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 ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

This quantum output was mixed with the original image data and analyzed using a simple linear classifier. This hybrid strategy maintained information while outperforming all similarly sized machine ...

IonQ plans to acquire Seed Innovations to add machine learning and cloud expertise to its quantum infrastructure business.

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 ...

New hybrid quantum applications show quantum computing’s ability to optimize materials science properties using Quantum-Enhanced Generative Adversarial Networks (QGANs) and fine-tune LLM models using ...

In their simulated system, image data is first simplified using a process called principal component analysis (PCA), which reduces the amount of information while preserving key features. A complex ...

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 ...

A team of researchers from the University of Chicago's Pritzker School of Molecular Engineering (UChicago PME) has used Quantum Machine Learning (QML) to identify cancer early.