Saved in:
| Main Authors: | Kubo, Kentaro, Goto, Hayato |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.02323 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
High-performance multiqubit system with double-transmon couplers: Toward scalable superconducting quantum computers
by: Kubo, Kentaro, et al.
Published: (2024)
by: Kubo, Kentaro, et al.
Published: (2024)
Quantum Boltzmann Machines for Sample-Efficient Reinforcement Learning
by: Gerlach, Thore, et al.
Published: (2025)
by: Gerlach, Thore, et al.
Published: (2025)
On the Sample Complexity of Quantum Boltzmann Machine Learning
by: Coopmans, Luuk, et al.
Published: (2023)
by: Coopmans, Luuk, et al.
Published: (2023)
Realization of High-Fidelity CZ Gate based on a Double-Transmon Coupler
by: Li, Rui, et al.
Published: (2024)
by: Li, Rui, et al.
Published: (2024)
Parametrically Driven iSWAP Gate Using a Capacitively Shunted Double-Transmon Coupler at the Zero-Flux Sweet Spot
by: Inoue, Shinichi, et al.
Published: (2026)
by: Inoue, Shinichi, et al.
Published: (2026)
Fraud detection in credit card transactions using Quantum-Assisted Restricted Boltzmann Machines
by: Neto, João Marcos Cavalcanti de Albuquerque, et al.
Published: (2025)
by: Neto, João Marcos Cavalcanti de Albuquerque, et al.
Published: (2025)
Using Quantum Solved Deep Boltzmann Machines to Increase the Data Efficiency of RL Agents
by: Kent, Daniel, et al.
Published: (2024)
by: Kent, Daniel, et al.
Published: (2024)
Investigation of D-Wave quantum annealing for training Restricted Boltzmann Machines and mitigating catastrophic forgetting
by: El-Yazizi, Abdelmoula, et al.
Published: (2025)
by: El-Yazizi, Abdelmoula, et al.
Published: (2025)
Capacitively Shunted Double-Transmon Coupler Realizing Bias-Free Idling and High-Fidelity CZ Gate
by: Li, Rui, et al.
Published: (2025)
by: Li, Rui, et al.
Published: (2025)
Quantum Boltzmann Machines using Parallel Annealing for Medical Image Classification
by: Schuman, Daniëlle, et al.
Published: (2025)
by: Schuman, Daniëlle, et al.
Published: (2025)
Machine Failure Detection Based on Projected Quantum Models
by: Bowden, Larry, et al.
Published: (2026)
by: Bowden, Larry, et al.
Published: (2026)
Many-hypercube codes: High-rate quantum error-correcting codes for high-performance fault-tolerant quantum computing
by: Goto, Hayato
Published: (2024)
by: Goto, Hayato
Published: (2024)
Meta-learning of Gibbs states for many-body Hamiltonians with applications to Quantum Boltzmann Machines
by: Bhat, Ruchira V, et al.
Published: (2025)
by: Bhat, Ruchira V, et al.
Published: (2025)
Expressive equivalence of classical and quantum restricted Boltzmann machines
by: Demidik, Maria, et al.
Published: (2025)
by: Demidik, Maria, et al.
Published: (2025)
Comparison of D-Wave Quantum Annealing and Markov Chain Monte Carlo for Sampling from a Probability Distribution of a Restricted Boltzmann Machine
by: Yazizi, Abdelmoula El, et al.
Published: (2025)
by: Yazizi, Abdelmoula El, et al.
Published: (2025)
Optimized Many-Hypercube Codes toward Lower Logical Error Rates and Earlier Realization
by: Goto, Hayato
Published: (2025)
by: Goto, Hayato
Published: (2025)
Structured quantum learning via em algorithm for Boltzmann machines
by: Kimura, Takeshi, et al.
Published: (2025)
by: Kimura, Takeshi, et al.
Published: (2025)
Neural Architecture Search Algorithms for Quantum Autoencoders
by: Kulshrestha, Ankit, et al.
Published: (2025)
by: Kulshrestha, Ankit, et al.
Published: (2025)
Neural Network Matrix Product Operator: A Multi-Dimensionally Integrable Machine Learning Potential
by: Hino, Kentaro, et al.
Published: (2024)
by: Hino, Kentaro, et al.
Published: (2024)
Surrogate Quantum Circuit Design for the Lattice Boltzmann Collision Operator
by: Lăcătuş, Monica, et al.
Published: (2025)
by: Lăcătuş, Monica, et al.
Published: (2025)
A Study on Stabilizer Rényi Entropy Estimation using Machine Learning
by: Lipardi, Vincenzo, et al.
Published: (2025)
by: Lipardi, Vincenzo, et al.
Published: (2025)
Efficient Mutation Testing of Quantum Machine Learning Models
by: Andrews, Emma, et al.
Published: (2026)
by: Andrews, Emma, et al.
Published: (2026)
QAdaPrune: Adaptive Parameter Pruning For Training Variational Quantum Circuits
by: Kulshrestha, Ankit, et al.
Published: (2024)
by: Kulshrestha, Ankit, et al.
Published: (2024)
A Modified Depolarization Approach for Efficient Quantum Machine Learning
by: Khanal, Bikram, et al.
Published: (2024)
by: Khanal, Bikram, et al.
Published: (2024)
Generative modeling using evolved quantum Boltzmann machines
by: Wilde, Mark M.
Published: (2025)
by: Wilde, Mark M.
Published: (2025)
Analogy between Boltzmann machines and Feynman path integrals
by: Iyengar, Srinivasan S., et al.
Published: (2023)
by: Iyengar, Srinivasan S., et al.
Published: (2023)
Efficient Bit Labeling in Factorization Machines with Annealing for Traveling Salesman Problem
by: Koshikawa, Shota, et al.
Published: (2024)
by: Koshikawa, Shota, et al.
Published: (2024)
A Qubit-Efficient Hybrid Quantum Encoding Mechanism for Quantum Machine Learning
by: Cowlessur, Hevish, et al.
Published: (2025)
by: Cowlessur, Hevish, et al.
Published: (2025)
Fundamentals of quantum Boltzmann machine learning with visible and hidden units
by: Wilde, Mark M.
Published: (2025)
by: Wilde, Mark M.
Published: (2025)
Subsystem many-hypercube codes: High-rate concatenated codes with low-weight syndrome measurements
by: Nakai, Ryota, et al.
Published: (2025)
by: Nakai, Ryota, et al.
Published: (2025)
Fault-tolerant quantum computing with a high-rate symplectic double code
by: Kanomata, Naoyuki, et al.
Published: (2025)
by: Kanomata, Naoyuki, et al.
Published: (2025)
Quantum chemistry based on classical mechanics inspired by simulated bifurcation
by: Aiga, Fumihiko, et al.
Published: (2026)
by: Aiga, Fumihiko, et al.
Published: (2026)
Efficient Quantum Gradient and Higher-order Derivative Estimation via Generalized Hadamard Test
by: Li, Dantong, et al.
Published: (2024)
by: Li, Dantong, et al.
Published: (2024)
Multi-Mode Quantum Annealing for Generative Representation Learning with Boltzmann Priors
by: Kim, Gilhan, et al.
Published: (2026)
by: Kim, Gilhan, et al.
Published: (2026)
Towards Transfer Learning for Large-Scale Image Classification Using Annealing-based Quantum Boltzmann Machines
by: Schuman, Daniëlle, et al.
Published: (2023)
by: Schuman, Daniëlle, et al.
Published: (2023)
Fast elementary gates for universal quantum computation with Kerr parametric oscillator qubits
by: Kanao, Taro, et al.
Published: (2023)
by: Kanao, Taro, et al.
Published: (2023)
High-performance conditional-driving gate for Kerr parametric oscillator qubits
by: Chono, Hiroomi, et al.
Published: (2024)
by: Chono, Hiroomi, et al.
Published: (2024)
Seeding neural network quantum states with tensor network states
by: Kaneko, Ryui, et al.
Published: (2025)
by: Kaneko, Ryui, et al.
Published: (2025)
Implementing Large Quantum Boltzmann Machines as Generative AI Models for Dataset Balancing
by: Sinno, Salvatore, et al.
Published: (2025)
by: Sinno, Salvatore, et al.
Published: (2025)
Quantum Boltzmann machine learning of ground-state energies
by: Patel, Dhrumil, et al.
Published: (2024)
by: Patel, Dhrumil, et al.
Published: (2024)
Similar Items
-
High-performance multiqubit system with double-transmon couplers: Toward scalable superconducting quantum computers
by: Kubo, Kentaro, et al.
Published: (2024) -
Quantum Boltzmann Machines for Sample-Efficient Reinforcement Learning
by: Gerlach, Thore, et al.
Published: (2025) -
On the Sample Complexity of Quantum Boltzmann Machine Learning
by: Coopmans, Luuk, et al.
Published: (2023) -
Realization of High-Fidelity CZ Gate based on a Double-Transmon Coupler
by: Li, Rui, et al.
Published: (2024) -
Parametrically Driven iSWAP Gate Using a Capacitively Shunted Double-Transmon Coupler at the Zero-Flux Sweet Spot
by: Inoue, Shinichi, et al.
Published: (2026)