Here is a (heavily biased!) list of random things I would recommend. I hope you find some useful suggestion(s) below.

Textbooks

• Dragan Huterer’s book, A Course in Cosmology: From Theory to Practice, provides the perfect balance (and connection) between theory and observation. If you are an undergrad or first-year grad student, I think this is a great starting point.

• Scott Dodelson’s and Fabian Schmidt’s Modern Cosmology (2nd edition) discusses both theories of CMB and LSS, and how to connect them to observation. The treatment of perturbations, starting from Bolztmann equations, is extremely comprehensive.

Online lectures

Cosmic Microwave Background

• Eiichiro Komatsu’s course on CMB within the IMPRS program 2020 can be found here. It provides an excellent starting point. Much more useful CMB materials on CMB can also be found on the same page.

• Wayne Hu’s tutorials on CMB and references therein is also a super helpful source to gain intuitions and excellent insights on physics of the CMB.

Large-scale structure

• Fabian’s lecture at the IV Joint ICTP-Trieste/ICTP-SAIFR School on Cosmology 2021 should provide just enough background about the formation of large-scale structure, covering both perturbation theory and N-body simulations.

Cosmology from large-scale structure

• Dragan’s lecture at the IV Joint ICTP-Trieste/ICTP-SAIFR School on Cosmology 2021 presents a very hands-on approach that will be super useful for students who are already familiar with python and jupyter.

Review articles

Cosmology from large-scale structure and galaxy redshift surveys

• Donghui Jeong’s PhD thesis provides a succint account that helped me out tremendously when I first started as a PhD student.

• Bernardeau et al. 2001 provides a very extensive review of LSS in the context of perturbation theory.

• Everything we know about galaxy bias (up to 2016-2019) was covered by this review by Vincent, Donghui and Fabian.

Sunyaev-Zel’dovich effect

• Physics behind the Sunyaev-Zel’dovich effect was discussed thoroughly in this review by M. Birkinshaw.

Bayesian sampling methods

• Hamiltonian Monte Carlo (HMC) sampling: Half of HMC practitioners learned HMC from Neal’s article, the other half learned from Betancourt’s article.

• Slice sampling: this article, in Neal’s words, was “written for statisticians, but of interest to physicists who use Monte Carlo methods”.

Code

• Dask provides a straightforward way to scale up your python implementation to handle big datasets while giving you a lot of control.
• CosmoSIS is a framework to analyze Weak Lensing survey data. Here is a manual installation guide for new developers.

General advice on doing research

I wholeheartedly recommend the following articles, which were suggested to me and all MPA PhD students by Eiichiro:

• Steven Weinberg’s Nature article, “Four golden lessons”.
• Martin’s Schwartz’s essay, The importance of stupidity in scientific research

Activities

Ann Arbor

• Kayak (along the Huron river)
• Ice skate (any lake during winter)
• Watch our football team play at the Michigan stadium

Munich

• Christmas markets (Christkindlmarkt): all of them
• Parks: Englischen Garten, Olympiapark (esp. during the cherry blossom or festival seasons), Luitpoldpark (next to Olympiapark, you can see the Alps from the top of the hill)
• Museums on Sundays
• Beer gardens: Hirschgarten or SEEHAUS in Englischen Garten
• Gelato: Der verrückte Eismacher - im Wunderland (they have beer and obatzda flavors!), True & 12
• Pâtisserie and/or chocolaterie: Widmann, Tanpopo, Andreas Muschler (in Freising not Munich, but it is worth it!)
• Billiards: Q-Billard