HEPfit is a flexible open-source tool which, given the Standard Model or any of its extensions, allows to (i) fit the model parameters to a given set of experimental observables; (ii) obtain predictions for observables. HEPfit can be used either in Monte Carlo mode, to perform a Bayesian Markov Chain Monte Carlo analysis of a given model, or as a library, to obtain predictions of observables for a given point in the parameter space of the model, allowing HEPfit to be used in any statistical framework. In the present version, around a thousand observables have been implemented in the Standard Model and in several new physics scenarios. In this paper, we describe the general structure of the code as well as models and observables implemented in the current release.

中文翻译：

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HEPfit：将高能物理模型上的间接约束和直接约束相结合的代码

HEPfit是一种灵活的开源工具，在提供标准模型或其任何扩展的情况下，它允许（i）将模型参数拟合到一组给定的实验可观察量；（ii）获得可观察物的预测。HEPfit可以在蒙特卡洛模式下使用，以执行一个给定的模型的马尔可夫贝叶斯链蒙特卡洛分析，或作为一个库，以获得用于在模型的参数空间中的给定点观测值的预测，从而允许HEPfit是用于任何统计框架。在当前版本中，已经在标准模型和几种新的物理方案中实现了约一千个可观测值。在本文中，我们描述了代码的一般结构以及当前版本中实现的模型和可观察对象。