Quantum signal processing over SU(N)

TL;DR

This paper extends quantum signal processing techniques by introducing multiple control qubits, enabling more complex polynomial transformations on matrices, which could enhance quantum algorithms like Shor's algorithm.

Contribution

It generalizes the QSP framework to multiple control qubits, allowing implementation of nearly any polynomial vector with polynomial gate complexity.

Findings

Multi-qubit QSP can implement nearly any polynomial vector.

Gate complexity scales polynomially with state dimension.

Polynomial degrees can grow exponentially with control qubits under certain conditions.

Abstract

Quantum signal processing (QSP) and the quantum singular value transformation (QSVT) are pivotal tools for simplifying the development of quantum algorithms. These techniques leverage polynomial transformations on the eigenvalues or singular values of block-encoded matrices, achieved with the use of just one control qubit. In contexts where the control qubit is used to extract information about the eigenvalues or singular values, the amount of extractable information is limited to one bit per protocol. In this work, we extend the original QSP ansatz by introducing multiple control qubits. We show that, much like in the single-qubit case, nearly any vector of polynomials can be implemented with a multi-qubit QSP ansatz, and the gate complexity scales polynomially with the dimension of such states. Moreover, assuming that powers of the matrix to transform are easily implementable - as in Shor's algorithm - we can achieve polynomial transformations with degrees that scale exponentially with the number of control qubits. This work aims to provide a partial characterization of the polynomials that can be implemented using this approach, with phase estimation schemes and discrete logarithm serving as illustrative examples.