Optimizing ZX-Diagrams with Deep Reinforcement Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Nägele, Maximilian, Marquardt, Florian |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Optimizing Quantum Circuits via ZX Diagrams using Reinforcement Learning and Graph Neural Networks
by: Mattick, Alexander, et al.
Published: (2025)
by: Mattick, Alexander, et al.
Published: (2025)
Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning
by: Nägele, Maximilian, et al.
Published: (2024)
by: Nägele, Maximilian, et al.
Published: (2024)
Agentic Exploration of Physics Models
by: Nägele, Maximilian, et al.
Published: (2025)
by: Nägele, Maximilian, et al.
Published: (2025)
Differentiating and Integrating ZX Diagrams with Applications to Quantum Machine Learning
by: Wang, Quanlong, et al.
Published: (2022)
by: Wang, Quanlong, et al.
Published: (2022)
Reusability Report: Optimizing T-count in General Quantum Circuits with AlphaTensor-Quantum
by: Zen, Remmy, et al.
Published: (2025)
by: Zen, Remmy, et al.
Published: (2025)
Reinforcement Learning for Quantum Technology
by: Bukov, Marin, et al.
Published: (2026)
by: Bukov, Marin, et al.
Published: (2026)
Completeness for Fault Equivalence of Clifford ZX Diagrams
by: Rüsch, Maximilian, et al.
Published: (2025)
by: Rüsch, Maximilian, et al.
Published: (2025)
Quantum feedback control with a transformer neural network architecture
by: Vaidhyanathan, Pranav, et al.
Published: (2024)
by: Vaidhyanathan, Pranav, et al.
Published: (2024)
ZX-Flow: A Flexible Criterion for Deterministic Computation with ZX-Diagrams
by: Kissinger, Aleks, et al.
Published: (2026)
by: Kissinger, Aleks, et al.
Published: (2026)
Quantum Equilibrium Propagation for efficient training of quantum systems based on Onsager reciprocity
by: Wanjura, Clara C., et al.
Published: (2024)
by: Wanjura, Clara C., et al.
Published: (2024)
Optimizing Variational Quantum Circuits Using Metaheuristic Strategies in Reinforcement Learning
by: Kölle, Michael, et al.
Published: (2024)
by: Kölle, Michael, et al.
Published: (2024)
Quantum Distance Approximation for Persistence Diagrams
by: Ameneyro, Bernardo, et al.
Published: (2024)
by: Ameneyro, Bernardo, et al.
Published: (2024)
Hamiltonian-based Quantum Reinforcement Learning for Neural Combinatorial Optimization
by: Kruse, Georg, et al.
Published: (2024)
by: Kruse, Georg, et al.
Published: (2024)
Automated Discovery of Gadgets in Quantum Circuits for Efficient Reinforcement Learning
by: Yevtushenko, Oleg M., et al.
Published: (2025)
by: Yevtushenko, Oleg M., et al.
Published: (2025)
Quantum Deep Reinforcement Learning for Robot Navigation Tasks
by: Hohenfeld, Hans, et al.
Published: (2022)
by: Hohenfeld, Hans, et al.
Published: (2022)
Reinforcement Learning Based Quantum Circuit Optimization via ZX-Calculus
by: Riu, Jordi, et al.
Published: (2023)
by: Riu, Jordi, et al.
Published: (2023)
Speedy Contraction of ZX Diagrams with Triangles via Stabiliser Decompositions
by: Koch, Mark, et al.
Published: (2023)
by: Koch, Mark, et al.
Published: (2023)
Breaking Through Barren Plateaus: Reinforcement Learning Initializations for Deep Variational Quantum Circuits
by: Peng, Yifeng, et al.
Published: (2025)
by: Peng, Yifeng, et al.
Published: (2025)
Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer
by: Hagiwara, Ryo, et al.
Published: (2025)
by: Hagiwara, Ryo, et al.
Published: (2025)
Scalable Quantum Reinforcement Learning on NISQ Devices with Dynamic-Circuit Qubit Reuse and Grover Optimization
by: Su, Thet Htar, et al.
Published: (2025)
by: Su, Thet Htar, et al.
Published: (2025)
Procedurally Optimised ZX-Diagram Cutting for Efficient T-Decomposition in Classical Simulation
by: Sutcliffe, Matthew, et al.
Published: (2024)
by: Sutcliffe, Matthew, et al.
Published: (2024)
Quantum Advantage Actor-Critic for Reinforcement Learning
by: Kölle, Michael, et al.
Published: (2024)
by: Kölle, Michael, et al.
Published: (2024)
Compiler Optimization for Quantum Computing Using Reinforcement Learning
by: Quetschlich, Nils, et al.
Published: (2022)
by: Quetschlich, Nils, et al.
Published: (2022)
Benchmarking Quantum Reinforcement Learning
by: Meyer, Nico, et al.
Published: (2025)
by: Meyer, Nico, et al.
Published: (2025)
Reinforcement learning for ion shuttling on trapped-ion quantum computers
by: Schier, Maximilian, et al.
Published: (2026)
by: Schier, Maximilian, et al.
Published: (2026)
From Betti Numbers to Persistence Diagrams: A Hybrid Quantum Algorithm for Topological Data Analysis
by: Liu, Dong
Published: (2025)
by: Liu, Dong
Published: (2025)
Scaling the Automated Discovery of Quantum Circuits via Reinforcement Learning with Gadgets
by: Olle, Jan, et al.
Published: (2025)
by: Olle, Jan, et al.
Published: (2025)
A Survey on Quantum Reinforcement Learning
by: Meyer, Nico, et al.
Published: (2022)
by: Meyer, Nico, et al.
Published: (2022)
A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning
by: Kölle, Michael, et al.
Published: (2024)
by: Kölle, Michael, et al.
Published: (2024)
Reconstructing Quantum Dot Charge Stability Diagrams with Diffusion Models
by: Hernandes, Vinicius, et al.
Published: (2026)
by: Hernandes, Vinicius, et al.
Published: (2026)
Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning
by: Wendlinger, Maximilian, et al.
Published: (2025)
by: Wendlinger, Maximilian, et al.
Published: (2025)
Challenges for Reinforcement Learning in Quantum Circuit Design
by: Altmann, Philipp, et al.
Published: (2023)
by: Altmann, Philipp, et al.
Published: (2023)
Reinforcement Learning for Variational Quantum Circuits Design
by: Foderà, Simone, et al.
Published: (2024)
by: Foderà, Simone, et al.
Published: (2024)
Minor Embedding for Quantum Annealing with Reinforcement Learning
by: Nembrini, Riccardo, et al.
Published: (2025)
by: Nembrini, Riccardo, et al.
Published: (2025)
Investigating Parameter-Efficiency of Hybrid QuGANs Based on Geometric Properties of Generated Sea Route Graphs
by: Rohe, Tobias, et al.
Published: (2025)
by: Rohe, Tobias, et al.
Published: (2025)
Vehicle Routing Problems via Quantum Graph Attention Network Deep Reinforcement Learning
by: Giang, Le Tung, et al.
Published: (2025)
by: Giang, Le Tung, et al.
Published: (2025)
Quantum Boltzmann Machines for Sample-Efficient Reinforcement Learning
by: Gerlach, Thore, et al.
Published: (2025)
by: Gerlach, Thore, et al.
Published: (2025)
Quantum Compiling with Reinforcement Learning on a Superconducting Processor
by: Wang, Z. T., et al.
Published: (2024)
by: Wang, Z. T., et al.
Published: (2024)
Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis
by: Yeung, Richie, et al.
Published: (2026)
by: Yeung, Richie, et al.
Published: (2026)
Dynamic Inhomogeneous Quantum Resource Scheduling with Reinforcement Learning
by: Li, Linsen, et al.
Published: (2024)
by: Li, Linsen, et al.
Published: (2024)
Similar Items
-
Optimizing Quantum Circuits via ZX Diagrams using Reinforcement Learning and Graph Neural Networks
by: Mattick, Alexander, et al.
Published: (2025) -
Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning
by: Nägele, Maximilian, et al.
Published: (2024) -
Agentic Exploration of Physics Models
by: Nägele, Maximilian, et al.
Published: (2025) -
Differentiating and Integrating ZX Diagrams with Applications to Quantum Machine Learning
by: Wang, Quanlong, et al.
Published: (2022) -
Reusability Report: Optimizing T-count in General Quantum Circuits with AlphaTensor-Quantum
by: Zen, Remmy, et al.
Published: (2025)