* Add comment regarding meaning of '*' operator with sparse matrices

* Implement sparse dot product in numba

* Overload T attribute in numba sparse matrices

* Implement toarray

* Add tocsr

Co-authored-by: Jesse Grabowski <48652735+jessegrabowski@users.noreply.github.com>

Co-authored-by: Jesse Grabowski <48652735+jessegrabowski@users.noreply.github.com>

Co-authored-by: Adrian Seyboldt <aseyboldt@users.noreply.github.com>
Co-authored-by: Jesse Grabowski <48652735+jessegrabowski@users.noreply.github.com>

2304 -> 288

* Handle static shape
* Rename to more readable Op classes
* Simplify perform

Add Schur decomposition Op

Co-authored-by: Jesse Grabowski <48652735+jessegrabowski@users.noreply.github.com>

Co-authored-by: Jesse Grabowski <48652735+jessegrabowski@users.noreply.github.com>

* More precise imports

* Fix gradient of `minimize` and `root` wrt higher-dimensional arguments

Also:
* Allow several inputs to be optimized
* Handle disconnected and undefined gradients

---------
Co-authored-by: ricardoV94 <ricardo.vieira1994@gmail.com>

Mainly, joining 0 axes is equivalent to inserting a new dimension. This is the mirror of how splitting a single axis into an empty shape is equivalent to squeezing it.

Also:
* Allow default `None` on unpack

Due to https://github.com/scipy/scipy/issues/24345

Remove cases where type-hints are better than bad type-hints