Quanta Magazine

Biofilms lead lives of liminality. Just a few cells thick, these layered communities of microbes anchor themselves to solid surfaces at interfaces — between rocks and salt water on slimy rocks in tide pools, where plants meet dirt in the root systems of plants, or on the saliva-covered surface of your teeth. Amalgamations of single cells, biofilms grow and develop into unified life forms that can split back into their component cells under duress. Biofilms, then, are somehow both unicellular and multicellular — and simultaneously neither.

Biofilms have emergent properties: traits that appear only when a system of individual items interacts. It was this emergence that attracted the biophysicist Peter Yunker to the microbial structures. Trained in soft matter physics — the study of materials that can be structurally altered — he is interested in understanding how the interactions between individual bacteria result in the higher-order structure of a biofilm.

As cells divide and a biofilm grows, it doesn’t simply expand outward. What starts as a flat, smooth layer of cells stretches and pulses. Strange, sticky shapes appear as the bacteria reassemble into ridges and depressions that warp and buckle, almost as if the collective is breathing. In recent years, researchers have been studying the role of shape and geometry in biofilms and how physical laws, such as those governing cellular metabolism and the diffusion of nutrients, determine how biofilms grow and thrive.

🧫 Keep reading: www.quantamagazine.org/how-a-biofilms-strange-shap…

🎨 Scott Chimileski and Roberto Kolter

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1 week ago | [YT] | 1,344

Quanta Magazine

Quantum gravity is one of the biggest unresolved and challenging problems in physics, as it seeks to reconcile quantum mechanics, which governs the microscopic world, and general relativity, which describes the macroscopic world of gravity and space-time.

Efforts to understand quantum gravity have been focused almost entirely at the theoretical level, but Monika Schleier-Smith at Stanford University has been exploring a novel experimental approach — trying to create quantum gravity from scratch. Using laser-cooled clouds of atoms, she is testing the idea that gravity might be an emergent phenomenon arising from quantum entanglement.

In this episode of The Joy of Why podcast, Schleier-Smith discusses the thinking behind what she admits is a high-risk, high-reward approach, and how her experiments could provide important insights about entanglement and quantum mechanical systems even if the end goal of simulating quantum gravity is never achieved.

🎧 Listen to the episode: www.quantamagazine.org/can-quantum-gravity-be-crea…

🎨 Peter Greenwood for Quanta Magazine; Logo by Jaki King for Quanta Magazine

1 week ago | [YT] | 984

Quanta Magazine

Language isn’t always necessary. While it certainly helps in getting across certain ideas, some neuroscientists have argued that many forms of human thought and reasoning don’t require the medium of words and grammar. Sometimes, the argument goes, having to turn ideas into language actually slows down the thought process.

Now there’s intriguing evidence that certain artificial intelligence systems could also benefit from “thinking” independently of language.

When large language models (LLMs) process information, they do so in mathematical spaces, far from the world of words. That’s because LLMs are built using deep neural networks, which essentially transform one sequence of numbers into another — they’re effectively complicated math functions. Researchers call the numerical universe in which these calculations take place a latent space.

But these models must often leave the latent space for the much more constrained one of individual words. This can be expensive, since it requires extra computational resources to convert the neural network’s latent representations of various concepts into words. This reliance on filtering concepts through the sieve of language can also result in a loss of information, just as digitizing a photograph inevitably means losing some of the definition in the original. “A lot of researchers are curious,” said Mike Knoop, co-creator of one of the leading benchmarks for testing abstract reasoning in AI models. “Can you do reasoning purely in latent space?”
Two recent papers suggest that the answer may be yes. In them, researchers introduce deep neural networks that allow language models to continue thinking in mathematical spaces before producing any text. While still fairly basic, these models are more efficient and reason better than their standard alternatives.

“It’s an exciting new research direction,” said Luke Zettlemoyer, a computer scientist and natural language processing expert at the University of Washington who wasn’t involved in either paper.

🔗 Keep reading: www.quantamagazine.org/to-make-language-models-wor…

🎨 Myriam Wares

2 weeks ago | [YT] | 1,218

Quanta Magazine

On a quiet pandemic afternoon in 2021, Zihyuan Wang, then a graduate student at Rice University, was alleviating his boredom by working on a weird mathematical problem. After he found an exotic solution, he started to wonder if the math could be interpreted physically. Eventually, he realized that it seemed to describe a new type of particle: one that’s neither a matter particle nor a force-carrying particle. It appeared to be something else altogether.

Wang was eager to develop the accidental discovery into a full theory of this third kind of particle. He brought the idea to Kaden Hazzard, his academic adviser.

“I said, I’m not sure I believe this can be true,” Hazzard recalled, “but if you really think it is, you should put all your time on this and drop everything else you’re working on.”

This January, Wang, now a postdoctoral researcher at the Max Planck Institute of Quantum Optics in Germany, and Hazzard published their refined result in the journal Nature. They say that a third class of particles, called paraparticles, can indeed exist, and that these particles could produce strange new materials.

When the paper appeared, Markus Müller, a physicist at the Institute for Quantum Optics and Quantum Information in Vienna, was already contending with the notion of paraparticles for a different reason. According to quantum mechanics, an object or observer can be in multiple locations at once. Müller was thinking about how you can, on paper, switch between the perspectives of observers in these coexisting “branches” of reality. He realized that this came with new constraints on the possibility of paraparticles, and his team described their results in a preprint in February that’s now under review for publication in a journal.

The close timing of the two papers was a coincidence. But taken together, the work is reopening the case of a physics mystery that was believed to be solved decades ago. A basic question is being reevaluated: What kinds of particles does our world allow?

🔗 Read the story: www.quantamagazine.org/paraparticles-would-be-a-th…

🎨 Kristina Armitage

2 weeks ago | [YT] | 1,425

Quanta Magazine

Growing up, Tai-Danae Bradley had no love for math. In 2008, she entered the City College of New York, where she played for the basketball team and hoped to start a career in sports nutrition. She saw her math courses as a curricular hurdle that only geniuses could really excel in. “I’d have rather had all my teeth pulled than do it for a living,” she said.

But in her sophomore year, her calculus professor changed her mind. Mathematics, she learned, was the language that all the sciences are written in. “There’s something deeper out there than what’s in the textbooks,” she said. “It’s a really delightful world that we live in, and mathematics is a way to see some of that.”

She quit the basketball team and decided to double-major in math and physics. Now, as a researcher at the artificial intelligence company SandboxAQ, and a visiting professor at the Master’s University in California, Bradley is using the language of math to try to better understand language itself.

Her lens is category theory, a way of stepping back from the specifics of any individual field in favor of a broader underlying framework that bridges all of them. By thinking of language as a mathematical category, she’s been able to apply established tools to study it and glean new insights.

Linguists hope her model can help them to prove certain theories about how grammar and meaning emerge from strings of words, and to identify how AI-generated text differs from human language. Bradley herself is more interested in how studying language in this way might allow her to develop new mathematical tools.

Quanta spoke with Bradley about how mathematics can inform the study of language and vice versa. The interview has been condensed and edited for clarity.

🔗 Read the interview: lnkd.in/eJDCUNAF

📸 Monica Almeida for Quanta Magazine

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2 weeks ago | [YT] | 1,067

Quanta Magazine

Humans tend to put our own intelligence on a pedestal. Our brains can do math, employ logic, explore abstractions and think critically. But we can’t claim a monopoly on thought. Among a variety of nonhuman species known to display intelligent behavior, birds have been shown time and again to have advanced cognitive abilities. Ravens plan for the future, crows count and use tools, cockatoos open and pillage booby-trapped garbage cans, and chickadees keep track of tens of thousands of seeds cached across a landscape. Notably, birds achieve such feats with brains that look completely different from ours: They’re smaller and lack the highly organized structures that scientists associate with mammalian intelligence.

“A bird with a 10-gram brain is doing pretty much the same as a chimp with a 400-gram brain,” said Onur Güntürkün, who studies brain structures at Ruhr University Bochum in Germany. “How is it possible?”

Researchers have long debated about the relationship between avian and mammalian intelligences. One possibility is that intelligence in vertebrates — animals with backbones, including mammals and birds — evolved once. In that case, both groups would have inherited the complex neural pathways that support cognition from a common ancestor: a lizardlike creature that lived 320 million years ago, when Earth’s continents were squished into one landmass. The other possibility is that the kinds of neural circuits that support vertebrate intelligence evolved independently in birds and mammals.

It’s hard to track down which path evolution took, given that any trace of the ancient ancestor’s actual brain vanished in a geological blink. So biologists have taken other approaches — such as comparing brain structures in adult and developing animals today — to piece together how this kind of neurological complexity might have emerged.

A series of studies published in @sciencemagazine in February 2025 provides the best evidence yet that birds and mammals did not inherit the neural pathways that generate intelligence from a common ancestor, but rather evolved them independently.

🐤 Read the full story: www.quantamagazine.org/intelligence-evolved-at-lea…

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1, 2: Samantha Mash for Quanta Magazine
3: Courtesy of Bastienne Zaremba
4: Tatiana Gallego Flores
5: Mark Belan/Quanta Magazine

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3 weeks ago | [YT] | 1,261

Quanta Magazine

Quanta has been nominated for Best Science Website in The Webby Awards! Help us win by voting here: vote.webbyawards.com/PublicVoting#/2025/websites-a…

3 weeks ago | [YT] | 822

Quanta Magazine

In 1950 the Italian physicist Enrico Fermi was discussing the possibility of intelligent alien life with his colleagues. If alien civilizations exist, he said, some should surely have had enough time to expand throughout the cosmos. So where are they?

Many answers to Fermi’s “paradox” have been proposed: Maybe alien civilizations burn out or destroy themselves before they can become interstellar wanderers. But perhaps the simplest answer is that such civilizations don’t appear in the first place: Intelligent life is extremely unlikely, and we pose the question only because we are the supremely rare exception.

A new proposal by an interdisciplinary team of researchers challenges that bleak conclusion. They have proposed nothing less than a new law of nature, according to which the complexity of entities in the universe increases over time with an inexorability comparable to the second law of thermodynamics — the law that dictates an inevitable rise in entropy, a measure of disorder. If they’re right, complex and intelligent life should be widespread.

In this new view, biological evolution appears not as a unique process that gave rise to a qualitatively distinct form of matter — living organisms. Instead, evolution is a special (and perhaps inevitable) case of a more general principle that governs the universe. According to this principle, entities are selected because they are richer in a kind of information that enables them to perform some kind of function.

🔗 Read the full story: www.quantamagazine.org/why-everything-in-the-unive…

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1, 2: Irene Pérez for Quanta Magazine
3: Katherine Cain/Carnegie Science, Courtesy of Robert Hazen

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3 weeks ago | [YT] | 849

Quanta Magazine

Imagine an ice cube floating in a glass of water. As it melts, its surface gets smoother, and any irregularities or sharp edges gradually vanish. Mathematicians want to understand this process in greater detail — to be able to say exactly how the surface of the ice changes over time.

To analyze this phenomenon, they study how more abstract mathematical surfaces and shapes evolve according to a particular set of rules. This set of rules defines a process called mean curvature flow, which simultaneously smooths out a surface and shrinks it.

But as the surface evolves, singularities can form: points where our mathematical descriptions break down. The surface might jut out sharply, or it might thin to a point where the curvature “blows up” to infinity. Many common kinds of surfaces — such as those that are closed up, like a sphere — are guaranteed to exhibit singularities during mean curvature flow.

If these singularities are too complicated, it becomes impossible for the flow to continue.
Mathematicians want to ensure that even after a singularity forms, they can still analyze how the surface will continue to evolve. In 1995, Tom Ilmanen proposed the “multiplicity-one” conjecture. It stated that any singularities that do form during the process of mean curvature flow must be relatively simple. “Bad” behavior should be limited to individual points: You should never see, for instance, multiple regions stacked on top of each other.

If true, the multiplicity-one conjecture would affirm that singularities are not a showstopper when it comes to mean curvature flow. Should a singularity appear, the flow can go on — making it possible for mathematicians to assess the surface’s evolution.

Over the past few decades, mathematicians have made many advances in characterizing the behavior of surfaces as they move through mean curvature flow. “But a lot of the results achieved so far were contingent on the multiplicity-one conjecture being true,” said Richard Bamler. “Somehow, the main stumbling block was always the multiplicity-one conjecture.”

Now, he and Bruce Kleiner have finally proved that the conjecture is in fact true.

🧊 Read the story: www.quantamagazine.org/a-new-proof-smooths-out-the…

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1: Claus Jensen/Science Source
2, 3: Mark Belan/Quanta Magazine

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4 weeks ago | [YT] | 1,116

Quanta Magazine

Nothing is certain in the quantum realm. A particle, for example, can exist in multiple quantum states simultaneously. The same goes for a quantum bit, or qubit — the basic unit of information used in quantum computing. The act of measurement causes these objects to collapse into a single state, and usually the best you can do is calculate the probability of a particular outcome. 
 
The unpredictability at the heart of the quantum realm has been immensely useful for computing and cryptography, where experts have learned to harness randomness as a tool. But as useful as it is for quantum circuits to incorporate true randomness, it’s a difficult state to achieve, with steep costs. “Generating randomness is pretty expensive,” said William Kretschmer, a researcher at the Simons Institute for the Theory of Computing who studies quantum complexity. 
 
As a result, quantum researchers have long wanted to see if they could possibly fake that randomness. They wanted to build “pseudorandom” quantum circuits, which seem to be truly random but can nonetheless be constructed relatively simply and manageably. The only problem was that no one knew if it was possible to actually build one.
 
After years of uncertainty, two researchers posted a paper last October that proved that it is in fact possible to construct such a circuit. Their work provides an elegant and secure way to represent quantum randomness that’s indistinguishable from the real thing, without the enormous computational load — though it’s only possible in a world where some basic theoretical assumptions of cryptography are correct. The proof could open new doors for quantum computing and cryptography research.
 
“Before this recent result on pseudorandom [circuits], we didn’t have good evidence that they actually exist,” said Alexander Poremba, a quantum computing researcher at the Massachusetts Institute of Technology who was not involved with the new paper. Now, “for the first time, we have very good evidence that pseudorandomness is a real concept.”

🔗 Keep reading: www.quantamagazine.org/the-high-cost-of-quantum-ra…

🎨 Maggie Chiang for Quanta Magazine

1 month ago (edited) | [YT] | 867