Quanta Magazine

All the activity on Earth’s surface — erupting volcanoes, shifting tectonic plates, restless seas and myriad forms of life — depends on the two-part engine under the hood. Directly beneath Earth’s crust lies the mantle: rock that melts, churns and flows like putty, driving the volcanic and tectonic activity at the surface. And below that, there’s the outer core, a liquid-metal ocean whose swirling streams surround the planet with a protective magnetic field.

A longtime assumption of geoscientists is that the boundary between the mantle and the outer core is clear and severe. After all, lighter mantle rock should essentially float atop the denser metallic core. But a recently published pair of studies tells a surprising story, one that was already suspected: Earth’s core is leaking material. This stuff is making its way right up to the surface, potentially ferried through two monster-size blobs sitting at the core-mantle boundary.

This “is kind of crazy,” said Harriet Lau, a geodynamicist at Brown University who was not involved with either study. If material is effusing from the core into the mantle, is the boundary between them “as distinct as we think?”

The research concludes that this abyssal wall has doorways.

🌋 Keep reading: www.quantamagazine.org/earths-core-appears-to-be-l…

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3 weeks ago | [YT] | 801

Quanta Magazine

Take a deep breath. A flow of oxygenated air has rushed into your lungs and bloodstream, fueling metabolic fires in cells throughout your body. You, being an aerobic organism, use oxygen as the cellular spark that frees molecular energy from the food you eat. But not all organisms on the planet live or breathe this way. Instead of using oxygen to harvest energy, many single-celled life forms that live in environments far from oxygen’s reach, such as deep-sea hydrothermal vents or stygian crevices in the soil, wield other elements to respire and unlock energy.

This physical separation of the oxygen-rich and oxygen-free worlds is not merely a matter of life utilizing available resources; it’s a biochemical necessity. Oxygen doesn’t play nice with the metabolic pathways that make it possible to respire with the use of other elements, such as sulfur or manganese. It gives aerobes like us life, but for many anaerobes, or creatures that respire without oxygen, it is a toxin that reacts with and damages their specialized molecular machinery.

“Oxygen — we love it, of course,” said Courtney Stairs, an evolutionary biologist at Lund University in Sweden. “But it’s actually a pretty harmful molecule for most of life on our planet, and even ourselves. We have ways to mitigate the negative effects of oxygen. So we can’t imagine life without it, but life is actually quite hard with it.”

For the first couple billion years of life on Earth, organisms avoided this predicament altogether. Back then, the air and oceans were mostly devoid of oxygen, so life was almost entirely anaerobic. Then, around 2.7 billion years ago, the seas filled with industrious, photosynthetic cyanobacteria. They had invented a way to turn sunlight into sugar and oxygen, and they flourished. Over hundreds of millions of years, their accumulated breathing filled the atmosphere and oceans with oxygen. This so-called Great Oxidation Event was a pivotal transformation in the biosphere and the physical chemistry of Earth’s atmosphere and oceans. In this new environment, aerobic respiration evolved to dominate the world.

An ongoing mystery for researchers is how life navigated the shift from anaerobic to aerobic respiration; so much microbial biodiversity had to adapt to a world filled with what was once a biochemical bane. Now researchers have fresh insight into what that transition could have looked like billions of years ago, gleaned from an organism living today. A bacterium that researchers collected from the cauldron of a Yellowstone National Park hot spring does something that life really shouldn’t be able to do: It runs aerobic and anaerobic metabolisms simultaneously. It breathes oxygen and sulfur at the same time.

🔗 Keep reading: www.quantamagazine.org/the-cells-that-breathe-two-…
📸 Eric Boyd

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1 month ago | [YT] | 654

Quanta Magazine

There are precision measurements, and then there’s the Laser Interferometer Gravitational-Wave Observatory. In each of LIGO’s twin gravitational wave detectors (one in Hanford, Washington, and the other in Livingston, Louisiana), laser beams bounce back and forth down the four-kilometer arms of a giant L. When a gravitational wave passes through, the length of one arm changes relative to the other by less than the width of a proton. It’s by measuring these minuscule differences — a sensitivity akin to sensing the distance to the star Alpha Centauri down to the width of a human hair — that discoveries are made.

The design of the machine was decades in the making, as physicists needed to push every aspect to its absolute physical limits. Construction began in 1994 and took more than 20 years, including a four-year shutdown to improve the detectors, before LIGO detected its first gravitational wave in 2015: a ripple in the space-time fabric coming from the faraway collision of a pair of black holes.

Physicist Rana Adhikari led the detector optimization team in the mid-2000s. He and a handful of collaborators painstakingly honed parts of the LIGO design, exploring the contours of every limit that stood in the way of a more sensitive machine.

But after the 2015 detection, Adhikari wanted to see if they could improve upon LIGO’s design, enabling it, for instance, to pick up gravitational waves in a broader band of frequencies. Such an improvement would enable LIGO to see merging black holes of different sizes, as well as potential surprises. “What we’d really like to discover is the wild new astrophysical thing no one has imagined,” Adhikari said. “We should have no prejudice about what the universe makes.”

He and his team turned to AI. Initially, the AI’s designs seemed outlandish. “The outputs that the thing was giving us were really not comprehensible by people,” Adhikari said. “They were too complicated, and they looked like alien things or AI things. Just nothing that a human being would make, because it had no sense of symmetry, beauty, anything. It was just a mess.” But the design was clearly effective.

🔗 Keep reading: www.quantamagazine.org/ai-comes-up-with-bizarre-ph…

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📸 2: Steve Babuljak

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1 month ago | [YT] | 883

Quanta Magazine

The universe is not always smooth — at the centers of black holes, for instance, the curvature of space-time explodes to infinity, forming a singularity., Whenever space-time isn’t sufficiently smooth, the 10 interconnected differential equations underlying Albert Einstein’s general theory of relativity stop working.

In October 2015, a young mathematician named Clemens Sämann was flying home to Austria from a conference in Turin, Italy, when he had a chance encounter. He found himself seated beside Michael Kunzinger, another conference attendee. Kunzinger was a math professor at the University of Vienna, where Sämann had just started his postdoctoral research. They soon got to talking, and landed on Einstein’s general theory of relativity and its limitation to smooth space-times. They wondered whether there was a mathematical way to get around this limitation.

The pair wouldn’t start working on the problem in earnest for another year. But since then, they’ve made significant advances toward their goal. They’ve found new ways to estimate curvature and other geometric properties without relying on the assumption that space-time is smooth. In collaboration with other researchers, they’ve used their methods to rederive (and sometimes strengthen) core theorems about the universe without depending on Einstein’s equations, putting those theorems on even firmer mathematical footing.

And they’re now part of an ambitious new program — launched last year under the direction of Roland Steinbauer, another University of Vienna mathematician — that aims to provide “a new geometry for Einstein’s theory of relativity and beyond.”

“Standard general relativity talks about geometric objects, namely space-times, but only if they behave nicely enough,” Steinbauer said. “With this new framework, we can go beyond that. We can handle very edgy objects, very badly behaved objects.”

Read the full story: www.quantamagazine.org/a-new-geometry-for-einstein…

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1 month ago | [YT] | 1,180

Quanta Magazine

Climate models have changed the way we view the world. While effective, these models are imperfect, and scientists are constantly looking at ways to improve their accuracy and predictability.

MIT professor Elfatih Eltahir has spent decades developing complex models to understand how climate change affects vulnerable regions like the Nile Basin and Singapore. In this episode of The Joy of Why, Eltahir tells co-host Steven Strogatz how growing up near the Nile in Sudan helped him realize that climate change doesn’t occur in isolation. To better understand climate-related impacts and to create more effective adaptation strategies, Eltahir says we need regional models that incorporate contextual data like disease spread and population growth. Eltahir also discusses his “Equation of the Future of Africa,” and he introduces the concept of “outdoor days,” which he hopes can improve public perception about climate change.

🎧 Listen to the episode: www.quantamagazine.org/how-can-regional-models-adv…

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1 month ago | [YT] | 436

Quanta Magazine

Randomness is a source of power. From the coin toss that decides which team gets the ball to the random keys that secure online interactions, randomness lets us make choices that are fair and impossible to predict. 

So instead, programmers often rely on things called hash functions, which swirl data around and extract some small portion in a way that looks random. For decades, many computer scientists have presumed that for practical purposes, the outputs of good hash functions are generally indistinguishable from genuine randomness — an assumption they call the random oracle model.

“It’s hard to find today a cryptographic application… whose security analysis does not use this methodology,” said Ran Canetti of Boston University.

Now, a new paper has shaken that bedrock assumption. It demonstrates a method for tricking a commercially available proof system into certifying false statements, even though the system is demonstrably secure if you accept the random oracle model. Proof systems related to this one are essential for the blockchains that record cryptocurrency transactions, where they are used to certify computations performed by outside servers.

There’s “a lot of money relying on this stuff,” said Eylon Yogev of Bar-Ilan University in Israel. For blockchain proof protocols, “there’s a huge motivation for attackers to break the security of the system.”

In the new paper — by Dmitry Khovratovich of the Ethereum Foundation, Ron Rothblum of the zero-knowledge proof technology company Succinct and the Technion in Haifa, Israel, and Lev Soukhanov of the blockchain-focused start-up [[alloc] init] — the researchers are able to prove lies no matter which hash function is used to generate the “randomness” the proof system relies upon.

When Yogev heard about the team’s result, he said, “I had the feeling that someone is pulling the carpet from under my feet.” He and others have been working to patch up these vulnerabilities. But “it’s far from being a solved issue,” he said.

More broadly, the new result is forcing a reckoning about the random oracle model. “This is a time to rethink,” Canetti said.

🎨 Wei-An Jin/Quanta Magazine

🔗 Read the full story: www.quantamagazine.org/computer-scientists-figure-…

1 month ago | [YT] | 678

Quanta Magazine

When Thomas Hummel gets a whiff of an unripe, green tomato, he finds himself in his childhood home in Bavaria. Under the tilted ceilings of the bedroom that he shared with his two older brothers, there were three beds, a simple table and a cupboard. “My mother put those green tomatoes on the cupboard for them to ripen,” said Hummel, an olfaction researcher at the Carl Gustav Carus University Hospital in Germany. “They have this very specific smell.”

It’s grassy, green, pungent, rough and bitter, he said. When he passes by a bin of tomatoes at the market today, “it is always to some degree emotional,” he said, “like every smell is emotional.”

Smell is deeply tied with the emotion and memory centers of our brain. Lavender perfume might evoke memories of a close friend. A waft of cheap vodka, a relic of college days, might make you grimace. The smell of a certain laundry detergent, the same one your grandparents used, might bring tears to your eyes.

Smell is also our most ancient sense, tracing back billions of years to the first chemical-sensing cells. But scientists know little about it compared to other senses — vision and hearing in particular. That’s in part because smell has not been deemed critical to our survival; humans have been wrongly considered “bad smellers” for more than a century. It’s also not easy to study.

“It’s a highly dimensional sense,” said Valentina Parma, an olfactory researcher at the Monell Chemical Senses Center in Philadelphia. “We don’t know exactly how chemicals translate to perception.” But scientists are making progress toward systematically characterizing and quantifying what it means to smell by breaking the process down to its most fundamental elements — from the odor molecules that enter your nose to the individual neurons that process them in the brain.

Several new databases, including one recently published in the journal 𝘚𝘤𝘪𝘦𝘯𝘵𝘪𝘧𝘪𝘤 𝘋𝘢𝘵𝘢, are attempting to establish a shared scientific language for the perception of molecular scents — what individual molecules “smell like” to us. And on the other end of the pathway, researchers recently published a study in 𝘕𝘢𝘵𝘶𝘳𝘦 describing how those scent molecules are translated into a neural language that triggers emotions and memories.

Together, these efforts are painting a richer picture of our strongest memory-teleportation device. This higher-resolution look is challenging the long-held assumption that smell is our least important sense.

👃Read the full story: www.quantamagazine.org/how-smell-guides-our-inner-…

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1 month ago | [YT] | 602

Quanta Magazine

The natural world is awash with color, and many of these vibrant hues are meant to be seen. Apples blush red to coax animals to spread their seeds, lavender blooms are violet to lure in pollinating bees, and male peacocks trailed by flashy blue trains more successfully attract mates.

However, the world is colorful only for some of us. These vivid signals can be perceived by animals that can see in color; to organisms that have limited or no color vision, many of these bright colors don’t mean anything at all. This raises interesting evolutionary questions. Which came first: colorful signals or the color vision needed to see them? And when did these optical signals emerge and take off, painting the natural world in the kaleidoscopic spectrum we see today?

“Some birds are red, some snakes are red, and some plants have red fruits. In each of these cases, the red coloration serves as a signal,” said Zachary Emberts, an evolutionary biologist at Oklahoma State University. “This led us to wonder: What was the initial function of conspicuous coloration, like red, and color vision?”

Emberts and his former postdoctoral adviser John Wiens, an evolutionary ecologist at the University of Arizona, combed through research encompassing hundreds of millions of years of evolutionary history to offer a scientific answer to the chicken-and-egg question of color. The researchers used the fossil record and phylogenetic trees — timelines of species emergence that are based largely on modern traits — to infer when colorful signals may have first emerged in plants and animals. Then they tested their hypothesis that color vision and colorful signals evolved together.

“What I love about this paper is the ambition and confidence to pursue big questions and explore ideas that will inevitably involve speculation,” said William Allen, an ecologist who studies sensory systems at Swansea University in Wales and was not involved in the new study. “There is a tendency for science in the 21st century to focus on applying analytic techniques to data, and this can sometimes be at the detriment to deep thought, natural history and curiosity.”

🌈 Read the full story: www.quantamagazine.org/when-did-nature-burst-into-…

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2 months ago | [YT] | 657

Quanta Magazine

Born in the 18th century when Leonhard Euler solved the puzzle of the seven bridges of Königsberg, graph theory has become a foundational tool in mathematics. It studies relationships through nodes (vertices) and the links (edges) that connect them, transforming the complexity of systems — from friendship networks to airline routes — into elegant abstractions that reveal underlying structure and interaction.

Maria Chudnovsky from Princeton University is a leading mathematician in the field. In this episode of The Joy of Why, Chudnovsky talks with co-host Janna Levin about how she got into graph theory, solved the decades-old perfect graph problem, and used it to plan her wedding seating chart. Chudnovsky also reflects on her appearance in commercials as a “superstar mathematician,” and how her background primed her for a discipline that transcends language, culture and time.

🎧 Listen to the episode: www.quantamagazine.org/how-does-graph-theory-shape…

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2 months ago | [YT] | 659

Quanta Magazine

Beneath the richness of our world lies a pristine simplicity. Everything is made of a set of just 17 fundamental particles, and those particles, though they may differ by mass or charge, come in just two basic types. Each is either a “boson” or a “fermion.”

The physicist Paul Dirac coined both terms in a speech in 1945, naming the two particle kingdoms after physicists who helped elucidate their properties: Satyendra Nath Bose and Enrico Fermi.

In 1924, Bose was working at the University of Dhaka, in what is known today as Bangladesh. Earlier, around 1900, Max Planck had proposed a law for how much light of each color a hot object emits. (Planck’s insight that this light comes in discrete packets, or “quanta,” set physicists on the path to quantum mechanics.) Bose found a stronger mathematical derivation of Planck’s law. He wrote to Albert Einstein, asking for help in submitting the result to a German journal, then collaborated with Einstein to flesh out the idea.

Bose and Einstein’s math described a situation where multiple particles can be perfectly alike: not just have the same charge, mass and energy but even exist in the same place at the same time. Photons, the particles of light, behave this way. A laser, for instance, consists of many photons synchronized at the same wavelength, together in a single beam. We now call such particles bosons.

🔗 Learn more about bosons and fermions in Matt von Hippel’s new explainer: www.quantamagazine.org/matter-vs-force-why-there-a…

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2 months ago | [YT] | 773