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Dark matter: evidence, theory and constraints

24 January 2025

Dark Matter: Evidence, Theory and Constraints, by David J E Marsh, David Ellis and Viraf M Mehta, Princeton University Press

Dark Matter: Evidence, Theory and Constraints

Cold non-baryonic dark matter appears to make up 85% of the matter and 25% of the energy in our universe. However, we don’t yet know what it is. As the opening of many research proposals state, “The nature of dark matter is one of the major open questions in physics.”

The evidence for dark matter comes from astronomical and cosmological observations. Theoretical particle physics provides us with various well motivated candidates, such as weakly interacting massive particles (WIMPs), axions and primordial black holes. Each has different experimental and observational signatures and a wide range of searches are taking place. Dark-matter research spans a very broad range of topics and methods. This makes it a challenging research field to enter and master. Dark Matter: Evidence, Theory and Constraints by David Marsh, David Ellis and Viraf Mehta, the latest addition to the Princeton Series in Astrophysics, clearly presents the relevant essentials of all of these areas.

The book starts with a brief history of dark matter and some warm-up calculations involving units. Part one outlines the evidence for dark matter, on scales ranging from individual galaxies to the entire universe. It compactly summarises the essential background material, including cosmological perturbation theory.

Part two focuses on theories of dark matter. After an overview of the Standard Model of particle physics, it covers three candidates with very different motivations, properties and phenomenology: WIMPs, axions and primordial black holes. Part three then covers both direct and indirect searches for these candidates. I particularly like the schematic illustrations of experiments; they should be helpful for theorists who want to (and should!) understand the essentials of experimental searches.

The main content finishes with a brief overview of other dark-matter candidates. Some of these arguably merit more extensive coverage, in particular sterile neutrinos. The book ends with extensive recommendations for further reading, including textbooks, review papers and key research papers.

Dark-matter research spans a broad range of topics and methods, making it a challenging field to master

The one thing I would argue with is the claim in the introduction that dark matter has already been discovered. I agree with the authors that the evidence for dark matter is strong and currently cannot all be explained by modified gravity theories. However, given that all of the evidence for dark matter comes from its gravitational effects, I’m open to the possibility that our understanding of gravity is incorrect or incomplete. The authors are also more positive than I am about the prospects for dark-matter detection in the near future, claiming that we will soon know which dark-matter candidates exist “in the real pantheon of nature”. Optimism is a good thing, but this is a promise that dark-matter researchers (myself included…) have now been making for several decades.

The conversational writing style is engaging and easy to read. The annotation of equations with explanatory text is novel and helpful, and  the inclusion of numerous diagrams – simple and illustrative where possible and complex when called for – aids understanding. The attention to detail is impressive. I reviewed a draft copy for the publishers, and all of my comments and suggestions have been addressed in detail.

This book will be extremely useful to newcomers to the field, and I recommend it strongly to PhD students and undergraduate research students. It is particularly well suited as a companion to a lecture course, with numerous quizzes, problems and online materials, including numerical calculations and plots using Jupyter notebooks. It will also be useful to those who wish to broaden or extend their research interests, for instance to a different dark-matter candidate.

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