In recent decades, structural health monitoring (SHM) has gained increased importance for
ensuring the sustainability and serviceability of large and complex structures. To design an …

A fault-tolerant circuit is required for robust quantum computing in the presence of noise.
Clifford+ T circuits are widely used in fault-tolerant implementations. As a result, reducing T …

An elegant quantum version of least-square support vector machine, which is exponentially
faster than the classical counterpart, was given by Rebentrost et al. using the matrix …

The minimum vertex cover problem belongs to a NP-complete problem, which is difficult to
obtain the near-optimal solution in the polynomial time range using classical algorithms. In …

Quantum federated learning (QFL) enables collaborative training of a quantum machine
learning (QML) model among multiple clients possessing quantum computing capabilities …

Electrically tunable metasurfaces can realize two-dimensional pixelated spatial light
modulation and have a wide range of applications in optical switching, free-space …

Metasurface has attracted massive interest owing to its ability to control light arbitrarily in a
wide range of applications, such as high-speed imaging, optical interconnection, and …

The gradient descent approach is the key ingredient in variational quantum algorithms and
machine learning tasks, which is an optimization algorithm for finding a local minimum of an …

Different from the concept of universal computation, the universality of a quantum neural
network focuses on the ability to approximate arbitrary functions and is an important …

Combinatorial optimization has wide and high-value applications in many fields of science
and industry, but solving general combinatorial optimization problems is non-deterministic …