Skip to main content

The Cosmic Web - J. Richard Gott ****

This is a book about the large-scale structure of the universe. It’s a subject Richard Gott is particularly well qualified to talk about, having been associated with it since the 1970s. When he was still a graduate student he did pioneering work on the gravitational clumping of galaxies into galaxy clusters. Initially it was believed that this clumping tendency would repeat itself in an ever-ascending hierarchy, with stars clumping into galaxies, galaxies into clusters, clusters into superclusters and so on up to the very largest scales. In time, however, both observational and theoretical work led to a much more complex picture – the ‘cosmic web’ of the book’s title.

Topologically, the universe resembles a giant sea sponge. Unlike the hierarchical model, the high density concentrations of matter (corresponding to the body of the sponge) are not isolated clumps, but a single intricately connected structure. At the same time, the low density ‘voids’ running through it are likewise continuously connected – in contrast to the holes in a Swiss cheese, which was another early model that had to be discarded. Gott was among the first people to recognize the sponge-like structure of the universe – in part because, as a precocious high-school student back in the 1960s, he had done a science fair project on topological models of exactly that kind.

There’s no question that Gott is one of the world’s leading experts in this subject – but is he the best person to write a popular science book about it? I think the answer is a qualified ‘yes’. I really enjoyed his writing style, which is as lucid and unadorned as I’ve ever come across in an academic author. The theory never gets too difficult, either – mainly classical dynamics and statistics, with no relativistic or quantum complications. Nevertheless, Gott is not one of those writers who pretends you can have mathematics-free physics. There are no actual equations (except in the small print at the end of the book), but there are plenty of graphs, Greek letters and powers-of-ten numbers. This is not a book for people who are scared of such things.

At one point, Gott recounts an amusing anecdote he heard from the great Russian physicist Yakov Zeldovich, highlighting the benefits of using the median rather than the mean as a statistical measure. Yet he tells it to the reader exactly the way Zeldovich told it to him – without explaining how the mean and median are defined, or what they are used for. If those things are second nature to you, then you’ll appreciate the anecdote… and you’ll probably enjoy the whole book, too. If not, then you may find it heavy going.

This is the sort of book I would have loved when I was an undergraduate, or possibly even as a mind-stretching read in high school. It’s a young audience of future scientists who will probably get the most out of it today – not just for the picture it paints of how the universe is made, but for its unique inside view of four decades of cutting-edge research.


Hardback 

Kindle 
Using these links earns us commission at no cost to you
Review by Andrew May

Comments

Popular posts from this blog

David Spiegelhalter Five Way interview

Professor Sir David Spiegelhalter FRS OBE is Emeritus Professor of Statistics in the Centre for Mathematical Sciences at the University of Cambridge. He was previously Chair of the Winton Centre for Risk and Evidence Communication and has presented the BBC4 documentaries Tails you Win: the Science of Chance, the award-winning Climate Change by Numbers. His bestselling book, The Art of Statistics , was published in March 2019. He was knighted in 2014 for services to medical statistics, was President of the Royal Statistical Society (2017-2018), and became a Non-Executive Director of the UK Statistics Authority in 2020. His latest book is The Art of Uncertainty . Why probability? because I have been fascinated by the idea of probability, and what it might be, for over 50 years. Why is the ‘P’ word missing from the title? That's a good question.  Partly so as not to make it sound like a technical book, but also because I did not want to give the impression that it was yet another book

The Genetic Book of the Dead: Richard Dawkins ****

When someone came up with the title for this book they were probably thinking deep cultural echoes - I suspect I'm not the only Robert Rankin fan in whom it raised a smile instead, thinking of The Suburban Book of the Dead . That aside, this is a glossy and engaging book showing how physical makeup (phenotype), behaviour and more tell us about the past, with the messenger being (inevitably, this being Richard Dawkins) the genes. Worthy of comment straight away are the illustrations - this is one of the best illustrated science books I've ever come across. Generally illustrations are either an afterthought, or the book is heavily illustrated and the text is really just an accompaniment to the pictures. Here the full colour images tie in directly to the text. They are not asides, but are 'read' with the text by placing them strategically so the picture is directly with the text that refers to it. Many are photographs, though some are effective paintings by Jana LenzovĂ¡. T

Everything is Predictable - Tom Chivers *****

There's a stereotype of computer users: Mac users are creative and cool, while PC users are businesslike and unimaginative. Less well-known is that the world of statistics has an equivalent division. Bayesians are the Mac users of the stats world, where frequentists are the PC people. This book sets out to show why Bayesians are not just cool, but also mostly right. Tom Chivers does an excellent job of giving us some historical background, then dives into two key aspects of the use of statistics. These are in science, where the standard approach is frequentist and Bayes only creeps into a few specific applications, such as the accuracy of medical tests, and in decision theory where Bayes is dominant. If this all sounds very dry and unexciting, it's quite the reverse. I admit, I love probability and statistics, and I am something of a closet Bayesian*), but Chivers' light and entertaining style means that what could have been the mathematical equivalent of debating angels on