Sequential Markowitz model + doc

[bqth29]

PR decription

Following the discussion in #17, the Markowitz API has been enhanced with a new sequential model that allow an optimization of the portfolio relying among others on rebalancing costs which couple the timestamps together:

$$\hbox{argmax } \sum{t = 1}^{T} w{t}^{T} \mu{t} - \frac{\gamma}{2} w{t}^{T} \Sigma{t} w{t} - \Delta w_t^T \Lambda_t \Delta w_t$$

This model is implemented as the SequentialMarkowitz class of the simulated_bifurcation.models module.

New features

• The SequentialMarkowitz model has been added to the models pool (simulated_bifurcation.models module)
• It is now possible to create optimization models without explicitly importing the simulated_bifurcation.models module

import simulated_bifurcation as sb

qubo = sb.models.QUBO()

• Minor fixes on the Markowitz class
• Unit tests have been added to cover the optimization models
• Other minor fixes
• Improved docstrings

[codecov[bot]]

Codecov Report

All modified lines are covered by tests :white_check_mark:

Files	Coverage Δ
src/simulated_bifurcation/__init__.py	100.00% <100.00%> (ø)
src/simulated_bifurcation/ising_core.py	100.00% <100.00%> (ø)
src/simulated_bifurcation/models/__init__.py	100.00% <100.00%> (ø)
src/simulated_bifurcation/models/markowitz.py	100.00% <100.00%> (ø)
...ation/optimizer/simulated_bifurcation_optimizer.py	100.00% <100.00%> (ø)
src/simulated_bifurcation/optimizer/stop_window.py	100.00% <100.00%> (ø)
...ted_bifurcation/optimizer/symplectic_integrator.py	100.00% <100.00%> (ø)
src/simulated_bifurcation/polynomial/__init__.py	100.00% <100.00%> (ø)
...ulated_bifurcation/polynomial/binary_polynomial.py	100.00% <100.00%> (ø)
...lated_bifurcation/polynomial/integer_polynomial.py	100.00% <100.00%> (ø)
... and 20 more

... and 3 files with indirect coverage changes

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