Skip to main content

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:

  1. 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.

  2. 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!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

entropylab-qpudb-0.0.10.tar.gz (12.6 kB view details)

Uploaded Source

Built Distribution

entropylab_qpudb-0.0.10-py3-none-any.whl (13.2 kB view details)

Uploaded Python 3

File details

Details for the file entropylab-qpudb-0.0.10.tar.gz.

File metadata

  • Download URL: entropylab-qpudb-0.0.10.tar.gz
  • Upload date:
  • Size: 12.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10

File hashes

Hashes for entropylab-qpudb-0.0.10.tar.gz
Algorithm Hash digest
SHA256 376f305f22985465d40ffe1392d45064e657c393c576b0ae97e7cfd09e725ff7
MD5 34d3fe4228dedd3514207b4167ab3b1c
BLAKE2b-256 11a5efed202436d7e9474aa99ea8e133f8f739711bc9a502cb78681514191ab5

See more details on using hashes here.

File details

Details for the file entropylab_qpudb-0.0.10-py3-none-any.whl.

File metadata

  • Download URL: entropylab_qpudb-0.0.10-py3-none-any.whl
  • Upload date:
  • Size: 13.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10

File hashes

Hashes for entropylab_qpudb-0.0.10-py3-none-any.whl
Algorithm Hash digest
SHA256 138d5e8393b6b426413594fd9339f8523d678fe8d1cbbd3f2a18e616ceb6ed27
MD5 e9c6e0f2a2a7b0e77ae2c2128d075c99
BLAKE2b-256 77359096dbf13155d45905ba547ec82a5696a5b45c01bb74009ea271d2576b35

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page