Two hedge fund quants say they have built a machine learning model that—like humans—is able to learn broad ideas from small amounts of data. Kharen Musaelian and Dario Villani, co-founders of ...

Using a conventional computer and cutting-edge mathematical tools and code, physicists at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation's Flatiron Institute and ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...

BUFFALO, N.Y. — Imagine zooming into matter at the quantum scale, where tiny particles can interact in more than a trillion configurations at once. If that sounds complicated, it is: Physicists often ...

Predicting the behavior of many interacting quantum particles is a complicated process but is key to harness quantum computing for real-world applications. Researchers have developed a method for ...

Photo of the experimental setup to couple MWs to N- 𝑉⁢s using grape dimers. A stripped optical fiber with N- 𝑉 spins, cantilevered from a rod, lies between two grapes. The grapes were positioned on ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

Modern encryption relies on mathematical assumptions that quantum computers may soon render obsolete. This technological shift creates new ...