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Updated: May 12, 2025

Setting Limits on Supersymmetry Using Simplified Models
07:46

Setting Limits on Supersymmetry Using Simplified Models

Published on: November 15, 2013

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在CMS实验中,使用机器学习技术重量化模拟事件

A Hayrapetyan1, A Tumasyan1,2, W Adam3

  • 1Yerevan Physics Institute, Yerevan, Armenia.

The European physical journal. C, Particles and fields
|May 9, 2025
PubMed
概括

机器学习重权缩减可以降低粒子物理模拟中的计算成本. 这种技术避免了重新模拟探测器响应,使得像大型强子对撞机 (LHC) 这样的实验能够更有效地分析数据.

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Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
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Weighted Mean00:57

Weighted Mean

While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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Censoring Survival Data

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Prediction Intervals01:03

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