Topology is an area of mathematics with which I have no prior experience. I guess it was felt historically that engineers don’t really need topology, and this has filtered down the generations of study. Yet I’ve always found the ideas of topology intriguing, even if I have not deeply understood them. They seem to pop up in the most wide variety of places. While running a math circle for primary school kids, we ended up discussing Euler’s Polyhedron Formula, and I realised that if I wanted to explore these ideas more deeply, I would need a proper grounding in topology. From the wonderful lectures of Tadashi Tokieda which I watch with my son, to the more theoretical end of computer science I bump up against in my day-to-day research, topology seems to be everywhere. I found this book, Essential Topology by Martin D. Crossley, while browsing in a bookshop and decided to take it on holiday as holiday reading.

As presented, the book naturally falls into three parts: an introductory section, a section on basic topology, and a section on more advanced algebraic topology. Although short, the book is written as a sequence of a good number of chapters, 11 in total, which make the material more digestible. Moreover, I found the two “interludes” between sections of the book to be a great innovation – invaluable as a mechanism for orienting my reading, providing the appropriate informal guidance about the journey on which the text was taking me.

The introductory section begins with looking at the question of continuity from a rigorous perspective, bringing in both the epsilon-delta approach to continuity with which I am familiar, and an approach based on open sets with which I was not – but which is easily generalised to functions other than from to . It then moves on to axiomatically defines topological spaces, some standard topologies, and bases for topologies.

The second section begins to explore some of the properties that can be proved using the equipment set up in the previous chapters: connectedness, compactness, the Hausdorff property, homeomorphisms, disjoint unions, product and quotient spaces. I enjoyed this section greatly.

The third section then goes on to discuss various more advanced topics, looking at various topological invariants that have been well studied. Some highlight for me included:

Chapter 6 discusses the idea of homotopy as an equivalence between maps: two maps are homotopic iff there is a continuous function allowing for a kind of continuous deformation of one function into the other, i.e. with and . This is shown to be rather a broad equivalence, for example all continuous functions on are homotopic. However, working with other topological spaces, things get quite interesting. A big part of the chapter is given over to working with circles , where it is shown that there is a countable set of homotopy classes of functions from to . This is very clearly described, and I seem to remember through the mists of time some of these issues cropping up informally in the context of my control theory courses as an undergraduate (or, for that matter, fathoming in Matlab as an undergraduate!) The chapter ends with a proof of the fantastically named “Hairy ball theorem,” from which – amongst other things – it follows that at any given point in time, there’s a part of the world with zero wind speed!

Chapter 7 discusses the Euler characteristic as a topological invariant and introduces some interesting theorems. After introducing the idea of a ‘triangulable space’, it is stated that if two such spaces are homotopy equivalent then they have the same Euler number. More remarkable (to me!) is that when restricted to surfaces, it is sufficient for two such surfaces to have the same Euler number and the same orientability in order for them to be homotopy equivalent. Unfortunately, the proofs of both these results are omitted – apparently they are rather involved – references are given. I certainly appreciated the results collected in this chapter, but I found the exercises quite hard compared to other chapters, possibly partly because of the proof issue, but also because I found it hard to visualise some aspects, e.g. triangulation of a surface of genus 2, and since such surfaces had only been defined informally in the preceding chapters I could not (easily) fall back on a purely algebraic approach to the geometry. I did find it particularly interesting to see the Euler characteristic rigorously defined for a general class of spaces – the very definition in the primary math circle that had brought me to this book in the first place!

Chapter 8 discusses homotopy groups. The basic idea is that one can work with homotopy classes of maps from , the -dimensional sphere, to a space (actually pointed homotopy classes of pointed maps, but lets keep things simple) and it turns out that these classes form a group structure: they have an identity element (constant maps), an addition operation, etc. I guess the purpose here is to bring out the topological structure of , though the special role played by was not totally apparent to me – why is this particular space so fruitful to study? I wonder if any readers can comment on this point for me.

Chapter 9 provides an introduction to Simplicial Homology, the idea – roughly – that those combinations of simplices within a simplicial complex which ‘could’ form boundaries of other simplices but ‘do’ not, tell us something about the topology of the simplicial complex. Homology is then introduced in a different form (Singular Homology) in Chapter 10, and it is stated that the two approaches coincide for triangulable spaces.

In these latter chapters of the book, some theorems tend to be stated without proof. The author is always careful to refer to other textbooks for proof, and I guess this is a necessary aspect of trying to introduce a very large subject in a brief textbook, but for me this made them somewhat less appealing than those in the first two sections. Nevertheless, I now feel suitably armed to begin looking at the world through a more topological lens. I wonder what I will see. For now I’m off to eat a coffee cup.

This Summer I had a long flight to Singapore. A few hours into long flights I tend to lose the will to read anything challenging, so I decided to return to a book I first read as a young teen when it was lent to me by family friend fred harris, the book Surely You’re Joking, Mr Feynman. I remember at the time that this book was an eye opener. Here was a Nobel prize winning physicist with a real lust for life coupled with an inherent enthusiasm for applying the scientific method to all aspects of life and a healthy lack of respect for rules and authority. As a teenager equally keen to apply the scientific method to anything and everything, and keen to work out my own ideas on authority and rules, yet somewhat lacking the personal confidence of Feynman, I found the book hugely enjoyable.

I still find the book hugely enjoyable. I was chuckling throughout – the practical jokes, the encounters with non-scientific “experts” and authority figures. However, I was also somewhat taken aback by Feynman’s attitude to women, which I found misogynistic in places, something that had totally passed me by as a teenager. Feynman’s attitudes were probably unremarkable for his time (Feynman was born in 1918) so I’m not attributing blame here, but I find it odd that I didn’t notice this in the 1980s. Googling for it now, I find commentary about this point is all over the Internet. It just goes to show how many subtleties pass children and teens by, something parents and educators would do well to remember.

I have a friend who thinks she does not understand maths (apologies to the American readers, I will use “maths” in this review rather than the “math” in the book title). She thinks maths is “all about numbers”. She thinks she’s not particularly good at it. She is wrong. Actually, I think she is remarkably gifted, primarily because she asks amazingly prescient questions. She has an inquisitive nature that I fear is often drilled out of most people by our “rigorous” schooling in the tedium of official school maths.

Over the past few months, I have spent quite a bit of time discussing maths with this friend, introducing her to set theory and trying to overcome a fear of algebra. (It is remarkable how many super bright people can reason about insanely complex general phenomena in their head without algebra in a way I never could, yet stumble over a simple equation!)

I saw this book reviewed elsewhere – I can’t quite remember where. It was a short but positive review, and the title is attractive to me, given my recent discussions. The author, Edward Frenkel, is a professor of mathematics at UC Berkeley, has made considerable contributions to mathematics himself, and also has a direct personal knowledge of many of the larger-than-life characters he talks about in the book. I knew nothing about his work, or his life, both of which turn out to be rather interesting, before reading this book.

The book is part autobiography and part introduction to the joy of mathematics. We learn about the author’s early career, the anti-Semitism he faced in Russia and his conversion as a teen from physics to mathematics, before the two come back together through quantum physics later in his career. We learn about his immersion in the Langlands Program.

As a book about “doing mathematics”, I think he does quite well at getting his feelings across. The detail of much of the mathematics is missing; sketches of subjects are given: Galois Groups, the Shimura-Taniyama-Weil Conjecture, Lie groups and Lie algebras, etc., but only very brief sketches. While this gives the reader insight into the depth of the subject areas covered by modern mathematics (and certainly helps to show the breadth of maths beyond school arithmetic) it doesn’t really show the reader mathematics. We read about proof, but we don’t experience proof. We read about revelation, but we don’t feel the revelation ourselves. We are told that mathematics rests on clear and unequivocal definitions, but these are absent from the book. Initially, this left me feeling unsatisfied. Slowly, I put aside my usual desire to understand everything I was reading, and began to enjoy the book as a novel, a love affair between the author and his subject, in which specific theorems appear only as partially sketched characters. From this perspective, the bulk of the book was very enjoyable, and provides insight not only into the beauty of mathematics, but also the ways in which mathematicians think. As an engineer, albeit one who has a lot of time for – and use for – pure mathematics, my way of thinking remains quite distinct from some of the methods and approaches outlined in this book. However, late in the book, where the author covers the links between this mathematics and quantum physics, I feel the unexplained mathematics again gets in the way. The author seems to acknowledge this, when he says (p.221), “All this stuff, as my dad put it, is quite heavy: we’ve got Hitchin moduli spaces, mirror symmetry, A-branes, B-branes, automorphic sheaves […] But my point is not for you to learn them all…”

The final chapter of the book takes a violent switch in direction as we learn of Frenkel’s artistic projects, in particular his film Rites of Love and Math. Had I known about this work beforehand, the book would have made a lot more sense! In this chapter, Frenkel provides his philosophical opinions on the nature of the material world, the world of our consciousness, and – in his view – the entirely separate Platonic world of mathematics. He says his approach to making the film was “let the viewers first feel rather than understand” – much the same could be said of this book.

The experience of reading this book has got me thinking in two directions.

Firstly, this is not the book I initially expected from the first few chapters. But how easy would it be to write a book which both conveys the joy of solving problems, say in Lie algebras, which Frenkel explores in some depth, and at the same time covers enough mathematics for a reasonably rigorous approach to the problem for a general reader? Perhaps such a task is impossible, and I ask too much. Does this mean that the beauty of modern mathematics is necessarily harder to access than than the beauty of modern art? Does this mean that we must necessarily pay the price of “boring maths” in order to be able to access “beautiful maths”? Or is there actually no “boring maths” and the prerequisite knowledge can also be described in a way that appeals and excites, even if not in one volume. I hope for the latter.

Secondly, the book has made me realise that I am far less certain of my own philosophical viewpoint on reality, Platonism, and knowledge than I used to be. It has made me want to explore these issues again and read more. Perhaps I will start with Penrose.

Is this the book I wanted for my friend? Probably not, but it’s certainly stimulated my thinking, and probably would also stimulate the thinking of others, regardless of their current level of mathematical maturity.

I read this book largely by accident, because I was attracted by the title. As an academic in (or rather, on the edge of) computer science, I come across logic regularly, both in teaching and research. Mathematics underpins almost everything I do, and I’m certainly interested in whether a mathematician’s view of logic differs significantly from that of a theoretical computer scientist (as a keen reader of mathematics, I’m well aware that standard mathematical practice of proof differs quite strongly from the formal approach studied in computer science, but this isn’t quite the same thing!) I once had a strong interest in philosophy, most significantly in epistemology, which is being rekindled by my involvement in education at the school level, and so combining all these factors, the title was very appealing. What I actually discovered when I started reading wasn’t exactly what I expected. But this book turns out to be an excellent, crystal clear, textbook suitable for undergraduates and those with just a limited level of mathematical maturity. The book is explicitly partitioned into three sections, but in practice I found that the first two sections, proof theory and computability theory (the “maths” and the “computer science”) were very familiar material for any computer scientist, and from my perspective there was no very clear difference in approach taken, just a difference in the range of topics covered.

Part 1, by Loveland, covers propositional and predicate logic, with a particular focus on automated proof by resolution. I found the description of resolution to be very clear, with a particular focus on the difference between resolution for propositional and predicate logic, and with one of the clearest descriptions of completeness results I’ve seen.

Part 2, by Hodel, covers computability theory. Again, the clarity is exemplary. The first chapter discusses concepts informally, the second precisely defines two machine models in a way very accessible to a computer engineer (effectively one supporting general recursion and one supporting only primitive recursion) and discusses their relative computational power. The insistence of an informal discussion first makes these distinctions come to life, and allows Hodel to frame the discussion around the Church-Turing thesis. The focus on compositionality when preserving partial recursiveness, and the emphasis on the ‘minimalisation’ operator (bounded and unbounded) was new to me, and again very clearly presented. Most introductory texts I’ve read only tend to hint at the link between Gödel’s Incompleteness Theorem and Church’s Undecidability Theorem, whereas Hodel makes this link precise and explicit in Section 6.6, Computability and the Incompleteness Theorem.

Part 3, by Sterrett, covers philosophical logic. In particular, Sterrett considers the existence of alternatives to (rather than extensions of) classical logics. She focuses on the logic of entailment aka relevance logic introduced by Anderson and Belnap, into which she goes into depth. This logic comes from rethinking the meaning ascribed to the connective, , logical implication. In classical logic, this is a most confusing connective (or at least was to my students when I taught an introductory undergraduate course in the subject long ago). I would give my students examples of true statements such as “George is the Pope” implies “George is Hindu” to emphasise the difference between the material implication of classical logic and our everyday use of the word. It is exactly this discrepancy addressed by Anderson and Belnap’s logic. I was least familiar with the content of this part of the book, therefore the initial sections came as something of a surprise, as I found them rather drawn out and repetitive for my taste, certainly compared to the crisp presentation in Parts 1 and 2. However, things got exciting and much more fast moving by Chapter 8, Natural Deduction, where there are clear philosophical arguments to be had on both sides. In general, I found the discussion very interesting. Clearly a major issue with the line of reasoning given by my Pope/Hindu example above is that of relevance. Relevance might be a slippery notion to formalise, but it is done so here in a conceptually simple way: “in order to derive an implication, there must be a proof of the consequent in which the antecedent was actually used to prove the consequent.” Actually making this work in practice requires a significant amount of baggage, based on tagging wffs with relevance indices, which get propagated through the rules of deduction, recalling to my mind, my limited reading on the Curry-Howard correspondence. The book finishes with a semantics of Anderson and Belnap’s logic, based on four truth values rather than the two (true/false) of classical logic.

I can’t emphasise enough how easy this book is to read compared to most I’ve read on the subject. For example, I read all of Part 1 on a single plane journey.  I will be recommending this book to any of my research students who need a basic grounding in computability or logic.

A lot of my work revolves around various problems encountered when one tries to automate the production of hardware from a description of the behaviour the hardware is supposed to exhibit when in use. This problem has a long history, most recently going by the name “High Level Synthesis”. A natural question, but one that is oddly rarely asked in computer-aided design, is “what kind of description?”

Of course not only hardware designers need to specify behaviour. The most common kind of formal description is that of a programming language, so it seems natural to ask what the active community of programming language specialists have to say. I am  fortunate enough to be an investigator on a multidisciplinary EPSRC project with my friend and colleague Dan Ghica, specifically aimed at bringing together these two communities, and I thought it was time to undertake sufficient reading to help me bridge some gaps in terminology between our fields.

With this is mind, I recently read Bob Harper‘s Practical Foundations for Programming Languages. For an outsider to the field, this seems to be a fairly encyclopaedic book describing a broad range of theory in a fairly accessible way, although it did become less readily accessible to me as the book progressed. My colleague Andy Pitts is quoted on the back cover as saying that this book “reveals the theory of programming languages as a coherent scientific subject,” so with no further recommendation required, I jumped in!

I like the structure of this book because as a non-specialist I find this material heavy going: Harper has split a 500 page book into fully 50 chapters, which suits me very well. Each chapter has an introduction and a “notes” section and – for the parts in which I’m not very interested – I can read these bits to still get the gist of the material. Moreover, there is a common structure to these chapters, where each feature is typically first described in terms of its statics and then its dynamics. The 50 chapters are divided into 15 “parts”, to provide further structure to the material.

The early parts of the book are interesting, but not of immediate practical relevance to me as someone who wants to find a use for these ideas rather than study them in their own right. It is nice, however, to see many of the practical concepts I use in the rare occasions I get to write my own code, shown in their theoretical depth – function types, product types, sum types, polymorphism, classes and methods, etc. Part V, “Infinite Data Types” is of greater interest to me just because anything infinite seems to be of interest to me (and, more seriously, because one of the most significant issues I deal with in my work is mapping of algorithms conceptually defined over infinite structures into finite implementations).

Where things really get interesting for me is in Part XI, “Types as Propositions”. (I also love Harper’s distinction between constructive and classical logic as “logic as if people matter” versus “the logic of the mind of God”, and I wonder whether anyone has explored the connections between the constructive / classical logic dichotomy and the philosophical idealist / materialist one?) This left me wanting more, though, and in particular I am determined to get around to reading more about Martin-Löf type theory, which is not covered in this text.

Part XIV, Laziness, is also interesting for someone who has only played with laziness in the context of streams (in both Haskell and Scala, which take quite different philosophical approaches). Harper argues strongly in favour of allowing the programmer to make evaluation choices (lazy / strict, etc.).

Part XV, Parallelism, starts with the construction of a cost dynamics, which is fairly straight forward. The second chapter in this part looks at a concept called futures and their use in pipelining; while pipelining is my bread and butter in hardware design, the idea of a future was new to me. Part XVI, Concurrency, is also relevant to hardware design, of course. Chapter 43 makes an unexpected (for me!) link between the type system of a distributed concurrent language with modal logics, another area in which I am personally interested for epistemological reasons, but know little.

After discussing modularity, the book finishes off with a discussion of notions of equivalence.

I found this to be an enlightening read, and would recommend it to others with an interest in programming languages, an appetite for theoretical concerns, but a lack of exposure to the topics explored in programming language research.

My third and final piece of holiday reading this Summer was Margaret Donaldson’s Children’s Minds, the first book I’ve read on child psychology.

This is a book first published in 1978, but various sources suggested it to me as a good introduction to the field.

I wasn’t quite sure what to make of this book. The initial chapters seem to be very much “of the time”, a detailed critique of the theory of Piaget, which meant little to me without a first hand knowledge of Piaget’s views. Donaldson does, however, include her own summary of Piaget’s theories as an appendix.

Donaldson argues that children are actually very capable thinkers at all ages, but that effort must be made to communicate to them in a way they can understand. Several interesting experiments by Piaget, from which he apparently concluded that children are incapable of certain forms of thought, are contrasted against others by later researchers who found that by setting up the experiments using more child-friendly communication, these forms are apparently exhibited.

The latter half of the book becomes quite interesting, as Donaldson explores what schools can do during reception (kindergarten) age and beyond to ensure that the early excitement of learning which most children have is not destroyed by schools themselves. It is fascinating, for example, to read that

There is now a substantial amount of evidence pointing to the conclusion that if an activity is rewarded by some extrinsic prize or token – something quite external to the activity itself – then that activity is less likely to be engaged in later in a free and voluntary manner when the rewards are absent, and it is less likely to be enjoyed.

I would be most interested in what work has been done since the 70s on this point, as if this is true then it seems to clash markedly with practice in the vast majority of primary schools I know.

The final part of the text is remarkably polemical:

Perhaps it is the convenience of having educational failures which explains why we have tolerated so many of them for so long…

A vigorous self-confident young population of educational successes would not be easy to employ on our present production lines. So we might at last be forced to face up to the problem of making it more attractive to work in our factories – and elsewhere – and, if we had done our job in the schools really well, we should expect to find that economic attractions would not be enough. We might be compelled at last to look seriously for ways of making working lives more satisfying.

Little progress since the 70s, then! Interestingly (for me) Donaldson approvingly quotes A.N. Whitehead’s views on the inertia of education; I know Whitehead as a mathematician, and was completely unaware of his educational work.

As I mentioned, this is the first book on child psychology I’ve read. I found it rather odd; I am not used to reading assertions without significant citations and hard data to back up the assertions. I am not sure whether this is common in the field, whether it is Donaldson’s writing, or whether it is because this is clearly Donaldson writing for the greater public. I tended to agree with much of what was written, but I would have been far more comfortable with greater emphasis on experimental rigour. There is much in here to discuss with your local reception class teacher; I want to know more about older children.

My second piece of holiday reading this Summer was Gigerenzer’s Risk Savvy. This is an “entertaining book” for a general readership.

I learnt quite a bit from this book, but still found it frustrating and somewhat repetitive. There are many very interesting anecdotes about risk and poor decision making under risk, as well as lots of examples of how we are manipulated by the press and corporations into acting out of fear.

However, I don’t necessarily agree with the conclusions reached.

As an example, Gigerenzer clearly shows that PSA testing for prostate cancer is the US does more harm than good compared to the UK’s approach. More people are rendered incontinent and impotent through early intervention, without any significant difference in mortality rate. A similar story is told for routine mammography. But the conclusion that Gigerenzer seems to draw from these – and similar – studies, is that “it’s better not to know”, whereas my conclusion would be “it’s better not to intervene immediately”. I can’t see why simply knowing more should be worse.

I was also frustrated by the way Gigerenzer deals with the classification of risks into “known risks”, i.e. those for which good statistical information is available, and “unknown risks”. He convincingly shows that – all too often – we deal with unknown risks as if they were known risks, resulting in poor decision making. To me this appears to be a mirror of the two ways I know of dealing with uncertainty in mathematical optimization: stochastic versus robust optimization. This is a valuable dichotomy, but I don’t think that Gigerenzer’s conclusion that, in the presence of “unknown risk”, “simple is good” and “go with your gut feeling” is well justified. I do think that more needs to be done by decision makers to factor in the computational complexity of making decisions – and the overfitting of overly complex models – into decision making methodologies, but if “simple is good” then this should be a derivable result; I would love to see some mathematically rigorous work in this area.

One of the books I took on holiday this year was Gilles Godefroy’s The Adventure of Numbers. This is a great book!

The book takes the reader on a tour of numbers: ancient number systems, Sumerian and Babylonian number systems (decimal coded base 60, from which we probably get our time system of hours, minutes and seconds), ancient Greeks and the discovery of irrational numbers, Arabs, the development of imaginary numbers, transcendentals, Dedekind’s construction of the reals, p-adic numbers, infinite ordinals, and the limits of proof.

This is a huge range, well written, and while fairly rigorous only requires basic mathematics.

I love the fact that I got from this book both things that I can talk to primary school children about (indivisibility of space through a geometric construction of the square root of two and its irrationality) and also – unexpectedly – an introduction to the deep and beautiful MRDP theorem which links two sublime interests for me: computation (in a remarkably general sense) and Diophantine equations.

What’s not to love?