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23 Dec, 2023

- The Year in Math

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2023 in Review

The Year in Math

By Konstantin Kakaes

December 22, 2023

Landmark results in Ramsey theory and a remarkably simple aperiodic tile capped a year of mathematical delight and discovery.

Video: In 2023, mathematicians improved bounds on Ramsey numbers, a central measure of order in graphs; found a new aperiodic monotile; and discovered a new upper bound to the size of sets without 3-term arithmetic progressions.

Christopher Webb Young, Kristina Armitage and Merrill Sherman/Quanta Magazine

Introduction

Mathematical truths are often born of the conflict between order and disorder. Mathematicians discover patterns, and, to better understand the mysterious forces at play, they look for countervailing impulses that disrupt those patterns.

That tension came up repeatedly in our coverage this past year. We covered breakthroughs in graph theory, combinatorics, number theory and geometry — areas where patterns arise in unexpected ways, sometimes because of connections between seemingly distinct mathematical structures, and sometimes because of hidden intrinsic mechanisms uncovered by mathematicians in new proofs.

In a riveting interview with our senior writer Jordana Cepelewicz, Andrew Granville discussed how calculation and experimentation can, in sometimes forgotten ways, help mathematicians search for hidden patterns. He also spoke about changes in what it takes to convince other mathematicians that a result is true, and why he believes that examining the social nature of mathematics is essential to understanding what a proof is.

This was one of several conversations we published this past year about the nature of mathematical truth. Eugenia Cheng spoke with Joy of Why podcast host Steven Strogatz about category theory, a sort of “mathematics of mathematics” that can scare off other mathematicians with its level of abstraction. And Justin Moore spoke with Strogatz about the limits of the axioms — basic, obvious truths — of set theory and why there will always be important, unanswerable mathematical questions.

Though the bulk of our coverage fell squarely in the abstract realm, Minhyong Kim spoke with Kevin Hartnett about Mathematics for Humanity, an organization he founded to support mathematicians who want to use math to solve social challenges. And Mike Orcutt reported on how mathematics is used to ascertain the fairness of legislative district maps and to draw more equitable ones.

DVDP for Quanta Magazine

Introduction

A Big Year in Graph Theory

If there is one area of math that was particularly fruitful in 2023, it’s graph theory. One of the biggest mathematical discoveries of the past year was the proof of a new, tighter upper bound to Ramsey numbers. These numbers measure the size that graphs must reach before inevitably containing objects called cliques. The discovery, announced in March, was the first advance of its type since 1935. It pertained to so-called symmetric Ramsey numbers. This was followed in June by a new result on the more general asymmetric case.

Both of these papers concerned what happens as graphs grow infinitely large. But Quanta also pondered the middle distance, looking at what mathematicians can prove about graphs that are too large to analyze using brute force, but smaller than the infinite, asymptotic limit.

We chronicled new results on how networks of connected oscillators come into synchrony and how graph theory connects to quantum field theory. We reported a new discovery about the possibilities of subdividing mathematical objects called vector spaces in a particular way into subsets called designs. And Patrick Honner, our Quantized Academy columnist, wrote about the way that local properties of graphs govern their global structure.

Quanta also published articles on two long-standing coloring problems. One explored the proof of the famous four-color theorem, which shows how four colors are enough to color any map on the plane so that no two adjacent regions have the same color. The other covered a new result on a less well-known but equally intriguing question, which asks how much of a plane can be colored in a way that ensures that no two points that are exactly one unit apart have the same color.

Samuel Velasco/Quanta Magazine

Introduction

Making Combinatorics Conjectures Count

Graph theory can be thought of as a branch of combinatorics — the mathematical study of counting. Counting what can happen with collections of nodes and edges is, in some sense, a special case of counting combinations more generally.

The year ended with a landmark proof by four prominent mathematicians of a longstanding conjecture that relates combinatorics to the algebraic structure of sets.

Back in February, two computer scientists, Zander Kelley and Raghu Meka, stunned mathematicians with news of an out-of-left-field breakthrough on an old combinatorics question: How many integers can you throw into a bucket while making sure that no three of them form an evenly spaced progression (like 3, 8 and 13 or 101, 201 and 301)? Kelley and Meka smashed a long-standing upper bound on the number of integers smaller than some cap N that could be put in the bucket without creating such a pattern.

The previous month, Kevin Hartnett reported on a paper from November 2022 by another outsider — a researcher at Google named Justin Gilmer who had left mathematics years before, but had never stopped thinking about a combinatorial problem called the union-closed conjecture. This conjecture concerns families of sets like {1}, {1, 2}, {2, 3, 4}, {1, 2, 3, 4}. This family is “union-closed” because if you combine any two sets in the family, the combination is also in the family. The conjecture, which Gilmer proved, says that if a family is union-closed, it must have at least one number that appears in at least half the sets. Gilmer used an argument drawn from information theory that relied on randomly choosing two sets from a union-closed family that met certain characteristics. His argument is yet another example of how randomness can be used as a tool to infer the existence of structure.

By contrast, an April article by Kevin Hartnett described an instance where intricate but simple structures surprisingly turn out to be possible. Bernardo Subercaseaux and Marijn Heule showed that it’s possible to fill an infinite grid with numbers in such a way that the distance between two occurrences of the same number must be greater than the number itself — using only the numbers between 1 and 15.

And longtime Quanta contributor Erica Klarreich wrote about the surprising prevalence of so-called intransitive dice. These are, for example, sets of three dice A, B and C in which A is likely to beat (roll a higher number than) B, B is likely to beat C and C is likely to beat A. A new paper showed that if you know only that die A beats die B and B beats C, that gives no information about whether A or C is likely to prevail in a head-to-head matchup.

Courtesy of Samuel Jinglian Li

Introduction

New Connections in Number Theory

Perhaps more than in any other area of mathematics, number theorists can prove simple-sounding theorems using incredibly complicated technical constructions. This year, Quanta took readers on a tour of some of those constructions. We published an in-depth visual explainer of modular forms, which have been described as the “fifth fundamental operation” of math, along with addition, subtraction, multiplication and division. And we took readers on a historical tour of quadratic reciprocity, one of number theory’s most powerful tools. The modular-forms explainer was inspired by an article about so-called noncongruence modular forms — a less well-studied type of function that nevertheless has major implications for physics.

Max Levy, who wrote the quadratic-reciprocity explainer, got interested in the subject while reporting about a surprising summer discovery about patterns that circles can make. Levy recounted how two students working on a summer research project helped disprove a long-standing conjecture about how circles can be harmoniously nested, called the local-to-global conjecture. It was one of many developments this year that showcased the increasing utility of computational tools in mathematics. The students and their co-authors first found evidence that the conjecture was false by poring over computer-generated plots they’d created in an effort to see it at work.

Modular forms are closely related to elliptic curves — smooth functions of two variables where one variable is squared and the other cubed. (The functions also satisfy some particular mathematical constraints.) The relationship between the two was central to Andrew Wiles’ 1994 proof of Fermat’s Last Theorem. Hartnett wrote about advances in researchers’ understanding of that relationship for elliptic curves that are defined with variables drawn from imaginary quadratic fields — numbers of the form a + b $latex \sqrt{-5}$ where a and b are both rational numbers, or fractions.

He also wrote about a long-awaited magnum opus — a 451-page manuscript by the Fields medalist Akshay Venkatesh, together with Yiannis Sakellaridis and David Ben-Zvi, which elaborates further connections between objects related to modular forms and L-functions, an important type of infinite sum with a deep relationship to prime numbers.

Number theorists pay particular attention to prime numbers and the subtle and beautiful ways they’re distributed among the other integers. Intriguingly, if you consider them going out to infinity, it has long been known that the primes leave equal numbers of remainders when divided by some number — for instance, if you divide all the prime numbers by 5, you’ll get equal numbers of the remainders 1, 2, 3 and 4. But mathematicians keep striving to prove results about how quickly primes even out. In October, we reported on a new generation of mathematicians proving theorems about the ways in which primes are distributed.

We also introduced — and reintroduced — a fun mathematical game called Hyperjumps that explores the tension between structure and randomness by challenging players to create simple sequences of numbers using basic arithmetic.

Samuel Velasco/Quanta Magazine

Introduction

Aperiodic Monotile Found After Long Search

It was also an exciting year in geometry. The most attention-getting result of the year was the discovery of a new kind of tile that covers the plane in a pattern that never repeats. A two-tile combination that does this has been known since the 1970s, but the single tile, discovered by a hobbyist named David Smith and announced in March, was a sensation. Fans used the simple design as a cookie cutter and sewed it into quilts. We followed our news coverage with a column explaining some of the underlying math and another giving a brief history of tiling.

Speaking of needles, it was also a year of progress on the Kakeya conjecture, which asks how small a volume of space an idealized needle can occupy while spinning in all directions. A new proof of a special case of the conjecture (called the “sticky” Kakeya conjecture) gives strong evidence that the more general conjecture is true.

The conjecture turns out to have implications not only for geometry, but also for harmonic analysis and the study of partial differential equations. A follow-up explainer examines those implications. And a Quantized Academy columntakes readers through the conjecture’s underlying logic.

In other geometry news, a long-standing idea about maps between spheres of different dimensionality, called the telescope conjecture, was shown to be false. Particular types of contact structures (patterns of planes that satisfy certain mathematical properties) that had long been thought to be impossible turned out to exist.

We interviewed Emmy Murphy, a geometer who studies such contact structures. Murphy describes contact geometry (and its sibling, symplectic geometry) as existing in the middle of a spectrum of rigidity and flexibility. In rigid geometry, much depends, she said, on precise measurements, while flexible geometry tends to resemble algebra. But in between, she said, is where “visual thinking is more useful.”

In January, the mathematician Assaf Naor and the computer scientist Oded Regev proved the existence of so-called spherical cubes. These are objects whose surface area grows slowly — as does the surface area of spheres in higher dimensions — but which can completely fill space the way cubes can.

One of the most prominent geometers of the 20th century, Eugenio Calabi, died at age 100 on September 25. Jerry Kazdan, one of his longtime colleagues, said that Calabi would “ask interesting questions that no one else was thinking about.” Our obituary of Calabi explores those questions, focusing particularly on his best-known discovery, Calabi-Yau manifolds, which later became central to string theory in physics.

Harol Bustos for Quanta Magazine

Introduction

It’s an Unstable World After All

Speaking of physics, we also published several new results about the mathematics of black holes, a favorite subject of contributing writer Steve Nadis. He wrote about a new paper that found an infinite number of different black hole shapes in higher dimensions, and another paper that clarifies the mathematics of the boundaries of black holes.

In April, we described how mathematicians are teaming up with physicists to understand new kinds of symmetries in quantum field theories.

Kathryn Mann and Thomas Barthelmé, along with Steven Frankel, published a series of papers characterizing dynamical systems called Anosov flows that balance chaos and stability. At any given point, the flows converge in one direction and diverge in another.

And in what might be the most unsettling math article of the year, we related news of a series of three papers by Marcel Guàrdia, Jacques Fejoz and Andrew Clarke showing that planetary orbits in a model solar system will always be unstable. The good news is that their model is quite unlike our solar system, although Clarke thinks similar instabilities may exist here as well.

But if they do, they’re not going to send any of the planets out of their orbits anytime soon, so you can look forward to another year of math coverage from Quanta in 2024.

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21 Dec, 2023

- The Year in Physics

Previous: 2023 in ReviewThe Year in Computer Science

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2023 in Review

The Year in Physics

By Nadia Drake

December 21, 2023

From the smallest scales to the largest, the physical world provided no shortage of surprises this year.

Video: In 2023, physicists found the gravitational wave background that’s made by supermassive black hole collisions, teleported quantum energy in the lab, and puzzled over JWST’s potentially cosmology-breaking discoveries.

Emily Buder/Quanta Magazine; Myriam Wares and Ibrahim Rayintakath for Quanta Magazine

Introduction

By one metric, this year’s biggest physics news happened 80 years ago. Yet while the success of a movie about the making of the atomic bomb was a surprise, the discoveries coming out of actual physics laboratories — including the grandest laboratory of them all, the universe itself — were no less impressive than the surge in interest about J. Robert Oppenheimer.

The James Webb Space Telescope, now in year two of science operations, continues to return stunning images of the cosmos, and the trickle of science results from 2022 has now swelled into a torrent. From its perch a million miles away, JWST studies everything from the universe’s most distant galaxies to the planets and moons right next door. The only constant has been surprise: The telescope’s observations continually challenge well-established theories and force scientists to reimagine how familiar cosmic objects came to be — things like stars and planets and black holes.

Black holes are also at the center of one of 2023’s most notable discoveries: evidence for gravitational waves produced by colliding supermassive black holes. To detect those ripples in space-time, several consortia of astronomers scrutinized the cosmos for 15 years — long enough to detect the tiny temporal fluctuations that occur as gravitational waves wash over the Earth.

Closer to home, scientists are busy both manipulating and understanding the quantum world — a realm that often doesn’t play by normal rules. This year saw some remarkable advances in quantum computing’s most basic hardware, the qubits that in their final form could power enormously complex calculations. And, crucially, researchers also made improvements in quantum error correction, which remains one of the trickiest problems to solve.

But these advances don’t mean we’re done understanding the universe from the largest of its scales to the tiniest. Our next orbit around the sun could be full of even more profound revelations.

Courtesy of Jorryt Matthee. Data from the EIGER / FRESCO surveys

Introduction

The Cosmos, Unveiled

It has often been said that each time we look at the universe in a new light — or through a new lens — we see things we never imagined. NASA’s James Webb Space Telescope has delivered on that promise. At the turn of the year, astronomers announced that the telescope’s golden, honeycombed eye had stolen glances of the universe’s first stars. JWST has also seen the light from galaxies that glowed some 300 million years after the great big clap that created the universe as we know it. In JWST images, those galaxies are “just so stupidly bright,” said Rohan Naidu of the Massachusetts Institute of Technology. Now, astronomers are struggling to explain how those galaxies grew so big so fast, as their size and precociousness defy expectations.

The same is true for the supermassive black holes that anchor galaxies to the cosmic tapestry. Scientists expected to see a few bulky black holes in the early universe, but JWST is spotting them by the bucketful. And they’re showing up earlier, and with more heft, than expected. Astronomers hope such observations will reveal how those gargantuan black holes formed. “I’ve been waiting for these things for so long,” said Marta Volonteri, an astrophysicist at the Paris Institute of Astrophysics.

Closer to home, in our galaxy’s Orion nebula, JWST recently spotted 42 intriguing pairs of objects that orbit one another. These worlds might be stars, or they might be free-floating planets. It’s hard to tell. But either way, these enigmatic worlds don’t fit neatly into existing theories describing how either stars or free-floating planets form. As with all new ways of seeing, JWST is inspiring far more questions than it answers.

Merrill Sherman/Quanta Magazine

Introduction

Stronger Quantum Knots

Earlier this year, quantum researchers announced that they’d taken a step toward developing a more reliable quantum computer. In this system, information is stored topologically; it is woven into almost mythical particles that share memories and remember their pasts. Braiding two of these “non-abelian anyons” together stores information in the twists — thus, you can measure one or the other without losing that information. As my colleague Charlie Wood explained, “By maintaining nearly indestructible records of their journeys through space and time, non-abelian anyons could offer the most promising platform for building error-tolerant quantum computers.”

Then in August, scientists tackling the trickiness of quantum error correction announced that they had developed a powerful new class of codes that could — at least in theory — help with the persnickety problem of flimsy, error-prone quantum bits.

Kristina Armitage/Quanta Magazine

Introduction

Quantum Magic

In a feat reminiscent of a magic trick, scientists reported earlier this year that they had pulled energy out of a vacuum. Or had they? Rather than conjuring something from nothing, physicists managed to teleport energy over microscopic distances. The leap worked because the team exploited the strange properties of the quantum vacuum — a peculiar type of nothing that is actually imbued with a sort of sizzling quantum energy.

Earlier this year, scientists discovered a new type of phase transition, akin to the transformation of a solid into a liquid. Except this was a transition in the structure of information. When quantum bits (or qubits) are entangled, measuring one reveals the states of any others. Entanglement can spread, but measurement destroys the web of entanglement — it’s like snipping the wires in a chain-link fence. What happens when entanglement and measurement duke it out in a grid of entangled qubits? The transition between a state in which entanglement survives and one in which it succumbs to the wire cutters of measurement is what physicists identified and observed in the lab. “It’s where the properties in information — how information is shared between things — undergo a very abrupt change,” said Brian Skinner of Ohio State University.

When it comes to these systems, we throw around the term “quantum” almost as if quantum and not-quantum exist in a binary. That isn’t necessarily true. In the effort to quantify quantumness — or the degree to which a quantum system cannot be simulated on a classical computer — researchers recently unveiled a new metric, bringing the total known metrics to three. First there was entanglement. Then there was “magic.” Now, there’s “fermionic magic.”

Olena Shmahalo for Quanta Magazine

Introduction

Toward Quantum Gravity

It’s an old problem in physics: Quantum mechanics describes the world one way, Einstein’s theory of gravity another, and when the two come together you get nonsense. Some scientists, like Renate Loll, believe that gravity must be quantized; others, like Jonathan Oppenheim, would bet against that idea. While Loll has pioneered a computationally driven approach to quantum gravity that involves deriving the shape of space-time from first principles, Oppenheim is searching for an even deeper fundamental “something” that might connect the two.

And yet quantum gravity keeps showing up in the solutions to seemingly intractable paradoxes.

A group of leading theorists believe they’ve pinpointed the mistake that led to Hawking’s famous black hole information paradox, in which indestructible information inside a black hole is seemingly lost as the black hole evaporates. Hawking’s apparent mistake was that he (and the generations of physicists that followed) didn’t realize that the normally reliable “semiclassical” treatment of gravity can’t handle the complexity of states a black hole can produce, unexpectedly breaking down at the black hole’s outer surface. The group has now developed a more sophisticated theory of gravity that can handle the region just inside the event horizon and doesn’t violate any current experimental data.

Jim Hoover

Introduction

A Hum of Gravitational Waves

When galaxies collide, their supermassive central black holes merge — a smashup so violent that it shakes the very fabric of space-time itself. In June, multiple international collaborations announced that they had found the resulting gravitational waves. To do this, the teams used pulsars, rapidly spinning stellar corpses that serve as perfect cosmic clocks. The gravitational waves alter the apparent rhythm of the pulsars, but it took 15 years of study to identify this signature of violent events that continually rock the cosmos.

Editor’s note: Michael Moyer contributed to this article.

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20 Dec, 2023

- The Year in Computer Science

- New Clues for What Will Happen When the Sun Eats the Earth

Previous: 2023 in ReviewThe Year in Biology

Next: 2023 in ReviewThe Year in Physics

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2023 in Review

The Year in Computer Science

By Bill Andrews

December 20, 2023

Artificial intelligence learned how to generate text and art better than ever before, while computer scientists developed algorithms that solved long-standing problems.

Video: In 2023, computer scientists made progress on a new vector-driven approach to AI, fundamentally improved Shor’s algorithm for factoring large numbers, and examined the surprising and powerful behaviors that can emerge from large language models.

Myriam Wares for Quanta Magazine (cover); Emily Buder/Quanta Magazine and Taylor Hess and Noah Hutton for Quanta Magazine (video)

Introduction

In 2023, artificial intelligence dominated popular culture — showing up in everything from internet memes to Senate hearings. Large language models such as those behind ChatGPT fueled a lot of this excitement, even as researchers still struggled to pry open the “black box” that describes their inner workings. Image generation systems also routinely impressed and unsettled us with their artistic abilities, yet these were explicitly founded on concepts borrowed from physics.

The year brought many other advances in computer science. Researchers made subtle but important progress on one of the oldest problems in the field, a question about the nature of hard problems referred to as “P versus NP.” In August, my colleague Ben Brubaker explored this seminal problem and the attempts of computational complexity theorists to answer the question: Why is it hard (in a precise, quantitative sense) to understand what makes hard problems hard? “It hasn’t been an easy journey — the path is littered with false turns and roadblocks, and it loops back on itself again and again,” Brubaker wrote. “Yet for meta-complexity researchers, that journey into an uncharted landscape is its own reward.”

The year was also full of more discrete but still important pieces of individual progress. Shor’s algorithm, the long-promised killer app of quantum computing, got its first significant upgrade after nearly 30 years. Researchers finally learned how to find the shortest route through a general type of network nearly as fast as theoretically possible. And cryptographers, forging an unexpected connection to AI, showed how machine learning models and machine-generated content must also contend with hidden vulnerabilities and messages.

Some problems, it seems, are still beyond our ability to solve — for now.

Tommy Parker for Quanta Magazine

Introduction

Hard Questions, Hard Answers

For 50 years, computer scientists have tried to solve the biggest open question in their field, known as “P versus NP.” It asks, roughly, how hard certain hard problems are. And for 50 years, their attempts have ended in failure. Many times, just as they began to make progress with a new approach, they hit a barrier proving that the tactic would never work. Eventually, they began to wonder why it’s so hard to prove that some problems are hard. Their efforts to answer such inward-looking questions have blossomed into a subfield, called meta-complexity, which has provided the greatest insights into the question yet.

In an August article and a short documentary video, Quanta explained exactly what we know, how we know it and what we’re just starting to figure out when it comes to meta-complexity. At stake is not just the curiosity of the researchers involved: Resolving P versus NP could solve countless logistical problems, render all cryptography moot, and even speak to the ultimate nature of what’s knowable and what’s forever beyond our grasp.

Paul Chaikin/Quanta Magazine

Introduction

The Powers of Large Language Models

Get enough stuff together, and you might be surprised by what can happen. Water molecules create waves, flocks of birds swoop and soar as one, and unconscious atoms combine into life. Scientists call these “emergent behaviors,” and they’ve recently seen the same thing happen with large language models — AI programs trained on enormous collections of text to produce humanlike writing. After they reach a certain size, these models can suddenly do unexpected things that smaller models can’t, such as solving certain math problems.

Yet the surge of interest in large language models has raised new concerns. These programs invent falsehoods, perpetrate social biases, and fail to handle even some of the most elementary elements of human language. Moreover, these programs remain a black box, their internal logic unknowable, though some researchers have ideas about how to change that.

Samuel Velasco/Quanta Magazine

Introduction

Solving Negativity

Computer scientists have long known of algorithms that can whiz through graphs — networks of nodes connected by edges — where the connections have some cost, like a toll road connecting two cities. But for decades, they couldn’t find any fast algorithm for determining the shortest path when a road could have either a cost or a reward. Late last year, a trio of researchers delivered a workable algorithm that’s nearly as fast as theoretically possible.

Then in March, researchers posted a new algorithm that can determine when two types of mathematical objects known as groups are the same in a precise way; the work may lead to algorithms that can quickly compare groups (and perhaps other objects) more generally, a surprisingly difficult task. Other big algorithm news this year included a new way of computing prime numbers by incorporating random and deterministic approaches, the refutation of a long-standing conjecture about the performance of information-limited algorithms, and an analysis that shows how an unintuitive idea can improve the performance of gradient descent algorithms, which are ubiquitous in machine learning programs and other areas.

Samuel Velasco/Quanta Magazine; source: Shutterstock

Introduction

Appreciating AI Art

Image-generating tools like DALL·E 2 exploded in popularity this year. Simply feed them a written prompt, and they’ll spit back a tableau of art depicting whatever you requested. But the work that made most of these artificial artists possible had been brewing for many years. Based on concepts from physics that describe spreading fluids, these so-called diffusion models effectively learn how to unscramble formless noise into a sharp image — as if turning back the clock on a cup of coffee to see the evenly distributed cream reconstitute into a well-defined dollop.

AI tools have also been successful in improving the fidelity of existing images, though we’re still far from the TV trope of a cop repeatedly shouting “Enhance!” More recently, researchers have turned to physical processes besides diffusion to explore new ways for machines to generate images. A newer approach governed by the Poisson equation, which describes how electric forces vary over distance, has already proved more capable of handling errors and is easier to train than diffusion models, in some cases.

DVDP for Quanta Magazine

Introduction

Improving the Quantum Standard

For decades, Shor’s algorithm has been the paragon of the power of quantum computers. Developed by Peter Shor in 1994, this set of instructions allows a machine that can exploit the quirks of quantum physics to break large numbers into their prime factors much faster than a regular, classical computer — potentially laying waste to much of the internet’s security systems. In August, a computer scientist developed an even faster variation of Shor’s algorithm, the first significant improvement since its invention. “I would have thought that any algorithm that worked with this basic outline would be doomed,” Shor said. “But I was wrong.”

Yet practical quantum computers are still beyond reach. In real life, tiny errors can quickly add up, ruining calculations and taking away any quantum benefits. In fact, late last year, a team of computer scientists showed that for a specific problem, a classical algorithm does roughly as well as a quantum one that includes errors. But there is hope: Work in August showed that certain error-correcting codes, known as low-density parity check codes, are at least 10 times more efficient than the current standard.

Harol Bustos for Quanta Magazine

Introduction

Hiding Secrets in AI

In an unusual finding at the intersection of cryptography and artificial intelligence, a team of computer scientists showed it was possible to insert into machine learning models certain backdoors that were practically invisible, their undetectability backed up by the same logic as the best modern encryption methods. The researchers focused on relatively simple models, so it’s unclear whether the same holds true for the more complicated models behind much of today’s AI tech. But the findings do suggest ways for future systems to guard against such security vulnerabilities, while also signaling a renewed interest in how the two fields can help each other grow.

These kinds of security issues are part of the reason Cynthia Rudin has championed using interpretable models to better understand what’s happening inside machine learning algorithms; researchers like Yael Tauman Kalai, meanwhile, have advanced our notions of security and privacy, even in the face of looming quantum technology. And a result in the related field of steganography showed how to hide a message with perfect security within machine-generated media.

Myriam Wares for Quanta Magazine

Introduction

Vector-Driven AI

As powerful as AI has become, the artificial neural networks that underpin most modern systems share two flaws: They require tremendous resources to train and operate, and it’s too easy for them to become inscrutable black boxes. Many researchers argue that perhaps it’s time for another approach. Instead of using artificial neurons that detect individual traits or characteristics, AI systems could represent concepts with endless variations of hyperdimensional vectors — arrays of thousands of numbers. This system is more versatile and better equipped to handle errors, making its computations far more efficient, and it allows researchers to work directly with the ideas and relationships these models consider, giving them greater insight into the model’s reasoning. Hyperdimensional computing is still in its infancy, but as it gets put to bigger tests, we may see the new approach start to take hold.

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astrophysics

New Clues for What Will Happen When the Sun Eats the Earth

By Jonathan O'Callaghan

December 20, 2023

Recent observations of an aging, alien planetary system are helping to answer the question: What will happen to our planet when the sun dies?

As our sun ages, it will swell into a star so big it might engulf (and destroy) Earth.

Courtesy of MIT

Introduction

Earth’s fate rests on a coin flip.

In 5 billion years, our sun will balloon into a red giant star. Whether Earth survives is an “open question,” said Melinda Soares-Furtado, an astrophysicist at the University of Wisconsin, Madison. Sure, Earth could be swallowed by the sun and destroyed. But in some scenarios, Earth escapes and is pushed further out into the solar system.

Now, a nearby planetary system has offered clues to our planet’s cosmic hereafter. About 57 light-years away, four planets orbit a sunlike star that is 10 billion years old — twice as old as the sun, and already in the advanced stages of its life. Stephen Kane, an astrophysicist specializing in planetary habitability at the University of California, Riverside, recently modeled what might happen to the elderly system’s planets when the star becomes a red giant in a billion years. He found that most of the inner planets will be engulfed, but that the outermost known planet, which has an orbit similar to Venus’, might survive.

The star’s advanced age makes it easier to model its expansion and offers a more accurate forecast of our own planetary system’s future. “It’s a very interesting paper,” said Jonathon Zink, an astrophysicist at the California Institute of Technology. “If we can find [more] systems at various phases of stellar evolution, we can probably piece together what’s going [to happen].”

Crispy Worlds

When a planet is engulfed, death can be swift. In 2022, Ricardo Yarza, a stellar astrophysicist at the University of California, Santa Cruz, simulated what happens when a red giant swallows a planet. He found that if the planet starts out close enough to the star, its orbit rapidly decays. Gas in the star’s atmosphere creates a drag on the planet, and “the planet keeps plunging deeper and deeper into the star,” Yarza said. Within a few hundred years, most planets will be destroyed.

Until recently, these final moments of a doomed planet’s life “had never been observed directly,” said Kishalay De, an astronomer at the Massachusetts Institute of Technology. But in 2020, De’s team saw a star 12,000 light-years away temporarily become a few hundred times brighter. The flash was too dim to have come from a merger with another star. But it was just the right intensity to have been produced by a planet-size meal, De and his colleagues reported in May.

The team surmised that a planet a few times more massive than Jupiter had been caught up as the 10-billion-year-old star began expanding into a red giant. “This is the future of our solar system,” De said.

Our Evolving Star

When a main-sequence star like our sun — also called a G-type star or yellow dwarf — reaches the end of its life, it runs out of the hydrogen needed to power nuclear fusion in its core. As the star turns to other fuel sources and loses mass, its core gets hotter, and its atmosphere puffs up over millions of years. Eventually, our sun will grow more than 200 times as wide as its present size.

That swelling sun will consume Mercury and probably Venus, before growing so large it approaches Earth’s orbit — a distance known as one astronomical unit, or AU. But it could expand even further. “In some models,” said Antonino Lanza, an astronomer at the Astrophysical Observatory of Catania in Italy, “it can engulf Mars.” The main uncertainty, he said, lies in how much mass the sun will lose as it ages; the more it sheds, the smaller its final radius will be. “That is poorly known,” he said.

For now, our best estimates suggest that the sun will grow to somewhere between 0.85 and 1.5 AU. But as the star loses mass, the weaker pull of gravity will increase Earth’s orbit, meaning our planet could escape engulfment.

To see Earth’s future, astronomers turn to a crystal ball filled with alien planetary systems. Their goal is to find sunlike stars that will soon balloon (or have just ballooned) into red giants.

That’s why Rho Coronae Borealis, a nearby yellow dwarf star that’s thought to be reaching the end of its sunny life, caught Kane’s attention. Three of its four known planets orbit close to the star, well within Venus’ path around our sun. The outermost planet, with a year lasting 282 days, is similar in orbit to Venus.

Kane’s analysis, published last month, shows that the growing star will engulf the three inner planets. The innermost of those worlds, thought to be rocky and nearly four times the mass of Earth, will evaporate within a few hundred years. “The plasma superheats the planet and causes it to essentially break down,” Kane said. “Even the rocks on the surface will melt away.” The next world out, a Jupiter-mass gas giant, is so large that it will spiral inward and be ripped apart by the star’s gravity, rather than evaporating. The third planet, a smaller Neptune-mass world, will likely also be engulfed and evaporated.

But the outermost planet — also about the mass of Neptune — may survive. As the star expands, it will temporarily engulf the planet for several thousand years. During this time, extreme temperatures will roast the planet’s surface, but the planet itself should survive because the star’s atmosphere isn’t very dense at this distance. The star will then contract and expand once more, again engulfing the planet for several millennia. If the planet can survive being toyed with like a tomcat’s mouse, it could then emerge from the atmosphere as the star shrinks for a final time. “So it has an opportunity right at the end to escape,” Kane said.

Kane, for one, is sanguine about the planet’s chances and what they might mean for our own world. “I suspect that Earth will move outward, and it will survive,” he said.

The Great Escape

If a planet can escape engulfment, its chances for a longer life are promising. When a star like our sun expands into a red giant and sheds its outer layers, eventually the only thing left is a dense, white-hot stellar corpse known as a white dwarf. These objects contain as much as half the mass of the original star, packed into an area the size of Earth. They should continue to burn for trillions of years.

In the past two decades, scientists have found a handful of exoplanets orbiting white dwarfs, said Mary Anne Limbach, an exoplanet scientist at the University of Michigan. These planets survived their star’s red giant phase, although it’s not clear exactly how. Some of the worlds — which tend to be larger gas giants — were probably too far from their star to be swallowed, while others may have been pushed outward as the star huffed and puffed. (Astronomers have also seen evidence that some planets were not so lucky in the form of polluted white dwarfs, which are rich in elements associated with planets, such as magnesium and iron.) Ongoing observations by the James Webb Space Telescope (JWST) are expected to turn up dozens more exoplanets orbiting white dwarfs.

As unusual as they might seem, these planetary systems could still be habitable, said Limbach, who leads some of the JWST white dwarf observations. “There is a place around a white dwarf where you can get liquid water” on a planet’s surface, she said. But “it’s a very challenging environment.”

More observations of evolved solar systems, and more models like Kane’s, could provide greater insight into the fate of our own. For now, the death of our planet is a roll of the dice away from certainty. Humans may be long gone from Earth’s surface, but anyone glancing in our direction 5 billion years from now might see our planet ride out our sun’s dying breaths — or, perhaps, disappear in a brief flash of light.

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19 Dec, 2023

- The Year in Biology

Next: 2023 in ReviewThe Year in Computer Science

SERIES

2023 in Review

The Year in Biology

By Hannah Waters

December 19, 2023

In a year packed with fascinating discoveries, biologists pushed the limits of synthetic life, probed how organisms keep time, and refined theories about consciousness and emotional health.

Video: During 2023, Quanta turned a spotlight on important research progress into the nature of consciousness, the origins of our microbiomes and the timekeeping mechanisms that govern our lives and development, among many other discoveries.

Ibrahim Rayintakath for Quanta Magazine (cover); Emily Buder/Quanta Magazine and Taylor Hess and Noah Hutton for Quanta Magazine (video)

Introduction

Revolutions in the biological sciences can take many forms. Sometimes they erupt from the use of a novel tool or the invention of a radical theory that suddenly opens so many new avenues for research, it can feel dizzying. Sometimes they take shape slowly, through the slow accumulation of studies, each one representing years of painstaking work, that collectively chip away at the prevailing wisdom and reveal a stronger, better intellectual framework. Both kinds of revolution unleash avalanches of new ideas and insights that improve our understanding of how life works.

This past year has had no shortage of these. For example, researchers successfully grew “embryo models” — lab-grown artificial embryos that mature like real ones — that reached a more advanced developmental stage than ever before. That accomplishment could eventually yield valuable new insights into how human fetuses grow, although debate about the ethical status of those models seems likely, too. Meanwhile, in the world of neuroscience, researchers studying depression have continued to move away from the theory that has generally guided much of the research and pharmaceutical treatment of that disease for decades.

But those kinds of biological revolution involve human ingenuity, with researchers in the life sciences coming to new realizations. Revolutions also occur in the biology itself — when evolution has enabled organisms to do something unprecedented. Biologists have recently discovered many more instances of this kind of breakthrough.

Keeping track of time, for instance, is a function that’s essential to all living things, from microorganisms biding their time till the next cell division to embryos growing limbs and organs, to more complex critters tracking the passage of day and night. Teams of researchers plugging away in laboratories around the world have recently discovered that some key features of timekeeping are tied to cellular metabolism — which means that the organelle called the mitochondrion is both a generator and a clock. Other aspects of timekeeping are metered by the progress of a molecular ballet in which specialized proteins pirouette together before separating again.

Researchers also hope to soon make important discoveries now that they can culture some of the primitive, long-lost cells called Asgard archaea. A billion years ago, Asgard archaea (or cells much like them) took the outrageous step of forming permanent partnerships with the ancestors of mitochondria, thereby giving birth to the first complex cells. The secrets of how and why that biological breakthrough happened may be lurking in those exotic cell cultures. Meanwhile, other researchers are scrutinizing the “grit crust” microbes that live in the infamously arid Atacama Desert of Chile for clues to how the first land-dwelling cells survived.

Enough marvelous biological innovations were discovered in 2023 to form a veritable parade: plankton that supercharged their photosynthetic abilities by repurposing one of their membranes, and underground microbes that learned to make oxygen in total darkness. An immunological trick that protects babies in the womb, and a neurological trick that lets the brain map out social relationships like physical landscapes. A simple mutation that transformed ants into complex social parasites virtually overnight, and a strategic demolition of DNA that worms use to safeguard their genomes.

Quanta chronicled all those and more this year, and as new breakthroughs in fundamental biology come to light in the years ahead, we will be there for them too.

University of Cambridge

Introduction

Pushing the Bounds of Synthetic Life

In the same way that physical scientists build simple model systems as steppingstones to understanding more complex phenomena, some biologists prefer to learn how life works by creating simpler versions. This year they made progress on two fronts: on large scales, in creating “embryo models,” and on small scales, in studying the most minimal cell possible.

Embryo models, or synthetic embryos, are laboratory products of stem cells that can be induced to grow faithfully through the early stages of development, although they self-terminate before reenacting the full embryonic development process. They were devised as potential tools for the ethical experimental study of human development. This year, research groups in Israel and the United Kingdom showed that they could nurture embryo models all the way up through (and possibly beyond) the stage at which research on live human embryos is legally allowed. Researchers in China even briefly initiated pregnancies in monkeys with embryo models. Those successes are considered major breakthroughs for a technique that could help scientists answer important questions about prenatal development, and they might eventually pay off in preventing miscarriages and birth defects. At the same time, the experiments reawakened ethical arguments about this line of research, given that as the embryo models become more developmentally advanced, they can also start to seem more intrinsically deserving of protection.

Synthetic life isn’t always ethically contentious. This year, researchers tested the limits of “minimal” cells, simple organisms derived from bacteria that have been stripped down to their genomic bare bones. These minimal cells have the tools to reproduce, but any genes that aren’t otherwise essential have been removed. In an important validation of how naturally lifelike the minimal cells are, researchers discovered that this minimal genome was able to evolve and adapt. After 300 days of growth and natural selection in the lab, the minimal cells could successfully compete against the ancestral bacteria from which they were derived. The findings demonstrated the robustness of the rules of life — that even after being robbed of nearly every genetic resource, the minimal cells could use the tools of natural selection to recover into more successful life forms.

Señor Salme for Quanta Magazine

Introduction

The Investigation of Consciousness

Consciousness is the feeling of being — the awareness of having a unique self, a picture of reality and a place in the world. It’s long been the terrain of philosophers, but recently scientists have made progress (of sorts) in understanding its neurobiological basis.

In an interview on the Joy of Why podcast released in May, the neuroscience researcher Anil Seth of the University of Sussex described consciousness as a kind of “controlled hallucination,” in that our experience of reality emerges from within us. None of us can directly know what the world is like; indeed, every organism (and individual) experiences the world differently. Our sense of reality is shaped by the sensory information we take in and the way our brain organizes it and constructs it in our consciousness. In that sense, our entire experience is a hallucination — but it is a controlled hallucination, the brain’s best-guess description of the immediate environment and larger world based on its memories and other encoded information.

Our minds are constantly taking in new external information and also creating their own internal imagery and narratives. How can we distinguish reality from fantasy? This year, researchers discovered that the brain has a “reality threshold” against which it constantly evaluates processed signals. Most of our mental images have a pretty weak signal, and so our reality threshold easily consigns them to the “fake” pile. But sometimes our perceptions and imagination can mix, and if those images are strong enough, we can get confused — potentially mistaking our hallucinations for real life.

How does consciousness emerge in the mind? Is it more about thinking, or is it a product of sensory experiences? This year, the results of a high-profile adversarial collaboration that pitted two major theories of consciousness against each other were announced. Over the course of five years, two teams of researchers — one representing global neuronal workspace theory, which focuses on cognition, and the other representing integrated information theory, which focuses on perception — co-created and then led experiments aimed at testing which theory’s predictions were more accurate. The results may have been a letdown for anyone hoping for definitive answers. Onstage in New York City, at the 26th meeting of the Association for the Scientific Study of Consciousness, the researchers acknowledged ways in which the experiments had challenged both theories and highlighted differences between them, but they declined to pronounce either theory the winner. However, the evening wasn’t entirely unsatisfying: The neuroscientist Christof Koch of the Allen Institute for Brain Science conceded a 25-year-old bet with the philosopher David Chalmers of New York University that the neural correlates of consciousness would have been identified by now.

Harol Bustos for Quanta Magazine

Introduction

New Ideas About Anguish

It’s often taken for granted that depression is caused by a chemical imbalance in the brain: specifically, a chronic deficiency of serotonin, a neurotransmitter that carries messages between nerve cells. Yet even though millions of depressed people around the world get relief from taking Prozac and the other drugs known as selective serotonin reuptake inhibitors, or SSRIs, based on that theory, decades’ worth of neuropsychiatric research has failed to validate the assumptions of that model. The hum of scientific dissent has been growing louder: An international team of scientists screened more than 350 papers and found no convincing evidence that lower levels of serotonin are associated with depression.

The realization that serotonin deficiency may not be the cause is forcing researchers to fundamentally rethink what depression is. It’s possible that SSRIs alleviate some symptoms of depression by altering other chemicals or processes in the brain that are more direct causes of depression. It’s also possible that what we call “depression” encompasses a variety of disorders that manifest with a similar set of symptoms, including fatigue, apathy, changes in appetite, suicidal thoughts and sleep issues. If that’s the case, significant additional research will be needed to unpack this complexity — to differentiate the kinds and causes of depression and to develop better treatments.

Depression can be an isolating experience. But it is distinct from loneliness, an emotional condition that neuroscientists have better defined in recent years. Loneliness is not the same as social isolation, which is an objective measure of the number of relationships a person is in: Someone can be in many relationships and still be lonely. Nor is it social anxiety, which is a fear of relationships or of certain relational experiences.

Instead, a growing body of neurobiological research suggests that loneliness is a bias in the mind toward interpreting social information in a negative, self-punishing way. It’s as if a survival signal that evolved to urge us to reconnect with the people we rely on has short-circuited, creating a self-perpetuating loop of felt isolation. Scientists haven’t yet found a medical treatment for loneliness, but perhaps simply understanding that negative loop can help the chronically lonely to escape the cycle and find comfort in their existing connections or in new ones.

Andreas Klingl, Ludwig Maximilian University; modified by Quanta

Introduction

The Origins of Complex Life

Where do we come from, and how did we get here? Those timeless questions could be answered in many ways, and they have set numerous biologists on a search for the origins of the eukaryotes — the 2-billion-year-old lineage of life that includes all animals, plants and fungi and many single-celled creatures more complex than bacteria.

The search for the first eukaryote has researchers painstakingly coaxing rare microbes from seafloor sludge. Recently, after six years of work, a European laboratory became only the second to successfully cultivate one of the Asgard archaea— a group of primitive single-celled organisms that have genomes with eyebrow-raising similarities to those of eukaryotes, and that are thought to be ancestral to them. Scientists hope that directly studying the cells in the lab will reveal new information about how eukaryotes evolved and edge us closer to understanding our origins.

The evolutionary journey of that first eukaryote is shrouded in mystery. This year, scientists found a way to fill in an 800-million-year gap in the molecular fossil record between the appearance of the earliest eukaryote and that of the most recent ancestor of all eukaryotes alive today. Previously, when seeking information about eukaryotes that lived in the blank space from roughly 800 million to 1.6 billion years ago, scientists couldn’t find the molecular fossils they expected. But when an Australian team tweaked their search filter to look for fossilized versions of more primitive molecules, they found them in abundance. The findings revealed what the authors call “a lost world” of eukaryotes that helps tell the story of the early evolutionary history of our ancient ancestors.

Tagide deCarvalho

Introduction

Microbiomes Evolve With Us

Research over the last decade has better characterized the microbiome — the collection of microorganisms that live in our guts and elsewhere in our body — and the subtle ways in which it influences our health. This year, scientists revealed in the greatest detail yet where our microbiomes come from and how they evolve throughout our lives.

Unsurprisingly, the first seeds of our microbiome usually come from mom — transmitted during birth and also through breastfeeding. Research published this year found that a mother’s contributions aren’t only whole microbial organisms, but also small snippets of DNA called mobile genetic elements. Up through the first year of life, these mobile genetic elements hop from the mother’s bacteria to the baby’s through a process called horizontal gene transfer. The discovery surprised researchers, who didn’t expect the high degree of coevolution between the mother’s microbiome and the baby’s to go on for so long after birth.

That’s not the end of the story: The microbiome evolves throughout our lives. The largest analysis yet of human microbiome transmission, also published this year, revealed how microbiomes shuffle and reassemble over many decades. It provided clear evidence that microbiome organisms spread between people, especially those with whom we spend the most time, such as family members, partners and roommates. And the study raised the intriguing possibility that some illnesses considered noncommunicable might actually be transmissible, in sometimes subtle ways, through gut flora.

Carlos Arrojo for Quanta Magazine

Introduction

How Life Keeps Time

Eons before the invention of sundials, watches and atomic clocks, organisms evolved biological tools to keep time. They need internal circadian clocks that can keep their metabolic processes in sync with the cycle of day and night, and also clocks akin to calendars to keep their developmental processes on track. This year, researchers made important advances in understanding both.

A flurry of research over the past several years, made possible by new stem cell technologies, has proffered new explanations for what’s known as developmental tempo. All vertebrates start life as a simple embryo — but the rate at which an embryo develops, and the timing of when its tissues mature, dramatically varies between species and determines their final form. What controls the ticking of the developmental clock? This year, a series of careful experiments in labs around the world, focusing on different species and systems, pointed to a common explanation: that fundamental metabolic processes, including biochemical reactions and the gene expression that underlies them, all set the pace. Those metabolic processes appear to be organized fundamentally by the mitochondria, which may very well serve dual roles as the complex cell’s timekeeper and power source.

While those researchers were scattered across the world, novel work on the circadian clock has been done in the lab of a single scientist: the biochemist Carrie Partch at the University of California, Santa Cruz. Partch is driven by a unique obsession not only with the basic steps of the clock, but also with the intricate dance that clock proteins perform as they are built and as they interact and degrade. Like any watchmaker, she isn’t satisfied with knowing what the gears and cogs are — she also needs to understand how they fit together. In paying such close attention to a single system over the course of her career, she has made discoveries about the dance of clock proteins that represent broader truths, for example that unstructured or even disordered proteins are fundamental to biological processes.

David Robertson, ICR / Science Source

Introduction

Refining the Brain’s Complexity

One sign of the progress in neuroscience is that it grows continually more precise. Using new tools that are more firmly grounded in sound science, scientists can now focus their attention on defining the quirks of individual brain cells. This year they located the social map of bats, which turned out to be superimposed on the bats’ map of their physical environment — the same exact brain cells in the hippocampus encode multiple kinds of environmental information. Other researchers seem to have resolved a 30-year debate over whether some of the brain’s glial cells — historically considered to be barely more than padding for the more prestigious neurons — can stimulate electrical signals. A team of neuroscientists and clinical researchers, helped by epilepsy patients who had electrodes implanted to improve their medical care, discovered that the brain has different systems for representing small and large numbers. And for the very first time, researchers visualized in three dimensions how an olfactory receptor grabs onto an odor molecule — a significant step in understanding how the nose and brain can intercept airborne chemicals and gain crucial sensory information about the environment.

Next

Table of Contents

Quanta Magazine: 23 Dec, 2023

23 Dec, 2023

The Year in Math

21 Dec, 2023

The Year in Physics

20 Dec, 2023

The Year in Computer Science

New Clues for What Will Happen When the Sun Eats the Earth

19 Dec, 2023

The Year in Biology