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Penghui Yao

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6 papers
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6

STOC Conference 2025 Conference Paper

On the Computational Power of QAC0 with Barely Superlinear Ancillae

  • Anurag Anshu
  • Yangjing Dong
  • Fengning Ou
  • Penghui Yao

QAC 0 is the family of constant-depth polynomial-size quantum circuits consisting of arbitrary single qubit unitaries and multi-qubit Toffoli gates. It was introduced by Moore as a quantum counterpart of AC 0 , along with the conjecture that QAC 0 circuits can not compute PARITY. In this work we make progress on this longstanding conjecture: we show that any depth- d QAC 0 circuit requires n 1+3 − d ancillae to compute a function with approximate degree Θ( n ), which includes PARITY, MAJORITY and MOD k . We further establish superlinear lower bounds on quantum state synthesis and quantum channel synthesis. This is the first superlinear lower bound on the super-linear sized QAC 0 . Regarding PARITY, we show that any further improvement on the size of ancillae to n 1+exp(− o ( d )) would imply that PARITY ∉ QAC0. These lower bounds are derived by giving low-degree approximations to QAC 0 circuits. We show that a depth- d QAC 0 circuit with a ancillae, when applied to low-degree operators, has a degree ( n + a ) 1−3 − d polynomial approximation in the spectral norm. This implies that the class QLC 0 , corresponding to linear size QAC 0 circuits, has approximate degree o ( n ). This is a quantum generalization of the result that LC 0 circuits have approximate degree o ( n ) by Bun, Robin, and Thaler. Our result also implies that QLC 0 ≠ NC 1 .

FOCS Conference 2012 Conference Paper

A Direct Product Theorem for the Two-Party Bounded-Round Public-Coin Communication Complexity

  • Rahul Jain 0001
  • Attila Pereszlényi
  • Penghui Yao

A strong direct product theorem for a problem in a given model of computation states that, in order to compute k instances of the problem, if we provide resource which is less than k times the resource required for computing one instance of the problem with constant success probability, then the probability of correctly computing all the k instances together, is exponentially small in k. In this paper, we consider the model of two-party bounded-round public-coin randomized communication complexity. We show a direct product theorem for the communication complexity of any relation in this model. In particular, our result implies a strong direct product theorem for the two-party constant-message public-coin randomized communication complexity of all relations. As an immediate application of our result, we get a strong direct product theorem for the pointer chasing problem. This problem has been well studied for understanding round v/s communication trade-offs in both classical and quantum communication protocols. Our result generalizes the result of Jain [2011] which can be regarded as the special case when t=1. Our result can be considered as an important progress towards settling the strong direct product conjecture for the two-party public-coin communication complexity, a major open question in this area. We show our result using information theoretic arguments. Our arguments and techniques build on the ones used in Jain~\cite{Jain: 2011}. %, where a strong direct product theorem for the %two-party one-way public-coin communication complexity of all %relations is shown (that is the special case of our result when $t=1$). One key tool used in our work and also in Jain~\cite{Jain: 2011} is a message compression technique due to Braver man and Rao~\cite{Braverman2011}, who used it to show a {\em direct sum} theorem in the same model of communication complexity as considered by us. Another important tool that we use is a correlated sampling protocol, which for example, has been used in Holenstein~\cite{Holenstein2007} for proving a parallel repetition theorem for two-prover games.

FOCS Conference 2011 Conference Paper

A Parallel Approximation Algorithm for Positive Semidefinite Programming

  • Rahul Jain 0001
  • Penghui Yao

Positive semi definite programs are an important subclass of semi definite programs in which all matrices involved in the specification of the problem are positive semi definite and all scalars involved are non-negative. We present a parallel algorithm, which given an instance of a positive semi definite program of size N and an approximation factor ε >; 0, runs in (parallel) time poly(1/ε)·polylog(N), using poly(N) processors, and outputs a value which is within multiplicative factor of (1+ε) to the optimal. Our result generalizes analogous result of Luby and Nisan (1993) for positive linear programs and our algorithm is inspired by their algorithm of [10].