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How Rare Events Remember

A new theory of rare recurrent events dispenses with the simplifying assumption that recent events lack memory of previous ones.

Recurring earthquakes, stock-market crashes, catastrophic floods, and other rare events are statistically unlikely but significantly impactful. Their prediction is commonly based on the Arrhenius-Kramers paradigm [1], one of the most broadly applied frameworks in statistical physics. Implicit in this formalism are two strong universal features. First, the distribution of times to reach a rare event is exponential and independent of initial conditions, implying no correlation exists between successive rare events. Second, the mean waiting time increases exponentially with the size of the energy barrier (or effective energy) to be overcome. Despite its applicability, nature sometimes defies the Arrhenius-Kramers paradigm. Proteins can cross energy barriers with nonexponential kinetics [2], rainfall extremes can cluster in time [3] (Fig.

‘Flying focus’ laser overcomes key limitation in plasma-based particle accelerators

In a new Nature Physics study, researchers accelerated electrons to more than twice the energy predicted by the traditional dephasing limit for laser-plasma accelerators operating over the same distance. This was made possible by a specially engineered laser pulse called a flying focus, which counteracts a longstanding limitation known as “dephasing.”

Laser-plasma accelerators use an intense, ultrashort laser pulse to drive a wave of charge through a plasma. In principle, this makes it possible to accelerate particles to very high energies over just centimeters, rather than kilometers.

The problem is that the accelerating plasma wave cannot keep pace with the electrons riding it. The electrons move at speeds close to the speed of light, but the laser pulse driving the wave travels slightly slower. Over distance, the electrons manage to outrun the plasma wave. This dephasing causes the electrons to stop gaining energy, thereby affecting the amount of energy such accelerators can deliver.

When it comes to predicting people’s preferences, it pays to consider ‘the power of three’

In his 1927 paper, “A law of comparative judgment,” the American psychologist L. L. Thurstone proposed that when people select one option among multiple alternatives, they are picking the one that has the highest value to them, even though they cannot assign a particular number to that choice.

Thurstone was a pioneer of “psychometrics”—a field built on the premise that mental processes, which we cannot see, can nevertheless be measured and quantified. His 1927 paper laid the groundwork for what are now called random utility models, which provide a mathematical framework for describing human preferences—information that can be relied on, in turn, to make predictions about various hypothetical situations.

Random utility models (RUMs) are so named because they assess the “utility,” or benefit, that can be obtained from a given choice—such as deciding which book to read first among the stack of novels you brought back from the library.

DNA repair enzymes favor specific sequences, shaping mutation patterns in the human genome

When a wound does not heal properly, it leaves a scar. Similarly, mutations—which are permanent changes to genetic code—are often the result of damaged DNA that has not been properly repaired. Mutations can impede the function of genes and lead to disease and aging, but they are also the source of genetic variation, which allows new traits to emerge and facilitates the evolutionary process. Scientists still do not fully understand why some damaged DNA segments are successfully repaired while others are not.

In a new study published in Nature Communications, researchers from the Weizmann Institute of Science succeeded in identifying which DNA sequences and structures are the preferred targets for several of the most important DNA repair enzymes. The findings from the laboratory of Dr. Ariel Afek suggest that these preferences shaped the human genome and could even help explain how cells become cancerous.

Every day, thousands of chemical reactions take place in every living cell, damaging the genome. “When DNA repair systems work properly, they repair most of the damage, but not all of it,” Afek explains. “Therefore, the rate at which mutations accumulate is a balance between the rate of damage and the rate of repair.

Engineered enzymes forge carbon-carbon and carbon-nitrogen bonds with high selectivity

Researchers from the Manchester Institute of Biotechnology, including Dr. Zachary Birch-Price and professor Anthony Green, have developed a new family of engineered enzymes that can create several different types of chemical bonds used to build complex molecules. This work demonstrates how artificial enzymes can be adapted to carry out a broad range of carbon-carbon (C-C) and carbon-nitrogen (C-N) bond-forming reactions with high selectivity, offering new possibilities for biocatalysis.

Published in Nature Catalysis, the research addresses a long-standing challenge in chemistry: developing biological catalysts that can selectively construct complex molecular architectures. Carbon-carbon and carbon-nitrogen bonds are fundamental building blocks in many chemicals, pharmaceuticals and advanced materials.

“Biocatalysis has transformed our ability to carry out many chemical reactions using enzymes, but there are still important areas of chemistry that remain difficult to access. In this work, we show that artificial enzymes can be engineered to perform a wide variety of bond-forming reactions. What is particularly exciting is that the same underlying catalytic strategy can be adapted to work with many different reaction partners. This versatility gives us a foundation for developing new enzyme platforms capable of producing a wide range of valuable chemical structures,” said Green, professor of chemical biology and director of the MIB.

Graphene-powered soft lens could pave the way for smarter glasses, cameras and medical devices

The ability to change focus instantly is something most people take for granted. Every day, our eyes effortlessly switch between reading a book, recognizing a face across the room or watching a bird fly overhead. Replicating that remarkable technological flexibility, however, has proved far more difficult.

Researchers at Queen Mary University of London, led by Professor James Busfield, have taken an important step toward making adaptive lenses smaller, lighter and more practical by developing a transparent graphene-based material that allows soft lenses to change focus electronically without bulky moving parts. The work has eliminated key design constraints limiting electrostatically actuated lenses, opening the door to opportunities for compact medical imaging devices, autofocus cameras and wearable displays.

Published in Advanced Functional Materials, the study demonstrates how ultrathin transparent electrodes made from reduced graphene oxide can be integrated into a soft, electrically driven lens. The result is a compact device capable of changing its focal distance simply by applying a small electric field.

Quantum heat circuits learn electronics’ oldest trick: Sharing a power supply

Every electronic and optoelectronic device generates heat, and today that heat is managed almost entirely from the outside. Heatsinks, fans, cold plates and refrigerators are bulky exterior measures bolted onto a chip or package after the fact. They treat heat as a single averaged quantity to be removed in bulk, even though the heat is actually produced locally, component by component, deep inside the circuitry.

Quantum thermal devices offer a fundamentally different approach. Because they are tiny, heat-management circuitry can, in principle, be built right next to each electronic or optoelectronic component that needs it.

Instead of one bulk, averaged solution for an entire chip, each component could have its own tailored thermal circuit beside it, steering heat away exactly where it arises. That is the long-term technological promise motivating this field.

Distant time crystals oscillate in unison, paving the way for spin networks

In January 2024, physicists at TU Dortmund University demonstrated a continuous time crystal in a semiconductor whose oscillations remained stable for hours. In a new study published in Nature Communications, Professor Alex Greilich and his team show that many such time crystals can form in the same material and synchronize their electron-nuclear spin oscillations.

Time crystals are systems whose internal dynamics repeat periodically in time without being driven by a periodic external signal. In the TU Dortmund experiment, they are created in a semiconductor made of gallium arsenide containing small amounts of indium and silicon, which provides localized electrons. At temperatures close to −270°C (−454°F), each electron interacts with about one million surrounding nuclear spins.

A pump laser aligns the electron spins, which transfer their polarization to the nuclear spins. In a weak magnetic field, the nuclear-spin polarization begins to rotate. The resulting feedback between the electron and nuclear spins sustains the oscillations, while a second laser is used to observe them.

Discovery of ‘slow’ electrons in 2D material could lead to new memory device

Over the last decade, researchers have developed two-dimensional materials with fascinating quantum effects that could be harnessed for next-generation technologies.

Such materials have shown superconductivity—conducting electricity without energy loss—and charge orders, where electrons arrange in frozen patterns rather than moving freely in the material.

At the University of Chicago Pritzker School of Molecular Engineering (UChicago PME), a research team discovered that one such material, Fe5GeTe2, exhibits a charge-ordered state in which electrons move collectively and unusually slowly while remaining quantum coherent.

‘Lying mirror’ uses structured surfaces to conceal optical information

Mirrors normally reveal what is placed in front of them, even when their curvature distorts a reflection. Researchers at the University of California, Los Angeles (UCLA) have introduced a different optical concept: a “lying mirror” that hides information carried by an input image and transforms it into a misleading, ordinary-looking pattern at the output. The study is published in the journal Nature Communications.

The all-optical system combines a reflective mirror with an optimized structured diffractive surface. Instead of using a computer to digitally alter an image, the lying mirror performs the transformation through programmed light diffraction and passive light-matter interactions. Once the diffractive surface is designed and fabricated, the optical transformation that hides the input information requires no digital computation.

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