Cosmological constraints on cosmic strings

随着有关宇宙结构的数据以越来越快的速度积累，宇宙学现在可以用来约束基础物理学。我感兴趣的是使用星系巡天、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）之外的新物理，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暴胀场景导致在暴胀阶段结束时形成规范理论宇宙弦，而在一大类膜暴胀模型中，暴胀以形成宇宙超弦网络而结束，这些超弦网络可以稳定为宏观物体。虽然宇宙弦不可能是原初波动的主要来源，但它们仍然可以是次要来源。因此，寻找宇宙弦探测了SM之外的粒子物理学，其能量范围与粒子加速器探测的能量范围互补。 ** 弦的引力效应可以通过它的弦张力来参数化，弦张力是一个无量纲常数，对于大统一模型来说，它预计在1 e-8和1 e-6之间，对于宇宙超弦来说，它预计在1 e-12和1 e-6之间。最好的实验极限来自普朗克合作组对CMB角功率谱的测量，导致弦张力小于1 e-7。** 近年来，人们做了大量的研究，以在CMB和21 cm强度图中找到更灵敏的宇宙弦探测器。 当长的宇宙弦移动时，它们将物质吸积成过密的尾流，这会干扰CMB光，特别是21厘米的线。边缘和形状检测算法，如Canny算法，以及小波和曲波已被提出作为替代功率谱在寻找宇宙弦在这些地图。虽然很有希望，但对这些建议在数值模拟地图上的研究还没有产生比普朗克更强的限制。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弦的位置。我们最近提出了一个宇宙弦探测的贝叶斯解释，改进了这些缺点。在这里，我们提出了我们的程序来开发机器学习技术和神经网络，以搜索星系巡天，CMB和21厘米强度图中的宇宙弦。在用于实际数据之前，神经网络将通过涉及现实噪声的数值模拟来开发。我们希望找到弦的证据，或者确定弦的张力低于1 e-12，从而限制SM的扩展。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.