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- update to 1.8.4:
  * support for numpy v2.0 and scipy v1.14
  * add MPS sampling: `MatrixProductState.sample_configuration`
    and `MatrixProductState.sample` (generating multiple samples)
    and use these for `CircuitMPS.sample` and
    `CircuitPermMPS.sample`.
  * add basic `.plot()` method for SimpleUpdate classes
  * add `edges_1d_chain` for generating 1D chain edges
  * operatorbuilder: better coefficient placement for long range
    MPO building
  * `TNOptimizer` can now accept an arbitrary pytree (nested
    combination of dicts, lists, tuples, etc. with
    `TensorNetwork`, `Tensor` or raw `array_like` objects as the
    leaves) as the target object to optimize.
  * `TNOptimizer` can now directly optimize `Circuit` objects,
    returning a new optimized circuit with updated parameters.
  * `Circuit`: add `.copy()`, `.get_params()` and `.set_params()`
    interface methods.
  * Update generic TN optimizer docs.
  * add `tn.gen_inds_loops` for generating all loops of indices
    in a TN.
  * add `tn.gen_inds_connected` for generating all connected sets
    of indices in a TN.
  * make SVD fallback error catching more generic ({pull}`#238`)
  * fix some windows + numba CI issues.
  * `approx_spectral_function` add plotting and tracking
  * add dispatching to various tensor primitives to allow
    overriding
  * `CircuitMPS` now supports multi qubit gates, including
    arbitrary multi-controls (which are treated in a low-rank

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Forwarded request #1152767 from bnavigator

- Update to 1.7.3
   ## Enhancements:
    * qu.randn: support dist="rademacher".
    * support dist and other randn options in various TN builders.
    ## Bug fixes:
    * restore fallback (to scipy.linalg.svd with driver='gesvd')
      behavior for truncated SVD with numpy backend.
  - Release 1.7.2
    ## Bug fixes:
    * removed import of deprecated numba.generated_jit decorator.
    ## Enhancements:
    * add normalized=True option to tensor_network_distance for
      computing the normalized distance between tensor networks,
      which is useful for convergence checks.
      Tensor.distance_normalized and
      TensorNetwork.distance_normalized added as aliases.
    * add TensorNetwork.cut_bond for cutting a bond index
  - Release v1.7.1
    ## Enhancements:
    * add TensorNetwork.visualize_tensors for visualizing the actual
      data entries of an entire tensor network.
    * add ham.build_mpo_propagator_trotterized for building a
      trotterized propagator from a local 1D hamiltonian. This also
      includes updates for creating 'empty' tensor networks using
      TensorNetwork.new, and building up gates from empty tensor
      networks using TensorNetwork.gate_inds_with_tn.
    * add more options to Tensor.expand_ind and Tensor.new_ind:
      repeat tiling mode and random padding mode.
    * tensor decomposition: make eigh_truncated backend agnostic.
    * tensor_compress_bond: add reduced="left" and reduced="right"

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- Numba now exists for Python 3.11, stop skipping it.

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- upgrade opt-einsum to requires as it is imported by tensor/
  unconditionally

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