Cover Image

Quantum EigenGame for excited state calculation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Quiroga, David, Han, Jason, Kyrillidis, Anastasios
Format:	Preprint
Published:	2025
Subjects:	Quantum Physics Data Structures and Algorithms Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm
by: Kim, Junhyung Lyle, et al.
Published: (2024)

Exploiting Low-Rank Structure in Max-K-Cut Problems
by: Stevens, Ria, et al.
Published: (2026)

Convergence Analysis of Two-Layer Neural Networks under Gaussian Input Masking
by: Kolomvaki, Afroditi, et al.
Published: (2026)

Quantum Langevin Dynamics for Optimization
by: Chen, Zherui, et al.
Published: (2023)

Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
by: Zhang, Yexin, et al.
Published: (2024)

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities
by: Su, Yuexin, et al.
Published: (2025)

Quantum thermodynamics and semi-definite optimization
by: Liu, Nana, et al.
Published: (2025)

Quantum speedups for stochastic optimization
by: Sidford, Aaron, et al.
Published: (2023)

On Speedups for Convex Optimization via Quantum Dynamics
by: Chakrabarti, Shouvanik, et al.
Published: (2025)

Min-Max Optimization Is Strictly Easier Than Variational Inequalities
by: Shugart, Henry, et al.
Published: (2025)

Negative Stepsizes Make Gradient-Descent-Ascent Converge
by: Shugart, Henry, et al.
Published: (2025)

Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss
by: Wang, Hao, et al.
Published: (2024)

Gibbs Sampling of Continuous Potentials on a Quantum Computer
by: Motamedi, Arsalan, et al.
Published: (2022)

Quantum Speedups for Group Relaxations of Integer Linear Programs
by: Augustino, Brandon, et al.
Published: (2026)

Quantum speedups for linear programming via interior point methods
by: Apers, Simon, et al.
Published: (2023)

Quantum Optimization Algorithms in Operations Research: Methods, Applications, and Implications
by: Klug, Florian
Published: (2023)

Quantum Approximate Optimization Algorithms for Maximum Cut on Low-Girth Graphs
by: Li, Tongyang, et al.
Published: (2024)

Negative Momentum for Convex-Concave Optimization
by: Shugart, Henry, et al.
Published: (2026)

Complexity of Classical Acceleration for $\ell_1$-Regularized PageRank
by: Fountoulakis, Kimon, et al.
Published: (2026)

Non-Euclidean High-Order Smooth Convex Optimization
by: Contreras, Juan Pablo, et al.
Published: (2024)

Generalized Short Path Algorithms: Towards Super-Quadratic Speedup over Markov Chain Search for Combinatorial Optimization
by: Chakrabarti, Shouvanik, et al.
Published: (2024)

Expanding the reach of quantum optimization with fermionic embeddings
by: Zhao, Andrew, et al.
Published: (2023)

A quantum central path algorithm for linear optimization
by: Augustino, Brandon, et al.
Published: (2023)

No quantum advantage implies improved bounds and classical algorithms for the binary paint shop problem
by: Goh, Mark, et al.
Published: (2026)

Mechanisms for Quantum Advantage in Global Optimization of Nonconvex Functions
by: Herman, Dylan, et al.
Published: (2025)

Optimal Bounds for Adversarial Constrained Online Convex Optimization
by: Ferreira, Ricardo N., et al.
Published: (2025)

Online Convex Optimization with Switching Cost with Only One Single Gradient Evaluation
by: Shah, Harsh, et al.
Published: (2025)

Distributionally Robust Optimization with Adversarial Data Contamination
by: Li, Shuyao, et al.
Published: (2025)

Oracle-based Uniform Sampling from Convex Bodies
by: Dang, Thanh, et al.
Published: (2025)

Discrete and Continuous Difference of Submodular Minimization
by: Orfanides, George, et al.
Published: (2025)

Gradient Testing and Estimation by Comparisons
by: Tao, Xiwen, et al.
Published: (2024)

Learning to Schedule in Parallel-Server Queues with Stochastic Bilinear Rewards
by: Kim, Jung-hun, et al.
Published: (2021)

Constrained and Composite Sampling via Proximal Sampler
by: Dang, Thanh, et al.
Published: (2026)

Importance Sparsification for Sinkhorn Algorithm
by: Li, Mengyu, et al.
Published: (2023)

Robust Learning of a Group DRO Neuron
by: Cao, Guyang, et al.
Published: (2026)

Online Linear Programming with Replenishment
by: Chen, Yuze, et al.
Published: (2026)

Learning-Augmented Algorithms for Online Concave Packing and Convex Covering Problems
by: Grigorescu, Elena, et al.
Published: (2024)

Learning Mixtures of Spherical Gaussians via Fourier Analysis
by: Chakraborty, Somnath, et al.
Published: (2020)

Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling
by: Kook, Yunbum, et al.
Published: (2023)

Learning-Augmented Algorithms for the Bahncard Problem
by: Zhao, Hailiang, et al.
Published: (2024)