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Generalized Quantum Signal Processing and Non-Linear Fourier Transform are equivalent
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abstract
Quantum signal processing (QSP) and quantum singular value transformation (QSVT) are powerful techniques for the development of quantum procedures. They allow to derive circuits preparing desired polynomial transformations. Recent research [Alexis et al. 2024] showed that Non-Linear Fourier Analysis (NLFA) can be employed to numerically compute a QSP protocol, with provable stability. In this work we extend their result, showing that GQSP and the Non-Linear Fourier Transform over $SU(2)$ are the same object. This statement - proven by a simple argument - has a bunch of consequences: first, the Riemann-Hilbert-Weiss algorithm can be turned, with little modifications and no penalty in complexity, into a unified, provably stable algorithm for the computation of phase factors in any QSP variant, including GQSP. Secondly, we derive a uniqueness result for the existence of GQSP phase factors based on the bijectivity of the Non-Linear Fourier Transform. Furthermore, NLFA provides a complete theory of infinite generalized quantum signal processing, which characterizes the class of functions approximable by GQSP protocols.
Forward citations
Cited by 2 Pith papers
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Oscillator-qubit generalized quantum signal processing for vibronic models: a case study of uracil cation
A GQSP-based compiler synthesizes arbitrary bosonic phase gates from conditional-displacement gates on hybrid qubit-oscillator processors and applies them to anharmonic vibronic dynamics of the uracil cation.
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Matrix inversion polynomials for the quantum singular value transformation
An explicit, provably optimal polynomial for approximating 1/x in QSVT matrix inversion, with a stable recurrence and minimum degree formula.
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