Kolmogorov-Smirnov test and its use for the identification of fireball fragmentation

被引:10
|
作者
Melo, Ivan [1 ,2 ]
Tomasik, Boris [3 ]
Torrieri, Giorgio [4 ]
Vogel, Sascha [5 ]
Bleicher, Marcus [5 ]
Korony, Samuel [2 ]
Gintner, Mikulas [1 ,2 ]
机构
[1] Zilinska Univ, Zilina 01026, Slovakia
[2] Univ Mateja Bela, Banska Bystrica 97401, Slovakia
[3] Czech Tech Univ, Fac Nucl Sci & Phys Engn, CR-11519 Prague, Czech Republic
[4] Goethe Univ Frankfurt, Frankfurt Inst Adv Studies, D-60438 Frankfurt, Germany
[5] Goethe Univ Frankfurt, Inst Theoret Phys, D-60438 Frankfurt, Germany
来源
PHYSICAL REVIEW C | 2009年 / 80卷 / 02期
关键词
QUARK-GLUON PLASMA; NUCLEUS-NUCLEUS COLLISIONS; FLUCTUATIONS; PERSPECTIVE; TRANSITION;
D O I
10.1103/PhysRevC.80.024904
中图分类号
O57 [原子核物理学、高能物理学];
学科分类号
070202 ;
摘要
We propose an application of the Kolmogorov-Smirnov test for rapidity distributions of individual events in ultrarelativistic heavy-ion collisions. The test is particularly suited to recognizing nonstatistical differences between the events. Thus when applied to a narrow centrality class it could indicate differences between events that would not be expected if all events evolved according to the same scenario. In particular, as an example we assume here a possible fragmentation of the fireball into smaller pieces at the quark/hadron phase transition. Quantitative studies are performed with a Monte Carlo model capable of simulating such a distribution of hadrons. We conclude that the Kolmogorov-Smirnov test is a very powerful tool for the identification of the fragmentation process.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] A Higher-Order Kolmogorov-Smirnov Test
    Sadhanala, Veeranjaneyulu
    Wang, Yu-Xiang
    Ramdas, Aaditya
    Tibshirani, Ryan J.
    22ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 89, 2019, 89
  • [32] The Performance Of Kolmogorov-Smirnov Statistic In Noise Identification
    Ma, Yingchao
    Gao, Yanping
    Han, Yu
    EQUIPMENT MANUFACTURING TECHNOLOGY, 2012, 422 : 342 - 346
  • [33] Application of Bootstrap Method in Kolmogorov-Smirnov Test
    Wang, Chengdong
    Zeng, Bo
    Shao, Jiye
    2011 INTERNATIONAL CONFERENCE ON QUALITY, RELIABILITY, RISK, MAINTENANCE, AND SAFETY ENGINEERING (ICQR2MSE), 2011, : 287 - 291
  • [34] Kolmogorov-Smirnov test for life test data with hybrid censoring
    Banerjee, Buddhananda
    Pradhan, Biswabrata
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2018, 47 (11) : 2590 - 2604
  • [35] Sequential detection of influenza epidemics by the Kolmogorov-Smirnov test
    Pau Closas
    Ermengol Coma
    Leonardo Méndez
    BMC Medical Informatics and Decision Making, 12
  • [37] Binary tree classifier based on Kolmogorov-Smirnov test
    Georgiev G.
    Valova I.
    Gueorguieva N.
    Smart Innovation, Systems and Technologies, 2010, 4 : 571 - 579
  • [38] Modulation Classification based on Modified Kolmogorov-Smirnov Test
    Azim, Ali Waqar
    Khalid, Syed Safwan
    Abrar, Shafayat
    2013 IEEE 9TH INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES (ICET 2013), 2013, : 176 - 181
  • [39] A MODIFIED KOLMOGOROV-SMIRNOV TEST SENSITIVE TO TAIL ALTERNATIVES
    MASON, DM
    SCHUENEMEYER, JH
    ANNALS OF STATISTICS, 1983, 11 (03): : 933 - 946
  • [40] Minimum Kolmogorov-Smirnov test statistic parameter estimates
    Weber, MD
    Leemis, LM
    Kincaid, RK
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2006, 76 (03) : 195 - 206