Circuits

Kinetic-inductance-incorporated quantization for accurate Hamiltonian prediction in superconducting circuits

• Abstract We propose an improved method for quantizing superconducting circuits that incorporates material- and geometry-dependent kinetic inductance • Our approach models thin su

Learning parameterized quantum circuits with quantum gradient

• Abstract Parameterized quantum circuits (PQCs) are crucial for quantum machine learning and circuit synthesis, enabling the practical implementation of complex quantum tasks • Ho