Quantum algorithms for escaping from saddle points
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Abstract (arXiv)
We initiate the study of quantum algorithms for escaping from saddle points with provable guarantee. Given a function fcolonℝn→ℝ, our quantum algorithm outputs an ε-approximate second-order stationary point using tildeO(log2 (n)/ε1.75) queries to the quantum evaluation oracle (i.e., the zeroth-order oracle). Compared to the classical state-of-the-art algorithm by Jin et al. with tildeO(log6 (n)/ε1.75) queries to the gradient oracle (i.e., the first-order oracle), our quantum algorithm is polynomially better in terms of log n and matches its complexity in terms of 1/ε. Technically, our main contribution is the idea of replacing the classical perturbations in gradient descent methods by simulating quantum wave equations, which constitutes the improvement in the quantum query complexity with log n factors for escaping from saddle points. We also show how to use a quantum gradient computation algorithm due to Jordan to replace the classical gradient queries by quantum evaluation queries with the same complexity. Finally, we also perform numerical experiments that support our theoretical findings.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jul 2020.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 3; 2025: 2.
10 papers.
- 2021Quantum Algorithms and Lower Bounds for Linear Regression with Norm Constraintscited by 11
- 2022Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Banditscited by 11
- 2022On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walkscited by 9
- 2022Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constantscited by 8
- 2023Quantum Langevin Dynamics for Optimizationcited by 7
- 2024Quantum Algorithms and Lower Bounds for Finite-Sum Optimizationcited by 3
- 2024Enhancing the Trainability of Variational Quantum Circuits with Regularization Strategiescited by 2
- 2025Quantum Non-Linear Bandit Optimizationcited by 2
- 2024Gradient Testing and Estimation by Comparisonscited by 0
- 2025Quantum Optimization via Gradient-Based Hamiltonian Descentcited by 0
- 2025Quantum Optimization via Gradient-Based Hamiltonian Descent20 May 2025
- 2025Quantum Non-Linear Bandit Optimization4 Mar 2025
- 2024Quantum Algorithms and Lower Bounds for Finite-Sum Optimization5 Jun 2024
- 2024Gradient Testing and Estimation by Comparisons19 May 2024
- 2024Enhancing the Trainability of Variational Quantum Circuits with Regularization Strategies2 May 2024
- 2023Quantum Langevin Dynamics for Optimization27 Nov 2023
- 2022Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants12 Oct 2022
- 2022On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks29 Sep 2022
- 2022Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits26 Sep 2022
- 2021Quantum Algorithms and Lower Bounds for Linear Regression with Norm Constraints25 Oct 2021