Webb Office Hours Session 45: February 12, 2026
Q&A's:
Q1: Where are the Webb Office Hours procedures and guidelines?
A1: Webb Office Hours. Type your question into the WebEx chat. We will asynchronously copy questions from the chat to this main page and work through them as a group. If you have images to share please give WebEx permission to share your screen (you may need to log out and log back in again to enable this feature.)
Q2: I'm seeing some variation in my NIRSpec time series light curves and trying to understand what could be causing it, do you have any advice?
A2: One common source of additional noise in time series data is 1/f noise, a correlated read noise that changes between groups and integrations. This could be adding noise to your light curve, but there are some options in the JWST pipeline and other community options that you could use to try removing 1/f noise and see if that reduces the variations you see in your light curves. The JWST pipeline step to clean 1/f noise is called clean_flicker_noise which can be run as part of the detector1 pipeline when processing data from uncal files to rateints files. You can additionally run this step on your rateints images, and in some cases we know that users see an improvement in the 1/f noise correction when running this step in both of these places (i.e., running this step when generating rateints images and then running it a second time on the rateints images). Some general documentation about this step and running it on NIRSpec data can be found on this page: https://jwst-docs.stsci.edu/known-issues-with-jwst-data/1-f-noise#id-1/fNoise-AdviceforNIRSpecObservations, though the NIRSpec team is currently investigating optimal parameters for the step and currently would recommend starting with the following parameter settings:
n_sigma = 1.5
background_method = None
mask_science_regions = False
fit_method = median
If this does not improve the noise in your light curves, you may want to check the uncertainties on your data to see if the variation you see is consistent with being random errors given the signal to noise in your data.
If neither of these can explain your variations, we would recommend submitting a help desk ticket so that time series observation experts can provide more specific recommendations or point out what physical properties of the instrument might be changing over time that could impact light curve variations.
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