API reference

The package has two halves: the physics in dbac, and the plotting in dbac.plotting. The physics modules never import matplotlib.

If you are new to the package, the guide explains each module with runnable examples. These pages list every public function and its arguments.

module	what it is for	guide
dbac.utils	building initial states, fidelity, noise	States and conventions
dbac.dme	density matrix exponentiation, four implementations	Density matrix exponentiation
dbac.dbqite	one DBAC step, the Hamiltonian	One DBAC step
dbac.gci	running several steps, reading the results	Running the recursion
dbac.hbac	heat-bath algorithmic cooling, for comparison	HBAC baseline
dbac.plotting	every figure: cooling curves, circuits, Bloch sphere, PTMs	Plotting

How the pieces fit together

A typical calculation touches the modules in this order:

1. dbac.utils.rx_sweep builds the initial states;

2. dbac.dbqite.QITE_dme_select_M makes a DBAC step function, which uses DME internally;

3. dbac.gci.GCI runs that step \(k\) times and records energy and fidelity;

4. dbac.plotting draws the result.

import numpy as np
from dbac.utils import rx_sweep
from dbac.dbqite import QITE_dme_select_M
from dbac.gci import GCI

psi = rx_sweep([0.5])[0]                                    # 1. initial state
step = QITE_dme_select_M(1)                                 # 2. step with M = 1
results = GCI(step, psi, None, [np.pi / 4] * 2).execute_gci()  # 3. k = 2 steps
print(results[-1])                                          # fidelity after 0, 1, 2 steps