Author's posts
Apr 03 2011
Obsession
This is a short story about obsession: with a map, four books and some numbers.
My last blog post was on Ken Alder’s book “The Measure of All Things” on the surveying of the meridian across France, through Paris, in order to provide a definition for a new unit of measure, the metre, during the period of the French Revolution. Reading this book I noticed lots of place names being mentioned, and indeed the core of the whole process of surveying is turning up at places and measuring the angles to other places in a process of triangulation.
To me places imply maps, and whilst I was reading I popped a few of the places into Google Maps but this was unsatisfactory to me. Delambre and Mechain, the surveyors of the meridian, had been to many places. I wanted to see where they all were. Ken Alder has gone a little way towards this in providing a map: you can see it on his website but it’s an unsatisfying thing: very few of the places are named and you can’t zoom into it.
In my investigations for the last blog post, I discovered the full text of the report of the surveying mission, “Base du système métrique décimal”, was available online and flicking through it I found a table of all 115 triangles used in determining the meridian. So a plan is formed: enter the names of the stations forming the 115 triangles into a three column spreadsheet; determine the latitude and longitude of each of these stations using the Google Maps API; write these locations out into a KML file which can be viewed in Google Maps or Google Earth.
The problem is that place names are not unique and things have changed in the last 200 years. I have spent hours transcribing the tables and hunting down names of obscure places in rural France, hacking away with Python and loved every minute of it. Cassini’s earlier map of France is available online but the navigation is rather clumsy so I didn’t use it. Although now I come to writing this I see someone else has made a better job of it.
Beside three entries in the tables of triangles are the words: “Ce triangle est inutile” – “This triangle is useless”. Instantly I have a direct bond with Delambre, who wrote those words 200 years ago – I know that feeling: in my loft is a sequence of about 20 lab books I used through my academic career and I know that besides an (unfortunately large) number of results the word “Bollocks!” is scrawled for very similar reasons.
The scheme with the the Google Maps API is that your program provides a place name “Chester, UK”, for example, and the API provides you with the latitude and longitude of the point requested. Sometimes this doesn’t work, either because there are several places with the same name or the placename is not in the database.
I did have a genuine Eureka moment: after several hours trying to find missing places on the map I had a bath and whilst there I had an idea: Google Earth supports overlay images on its maps. At the back of the “Base du système métrique décimal” there is a set of images showing where the stations are as a set of simple line diagrams. Surely I could overlay the images from Base onto Google Earth and find the missing stations? I didn’t leap straight from the bath, but I did stay up overlaying images onto maps deep into the night. It turns out the diagrams are not at all bad for finding missing stations. This manual fiddling to sort out errant stations is intellectually unsatisfying but some things it’s just quicker to do by hand!
You can see the results of my fiddling by loading this KML file into Google Earth, if you’re really keen this is a zip file containing the image overlays from “Base du système métrique décimal” – they match up pretty well given they are photocopies of diagrams subject to limitations in the original drawing and distortion by scanning.
What have I learned in this process?
- I’ve learnt that although it’s possible to make dictionaries of dictionaries in Python it is not straightforward to pickle them.
- I’ve enjoyed exploring the quiet corners of France on Google Maps
- I’ve had a bit more practice using OneNote, Paint .Net, Python and Google Earth so when the next interesting thing comes along I’ll have a head start.
- Handling French accents in Python is a bit beyond my wrangling skills.
You’ve hopefully learnt something of the immutable mind of a scientist!
View
Mar 31 2011
Book review: The Measure of All Things by Ken Alder
“The Measure of All Things“ by Ken Alder tells the story of Pierre Méchain and Jean Baptiste Joseph Delambre’s efforts to survey the line of constant longitude (or meridian) between Dunkerque and Barcelona through Paris, starting amidst the French Revolution in 1792.
The survey of the meridian was part of a scheme to introduce a new, unified system of measures. The idea was to fix the length of the new unit, the metre, as 1/10,000,000th of the distance between the North Pole and the equator on a meridian passing through Paris.
At the time France used an estimated 250,000 different measures across the country with each parish having it’s own (uncalibrated) weights and measures with different measures for different types of material i.e. a “yard” of cotton was different from a “yard” of silk, and different if you were buying wholesale or selling to end users. These measures had evolved over time to suit local needs, but acted to supress trade between communities. Most nations found themselves in a similar situation.
Although the process of measuring the meridian started under the ancien regime, it continued in revolutionary France as a scheme that united the country. The names associated with the scheme: Laplace, Legrendre, Lavoisier, Cassini, Condorcet, leading lights of the Academie des Sciences, are still well known to scientists today.
Such surveying measurements are made by triangulation, a strip of triangles is surveyed along the line of interest. This involves precisely measuring the angles between each each vertex of the triangles in succession: given the three angles of a triangle and the length of one side of the triangle the lengths of the other two sides can be calculated. It’s actually only necessary to measure the length of one side on one triangle on the ground. Once you’ve done that you can use the previously determined lengths for successive triangles. All of France had been surveyed under the direction of César-François Cassini in 1740-80, the meridian survey used a subset of these sites measured at higher precision thanks to the newly invented Borda repeating circle. As well as this triangulation survey a measure of latitude was made at points along the meridian by examining the stars.
The book captures well the feeling of experimental measurement: the obsession with getting things to match up via different routes; the sick feeling when you realise you’ve made a mistake perhaps never to be reversed; the frustration at staring at pages of scribbles trying to find the mistake; the pleasure in things adding up.
Méchain and Delambre split up to measure the meridian in two sections: Delambre taking the northern section from Dunkerque to Rodez and Méchain the section from Rodez to Barcelona. Méchain delayed endlessly throughout the project, trusting little measurement to his accompanying team. Early on in the process, at Barcelona, he believed he had made a terrible error in measurement, but was unable to check whilst Spain and France were at war. He was wracked by doubt for the following years, only handing over doctored notes with great reluctance at the very end of the project. He was to die not long after the initial measurements were completed, leaving his original notes for Delambre to sift through.
At the time the measurements were originally made the understanding of experimental uncertainty, precision and accuracy were poorly developed. Driven in part by the meridian project and similar survey work by Gauss in Germany, statistical methods for handling experimental error more rigorously were developed not long afterwards. I wrote a little about this back here. Satellite surveying methods show that the error in the measurement by Méchain and Delambre is equivalent to 0.2 millimetres in a metre or 0.02%.
In the end the Earth turns out not to be a great object on which to base a measurement system: although it’s pretty uniform it isn’t really uniform and this limits the accuracy of your units. The alternative proposed at the time was to base the metre on a pendulum: it was to have the length necessary to produce a pendulum of period 2 seconds. This is also ultimately based on properties of the Earth since the second was defined as a certain fraction of the day (the time the Earth takes to rotate on its axis) and the local gravity which varies slightly from place to place, as Maskelyne demonstrated.
Following the Revolution, France adopted, for a short time, a decimal system of time as well as metric units but these soon lapsed. However, the new metric units were taken up across the world over the following years – often this was during unification following war and upheaval.
The definition of the basic units used in science is still an active area. The definition of the metre has not relied on a unique physical object since 1960, rather it is defined by a process: the distance light travels in a small moment of time. However, the kilogram is still defined by a physical object but this may end soon with some exquisitely crafted silicon spheres.
I must admit to being a bit wary of this book in the first instance, how interesting can it be to measure the length of a line? However, it turns out I like to read history through the medium of science and the book provides an insight into France at the Revolution. Furthermore measuring the length of a line is interesting, or it is to a physicist like me.
Thanks to @beckyfh for recommending it!
Footnotes
1. The full-text of the three volume “Base du système métrique décimal” written by Delambre is available online. The back of the second volume contains summary tables of all the triangles and a diagram showing their locations.
2. The author’s website.
3. Some locations in Google Maps.
Mar 22 2011
Book review: The Ascent of Money by Niall Ferguson
This blog post is my review and notes on “The Ascent of Money: A Financial History of the World” by Niall Ferguson. It’s a thematic run through the key elements of our current global finance system which ends with subprime mortgages and the present day.
Money, tokens representing value, started with the clay tablets of Mesopotamia as “promissory notes” for goods some 4000 years ago. For a very long time the basis of all money was precious metals such as gold and silver, it’s only been in the last 40 years or so that the link to gold has been broken for major currencies. The Spanish were burnt by metal coin when they started extensive mining for silver in South America – devaluing the coin in Europe through excess supply.
Fibonacci helped to introduce Hindu-Arabic numerals to Europe in 1202 through his book, Liber Abaci, which contained commercial calculations including currency and interest rates. Many of the early bankers were Jewish, they were legally restricted from taking part in many sorts of commerce and, through usury laws, the Christians were unable to lend but Jews could (their usury laws restricting lending to other Jews). Banking really took off with the Medici family during the 15th century, originally they dealt in foreign currency but diversified and, critically, became big. Size was important, because large size reduces risk.
Banking innovation then moved north from Italy with three innovations: the Amsterdam Exchange Bank (1609) introduced a standard currency, the Stockholm Banco (1657) started lending and then the Bank of England (1694) started issuing notes which meant there was no need for an account with the bank.
This is followed by the issuing of government bonds, these are essentially the way governments raise debt. Bonds have a face value – and an annual percentage return on their face value but the price at which they are sold in the market may vary. They were initially used by governments to raise money for wars. Rothschild bank made it’s money in this way in the early 19th century. Bonds are seen as very secure investments, but governments do default – most recently the Russia government in 1998.
The final innovation was the limited-liability company, a way by which individuals could band together to undertake longer term projects without risking everything (they only risked the value of their shares). The first of these was the Dutch East India Company founded in 1602 – formed to conduct the spice trade with the Far East (a risky and expensive business). In theory the directors and shareholders hold the company to account but in practice the value of the company shares on the stock market is the real control.
The first great stock market bubble was the Mississippi Company in France and was led by a Scotsman, John Law. Along with with control of the company he also exerted considerable control over the Banque Royale – the French national bank. The result was a system of share sales which spiralled completely out of control with the central bank making almost daily changes in its rules to enable the sale of more shares in the Mississippi company or to support their price. Ultimately the whole system crashed in 1720; Ferguson argues that this led in part to the French Revolution since the whole performance put the French off exciting financial innovations which could have lead to a more stable system.
Ferguson identifies five stages to a speculative bubble:
- Displacement – something changes which leads to a new economic opportunity.
- Euphoria – prices start to spiral upwards.
- Mania – first time buyers rush in and fall prey to swindlers.
- Distress – insiders realise the game is up and start to leave.
- Revulsion – everyone else realises the game is up and try too leave too. The bubble bursts.
The depressing thing is that people have been dutifully following these five steps for nearly 300 years!
Next up is insurance, and scientific developments in statistics make an appearance. Ferguson focuses on the Scottish Widows insurance scheme, set up in 1744, to pay pensions to the widows of Scottish clergymen. Although he introduces a wide range of statistical developments including work by Pascal, Bernoulli’s (Jacob and Daniel), de Moivre and Bayes it seems to me the key development were the mortality tables compiled by John Graunt in 1662.
The presence of numerate scientists should not be seen as a panacea though, the Black-Scholes equation for pricing options looks like a piece of thermodynamics: Merton and Scholes won a Nobel Prize for it (Black missed out having died) nevertheless over-enthusiastic application of this equation lead to a fairly serious crash.
Ferguson comments that we are currently in a second round of globalisation, prior to the First World War financial markets were already fairly globalised although quite often under circumstances of colonisation. The outbreak of war necessitated a substantial increase in government support and intervention in the markets and after the war difficult economic circumstances made it easy to continue with this.
It’s interesting to note that the idea of the property owning democracy grew out of the New Deal in the US in the 1930’s prior to that time only 40% of householders in the US were homeowners – the figure now approaches 70%. The same has happened in the UK, although somewhat later with fewer than half of people homeowners in 1970 and a level of approximately 70% now. In a sense the subprime mortgage lending that led to the recent recession is the final playing out of this policy. Ferguson is clearly not too enamoured of the property-owning democracy – seeing it as an over-concentration on a single asset class.
I found this a nice background to understanding economics, it shows how various financial innovations were introduced and how they can contribute to a successful economy. It also highlights how the misuse of such innovations can lead to financial disaster, and does so with depressing frequency. The chronology through the book is not very clear, I suspect he expands on particular instances that best illustrate his point rather focusing on first introduction. Although it has extensive notes and indexes, it could do with a glossary.
Mar 19 2011
Inordinately fond of bottles…
J.B.S. Haldane, when asked “What has the study of biology taught you about the Creator, Dr. Haldane?”, he replied:
“I’m not sure, but He seems to be inordinately fond of beetles.”
The National Museum of Science & Industry (NMSI) has recently released a catalogue of its collection in easily readable form, you can get it here. The data includes descriptions, types of object, date made, materials, sizes, and place made – although not all objects have data for all these items. Their intention was to give people an opportunity to use the data, now who would do such a thing?
The data comes in four 16mb CSV files plus a couple of other smaller ones covering the media library (pictures) and a small “events” library. I’ve focussed on the main catalogue. You can load these files individually into Microsoft Excel, each one has about 65536 rows so they’re a bit of a pain to use, alternatively you can upload them to a SQL database. This turns out to be exceedingly whizzy! I wrote a few blog posts about SQL a while back as I learnt about it and this is my first serious attempt to use it. Essentially SQL allows you to ask nearly human language looking questions of big datasets, like this:
USE sciencemuseum;
SELECT collection,
COUNT(collection)
FROM sciencemuseum.objects
GROUP BY collection
ORDER BY COUNT(collection) DESC
LIMIT 0, 11000;
This gets you a list of all the collections inside the Science Museums catalogue (there are 162) and tells you how many objects are in each of these collections. Collections have names like “SRM – Acoustics” and “NRM – Railway Timepieces”, the NMSI incorporates the National Railway Museum (NRM), and the National Media Museum (NMEM) as well as the Science Museum (SCM) – hence the first three letters of the collection name. I took the collection data and fed it into Many Eyes to make a bubble chart:
The size of the bubble shows you how many objects are in a particular collection, you can see a majority of the major collections are medical related. So what’s in these collections? As well as longer descriptions, many objects are classified into a more limited number of types. This bubble chart shows the number of objects of each type:
This is where we learn that the Science Museum is inordinately fond of bottles (or jars, or specimen jars, or albarello’s or “shop rounds”). There are also a lot of prints and posters, from the National Railway Museum. This highlights a limitation to this type of approach: the fact that there are many of an object tells you little. It perhaps tells you how pervasive medicine has been in science – it is the visible face of science and has been for many years.
I have also plotted when the objects in the collection were made:
This turns out to be slightly tricky since over the years different curators have had different ideas about how *exactly* to describe the date when an object was made. Unsurprisingly in the 19th century they probably didn’t consider that a computer would be able to process 200,000 records in 1/4 second but simultaneously be unable to understand that circa 1680, c. 1680, c1680, ca 1680 and ca. 1680 actually all mean the same thing. This shows a number of objects in the first few centuries AD, followed by a long break and gradual rise after 1600 – the period of the Scientific Revolution. The pace picks up once again at the beginning of the 19th century.
I also made a crack at plotting where all the objects originating in the UK came from, on PC this is a live Google Map and is zoomable, beneath the red bubbles are disks sized in proportion to the number of objects from that location:
From this I learnt that there was a Pilkingtons factory in St Asaph, and a man in Chirk made railway models. To me this is the value of programming, the compilers of the catalogue made decisions as to what they included but once in my hands I can look into the catalogue according to my interests. I can explore in my own way, if I were a better programmer I could perhaps present you with a slick interface to do the same.
Finally for this post, I tried to plot when the objects arrived at the museum, this was a bit tricky: for about 60% of the objects the object reference number for objects contains the year as the first four characters so I just have the data for these:
The Science Museum started in 1857, the enormous spike in 1889 is due to the acquisition of the collection of Sir John Percy on his death, I discovered this on the the Science Museum website. Actually, I’d like to commend the whole Science Museum site to you, it’s very nice.
I visited the Science Museum a number of times in my childhood, I must admit to preferring it to the Natural History Museum, which seemed to be overwhelming large. The only record I have of these visits is this picture of a German Exchange visit to the museum, in 1985:
I must admit to not being a big fan of museums and galleries, they make my feet ache and I can’t find what I’m looking for or I don’t know what I’m looking for, and there never seems to be enough information on the things I’m looking at. This adventure into the data is my way of visiting a museum, I think I’ll spend a bit more time in wandering around the museum.
I had an alternative title for people who had never heard of J.B.S. Haldane: “It’s full of jars”
Footnote
If the Many Eyes visualisation above don’t work, you can see them in different formats from my profile page.
Mar 08 2011
Book review: Doomsday Men by P.D. Smith
My next book review is on Doomsday Men: The Real Dr Strangelove and the Dream of the Superweapon by P.D. Smith. I arrived at this book via the comments on my earlier post about the Manhattan Project, the Allied project to develop the atomic bombs dropped on Hiroshima and Nagasaki at the end of the Second World War. I also wrote about science fiction, which is relevant to this book too.
Doomsday Men brings context to the Manhattan Project, it shows the early imagining of what radioactivity could bring in terms of weapons of war, it shows science fiction writers foreseeing the applications, politicians considering the practical use of weapons of mass destruction and scientists working towards them. Alongside atomic weapons the potential for war from the air had been well considered before it was implemented.
The book starts with the conception of a genuine doomsday superweapon, that’s to say one that would wipe out all life on earth. This had been a theme of science fiction in the past, but in the early 1950’s it became plausible. Essentially the trick is to set off a fusion explosion in the presence of a large quantity of a particular element, cobalt, which would pick up neutrons becoming intensely radioactive whilst being vapourised and cast up into the atmosphere to settle the world over providing a lethal dose of radiation. The amount of cobalt required is about 10,000 tonnes which is only a cube with sides 10 metres long. There’s an open question as to whether the dust would be distributed uniformly enough to wipe out all life.
Leo Szilard is a central character through the book, along with fellow Hungarians John Von Neumann, Eugene Wigner and Edward Teller, known collectively as the Hungarian Quartet. They arrived in the US, fleeing anti-Semitism in Europe and were to play an important part in the development of nuclear weapons. It’s very striking the number of European Jews who migrated to the US in the period after the First World War, including Albert Einstein and Enrico Fermi. In the first instance many of them were keen to help in the development of nuclear weapons as a response to Hitler’s rise in Germany: a state they believed had both the technical ability to make such weapons and, with Hitler, the will to use them in war. Towards the end of the Second World War many of them felt less enthusiastic about their use against the Japanese, despite Japan’s hideous development and use of biological weapons against the Chinese in the 1930’s. Following the war, Von Neumann and particularly Teller continued to be involved in further developments now driven by anti-Communism sentiments.
The route to the doomsday weapon started with the discovery of radioactivity towards the end of the 19th century, and in particular the discovery of radium by Pierre and Marie Curie at the turn of the century. Around 1902 Frederick Soddy and Sir William Crookes both highlighted the huge amounts of energy was bound up in matter. Crookes saying: “one gram could raise the entire fleet of the British Navy several thousand fleet in the sky”. By 1913 H.G. Wells had very explicitly written about a nuclear weapon in “A World Set Free”. The use of chemical weapons, tanks and aeroplanes in war had all been imagined well before they were used too. Clearly there are big technical issues to address in going from a science fiction idea to a real system in battle, but the point here is that these ideas had serious public currency well before they were realised: there could be no “we’ll keep this quiet and no-one will think of it”. In a sense the key theme of the book is the interweaving of fiction with fact through the first half of the 20th century.
It was during the First World War that “scientific” superweapons started to be used, and the importance of science in waging war started to be recognised explicitly. Fritz Haber, a chemist, Nobel prize-winner for his commercial synthesis of ammonia, contemporary of Einstein, was instrumental in bringing chemical weapons to war, he was a German nationalist and felt the development of such weapons a duty to his country. He seemed quite enthusiastic about his work, writing:
“Chlorine: easy to liquefy, disastrous to the human organism, very cheap, mind you! Phosgene: ten times as strong as chlorine. Mustard gas: the best fighting gas of all”.
Once the Germans had used chemical weapons the British and French quickly developed their own. Research and manufacture of chemical weapons was to involve up to 75,000 people by the end of the war – this is about half the number involved in the Manhattan Project. A minority of scientists considered chemical warfare as a blessing compared to the conventional equivalent, for many others it was utterly abhorrent. The military had mixed feelings. Chemical weapons were banned by a variety of treaties, practically they seemed something of a double-edged sword with the first British use of chlorine at Loos causing 2000 casualties on their own side which perhaps explains why they’ve been so rarely used since. With the rise of Nazism Haber, a Jew, was to flee Germany and die shortly thereafter.
The First World War also saw the foundation of the British Board of Invention and Research in 1916, tasked with finding science to fight wars – it sought ideas from the public, one of the which was to train cormorants to peck out the mortar between bricks!
Biological weapons were to be developed by the Japanese whilst at war in China during the 1930’s and the Second World War, in an effort led by Shiro Ishii. During this period thousands were to die through his work, many in a range of human experiments to match those carried out by the Nazi doctors. Following the Second World War Ishii was given immunity from prosecution in order that the US could obtain information on biological weapons from him.
So chemistry and biology produced rather unpleasant weapons but they could not be described as decisive: for that you need physicists.
Szilard was first to realise (in 1933) that an atomic bomb might be made via a chain reaction: the fission of an atomic nucleus producing two or more neutrons which would drive further fission. He made some effort to keep the idea secret, at least from the Germans, via a patent held by the British Admirality. This was a very unusual move for a scientist in an area of pure science. In 1939 he was to visit Roosevelt with Einstein to warn him of the potential for an atomic bomb and the possibility that the Germans would make one. Ultimately this contact led to the Manhattan Project and the bombs dropped on Hiroshima and Nagasaki: killing at least 200,000 people.
One of the recurring themes in fiction was the idea of a scientist discovering the doomsday weapon and then holding the world to ransom for peace with the new “system of the world”: a world government led by scientists and technocrats. This sort of idea is better described as left-wing rather than right-wing. And I can say, as a scientist, that it has a certain appeal! Perhaps this explains something of why scientists are more often perceived as left-wing rather than right-wing.
Doomsday Men ends with the story of Stanley Kubrick’s 1964 film “Dr Strangelove: or How I stopped worrying and learned to love the Bomb”. The title character appears to have been based on a combination of Teller, von Neumann and perhaps Werner von Braun – the German rocket scientist captured by the Americans who went on to found the US space programme.
Overall a rather good read: providing good context to the Manhattan Project and the Cold War, and the importance of science fiction in seeing into the future.
Footnote: one of the drawbacks of reading on a Kindle: I reached the end rather unexpectedly since the footnotes, bibliography, and index take up a third of the book!