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 ...

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 ...

Entanglement plays a crucial role in advancing quantum technologies and exploring quantum many-body simulations. Here, we introduce a protocol aided by neural networks for measuring entanglement in ...

Quantum algorithms have become a popular research domain in recent times for discovering quantum-enhanced solutions in machine learning applications. Quantum kernels are one of the directions that ...

For over a decade, researchers have considered boson sampling—a quantum computing protocol involving light particles—as a key milestone toward demonstrating the advantages of quantum methods over ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

Image courtesy by QUE.com The intersection of Quantum Computing (QC) and Artificial Intelligence (AI) represents one of the ...

Madras is continuing to expand its quantum research ecosystem. The institute's Mphasis Centre for Quantum Information, ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, has announced a groundbreaking achievement of great theoretical and engineering significance: its ...

Machine learning helped identify new superconductors and a process that could speed the discovery of thousands more ...

A Honeywell-backed (HON) company is aiming for one of the biggest public market tests yet for the quantum computing trade. Quantinuum is seeking to raise as much as $1.05 billion in its IPO, offering ...