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Countries in the Global South risk being left out of the quantum revolution — along with its economic, technological and security benefits — due to growing export controls, siloed research initiatives and national security concerns, a new policy analysis argues.

In the first of a series of articles on quantum technologies published by the policy journal Just Securit y, researchers Michael Karanicolas, of Dalhousie University, and Alessia Zornetta, of UCLA Law, examine how the geopolitics of emerging quantum technologies are replicating long-standing patterns of technological exclusion. The authors argue that absent meaningful interventions, quantum could become another engine of global inequality, one that threatens to lock poorer nations out of the next era of technological and economic development.

The authors trace the roots of this divide to export control regimes that are quickly expanding in response to the strategic potential of quantum systems. Since 2020, governments in the U.S., EU and China have implemented targeted restrictions on quantum-enabling hardware, software, and communications systems.

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For years, quantum computing has been the tech world’s version of “almost there”. But now, engineers at MIT have pulled off something that might change the game. They’ve made a critical leap in quantum error correction, bringing us one step closer to reliable, real-world quantum computers.

In a traditional computer, everything runs on bits —zeroes and ones that flip on and off like tiny digital switches. Quantum computers, on the other hand, use qubits. These are bizarre little things that can be both 0 and 1 at the same time, thanks to a quantum property called superposition. They’re also capable of entanglement, meaning one qubit can instantly influence another, even at a distance.

All this weirdness gives quantum computers enormous potential power. They could solve problems in seconds that might take today’s fastest supercomputers years. Think of it like having thousands of parallel universes doing your math homework at once. But there’s a catch.

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RIKEN chemists have hit upon a fast and easy way to combine so-called nanobelts of carbon with sulfur-containing functional groups. The work is published in the journal Nature Communications.

This new material has intriguing properties that make it promising for use in novel optoelectronic devices.

Ever since their discovery in 1991, carbon nanotubes—tiny hollow cylinders made entirely from carbon atoms—have been attracting a lot of interest, being used in applications ranging from electronics to medicine.

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Introduction One thing newcomers to machine learning (ML) and many experienced practitioners often don’t realize is that ML doesn’t extrapolate. After training an ML model on compounds with µM potency, people frequently ask why none of the molecules they designed were predicted to have nM potency. If you’re new to drug discovery, 1nM = 0.001µM. A lower potency value is usually better. It’s important to remember that a model can only predict values within the range of the training set. If we’ve trained a model on compounds with IC50s between 5 and 100 µM, the model won’t be able to predict an IC50 of 0.1 µM. I’d like to illustrate this with a simple example. As always, all the code that accompanies this post is available on GitHub.

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Digger wasps make a short burrow for each egg, stocking it with food and returning a few days later to provide more. A new study reveals that mother wasps can remember the locations of up to nine separate nests at once, rarely making mistakes, despite the fact nests are dug in bare sand containing hundreds belonging to other females.

The paper is published in the journal Current Biology and is titled “Memory and the scheduling of parental care in an in the wild.”

Mothers feed their young in age order, adjusting the order if one dies, and they can even delay feeding offspring that had more food at the first visit. Their intricate scheduling reduces the chance that offspring starve.

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Ferroelectrics are a class of materials that exhibit so-called spontaneous electric polarization, which is the separation of electric charges that can be reversed when an external electric field is applied to them. The dipole moments (i.e., pairs of equal and opposite charges) in these materials can sometimes be arranged in complex configurations known as topological textures.

The topological structures of some ferroelectric materials can interact with light in interesting and unexpected ways, which could have interesting implications for the development of optical technologies and . The size of ferroelectric polar topologies unveiled and studied to date, however, is not aligned with that of laser light modes, which limited their previous use for the development of optical technologies.

Researchers at Nanjing University recently realized a micrometer-scale center-convergent ferroelectric topology using barium titanate (BaTiO3) membranes that enables the precise spatial control of light fields.

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A team from the University of Science and Technology of China (USTC) of the Chinese Academy of Sciences (CAS) has resolved a critical challenge in pure-red perovskite light-emitting diodes (PeLEDs) by identifying and addressing the root cause of efficiency loss at high brightness.

Published in Nature, their study introduces a novel material design that enables record-breaking device performance, achieving a peak external quantum efficiency (EQE) of 24.2% and a maximum luminance of 24,600 cd m-2 —the brightest pure-red PeLED reported to date.

Pure-red PeLEDs, crucial for vivid displays and lighting, have long faced a trade-off between efficiency and brightness. While 3D mixed-halide perovskites like CsPbI3-x Brx offer excellent charge transport, their efficiency plummets under high current due to unresolved carrier leakage.

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