Detection of Phase Transition via Convolutional Neural Networks

被引：128

作者：

Tanaka, Akinori ^{[1
]}

Tomiya, Akio ^{[2
,3
]}

机构：

[1] RIKEN, Interdisciplinary Math & Computat Collaborat Team, Wako, Saitama 3510198, Japan

[2] Cent China Normal Univ, Key Lab Quark & Lepton Phys MOE, Wuhan 430079, Peoples R China

[3] Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China

来源：

JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN | 2017年 / 86卷 / 06期

关键词：

D O I：

10.7566/JPSJ.86.063001

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

A convolutional neural network (CNN) is designed to study correlation between the temperature and the spin configuration of the two-dimensional Ising model. Our CNN is able to find the characteristic feature of the phase transition without prior knowledge. Also a novel order parameter on the basis of the CNN is introduced to identify the location of the critical temperature; the result is found to be consistent with the exact value.

引用

页数：4

共 50 条

[21] Shallow buried improvised explosive device detection via convolutional neural networks
Colreavy-Donnelly, Simon
Caraffini, Fabio
Kuhn, Stefan
Gongora, Mario
Florez-Lozano, Johana
Parra, Carlos
INTEGRATED COMPUTER-AIDED ENGINEERING, 2020, 27 (04) : 403 - 416
[22] Lumen-based Detection of Prostate Cancer via Convolutional Neural Networks
Kwak, Jin Tae
Hewitt, Stephen M.
MEDICAL IMAGING 2017: DIGITAL PATHOLOGY, 2017, 10140
[23] Object Detection from the Video Taken by Drone via Convolutional Neural Networks
Sun, Chenfan
Zhan, Wei
She, Jinhiu
Zhang, Yangyang
MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020 (2020)
[24] Bone Age Detection via Carpogram Analysis using Convolutional Neural Networks
Torres, Felipe
Alejandra Bravo, Maria
Salinas, Emmanuel
Triana, Gustavo
Arbelaez, Pablo
13TH INTERNATIONAL CONFERENCE ON MEDICAL INFORMATION PROCESSING AND ANALYSIS, 2017, 10572
[25] Object Detection for Unmanned Aerial Vehicle Camera via Convolutional Neural Networks
Saetchnikov I.V.
Tcherniavskaia E.A.
Skakun V.V.
IEEE Journal on Miniaturization for Air and Space Systems, 2021, 2 (02): : 98 - 103
[26] Automatic detection of human faces in color images via convolutional neural networks
Sang, Haitao (sanghaitao79@163.com), 2016, ICIC Express Letters Office (07):
[27] Compressing Convolutional Neural Networks via Factorized Convolutional Filters
Li, Tuanhui
Wu, Baoyuan
Yang, Yujiu
Fan, Yanbo
Zhang, Yong
Liu, Wei
2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 3972 - 3981
[28] Convolutional Neural Networks Analyzed via Convolutional Sparse Coding
Papyan, Vardan
Romano, Yaniv
Elad, Michael
JOURNAL OF MACHINE LEARNING RESEARCH, 2017, 18 : 1 - 52
[29] The Importance of the Instantaneous Phase for Pace Detection using Simple Convolutional Neural Networks
Tapia, Luis Sanchez
Pattichis, Marios S.
Celedon-Pattichis, Sylvia
LopezLeiva, Carlos
2020 IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION (SSIAI 2020), 2020, : 9 - 12
[30] Pansharpening via Unsupervised Convolutional Neural Networks
Luo, Shuyue
Zhou, Shangbo
Feng, Yong
Xie, Jiangan
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 13 : 4295 - 4310

← 1 2 3 4 5 →