Create test TestNonequilibriumCyclingProtocol that uses Gaussian random numbers to quickly generate analyzable test data

In order to test our workflows, we might want to implement a very fast Protocol that generates valid nonequilibrium cycling data with analytically known results and very fast execution times.

To do this, we can sample from two harmonic oscillators with a specific free energy difference and transformation difficulty (which arises from the stddev of work values).

We can use HarmonicOscillatorsTestCase from pymbar.testsystems to do this, using code like this:

    # Generate analytical samples
    >>> testcase = HarmonicOscillatorsTestCase(O_k=[0, 1], K_k=[1, 2])
    >>> w_F, w_R, N_k = testcase.sample(N_k=[40, 50], mode='wFwR')
    # Get true free energies
    >>> analytical_free_energies = testcase.analytical_free_energies()

To make sure the free energies are reproducible, we could extract the dimensionless harmonic oscillator centers (O_k) and spring constants (K_k) for each harmonic oscillator from the transformation inputs so that they are deterministic and depend on the inputs for each ligand.

Read pymbar/testsystems/harmonic_oscillators.py and trace the Protocol entry point used by the repository's workflows. Use HarmonicOscillatorsTestCase as the reference for generating valid nonequilibrium cycling data, with oscillator parameters derived deterministically from transformation inputs. Done means the new TestNonequilibriumCyclingProtocol produces fast, reproducible data with analytically known free energies.