Better interface to describe HSCA error generators

[sserita]

Is your feature request related to a problem? Please describe.
It is difficult to instantiate models with entire blocks of error generators, e.g. all weight-2 Hamiltonian and stochastic errors, and weight-1 correlated/active errors.

Describe the solution you'd like
I'd like it to be easy to specify error generators with different support, type, and weight, something like selecting blocks out of Fig 2 of the taxonomy paper.
Maybe an dict of strings constructor for LindbladCoefficientBlocks? With plumbing up into modelconstruction functions?

Describe alternatives you've considered
My current best is something like this:

import itertools
import numpy as np

import pygsti
from pygsti.baseobjs.basis import Basis as _Basis
import pygsti.modelmembers.operations as _ops
from pygsti.modelmembers.operations.lindbladcoefficients import LindbladCoefficientBlock as _LindbladCBlock

qubit_labels = ('Q0','Q1','Q2','Q3')
state_space = pygsti.baseobjs.QubitSpace(qubit_labels)

pspec = pygsti.processors.QubitProcessorSpec(4,
    ['Gxpi2', 'Gxmpi2', 'Gypi2', 'Gympi2', 'Gcphase'], qubit_labels=qubit_labels,
    availability={
        'Gxpi2': [(q,) for q in qubit_labels],
        'Gypi2': [(q,) for q in qubit_labels],
        'Gxmpi2': [(q,) for q in qubit_labels],
        'Gympi2': [(q,) for q in qubit_labels],
        'Gcphase': [('Q0', 'Q1'), ('Q1', 'Q2'), ('Q2', 'Q3')]
    })

ex_model = pygsti.models.create_explicit_model(pspec)

H2S2A1_model = ex_model.copy()
H2S2A1_model.operations.flags['auto_embed'] = False

pp_basis = _Basis.cast('pp', 4**4)
w1_lbls = [lbl for lbl in pp_basis.labels if sum([c != 'I' for c in lbl]) == 1]
w2_lbls = [lbl for lbl in pp_basis.labels if sum([c != 'I' for c in lbl]) == 2]

for lbl, op in H2S2A1_model.operations.items():

    errgen_dict = {}

    # Lindblad coefficient blocks
    H12_block = _LindbladCBlock('ham', pp_basis, w1_lbls + w2_lbls, param_mode='elements')
    
    S2_block = _LindbladCBlock('other_diagonal', pp_basis, w2_lbls, param_mode='cholesky')
    
    SCA1_block = _LindbladCBlock('other', pp_basis, w1_lbls, param_mode='cholesky')
    
    # Build op
    errgen = _ops.LindbladErrorgen([H12_block, S2_block, SCA1_block], state_space=state_space)
    
    H2S2A1_model.operations[lbl] = _ops.ComposedOp([
        _ops.StaticUnitaryOp(op),
        _ops.ExpErrorgenOp(errgen)
    ])

[sserita]

A half-baked version of this is implemented in the feature-cloudnoise-experimental branch for CloudNoiseModels.