Quantum computer research is advancing at a rapid pace. Today's devices, however, still have significant limitations: For example, the length of a quantum computation is severely limited—that is, the ...

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as weather patterns, recorded speech or stock market trends. Classical ...

A team of scientists from Princeton University has measured the energies of electrons in a new class of quantum materials and has found them to follow a fractal pattern. Fractals are self-repeating ...

Duke Quantum Center researchers use a neutral-atom platform to simulate unusual localization effects that could underpin robust quantum information storage.

A sensitive matter-wave interferometer measuring moiré fringes offers force sensitivity comparable to quantum interference experiments.

To capture higher-definition and sharper images of cosmological objects, astronomers sometimes combine the data collected by ...

Where do you see patterns in chaos? It has been proven, in the incredibly tiny quantum realm, by an international team co-led by UC Santa Cruz physicist Jairo Velasco, Jr. In a new paper published on ...

The mystery of quantum phenomena inside materials—such as superconductivity, where electric current flows without energy loss—lies in when electrons move together and when they break apart. KAIST ...

Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially a ...

At the smallest scales of nature, the rules of the world shift in ways that can feel unsettling and beautiful at the same ...