Sa1993a Reduced Expression of Prostaglandin Transporter Promotes Angiogenesis in Gastric Cancer

Takeda, Shogo; Tanigawa, Tetsuya; Watanabe, Toshio; Tatsuwaki, Hiroshi; Nadatani, Yuji; Otani, Koji; Tanaka, Fumio; Kamata, Noriko; Yamagami, Hirokazu; Shiba, Masatsugu; Tominaga, Kazunari; Fujiwara, Yasuhiro; Muguruma, Kazuya; Hirakawa, Kosei

doi:10.1016/s0016-5085(15)31267-1

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2019

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A striking feature of the tensor network method is that it is free of the sign problem. With this property, the method attracts attention beyond condensedmatter physics [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31]. There are, in fact, many interesting models which are suffering from the sign problem in high-energy physics: QCD with finite quark density, the θ vacuum of QCD, chiral gauge theory, the supersymmetric model, and so on.…”

Section: Introductionmentioning

confidence: 99%

Tensor renormalization group algorithms with a projective truncation method

2019

View full text Add to dashboard Cite

We apply the projective truncation technique to the tensor renormalization group (TRG) algorithm in order to reduce the computational cost from O(χ 6 ) to O(χ 5 ), where χ is the bond dimension, and propose three kinds of algorithms for demonstration. On the other hand, the technique causes a systematic error due to the incompleteness of a projector composed of isometries, and in addition requires iteration steps to determine the isometries. Nevertheless, we find that the accuracy of the free energy for the Ising model on a square lattice is recovered to the level of TRG with a few iteration steps even at the critical temperature for χ = 32, 48, and 64.

show abstract