6 papers
Structured quantum learning via em algorithm for Boltzmann machines
Takeshi Kimura, Kohtaro Kato, Masahito Hayashi
Quantum Boltzmann machines (QBMs) are generative models with potential advantages in quantum machine learning, yet their training is fundamentally limited by the barren plateau pro…
Double Markovity for quantum systems
Masahito Hayashi, Jinpei Zhao
The subadditivity-doubling-rotation (SDR) technique is a powerful route to Gaussian optimality in classical information theory and relies on strict subadditivity and its equality-c…
A Posteriori Certification Framework for Generalized Quantum Arimoto-Blahut Algorithms
Geng Liu, Masahito Hayashi
The generalized quantum Arimoto--Blahut (QAB) algorithm is a powerful derivative-free iterative method in quantum information theory. A key obstacle to its broader use is that exis…
Universal classical-quantum channel resolvability and private channel coding
Takaya Matsuura, Masahito Hayashi, Min-Hsiu Hsieh
We address the problem of constructing fully universal private channel coding protocols for classical-quantum (c-q) channels. Previous work constructed universal decoding strategie…
String commitment from unstructured noise
Jiawei Wu, Masahito Hayashi, Marco Tomamichel
Noisy channels are a foundational resource for constructing cryptographic primitives such as string commitment and oblivious transfer. The noisy channel model has been extended to…
-Racah probability distribution
Masahito Hayashi, Akihito Hora, Shintarou Yanagida
We introduce a certain discrete probability distribution having non-negative integer parameters and quantum parameter which arises from a zonal spheri…