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Peter Manohar

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

6 papers
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6

FOCS Conference 2025 Conference Paper

A k q/q-2 Lower Bound for Odd Query Locally Decodable Codes from Bipartite Kikuchi Graphs

  • Oliver Janzer
  • Peter Manohar

A code $\mathcal{C}: \{0, 1\}^{k} \rightarrow\{0, 1\}^{n}$ is a q-query locally decodable code (q-LDC) if one can recover any chosen bit $b_{i}$ of the message $b \in\{0, 1\}^{k}$ with good confidence by querying a corrupted string $\tilde{x}$ of the codeword $x=\mathcal{C}(b)$ in at most q coordinates. For 2 queries, the Hadamard code is a 2-LDC of length $n=2^{k}$, and this code is in fact essentially optimal [1], [2]. For $q \geq 3$, there is a large gap in our understanding: the best constructions achieve $n=\exp \left(k^{o(1)}\right)$, while prior to the recent work of [3], the best lower bounds were $n \geq \tilde{\Omega}\left(k^{\frac{q}{q-2}}\right)$ for q even and $n \geq \tilde{\Omega}\left(k^{\frac{q+1}{q-1}}\right)$ for q odd. The recent work of [3] used techniques from semirandom XOR refutation to prove a lower bound of $n \geq \tilde{\Omega}\left(k^{3}\right)$ for q = 3, thus achieving the “ $k^{\frac{q}{q-2}}$ bound” for an odd value of q. However, their proof does not extend to any odd $q \geq 5$. In this paper, we prove a q-LDC lower bound of $n \geq \tilde{\Omega}\left(k^{\frac{q}{q-2}}\right)$ for any odd q. Our key technical idea is the use of an imbalanced bipartite Kikuchi graph, which gives a simpler method to analyze spectral refutations of odd arity XOR without using the standard “Cauchy-Schwarz trick” ― a trick that typically produces random matrices with nontrivially correlated entries and makes the analysis for odd arity XOR significantly more complicated than even arity XOR.

STOC Conference 2024 Conference Paper

An Exponential Lower Bound for Linear 3-Query Locally Correctable Codes

  • Pravesh K. Kothari
  • Peter Manohar

We prove that the blocklength n of a linear 3-query locally correctable code (LCC) L ∶ F k → F n with distance δ must be at least n ≥ 2 Ω((δ 2 k /(|F|−1) 2 ) 1/8 ) . In particular, the blocklength of a linear 3-query LCC with constant distance over any small field grows exponentially with k . This improves on the best prior lower bound of n ≥ Ω( k 3 ), which holds even for the weaker setting of 3-query locally decodable codes (LDCs), and comes close to matching the best-known construction of 3-query LCCs based on binary Reed–Muller codes, which achieve n ≤ 2 O ( k 1/2 ) . Because there is a 3-query LDC with a strictly subexponential blocklength, as a corollary we obtain the first strong separation between q -query LCCs and LDCs for any constant ‍ q ≥ 3. Our proof is based on a new upgrade of the method of spectral refutations via Kikuchi matrices developed in recent works that reduces establishing (non-)existence of combinatorial objects to proving unsatisfiability of associated XOR instances. Our key conceptual idea is to apply this method with XOR instances obtained via long-chain derivations — a structured variant of low-width resolution for XOR formulas from proof complexity.

FOCS Conference 2024 Conference Paper

Exponential Lower Bounds for Smooth 3-LCCs and Sharp Bounds for Designs

  • Pravesh K. Kothari
  • Peter Manohar

We give improved lower bounds for binary 3-query locally correctable codes (3-LCCs) $C: \{\ 0, 1 \}^k \rightarrow \{\ 0, 1 \}^n$. Specifically, we prove: 1) If C is a linear design 3-LCC, then $n \geq 2^{(1 - o(1))\sqrt{k} }$. A design 3-LCC has the additional property that the correcting sets for every codeword bit form a perfect matching, and every pair of codeword bits is queried an equal number of times across all matchings. Our bound is tight up to a factor $\sqrt{8}$ in the exponent of 2, as the best construction of binary 3-LCCs (obtained by taking Reed--Muller codes on F_4 and applying a natural projection map) is a design 3-LCC with $n \leq 2^{\sqrt{8 k}}$. Up to a factor of 8, this resolves the Hamada conjecture on the maximum F_2-codimension of a 4-design. 2) If C is a smooth, non-linear, adaptive 3-LCC with perfect completeness, then, $n \geq 2^{\Omega(k^{1/5})}$. 3) If C is a smooth, non-linear, adaptive 3-LCC with completeness 1 - \eps, then n \geq \Omega(k^{\frac ${1}{2\eps}}). In particular, when $\eps$ is a small constant, this implies a lower bound for general non-linear LCCs that beats the prior best $n \geq \Omega(k^3)$ lower bound of Alrabiah-Guruswami-Kothari-Manohar by a polynomial factor. Our design LCC lower bound is obtained via a fine-grained analysis of the Kikuchi matrix method applied to a variant of the matrix used in the work of Kothari and Manohar (2023). Our lower bounds for non-linear codes are obtained by designing a from-scratch reduction from nonlinear 3-LCCs to a system of “chain XOR equations” — polynomial equations with a similar structure to the long chain derivations that arise in the lower bounds for linear 3-LCCs of Kothari and Manohar.

STOC Conference 2023 Conference Paper

A Near-Cubic Lower Bound for 3-Query Locally Decodable Codes from Semirandom CSP Refutation

  • Omar Alrabiah
  • Venkatesan Guruswami
  • Pravesh K. Kothari
  • Peter Manohar

A code C ∶ {0,1} k → {0,1} n is a q -locally decodable code ( q -LDC) if one can recover any chosen bit b i of the message b ∈ {0,1} k with good confidence by randomly querying the encoding x = C ( b ) on at most q coordinates. Existing constructions of 2-LDCs achieve n = exp( O ( k )), and lower bounds show that this is in fact tight. However, when q = 3, far less is known: the best constructions achieve n = exp( k o (1) ), while the best known results only show a quadratic lower bound n ≥ Ω( k 2 /log( k )) on the blocklength. In this paper, we prove a near-cubic lower bound of n ≥ Ω( k 3 /log 6 ( k )) on the blocklength of 3-query LDCs. This improves on the best known prior works by a polynomial factor in k . Our proof relies on a new connection between LDCs and refuting constraint satisfaction problems with limited randomness. Our quantitative improvement builds on the new techniques for refuting semirandom instances of CSPs and, in particular, relies on bounding the spectral norm of appropriate Kikuchi matrices.

FOCS Conference 2023 Conference Paper

Efficient Algorithms for Semirandom Planted CSPs at the Refutation Threshold

  • Venkatesan Guruswami
  • Jun-Ting Hsieh
  • Pravesh K. Kothari
  • Peter Manohar

We present an efficient algorithm to solve semirandom planted instances of any Boolean constraint satisfaction problem (CSP). The semirandom model is a hybrid between worst case and average case input models, where the input is generated by (1) choosing an arbitrary planted assignment $x^{*}$, (2) choosing an arbitrary clause structure, and (3) choosing literal negations for each clause from an arbitrary distribution “shifted by $x^{*}$” so that $x^{*}$ satisfies each constraint. For an n variable semirandom planted instance of a k-arity CSP, our algorithm runs in polynomial time and outputs an assignment that satisfies all but a $o(1)$-fraction of constraints, provided that the instance has at least $\tilde{O}\left(n^{k / 2}\right)$ constraints. This matches, up to ${\mathrm {polylog}} (n)$ factors, the clause threshold for algorithms that solve fully random planted CSPs [23], as well as algorithms that refute random and semirandom CSPs [1], [4]. Our result shows that despite having worst case clause structure, the randomness in the literal patterns makes semirandom planted CSPs significantly easier than worst case, where analogous results require $O\left(n^{k}\right)$ constraints [7], [26]. Perhaps surprisingly, our algorithm follows a significantly different conceptual framework when compared to the recent resolution of semirandom CSP refutation. This turns out to be inherent and, at a technical level, can be attributed to the need for relative spectral approximation of certain random matrices — reminiscent of the classical spectral sparsification — which ensures that an SDP can certify the uniqueness of the planted assignment. In contrast, in the refutation setting, it suffices to obtain a weaker guarantee of absolute upper bounds on the spectral norm of related matrices.

STOC Conference 2022 Conference Paper

Algorithms and certificates for Boolean CSP refutation: smoothed is no harder than random

  • Venkatesan Guruswami
  • Pravesh K. Kothari
  • Peter Manohar

We present an algorithm for strongly refuting smoothed instances of all Boolean CSPs. The smoothed model is a hybrid between worst and average-case input models, where the input is an arbitrary instance of the CSP with only the negation patterns of the literals re-randomized with some small probability. For an n-variable smoothed instance of a k-arity CSP, our algorithm runs in n^O(ℓ) time, and succeeds with high probability in bounding the optimum fraction of satisfiable constraints away from 1, provided that the number of constraints is at least Õ(n) (n/ell)^(k/2 - 1). This matches, up to polylogarithmic factors in n, the trade-off between running time and the number of constraints of the state-of-the-art algorithms for refuting fully random instances of CSPs. We also make a surprising connection between the analysis of our refutation algorithm in the significantly ”randomness starved” setting of semi-random k-XOR and the existence of even covers in worst-case hypergraphs. We use this connection to positively resolve Feige’s 2008 conjecture – an extremal combinatorics conjecture on the existence of even covers in sufficiently dense hypergraphs that generalizes the well-known Moore bound for the girth of graphs. As a corollary, we show that polynomial-size refutation witnesses exist for arbitrary smoothed CSP instances with number of constraints a polynomial factor below the ”spectral threshold” of n^(k/2), extending the celebrated result for random 3-SAT of Feige, Kim and Ofek.