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 ...

Silicon Quantum Computing ("SQC"), a leader in quantum computing and quantum machine learning, today announced the launch of Quantum Twins, an application-specific quantum simulator designed to ...

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 ...

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 ...

SQC's Founder and CEO, Michelle Simmons, said: "Quantum Twins represents a window into the quantum world that customers can use for materials discovery today. The enabler is that we can engineer ...

Quantum researchers from CSIRO, Australia's national science agency, have demonstrated the potential for quantum computing to significantly improve how we solve complex problems involving large ...

The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

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 ...

Overview  Quantum computing skills now influence hiring decisions across technology, finance, research, and national security sectors.Employers prefer cand ...