Simcats

- Added a new parameter sampler: ExponentialSamplingRange
- NormalSamplingRange now allows to set a specific mean value instead of always using the center of the range.
- Updated the readme:
- Added a logo.
- Added a link to our publication in IEEE TQE: [doi.org/10.1109/TQE.2024.3445967](https://doi.org/10.1109/TQE.2024.3445967).
- Added instructions for citing our work.

Please have a look at the documentation on [ReadTheDocs](https://simcats.readthedocs.io/)

Changes:
- Updated `readme`.
- `tct_bezier` no longer initializes the implicit function (with `sympy`) if lookup table entries (`lut_entries`) are defined. This leads to a significant speedup (reduced simulation time by at least 50%).
- Fixed bug in `OccupationDotJumps`: Using `freeze=True` with no previous noise (=deactivated), led to an exception because the object tried to use the non-existent previous noise.
- Fixed bug in `OccupationDotJumps`: If the resolution is not the same for both gates of the CSD and new values outside the current range must be generated for jumps (to be shifted into the image range), the wrong shape was used causing an exception.
- Added a new implementation of the `ParameterSamplingInterface`: `LogNormalSamplingRange`.
- Fixed `NormalSamplingRange` cut-off: Previously, this sampler returned the min/max range values for all values outside the `sampling_range` limits instead of resampling.
- The function `ideal_csd_geometric` is now included in the documentation.

Please have a look at the documentation on [ReadTheDocs](https://simcats.readthedocs.io/)

First publicly available version of Simulation of CSDs for Automated Tuning Solutions (SimCATS).

It is a python framework for simulating charge stability diagrams (CSDs) typically measured during the tuning process of qubits.

Please have a look at the documentation on [ReadTheDocs](https://simcats.readthedocs.io/)