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arXiv 1809.08892nucl-exhep-exnucl-th
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重离子碰撞实验中有限统计量对高阶累积量测量的影响

Effect of limited statistics on higher order cumulants measurement in heavy-ion collision experiments

Ashish Pandav, Debasish Mallick, Bedangadas Mohanty

摘要:

假设质子和反质子分布服从泊松分布和二项分布,初始参数由两个最高质心能量的实验结果确定,研究了有限的统计量对测量净质子分布不同阶累积量的影响在相对论重离子对撞机(RHIC)上测量了最中心($0-5$ %)Au $+$ Au碰撞中的($\sqrt{s_{\mathrm{NN}}}=200$和$62.4$ GeV)电子能谱。在该模拟中,我们观察到高阶累积量的中心值对事件样本大小具有很强的依赖性,并且由于统计随机性,高阶累积量的中心值可能变为负值。我们还提出了一个研究的累积量的统计误差的确定使用德尔塔定理,自助法和子群方法,并验证了它们的适用性,采用Monte Carlo程序。基于我们的研究,我们发现,自助法提供了一个强大的方法来估计高阶累积量的统计误差。我们还提出了排除限制的最小事件统计所需的累积量的测定,如果信号强度(相变或临界点)是在一个水平的$5$ %和$10$ %以上的统计水平。这一研究将有助于实验获得所需的最小事件统计量和选择合适的高阶累积量测量的统计误差估计方法。

英文摘要:

We have studied the effect of limited statistics of data on measurement of the different order of cumulants of net-proton distribution assuming that the proton and antiproton distributions follow Possionian and Binomial distributions with initial parameters determined from experimental results for two top center of mass energies ($\sqrt{s_{\mathrm{NN}}}=200$ and $62.4$ GeV) in most central ($0-5$%) Au$+$Au collisions at Relativistic Heavy Ion Collider (RHIC). In this simulation, we observe that the central values for higher order cumulants have a strong dependence on event sample size and due to statistical randomness the central values of higher order cumulants could become negative. We also present a study on the determination of the statistical error on cumulants using delta theorem, bootstrap and sub-group methods and verified their suitability by employing a Monte Carlo procedure. Based on our study we find that the bootstrap method provides a robust way for statistical error estimation on high order cumulants. We also present the exclusion limits on the minimum event statistics needed for determination of cumulants if the signal strength (phase transition or critical point) is at a level of $5$% and $10$% above the statistical level. This study will help the experiments to arrive at the minimum required event statistics and choice of proper method for statistical error estimation for high order cumulant measurements.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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