Imagen de Portada

Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Quiroga, David A., Kyrillidis, Anastasios
Formato:	Preprint
Publicado:	2023
Materias:	Quantum Physics Optimization and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Quantum EigenGame for excited state calculation
por: Quiroga, David, et al.
Publicado: (2025)

Random coordinate descent: a simple alternative for optimizing parameterized quantum circuits
por: Ding, Zhiyan, et al.
Publicado: (2023)

Introduction: Swarm-based gradient descent for non convex optimization
por: Tikko, Janina
Publicado: (2024)

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

Interpolation-based coordinate descent method for parameterized quantum circuits
por: Lai, Zhijian, et al.
Publicado: (2025)

The polarization hierarchy for polynomial optimization over convex bodies, with applications to nonnegative matrix rank
por: Plávala, Martin, et al.
Publicado: (2024)

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

First-order optimality conditions for non-commutative optimization problems
por: Araújo, Mateus, et al.
Publicado: (2023)

On the convergence of the variational quantum eigensolver and quantum optimal control
por: Wiedmann, Marco, et al.
Publicado: (2025)

Syndrome decoding by quantum approximate optimization
por: Lai, Ching-Yi, et al.
Publicado: (2022)

Globally optimal control of quantum dynamics
por: Bondar, Denys I., et al.
Publicado: (2022)

Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks
por: Liao, Fangshuo, et al.
Publicado: (2023)

Guided by the Experts: Provable Feature Learning Dynamic of Soft-Routed Mixture-of-Experts
por: Liao, Fangshuo, et al.
Publicado: (2025)

Robustness of optimal quantum annealing protocols
por: Funcke, Niklas, et al.
Publicado: (2024)

Convex semidefinite tensor optimization and quantum entanglement
por: Xu, Liding, et al.
Publicado: (2025)

Strategies for optimizing double-bracket quantum algorithms
por: Xiaoyue, Li, et al.
Publicado: (2024)

An introduction to variational quantum algorithms for combinatorial optimization problems
por: Grange, Camille, et al.
Publicado: (2022)

Velocity Verlet-based optimization for variational quantum eigensolvers
por: Miura, Rinka
Publicado: (2026)

Geometric optimization for quantum communication
por: Zhu, Chengkai, et al.
Publicado: (2025)

A meaningful optimal control problem in quantum and classical physics
por: Lazarus, Arnaud, et al.
Publicado: (2025)

Parallel variational quantum algorithms with gradient-informed restart to speed up optimisation in the presence of barren plateaus
por: Mastropietro, Daniel, et al.
Publicado: (2023)

Solving quadratic binary optimization problems using quantum SDP methods: Non-asymptotic running time analysis
por: Henze, Fabian, et al.
Publicado: (2025)

Model predictive quantum control: A modular approach for efficient and robust quantum optimal control
por: Guizani, Eya, et al.
Publicado: (2025)

A heuristic for solving the irregular strip packing problem with quantum optimization
por: Matt, Paul-Amaury, et al.
Publicado: (2024)

A comparison on constrain encoding methods for quantum approximate optimization algorithm
por: Liu, Yiwen, et al.
Publicado: (2024)

Radiation design in computed tomography via convex optimization
por: Juditsky, Anatoli, et al.
Publicado: (2023)

Integrating quantum and classical computing for multi-energy system optimization using Benders decomposition
por: Leenders, Ludger, et al.
Publicado: (2023)

A quadratic Grassmann manifold optimization problem arising from quantum embedding methods
por: Ayral, Thomas, et al.
Publicado: (2026)

Gate generation for open quantum systems via a monotonic algorithm with time optimization
por: da Silva, Paulo Sergio Pereira, et al.
Publicado: (2024)

Quantum Algorithms for Non-smooth Non-convex Optimization
por: Liu, Chengchang, et al.
Publicado: (2024)

Transfer learning of optimal QAOA parameters in combinatorial optimization
por: Montanez-Barrera, J. A., et al.
Publicado: (2024)

Research on the descent direction of prediction correction algorithms for pseudo-convex/convex optimization problems
por: Li, Ting, et al.
Publicado: (2025)

Operator convexity along lines, self-concordance, and sandwiched Rényi entropies
por: He, Kerry, et al.
Publicado: (2025)

Finite de Finetti for convex bodies and Polynomial Optimization
por: Zeiss, Julius A., et al.
Publicado: (2026)

An overview of the fractional-order gradient descent method and its applications
por: Ferreira, Higor V. M., et al.
Publicado: (2026)

Using quantum computers in control: interval matrix properties
por: Schneider, Jan, et al.
Publicado: (2024)

Worst-case convergence analysis of relatively inexact gradient descent on smooth convex functions
por: Vernimmen, Pierre, et al.
Publicado: (2025)

Scalable iterative pruning of large language and vision models using block coordinate descent
por: Rosenberg, Gili, et al.
Publicado: (2024)

Classical optimization algorithms for diagonalizing quantum Hamiltonians
por: Ko, Taehee, et al.
Publicado: (2025)

Certified bounds on optimization problems in quantum theory
por: Naceur, Younes, et al.
Publicado: (2025)