https://github.com/agnostiqhq/tutorials_covalent_qsite_2023
https://github.com/agnostiqhq/tutorials_covalent_qsite_2023
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/agnostiqhq/tutorials_covalent_qsite_2023
- Owner: AgnostiqHQ
- Created: 2023-10-03T13:24:59.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-03T13:57:33.000Z (about 2 years ago)
- Last Synced: 2025-01-18T03:26:09.597Z (9 months ago)
- Language: Jupyter Notebook
- Size: 3.7 MB
- Stars: 0
- Watchers: 7
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Covalent Tutorials - QSITE 2023
Covalent x Pennylane tutorial notebook for QSITE 2023 (at University of Toronto).
### Time Series Anomaly Detection with Quantum Variational Rewinding.
- See the original demo for Pennylane: [Quantum detection of time series anomalies](https://pennylane.ai/qml/demos/tutorial_univariate_qvr).
## Setup
Clone this repository and create the `conda` [environment](https://docs.anaconda.com/free/anaconda/install/index.html) from the `environment.yml` file:
```bash
git clone https://github.com/AgnostiqHQ/tutorials_covalent_qsite_2023.git
cd tutorials_variational_rewinding/quantum_variational_rewinding
conda env create -f environment.yml
conda activate QVR
```
Before dispatching to Covalent, make sure covalent is running
```bash
covalent start
```
Once you're finished, simply run
```bash
covalent stop
```
## 🔗 Links
- ⭐️ [Covalent GitHub](https://github.com/AgnostiqHQ/covalent) ⭐️
- 📺 [Covalent Slack Channel](https://join.slack.com/t/covalentworkflows/shared_invite/zt-22kwbb7k6-x88XLf_alvKP2z11viuVng)
- 📚 [Documentation](https://docs.covalent.xyz/docs/)
- 👩🏫 [Tutorials](https://docs.covalent.xyz/docs/user-documentation/tutorials/)
## References
- Baker, Jack S., et al. "Quantum Variational Rewinding for Time Series Anomaly Detection." arXiv preprint [arXiv:2210.16438](https://arxiv.org/abs/2210.16438) (2022).