# Fast Black-Box Quantum State Preparation

arXiv: https://arxiv.org/abs/2009.10709 · HTML: https://mlsanity.com/paper/2009.10709/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Sep 2020.

## Built on by (most cited first, 5 of 5)

- [Representation of binary classification trees with binary features by quantum circuits](https://mlsanity.com/paper/2108.13207/) (2021)
- [GQHAN: A Grover-inspired Quantum Hard Attention Network](https://mlsanity.com/paper/2401.14089/) (2024)
- [Data is often loadable in short depth: Quantum circuits from tensor networks for finance, images, fluids, and proteins](https://mlsanity.com/paper/2309.13108/) (2023)
- [Optimisation-free Classification and Density Estimation with Quantum Circuits](https://mlsanity.com/paper/2203.14452/) (2022)
- [Time series generation for option pricing on quantum computers using tensor network](https://mlsanity.com/paper/2402.17148/) (2024)

## Abstract (arXiv)

Quantum state preparation is an important ingredient for other higher-level quantum algorithms, such as Hamiltonian simulation, or for loading distributions into a quantum device to be used e.g. in the context of optimization tasks such as machine learning. Starting with a generic "black box" method devised by Grover in 2000, which employs amplitude amplification to load coefficients calculated by an oracle, there has been a long series of results and improvements with various additional conditions on the amplitudes to be loaded, culminating in Sanders et al.'s work which avoids almost all arithmetic during the preparation stage. In this work, we construct an optimized black box state loading scheme with which various important sets of coefficients can be loaded significantly faster than in O(√ N) rounds of amplitude amplification, up to only O(1) many. We achieve this with two variants of our algorithm. The first employs a modification of the oracle from Sanders et al., which requires fewer ancillas (log2 g vs g+2 in the bit precision g), and fewer non-Clifford operations per amplitude amplification round within the context of our algorithm. The second utilizes the same oracle, but at slightly increased cost in terms of ancillas (g+log2g) and non-Clifford operations per amplification round. As the number of amplitude amplification rounds enters as multiplicative factor, our black box state loading scheme yields an up to exponential speedup as compared to prior methods. This speedup translates beyond the black box case.