Skip to main content

FiQCI Error Mitigation Service

Project description

FiQCI EMS

FiQCI Error Mitigation Service (EMS) is a python library for error mitigation as part of the Finnish Quantum Computing Infrastructure.

This python package can be pre-installed on a HPC system or installed by the user. The main goal of the project is to allow users using FiQCI quantum computers to easily add flags to run error mitigation levels. A user can specify mitigation levels 0, 1, 2 or 3.

Mitigation Level Mitigation Applied Techniques used
0 No Mitigation Applied None
1 Readout Error Mitigation M3
2 Level 1 +
3 Level 2 +

At a basic level the user does not need to do anything and mitigation level 1 is used which means readout error mitigation. At a medium level the user and specify different mitigation levels and at an advanced level the user can configure the error mitigation themselves e.g running Zero noise extrapolation but not gate twirling.

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

fiqci_ems-0.1.0.tar.gz (93.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fiqci_ems-0.1.0-py3-none-any.whl (12.5 kB view details)

Uploaded Python 3

File details

Details for the file fiqci_ems-0.1.0.tar.gz.

File metadata

  • Download URL: fiqci_ems-0.1.0.tar.gz
  • Upload date:
  • Size: 93.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for fiqci_ems-0.1.0.tar.gz
Algorithm Hash digest
SHA256 0a0e04c7cc470ec4b0624e5762f3e18655f4d73f9222041cc25903f2577a0893
MD5 f5048eba46b546de89aa8bc1bb31bc23
BLAKE2b-256 de3f61cb27dc26a36028dd72bd29a8867043108e8cd354ba486366acc4bed723

See more details on using hashes here.

File details

Details for the file fiqci_ems-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: fiqci_ems-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 12.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for fiqci_ems-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 041c3c219075b6225a4dbab9f070c3fdf0bb3f3fe69497422ff0a714b9e47c65
MD5 3f696b69f637514ad8e5a7b9e5188f0d
BLAKE2b-256 37786dad2fb1425ae43de0495ab33428c3e96d1a6f01172e9c9886417a794da9

See more details on using hashes here.

Supported by

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