May 08 2020

Book review: The Pope of Physics by Gino Segrè and Bettina Hoerlin

fermiThe Pope of Physics by Gino Segrè and Bettina Hoerlin is the biography of Enrico Fermi. I haven’t read any scientific biography for a while and this book on Enrico Fermi was on my list. He is perhaps best known for leading the team that constructed the first artificial nuclear reactor as part of the Manhattan Project. As a lapsed chemical physicist I also know him for Fermi surfaces, Fermi-Dirac statistics, and the Fermi method. Looking on Wikipedia there is a whole page of physics related items named for him.

Fermi was born at the beginning of the 20th century, his parents were born before Italy was unified in 1870 when illiteracy was not uncommon and people typically stayed close to home since travel quickly involved crossing borders.

Fermi was identified as something of a prodigy whom a friend of his father, Adolfo Amidei, took under his wing and smoothed his path to Pisa Scuola Normale Superior. As I sit here in in a mild lockdown I was bemused to note that the entrance exams Fermi took were delayed by the 1918 Spanish Flu pandemic. At Pisa Fermi learned largely under his own steam, at the time physics was not an important subject – the Pisa Scuola had five professors in physics and only one in physics. Fermi graduated at the top of his class.

After Pisa Fermi fell into the path of Orso Mario Corbino, a physicist, politician and talented organiser who set about helping Fermi to build a career in physics. At the time a new quantum physics was growing, led primarily by young men such as Pauli, Dirac, Heisenberg and Schrödinger who was a little older. Fermi met them on a scholarship to Göttingen in Germany. He later went to Leiden on a scholarship where he met Ehrenfest, and Einstein who was very taken with him. This was preparation for building a new physics capability in Italy.

The fruits of this preparation were a period in the mid-1930s which saw Fermi and his research group at Rome University invent a theory of nuclear decay which revealed the weak nuclear force and postulated the existence of the neutrino (this theoretical work was Fermi’s alone). The wider research group studied the transmutation of elements by slow neutron bombardment. This work was to win Fermi the 1938 Nobel Prize for Physics.

This research led on directly to the discovery of nuclear fission and the chain reaction which became highly relevant as Fermi fled Italy to the US with his wife on the eve of the Second World War. Many of Fermi’s friends, including his wife Laura, were Jewish. Fermi steered clear of politics to a large degree, he benefitted from the patronage of Mussolini but was no fascist enthusiast. The Italian uses of chemical weapons in Ethopia and, ultimately, the racial laws of the late 1930s which expelled Jews from their positions drove him from the country. He had visited the US a number of times in the early 1930s and had little trouble finding a position at Columbia University.

The route to the atomic bomb was not quick and smooth in the early years of the war, a number of physicists had noted the possibility of the fission bomb and attempted to warn politicians of its potential. This all changed when the Americans joined the war, following the Japanese attack on Pearl Harbour.

Building an atomic bomb presented a number of scientific challenges which Fermi was well-placed to address, primary amongst these was building “Critical Pile 1” the first system to undergo a self-sustaining nuclear chain reaction. It was constructed, slightly surreptitiously, in a squash court at Chicago University. It was built there as a result of a dispute with the contractor who was due to build it a little outside Chicago, at Argonne.

The “critical pile” demonstrated two things: firstly that chain reactions existed, and secondly it provided a route to producing the nuclear isotopes required to produce a bomb. It still left the question of how to purify the isotopes, and the question of how to produce a critical mass fast enough to cause a worthwhile explosion.

Fermi would go on to help in the Manhattan Project at Hanford and then Los Alamos where he held a position combining both universal scientific consultancy and administration, or at least organisation.

It is difficult to talk about Fermi’s strengths as a physicist – he had so many – he is almost unique in being both a top flight experimentalist, and theoretician. This is the great divide in physics, and people who are talented in both fields are rare. He was also clearly an excellent teacher, as well as undergraduate teaching and writing a high school physics book he supervised 7 students who would go on to earn Nobel Prizes in physics. Alongside this he was clearly personable.

Fermi died in November 1954 a little after his 53rd birthday, leaving in his wake a large number of prizes, buildings and discoveries as a memorial.

I found The Pope of Physics highly readable, the chapters are quite short but focused.

Apr 18 2020

Book review: Sea monsters on Medieval and Renaissance Maps by Chet van Duzer

sea_monstersA borrowed book for my next review: Sea monsters on Medieval and Renaissance Maps by Chet van Duzer. Mrs H bought this as a by-product of buying a Christmas present on some quirky gifts site.

The book is well-described by its title, it is about sea monsters on medieval and Renaissance maps. Although a couple of classical antecedents are mentioned the main action starts in the 9th century and finishes at the beginning of the 17th century.

The book is organised roughly chronologically without chapters but with sections recorded in the contents – there are approximately 50 sections broken up by four "pictorial excursions". Much of the material is from the 16th century. As we go further back in time fewer and fewer examples of any sort of written or printed materials survive. Prior to 1472 any maps will have been reproduced by hand rather than printed.

Sea monsters were not found universally in maps through this period, in fact they were relatively rare. Adding sea monster was an additional cost and rarely added any useful information. The sea monsters were often drawn separately from the cartographic elements of the map, suggesting they were a specialisation. Sometimes they were direct copies from other sources. Sea monsters were often derived from recent scientific works, and influences can be seen across multiple maps. Sometimes the sea monsters depicted are playing a role in myths or stories such as Jonah and the whale, or the story of Saint Brendan who, on a voyage, is said to have landed on a whale, not realising its nature a fire was lit and the whale sank beneath them.

There is a lot of evidence of artist working from verbal descriptions of animals by non-expert observers. This is at a time before naturalists had been invented so observations of wildlife were not systematic. There’s a great double page spread illustrating the development of drawings of walruses from pretty much elephants to recognisable walruses(see below).

walruses_1walruses_2

Figure 1: The cartographic career of the Walrus

Sea monsters came in various forms, many reflected real animals we might see today, although rendered strangely as we see with the walrus. Others were human – animal hybrids such as mermaids. Finally there are the outright whimsical – various dragons, krakens, unicorns – owl faced creatures and the like.

Mappamundi were the earliest maps to contain sea monsters although they are not maps as we would recognise them, you couldn’t navigate by them. They were symbolic representations of the world both physical and spiritual, rather than being entirely useful for navigation. A common feature was that the focus in these maps on the land rather than the sea. I was confused by mentions of the Beatus mappamundi which appears in multiple locations before realising that these were copies of a single mappamundi which varied since they were manually created. The place name refers to a particular copy (i.e. Genoa or Manchester), and different copies have different sea monsters. They are based on a map found in the Commentary on the Apocalypse by Beatus of Liébana. This was written sometime in the 8th century and subsequently copied.

The earliest surviving navigational maps are from the 13th century, these are intended as more functional objects and initially focussed on the region around the Mediterranean. In contrast to the mappmundi, these maps were focussed on the sea and coastal areas. There were variants made which clearly played a more decorative role, collectors items that showed your wealth and knowledge. These maps were more likely to contain illustrations of sea monsters.

In addition to freestanding maps there were also illustrated versions of Ptolemy’s Geography which included sea monsters, although the Madrid version of 1455-60 is the only manuscript version to include such sea monsters. Later printed version contained more sea monsters.

The sea monsters in Olaus Magnus’s Nautical chart and description of the Northern lands and Wonders published in 1539 are particularly rich and varied. They can also be found copied in Mercator’s globe of 1541 and Euphrosynus Ulpius’s globe of 1542. Mercator was less eclectic in his collecting of sea monsters for his atlas of 1569.

The book finishes as the 17th century opens when fantastical sea monsters on maps largely fell out of favour to be replaced with more ships and practical illustrations of whaling and the like. The sea was no longer quite so mysterious and man was increasingly exerting control over it, and its contents.

This is a fun book, a nice present for a cartophile. It would have been good to have a timeline of the maps discussed. There is probably an interesting parallel book on the monsters seen in terrestrial maps of the same period.

Mar 05 2020

Book Review: The Egg & Sperm Race by Matthew Cobb

egg_and_spermI follow quite a few writers on Twitter, and this often leads me to read their books. The Egg & Sperm Race by Matthew Cobb is one such book. It traces the transition in thinking on the reproduction of animals, including humans, which occurred during the second half of the 17th century.

Prior to this we had some pretty odd ideas as to how animals reproduced, much of it carried over from the Ancient Greeks. Ovid and Virgil both claimed that you could make bees by burying a bull with its horns protruding from the ground, waiting and then cutting off the horns to release the bees! This confusion is not surprising, the time between mating and the appearance of young is quite long, and the early stages of the process are hidden by being very small, and deep inside animals.

A random “fact” I cannot help but repeat is that Avicena wrote that “a scorpion will fall dead if confronted with a crab which a piece of sweet basil basil has been tied”. I wonder sometimes with quotes such as these whether they are a result of mistranslation, or a bored scribe. The point really is such ideas were not discounted out of hand at the time. The Egg & Sperm Race starts with a description of da Vinci’s copulating couple which is beautiful but wrong – da Vinci connects the testicles to the brain – these structures do not exist.

The heart of the action in The Egg and Sperm Race is in the Netherlands, in England the Royal Society showed relatively little interest in generation aside from some experiments on the spontaneous generation of cheese mites. The Chinese and Arab scholars who had worked in various fields showed little interest in generation.

The central characters are Jan Swammerdam, Niels Stensen (known as Steno) and Reinier de Graaf, who met in Leiden at the university in the early 1660s when they were in their early twenties. Swammerdam and Steno were a little older than de Graaf and were close friends. Soon after meeting in Leiden they visited Paris where they continued to build contacts in the scientific community.

In understanding generation a first step was to realise that all animals came from other animals of the same species, and that this meant mating between two animals of the same species. Steno went to Italy and worked with Francesco Redi’s whose experiments were key to this, he checked exhaustively that insects did not arise from the putrefaction of material. Swammerdam was also interested in insects, classifying four different types of invertebrate development and showing that in moths traces of the adult form are found in the caterpillar. At the time it was not clear that the larval stage and the adult were the same species.

A second step was to realise that all animals came from eggs of some sort, William Harvey –  of blood circulation fame – did experiments in this area but although he stated this conclusion but it was not well-supported by his experiments. In the period at the beginning of this book, the role of the ovary was not understand. Steno carried out dissections on fish both those that laid eggs, and those that gave birth to live young from this he concluded that the ovaries were the source of eggs and asserted that this was the case for humans as well. This idea rapidly gained acceptance.

The discovery of the human egg, and its origins in the ovary, was the subject of a dispute between de Graaf and Swammerdam on priority. The Royal Society decided in favour of van Horne with whom Swammerdam had worked on the dissection and illustration of female reproductive anatomy. To modern eyes the written record of the dispute, in letters, and publications is surprisingly personal. De Graaf died at the age of 32 just prior to the Royal Society decision. It was a difficult time in the Netherlands with the country at war with England and France with France troops invading parts of the country.

Leeuwenhook cast a spanner into the works with his microscopical studies, he observed spermatozoa but not the female egg and as a result became a “spermist”, believing that life came from the sperm in contrast to the “ovists” who believed life came from the egg. We now know that they are both right. The human egg was not observed until 1826 by von Baer. And I have to mention Spallazani’s experiments on frogs wearing taffeta shorts, demonstrating that male sperm was required to fertilise the female egg.

The final chapter covers events from the end of the 17th century or a little later to present day. Linneaus’s classification work, and Darwin’s theory of evolution follow on from some of the core realisations of this earlier period. Neither Linneaus’ work nor Darwin’s work make much sense if you don’t believe that animals (and plants) grow from eggs/seeds which came from the same species. It wasn’t until von Baer’s work in the early 19th century that the female egg was observed.

Jan 30 2020

Book review: How the States got their Shapes by Mark Stein

how_the_statesHow the States got their Shapes by Mark Stein is that book that does exactly what it says on the cover: explain the origin of the shapes of the states of the United States. The book starts with some broad brush strokes that underpin the shaping of many states before going through each State in alphabetical order.

States are not strictly comparable with European nations but it is interesting to compare the never-straight borders of Europe with the regularity of particularly Western states. To a British European the events described in the book are all terribly recent – much of the action occurs during the 19th century! I considered extending this statement to all Europeans but there has been quite a bit of change in national borders in Europe over the last 200 years.

The large scale features of the USA arise from a number of sources. The earliest of these originate from the French and Indian War in the mid-18th century which saw the England and the colonists take the territory around the Great Lakes from the French and subsequently take further land from the French in the Louisiana Purchase. Further to the west territory came from the Spanish and then a newly independent Mexico. The border with Canada was agreed largely at the 49th parallel with the British in 1818. Later the Dutch would cede their territory along the Hudson river and the Spanish the last of their territory in what is Florida.

There are some recurring themes determining the shapes of states, one that comes up repeatedly is the desire for Congress to create States of equal size, in the West there are sets of states with the same height (3o) and width (7o). This concept extended to access to resources, so the ports on the Great Lakes are shared amongst the surrounding States. A second big driving force is slavery, the Missouri Compromise placed a boundary at a latitude of 36o 30′ below which slavery was allowed, and above which it was not. This motivated boundaries of states, and led to a battle to create equal numbers of states above and below the line.

There are irregularities. Boston Corner looks like it should belong in  Massachusetts but is actually in New York state, this is because the terrain made access to Boston Corner from the rest of Massachusetts difficult. In the early days this type of inaccessibility led to lawlessness, so states were willing to cede territory to avoid it. Whole states were created to address potential lawlessness, when gold was discovered in what is now Idaho it was felt too distant from Oregon to be ruled from there with the influx of unruly gold miners. There was also a concern that they would displace the coastal Oregonians from government.

Sometimes a river makes a good boundary although when the river has tributaries things get a bit tricky, it is even worse when borders are defined with reference to “head waters” which are notoriously difficult to locate. The other problem with rivers is that they meander – meaning that chunks of a State may find themselves on the “wrong” side of a river when the river moves. In some cases surveying errors and mistakes in negotiations led to oddly formed borders.

The supersize California and Texas states are a result of their own origins in virtual nationhood. Texas was, for a brief period, an independent country which subsequently joined the Union. California formed with the influx of the miners who came for gold, the Union was more concerned that they join than try to enforce borders upon the new State.

The charters of the original US colonies which later evolved into states typically gave them territories that stretched all the way from the Atlantic to the Pacific coast, during the 17th and 18th centuries this was largely moot – colonies scarcely had the wherewithal to maintain small populations on the  Eastern seaboard. The British monarchs granting these charters were not necessarily consistent, or particularly well-advised. So some boundaries are defined by “headwaters” which are notoriously ill-defined.

It is inevitable that the book is a bit repetitive, after all every border has two sides. This is occasionally jarring but usually handled quite well with cross referencing.

Missing from this book is much reference to the Native Americans, they are mentioned as an aside in a few places but little more than that. There is another book in the territories of the Native Americans prior to the European colonisation of the country – I just don’t know where it is! This article on The best books on Native Americans and Colonisers looks like a good place to start.

Overall I quite enjoyed this book, I read most of it on a long train ride. I suspect maps and boundaries are a bit of a niche interest but I feel I also picked up the broad shape of the creation of the USA.

Jan 14 2020

Book review: You look like a thing and I love you by Janelle Shane

You look like a thing and I love you by Janelle Shane is a non-technical overview of machine learning. This isn’t to say it doesn’t goYou look like a thing and I love you book cover into some depth, and that if you are experienced practitioner in machine learning you won’t learn something. The book is subtitled “How Artificial Intelligence Works and Why It’s Making the World a Weirder Place” but Shane makes clear at the outset that it is all about machine learning – Artificial Intelligence is essentially the non-specialist term for the field.

Machine learning is based around training an algorithm with a set of data which represents the task at hand. It might be a list of names (of kittens, for example) where essentially we are telling the algorithm “all these things here are examples of what we want”. Or it might be a set of images where we indicate the presence of dogs, cats or whatever we are interested in. Or, to use one of Shane’s examples, it might be sandwich recipes labelled as “tasty” or “not so tasty”.  After training, the algorithm will be able to generate names consistent with the training set, label images as containing cats or dogs or tell you whether a sandwich is potentially tasty.

The book has grown out of Shane’s blog AI Weirdness where she began posting about her experiences of training recurrent neural networks (a machine learning algorithm) at the beginning of 2016. This started with her attempts to generate recipes. The results are, at times, hysterically funny. Following attempts at recipes she went on to the naming of things, using neural networks to generate the names of kittens, guinea pigs, craft beers, Star Wars planet names and to generate knitting patterns. More recently she has been looking at image labelling using machine learning, and at image generation using generative adversarial networks.

The “happy path” of machine learning is interrupted by a wide range of bumps in the road which Shane identifies, these include:

  • Messy training data – the recipe data, at one point, had ISBN numbers mixed in which led to the neural network erroneously trying to include ISBN-like numbers in recipes;
  • Biased training data – someone tried to analyse the sentiment of restaurant reviews but found that Mexican restaurants were penalised because the Word2vec training set (word2vec is a popular machine learning library which they used in there system) associated Mexican with “illegal”;
  • Not detecting the thing you thought it was detecting – Shane uses giraffes as an example, image labelling systems have a tendency to see giraffes where they don’t exist. This is because if you train a system to recognise animals then in all likelihood you will not include pictures with no animals. Therefore show a neural network an image of some fields and trees with no animals in it will likely “see” an animal because, to its knowledge, animals are always found in such scenes. And neural networks just like giraffes;
  • Inappropriate reward functions – you might think you have given your machine learning system an appropriate “reward function” aka a measure for success but is it really the right one? For example the COMPAS system, which recommends whether prisoners in the US should be recommended for parole, was trained using a reward based on re-arrest, not re-offend. Therefore it tended to recommend against parole for black prisoners because they were more likely to be arrested (not because they were more likely to re-offend);
  • “Hacking the Matrix” – in some instances you might train your system in a simulation of the real world, for example if you want to train a robot to walk then rather than trying to build real robots you would build virtual robots and try them out in a simulated environment. The problem comes when your virtual robot works out how to cheat in the simulated environment, for example by exploiting limitations of collision detection to generate energy;
  • Problems unsuited to machine learning – some tasks are not amenable to machine learning solutions. For example, in the recipe generation problem the “memory” of the neural network limits the recipes generated because by the time a neural network has reached the 10th ingredient in a list it has effectively forgotten the first ingredient. Furthermore, once trained in one task, a neural network will “catastrophically forget” how to do that task if it is subsequently trained to do another task – machine learning systems are not generalists;

My favourite of these is “Hacking the matrix” where algorithms discover flaws in the simulations in which they run, or flaws in their reward system, and exploit them for gain. This blog post on AI Weirdness provides some examples, and links to original research.

Some of this is quite concerning, the examples Shane finds are the obvious ones – the flight simulator which found that it could meet the goal of a “minimum force” landing by making the landing force enormous and overflowing the variable that stored the value, making it zero. This is catastrophic from the pilot’s point of view. This would have been a very obvious problem which could be identified without systematic testing. But what if the problem is not so obvious but equally catastrophic when it occurs?

A comment that struck me towards the end of the book was that humans “fake intelligence” with prejudices and stereotypes, it isn’t just machines that use shortcuts when they can.

The book finishes with how Shane sees the future of artificial intelligence, essentially in a recognition that these systems have strengths and weaknesses and that the way forward is to combine artificial and human intelligence.

Definitely worth a read!

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