Cosmological constraints on cosmic strings

随着有关宇宙结构的数据以不断增长的速度积累，宇宙学现在可以用来约束基本物理。我感兴趣的是使用星系勘测、宇宙微波背景(CMB)和21厘米宇宙学来寻找和约束粒子物理标准模型(SM)以外的新物理，特别是宇宙弦。*宇宙弦是线性拓扑缺陷，可以在SM的一大类扩展中形成。在超引力模型的背景下构建的许多膨胀情景导致在膨胀阶段结束时形成规范理论宇宙弦，而在一大类膜膨胀模型中，膨胀以形成可以稳定为宏观对象的宇宙超弦网络而结束。虽然宇宙弦不能成为原始起伏的主要来源，但它们仍然可以是次要来源。因此，寻找宇宙弦可以探测SM以外的粒子物理，能量范围与粒子加速器探测的能量范围是互补的。*弦的引力效应可以通过弦的张力来参数化，弦张力是一个无量纲常数，对于Grand Uniform模型，预计在1e-8和1e-6之间，对于宇宙超弦，预计在1e-12和1e-6之间。最可靠的实验极限来自普朗克合作对CMB角功率谱的测量，导致弦张力小于约1e-7。*近年来，人们进行了大量研究，以寻找对CMB和21厘米强度图中的宇宙弦进行更灵敏的探测。随着长长的宇宙弦移动，它们将物质聚集成过密集的尾流，扰乱了CMB的光，特别是21厘米的线。在这些地图中寻找宇宙弦时，已经提出了边缘和形状检测算法，如Canny算法，以及小波和曲线作为功率谱的替代方案。尽管前景看好，但在数值模拟地图上对这些提议的研究还没有比普朗克的研究得出明显更强的限制。此外，所有这些建议都涉及选择，目前尚不清楚不同的选择是否会改善检测。最后，上面的建议都没有在天空地图上找到字符串的位置。我们最近提出了一种对宇宙弦检测的贝叶斯解释，改进了这些缺点。在这里，我们提出了开发机器学习技术和神经网络的计划，以在星系调查、CMB和21厘米强度图中搜索宇宙弦。神经网络将在实际数据上使用之前，通过包含真实噪声的数值模拟来开发。我们希望要么找到弦的证据，要么确定弦的张力低于1e-12，从而限制SM的延伸。我们的计划将对培养下一代科学家产生重大影响。

With data about the universe's structure accumulating at an ever-increasing rate, cosmology can now be used to constrain fundamental physics. I am interested in using galaxy surveys, the cosmic microwave background (CMB), and 21 cm cosmology to search for and constrain new physics beyond the particle physics Standard Model (SM), in particular cosmic strings.******Cosmic strings are linear topological defects that can form in a large class of extensions of the SM. Many inflationary scenarios constructed in the context of supergravity models lead to the formation of gauge theory cosmic strings at the end of the inflationary phase, and in a large class of brane inflation models, inflation ends with the formation of a network of cosmic superstrings which can be stabilized as macroscopic objects. Whereas cosmic strings cannot be the dominant source of the primordial fluctuations they can still be a secondary source. Thus searching for cosmic strings probes particle physics beyond the SM in an energy range complementary to that probed by particle accelerators. ******The gravitational effects of the string can be parametrized by its string tension a dimensionless constant which is predicted to be between 1e-8 and 1e-6 for Grand Unified models, and between 1e-12 and 1e-6 for cosmic superstrings. The best robust experimental limit comes from the Planck collaboration's measurement of the CMB angular power spectrum leading to a string tension less than about 1e-7. ******In recent years much research has been done to find a more sensitive probe of cosmic strings in CMB and 21 cm intensity maps. As long cosmic strings move, they accrete matter into over-dense wakes which perturb the CMB light and the 21 cm line in particular. Edge and shape detection algorithms such as the Canny algorithm, as well as wavelets, and curvelets have been proposed as alternatives to the power spectrum in looking for cosmic strings in these maps. While promising, studies of these proposals on numerically simulated maps have not yet yielded significantly stronger limits than those from Planck. Furthermore, all these proposals involve choices and it remains unclear whether or not different choices would improve detection. Finally, none of the above proposals find the location of strings on sky maps. We recently proposed a Bayesian interpretation of cosmic string detection that improves on these shortcomings. Here we present our program to develop machine learning techniques and neural networks to search for cosmic strings in galaxy surveys, CMB, and 21 cm intensity maps. The neural networks will be developed with numerical simulation involving realistic noise, before being used on actual data. We hope to either find evidence for strings or determine that the string tension is below 1e-12 and thus constrain extensions of the SM. Our program will have a significant impact in the training of the next generation of scientists.