Copertina

Physics-inspired transformer quantum states via latent imaginary-time evolution

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yamazaki, Kimihiro, Sakata, Itsushi, Konishi, Takuya, Kawahara, Yoshinobu
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Disordered Systems and Neural Networks Machine Learning Quantum Physics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Geometric quantum machine learning of BQP$^A$ protocols and latent graph classifiers
di: Umeano, Chukwudubem, et al.
Pubblicazione: (2024)

Application of time-series quantum generative model to financial data
di: Okumura, Shun, et al.
Pubblicazione: (2024)

New non-Euclidean neural quantum states from additional types of hyperbolic recurrent neural networks
di: Dao, H. L.
Pubblicazione: (2026)

Perfect reconstruction of sparse signals using nonconvexity control and one-step RSB message passing
di: Gu, Xiaosi, et al.
Pubblicazione: (2025)

The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model
di: Takanami, Kaito, et al.
Pubblicazione: (2025)

Noise tolerance via reinforcement: Learning a reinforced quantum dynamics
di: Ramezanpour, Abolfazl
Pubblicazione: (2025)

What can we learn from quantum convolutional neural networks?
di: Umeano, Chukwudubem, et al.
Pubblicazione: (2023)

Role of scrambling and noise in temporal information processing with quantum systems
di: Xiong, Weijie, et al.
Pubblicazione: (2025)

Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms
di: Srimahajariyapong, Kasidit, et al.
Pubblicazione: (2025)

Hyperbolic recurrent neural network as the first type of non-Euclidean neural quantum state ansatz
di: Dao, H. L.
Pubblicazione: (2025)

Signal amplification in a solid-state quantum sensor via asymmetric time-reversal of many-body dynamics
di: Gao, Haoyang, et al.
Pubblicazione: (2025)

In-context denoising with one-layer transformers: connections between attention and associative memory retrieval
di: Smart, Matthew, et al.
Pubblicazione: (2025)

Paths towards time evolution with larger neural-network quantum states
di: Zhang, Wenxuan, et al.
Pubblicazione: (2024)

Expressibility of neural quantum states: a Walsh-complexity perspective
di: Wang, Taige
Pubblicazione: (2026)

Variational optimization of the amplitude of neural-network quantum many-body ground states
di: Wang, Jia-Qi, et al.
Pubblicazione: (2023)

Optimizing quantum transport via the quantum Doob transform
di: Esteve, Dolores, et al.
Pubblicazione: (2025)

Bound on entanglement in neural quantum states
di: Paul, Nisarga
Pubblicazione: (2025)

Iterative quantum optimisation with a warm-started quantum state
di: Yuan, Haomu, et al.
Pubblicazione: (2025)

Generalized Probabilistic Approximate Optimization Algorithm
di: Abdelrahman, Abdelrahman S., et al.
Pubblicazione: (2025)

Lindbladian Learning with Neural Differential Equations
di: Heightman, Timothy, et al.
Pubblicazione: (2026)

Unlearnable phases of matter
di: Kumar, Tarun Advaith, et al.
Pubblicazione: (2026)

A Framework for Demonstrating Practical Quantum Advantage: Racing Quantum against Classical Generative Models
di: Hibat-Allah, Mohamed, et al.
Pubblicazione: (2023)

Quantum Equilibrium Propagation: Gradient-Descent Training of Quantum Systems
di: Scellier, Benjamin
Pubblicazione: (2024)

Natural Quantization of Neural Networks
di: Barney, Richard, et al.
Pubblicazione: (2025)

Investigating layer-selective transfer learning of QAOA parameters for Max-Cut problem
di: Venturelli, Francesco Aldo, et al.
Pubblicazione: (2024)

Benchmarking a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware
di: Lakhdar-Hamina, Djamil, et al.
Pubblicazione: (2025)

Adiabatic transport of neural network quantum states
di: Medvidović, Matija, et al.
Pubblicazione: (2025)

Ground state-based quantum feature maps
di: Umeano, Chukwudubem, et al.
Pubblicazione: (2024)

Physical Reinforcement Learning
di: Dillavou, Sam, et al.
Pubblicazione: (2025)

Simplicity of mean-field theories in neural quantum states
di: Trigueros, Fabian Ballar, et al.
Pubblicazione: (2023)

Entanglement and optimization within autoregressive neural quantum states
di: Jreissaty, Andrew, et al.
Pubblicazione: (2025)

Neural-network quantum states for many-body physics
di: Medvidović, Matija, et al.
Pubblicazione: (2024)

On the role of non-linear latent features in bipartite generative neural networks
di: Bonnaire, Tony, et al.
Pubblicazione: (2025)

Finite-time Lyapunov exponents of deep neural networks
di: Storm, L., et al.
Pubblicazione: (2023)

Hybrid between biologically and quantum-inspired many-body states
di: Srdinšek, Miha, et al.
Pubblicazione: (2025)

Connectivity determines the capability of sparse neural network quantum states
di: Barton, Brandon, et al.
Pubblicazione: (2025)

Double descent: When do neural quantum states generalize?
di: Moss, M. Schuyler, et al.
Pubblicazione: (2025)

Solving excited states for long-range interacting trapped ions with neural networks
di: Ma, Yixuan, et al.
Pubblicazione: (2025)

Analog Physical Systems Can Exhibit Double Descent
di: Dillavou, Sam, et al.
Pubblicazione: (2025)

Quantum Equilibrium Propagation for efficient training of quantum systems based on Onsager reciprocity
di: Wanjura, Clara C., et al.
Pubblicazione: (2024)