One significant advantage of superconducting processors is their extensive design flexibility, which encompasses various types of qubits and interactions. Given the large number oftunable parameters of a processor, the ability to perform gradient optimization would be highly beneficial. Efficient backpropagation for gradient computation requires a tightly integrated software library, for which no open-source implementation is currently available. In this work, we introduce SuperGrad, a simulator that accelerates the design of superconducting quantum processors by incorporating gradient computation capabilities. SuperGrad offers a user-friendly interface for constructing Hamiltonians and computing both static and dynamic properties of composite systems. This differentiable simulation is valuable for a range of applications, including optimal control, design optimization, and experimental data fitting. In this paper, we demonstrate these applications through examples and code snippets.
Introducing disorderness in the superconducting materials has been considered promising to enhance the electromagnetic impedance and realize noise-resilient superconducting qubits.Despite a number of pioneering implementations, the understanding of the correlation between the material disorderness and the qubit coherence is still developing. Here, we demonstrate the first and a systematic characterization of fluxonium qubits with the superinductors made from titanium-aluminum-nitride with varied disorderness. From qubit noise spectroscopy, the flux noise and the dielectric loss are extracted as a measure of the coherence properties. Our results reveal that the 1/f flux noise dominates the qubit decoherence around the flux-frustration point, strongly correlated with the material disorderness; while the dielectric loss remains low under a wide range of material properties. From the flux-noise amplitudes, the areal density (σ) of the phenomenological spin defects and material disorderness are found to be approximately correlated by σ∝ρ3xx, or effectively (kFl)−3. This work has provided new insights on the origin of decoherence channels within superconductors, and could serve as a useful guideline for material design and optimization.