A extension of entropy lab for persistent storage of calibration parameters of a quantum processing unit (QPU).
Project description
Entropy QPU DB
Background
The entropy QPU DB is an extension designed to make it easy to calibrate and manage experimentation of quantum processing units. It provides two abilites:
-
to run automated calibrations of all parameters related to the qubits, couplers and readout elements that make up a QPU, using calibration graphs, as inspired by Google's Optimus method.
-
to store the calibration data in a persistent storage DB, and integrate that DB into the calibration framework.
One of the challenges of bringing up a QPU from "scratch" is that it's not always straightforward to understand which calibrations need to be, at what order and with which parameters. On the other hand, QPUs contain many parameters which require calibration and tracking, which makes automated tools essential for this task.
This means that the process of building the calibration graph for a QPU needs to be needs to be both flexible and powerful. The QPU DB is designed to allow to do just that.
Getting started
This package requires having entropy installed, which can be obtained from pipy here.
To get started, check out the tutorials under docs/
.
Contact info
The QPU DB was conceived and developed by Lior Ella, Gal Winer, Ilan Mitnikov and Yonatan Cohen, and is maintained by Guy Kerem. For any questions, suggestions or otherwise - please contact us on our discord server!
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