Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

BRANFORD, Conn.--(BUSINESS WIRE)--Quantum-Si Incorporated (Nasdaq: QSI) (“Quantum-Si,” “QSI” or the “Company”), a proteomics technology company redefining ...

Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning. The appeal of quantum machine learning lies in its potential to tackle problems ...

Artificial intelligence (AI) has become integral to our daily lives, from virtual assistants like Siri to personalized recommendations on Netflix. As AI technology advances, quantum machine learning ...

Catalysts play an indispensable role in modern manufacturing. More than 80% of all manufactured products, from pharmaceuticals to plastics, rely on catalytic processes at some stage of production.

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 ...

(Top left) Composition of the universe, showing that dark matter accounts for about 27%. (Top right) Proposed quantum sensor network, where superconducting qubits are connected in different graph ...