SQuADDS: A validated design database and simulation workflow for superconducting qubit design

  1. Sadman Shanto,
  2. Andre Kuo,
  3. Clark Miyamoto,
  4. Haimeng Zhang,
  5. Vivek Maurya,
  6. Evangelos Vlachos,
  7. Malida Hecht,
  8. Chung Wa Shum,
  9. and Eli Levenson-Falk
We present an open-source database of superconducting quantum device designs that may be used as the starting point for customized devices. Each design can be generated programmatically
using the open-source Qiskit Metal package, and simulated using finite-element electromagnetic solvers. We present a robust workflow for achieving high accuracy on design simulations. Many designs in the database are experimentally validated, showing excellent agreement between simulated and measured parameters. Our database includes a front-end interface that allows users to generate „best-guess“ designs based on desired circuit parameters. This project lowers the barrier to entry for research groups seeking to make a new class of devices by providing them a well-characterized starting point from which to refine their designs.

Modeling low- and high-frequency noise in transmon qubits with resource-efficient measurement

  1. Vinay Tripathi,
  2. Huo Chen,
  3. Eli Levenson-Falk,
  4. and Daniel A. Lidar
Transmon qubits experience open system effects that manifest as noise at a broad range of frequencies. We present a model of these effects using the Redfield master equation with a
hybrid bath consisting of low and high-frequency components. We use two-level fluctuators to simulate 1/f-like noise behavior, which is a dominant source of decoherence for superconducting qubits. By measuring quantum state fidelity under free evolution with and without dynamical decoupling (DD), we can fit the low- and high-frequency noise parameters in our model. We train and test our model using experiments on quantum devices available through IBM quantum experience. Our model accurately predicts the fidelity decay of random initial states, including the effect of DD pulse sequences. We compare our model with two simpler models and confirm the importance of including both high-frequency and 1/f noise in order to accurately predict transmon behavior.