By remotely accessing an IBM quantum computer, a research scientist at Lawrence Berkeley National Laboratory has successfully ...

Abstract: Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for ...

Classiq and Pontificia Universidad Católica de Chile (UC Chile) have announced a joint research project to develop hybrid quantum algorithms for biomedical image analysis – assisted by classical ...

Conducted through Hatch’s Dimension X open innovation challenge for the Singapore Home Team, the project used Classiq’s quantum software platform, AWS infrastructure for classical high-performance ...

Abstract: Hybrid quantum-classical algorithms, such as variational quantum algorithms (VQAs), are suitable for implementation on noisy intermediate-scale quantum computers. In this article, we expand ...

Although the potential applications of quantum computing are widespread, a new feasibility study suggests quantum computers still face major hurdles in solving quantum chemistry problems. The study, ...

Quantum machine learning (QML) is an emerging research field that deals with quantum algorithms for data analysis. It is hoped that QML will yield practical demonstrations of quantum advantage by ...

Accurate diagnostics form the foundation of effective medical treatment. Though highly developed, current diagnostic methods face limitations in processing the vast amount of patient-specific data ...

A curated list of recent textbooks, reviews, perspectives, and research papers related to quantum machine learning, variational quantum algorithms, tensor networks, and classical machine learning ...