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It’s not just how many, it’s when: People judge a potential partner’s sexual history by timing, not total number

A major international study has found that when it comes to choosing a long-term partner, people across the globe consider not just how many sexual partners someone has had, but also when those encounters took place.

This is the first time researchers have explored the timing of sexual history alongside quantity—offering a fresh perspective on human mating psychology. The study is published in the journal Scientific Reports.

Led by Swansea University, the study surveyed more than 5,000 participants from 11 countries across five continents. It found that people were generally less willing to commit to someone with a high number of past sexual partners but were more open if those encounters had become less frequent over time, suggesting a shift away from casual sex.

New measurement of free neutron lifetime achieves world-record precision

Incorporated into every aspect of everyday life, the neutron is a fundamental particle of nature. Now, a research collaboration led by Los Alamos National Laboratory has improved the precision of free neutron lifetime measurements. The team’s results highlight the success of the UCNTau experiment’s design and previews the effectiveness of new techniques and approaches that the team is incorporating into the next generation of the experiment.

“The precise lifetime of free neutrons is at the center of still-contested physics questions,” said Steven Clayton, physicist at Los Alamos. “Understanding the neutron lifetime can be used to test the nature of the weak force, one of the fundamental forces of the universe, and can also help search for physics beyond the Standard Model.

Our results here validate the UCNtau experimental approach and point the way toward design improvements that will further enhance our understanding of the physics involved.

Quantum framework offers new approach to analyzing complex network data

Whenever we mull over what film to watch on Netflix, or deliberate between different products on an e-commerce platform, the gears of recommendation algorithms spin under the hood. These systems sort through sprawling datasets to deliver personalized suggestions. However, as data becomes richer and more interconnected, today’s algorithms struggle to keep pace with capturing relationships that span more than just pairs, such as group ratings, cross-category tags, or interactions shaped by time and context.

A team of researchers led by Professor Kavan Modi from the Singapore University of Technology and Design (SUTD) has taken a conceptual leap into this complexity by developing a new quantum framework for analyzing higher-order network data.

Their work centers on a mathematical field called topological signal processing (TSP), which encodes more than connections between pairs of points but also among triplets, quadruplets, and beyond. Here, “signals” are information that lives on higher-dimensional shapes (triangles or tetrahedra) embedded in a network.

Packed particles power up: Physicists discover particles that accelerate when crowded

What if particles don’t slow down in a crowd, but move faster? Physicists from Leiden worked together and discovered a new state of matter, where particles pass on energy through collisions and create more movement when packed closely together.

We all know crowds of people, or cars in a traffic jam—when it gets too crowded, all you can do is stand still. Until now, scientists have mainly studied cases of large groups just like this, which slow down when they get too close to each other.

But what if the opposite happens? What if could start moving more when packed together? That question hadn’t been studied much—until now. Physicists Marine Le Blay, Joshua Saldi and Alexandre Morin from Leiden University do research in the field of active matter physics—they observe and analyze the collective behaviors that emerge when large groups of particles are packed together.

Ultrathin metallic films show tunable, directional charge flow using light at room temperature

In a major step toward next-generation electronics, researchers at the University of Minnesota Twin Cities have discovered a way to manipulate the direction of charge flow in ultrathin metallic films at room temperature using light. This discovery opens the door to more energy-efficient optical sensors, detectors, and quantum information devices.

The research is published in Science Advances.

The team showed that ultra-thin layers of ruthenium dioxide (RuO2), grown on (TiO2), can be made to behave differently depending on direction—both in how they respond to light and how electricity moves through them.

Gaussian processes provide a new path toward quantum machine learning

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then, that researchers wanted to transfer this same power to quantum computers—but all attempts to do so brought unforeseen problems.

Recently, however, a team at Los Alamos National Laboratory developed a new way to bring these same to quantum computers by leveraging something called the Gaussian process.

“Our goal for this project was to see if we could prove that genuine quantum Gaussian processes exist,” said Marco Cerezo, the Los Alamos team’s lead scientist. “Such a result would spur innovations and new forms of performing quantum .”

Ionic-electronic photodetector brings in-sensor vision closer to reality

In an advance at the intersection of neuromorphic engineering and photonics, researchers have developed an ionic-electronic photodetector that not only detects light but also performs in-sensor image processing, offering the potential to surpass some limitations of human vision—including color vision deficiencies.

Optimized cycle system recovers waste heat from fusion reactor

A research team led by Prof. Guo Bin from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has designed and optimized an organic Rankine cycle (ORC) system specifically for recovering low-grade waste heat from the steady-state Chinese Fusion Engineering Testing Reactor (CFETR) based on organic fluid R245fa, achieving enhanced thermal efficiency and reduced heat loss.

CFETR, a steady-state magnetic reactor, is a crucial step toward realizing commercial fusion energy. However, managing the large amount of low-grade waste heat produced by components such as the divertor and blanket remains a key challenge.

To solve the thermodynamic and heat integration issues, the researchers developed advanced simulation models using Engineering Equation Solver for cycle analysis and MATLAB-based LAMP modeling for dynamic system configuration. These tools enabled a comprehensive investigation and optimization of the ORC configuration, leading to significantly improved thermal performance.

Physicists Harness Light To Control Semiconductors in Trillionths of a Second

A peer-reviewed study reports the development of ultrafast modulation technology in nanoelectronics. Physicists from Bielefeld University and the Leibniz Institute for Solid State and Materials Research Dresden (IFW Dresden) have introduced a new technique that uses ultrashort light pulses to manip

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