Science

Researchers have demonstrated a practical implementation of Berry’s phase – a key concept in quantum mechanics – using passive optical elements and a photonic quantum processor.

Researchers demonstrate a novel approach to quantum energy storage by strategically engineering dissipation to unlock faster charging and enhanced efficiency.

A new framework clarifies how we can infer past quantum states based on present measurements, while respecting fundamental uncertainty principles.

A new theoretical result shows that strategically ‘shaking’ a quantum probe enhances its ability to measure temperature, offering a path to more precise thermal sensing.

Researchers have combined the strengths of quantum computing and classical algorithms to tackle complex integer linear programs, potentially unlocking faster and more efficient solutions.

New research details the experimental realization of confined quantum walks on a chip, offering insights into how noise and spatial constraints affect quantum evolution.

A novel approach leveraging Entropic Dynamics reconstructs the foundations of Quantum Electrodynamics, offering a fresh perspective on its underlying principles.

New research establishes theoretical performance guarantees for quantum neural estimators, paving the way for more efficient quantum machine learning algorithms.

Researchers have developed a novel machine learning framework that leverages hypercausal reasoning and quantum-inspired principles to maintain performance in constantly evolving environments.

Researchers have successfully used programmable quantum annealers to model antiferromagnetic hysteresis, opening new avenues for exploring complex magnetic phenomena.