scresonators-fit 0.5.1

Python library for measuring and fitting superconducting resonator data

scresonators

Welcome to the scresonators repository of the Boulder Cryogenic Quantum Testbed! This is a library for measuring the loss in superconducting resonators.

Installation

1. clone the repository into a folder of your choice with git clone https://github.com/Boulder-Cryogenic-Quantum-Testbed/scresonators.git
2. Install the dependencies, we strongly recommend using virtual environments for managing your dependences. To install dependencies run: pip install -r requirements.txt
3. If you are running on Windows, install Microsoft Visual Studio before using the library

Using the library

Here's an example using some of the data hosted on this repository. Hosted datasets from groups around the world can be found here.

This particular example code is meant to be run in the root directory.

import numpy as np
import fit_resonator.functions as ff
import fit_resonator.Sdata as fsd
import fit_resonator.resonator as res

url = 'https://raw.githubusercontent.com/Boulder-Cryogenic-Quantum-Testbed/scresonators/master/cryores/test_data/AWR/AWR_Data.csv'

# Load the raw data:
raw = np.loadtxt(url, delimiter=',')

# Choose a fitting method:
fit_type = 'DCM'
MC_iteration = 10
MC_rounds = 1e3
MC_fix = ['w1']
manual_init = None
method = res.FitMethod(fit_type, MC_iteration, MC_rounds=MC_rounds,
                       MC_fix=MC_fix, manual_init=manual_init, MC_step_const=0.3)

# Fit the data:
fsd.fit("output test", method, normalize=10, data_array=raw)

Ane in depth description is given in the fit_resonators folder.

Code Organization

Until the module is officially distributed, all code should live in the fit_resonator namespace. This ensures easy integration with other Python packages, and avoids name collisions; everything is referred to as e.g. fit_resonator.experiments rather than just experiments.