Researchers utilize classical shadows and quantum subspace expansion to analyze a complex spin model, reducing measurement ...

A new quantum algorithm, mirror subspace diagonalization (MSD), achieves near-optimal sampling cost for real-time evolution, ...

MIT researchers used a specialized self-attention neural network to solve complex equations related to quantum particles, confirming the existence of anti-Pfaffian topological states. This ...

The quantum kernel method, a promising quantum machine learning algorithm, possesses substantial potential for demonstrating a quantum advantage. While most quantum kernels are constructed in the ...

In quantum mechanics, observables such as energy and momentum are represented by operators.In finite-dimensional matrix ...