Quantum computers that were previously limited to theoretical physics now learn to discover patterns, optimize decisions and ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

QNNs achieved 95 percent accuracy, while QSVMs reached 94 percent, both surpassing classical machine learning methods, which ...

A device made from superconducting qubits could prove a powerful technology for enabling practical quantum computing or more ...

Day,” when quantum computers can break today’s encryption—possibly by 2030—posing risks for crypto, security, and finance.

Quantum computers promise enormous computational power, but the nature of quantum states makes computation and data ...

During the second quarter of 2025, Quantum Computing Inc. (QUBT), or QCi, sold its EmuCore reservoir computing device to a major global automotive manufacturer. Built on a field-programmable gate ...

This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...

COLLEGE PARK, Md.--(BUSINESS WIRE)--IonQ (NYSE: IONQ), a leader in the quantum computing industry, today announced the launch of its new Faculty & Researcher Learning Series in partnership with South ...

The race against Q-Day has begun, and success will require not just technical innovation, but the wisdom to learn from each ...