語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Machine Learning at the Belle II Exp...
~
Keck, Thomas.
Machine Learning at the Belle II Experiment = The Full Event Interpretation and Its Validation on Belle Data /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Machine Learning at the Belle II Experiment/ by Thomas Keck.
其他題名:
The Full Event Interpretation and Its Validation on Belle Data /
作者:
Keck, Thomas.
面頁冊數:
XI, 174 p. 84 illus., 16 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Elementary particles (Physics). -
電子資源:
https://doi.org/10.1007/978-3-319-98249-6
ISBN:
9783319982496
Machine Learning at the Belle II Experiment = The Full Event Interpretation and Its Validation on Belle Data /
Keck, Thomas.
Machine Learning at the Belle II Experiment
The Full Event Interpretation and Its Validation on Belle Data /[electronic resource] :by Thomas Keck. - 1st ed. 2018. - XI, 174 p. 84 illus., 16 illus. in color.online resource. - Springer Theses, Recognizing Outstanding Ph.D. Research,2190-5053. - Springer Theses, Recognizing Outstanding Ph.D. Research,.
Introduction -- From Belle to Belle II -- Multivariate Analysis Algorithms -- Full Event Interpretation -- B tau mu -- Conclusion.
This book explores how machine learning can be used to improve the efficiency of expensive fundamental science experiments. The first part introduces the Belle and Belle II experiments, providing a detailed description of the Belle to Belle II data conversion tool, currently used by many analysts. The second part covers machine learning in high-energy physics, discussing the Belle II machine learning infrastructure and selected algorithms in detail. Furthermore, it examines several machine learning techniques that can be used to control and reduce systematic uncertainties. The third part investigates the important exclusive B tagging technique, unique to physics experiments operating at the Υ resonances, and studies in-depth the novel Full Event Interpretation algorithm, which doubles the maximum tag-side efficiency of its predecessor. The fourth part presents a complete measurement of the branching fraction of the rare leptonic B decay “B→tau nu”, which is used to validate the algorithms discussed in previous parts.
ISBN: 9783319982496
Standard No.: 10.1007/978-3-319-98249-6doiSubjects--Topical Terms:
1254811
Elementary particles (Physics).
LC Class. No.: QC793-793.5
Dewey Class. No.: 539.72
Machine Learning at the Belle II Experiment = The Full Event Interpretation and Its Validation on Belle Data /
LDR
:02642nam a22004095i 4500
001
991099
003
DE-He213
005
20200630041519.0
007
cr nn 008mamaa
008
201225s2018 gw | s |||| 0|eng d
020
$a
9783319982496
$9
978-3-319-98249-6
024
7
$a
10.1007/978-3-319-98249-6
$2
doi
035
$a
978-3-319-98249-6
050
4
$a
QC793-793.5
050
4
$a
QC174.45-174.52
072
7
$a
PHQ
$2
bicssc
072
7
$a
SCI051000
$2
bisacsh
072
7
$a
PHQ
$2
thema
082
0 4
$a
539.72
$2
23
100
1
$a
Keck, Thomas.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1211932
245
1 0
$a
Machine Learning at the Belle II Experiment
$h
[electronic resource] :
$b
The Full Event Interpretation and Its Validation on Belle Data /
$c
by Thomas Keck.
250
$a
1st ed. 2018.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2018.
300
$a
XI, 174 p. 84 illus., 16 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Springer Theses, Recognizing Outstanding Ph.D. Research,
$x
2190-5053
505
0
$a
Introduction -- From Belle to Belle II -- Multivariate Analysis Algorithms -- Full Event Interpretation -- B tau mu -- Conclusion.
520
$a
This book explores how machine learning can be used to improve the efficiency of expensive fundamental science experiments. The first part introduces the Belle and Belle II experiments, providing a detailed description of the Belle to Belle II data conversion tool, currently used by many analysts. The second part covers machine learning in high-energy physics, discussing the Belle II machine learning infrastructure and selected algorithms in detail. Furthermore, it examines several machine learning techniques that can be used to control and reduce systematic uncertainties. The third part investigates the important exclusive B tagging technique, unique to physics experiments operating at the Υ resonances, and studies in-depth the novel Full Event Interpretation algorithm, which doubles the maximum tag-side efficiency of its predecessor. The fourth part presents a complete measurement of the branching fraction of the rare leptonic B decay “B→tau nu”, which is used to validate the algorithms discussed in previous parts.
650
0
$a
Elementary particles (Physics).
$3
1254811
650
0
$a
Quantum field theory.
$3
579915
650
0
$a
Artificial intelligence.
$3
559380
650
0
$a
Sociophysics.
$3
890761
650
0
$a
Econophysics.
$3
796705
650
0
$a
Physical measurements.
$3
902742
650
0
$a
Measurement .
$3
1253766
650
1 4
$a
Elementary Particles, Quantum Field Theory.
$3
672693
650
2 4
$a
Artificial Intelligence.
$3
646849
650
2 4
$a
Data-driven Science, Modeling and Theory Building.
$3
1112983
650
2 4
$a
Measurement Science and Instrumentation.
$3
769080
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783319982489
776
0 8
$i
Printed edition:
$z
9783319982502
830
0
$a
Springer Theses, Recognizing Outstanding Ph.D. Research,
$x
2190-5053
$3
1253569
856
4 0
$u
https://doi.org/10.1007/978-3-319-98249-6
912
$a
ZDB-2-PHA
912
$a
ZDB-2-SXP
950
$a
Physics and Astronomy (SpringerNature-11651)
950
$a
Physics and Astronomy (R0) (SpringerNature-43715)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入