HIV and AIDS have long been problematized in the People’s Republic of China as objects of governance in political frameworks and institutions. The state’s attitudes towards health programs have, nevertheless, changed significantly during the 21st century. Pilot programs at the beginning of the century, which focused on underground sex workers, have now developed into the roll-out of a nationwide program, with supportive legislation and broadcast media publicity. 
This book therefore examines China’s evolving AIDS response, providing an up to date investigation into the positions and practices of the state. It explains the origins, rationales and implementation of initiatives focused on female sex workers and explores the extension of such initiatives to include other populations identified as key to ending the AIDS epidemic, especially homosexual men and rural-to-urban migrant labourers. Ultimately, through an analysis of the different approaches to the governance of commercial sex and sexual health, Governing HIV in China concludes by considering the challenges raised by China’s commitment to the United Nations’ vision of ending AIDS as a global health threat by 2030. 
This book will be useful for students and scholars of Social Policy, Public Health Policy and Chinese Studies.

Governing HIV in China (Routledge Studies on China in Transition)

Jeffreys, Elaine

Su, Gang

Reference

Routledge

Tensor Network Contractions

Science & Math

Lewenstein, Maciej

Tagliacozzo, Luca

Physics

Saint Philip Street Press

Tensor network is a fundamental mathematical tool with a huge range of applications in physics, such as condensed matter physics, statistic physics, high energy physics, and quantum information sciences. This open access book aims to explain the tensor network contraction approaches in a systematic way, from the basic definitions to the important applications. This book is also useful to those who apply tensor networks in areas beyond physics, such as machine learning and the big-data analysis. Tensor network originates from the numerical renormalization group approach proposed by K. G. Wilson in 1975. Through a rapid development in the last two decades, tensor network has become a powerful numerical tool that can efficiently simulate a wide range of scientific problems, with particular success in quantum many-body physics. Varieties of tensor network algorithms have been proposed for different problems. However, the connections among different algorithms are not well discussed or reviewed. To fill this gap, this book explains the fundamental concepts and basic ideas that connect and/or unify different strategies of the tensor network contraction algorithms. In addition, some of the recent progresses in dealing with tensor decomposition techniques and quantum simulations are also represented in this book to help the readers to better understand tensor network. This open access book is intended for graduated students, but can also be used as a professional book for researchers in the related fields. To understand most of the contents in the book, only basic knowledge of quantum mechanics and linear algebra is required. In order to fully understand some advanced parts, the reader will need to be familiar with notion of condensed matter physics and quantum information, that however are not necessary to understand the main parts of the book. This book is a good source for non-specialists on quantum physics to understand tensor network algorithms and the related mathematics. 
This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Governing HIV in China: Commercial Sex, Homosexuality and Rural-to-Urban Migration (Routledge Studies on China in Transition)

Tensor network is a fundamental mathematical tool with a huge range of applications in physics, such as condensed matter physics, statistic physics, high energy physics, and quantum information sciences. This open access book aims to explain the tensor network contraction approaches in a systematic way, from the basic definitions to the important applications. This book is also useful to those who apply tensor networks in areas beyond physics, such as machine learning and the big-data analysis. &nbsp; Tensor network originates from the numerical renormalization group approach proposed by K. G. Wilson in 1975. Through a rapid development in the last two decades, tensor network has become a powerful numerical tool that can efficiently simulate a wide range of scientific problems, with particular success in quantum many-body physics. Varieties of tensor network algorithms have been proposed for different problems. However, the connections among different algorithms are not well discussed or reviewed. To fill this gap, this book explains the fundamental concepts and basic ideas that connect and/or unify different strategies of the tensor network contraction algorithms. In addition, some of the recent progresses in dealing with tensor decomposition techniques and quantum simulations are also represented in this book to help the readers to better understand tensor network. &nbsp; This open access book is intended for graduated students, but can also be used as a professional book for researchers in the related fields. To understand most of the contents in the book, only basic knowledge of quantum mechanics and linear algebra is required. In order to fully understand some advanced parts, the reader will need to be familiar with notion of condensed matter physics and quantum information, that however are not necessary to understand the main parts of the book. This book is a good source for non-specialists on quantum physics to understand tensor network algorithms and the related mathematics. &nbsp; &nbsp;

Tensor Network Contractions: Methods and Applications to Quantum Many-Body Systems (Lecture Notes in Physics)

Computers & Technology

CHEN, XI

Peng, Cheng

Ran, Shi-Ju

Tirrito, Emanuele

Computer Science

Springer

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