Semidefinite Programming in Quantum Information Science
By (author) Paul Skrzypczyk, Daniel Cavalcanti

Publication date:
07 March 2023Length of book:
125 pagesPublisher
Institute Of Physics PublishingDimensions:
254x178mm7x10"
ISBN-13: 9780750333412
Semidefinite programs (SDPs) are a class of optimisation problems that find application in numerous areas of physics, engineering and mathematics. Semidefinite programming is particularly suited to problems in quantum physics and quantum information science. Following a review of the theory of semidefinite programming, the book proceeds to describe how it can be used to address a wide range of important problems from across quantum information science. Specific applications include quantum state, measurement, and channel estimation and discrimination, entanglement detection and quantification, quantum distance measures, and measurement incompatibility. Though SDPs have become an increasingly important tool in quantum information science it’s not yet the kind of mathematics students learn routinely. Assuming only a basic knowledge of linear algebra and quantum physics and quantum information, this graduate-level book provides a unified and accessible presentation of one of the key numerical methods used in quantum information science. Whilst the focus is on the theoretical machinery of SDPs, the authors have provided an accompanying GitHub repository containing example code, covering some of the SDPs studied in this book.
Key features
- Accessible for graduate students in science and mathematics
- A unified and accessible presentation of one of the key numerical methods used in quantum information science
- Written by leading researchers on the topic
- Accompanying GitHub repository with sample code
"SDP is becoming an increasingly important tool in quantum information science. The techniques are ‘standard for experts’ but they are not taught routinely … a dedicated treatise introducing this will be a great resource for the years to come … The authors are among the very best in this field."- Nicolas Brunner, Université de Genève.