Quantum Backtracking in Qrisp Applied to Sudoku Problems

Fuente: arXiv
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Main Authors: Seidel, Raphael, Zander, René, Petrič, Matic, Steinmann, Niklas, Liu, David Q., Tcholtchev, Nikolay, Hauswirth, Manfred
Format: Preprint
Published: 2024
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author Seidel, Raphael
Zander, René
Petrič, Matic
Steinmann, Niklas
Liu, David Q.
Tcholtchev, Nikolay
Hauswirth, Manfred
author_facet Seidel, Raphael
Zander, René
Petrič, Matic
Steinmann, Niklas
Liu, David Q.
Tcholtchev, Nikolay
Hauswirth, Manfred
contents The quantum backtracking algorithm proposed by Ashley Montanaro raised considerable interest, as it provides a quantum speed-up for a large class of classical optimization algorithms. It does not suffer from Barren-Plateaus and transfers well into the fault-tolerant era, as it requires only a limited number of arbitrary angle gates. Despite its potential, the algorithm has seen limited implementation efforts, presumably due to its abstract formulation. In this work, we provide a detailed instruction on implementing the quantum step operator for arbitrary backtracking instances. For a single controlled diffuser of a binary backtracking tree with depth n, our implementation requires only $6n+14$ CX gates. We detail the process of constructing accept and reject oracles for Sudoku problems using our interface to quantum backtracking. The presented code is written using Qrisp, a high-level quantum programming language, making it executable on most current physical backends and simulators. Subsequently, we perform several simulator based experiments and demonstrate solving 4x4 Sudoku instances with up to 9 empty fields. This is, to the best of our knowledge, the first instance of a compilable implementation of this generality, marking a significant and exciting step forward in quantum software engineering.
format Preprint
id arxiv_https___arxiv_org_abs_2402_10060
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Quantum Backtracking in Qrisp Applied to Sudoku Problems
Seidel, Raphael
Zander, René
Petrič, Matic
Steinmann, Niklas
Liu, David Q.
Tcholtchev, Nikolay
Hauswirth, Manfred
Quantum Physics
Data Structures and Algorithms
Programming Languages
The quantum backtracking algorithm proposed by Ashley Montanaro raised considerable interest, as it provides a quantum speed-up for a large class of classical optimization algorithms. It does not suffer from Barren-Plateaus and transfers well into the fault-tolerant era, as it requires only a limited number of arbitrary angle gates. Despite its potential, the algorithm has seen limited implementation efforts, presumably due to its abstract formulation. In this work, we provide a detailed instruction on implementing the quantum step operator for arbitrary backtracking instances. For a single controlled diffuser of a binary backtracking tree with depth n, our implementation requires only $6n+14$ CX gates. We detail the process of constructing accept and reject oracles for Sudoku problems using our interface to quantum backtracking. The presented code is written using Qrisp, a high-level quantum programming language, making it executable on most current physical backends and simulators. Subsequently, we perform several simulator based experiments and demonstrate solving 4x4 Sudoku instances with up to 9 empty fields. This is, to the best of our knowledge, the first instance of a compilable implementation of this generality, marking a significant and exciting step forward in quantum software engineering.
title Quantum Backtracking in Qrisp Applied to Sudoku Problems
topic Quantum Physics
Data Structures and Algorithms
Programming Languages
url https://arxiv.org/abs/2402.10060