Skip to main content

Higgs Force - Nicholas Mee *****

There are plenty of books about the hunt for the Higgs boson, most notably Jim Baggott's excellent Higgs, so at first sight, Higgs Force, might seem to be more of the same, but in a couple of areas it is unparalleled in anything I've read in the field.

Where Higgs is very much the story of the hunt with a bit of physics thrown in, Higgs Force takes us on a journey through our developing understanding of the nature of the components of the universe, putting the eventual origin and significance of the Higgs field (and boson) into context.

It's not perfect, by any means, and I was on course to give it four stars rather than five. This is because it has a tendency to concentrate on the bit of the history of science that fit the picture that is being developed, and rather skims over, or even slightly distorts, those that don’t. A good example is the description of Dirac’s relativistic equation for the electron, and his prediction of the positron. The book gives the impression that Dirac stared into the fire for an evening then came up with the whole thing, which misses out a whole lot of duplication of other people’s work and near misses. But more importantly, this book is very much focused on the importance of symmetry and suggests that Dirac’s equation predicted the positron through symmetry considerations. In fact the equation predicted negative energy electrons, which brought Dirac to his outrageously bold suggestion of the negative energy sea, which is anything but symmetrical, and then to the idea that there could be holes in the negative energy sea which could be interpreted as positrons. A very different chain of thought.

However, the reason I eventually overlooked these foibles is that this book fills in the gaps that Higgs misses. In the review for that book I complained 'Like every other book I’ve read on the subject it falls down on making the linkage between the mathematics of symmetry and the particle physics comprehensible.' Although there a few bumpy moments (and I wish the author had given more detail on symmetry groups, which he never actually names) I would say that Nicholas Mee has achieved the impossible, and made a generally clear and (relatively) easy to follow explanation of the significance of symmetry and symmetry breaking that I'd say no one else has really managed. This is an extremely impressive feat. It leaves the description he gives of the various particle accelerators and the actual discover of the Higgs particle feeling rather flat - the book could easily lose a chunk of that, because by comparison it is mundane.

There's one other section where this book absolutely hits the spot: in its description of Feynman diagrams. Many books cover these, and show how they represent, say, the interaction of a photon and an electron - but Higgs Force has by far the best description of Feynman diagrams I’ve ever seen in a popular science book, properly explaining the interface between the diagram and the associated calculations, which is brilliant, and again pretty well unique.

So not a uniformly brilliant book (I also question the relevance of putting puzzles for the reader in a book like this), but where Mee does hit the spot, he achieves a remarkable ability to communicate complexity, and never more so than the fundamental aspect of symmetry and how it has shaped modern particle physics.


Hardback 


Kindle 
Using these links earns us commission at no cost to you
Review by Brian Clegg

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 Lenzová. 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