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arXiv 1408.0150hep-phnucl-exnucl-th
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质子半径的贝叶斯推断

The Proton Radius from Bayesian Inference

Krzysztof M. Graczyk, Cezary Juszczak

摘要:

利用贝叶斯统计方法,从弹性$ep$散射数据中提取质子半径值,并与模型无关。为了实现这一目标,大量的参数化(相当于神经网络计划)被认为是他们的条件概率$P(\mathrm{parametrization}\,|\,\mathrm{data})$,而不是使用最小误差标准和排名。结果得到了最可能的质子半径值($r_E^p=0.899\pm 0.003$ fm,$r_M^p=0.879\pm 0.007$ fm),并估计了由于参数化选择自由度而引起的系统误差。校正双光子交换效应的数据对于获得$r_E^p$和$r_M^p$值之间的一致性是重要的。结果不同意最近的μ子原子测量。

英文摘要:

The methods of Bayesian statistics are used to extract the value of the proton radius from the elastic $ep$ scattering data in a model independent way. To achieve that goal a large number of parametrizations (equivalent to neural network schemes) are considered and ranked by their conditional probability $P(\mathrm{parametrization}\,|\,\mathrm{data})$ instead of using the minimal error criterion. As a result the most probable proton radii values ($r_E^p=0.899\pm 0.003$ fm, $r_M^p=0.879\pm 0.007$ fm) are obtained and systematic error due to freedom in the choice of parametrization is estimated. Correcting the data for the two photon exchange effect turns out to be important to obtain the agreement between the $r_E^p$ and $r_M^p$ values. The results disagree with recent muonic atom 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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