# Quantum Algorithm for Signal Denoising

arXiv: https://arxiv.org/abs/2312.15411 · HTML: https://mlsanity.com/paper/2312.15411/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Dec 2023.

## Built on by (most cited first, 1 of 1)

- [Weight-Decay Turns Transformer Loss Landscapes Villani: Functional-Analytic Foundations for Optimization and Generalization](https://mlsanity.com/paper/2605.06599/) (2026)

## Abstract (arXiv)

This letter presents a novel textitquantum algorithm for signal denoising, which performs a thresholding in the frequency domain through amplitude amplification and using an adaptive threshold determined by local mean values. The proposed algorithm is able to process textitboth classical and quantum signals. It is parametrically faster than previous classical and quantum denoising algorithms. Numerical results show that it is efficient at removing noise of both classical and quantum origin, significantly outperforming existing quantum algorithms in this respect, especially in the presence of quantum noise.