Bhargav Thankey

dblp:259/4859 · DBLP profile ↗
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6ranked-venue papers
0as first author
5since 2021 · last 2026
0000-0002-5078-892XORCID · corroborated

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Theory of computation · 5 · 4 since 2021Security and privacy · 1 · 1 since 2021
YearPublicationVenuePosition
2026 On the Border Complexity of Sums of ROFs
Pranjal Dutta, Bhargav Thankey
COCOON2
2025 BrakingBase - A Linear Prover, Poly-Logarithmic Verifier, Field Agnostic Polynomial Commitment Scheme
Vineet Nair, Bhargav Thankey
ASIACRYPT (5)3
2023 Low-Depth Arithmetic Circuit Lower Bounds: Bypassing Set-Multilinearization
Prashanth Amireddy, Ankit Garg 0001, Neeraj Kayal, Chandan Saha 0001, Bhargav Thankey
ICALP5
2023 Equivalence Test for Read-Once Arithmetic Formulas
abstract
We study the polynomial equivalence problem for orbits of read-once arithmetic formulas (ROFs). Read- once formulas have received considerable attention in both algebraic and Boolean complexity and have served as a testbed for developing effective tools and techniques for analyzing circuits. Two n-variate polynomials f,g ∈
Nikhil Gupta 0008, Chandan Saha 0001, Bhargav Thankey
SODA3
2021 Hitting Sets for Orbits of Circuit Classes and Polynomial Families
abstract
The orbit of an n-variate polynomial f(𝐱) over a field 𝔽 is the set {f(A𝐱+𝐛) : A ∈ GL(n,𝔽) and 𝐛 ∈ 𝔽ⁿ}. In this paper, we initiate the study of explicit hitting sets for the orbits of polynomials computable by several natural and well-studied circuit classes and polynomial families. In particular, we give quasi-polynomial time hitting sets for the orbits of: 1) Low-individual-degree polynomials computable by commutative ROABPs. This implies quasi-polynomial time hitting sets for the orbits of the elementary symmetric polynomials. 2) Multilinear polynomials computable by constant-width ROABPs. This implies a quasi-polynomial time hitting set for the orbits of the family {IMM_{3,d}}_{d ∈ ℕ}, which is complete for arithmetic formulas. 3) Polynomials computable by constant-depth, constant-occur formulas. This implies quasi-polynomial time hitting sets for the orbits of multilinear depth-4 circuits with constant top fan-in, and also polynomial-time hitting sets for the orbits of the power symmetric and the sum-product polynomials. 4) Polynomials computable by occur-once formulas.
Chandan Saha 0001, Bhargav Thankey
APPROX-RANDOM2
2020 A Super-Quadratic Lower Bound for Depth Four Arithmetic Circuits
abstract
We show an Ω̃(n^2.5) lower bound for general depth four arithmetic circuits computing an explicit n-variate degree-Θ(n) multilinear polynomial over any field of characteristic zero. To our knowledge, and as stated in the survey [Amir Shpilka and Amir Yehudayoff, 2010], no super-quadratic lower bound was known for depth four circuits over fields of characteristic ≠ 2 before this work. The previous best lower bound is Ω̃(n^1.5) [Abhijat Sharma, 2017], which is a slight quantitative improvement over the roughly Ω(n^1.33) bound obtained by invoking the super-linear lower bound for constant depth circuits in [Ran Raz, 2010; Victor Shoup and Roman Smolensky, 1997]. Our lower bound proof follows the approach of the almost cubic lower bound for depth three circuits in [Neeraj Kayal et al., 2016] by replacing the shifted partials measure with a suitable variant of the projected shifted partials measure, but it differs from [Neeraj Kayal et al., 2016]’s proof at a crucial step - namely, the way "heavy" product gates are handled. Loosely speaking, a heavy product gate has a relatively high fan-in. Product gates of a depth three circuit compute products of affine forms, and so, it is easy to prune Θ(n) many heavy product gates by projecting the circuit to a low-dimensional affine subspace [Neeraj Kayal et al., 2016; Amir Shpilka and Avi Wigderson, 2001]. However, in a depth four circuit, the second (from the top) layer of product gates compute products of polynomials having arbitrary degree, and hence it was not clear how to prune such heavy product gates from the circuit. We show that heavy product gates can also be eliminated from a depth four circuit by projecting the circuit to a low-dimensional affine subspace, unless the heavy gates together account for Ω̃(n^2.5) size. This part of our argument is inspired by a well-known greedy approximation algorithm for the weighted set-cover problem.
Nikhil Gupta 0008, Chandan Saha 0001, Bhargav Thankey
CCC3