Nautilus profiles the great man, thusly:
Describing his life, shortly before his death, Newton put his contributions this way: â€œI donâ€™t know what I may seem to the world, but, as to myself, I seem to have been only like a boy playing on the sea shore, and diverting myself in now and then finding a smoother pebble or a prettier shell than ordinary, whilst the great ocean of truth lay undiscovered before me.â€
One thing Newton never did do, actually, was play at the seashore. In fact, though he profited greatly from occasional interaction with scientists elsewhere in Britain and on the Continentâ€”often by mailâ€”he never left the vicinity of the small triangle connecting his birthplace, Woolsthorpe, his university, Cambridge, and his capital city, London. Nor did he seem to â€œplayâ€ in any sense of the word that most of us use. Newtonâ€™s life did not include many friends, or family he felt close to, or even a single lover, for, at least until his later years, getting Newton to socialize was something like convincing cats to gather for a game of Scrabble. Perhaps most telling was a remark by a distant relative, Humphrey Newton, who served as his assistant for five years: he saw Newton laugh only onceâ€”when someone asked him why anyone would want to study Euclid.
Newton had a purely disinterested passion for understanding the world, not a drive to improve it to benefit humankind. He achieved much fame in his lifetime, but had no one to share it with. He achieved intellectual triumph, but never love. He received the highest of accolades and honors, but spent much of his time in intellectual quarrel. It would be nice to be able to say that this giant of intellect was an empathetic, agreeable man, but if he had any such tendencies he did a good job suppressing them and coming off as an arrogant misanthrope. He was the kind of man who, if you said it was a gray day, would say, â€œno, actually the sky is blue.â€ Even more annoying, he was the kind who could prove it. Physicist Richard Feynman voiced the feelings of many a self-absorbed scientist when he wrote a book titled, What Do You Care What Other People Think? Newton never wrote a memoir, but if he had, he probably would have called it I Hope I Really Pissed You Off, or maybe, Donâ€™t Bother Me, You Ass.
Lock, Stock, & History is similiarly irreverent.
Today we consider the great scientist Isaac Newton to be one of the greatest geniuses of history. After all he developed many laws and theories in the fields of physics, optics, mathematics, and astronomy which are still very relevant today. However if you actually met Sir Isaac Newton today, I guarantee you would think him to be a nutjob.
While Newton is celebrated today for his many scientific breakthroughs, his works in other, less scientific fields are largely forgotten. A dedicated alchemist and occultist, Newton spent much of his time working on experiments that are today mostly considered outright bizarre. A devoted follower of many interesting occult sects, Newton spent years trying to determine the â€œsacred geometryâ€ of Solomonâ€™s Temple, with hopes of mathematically divining the secrets of God. He also spent much time and energy trying to find and de-crypt the â€œBible Codeâ€. In a detailed study of the Bible, Newton made a prediction for the end of world using the chronology of the Holy Book. According to Newton, the world should come to an end in 2060 AD. Newton calculated the end of the world specifically â€œto put a stop to the rash conjectures of fanciful men who are frequently predicting the time of the end, and by doing so bring the sacred prophesies into discredit as often as their predictions fail.â€ Eat your hearts out Mayans!
Of all of Newtonâ€™s discoveries, from gravity to refraction of light, from divining the location of Atlantis to discovering how to communicate with angels, Newton believed his most important work was in creating the Philosopherâ€™s Stone. Newton believed that with the Philosophers Stone he could have everlasting life and be able to turn lead into gold. He spent years, if not decades studying the work of the noted alchemist Nicholas Flammel and other alchemists, with the believe that he was about to make a breakthrough at any moment. In fact, to Newton the discovery of the Philosopherâ€™s Stone was so important that all his other discoveries were trivial when compared to his work in alchemy. His obsession with the stone caused him to have a weird set of priorities. After developing calculus, he kept his results to himself for over 30 years because he didnâ€™t think it was important and â€œdisliked intellectual mattersâ€.
Finally some of Newtonâ€™s experiments were just downright kooky and creepy. According to writings in his notebook, one experiment involved him sticking a needle into his eyeball and twirling it around to analyze how light traveled through his optic nerve,
I tooke a bodkine (needle) & put it betwixt my eye & [the] bone as neare to [the] backside of my eye as I could: & pressing my eye [with the] end of it (soe as to make [the] curvature a, bcdef in my eye) there appeared severall white darke & coloured circles r, s, t, &c. Which circles were plainest when I continued to rub my eye [with the] point of [the] bodkine, but if I held my eye & [the] bodkin still, though I continued to presse my eye [with] it yet [the] circles would grow faint & often disappeare untill I removed [them] by moving my eye or [the] bodkin.
In another strange experiment, Newton stared directly at the sun for as long as he could bare with the same objective of his â€œneedle experimentâ€.
While dedicated to the discovery of the Philosopherâ€™s Stone, his work would all be in vain as he died in 1727. He never did figure out how to turn lead into gold.
Golden Ratio Ï† = (1+sqrt(5))/2 = 1.6180339887498948482â€¦
In mathematics, two quantities are in the golden ratio if their ratio is the same as the ratio of their sum to the larger of the two quantities. Expressed algebraically, for quantities a and b with a > b > 0. Two quantities a and b are said to be in the golden ratio Ï† if
(a+b)/a = a/b = Ï†
One method for finding the value of Ï† is to start with the left fraction. Through simplifying the fraction and substituting in b/a = 1/Ï†:
(a+b)/a = 1+ b/a = 1+1/Ï†
Therefore: 1+1/Ï† = Ï†
Multiplying by Ï† gives: Ï†^2 – Ï† – 1 = 0
Using the quadratic formula, two solutions are obtained::
Ï† = (1- sqrt(5))/2 or Ï† = (1+sqrt(5))/2
Because Ï† is the ratio between positive quantities Ï† is necessarily positive:
Ï† = (1+sqrt(5))/2 = 1.6180339887498948482â€¦
See more at Golden Ratio.
Image: Phi (golden number) by Steve Lewis.
From Ratak Monodosico.
Network combining the five major Icelandic sagas. White nodes represent characters who appear in more than one saga. There is a large overlap of characters from LaxdÃ¦la Saga (green) and NjÃ¡ls Saga (red). The other sagas are Egil (blue), Vatnsdaela (yellow), and Gisla (light blue).
Veronique Greenwood, at the Verge, describes a fascinating application of the techniques of statistical physics to identify patterns and relationships in medieval literature.
An unusual article recently appeared in the magazine of the Royal Statistical Society and American Statistical Association.
It featured web-like diagrams of lines connecting nodes, a hallmark of research that analyzes networks. But each node, rather than being a plain dot, was the head of a burly, red-bearded Viking sporting a horned hat, his tresses blowing in the wind.
This whimsical-seeming piece of scholarship went on to describe the social network of more than 1,500 characters in the Icelandic Sagas, epic tales about the colonization of Iceland around a thousand years ago that were first written down a few hundred years after that. It was the work of a pair of statistical physicists, Ralph Kenna of University of Coventry in the UK and his graduate student PÃ¡draig Mac Carron, now at Oxford, who are applying the tools of their trade to works of epic literature, legend, and myth.
For this particular analysis, they painstakingly recorded the relationship of every settler in 18 sagas. The resulting web of interactions helped shed light on theories humanities scholars have been discussing for years, and even picked up on some previously unnoticed patterns. Their work is part of a movement that promises a new way to approach old questions in literature, history, and archaeology, with fanciful diagrams as just the appetizer.
Demonstration of social network analysis, with red lines representing unfriendly connections and green lines representing friendly ones.
The story of how Kenna and Mac Carron got here begins with the Irish tale of the cattle-raid of Cooley, or the TÃ¡in BÃ³ CÃºailnge. That yarn tells how the warrior-queen Medb of Connacht rallies an army to steal a fine bull from Ulster, and how youthful CÃºchulainn, an Ulster folk hero, stands against her. Complete with a maiden prophet with three pupils in each eye, wild chariot rides, and an enormous cast of characters, it’s a story to grip anyone’s imagination.
It’s a story that Kenna and Mac Carron, who are both Irish, have known since childhood. Several years ago, Kenna, who has a successful career as a physicist, found his thoughts returning to mythology. It wasnâ€™t as big a departure as it might seem at first. “In statistical physics, you’re dealing with objects such as gasses that are comprised of molecules and atoms,” he says. “The system consists of many small entities, and so many of them you cannot deal with them individually, you have to deal with them statistically.” Some physicists have started to use similar methods to look at how large numbers of people interact to produce aspects of human society, and Kenna wondered whether they could be applied to myths and stories. The TÃ¡in, which comes to us in pieces from many different manuscripts, the oldest nearly 1,000 years old, is considered literature rather than historical account. But it might still encode, in a way statistics can reveal, information about the society that produced it. Math might also help classify tales in a new way, quantitatively, in addition to the usual qualitative classifications.
Hat tip to Karen L. Myers.
The latest wrinkle in the contemporary Jane Austen boom is described at Science Blog:
Austenâ€™s novels are game theory textbooks,â€ Michael Suk-Young Chwe writes in â€œJane Austen, Game Theorist,â€ which Princeton University Press published April 21. â€œSheâ€™s trying to get readers to use their higher thinking skills and to think strategically.â€
At its most basic level, game theory assesses all the choices available to two (or more) people in a given situation and assigns a numerical value to the benefit each person reaps from each choice. Often, the choice that is most valuable to one player comes at the expense of the other; hence, game theoryâ€™s best-known phrase â€” â€œzero-sum game.â€ But just as frequently, there is a choice with unexpected benefits for both players.
â€œIn game theory, you make choices by anticipating the payoffs for others,â€ Chwe explains.
Chwe argues that Austen explores this concept in all six of her novels, albeit with a different vocabulary than the one used by Nash, von Neumann and other game theory greats some 150 years later. In Austenâ€™s romantic fiction, this type of strategic thinking is described as â€œpenetration,â€ â€œforesightâ€ or â€œa good scheme.â€
In â€œPride and Prejudice,â€ for instance, Mrs. Bennet, a mother eager to marry off her five daughters, sends her oldest, Jane, on horseback to a neighboring estate, even though sheâ€™s aware a storm is on the way. â€œMrs. Bennet knows full well that because of the rain, Janeâ€™s hosts will invite her to spend the night, thus maximizing face time with the eligible bachelor there, Charles Bingley, whom Jane eventually marries,â€ Chwe said.
In â€œPersuasion,â€ the unmarried heroine, Anne Elliot, is approached by Sophia Croft, the sister of a man whose marriage proposal Anne spurned eight years earlier â€” a decision she still bitterly regrets. Mrs. Croft casually asks Anne whether sheâ€™s heard that her brother has married. Anne flinches, thinking the reference is to her former beau, Captain Frederick Wentworth, but relaxes upon learning that Mrs. Croft is actually referring to their younger brother, Edward.
â€œItâ€™s hard to imagine a better way for Mrs. Croft to gauge Anneâ€™s visceral interest in her unmarried brother,â€ said Chwe, a UCLA associate professor of political science (whose last name is pronounced like â€œchessâ€ without the â€œssâ€). The rest of the novel involves schemes to give Captain Wentworth so many signals of Anneâ€™s enduring love that he finds the courage to propose to her again.
Joseph C. McMurray discusses the Marquis de Condorcet’s mathematical analysis favoring decision-making by larger numbers of people.
An interesting, if somewhat uncommon, lens through which to view politics is that of mathematics. One of the strongest arguments ever made in favor of democracy, for example, was in 1785 by the political philosopher-mathematician, Nicolas de Condorcet. Because different people possess different pieces of information about an issue, he reasoned, they predict different outcomes from the same policy proposals, and will thus favor different policies, even when they actually share a common goal. Ultimately, however, if the future were perfectly known, some of these predictions would prove more accurate than others. From a present vantage point, then, each voter has some probability of actually favoring an inferior policy. Individually, this probability may be rather high, but collective decisions draw information from large numbers of sources, mistaking mistakes less likely.
To clarify Condorcetâ€™s argument, note that an individual who knows nothing can identify the more effective of two policies with 50% probability; if she knows a lot about an issue, her odds are higher. For the sake of argument, suppose that a citizen correctly identifies the better alternative 51% of the time. On any given issue, then, many will erroneously support the inferior policy, but (assuming that voters form opinions independently, in a statistical sense) a 51% majority will favor whichever policy is actually superior. More formally, the probability of a collective mistake approaches zero as the number of voters grows large.
Condorcetâ€™s mathematical analysis assumes that votersâ€™ opinions are equally reliable, but in reality, expertise varies widely on any issue, which raises the question of who should be voting? One conventional view is that everyone should participate; in fact, this has a mathematical justification, since in Condorcetâ€™s model, collective errors become less likely as the number of voters increases. On the other hand, another common view is that citizens with only limited information should abstain, leaving a decision to those who know the most about the issue. Ultimately, the question must be settled mathematically: assuming that different citizens have different probabilities of correctly identifying good policies, what configuration of voter participation maximizes the probability of making the right collective decision?
It turns out that, when voters differ in expertise, it is not optimal for all to vote, even when each citizenâ€™s private accuracy exceeds 50%. In other words, a citizen with only limited expertise on an issue can best serve the electorate by ignoring her own opinion and abstaining, in deference to those who know more. …
This raises a new question, however, which is who should continue voting: if the least informed citizens all abstain, then a moderately informed citizen now becomes the least informed voter; should she abstain, as well?
Mathematically, it turns out that for any distribution of expertise, there is a threshold above which citizens should continue voting, no matter how large the electorate grows. A citizen right at this threshold is less knowledgeable than other voters, but nevertheless improves the collective electoral decision by bolstering the number of votes. The formula that derives this threshold is of limited practical use, since voter accuracies cannot readily be measured, but simple example distributions demonstrate that voting may well be optimal for a sizeable majority of the electorate.
The dual message that poorly informed votes reduce the quality of electoral decisions, but that moderately informed votes can improve even the decisions made even by more expert peers, may leave an individual feeling conflicted as to whether she should express her tentative opinions, or abstain in deference to those with better expertise. Assuming that her peers vote and abstain optimally, it may be useful to first predict voter turnout, and then participate (or not) accordingly: when half the electorate votes, it should be the better-informed half; when voter turnout is 75%, all but the least-informed quartile should participate. …
If Condorcetâ€™s basic premise is right, an uninformed citizenâ€™s highest contribution may actually be to abstain from voting, trusting her peers to make decisions on her behalf. At the same time, voters with only limited expertise can rest assured that a single, moderately-informed vote can improve upon the decision made by a large number of experts. One might say that this is the true essence of democracy.
His conclusion seems to accord with observed results. Ordinary people are surprisingly well able to correct the follies and delusions which too commonly afflict the experts and elites, but there are also people so clueless that they are always going to vote wrong.
Hat tip to The Meta Picture via Kathleen Wagner.
“How do you read a two-thousand-year-old manuscript that has been erased, cut up, written on and painted over [i.e., a palimpsest]? With a powerful particle accelerator, of course! Ancient books curator William Noel tells the fascinating story behind the Archimedes palimpsest, a Byzantine prayer book containing previously-unknown original writings from ancient Greek mathematician Archimedes and others.”
Archimedes Palimpsest website
Hat tip to Dot Porter.