Generate matrices (in the n, l, j, mj basis) with system/hamiltonians/hamiltonians.py.
Running the file will generate the mat_1, mat_2, mat_2_minus, and mat_2_plus matrices and save them into
the system/hamiltonians/generated_hamiltonians folder.
These matrices are saved as a single (combined) npz file.
The load_hamiltonian() function provides an interface for loading the matrices from the npz file.
The information required for basis transformation is generated with
system/transformations/transformation_generator.py.
This is done with nljmj_to_nlmlms() and nlmlms_to_n1n2mlms().
No other transformations are supported at this time.
system.states.States enable the generation of basis states in the following basis:
Basis.N_L_J_MJBasis.N_L_ML_MSBasis.N1_N2_ML_MS
- Generate Hamiltonian matrices with
system/hamiltonians/hamiltonians.py - Generate basis transformation matrices with
system/transformations/transformation_generator.py
Energy against ml is plotted with plots/ladder.py. This plot is interactive, and clicking on the figure prints
information about the state clicked on.
Eigenvalues across an ARP protocol is plotted with plots/eigenvalues_across_protocol.py.
Because pathlib and typing is used, this requires Python >=3.5.
A higher version of Python may be required due to changes in the library interfaces.
Development was done with Python 3.8.3.
The following command should include all necessary packages:
pip install numpy scipy matplotlib ARC-Alkali-Rydberg-Calculator qutip tqdm
- Reduce optimisation parameters:
- Switch off B field, fix rf_freq = 230 MHz
- 3 time slices instead of 4 per control
- Use default ml = 2
- Use 1ms duration
- Refactor: Move conversion of mat_2_plus and mat_2_minus to GHz into hamiltonian.py, to mirror mat_1 and mat_2.
- Rename rf_energy to rf_field
- Rename Simulation.t to t_p
- Add option to limit sigma plus and minus to be selective on n1
- Look at m_s taking + and - instead of discarding negatives
- Use either s=0 or 1 for Sr
- Add B field to top panel of plot.