bbm92-cw
Release 0.0.2

BBM92_CW

This project is an implementation of the model laid out in [1].

The model treats a Continuous Wave (CW) source of photon pairs that are perfectly correlated in time, and formalises what the expected asymptotic secure key rate (AKR) is if you use them to perform passive BBM92.

The package is meant to calculate the optimal brightness, coincidence window and corresponding AKR for a given link loss.

Installation

pip install bbm92_cw

Examples

You can now use the module like you would any other python package. To understand better what the functionality offers, have a look at the following examples:

satellite overpass

In an overpass, we assume a constant loss of 20 dB on the terrestrial arm, and a variable loss on the free-space arm. The specs of the detectors are read out from a yaml file

BBM92_CW/bbm92_cw/example/example_overpass.py

Lines 1 to 42 in 4760e5c

    
           from bbm92_cw.secure_key_rates import secure_key_rates 
        
           import numpy as np 
        
           import yaml 
        
           # read in the detector settings and such from a yml file 
        
           with open("settings.yml", "r") as config_file: 
        
               params = yaml.safe_load(config_file) 
        
           for key, value in params.items(): 
        
               globals()[key] = value 
        
           # Loss profile in an overpass, just example data 
        
           loss_terrestrial = 20  # dB 
        
           time_step = 5 
        
           time = np.arange(-100, 100, step=time_step) 
        
           loss_free_space = -10 * np.log10(1e-4 / ((time / 40) ** 2 + 1))  # dB 
        
           # Loop through the loss evolution 
        
           rate_curve = [] 
        
           for i, loss_free in enumerate(loss_free_space): 
        
               link = secure_key_rates( 
        
                   name=f"sat overpass link", 
        
                   d=d, 
        
                   t_delta=jitters, 
        
                   eff_A=loss_terrestrial, 
        
                   eff_B=loss_free, 
        
                   DC_A=darkcounts_OGS, 
        
                   DC_B=darkcounts_SAT, 
        
                   e_b=bit_error, 
        
                   e_p=phase_error, 
        
                   f=f, 
        
                   t_dead=dead_times, 
        
                   loss_format="dB", 
        
               ) 
        
               tcc, B = link.optimal_params 
        
               rate = link.optimal_key_rate 
        
               rate_curve.append(rate) 
        
           # integrate to find the total key size 
        
           integrated_key = ( 
        
               sum([rate_curve[i] if rate_curve[i] > 0 else 0 for i in range(len(rate_curve))]) * time_step 
        
           ) 
        
           print(f"total asymptotic secure key of {integrated_key:.2e}")

Resulting in the following instantaneous key generation rate, which integrates to 27.6 kbit.

Instantaneous figures

Here we illustrate all interesting values that can be extracted from the calculation

BBM92_CW/bbm92_cw/example/example_figures.py

Lines 31 to 43 in f0b9f06

    
           tcc, B = link.optimal_params 
        
           rate = link.optimal_key_rate 
        
           error = link.error_rate([tcc, B]) 
        
           # We can also calculate the performance for non optimal parameters 
        
           tcc, B = 1e-9, 1e7 
        
           rate = link.custom_performance([tcc, B]) 
        
           error = link.error_rate([tcc, B]) 
        
           raw_rate = link.raw_rate([tcc, B]) 
        
           # Often the laser doesn't allow for arbitrary tuning so it is useful 
        
           # to optimize only the coincidence window. 
        
           tcc, rate = link.optimize_tcc_given_B(B)

References

[1] Neumann et al. (2021). Phys. Rev. A 104, 022406 10.1103/PhysRevA.104.022406

bbm92-cw
Release 0.0.2

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Documentation

BBM92_CW

Installation

Examples

satellite overpass

Instantaneous figures

References

Stats

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Contributors

	from bbm92_cw.secure_key_rates import secure_key_rates
	import numpy as np
	import yaml

	# read in the detector settings and such from a yml file
	with open("settings.yml", "r") as config_file:
	params = yaml.safe_load(config_file)
	for key, value in params.items():
	globals()[key] = value

	# Loss profile in an overpass, just example data
	loss_terrestrial = 20 # dB
	time_step = 5
	time = np.arange(-100, 100, step=time_step)
	loss_free_space = -10 * np.log10(1e-4 / ((time / 40) ** 2 + 1)) # dB

	# Loop through the loss evolution
	rate_curve = []
	for i, loss_free in enumerate(loss_free_space):
	link = secure_key_rates(
	name=f"sat overpass link",
	d=d,
	t_delta=jitters,
	eff_A=loss_terrestrial,
	eff_B=loss_free,
	DC_A=darkcounts_OGS,
	DC_B=darkcounts_SAT,
	e_b=bit_error,
	e_p=phase_error,
	f=f,
	t_dead=dead_times,
	loss_format="dB",
	)
	tcc, B = link.optimal_params
	rate = link.optimal_key_rate
	rate_curve.append(rate)

	# integrate to find the total key size
	integrated_key = (
	sum([rate_curve[i] if rate_curve[i] > 0 else 0 for i in range(len(rate_curve))]) * time_step
	)
	print(f"total asymptotic secure key of {integrated_key:.2e}")

	tcc, B = link.optimal_params
	rate = link.optimal_key_rate
	error = link.error_rate([tcc, B])

	# We can also calculate the performance for non optimal parameters
	tcc, B = 1e-9, 1e7
	rate = link.custom_performance([tcc, B])
	error = link.error_rate([tcc, B])
	raw_rate = link.raw_rate([tcc, B])

	# Often the laser doesn't allow for arbitrary tuning so it is useful
	# to optimize only the coincidence window.
	tcc, rate = link.optimize_tcc_given_B(B)

bbm92-cw Release 0.0.2

Release 0.0.2 Toggle Dropdown 0.0.2 0.0.1

Documentation

BBM92_CW

Installation

Examples

satellite overpass

Instantaneous figures

References

Stats

Development practices

Releases

Contributors

bbm92-cw
Release 0.0.2

Release 0.0.2

0.0.2

0.0.1