Téléchargez le livre : Artificial Intelligence for Scientific Discoveries

Artificial Intelligence for Scientific Discoveries

Extracting Physical Concepts from Experimental Data Using Deep Learning

de

Éditeur :

Springer


Paru le : 2023-04-11



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
137,14 €
Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

badge apple Application Louise Reader
badge Android Application Louise Reader
Description

Will research soon be done by artificial intelligence, thereby making human researchers superfluous? This book explains modern approaches to discovering physical concepts with machine learning and elucidates their strengths and limitations. The automation of the creation of experimental setups and physical models, as well as model testing are discussed. The focus of the book is the automation of an important step of the model creation, namely finding a minimal number of natural parameters that contain sufficient information to make predictions about the considered system. The basic idea of this approach is to employ a deep learning architecture, SciNet, to model a simplified version of a physicist's reasoning process. SciNet finds the relevant physical parameters, like the mass of a particle, from experimental data and makes predictions based on the parameters found. The author demonstrates how to extract conceptual information from such parameters, e.g., Copernicus' conclusion that the solar system is heliocentric. 

 
Pages
170 pages
Collection
n.c
Parution
2023-04-11
Marque
Springer
EAN papier
9783031270185
EAN PDF
9783031270192
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
5304 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
137,14 €
EAN EPUB
9783031270192
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
19558 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
137,14 €

Raban Iten studied Physics and Mathematics at ETH Zürich, followed by a Ph.D. in quantum computation. During his Ph.D., he worked on using machine learning to discover physical concepts from experimental data of classical and quantum systems. This work was widely covered in the media and pointed out as a research highlight of 2019 by Nature Reviews Physics. Furthermore, he developed algorithms for quantum compilers and contributed to various open-source libraries for quantum computing.

 

Suggestions personnalisées