Skip to main content

This library is designed to help data scientists easily conduct experiments with Quantum Neural Networks (QNNs) without the need to manually construct quantum circuits.

Project description

A PennyLane Based Quantum Programming Library Wrapper that allow Users to construct a Quantum Neural Networks based on ZZFeatureMap and Anstaz Twolocal at ease with flexibility to specify number of repss

##Usage

use Python 3.11.x only

#use virtual environment change python 3.x.x to 3.11.x
py -3.11 -m venv .venv
.venv\Scripts\Activate
# (.venv) PS D:\project>pip install qnnlib
# (.venv) PS D:\project>python ./test.py

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

qnnlib-0.1.6.tar.gz (8.8 kB view details)

Uploaded Source

File details

Details for the file qnnlib-0.1.6.tar.gz.

File metadata

  • Download URL: qnnlib-0.1.6.tar.gz
  • Upload date:
  • Size: 8.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.9

File hashes

Hashes for qnnlib-0.1.6.tar.gz
Algorithm Hash digest
SHA256 071062859b670f54dd4f5686e9f7b6e8ca275862b08a26e59b7c3654bbb97ee9
MD5 e268d9a04febd9fadba8c93fdc0df730
BLAKE2b-256 55ed94ec77f842a2808b687e5e24027afef4091870bbaa2492d49a34e755730f

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