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fix broken links
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dkweiss31 committed Oct 18, 2024
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -58,7 +58,7 @@ We are now ready to create an instance of the `FloquetAnalysis` class, and run t
floquet_analysis = ft.FloquetAnalysis(model, state_indices=state_indices)
data_vals = floquet_analysis.run()
```
`data_vals` is a dictionary containing all quantities computed during the call to `run()`. This includes the overlap with the "ideal" displaced state, which can be plotted to reveal "scars" in the drive frequency and amplitude space where resonances occur. This part of the analysis is based on [Xiao, Venkatraman et al, arXiv (2023)](https://arxiv.org/abs/2304.13656), see Appendices I and J. Additionally we perform a so-called branch analysis to understand which states are responsible for ionization, based on [Dumas et al, arXiv 2024](https://arxiv.org/abs/2402.06615). See the [demo](https://github.com/dkweiss31/floquet/blob/main/docs/examples/demo.ipynb) for more details on the analysis and how to plot and visualize the computed quantities.
`data_vals` is a dictionary containing all quantities computed during the call to `run()`. This includes the overlap with the "ideal" displaced state, which can be plotted to reveal "scars" in the drive frequency and amplitude space where resonances occur. This part of the analysis is based on [Xiao, Venkatraman et al, arXiv (2023)](https://arxiv.org/abs/2304.13656), see Appendices I and J. Additionally we perform a so-called branch analysis to understand which states are responsible for ionization, based on [Dumas et al, arXiv 2024](https://arxiv.org/abs/2402.06615). See the [demos](https://github.com/dkweiss31/floquet/blob/main/docs/examples) for example applications of the analysis, how to plot and visualize the computed quantities, etc.

## Citation

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2 changes: 1 addition & 1 deletion docs/index.md
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Expand Up @@ -51,7 +51,7 @@ options = ft.Options(num_cpus=6)
floquet_analysis = ft.FloquetAnalysis(model, state_indices=state_indices, options=options)
data_vals = floquet_analysis.run()
```
`data_vals` is a dictionary containing all quantities computed during the call to `run()`. This includes the overlap with the "ideal" displaced state, which can be plotted to reveal "scars" in the drive frequency and amplitude space where resonances occur. This part of the analysis is based on [Xiao, Venkatraman et al, arXiv (2023)](https://arxiv.org/abs/2304.13656), see Appendices I and J. Additionally we perform a so-called branch analysis to understand which states are responsible for ionization, based on [Dumas et al, arXiv 2024](https://arxiv.org/abs/2402.06615). See the tutorial notebook under Examples on the left for more details on the analysis and how to plot and visualize the computed quantities.
`data_vals` is a dictionary containing all quantities computed during the call to `run()`. This includes the overlap with the "ideal" displaced state, which can be plotted to reveal "scars" in the drive frequency and amplitude space where resonances occur. This part of the analysis is based on [Xiao, Venkatraman et al, arXiv (2023)](https://arxiv.org/abs/2304.13656), see Appendices I and J. Additionally we perform a so-called branch analysis to understand which states are responsible for ionization, based on [Dumas et al, arXiv 2024](https://arxiv.org/abs/2402.06615). See the tutorial notebooks under Examples on the left for example applications of the analysis, how to plot and visualize the computed quantities, etc.

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