Scalib

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* Build with the NTL dependency enabled for the linux CI.
* Change CI build to require x86-64-v3 instead of just AVX2. This is roughly
equivalent in terms of supported CPUs, but allows more instructions to be
used.
* Support numpy 2.
* Raise minimum supported python version to 3.10.
* Added a new histogram-based ranking method called 'scaledhist'.
This method enables correct FFT convolutions using scaled
histograms and improves precision by incorporating upper and lower histograms (184).
* In ``BPState``, add a `vars` parameter to ``propagate_factor`` and a
``factors`` pararameter to ``propagate_var`` (190).
* In ``BPState``, deprecate ``set_distribution``, replace by ``drop_distribution`` (190).
* Add ``LdaAcc`` and ``Lda`` classes: more efficient multi-variable LDA, with API separation between fit and prediction steps (192).
* Deprecate ``LdaClassifier`` and ``MultiLda`` (192)

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* **Breaking** change parameter names ``l`` to ``traces`` for many functions.
* **Breaking** remove unnecessary parameters from initializers (e.g. trace
length where it can be inferred).
* Fix misc. SASCA bugs with PUB, additions, generic factors

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* Add ``scalib.preprocessing.Quantizer`` for conversions of floating-point
traces to int.
* Support modular subtractions (generalized summation) in FactorGraph.
* Raise minimum supported python version to 3.9.

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* ``scalib.attacks.FactorGraph``:

* Add ``GENERIC`` factors

* Add clear beliefs flag for BP.

* Remove divisions in belief propagation (improves numerical robustness, fixes some NaN issues).

* Support python 3.12 in releases.

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* Add ``scalib.modeling.RLDAClassifier`` and ``scalib.metrics.RLDAInformationEstimator``.
* Fix build dependences and run build in an isolated environment.

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* Fix ``Distribution`` size bug in belief propagation computation (102).
* Do not include debug symbols in release builds (makes wheel much smaller).
* ``Ttest``: do not crash on non-contiguous/fortran-order arrays
* Improve examples and README