Abhijeet Alase (Jan 14 2025).
Abstract: Quantum signal processing (QSP) has emerged as a unifying subroutine in quantum algorithms. In QSP, we are given a function
f and a unitary black-box
U, and the goal is to construct a quantum circuit for implementing
f(U) to a given precision. The existing approaches to performing QSP require a classical preprocessing step to compute rotation angle parameters for quantum circuits that implement
f approximately. However, this classical computation often becomes a bottleneck, limiting the scalability and practicality of QSP. In this work, we propose a novel approach to QSP that bypasses the computationally intensive angle-finding step. Our method leverages a quantum circuit for implementing a diagonal operator that encodes
f, which can be constructed from a classical circuit for evaluating
f. This approach to QSP simplifies the circuit design significantly while enabling nearly optimal implementation of functions of block-encoded Hermitian matrices for black-box functions. Our circuit closely resembles the phase estimation-based circuit for function implementation, challenging conventional skepticism about its efficiency. By reducing classical overhead, our work significantly broadens the applicability of QSP in quantum computing.
