Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
The authors have performed a search for a charged partner of the X(3872) decaying to J/[psi][pi][sup [+-]][pi][sup 0]. The results set upper limits on the product branching fractions of B([bar B][sup 0]/B[sup 0] --> X[sup [+-]]K[sup [-+]], X[sup [+-]] --> J/[psi][sup [+-]][pi][sup 0]) 5.2 x 10[sup -6] and B(B[sup [+-]]) -- X[sup [+-]]K[sup 0][sub s], X[sup [+-]] --> J/[psi][sup [+-]][pi][sup 0]
Search for an X(3872) Charged Partner in the Decay Mode X- --] J/psi Pi- Pi0 in the B Meson Decays B0 --] X- K+ and B- --] X- Ks
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
The authors have performed a search for a charged partner of the X(3872) decaying to J/[psi][pi][sup [+-]][pi][sup 0]. The results set upper limits on the product branching fractions of B([bar B][sup 0]/B[sup 0] --> X[sup [+-]]K[sup [-+]], X[sup [+-]] --> J/[psi][sup [+-]][pi][sup 0]) 5.2 x 10[sup -6] and B(B[sup [+-]]) -- X[sup [+-]]K[sup 0][sub s], X[sup [+-]] --> J/[psi][sup [+-]][pi][sup 0]
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
The authors have performed a search for a charged partner of the X(3872) decaying to J/[psi][pi][sup [+-]][pi][sup 0]. The results set upper limits on the product branching fractions of B([bar B][sup 0]/B[sup 0] --> X[sup [+-]]K[sup [-+]], X[sup [+-]] --> J/[psi][sup [+-]][pi][sup 0]) 5.2 x 10[sup -6] and B(B[sup [+-]]) -- X[sup [+-]]K[sup 0][sub s], X[sup [+-]] --> J/[psi][sup [+-]][pi][sup 0]
Search for a Charged Partner of the X (3872) in the B Meson Decay B to X- K, X- to J/psi Pi- Pi0
Search for a Charged Partner of the X(3872) in B->J/[psi Pi Plus Or Minus Pi]0K with the Babar Detector
Author: Frank Winklmeier
Publisher:
ISBN:
Category : Mesons
Languages : en
Pages : 202
Book Description
Publisher:
ISBN:
Category : Mesons
Languages : en
Pages : 202
Book Description
Massive Stars
Author: Space Telescope Science Institute (U.S.). Symposium
Publisher: Cambridge University Press
ISBN: 0521762634
Category : Science
Languages : en
Pages : 253
Book Description
Presents observational and theoretical papers from world experts addressing the important role in astrophysics of massive stars.
Publisher: Cambridge University Press
ISBN: 0521762634
Category : Science
Languages : en
Pages : 253
Book Description
Presents observational and theoretical papers from world experts addressing the important role in astrophysics of massive stars.
Machine Learning in Chemistry
Author: Hugh M. Cartwright
Publisher: Royal Society of Chemistry
ISBN: 1788017897
Category : Science
Languages : en
Pages : 564
Book Description
Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.
Publisher: Royal Society of Chemistry
ISBN: 1788017897
Category : Science
Languages : en
Pages : 564
Book Description
Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.