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satorchi edited this page Mar 30, 2019 · 1 revision

Data analysis methods

ADU2I(ADU, offset=None)

conversion from the Analogue Digital Units returned by QubicStudio to current in micro Ampere

  • the optional offset will raise/lower the entire curve. Note that in general, offset is calculated by methods such as plot_iv() (see below). If you want to have the vector of points for an I-V curve, you can use the method Ites() described below.

adjusted_iv(TES)

return a vector with the measured current for each bias point. This is the current measured in μA. If you want the corresponding bias voltages, they can be found in the variable vbias. For example, if your QubicPack object is called go, then the bias voltages are found in go.vbias You might prefer to use the method Ites described below.

Ites(TES)

return the measured current in Amps (not μAmps).

Vtes(TES)

return the voltage across the TES. This is not the bias voltage. Vtes is calculated according to:

Vtes=Rshunt*(vbias/Rbias-Ites)

with:

  • Rshunt=0.01 Ω
  • Rbias=10000 Ω

Ptes(TES)

return the power across the TES which is simply Ites * Vtes

Rn_ratio(TES)

the ratio of TES resistance to Normal Resistance (see R1 below).

filter_iv(TES,residual_limit=3.0,abs_amplitude_limit=0.01,rel_amplitude_limit=0.1,bias_margin=0.2,jumplimit=2.0)

This method will apply a filter to the I-V curve of a given TES, and determine if this is a good pixel. The I-V curve is fit to a 3rd degree polynomial in order to find the turnover (operation) point of the TES. The dynamic normal resistance (resistance at high bias voltage) which should be on the order of 1 Ohm, is determined by fitting the final points to a straight line.

arguments:

  • TES is the TES number (required)
  • the remaining keywords are all optional:
    • residual_limit: this is an indication of the acceptable quality of the polynomial fit
    • abs_amplitude_limit: this is the lower limit for acceptable current measured
    • rel_amplitude_limit: this is the lower limit for the peak-to-peak variation in the measured current across the bias voltage range applied.
    • bias_margin: this is the proximity to the edge of the bias range which is considered to be acceptable
    • jump_limit: this is the current step size between bias points which is considered to be a jump. The polynomial fit takes this into account when it determines which points to fit.

filter_iv_all(residual_limit=3.0,abs_amplitude_limit=0.01,rel_amplitude_limit=0.1,bias_margin=0.2,jumplimit=2.0)

  • run a filter on the I-V data to determine which are good pixels. The keywords are as described above for filter_iv(). The result is stored in the qubicpack object and is used in subsequent plotting. The filter results are accessible via a number of helper methods, or directly in the python list called filtersummary.

is_good_iv(TES)

The return value is the determination of whether or not the TES is considered to be a good pixel. If no TES is specified, the return value is a list of True/False values corresponding to the evaluation of each TES.

ngood()

The return value is the total number of good pixels.

good_index()

The return value is a list of indexes corresponding to the TES which are considered to be good. WARNING!!! These indexes are not the same as the TES number! TES_index=TES-1 (python counts starting from zero). In general, wherever the word index is used, it refers to a count which begins at zero.

R1(TES)

The return value is the Dynamic Normal Resistance of the TES. This should be close to 1 Ohm. If no TES is specified, the return value is a list corresponding to the calculated R1 value of each TES.

turnover(TES)

The return value is the turnover (operating) point of the TES. If no TES is specified, the return value is a list corresponding to the calculated turnover point of each TES.

offset(TES)

The return value is the current offset used to make the I-V curve intersect with the R=1 Ohm line at the highest bias voltage. If no TES is specified, the return value is a list corresponding to the calculated offset of each TES.

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