8 citations · 17 across the 7 of their papers we have counts for
8 papers
Joint measurability of coplanar POVMs
Taro Yoshino, Koichi Tojo, Kei Hagihara +2
An unbiased qubit positive operator-valued measure (POVM) can be uniquely expressed in terms of the Bloch vector. We prove that for POVMs with coplanar Bloch vectors, they are join…
Frobenius structure on hypergeometric equations, p-adic polygamma values and p-adic L-values
Masanori Asakura, Kei Hagihara
Recently, Kedlaya proves certain formula describing explicitly the Frobenius structure on a hypergeometric equation. In this paper, we give a generalization of it. In our case, the…
The Hodge Realization of the Polylogarithm and the Shintani Generating Class for Totally Real Fields
Kenichi Bannai, Hohto Bekki, Kei Hagihara +3
In this article, we construct the Hodge realization of the polylogarithm class in the equivariant Deligne-Beilinson cohomology of a certain algebraic torus associated to a totally…
-adic Polylogarithms and -adic Hecke -functions for Totally Real Fields
Kenichi Bannai, Kei Hagihara, Kazuki Yamada +1
The purpose of this article is to newly define the -adic polylogarithm as an equivariant class in the cohomology of a certain infinite disjoint union of algebraic tori associate…
The Hodge realization of the polylogarithm on the product of multiplicative groups
Kenichi Bannai, Kei Hagihara, Kazuki Yamada +1
The purpose of this article is to describe explicitly the polylogarithm class in absolute Hodge cohomology of a product of multiplicative groups, in terms of the Bloch-Wigner-Ramak…
Canonical Equivariant Cohomology Classes Generating Zeta Values of Totally Real Fields
Kenichi Bannai, Kei Hagihara, Kazuki Yamada +1
It is known that the special values at nonpositive integers of a Dirichlet -function may be expressed using the generalized Bernoulli numbers, which are defined by a canonical g…
The global optimum of shallow neural network is attained by ridgelet transform
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda +4
We prove that the global minimum of the backpropagation (BP) training problem of neural networks with an arbitrary nonlinear activation is given by the ridgelet transform. A series…
Category of mixed plectic Hodge structures
Kenichi Bannai, Kei Hagihara, Shinichi Kobayashi +3
The purpose of this article is to investigate the properties of the category of mixed plectic Hodge structures defined by Nekovář and Scholl. We give an equivalent description of m…