WIggle Corrector Kit for NIRSpEc Data: WICKED

Context . The point spread function of the integral field unit (IFU) mode of the Near-Infrared Spectrograph (NIRSpec) detector of JWST is undersampled. The resampling of the spectra into a 3D data cube creates resampling noise seen as low-frequency sinusoidal-like artifacts, or “wiggles.” These artifacts in the data are not corrected in the JWST data pipeline and significantly impact the science that can be achieved at a single-pixel level. Aims . Here we present the tool “ WI ggle C orrector K it for NIRSp E c D ata” (WICKED) designed to remove these artifacts. While fully characterizing wiggles requires forward modeling of the instrument response, WICKED offers a faster and computationally efficient alternative using an empirical correction. Methods . WICKED uses the fast Fourier transform algorithm to identify wiggle-affected spaxels across the (IFU) data cube. Spectra are modeled with a mix of integrated aperture and annular templates, a power law, and a second-degree polynomial, thus avoiding the high-degree polynomials that distort spectral features. Our correction works across all medium- and high-resolution NIRSpec gratings: F070LP, F100LP, F170LP, and F290LP. Results . The overall spectral shape recovered by WICKED is up to 3.5 times better compared to uncorrected spectra. It recovers the equivalent width of absorption lines within 5% of the true value, which is also roughly three times better than the uncorrected spectra. WICKED7 significantly improves kinematic measurements, recovering the line-of-sight velocity (LOSV) within 1% of the true value – more than 100 times better than uncorrected spectra at S/N ~ 40. As a case study, we applied WICKED to G235H/F170LP IFU data of the elliptical galaxy NGC 5128, finding good agreement with previous studies. In wiggle-affected regions, the uncorrected spectrum showed a stellar LOSV and velocity dispersion differences ~17 times and ~36 times larger than the estimated uncertainties, respectively, compared to the WICKED-cleaned spectrum. Conclusions . Wiggles in NIRSpec IFU data can significantly distort the overall spectral shape and bias line measurements and kinematics to values larger than the expected uncertainties for uncorrected spectra. WICKED is a robust, user-friendly solution for mitigating wiggles in NIRSpec data that enables precise single-spaxel studies and enhances JWST’s potential for groundbreaking discoveries in galaxy kinematics and early Universe studies.

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Publication Details

Journal
Astronomy and Astrophysics
Published
2025-09-30
DOI
https://doi.org/10.1051/0004-6361/202554494
Citations
3
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
2.40
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article

WIggle Corrector Kit for NIRSpEc Data: WICKED

Jonelle L. Walsh, Nora Lützgendorf, Antoine Dumont, Kayhan Gültekin et al.
3 citations
Astronomy and Astrophysics
Air Quality Monitoring and Forecasting
2.40
article

WIggle Corrector Kit for NIRSpEc Data: WICKED

Jonelle L. Walsh, Nora Lützgendorf, Antoine Dumont, Kayhan Gültekin, Jenny E. Greene, Kameron Goold, Luis C. Ho, Nadine Neumayer, Anil C. Seth, Torsten Böker, Michael Eracleous
article en
3 citations

Abstract

Context . The point spread function of the integral field unit (IFU) mode of the Near-Infrared Spectrograph (NIRSpec) detector of JWST is undersampled. The resampling of the spectra into a 3D data cube creates resampling noise seen as low-frequency sinusoidal-like artifacts, or “wiggles.” These artifacts in the data are not corrected in the JWST data pipeline and significantly impact the science that can be achieved at a single-pixel level. Aims . Here we present the tool “ WI ggle C orrector K it for NIRSp E c D ata” (WICKED) designed to remove these artifacts. While fully characterizing wiggles requires forward modeling of the instrument response, WICKED offers a faster and computationally efficient alternative using an empirical correction. Methods . WICKED uses the fast Fourier transform algorithm to identify wiggle-affected spaxels across the (IFU) data cube. Spectra are modeled with a mix of integrated aperture and annular templates, a power law, and a second-degree polynomial, thus avoiding the high-degree polynomials that distort spectral features. Our correction works across all medium- and high-resolution NIRSpec gratings: F070LP, F100LP, F170LP, and F290LP. Results . The overall spectral shape recovered by WICKED is up to 3.5 times better compared to uncorrected spectra. It recovers the equivalent width of absorption lines within 5% of the true value, which is also roughly three times better than the uncorrected spectra. WICKED7 significantly improves kinematic measurements, recovering the line-of-sight velocity (LOSV) within 1% of the true value – more than 100 times better than uncorrected spectra at S/N ~ 40. As a case study, we applied WICKED to G235H/F170LP IFU data of the elliptical galaxy NGC 5128, finding good agreement with previous studies. In wiggle-affected regions, the uncorrected spectrum showed a stellar LOSV and velocity dispersion differences ~17 times and ~36 times larger than the estimated uncertainties, respectively, compared to the WICKED-cleaned spectrum. Conclusions . Wiggles in NIRSpec IFU data can significantly distort the overall spectral shape and bias line measurements and kinematics to values larger than the expected uncertainties for uncorrected spectra. WICKED is a robust, user-friendly solution for mitigating wiggles in NIRSpec data that enables precise single-spaxel studies and enhances JWST’s potential for groundbreaking discoveries in galaxy kinematics and early Universe studies.

Astronomy and AstrophysicsVol. 703
King University (US), Space Telescope Science Institute (US), Princeton University (US), Peking University (CN), University of Utah (US), University of Michigan (US), Mitchell Institute (US), European Space Agency (FR), Max Planck Institute for Astronomy (DE), European Space Research and Technology Centre (NL), Netherlands Institute for Radio Astronomy (NL)
Openalex Percentile: Top 11%
Air Quality Monitoring and Forecasting
2.40
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