Quantum Mechanics and Neural Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Ferko, Christian, Halverson, James |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Universality of Neural Network Field Theory
by: Ferko, Christian, et al.
Published: (2026)
by: Ferko, Christian, et al.
Published: (2026)
Topological Effects in Neural Network Field Theory
by: Ferko, Christian, et al.
Published: (2026)
by: Ferko, Christian, et al.
Published: (2026)
Anomalies in Neural Network Field Theory
by: Ferko, Christian, et al.
Published: (2026)
by: Ferko, Christian, et al.
Published: (2026)
Conformal Fields from Neural Networks
by: Halverson, James, et al.
Published: (2024)
by: Halverson, James, et al.
Published: (2024)
Metric Flows with Neural Networks
by: Halverson, James, et al.
Published: (2023)
by: Halverson, James, et al.
Published: (2023)
Fermions and Supersymmetry in Neural Network Field Theories
by: Frank, Samuel, et al.
Published: (2025)
by: Frank, Samuel, et al.
Published: (2025)
Entanglement cohomology for GHZ and W states
by: Ferko, Christian, et al.
Published: (2025)
by: Ferko, Christian, et al.
Published: (2025)
TASI Lectures on Physics for Machine Learning
by: Halverson, Jim
Published: (2024)
by: Halverson, Jim
Published: (2024)
Quantum Qualifiers for Neural Network Model Selection in Hadronic Physics
by: Le, Brandon B., et al.
Published: (2026)
by: Le, Brandon B., et al.
Published: (2026)
Compton Form Factor Extraction using Quantum Deep Neural Networks
by: Le, Brandon B., et al.
Published: (2025)
by: Le, Brandon B., et al.
Published: (2025)
Rigor with Machine Learning from Field Theory to the Poincaré Conjecture
by: Gukov, Sergei, et al.
Published: (2024)
by: Gukov, Sergei, et al.
Published: (2024)
Les Houches Lectures on Deep Learning at Large & Infinite Width
by: Bahri, Yasaman, et al.
Published: (2023)
by: Bahri, Yasaman, et al.
Published: (2023)
A Max-Flow approach to Random Tensor Networks
by: Fitter, Khurshed, et al.
Published: (2024)
by: Fitter, Khurshed, et al.
Published: (2024)
QINNs: Quantum-Informed Neural Networks
by: Bal, Aritra, et al.
Published: (2025)
by: Bal, Aritra, et al.
Published: (2025)
Holography with Null Boundaries
by: Ferko, Christian, et al.
Published: (2025)
by: Ferko, Christian, et al.
Published: (2025)
Lie-Equivariant Quantum Graph Neural Networks
by: Neto, Jogi Suda, et al.
Published: (2024)
by: Neto, Jogi Suda, et al.
Published: (2024)
Quantization of the ModMax Oscillator
by: Ferko, Christian, et al.
Published: (2023)
by: Ferko, Christian, et al.
Published: (2023)
Quantum-classical simulation of quantum field theory by quantum circuit learning
by: Ikeda, Kazuki
Published: (2023)
by: Ikeda, Kazuki
Published: (2023)
String Theory from Infinite Width Neural Networks
by: Frank, Samuel, et al.
Published: (2026)
by: Frank, Samuel, et al.
Published: (2026)
Adaptive H-EFT-VA: A Provably Safe Trajectory Through the Trainability-Expressibility Landscape of Variational Quantum Algorithms
by: Hamid, Eyad I. B.
Published: (2026)
by: Hamid, Eyad I. B.
Published: (2026)
From Reachability to Learnability: Geometric Design Principles for Quantum Neural Networks
by: Ngairangbam, Vishal S., et al.
Published: (2026)
by: Ngairangbam, Vishal S., et al.
Published: (2026)
Neural Network Learning and Quantum Gravity
by: Lanza, Stefano
Published: (2024)
by: Lanza, Stefano
Published: (2024)
Jet Discrimination with Quantum Complete Graph Neural Network
by: Chen, Yi-An, et al.
Published: (2024)
by: Chen, Yi-An, et al.
Published: (2024)
Random tensor networks with nontrivial links
by: Cheng, Newton, et al.
Published: (2022)
by: Cheng, Newton, et al.
Published: (2022)
Constructive Quantum Field Theory on Curved Surfaces and Related Topics
by: Lin, Jiasheng
Published: (2025)
by: Lin, Jiasheng
Published: (2025)
Hodge Theory for Entanglement Cohomology
by: Ferko, Christian, et al.
Published: (2024)
by: Ferko, Christian, et al.
Published: (2024)
Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems
by: Shem-Ur, Ori, et al.
Published: (2024)
by: Shem-Ur, Ori, et al.
Published: (2024)
$\mathbb{Z}_2\times \mathbb{Z}_2$ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks
by: Dong, Zhongtian, et al.
Published: (2023)
by: Dong, Zhongtian, et al.
Published: (2023)
A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks
by: Forestano, Roy T., et al.
Published: (2023)
by: Forestano, Roy T., et al.
Published: (2023)
Stochastic Calculus and Hochschild Homology
by: Li, Si, et al.
Published: (2025)
by: Li, Si, et al.
Published: (2025)
An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training
by: Backes, Mathias, et al.
Published: (2022)
by: Backes, Mathias, et al.
Published: (2022)
Hamiltonian Neural Networks approach to fuzzball geodesics
by: Cipriani, Andrea, et al.
Published: (2025)
by: Cipriani, Andrea, et al.
Published: (2025)
Machine Learning for Anomaly Detection in Particle Physics
by: Belis, Vasilis, et al.
Published: (2023)
by: Belis, Vasilis, et al.
Published: (2023)
Exploring the holographic entropy cone via reinforcement learning
by: He, Temple, et al.
Published: (2026)
by: He, Temple, et al.
Published: (2026)
Generative Invertible Quantum Neural Networks
by: Rousselot, Armand, et al.
Published: (2023)
by: Rousselot, Armand, et al.
Published: (2023)
Improved Ground State Estimation in Quantum Field Theories via Normalising Flow-Assisted Neural Quantum States
by: Ngairangbam, Vishal S., et al.
Published: (2025)
by: Ngairangbam, Vishal S., et al.
Published: (2025)
Rediscovery of Numerical Lüscher's Formula from the Neural Network
by: Lu, Yu, et al.
Published: (2022)
by: Lu, Yu, et al.
Published: (2022)
Quantum Fisher information matrices from Rényi relative entropies
by: Wilde, Mark M.
Published: (2025)
by: Wilde, Mark M.
Published: (2025)
Guided Graph Compression for Quantum Graph Neural Networks
by: Casals, Mikel, et al.
Published: (2025)
by: Casals, Mikel, et al.
Published: (2025)
Neural Scaling Laws for Jet Generation
by: Amram, Oz, et al.
Published: (2026)
by: Amram, Oz, et al.
Published: (2026)
Similar Items
-
Universality of Neural Network Field Theory
by: Ferko, Christian, et al.
Published: (2026) -
Topological Effects in Neural Network Field Theory
by: Ferko, Christian, et al.
Published: (2026) -
Anomalies in Neural Network Field Theory
by: Ferko, Christian, et al.
Published: (2026) -
Conformal Fields from Neural Networks
by: Halverson, James, et al.
Published: (2024) -
Metric Flows with Neural Networks
by: Halverson, James, et al.
Published: (2023)