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Quantum mechanics theory may work without imaginary numbers, new analysis suggests

Physicists from Heinrich Heine University Düsseldorf (HHU) have examined a fundamental property of quantum mechanics in collaboration with the German Aerospace Center (DLR). In an article published in the journal Physical Review Letters, they show that this theory does not necessarily need to be formulated with imaginary numbers—real numbers can, in fact, also be used.

The physical theory of quantum mechanics describes the world of atomic and subatomic particles. Its development began in the 1900s with physicists such as Max Planck, Niels Bohr, Werner Heisenberg and Erwin Schrödinger.

Quantum mechanics can effectively describe phenomena at microscopic scales, including, for example, the diffraction of particles at a double slit —which shows that particles also exhibit wave-like behavior—and the quantum tunneling effect, in which a certain probability exists that particles can penetrate a barrier even if they have insufficient energy to do so. Particularly important phenomena today include entanglement and coherence, which are key for applications such as quantum computers and communication.

Faster aptamer screening finds synthetic alternatives to antibodies in days instead of months

Aptamers are short DNA or RNA strands that can recognize and bind to a specific target molecule with high precision. Similar to antibodies, they can be used to detect these molecules or modulate their activity. Unlike antibodies, they are much more stable, can be produced synthetically and can be chemically modified to achieve the desired properties. As a result, they can offer capabilities that cannot be achieved with antibodies.

As demand grows for accurate and rapid diagnostic tools, aptamers are often better suited to these applications than antibodies. However, developing aptamers is both experimentally demanding and time-consuming. A team of scientists from IOCB Prague, led by Dr. Marek Ondruš and Prof. Michal Hocek, has now developed a technology that significantly shortens the development process. Their research is published in the journal Nature Communications.

Driverless cars are on the rise and now we may know why they crash

For the first time, new algorithms may be able to automatically explain why some self-driving cars crash—a question crucial to answer as more autonomous vehicles take to the roads. This new approach, developed by researchers at King’s College London, reviews past events to explain why specific instances of failure happened, in the hope that this can be used to make improvements in the future.

The research was presented at the 2026 IEEE International Conference of Robotics and Automation.

Self-driving vehicles are increasingly being rolled out across the globe, in cities like London and San Francisco, but collisions and serious breaches of road safety have put pressure on manufacturers to explain why they make the mistakes they do. This is often hard to do, and current methods only provide limited explanations for these.

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