3 papers
quant-ph2026
Component-Level Inverse Design of Transmon Qubits Using Neural Networks
Olivia Seidel, Firas Abouzahr, Abhishek Chakraborty +11
Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer ch…
quant-ph2026
QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding
Shuxiang Cao, Zijian Zhang, Abhishek Agarwal +29
Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representation for this task, yet no system…
quant-ph2025
Opportunities and Challenges of Computational Electromagnetics Methods for Superconducting Circuit Quantum Device Modeling: A Practical Review
Samuel T. Elkin, Ghazi Khan, Ebrahim Forati +5
High-fidelity numerical methods that model the physical layout of a device are essential for the design of many technologies. For methods that characterize electromagnetic effects,…