Tomography.buildTomoInput

Tomography.buildTomoInput(tomo_input, intensities)

Description not currently available

Parameters:
  • desc : This function build an input matrix based on a variety of inputs.

  • measurements : ndarray shape = ( Number of measurements , 2*NQubits )

    Each row in the matrix is a set of independent measurements.

  • counts : ndarray shape = (Number of measurements, NDetectors**NQubits )

    Each row in the matrix is a set of independent measurements.

  • crosstalk : ndarray shape = ( Number of measurements , 2**NQubits,2**NQubits ) (optional)

    The crosstalk matrix to compensate for inefficentcies in your beam splitter.

  • efficiency : 1darray with length = NQubits*NDetectors (optional)

    The relative efficienies between your detector pairs.

  • time : 1darray with length = Number of measurements (optional)

    The total duration of each measurment.

  • singles : ndarray shape = ( Number of measurements , 2*NQubits ) (optional)

    The singles counts on each detector.

  • window : 1darray with length = NQubits*NDetectors (optional)

    The coincidence window duration for each detector pair.

  • error : int (optional)

    The number of monte carlo states used to estimate the properties of the state.

  • intensities : 1darray with length = Number of measurements (optional)

    The relative intensity of each measurement. Used for drift correction.

  • method : ['MLE','HMLE','BME','LINER'] (optional)

    Which method to use to run tomography. Default is MLE

Returns:
  • tomo_input : ndarray

    The input data for the current tomography.

  • intensities : 1darray with length = number of measurements

    Relative pump power (arb. units) during measurement; used for drift correction. Default will be an array of ones


Contact

In case you have any further questions about the Python code, you should direct them to Scott Turro or Joey Shallat.