AI for physics
Material type:
TextSeries: AI for EverythingPublication details: Boca Raton : CRC Press, 2023. Description: xviii, 129 pages : 10 B/W IllustrationsISBN: 9781032151694Subject(s): Physics -- Data processing | Machine learning | Artificial intelligenceDDC classification: 53:004.8 Online resources: Table of content | Reviews Summary: Written in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences. Focusing in particular on AI's ability to extract patterns from data, known as machine learning (ML), the book includes a chapter on important machine learning algorithms and their respective applications in physics. It then explores the use of ML across a number of important sub-fields in more detail, ranging from particle, molecular and condensed matter physics, to astrophysics, cosmology and the theory of everything. The book covers such applications as the search for new particles and the detection of gravitational waves from the merging of black holes, and concludes by discussing what the future may hold.
| Item type | Current library | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
Book
|
NISER LIBRARY | 53:004.8 KNE-A (Browse shelf(Opens below)) | Available | 25767 |
Browsing NISER LIBRARY shelves Close shelf browser (Hides shelf browser)
| 53:004.01 LAN-C Computational problems for physics : with guided solutions using python | 53:004.42 CHA-C Computer applications in physics with Fortran, Basic and C | 53:004.42 CHA-C Computer applications in physics with Fortran, Basic and C | 53:004.8 KNE-A AI for physics | 53:004.85 BOL-M Machine learning : a physicist perspective | 53:004.85 CUN-M Machine learning for the physical sciences : fundamentals and prototyping with Julia | 530(076.5) SQU-P Practical physics |
Includes bibliographical references and index.
Written in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences. Focusing in particular on AI's ability to extract patterns from data, known as machine learning (ML), the book includes a chapter on important machine learning algorithms and their respective applications in physics. It then explores the use of ML across a number of important sub-fields in more detail, ranging from particle, molecular and condensed matter physics, to astrophysics, cosmology and the theory of everything. The book covers such applications as the search for new particles and the detection of gravitational waves from the merging of black holes, and concludes by discussing what the future may hold.
There are no comments on this title.