Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

SImBA - Systematic Inference of Bosonic quAntum systems

License: MIT Documentation Status

>>Documentation<<

Compute graphical quantum system representations from transfer functions

from simba import transfer_function_to_graph, tf2rss, adiabatically_eliminate
from sympy import symbols

s = symbols('s')
gamma_f, lmbda = symbols('gamma_f lambda', real=True, positive=True)
tf = (s**2 + s * gamma_f - lmbda) / (s**2 - s * gamma_f - lmbda)

transfer_function_to_graph(tf, 'active_coupled_cavity.png', layout='dot')
Active coupled cavity realisation

Calculate system transfer functions from the inferred system

split_network = tf2rss(tf).to_slh().split()
h_int = split_network.interaction_hamiltonian
h_int.expr.simplify()

Compute transfer functions between any degrees of freedom of the system

print(split_network.state_vector)
tfm = split_network.tfm
tf = tfm.open_loop('a_1', 'aout_1').simplify()
gamma_1, _ = split_network.aux_coupling_constants
adiabatically_eliminate(tf, gamma_1)

Installation

Install via pip install quantum-simba

See notebooks for examples.

To clone the dev environment run,

$ conda env create -f=environment.yml
$ conda activate simba

To install simba for development purposes,

$ pwd
... (simba code directory containing setup.py)
$ pip install -e .
(then to run test suite)
$ py.test

To build documentation locally,

$ pwd
... (simba code directory containing setup.py)
$ ./make_docs.sh

Motivation

Often when designing detectors for high-precision measurements, we are most interested in the frequency domain behaviour of such systems. For example, when computing the measurement shot noise of a gravitational wave detector, the noise spectrum is determined solely by the transfer function from the internal degree of freedom perturbed by the passing gravitational wave to the measurement output of the detector.

Until recently there has been no way to infer the layout of a quantum system directly from its transfer function, but now due to recent research in the quantum control community this is possible.

This software makes the process of finding a given physical realisation from the input-output transfer function completely automatic. Once this has been computed, it can then be used, for example, to deduce physical realisations, or more interestingly, to compute the most sensitive possible detector for a given numbers of internal degrees of freedom by minimizing the quantum Cramer-Rao bound.

TODO

  • Example notebooks
  • Write paper
  • Implement scattering matrix
  • Include examples on this page

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quantum-simba-0.8.dev0.tar.gz (19.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

quantum_simba-0.8.dev0-py3-none-any.whl (22.5 kB view details)

Uploaded Python 3

File details

Details for the file quantum-simba-0.8.dev0.tar.gz.

File metadata

  • Download URL: quantum-simba-0.8.dev0.tar.gz
  • Upload date:
  • Size: 19.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.1.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.3

File hashes

Hashes for quantum-simba-0.8.dev0.tar.gz
Algorithm Hash digest
SHA256 f766bf9447c7141377998f0bb5b6fb1b797c44007b1a358a78bb7b084214366a
MD5 ddbb91779b4f2db3b1f97bc95c336dd3
BLAKE2b-256 c88ee36cb93c7afdda2797aee2f3dee3fcf28aa010d05a2266defddd51ac5b8f

See more details on using hashes here.

File details

Details for the file quantum_simba-0.8.dev0-py3-none-any.whl.

File metadata

  • Download URL: quantum_simba-0.8.dev0-py3-none-any.whl
  • Upload date:
  • Size: 22.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.1.0 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.3

File hashes

Hashes for quantum_simba-0.8.dev0-py3-none-any.whl
Algorithm Hash digest
SHA256 ea4d2c0574b5116366c3f08939cda012c581367cff7c4f5798b71a3133ec42bc
MD5 6df26fe9c04480cf50c46502b9980aa2
BLAKE2b-256 18820dd30979c686f22f63ea72ebbd7d2c4641d3d1eb73b0671408148a32613d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page