Quantum computer succeeds where a classical algorithm fails Quantum computers coupled with traditional machine learning show clear benefits.

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 ...

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.

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 ...

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 ...

The quest for "quantum supremacy"—unambiguous proof that a quantum computer does something faster than an ordinary computer—has paradoxically led to a boom in quasi-quantum classical algorithms.

Tang’s discovery of a powerful new machine-learning algorithm for classical computers upended assumptions about computing challenges that were thought to require quantum computers.

Instead of running the algorithm on advanced quantum processors, the new approach uses a classical machine-learning algorithm that closely mimics the behavior of near-term quantum computers.

Our classical algorithm, based on Metropolised independence sampling, allowed the boson sampling problem to be solved for 30 photons with standard computing hardware.