Posts Tagged ‘Mathematics’
“It is entirely possible that you get unpredictable behavior out of predictable rules”*…
For centuries, the hypnotic winter flights of starlings were thought to be telepathy. Today, science reveals a much darker reality. Behind one of nature’s most breathtaking visual displays lies a mathematical masterpiece built entirely on fear. From The Great Planet…
During the autumn and winter months, if you look to the skies over Europe and North America about an hour before sunset, you might witness one of nature’s most breathtaking visual spectacles. These massive black clouds of tens of thousands of European starlings (Sturnus vulgaris)—constantly shifting into spheres, planes, and waves—are known in the scientific community as a “murmuration.” Named after the deep, resonant sound produced by thousands of wings beating in unison, the phenomenon looks from afar like a colossal calligraphy brushstroke across the sky or a ball of fire flickering in the wind. Yet, beyond this aesthetic illusion lies a ruthless and flawless algorithm for survival.
For centuries, researchers were baffled by how tens of thousands of birds could fly at speeds of around 45 kilometers per hour without a single collision. This coordination was so inconceivable that in 1931, prominent ornithologist Edmund Selous described it as “a madness in the sky.” To Selous, there was only one logical explanation for this complex behavior: telepathy. “They must think collectively, all at the same time,” he wrote.
Like many others, Selous assumed that complex behavior must stem from equally complex origins. However, groundbreaking observations made in 2005 by the married physicists Andrea Cavagna and Irene Giardina from the rooftop of the Palazzo Massimo in Rome revealed a truth far more striking than telepathy. Over three years of chilly evenings, the team used pairs of cameras to reconstruct the 3D positions of more than 4,000 birds in a single flock, proving that there is no overarching plan and no leader. Each starling in the flock interacts exclusively with its seven closest neighbors—a number researchers suggest might be the maximum capacity their brains can handle. The starlings do not keep track of these constantly changing alliances; they simply align their flight path with whichever seven birds are nearest, remaining close, but never too close.
The birds do not need to engage in complex communication to navigate their massive trajectories. When Charlotte Hemelrijk of the University of Groningen in the Netherlands plugged just three simple rules—avoidance, alignment, and attraction—along with basic aerodynamics into a computer model, the resulting virtual murmuration perfectly matched the real-world data gathered in Rome.
Physicists explain this vast web of interaction through the concept of “scale-free correlation.” When a starling turns, this new alignment influences its neighbors, who in turn influence theirs. Yet, unlike a children’s game of telephone, this transfer of information does not degrade with errors; instead, the errors are entirely washed away in the movement. No matter how large the flock becomes, the information arrives at the furthest edge completely uncorrupted. Even though each bird only pays attention to seven neighbors, its senses effectively extend across the entire murmuration, allowing it to instantly react to a movement hundreds of birds away. The reason the flock looks like a single entity from the outside is that, physically, it truly behaves like one.
Why do starlings expend such an immense amount of energy to constantly shift shape in the sky? For a long time, the scientific consensus leaned toward the “warmer together” hypothesis, assuming the displays served to advertise a roosting site and gather more birds for thermal benefits on cold nights. However, an analysis of over 3,000 murmurations across 23 countries, gathered through citizen science, revealed only a weak negative correlation between temperature and flock duration. The true determining factor was the “safer together” principle: defense against predators.
In approximately 30% of the recorded murmurations, birds of prey such as hawks, falcons, or harriers were present. As predators approached or actively engaged the flock, both the duration and the size of the murmuration increased…
… Millions of years of evolution have granted starlings this colossal collective intelligence, allowing them to outmaneuver even nature’s most apex aerial predators. Yet, the primary threat they face today comes not from the sky, but from human activity on the ground. While European starlings are omnivorous, they rely heavily on insect larvae, such as leatherjackets, that live in the soil beneath grasslands; as these grassy areas vanish, so does their food supply. Their habitats are rapidly shrinking due to urbanization and changing farming practices, such as moving livestock feed indoors…
… For a species to merely exist within an ecosystem, narrowly avoiding physical extinction, does not mean it has truly been saved. Earth’s most beautiful phenomena only emerge when living things can act together in great, thriving numbers. You can evolve a flawless biological algorithm based on scale-free correlation to outwit nature’s most ruthless predators, but when your habitat is suddenly paved over with concrete, evolution affords you no time to design a new defense mechanism. The fact that we have finally decoded the mathematical secret of the starling murmuration just as we are on the verge of losing it forever remains one of the most haunting questions suspended in our skies—a stark reflection of modern human hubris and our destructive relationship with the planet…
A flawless algorithm is fading from our skies: “The Mathematics of Fear: Why Starlings Murmurate.”
See also: “The brain has corridors surpassing / Material place.”
* Frank Heppner (an ornihologist who helped create the first computer simulations of bird flocks in flight)
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As we fly, we might send beautifully-plumed birthday greetings to Elliott Coues; he was born on this date in 1842. An army surgeon, historian, writer, and geographer, he led surveys of the Arizona Territory, first in his army posting there and later as secretary of the United States Geological and Geographical Survey of the Territories.
But we remember him here for his lifelong pursuit of his boyhood passion for birds. As a teen, he met many naturalists at the Smithsonian Institution and published his first ornithological paper in 1859, at age 19. As his army assignments took him to various locations throughout the West, he continued studying the bird life in each new area, and found new species. His Key to North American Birds (1872) was the first work of its kind to present a taxonomic classification of birds according to an artificial key and promoted the systematic study of wild fowl in North America. He founded the American Ornithological Union in 1883, and was editor of its publication, The Auk.
“Every river seems to come with a purpose”*…
The Yukon Delta in Alaska formed where the Yukon River flows into the Bering Sea
A simple scaling law brings order to the chaos of flowing water, rock, and sediment. As Natalie Wolchover reports, new findings have extended the law even further…
A river has my heart. It’s not the austere, black Thames winding through London, where I was born, but a lazy green one 5,000 miles away, where I spent my adolescence: the Blanco River in Texas. My maternal ancestors have dipped into its waters for generations, as I have on countless summer days.
The Blanco is a tributary of the San Marcos, which flows into the Guadalupe, and on into the Gulf of Mexico. You can probably picture how this looks on a map because all river networks look similar, creeping through the landscape, merging into ever wider and longer channels, downhill to the sea. The pattern resembles twigs on branches that connect to trunks of trees (and the branching of their root systems, too), and it likewise resembles the veins of plant leaves, our own systems of blood vessels, and train and highway networks that feed into cities.
There’s something appealing about this ubiquitous pattern, so appealing to me personally that I have it tattooed on my forearm: the silhouette of a tree, with leafless branches reaching upward and roots burrowing downward, almost in mirror image. “The shapes of rivers and leaf vasculature and so on — branching networks — you can just about grasp the pattern, but it’s still chaotic, so there’s something fascinating with that,” said Chris Paola, a river scientist at the University of Minnesota.
Systems that branch in this way are “transport networks”: They transport some fluid substance (water, blood, traffic) from every place to a single place (the sea, a heart, a city center). Of the various examples, rivers are especially revealing, I think, since they arise from neither biological evolution nor urban planning, but rather chaotic Earth processes. Yet they obey simple, universal laws…
…
… In 1957, a U.S. Geological Survey scientist named John Hack discovered the most important law of river networks. In rivers and streams in Virginia and Maryland, Hack measured the length of each stream and the area of the land that slopes toward that stream and therefore drains into it, called its basin or drainage area. What he discovered is now known as Hack’s law: Any stream, from the littlest brook to the mightiest river, has a length that’s proportional to its drainage area raised to the power of 0.6. (In symbolic form: L ~ A0.6.) There’s a bit of variance around that 0.6 value — Earth is, after all, a complicated place — but “the general regularity of the relation is nevertheless remarkable,” Hack wrote. “Stream lengths tend to increase proportionally to the 0.6 power of the drainage area, regardless of the geological or structural characteristics of the area.”
As more and better data has accrued, especially from satellite imagery, Hack’s law has held worldwide. Why this is the case is the essential mystery geomorphologists have grappled with ever since. “Hack’s law is still the big question,” said Hansjörg Seybold, a geomorphologist at the Institute for Interdisciplinary Mountain Research at the Austrian Academy of Sciences.
It’s not so surprising that the bigger the land area of the basin, the longer the stream that drains it. But in a purely mathematical sense, one might expect that stream length would follow a slightly different power law. Imagine a square patch of land. You might guess that regardless of slope or size, in idealized form, the land would drain into a stream that’s the length of one of its sides — a vertical line down the middle, for example. That length is the square root of the area — or A to the power of 0.5.
Under that circumstance, big river basins would have the same proportions as the small river basins that feed the tributaries within them. Their structure would be the same, regardless of size. But that’s not what Hack’s law reveals.
Instead, as a drainage areas get larger, the length of their streams increases faster. “A nice way to phrase it would be that small basins are short and squat, and large basins are long and thin,” said Daniel Rothman, a geophysicist at the Massachusetts Institute of Technology. We unknowingly pick up on this pattern when we look at a network of tributaries on a map; a perfectly self-similar, fractal river network wouldn’t look quite right. Basins and streams become elongated at larger scales, so that river networks have an inherent directionality that stretches toward the sea. One result of that elongation is that neighboring river networks must lie closer together than they would with a 0.5 power law…
…
… Rivers do shift their layouts all the time. In the 1990s, in parallel with the work on optimal channel networks, geomorphologists developed powerful landscape evolution models to capture this constant adjustment and show the mechanism by which Hack’s law etches itself on the landscape. These computer simulations start with water flowing downhill, eroding rock as it goes. Tiny, random irregularities in the topography cause some channels to capture more runoff than others. Those channels in turn erode faster and deepen, which causes them to attract still more water. One streambed might grow toward its neighbor, and thereby intercept some of its runoff. The victorious stream grows longer and carries more water, while the losing stream shrinks or disappears. These sorts of local adjustments like these route water along ever more efficient paths. As the entire drainage network gradually reorganizes over thousands of years or more, it attains and then continues to tweak a configuration that transports water downhill with minimal energy dissipation.
Gravity and friction are the driving forces of this process. Gravity supplies potential energy to flowing water. Friction, the cause of erosion, dissipates that energy. A channel configuration that wastes energy by forcing water along inefficient routes tends to erode rapidly and change. A configuration that routes water more effectively is stabler and therefore more persistent. The network becomes optimal through this dynamic evolution, eventually arriving at a form that adheres to Hack’s law.
That explanation of river network geometry hangs together for me, though geomorphologists still have many questions. Some study rivers that deviate from Hack’s law. Others organize transport networks that follow Hack’s law into one class of optimal transport networks, among a whole family of them. Trees, which branch in three dimensions instead of two, would be in a different class from rivers and follow different optimal scaling laws, for instance.
Now, geomorphologists have a new finding to explain. In April 2026, Tian Dong of the University of Texas, Rio Grande Valley and co-authors made the cover of Science for discovering that Hack’s law holds not only for rivers’ tributary networks, but also for their deltas, the fanlike structures that form where a river meets the sea.
Rivers essentially hit a brick wall when they reach the (nonflowing) ocean. The sudden deceleration of the water causes it to drop the sediments it carries. These pile up to form new land. In the process, the river’s water splits into a different kind of network of channels, which shift locations constantly as sediments build up and wash away.
Scientists told me that they’ve long wondered about the organization of channels in river deltas, but they are hard to study. Unlike the upstream river network, where slope and elevation differences make it easy to calculate the area of land that drains into any given tributary, deltas are flat and especially dynamic. But through a sophisticated analysis of satellite data that allowed them to distinguish land from water, Dong and his collaborators determined that the length of a channel in a river delta scales with the size of its nourishment area — the area that it supplies with sediments — raised to the power of 0.6. Rivers’ tributary networks and distributary networks are opposites — sediments are transported away from one end and deposited at the other — yet they abide by the same math. Geomorphologists are now considering why Hack’s law should apply in this inverse context.
Reflecting on my own question, I think it’s the coexistence of simplicity and determinism with chaos and randomness that makes the optimal structure of rivers so captivating. Natural efficiency is, perhaps, innately appealing to us…
The order in seeming chaos: “Why Are Rivers So Mathematical?” from @nattyover.bsky.social in @quantamagazine.org.
* Haruki Murakami, Kafka on the Shore
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As we go with the flow, we might send carefully-calculated birthday greetings to Moritz Cantor; he was born on this date in 1829. A historian of mathematics, he is best remembered for the four volume work Vorlesungen über Geschichte der Mathematik (“Lectures on the History of Mathematics”) which traces the history of mathematics up to 1799, the year of Gauss‘s doctoral thesis. Modern historians credit Moritz with introducing a new discipline to a field, the history of mathematics, that had hitherto lacked the sound, conscientious, and critical methods of other fields of history.
“Things that are so far removed from our daily experience… are inherently hard to understand”*…
That’s certainly true of numbers. And as the numbers grow, the cognitive challenges grow with them. (Indeed, by way of example: 1 million seconds, is roughly 11.5 days; 1 billion seconds is almost 32 years.)
We’ve looked before at the mysterious extremes of math: zero and infinity [and here]. But as Dan Falk reminds us, the numbers in between can seem pretty strange as well– especially the extremely large ones. In a review of Richard Elwes‘ Huge Numbers: A Story of Counting Ambitiously, From 4½ to Fish 7, Falk spotlights some of the largest numbers humans have ever contemplated…
… Aficionados of huge numbers are called “googologists,” a reference to the number 10100, known as a googol. Such numbers have a peculiar sort of existence. For the vast majority of us, they’re of limited everyday value. Calculations at the supermarket checkout, or at tax time in April, typically involve far more modest figures. Perhaps we’ve read that the U.S. national debt is in excess of $38 trillion — a mind-numbing figure, to be sure, but it’s not as though any one individual needs to count it up in stacks of $20 bills.
And yet, much larger numbers await those who seek them out. Consider the kinds of numbers that crop up in problems involving combinations and permutations. For example, in how many distinct ways can one shuffle a deck of cards? Elwes takes us through the calculation, and we end up with a figure of about 8×1067. Compared to that number, the odds of getting a royal flush when dealt a five-card poker hand seem pretty decent, sitting at a mere 1 in 649,740 (still rare enough that many poker players have never held such a hand). Or consider that famous 1980s cultural touchstone, the Rubik’s cube. In how many ways can one scramble the cube? It turns out that the figure is about 43 quintillion, or 4.3×1019 — but in spite of that ridiculously large figure, people do routinely solve the puzzle, and champions can do it in mere seconds. In fact, as Elwes explains, no Rubik’s cube arrangement is more than 20 moves away from any other arrangement.
Or consider the age of the universe, estimated to be about 13.8 billion years. This may seem like a lengthy span of time, but our cosmic future is where the really big numbers come up. Elwes examines the so-called heat death of the universe, in which all matter has broken down into subatomic particles. We may reach this point in [10 raised to the 10th power, raised again to the 120th power] years — this dizzying figure is 10 raised to the power of 10120 — at which point, Elwes says, the universe will have ballooned up to a diameter of 10 to the power of 10 to the power of 10120 light years. (Yes, that’s [10 raised to the 10th power, again to the 10th power, then to the 120th power] light years.) Elwes adds a footnote: “At this point, the choice of units hardly matters; the distance is so immense that whether we choose to measure it in Planck lengths or giga-light years makes little difference.” Let that sink in!
As mind numbing as such figures are, the highest numbers contemplated by humans come not from physics but from pure mathematics and computer science. Like “Graham’s number” — an immense figure put forward as the upper-bound for solutions to a problem in a branch of mathematics known as Ramsey theory. Some readers may find the ensuing discussion of multi-dimensional hypercubes a bit challenging, but one can enjoy the payoff regardless: We end up with a number that can’t even be expressed in conventional notation, and which earned a mention in the 1980 edition of the “Guinness Book of World Records” as “the highest number ever used in a mathematical proof.”
Reading this book is a little bit like sitting in the back row of an auction house where a rare Picasso (let’s say) is up for grabs: How high is this thing going to go? And indeed, Elwes keeps going. We eventually meet the so-called busy beaver numbers, a set of numbers that crop up in theoretical computer science, when one tries to deduce whether a particular computer program will eventually stop, or keep going forever — a conundrum known as the “halting problem.” As Elwes explains, it’s not at all straightforward to distinguish the two types of programs (and if it was, it would help mathematicians tackle some of the most vexing problems in their field).
The fifth busy beaver number, known as BB(5) — associated with a computer program that can access five internal states — works out to 47,176,870. And that’s as far as we’ve gotten, Elwes explains. No one has worked out the value of BB(6), but he assures us that it’s beyond the range of any physical computer; and BB(16) leaves even Graham’s number in the dust.
But wait, there’s more! “Rayo’s number,” concocted by Agustín Rayo — a dean and professor at MIT — using set theory, is bigger still (here’s a fun video about it); and “Fish 7,” mentioned in the book’s subtitle, named for a Japanese googologist who goes by the pseudonym “Fish,” builds on Rayo’s number, and … well, the details are not easily digested, but the mind-melting nature of these numbers comes across as a feature, not a bug, of Elwes’s story… the narrative is enlivened by explorations of the peculiarities of math history…
… Archimedes tried to estimate how many grains of sand would be needed to fill up the known universe, back in the third century B.C. Did he simply have too much time on his hands? Not at all, insists Elwes: The Greek thinker was articulating an important idea — that no matter how unfathomably large a quantity may be, we can describe it with precision, thanks to mathematics. “Archimedes,” he writes, “was penning a manifesto for the expressive power of large numbers.”…
… [Elwes focuses] on numbers that are ridiculously large and yet finite. In the end, perhaps this is the most mind-boggling fact of all: that these enormous numbers, from Graham’s number to Fish 7 and beyond, fall as far short of infinity as does the humble number 1…
The mysteries of the massive: “The Mind-Boggling Science of Enormous Numbers,” @danfalk.bsky.social on @richardelwes.bsky.social in @undark.org.
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As we enumerate enormity, we might spare a thought for a seminal mathematician, Alan Turing; he died on this date in 1954. He was a foundational computer science pioneer (inventor of the Turing Machine (an influential model for the general-purpose computer), creator of the “Turing Test” (only too relevant in these AI-infected times), inspiration for “The Turing Award” (the “Nobel Prize of computing“), and cryptographer (leading member of the team that cracked the Enigma code during WWII).
“Pure mathematics is, in its way, the poetry of logical ideas”*…
Alexander Grothendieck is revered in the world of math; outside of it, he’s known for his unusual life, if he’s known at all. Konstantin Kakaes outlines his actual mathematical contributions…
What Albert Einstein was to 20th-century physics, Alexander Grothendieck was to 20th-century mathematics. He is much less well known because math gets technical even more quickly than physics does. But as with Einstein, Grothendieck’s impact came not just from his own results, revolutionary though they were. His work also reoriented his entire discipline in radical new directions.
Grothendieck was intense and ascetic from his early days. Starting in the early 1950s, when he was in his 20s, he produced thousands of pages of formal and informal notes that changed the course of mathematics. Then in 1970, he quit. He left his post at a prestigious research institute just outside of Paris to teach at the provincial university in Montpellier where he studied as an undergraduate. He mostly stopped talking to other mathematicians. In the early 1990s, he moved to a small village in the Pyrenees, where he lived as a hermit.
Mathematicians are still grappling with the innovations he made half a century ago. His work pushed mathematics to a new level of abstraction by focusing on the relationships between objects rather than the objects themselves. “If there is one thing in mathematics which fascinates me more than any other (and undoubtedly always has), it is neither ‘number’ nor ‘size,’ but invariably shape,” he wrote in his memoirs. “And among the thousand and one faces under which shape chooses to reveal itself to us, that which has fascinated me more than any other and continues to do so is the structure hidden in mathematical things.”
His revolutionary mathematics centered around that search for hidden structure…
Read on: “How Alexander Grothendieck Revolutionized 20th-Century Mathematics,” from @kkakaes.bsky.social in @quantamagazine.bsky.social.
For more, see the section on Grothendieck in Benjamin Labatut‘s remarkable When We Cease To Understand the World.
* Albert Einstein
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As we study shape, we might send speculative birthday greetings to a man who, while not technically a mathematician, nonetheless created a famous equation: Frank Drake; he was born this date in 1930. An astronomer and astrophysicist, he formulated the Drake Equation in 1961 to estimate the number of technological civilizations that might exist in the Milky Way galaxy, N = R* × fp × ne× fl × fi × fc × L. Using plausible guesses for the parameters, Drake concluded perhaps 10 planets in our galaxy may have life originating detectable signals. In 1960, Drake led the first search, the two-month Project Ozma to listen for patterns in radio waves with a complex, ordered pattern that might be assumed to represent messages from some extraterrestrial intelligence.
Carl Sagan and Drake designed the plaques on Pioneer 10 and Pioneer 11 for the purpose of greeting and informing any extraterrestrial life that might find the vessels after they left the solar system.
“Something that doesn’t actually exist can still be useful”*…
Gregory Barber on ultrafinitism, a philosophy that rejects the infinite. Ultrafinitism has long been dismissed as mathematical heresy, but it is also producing new insights in math and beyond…
Doron Zeilberger is a mathematician who believes that all things come to an end. That just as we are limited beings, so too does nature have boundaries — and therefore so do numbers. Look out the window, and where others see reality as a continuous expanse, flowing inexorably forward from moment to moment, Zeilberger sees a universe that ticks. It is a discrete machine. In the smooth motion of the world around him, he catches the subtle blur of a flip-book.
To Zeilberger, believing in infinity is like believing in God. It’s an alluring idea that flatters our intuitions and helps us make sense of all sorts of phenomena. But the problem is that we cannot truly observe infinity, and so we cannot truly say what it is. Equations define lines that carry on off the chalkboard, but to where? Proofs are littered with suggestive ellipses. These equations and proofs are, according to Zeilberger — a longtime professor at Rutgers University and a famed figure in combinatorics — both “very ugly” and false. It is “completely nonsense,” he said, huffing out each syllable in a husky voice that seemed worn out from making his point.
As a matter of practicality, infinity can be scrubbed out, he contends. “You don’t really need it.” Mathematicians can construct a form of calculus without infinity, for instance, cutting infinitesimal limits out of the picture entirely. Curves might look smooth, but they hide a fine-grit roughness; computers handle math just fine with a finite allowance of digits. (Zeilberger lists his own computer, which he named “Shalosh B. Ekhad,” as a collaborator on his papers.) With infinity eliminated, the only thing lost is mathematics that was “not worth doing at all,” Zeilberger said.
Most mathematicians would say just the opposite — that it’s Zeilberger who spews complete nonsense. Not just because infinity is so useful and so natural to our descriptions of the universe, but because treating sets of numbers (like the integers) as actual, infinite objects is at the very core of mathematics, embedded in its most fundamental rules and assumptions.
At the very least, even if mathematicians don’t want to think about infinity as an actual entity, they acknowledge that sequences, shapes, and other mathematical objects have the potential to grow indefinitely. Two parallel lines can in theory go on forever; another number can always be added to the end of the number line.
Zeilberger disagrees. To him, what matters is not whether something is possible in principle, but whether it is actually feasible. What this means, in practice, is that not only is infinity suspect, but extremely large numbers are as well. Consider “Skewes’ number,” eee79. This is an exceptionally large number, and no one has ever been able to write it out in decimal form. So what can we really say about it? Is it an integer? Is it prime? Can we find such a number anywhere in nature? Could we ever write it down? Perhaps, then, it is not a number at all.
This raises obvious questions, such as where, exactly, we will find the end point. Zeilberger can’t say. Nobody can. Which is the first reason that many dismiss his philosophy, known as ultrafinitism. “When you first pitch the idea of ultrafinitism to somebody, it sounds like quackery — like ‘I think there’s a largest number’ or something,” said Justin Clarke-Doane, a philosopher at Columbia University.
“A lot of mathematicians just find the whole proposal preposterous,” said Joel David Hamkins, a set theorist at the University of Notre Dame. Ultrafinitism is not polite talk at a mathematical society dinner. Few (one might say an ultrafinite number) work on it. Fewer still are card-carrying members, like Zeilberger, willing to shout their views out into the void. That’s not just because ultrafinitism is contrarian, but because it advocates for a mathematics that is fundamentally smaller, one where certain important questions can no longer be asked.
And yet it gives Hamkins and others a good deal to think about. From one angle, ultrafinitism can be seen as a more realistic mathematics. It is math that better reflects the limits of what people can create and verify; it may even better reflect the physical universe. While we might be inclined to think of space and time as eternally expansive and divisible, the ultrafinitist would argue that these are assumptions that science has increasingly brought into question — much as, Zeilberger might say, science brought doubt to God’s doorstep.
“The world that we’re describing needs to be honest through and through,” said Clarke-Doane, who in April 2025 convened a rare gathering of experts to explore ultrafinitist ideas. “If there might only be finitely many things, then we’d better also be using a math that doesn’t just assume that there are infinitely many things at the get-go.” To him, “it sure seems like that should be part of the menu in the philosophy of math.”
For mathematicians to take it seriously, though, ultrafinitists first need to agree on what they’re talking about — to turn arguments that sound like “bluster,” as Hamkins puts it, into an official theory. Mathematics is steeped in formal systems and common frameworks. Ultrafinitism, meanwhile, lacks such structure.
It is one thing to tackle problems piecemeal. It is quite another to rewrite the logical foundations of mathematics itself. “I don’t think the reason ultrafinitism has been dismissed is that people have good arguments against it,” Clarke-Doane said. “The feeling is that, oh, well, it’s hopeless.”
That’s a problem that some ultrafinitists are still trying to address.
Zeilberger, meanwhile, is prepared to abandon mathematical ideals in favor of a mathematics that’s inherently messy — just like the world is. He is less a man of foundational theories than a man of opinions, of which he lists 195 on his website. “I cannot be a tenured professor without doing this crackpot stuff,” he said. But one day, he added, mathematicians will look back and see that this crackpot, like those of yore who questioned gods and superstitions, was right. “Luckily, heretics are no longer burned at the stake.”…
Read on for the history of ultrafinitism, the critical dialogue surrounding it, and its implications: “What Can We Gain by Losing Infinity?” from @gregbarber.bsky.social in @quantamagazine.bsky.social.
* Ian Stewart (whose point was somewhat different from Zeilberger’s :-), Infinity: A Very Short Introduction
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As we engage the endless, we might spare a thought for a man whose work touched on the infinitesimal, Isaac Barrow; he died on this date in 1677. A theologian and mathematician, he played a key role in the development of infinitesimal calculus (in particular, for a proof of the fundamental theorem of calculus). Barrow was the inaugural holder of the prestigious Lucasian Professorship of Mathematics at the University of Cambridge, a post later held by his student, Isaac Newton (who, of course, shares primary credit for the development of calculus with Gottfried Wilhelm Leibniz).
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