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We report on a particular example of noise and data representation interacting to introduce systematic error into scientific measurements. Many instruments collect integer digitized values and apply nonlinear coding, in particular square root coding, to compress the data for transfer or downlink; this can introduce surprising systematic errors when they are decoded for analysis. Square root coding and subsequent decoding typically introduces a variable ±1 count value-dependent systematic biasdoi:10.3847/1538-4357/ac7f3d fatcat:g2x6bo343jfbjazjjoxv6wjeve