LEADER 02816nam 2200529 450 001 9910734331803321 005 20230726160923.0 010 $a1-009-40180-7 024 7 $a10.1017/9781009401807 035 $a(CKB)27558708600041 035 $a(UkCbUP)CR9781009401807 035 $a(NjHacI)9927558708600041 035 $a(EXLCZ)9927558708600041 100 $a20230622e20231984 fy| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 181 $csti$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRenormalization $ean introduction to renormalization, the renormalization group and the operator-product expansion /$fJohn C. Collins$b[electronic resource] 205 $a1st ed. 210 1$aCambridge :$cCambridge University Press,$d2023. 215 $a1 online resource (x, 380 pages) $cillustrations (black and white), digital, PDF file(s) 225 1 $aCambridge monographs on mathematical physics 300 $aPreviously issued in print: 1984. 311 $a9781009401760 320 $aIncludes bibliographical references and index. 327 $a1. Introduction; 2. Quantum field theory; 3. Basic examples; 4. Dimensional regularization; 5. Renormalization; 6. Composite operators; 7. Renormalization group; 8. Large-mass expansion; 9. Global symmetries; 10. Operator-product expansion; 11. Coordinate space; 12. Renormalization of gauge theories; 13. Anomalies; 14. Deep-inelastic scattering; References; Index. 330 8 $aMost of the numerical predictions of experimental phenomena in particle physics over the last decade have been made possible by the discovery and exploitation of the simplifications that can happen when phenomena are investigated on short distance and time scales. This book provides a coherent exposition of the techniques underlying these calculations. After reminding the reader of some basic properties of field theories, examples are used to explain the problems to be treated. Then the technique of dimensional regularization and the renormalization group. Finally a number of key applications are treated, culminating in the treatment of deeply inelastic scattering. 410 0$aCambridge monographs on mathematical physics. 606 $aRenormalization (Physics) 606 $aRenormalization group 606 $aParticles (Nuclear physics) 606 $aScattering (Physics) 615 0$aRenormalization (Physics) 615 0$aRenormalization group. 615 0$aParticles (Nuclear physics) 615 0$aScattering (Physics) 676 $a530.143 700 $aCollins$b John C$g(John Clements),$f1949-$045837 801 0$bStDuBDS 801 1$bStDuBDS 906 $aBOOK 912 $a9910734331803321 996 $aRenormalization$9189935 997 $aUNINA LEADER 03484nam 22005775 450 001 9910484473703321 005 20251113202214.0 010 $a3-319-93061-3 024 7 $a10.1007/978-3-319-93061-9 035 $a(CKB)4100000005248369 035 $a(DE-He213)978-3-319-93061-9 035 $a(MiAaPQ)EBC5452086 035 $a(PPN)22950177X 035 $a(EXLCZ)994100000005248369 100 $a20180713d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data for the Greater Good /$fedited by Ali Emrouznejad, Vincent Charles 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (X, 204 p. 55 illus., 34 illus. in color.) 225 1 $aStudies in Big Data,$x2197-6511 ;$v42 311 08$a3-319-93060-5 327 $aBig Data for the Greater Good: An Introduction -- Big Data Analytics and Ethnography: Together for the Greater Good -- Big Data: A Global Overview -- Big data for predictive analytics in high acuity health settings -- A Novel Big Data-Enabled Approach Individualizing and Optimizing Brain Disorder Rehabilitation -- Big Data in Agricultural and Food Research: Challenges and Opportunities of an integrated Big Data e-Infrastructure -- Green neighbourhoods: the role of big data in low voltage networks' planning -- Big Data Improves Visitor Experience at Local, State, and National Parks ? Natural Language Processing Applied to Customer Feedback -- Big Data and Sensitive Data. 330 $aThis book highlights some of the most fascinating current uses, thought-provoking changes, and biggest challenges that Big Data means for our society. The explosive growth of data and advances in Big Data analytics have created a new frontier for innovation, competition, productivity, and well-being in almost every sector of our society, as well as a source of immense economic and societal value. From the derivation of customer feedback-based insights to fraud detection and preserving privacy; better medical treatments; agriculture and food management; and establishing low-voltage networks ? many innovations for the greater good can stem from Big Data. Given the insights it provides, this book will be of interest to both researchers in the field of Big Data, and practitioners from various fields who intend to apply Big Data technologies to improve their strategic and operational decision-making processes. 410 0$aStudies in Big Data,$x2197-6511 ;$v42 606 $aComputational intelligence 606 $aQuantitative research 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aData Analysis and Big Data 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aQuantitative research. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aData Analysis and Big Data. 615 24$aArtificial Intelligence. 676 $a303.4833 702 $aEmrouznejad$b Ali$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aCharles$b Vincent$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484473703321 996 $aBig Data for the Greater Good$92844529 997 $aUNINA