The three-dimensional world of ordinary experience—the universe filled with galaxies, stars, planets, houses, boulders, and ...

Scientists published the Cascaded Variational Quantum Eigensolver (CVQE) algorithm in a recent article, expected to become a powerful tool to investigate the physical properties in electronic systems.

based on variational quantum algorithms, significantly reduces the computational complexity of parameter updates through deep optimization of the core circuit. It also incorporates innovative ...

In supervised, unsupervised, and reinforcement learning domains, quantum processors show potential to accelerate AI model ...

A team of researchers led by Yumin Dong of Chongqing Normal University has developed a novel method to optimize parametric quantum circuits, a critical component of variational quantum algorithms.

As quantum computing hardware advances, the demand for scalable, precise, and fully automated verification techniques for ...

In this work, we present a Clifford-based Hamiltonian engineering algorithm, namely CHEM, that addresses the trade-off between circuit depth and accuracy. Based on variational quantum eigensolver and ...

The CVQE algorithm is a variant of the Variational Quantum Eigensolver (VQE) algorithm that only requires the execution of a set of quantum circuits once rather than at every iteration during the ...

In terms of circuit design, the technology adopts ... In the training process of classifiers based on variational quantum algorithms (VQA), parameter optimization is one of the most critical ...