As we talked about a decade ago in the wake of launching The Next Platform, quantum computers – at least the fault tolerant ...

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

Quantum researchers have deployed a new algorithm to manage noise in qubits in real time. The method can be applied to a wide ...

He calls the back and forth between the quantum- and classical-computing communities a “symbiotic relationship,” in which the two sides challenge each other by developing ever-more sophisticated ...

Today’s digital security relies on one fragile truth: that breaking today’s encryption standards, using tools available today ...

To address these issues, MicroAlgo has proposed a hybrid algorithm that combines the stability of classical computers with the efficiency of quantum computers.

The introduction of MicroAlgo's Classical Boosted Quantum Optimization Algorithm (CBQOA) marks the dawn of a new era in the fusion of quantum and classical computing for optimization.

Quantum machine learning (QML) combines quantum computing principles with artificial intelligence to solve problems that classical algorithms struggle to address.

A classical algorithm runs on conventional computers akin to laptops and smartphones, which process information as bits—like on/off switches representing 0s and 1s.

Seeking to reduce the computing power needed for the widely used dynamic mode decomposition algorithm, a team of researchers in China led by Guo-Ping Guo developed a quantum-classical hybrid ...

A few times, researchers thought they’d done it, discovering quantum algorithms that could solve problems faster than anything a classical computer could do. But then someone — often the young ...

The reliable engineering of quantum states, particularly those involving several particles, is central to the development of ...