Anurag and Sinhababu, Amit},
title =	{{Arithmetic Circuit Complexity of Division and Truncation}},
booktitle =	{36th Computational Complexity Conference (CCC 2021)},
pages =	{25:1--25:36},
series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN =	{978-3-95977-193-1},
ISSN =	{1868-8969},
year =	{2021},
volume =	{200},
editor =	{Kabanets, Valentine},
publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2021.25},
URN =		{urn:nbn:de:0030-drops-142990},
doi =		{10.4230/LIPIcs.CCC.2021.25},
annote =	{Keywords: Arithmetic Circuits, Division, Truncation, Division elimination, Rational function, Algebraic power series, Transcendental power series, Integer factorization}
}```
Document
##### Factorization of Polynomials Given By Arithmetic Branching Programs

Authors: Amit Sinhababu and Thomas Thierauf

Published in: LIPIcs, Volume 169, 35th Computational Complexity Conference (CCC 2020)

##### Abstract
Given a multivariate polynomial computed by an arithmetic branching program (ABP) of size s, we show that all its factors can be computed by arithmetic branching programs of size poly(s). Kaltofen gave a similar result for polynomials computed by arithmetic circuits. The previously known best upper bound for ABP-factors was poly(s^(log s)).

##### Cite as

Amit Sinhababu and Thomas Thierauf. Factorization of Polynomials Given By Arithmetic Branching Programs. In 35th Computational Complexity Conference (CCC 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 169, pp. 33:1-33:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

```@InProceedings{sinhababu_et_al:LIPIcs.CCC.2020.33,
author =	{Sinhababu, Amit and Thierauf, Thomas},
title =	{{Factorization of Polynomials Given By Arithmetic Branching Programs}},
booktitle =	{35th Computational Complexity Conference (CCC 2020)},
pages =	{33:1--33:19},
series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN =	{978-3-95977-156-6},
ISSN =	{1868-8969},
year =	{2020},
volume =	{169},
editor =	{Saraf, Shubhangi},
publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2020.33},
URN =		{urn:nbn:de:0030-drops-125854},
doi =		{10.4230/LIPIcs.CCC.2020.33},
annote =	{Keywords: Arithmetic Branching Program, Multivariate Polynomial Factorization, Hensel Lifting, Newton Iteration, Hardness vs Randomness}
}```
Document
##### Algebraic Dependencies and PSPACE Algorithms in Approximative Complexity

Authors: Zeyu Guo, Nitin Saxena, and Amit Sinhababu

Published in: LIPIcs, Volume 102, 33rd Computational Complexity Conference (CCC 2018)

##### Abstract
Testing whether a set f of polynomials has an algebraic dependence is a basic problem with several applications. The polynomials are given as algebraic circuits. Algebraic independence testing question is wide open over finite fields (Dvir, Gabizon, Wigderson, FOCS'07). Previously, the best complexity known was NP^{#P} (Mittmann, Saxena, Scheiblechner, Trans.AMS'14). In this work we put the problem in AM cap coAM. In particular, dependence testing is unlikely to be NP-hard and joins the league of problems of "intermediate" complexity, eg. graph isomorphism & integer factoring. Our proof method is algebro-geometric- estimating the size of the image/preimage of the polynomial map f over the finite field. A gap in this size is utilized in the AM protocols. Next, we study the open question of testing whether every annihilator of f has zero constant term (Kayal, CCC'09). We give a geometric characterization using Zariski closure of the image of f; introducing a new problem called approximate polynomials satisfiability (APS). We show that APS is NP-hard and, using projective algebraic-geometry ideas, we put APS in PSPACE (prior best was EXPSPACE via Gröbner basis computation). As an unexpected application of this to approximative complexity theory we get- over any field, hitting-sets for overline{VP} can be verified in PSPACE. This solves an open problem posed in (Mulmuley, FOCS'12, J.AMS 2017); greatly mitigating the GCT Chasm (exponentially in terms of space complexity).

##### Cite as

Zeyu Guo, Nitin Saxena, and Amit Sinhababu. Algebraic Dependencies and PSPACE Algorithms in Approximative Complexity. In 33rd Computational Complexity Conference (CCC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 102, pp. 10:1-10:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

```@InProceedings{guo_et_al:LIPIcs.CCC.2018.10,
author =	{Guo, Zeyu and Saxena, Nitin and Sinhababu, Amit},
title =	{{Algebraic Dependencies and PSPACE Algorithms in Approximative Complexity}},
booktitle =	{33rd Computational Complexity Conference (CCC 2018)},
pages =	{10:1--10:21},
series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN =	{978-3-95977-069-9},
ISSN =	{1868-8969},
year =	{2018},
volume =	{102},
editor =	{Servedio, Rocco A.},
publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2018.10},
URN =		{urn:nbn:de:0030-drops-88786},
doi =		{10.4230/LIPIcs.CCC.2018.10},
annote =	{Keywords: algebraic dependence, Jacobian, Arthur-Merlin, approximate polynomial, satisfiability, hitting-set, border VP, finite field, PSPACE, EXPSPACE, GCT Chasm}
}```
Document
##### Algebraic Independence over Positive Characteristic: New Criterion and Applications to Locally Low Algebraic Rank Circuits

Authors: Anurag Pandey, Nitin Saxena, and Amit Sinhababu

Published in: LIPIcs, Volume 58, 41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016)

##### Abstract
The motivation for this work comes from two problems--test algebraic independence of arithmetic circuits over a field of small characteristic, and generalize the structural property of algebraic dependence used by (Kumar, Saraf CCC'16) to arbitrary fields. It is known that in the case of zero, or large characteristic, using a classical criterion based on the Jacobian, we get a randomized poly-time algorithm to test algebraic independence. Over small characteristic, the Jacobian criterion fails and there is no subexponential time algorithm known. This problem could well be conjectured to be in RP, but the current best algorithm puts it in NP^#P (Mittmann, Saxena, Scheiblechner Trans.AMS'14). Currently, even the case of two bivariate circuits over F_2 is open. We come up with a natural generalization of Jacobian criterion, that works over all characteristic. The new criterion is efficient if the underlying inseparable degree is promised to be a constant. This is a modest step towards the open question of fast independence testing, over finite fields, posed in (Dvir, Gabizon, Wigderson FOCS'07). In a set of linearly dependent polynomials, any polynomial can be written as a linear combination of the polynomials forming a basis. The analogous property for algebraic dependence is false, but a property approximately in that spirit is named as ``functional dependence'' in (Kumar, Saraf CCC'16) and proved for zero or large characteristic. We show that functional dependence holds for arbitrary fields, thereby answering the open questions in (Kumar, Saraf CCC'16). Following them we use the functional dependence lemma to prove the first exponential lower bound for locally low algebraic rank circuits for arbitrary fields (a model that strongly generalizes homogeneous depth-4 circuits). We also recover their quasipoly-time hitting-set for such models, for fields of characteristic smaller than the ones known before. Our results show that approximate functional dependence is indeed a more fundamental concept than the Jacobian as it is field independent. We achieve the former by first picking a ``good'' transcendence basis, then translating the circuits by new variables, and finally approximating them by truncating higher degree monomials. We give a tight analysis of the ``degree'' of approximation needed in the criterion. To get the locally low algebraic rank circuit applications we follow the known shifted partial derivative based methods.

##### Cite as

Anurag Pandey, Nitin Saxena, and Amit Sinhababu. Algebraic Independence over Positive Characteristic: New Criterion and Applications to Locally Low Algebraic Rank Circuits. In 41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 58, pp. 74:1-74:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

```@InProceedings{pandey_et_al:LIPIcs.MFCS.2016.74,
author =	{Pandey, Anurag and Saxena, Nitin and Sinhababu, Amit},
title =	{{Algebraic Independence over Positive Characteristic: New Criterion and Applications to Locally Low Algebraic Rank Circuits}},
booktitle =	{41st International Symposium on Mathematical Foundations of Computer Science (MFCS 2016)},
pages =	{74:1--74:15},
series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN =	{978-3-95977-016-3},
ISSN =	{1868-8969},
year =	{2016},
volume =	{58},
editor =	{Faliszewski, Piotr and Muscholl, Anca and Niedermeier, Rolf},
publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2016.74},
URN =		{urn:nbn:de:0030-drops-65057},
doi =		{10.4230/LIPIcs.MFCS.2016.74},
annote =	{Keywords: independence, transcendence, finite field, Hasse-Schmidt, Jacobian, differential, inseparable, circuit, identity testing, lower bound, depth-4, shifte}
}```
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