Resolving cosmological tensions with diverse data, novel theories and Bayesian machine learning

我们的宇宙膨胀得比我们预期的要快。宇宙学的标准模型预测的哈勃常数与我们测量的有很大的不同。这远不是一个问题，而是令人兴奋的，因为它表明需要一个新的宇宙模型。然而，尽管经过三年的努力，宇宙学家们仍然无法解决这个宇宙难题。首先，没有一个单一的理论解决方案能够令人满意地解决所有的差异。其次，从测量误差中分离新物理是一个具有挑战性的未解决问题。第三，我们的模拟和数据分析管道是在标准模型的背景下设计和调整的，即使是最精心设计的方法也会产生偏差。这个雄心勃勃的项目旨在解决上述三个问题，并揭示和建立下一个理论和数据分析的宇宙学范式。一个由PI承担的理论、推理和观察研究的联锁方案，三名博士后和四名博士生将在五年内致力于同时解决宇宙学理论和数据处理方面的紧张关系。该项目的主要目标是：（a）用新的宇宙标准模型和下一代数值技术解决宇宙学观测之间的紧张关系（B）建立可能性-自由推论是我们宇宙学分析工具包的核心，为未来大量宇宙学数据的冲击做好准备;及（c）汇集一套不同的宇宙学和粒子物理数据集，并将它们组织在一个连贯的统计框架内。这是一项重要而实质的研究工作，只有ERC的启动拨款才能支持。

Our Universe is expanding faster than we expected. The standard model of cosmology predicts a Hubble constant which differs substantially from what we measure it to be. Far from being a problem, this is exciting as it indicates the need for a new model of the Universe. Despite three years of effort however, cosmologists have been unable to resolve this cosmic conundrum.The reasons for this community failure are threefold. First, no single theoretical solution is capable of satisfactorily resolving all discrepancies. Second, disentangling new physics from measurement error is a challenging unsolved problem. Third, our simulation and data analysis pipelines have been designed and tuned in the context of the standard model, which can bias even the most carefully designed approach.This ambitious project proposes to resolve all three of the above and uncover and establish the next cosmological paradigm for theory and data analysis. An interlocking programme of theory, inference and observational research, undertaken by the PI, three postdocs and four PhD students over five years will aim to simultaneously resolve the tensions in both cosmological theories and data processing.The broad aims of the project are to (a) Resolve the tensions between cosmological observations with a new standard model of the universe and next-generation numerical techniques (b) Establish likelihood-free inference at the heart of our cosmological analysis toolkit in preparation for the future onslaught of big cosmological data, and (c) Bring together a diverse set of cosmological and particle physics datasets and organise them in a coherent statistical framework.This is an essential and substantial research effort which only an ERC starting grant can support.