2024-large-deviation-full-counting-statistics-in-adiabatic-open-quantum-dynamics

Codes for reproducing the data and figures of the article entitled "Large Deviation Full Counting Statistics in Adiabatic Open Quantum Dynamics"

Authors: Paulo J. Paulino, Igor Lesanovsky, and Federico Carollo

Journal: Physical Review Letters, 05/2024

Arxiv: https://arxiv.org/abs/2401.11933

Basic Information about the Directories:

• The codes are organized in Jupyter notebooks, written in Python.
• The codes require NumPy, SciPy, QuTiP, and Matplotlib.

Folder Structure:

• Each notebook is self-contained, representing one part of the data.

• The "figures" folder contains a file .svg, where the figures were post-processed (adjusted font size, font style, legend size, etc.).

• Fig. 2

  1. The Jupyter notebook Fig2_AdiabaticDynamics.ipynb generates the data for Figure 2.
  2. The notebook Fig2_AdiabaticDynamics_NumericalCheck.ipynb checks the numerical results of Figure 2. The time-evolution of the biased density matrix can be unstable for large τ and s. This notebook employs a method that is slower but more robust against possible errors due to the stiffness of the differential equation.

• Fig. 3

  1. The Jupyter notebooks Fig3_Trajectory_Entropy.ipynb and Fig3_Trajectory_BlinkingSystem.ipynb generate the quantum trajectories for Figure 3.
  2. The notebook Fig3_RateFunctionMap_Entropy.ipynb and Fig3_RateFunctionMap_BlinkingSystem.ipynb generate the phase diagrams for the rate function depicted in Figure 3.
  3. The notebook Fig3_FiniteTau_Error.ipynb generates the data for estimating the error of the adiabatic approximation for the activity in function of $\gamma \tau$.

• Fig. SM

  1. The Jupyter notebook FigSM_RateFunctionMap_Activity.ipynb generates the rate function phase diagram for the Fig. in the SM.
  2. The Jupyter notebook FigSM_Trajectory_Activity.ipynb generate the quantum trajectory for the Fig. in the SM.

• Further checks

  1. The Jupyter notebooks with FigCheck contains some further checks we did for investigating heat flows in the system (These results are not in the publication).

• Plotting.

  1. The Jupyter notebooks Plotting_Fig2.ipynb, Plotting_Fig3.ipynb, and Plotting_FigSM.ipynb read the generated data and plot them.

• Figs editing

  1. The figures are post processed in the .svg file in the folder "Figures".