Skip to content

Virtual excitations in the ultra-strongly-coupled spin-boson model: physical results from unphysical modes

License

Notifications You must be signed in to change notification settings

nwlambert/matsubara

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

34 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

matsubara

Virtual excitations in the ultra-strongly-coupled spin-boson model: physical results from unphysical modes

Neill Lambert, Shahnawaz Ahmed, Mauro Cirio, Franco Nori

The is the code to reproduce the results in arXiv:1903.05892. A special matsubara.heom.HeomUB class is provided to implement the Hierarchical Equations of Motion method adapted for the underdamped Brownian motion spectral density.

We focus on the zero temperature case where the correlation function can be expressed using four exponents.

Installation

The code is in development and can be used by cloning the repository and performing an in-place installation using python.

git clone https://github.com/pyquantum/matsubara.git
cd matsubara
python setup.py develop

Numpy, Scipy and QuTiP are required. Install them with conda if you do not already have them using

conda install -c conda-forge numpy scipy qutip

Examples

In matsubara/docs/source/examples/ there are several examples from the paper which can be easily reproduced. The basic calcalation of the Matsubara and non Matsubara modes can be done in the following way:

from matsubara.correlation import (nonmatsubara_exponents,
                                   matsubara_zero_exponents,
                                   biexp_fit, sum_of_exponentials)

coup_strength, cav_broad, cav_freq = 0.2, 0.05, 1.
tlist = np.linspace(0, 100, 1000)

# Zero temperature case beta = 1/kT
beta = np.inf
ck1, vk1 = nonmatsubara_exponents(lam, gamma, w0, beta)

# Analytical zero temperature calculation of the Matsubara correlation
mats_data_zero = matsubara_zero_exponents(lam, gamma, w0, tlist)

# Fitting a biexponential function
ck20, vk20 = biexp_fit(tlist, mats_data_zero)

print("Coefficients:", ck1, ck20)
print("Frequencies:", vk1, vk20)
Coefficients: [0., 0.02] [-0.00020, -0.00010]
Frequencies: [-0.025 + 0.99j, -0.025-0.99j] [-1.61 - 0.32]

About

Virtual excitations in the ultra-strongly-coupled spin-boson model: physical results from unphysical modes

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%