What “impossible” meant to Feynman

Today in Nautilus:
“Impossible!” Feynman finally said. I nodded in agreement and smiled, because I knew that to be one of his greatest compliments.He looked back up at the wall, shaking his head. “Absolutely impossible! That is one of the most amazing things I have ever seen.”

From The Second Kind of Impossible: The Extraordinary Quest for a New Form of Matter by Paul Steinhardt. Copyright © 2017 by Paul J. Steinhardt. This is a fascinating book. Paul Steinhardt was a fellow fellow when I was at the Radcliffe Institute. I heard his story then. Here is a summary of his book from the publisher’s website.

“When leading Princeton physicist Paul Steinhardt began working in the 1980s, scientists thought they knew all the conceivable forms of matter. The Second Kind of Impossible is the story of Steinhardt’s thirty-five-year-long quest to challenge conventional wisdom. It begins with a curious geometric pattern that inspires two theoretical physicists to propose a radically new type of matter—one that raises the possibility of new materials with never before seen properties, but that violates laws set in stone for centuries. Steinhardt dubs this new form of matter “quasicrystal.” The rest of the scientific community calls it simply impossible.

The Second Kind of Impossible captures Steinhardt’s scientific odyssey as it unfolds over decades, first to prove viability, and then to pursue his wildest conjecture—that nature made quasicrystals long before humans discovered them. Along the way, his team encounters clandestine collectors, corrupt scientists, secret diaries, international smugglers, and KGB agents. Their quest culminates in a daring expedition to a distant corner of the Earth, in pursuit of tiny fragments of a meteorite forged at the birth of the solar system.”

Maryam Mirzakhani and the universe of all possible billiard tables

Maryam Mirzakhani has died today. She was 40 years old. From Stanford News: “A self-professed “slow” mathematician, Mirzakhani’s colleagues describe her as ambitious, resolute and fearless in the face of problems others would not, or could not, tackle. She denied herself the easy path, choosing instead to tackle thornier issues. Her preferred method of working on a problem was to doodle on large sheets of white paper, scribbling formulas on the periphery of her drawings. Her young daughter described her mother at work as “painting.” “You have to spend some energy and effort to see the beauty of math,” she told one reporter. In another interview, she said of her process: “I don’t have any particular recipe [for developing new proofs] … It is like being lost in a jungle and trying to use all the knowledge that you can gather to come up with some new tricks, and with some luck you might find a way out.”

In her honor, I am reposting a 2014 post from this blog. Sources: Wikepedia. Article on Maryam Mirzakhani in the Guardian. Article and video in Quanta Magazine.

Maryam_MirzakhaniJordan Ellenberg‘s popular explanation of what earned Mirzakhani the Fields Medal in 2014: “… [Her] work expertly blends dynamics with geometry. Among other things, she studies billiards. But now, in a move very characteristic of modern mathematics, it gets kind of meta: She considers not just one billiard table, but the universe of all possible billiard tables. And the kind of dynamics she studies doesn’t directly concern the motion of the billiards on the table, but instead a transformation of the billiard table itself, which is changing its shape in a rule-governed way; if you like, the table itself moves like a strange planet around the universe of all possible tables … This isn’t the kind of thing you do to win at pool, but it’s the kind of thing you do to win a Fields Medal. And it’s what you need to do in order to expose the dynamics at the heart of geometry; for there’s no question that they’re there.”

One of 10 people who mattered this year in science: Nature, volume 516, issue 7531, 17 December 2014. 2017 obituary in the New Yorker.

The slippery road towards academic dishonesty

Here are some reflections on the latest academic dishonesty scandal, as reported in the New York Times, 29 May 2015:

“The graduate student at the center of a scandal over a newly retracted study that has shaken trust in the conduct of social science apologized for lying about aspects of the study, including who paid for it and its methodology, but he said Friday in his first interview since the scandal broke that he stands by its finding that gay canvassers can influence voters’ attitudes on same-sex marriage.” Mr. LaCour objects to one of the main charges against him – that he improperly destroyed his raw data. But he admits that he lied about the agencies that funded his research. “Mr. LaCour said he thought the funding sources he claimed would shore up the plausibility of the work.”

Mr. LaCour very clearly crossed a line by misrepresenting funding sources for his study. But where is that line exactly? In academia, people can get away with lying in a more indirect way by exploiting implicatures in CVs, personnel evaluations, or grant applications. For example, X may list grants when reporting their achievements without specifying their exact role in those grants. This triggers the implicature that X was a Principal Investigator or Co-Principal Investigator for the grants. Or X may submit a list of PhD students, leaving out information about the exact role they played in those students’ training. In the US, this generates the implicature that X was chair or co-chair of the respective PhD committees. What if X shores up their CV in this way, calculating that false implicatures will be derived by supervisors and funding agencies? Is this a case of academic dishonesty? Has the line been crossed? 

What can we do to foster more sensitivity and respect for scholarly integrity in academia? Colin S. Diver, the former President of Reed College, makes a plea for abandoning the “higher education’s arms race” (from the Boston Globe, 5 September 2012): “Finally, no institution can convincingly preach ethical behavior to its students unless its own behavior is governed by the highest ethical standards. When higher education gets caught up in a frenzy of exaggerated marketing claims, misreporting of data, sale of admission slots, or varsity-sport abuses, it destroys its moral authority. As Reed’s president, I was proud to lead a college that refused to cooperate with the notorious US News & World Report rankings, which symbolize the distortion of academic virtues in pursuit of higher education’s arms race.”

Clever fish

Nature, 26 May 2015. Animal behavior: Inside the cunning, caring, and greedy minds of fish. This is an article describing the remarkable discoveries about fish intelligence made by behavioral ecologist Redouan Bshary.

“Primate chauvinism may now be poised to decline, thanks in large part to Bshary’s fish work,” says primatologist and ethologist Frans de Waal of Emory University in Atlanta, Georgia. “They now really do have to take on board that most species are going to have a type of smart intelligence.”

“Redouan has thrown down the gauntlet to us primatologists,” says Carel van Schaik, an expert in orang-utan culture at the University of Zurich in Switzerland. “He has made us realize that some of the explanations of primate intelligence that we have cherished don’t hold water anymore.”

The word “cooperation” covers a wide range of rather different behaviors, though. Here is a video on what human toddlers and chimps can do in the way of cooperation. I yet have to see a fish recognize what I am trying to do and come to my help.

The man who tried to redeem the world with logic


Source: Nautilus

From Nautilus:

“Though they started at opposite ends of the socioeconomic spectrum, McCulloch and Pitts were destined to live, work, and die together. Along the way, they would create the first mechanistic theory of the mind, the first computational approach to neuroscience, the logical design of modern computers, and the pillars of artificial intelligence. But this is more than a story about a fruitful research collaboration. It is also about the bonds of friendship, the fragility of the mind, and the limits of logic’s ability to redeem a messy and imperfect world.”

“The moment they spoke, they realized they shared a hero in common: Gottfried Leibniz. The 17th-century philosopher had attempted to create an alphabet of human thought, each letter of which represented a concept and could be combined and manipulated according to a set of logical rules to compute all knowledge—a vision that promised to transform the imperfect outside world into the rational sanctuary of a library.”

Kai von Fintel: Decoding the Meaning of Language

kai Kai von Fintel: “Linguistics is basically the science of language. You use a scientific approach, but you get to apply it to something central to humanity. We put these signals in the world and others can read our mind to some extent. I find that a baffling phenomenon — why not try to figure that out?” Full story by SHASS Communications.

“What makes linguistics, the science of language, so fascinating is that it exists at the intersection of science and the humanities. You use a scientific approach, and you get to apply it to something central to humanity.”

“We’re trying to find patterns in data, making hypotheses, throwing more data at it and seeing how it holds up,” he says. “We look at facts to distinguish what we can understand versus what we can’t.”

Festival delle Scienze 2015: The Unknown

festival delle scienze2015

“In order to make progress, one must leave the door to the unknown ajar – ajar only.”
“Per fare progressi, si deve tenere socchiusa la porta verso l’ignoto – socchiusa solamente.”
Richard Feynman

Co-directors Vittorio Bo & Jacopo Romoli: ” … this tenth edition of the Rome Science Festival aims to be a celebration of doubt, uncertainty and the unknown and the particular way to penetrate it known as the scientific method. The Festival programme is centred around questions involving physics, biology, psychology and linguistics: What is the relationship between uncertainty and indetermination? Between uncertainty and chance? What is hidden in black holes or in what we call dark matter or in the concept of infinity? How do we relate cognitively to uncertainty and the unknown and what language do we use to speak about them? How can we calculate uncertainty precisely? How do we use secrecy in politics?” The full program of the festival is here (Italian & English).

Learning everything about anything?

Source: Kurzweil Accelerating Intelligence.

Credit: University of Washington

Credit: University of Washington

“Computer scientists from the University of Washington and the Allen Institute for Artificial Intelligence in Seattle have created an automated computer program that they claim teaches everything there is to know about any visual concept. Called Learning Everything about Anything (LEVAN), the program searches millions of books and images on the Web to learn all possible variations of a concept, then displays the results to users as a comprehensive, browsable list of images, helping them explore and understand topics quickly in great detail. You can try it here.”

Intelligent as it may be, LEVAN doesn’t seem to know the difference between a horse eye and an eye horse, between a horse shoe and a shoe horse, or between a horse shed and a shed horse.  

Connections: the discussion of the headedness of noun-noun compounds in my Radcliffe video on Mapping Possibilities. Also: Teon Brooks on representing compounds in the brain. 

A dictionary for the meanings of genes

From Cori Bargmann’s autobiography

Source: http://www.rockefeller.edu/research/faculty/labheads/CoriBargmann/

Source: The Rockefeller University

“Human biology, especially human neurobiology, is very complex, and our view of the human brain is fragmentary. However, the genomes of humans and worms share more genes than any of us expected, including most classes of genes that are important in the nervous system. (The complexity of the human nervous system comes from regulating the genes in different ways, and from deploying them in vastly larger numbers of neurons.) The basic functions of those genes are similar in all animals, so if we view one goal of biology as building a “dictionary” containing the meaning of each gene, we can assemble definitions in that dictionary from any animal, with a good chance that the definitions and grammar will apply across all animals and humans. Those of us who study worms hope to meet those who study human brains in the middle, using the universality of biology to translate understanding across organisms.”

Cori Bargmann’s 2013 Breakthrough Prize talk: Using fixed circuits to generate flexible behavior

I am intrigued by the notion of compositionality displayed by the ‘grammar of genes’. A particular gene invariably makes the same contribution in every animal that has it, but this invariable contribution is altered through predictable contextual interactions so that the same set of genes can lead to very different outcomes. The issue is relevant for the old debate about meaning composition for conditionals. In my paper for the Edgington volume, for example, I showed that embedded conditionals interact with surrounding quantifiers in not completely ‘algorithmic’ ways. Does this mean that we should just give up on the idea of a compositional semantics for conditionals? Or should we rethink our ideas about compositionality in natural language semantics? Non-compositionality is a fact of life for content words (cat, blue, sing …), which are part of the non-logical vocabulary of natural languages. Nouns, adjectives, and verbs can change their meanings in seemingly unpredictable ways, depending on the linguistic and non-linguistic environment they find themselves in. But the semantic contribution of function words (if, and, every, …), which are part of the logical vocabulary of natural languages, seems to be invariant and resistant to uncontrolled contextual interference. Context seems to be able to affect the interpretation of function words only through certain grammatically determined ‘gates’ or ‘channels’  like those responsible for domain restrictions

Connections: Oxford Handbook of Compositionality.  

Connections: NIH BRAIN Working Group.