Exploring the Deep Universe by Computational Analysis of Data from Observations

在成功的标准Lambda-CDM形式主义的背景下，大质量星系的形成和演化是相当好的理解。然而，这种对宇宙演化的模拟给非常微弱的星系的体制带来了严重的挑战，包括被称为卫星丢失、太大而不能倒的问题，以及卫星星系的平面。随着天文测量产生了大量优秀的数据，随着新的任务计划产生更多甚至更高质量的数据，我们有一个独特的机会来解决这些问题。要做到这一点，我们需要信息技术的创新发展。在EDUCADO(通过对观测数据进行计算分析来探索深宇宙)中，我们聚集了来自不同学科和部门的专家，这是天文学和计算机科学交叉领域的密集合作。我们将培养10名博士生开发各种高质量的方法，解决形成所需的最薄弱的结构。我们将可靠地、可重复地从新的大面积观测中探测到前所未有数量的最微弱的可观测星系。我们将研究各类矮星系的大样本的形态、数量和分布，并比较不同环境中的矮星系数量和属性。我们将用星系形成和演化的宇宙学模型来对抗这一结果。最后，我们将对银河系和本星系群进行详细、有原则和稳健的模拟和观测，以与其他环境中的矮小星系进行比较。EDUCADO将提供一个全面的跨学科、跨部门和国际培训方案，包括在我们的11个联系伙伴之一借调到每个华盛顿特区。我们将提供一种新的、可持续的方式，培养具有跨学科和跨部门数据科学专业知识的博士科学家，这是欧洲未来竞争力的必要条件。

The formation and evolution of massive galaxies is reasonably well understood in the context of the successful standard lambda-CDMformalism. Such simulations of cosmic evolution, however, lead to serious challenges in the regime of the very faint galaxies,including the problems referred to as missing satellites, too big to fail, and planes of satellite galaxies. With the massive amounts ofexcellent data being produced by astronomical surveys, and with new missions scheduled to produce more data of even betterquality, we have a unique chance to solve these problems. To do this, we require innovative developments in information technology.In EDUCADO (Exploring the Deep Universe by Computational Analysis of Data from Observations), an intensive collaboration at theintersection of astronomy and computer science, we bring together experts from different disciplines and sectors. We will train 10Doctoral Candidates in the development of a variety of high-quality methods, needed to address the formation of the fainteststructures. We will reliably and reproducibly detect unprecedented numbers of the faintest observable galaxies from new large-areasurveys. We will study the morphology, populations, and distribution of large samples of various classes of dwarf galaxies andcompare dwarf galaxy populations and properties across different environments. We will confront the results with cosmologicalmodels of galaxy formation and evolution. Finally, we will perform detailed, principled, and robust simulations and observations ofthe Milky Way and the Local Group to compare with dwarf galaxies in other environments. EDUCADO will deliver a comprehensiveinterdisciplinary, intersectoral, and international training programme including a secondment at one of our 11 associated partners foreach DC. We will provide a fresh and sustainable way of training PhD scientists with interdisciplinary and intersectoral data scienceexpertise, a requisite for future European competitiveness.