"Machine Learning in Quantum Sciences", outcome of a collaborative effort from world-leading experts, offers both an introduction to machine learning and deep neural networks, and an overview of their ...

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 ...

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 ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

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

What advancements can be made to quantum computers that will allow them to surpass traditional computers in performing difficult tasks like problem-solving? This is what a five-year, $5 million grant ...

Google has demonstrated a 13,000 times speedup for the Quantum Echoes algorithm using its Willow quantum chip. The feat is repeatable, according to the company, and it paves the way toward real-world ...

Quantum computing made significant strides in 2024, but it’s yet to demonstrate a practical advantage over classical digital computers, according to a recent trends report released by Forrester ...