SQuADDS: A validated design database and simulation workflow for superconducting qubit design
- URL: http://arxiv.org/abs/2312.13483v3
- Date: Thu, 5 Sep 2024 21:16:05 GMT
- Title: SQuADDS: A validated design database and simulation workflow for superconducting qubit design
- Authors: Sadman Shanto, Andre Kuo, Clark Miyamoto, Haimeng Zhang, Vivek Maurya, Evangelos Vlachos, Malida Hecht, Chung Wa Shum, Eli Levenson-Falk,
- Abstract summary: We present an open-source database of superconducting device designs that may be used as starting point for customized quantum solvers.
We present a robust for achieving high accuracy on design simulations.
Our database includes a front-end interface that allows users to generate bestguess'' designs based on desired circuit parameters.
- Score: 2.394350905741035
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
Related papers
- Machine Learning for Arbitrary Single-Qubit Rotations on an Embedded Device [1.3753825907341728]
We present a technique for using machine learning (ML) for single-qubit gate synthesis on field programmable logic.
We first bootstrap a model based on simulation with access to the full statevector for measuring gate fidelity.
We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements.
arXiv Detail & Related papers (2024-11-20T04:59:38Z) - Mechanistic Design and Scaling of Hybrid Architectures [114.3129802943915]
We identify and test new hybrid architectures constructed from a variety of computational primitives.
We experimentally validate the resulting architectures via an extensive compute-optimal and a new state-optimal scaling law analysis.
We find MAD synthetics to correlate with compute-optimal perplexity, enabling accurate evaluation of new architectures.
arXiv Detail & Related papers (2024-03-26T16:33:12Z) - Quantum Computing Enhanced Service Ecosystem for Simulation in Manufacturing [56.61654656648898]
We propose a framework for a quantum computing-enhanced service ecosystem for simulation in manufacturing.
We analyse two high-value use cases with the aim of a quantitative evaluation of these new computing paradigms for industrially-relevant settings.
arXiv Detail & Related papers (2024-01-19T11:04:14Z) - CktGNN: Circuit Graph Neural Network for Electronic Design Automation [67.29634073660239]
This paper presents a Circuit Graph Neural Network (CktGNN) that simultaneously automates the circuit topology generation and device sizing.
We introduce Open Circuit Benchmark (OCB), an open-sourced dataset that contains $10$K distinct operational amplifiers.
Our work paves the way toward a learning-based open-sourced design automation for analog circuits.
arXiv Detail & Related papers (2023-08-31T02:20:25Z) - Tailoring potentials by simulation-aided design of gate layouts for spin
qubit applications [0.4276883312743397]
Gate-s of spin qubit devices are commonly adapted from previous successful devices.
We present a general approach for electrostatically modelling new spin qubit device layouts.
arXiv Detail & Related papers (2023-03-23T15:36:32Z) - Design Space Exploration and Explanation via Conditional Variational
Autoencoders in Meta-model-based Conceptual Design of Pedestrian Bridges [52.77024349608834]
This paper provides a performance-driven design exploration framework to augment the human designer through a Conditional Variational Autoencoder (CVAE)
The CVAE is trained on 18'000 synthetically generated instances of a pedestrian bridge in Switzerland.
arXiv Detail & Related papers (2022-11-29T17:28:31Z) - QuaSiMo: A Composable Library to Program Hybrid Workflows for Quantum
Simulation [48.341084094844746]
We present a composable design scheme for the development of hybrid quantum/classical algorithms and for applications of quantum simulation.
We implement our design scheme using the hardware-agnostic programming language QCOR into the QuaSiMo library.
arXiv Detail & Related papers (2021-05-17T16:17:57Z) - Composable Programming of Hybrid Workflows for Quantum Simulation [48.341084094844746]
We present a composable design scheme for the development of hybrid quantum/classical algorithms and for applications of quantum simulation.
We implement our design scheme using the hardware-agnostic programming language QCOR into the QuaSiMo library.
arXiv Detail & Related papers (2021-01-20T14:20:14Z) - Quantum Circuit Design Search [0.0]
This article explores search strategies for the design of parameterized quantum circuits.
We propose several optimization approaches including random search plus survival of the fittest.
We introduce nontrivial circuit architectures that are arduous to be hand-designed and efficient in terms of trainability.
arXiv Detail & Related papers (2020-12-07T20:41:57Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.