https://github.com/agnostiqhq/tutorials_covalent_ieee_2022
Tutorials for 2022 IEEE Quantum Week Workshop on Covalent
https://github.com/agnostiqhq/tutorials_covalent_ieee_2022
covalent-tutorial gqsim ieee ml qcw22 qml quantum-machine-learning siamese-network tutorial
Last synced: 5 months ago
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Tutorials for 2022 IEEE Quantum Week Workshop on Covalent
- Host: GitHub
- URL: https://github.com/agnostiqhq/tutorials_covalent_ieee_2022
- Owner: AgnostiqHQ
- Archived: true
- Created: 2022-08-08T18:15:22.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-08-14T23:08:56.000Z (about 2 years ago)
- Last Synced: 2025-03-25T07:01:50.726Z (7 months ago)
- Topics: covalent-tutorial, gqsim, ieee, ml, qcw22, qml, quantum-machine-learning, siamese-network, tutorial
- Language: Jupyter Notebook
- Homepage:
- Size: 14.1 MB
- Stars: 7
- Watchers: 11
- Forks: 1
- Open Issues: 12
-
Metadata Files:
- Readme: README.md
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README
# IEEE Quantum Week 2022: Covalent Workshop
This repository contains all the of the needed material to complete the `covalent` workshop hosted at IEEE Quantum Week 2022, Broomfield Colarado.
You will find:
1. The slides from the talk part of the workshop (`slides.pdf`)
2. Jupyter notebooks needed for the hands-on workshop (`workshop/machine_learning/similarity_learning.ipynb`)
3. `code_examples` contains several simple examples different features/aspects of Covalent
## Install instructions
To run the jupyter notebooks used in the hands-on workhsops, you will need a new `conda` environment with all of the dependices.
First, clone or download this repository to your local machine.
Next, if you don't already have conda, navigate to and install the correct version for your OS for either Miniconda or Anaconda.
In a terminal window, navigate to root directory of this repo (`~tutorials_covalent_ieee_2022`) and issue
`> conda env create -f environment.yml`
This will install the `ieee_covalent` environment. Let's activate it
`> conda activate ieee_covalent`
If you are confident with making this environment visible to your existing Jupyter Notebook viewer, you are done! If not, please continue with
`> python -m ipykernel install --user --name=ieee_covalent`
then issue
`> jupyter notebook &`
which will open a browser window in the Jupyter explorer. Navigate to the `*.ipynb` file you are interested in looking at within this repo and click it.
From the top drop-down menu, select `kernel > change kernel > ieee_covalent`. You are now good to go!
### Start Covalent
After successfully creating the conda environment, the Covalent server can be started as follows
```bash
covalent start --ignore-migrations
```
Covalent can optionally be started in debug mode for more verbose logging as follows
```bash
covalent start -d --ignore-migrations
```