Quantum Noise

Quantum noise, the inherent randomness and errors in quantum computations, is a major obstacle to realizing the full potential of quantum technologies. Current research focuses on mitigating noise through techniques like diffusion models, Bayesian inference, and neural network-based zero-noise extrapolation, often applied within variational quantum algorithms and quantum machine learning models. These efforts aim to improve the accuracy and reliability of quantum computations, impacting fields such as quantum sensing, optimization, and generative modeling by enabling more robust and efficient quantum algorithms. Ultimately, overcoming quantum noise is crucial for building practical and scalable quantum computers.