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-0.9.5.dev0.tar.gz (20.1 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-0.9.5.dev0-py3-none-any.whl (22.7 kB view details)

Uploaded Python 3

File details

Details for the file quantum-simba-0.9.5.dev0.tar.gz.

File metadata

  • Download URL: quantum-simba-0.9.5.dev0.tar.gz
  • Upload date:
  • Size: 20.1 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-0.9.5.dev0.tar.gz
Algorithm Hash digest
SHA256 946aa5bf23d24b8484446b6f72df3cbf36de3d1bf49b8947464d385aea5ab8b6
MD5 c014c1320a070722cd69e33ff58d7a52
BLAKE2b-256 aced461637946d3b32aa6eb358ec407d98490576f1bf08ccdf8e96bcbabb73f4

See more details on using hashes here.

File details

Details for the file quantum_simba-0.9.5.dev0-py3-none-any.whl.

File metadata

  • Download URL: quantum_simba-0.9.5.dev0-py3-none-any.whl
  • Upload date:
  • Size: 22.7 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-0.9.5.dev0-py3-none-any.whl
Algorithm Hash digest
SHA256 3e935bd1192b4ea958aeb11f34347338ee85f8d7c23e91acc03fb8c10f236d4a
MD5 cc0162c8292e4174cc9a96e0b3d67a00
BLAKE2b-256 b01c6ffa23d0b606a85922e89ff97a45b53530efbe3b132573a66b9ccf779c2e

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