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arxiv: 2604.24378 · v1 · submitted 2026-04-27 · 🌌 astro-ph.IM · astro-ph.GA· astro-ph.SR

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pyTANSPEC v1.0 and HxRGproc: Updated packages to Clean and Reduce TANSPEC data

Devendra K. Ojha, Joe P. Ninan, Saurabh Sharma, Supriyo Ghosh, Varghese Reji

Authors on Pith no claims yet

Pith reviewed 2026-05-07 17:35 UTC · model grok-4.3

classification 🌌 astro-ph.IM astro-ph.GAastro-ph.SR
keywords TANSPECdata reduction pipelinenear-infrared spectroscopywavelength calibrationflux calibrationHxRG detectorpyTANSPECinstrumentation
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The pith

Upgraded pyTANSPEC pipeline now supports data reduction from all TANSPEC slits in both low-resolution and cross-dispersed modes.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper describes an upgraded version of the pyTANSPEC data reduction package for the TANSPEC near-infrared spectrograph on the 3.6-m DOT telescope. It extends prior capabilities by enabling processing of spectra from every available slit width in both LR and XD modes. The update introduces template-matching for wavelength calibration, adds flux calibration, and improves the extraction algorithm. A companion package, HxRGproc, is also updated to clean H2RG detector data with non-linearity correction, cosmic-ray removal, and pink-noise filtering, with pre-processed outputs available directly from the TANSPEC server.

Core claim

The upgraded pyTANSPEC v1.0 enables the reduction of spectra from all available slits for both LR and XD modes, implements a template-matching method for more precise wavelength calibration, and includes a flux calibration step. HxRGproc is updated to work for the H2RG detector of TANSPEC and is set up on the TANSPEC server, ensuring users receive data that are pre-cleaned and non-linearity corrected.

What carries the argument

The pyTANSPEC pipeline, which performs data extraction, template-matching wavelength calibration, and flux calibration across all slits and modes.

If this is right

  • Observers can now reduce low-resolution mode spectra and data taken with any of the six slit widths.
  • Wavelength solutions gain precision from template matching instead of earlier methods.
  • Flux calibration becomes a standard step in the reduction sequence.
  • Users obtain pre-cleaned slope images with non-linearity correction directly from the instrument server.
  • The full 0.55-2.5 micrometer range is accessible in both resolution modes without prior slit restrictions.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Wider slit and mode support could increase the fraction of TANSPEC observations that reach publication.
  • Server-side pre-processing may shorten the time from observation to science-ready products.
  • Template-based calibration might reduce systematic differences between data sets taken under varying conditions.

Load-bearing premise

The template-matching wavelength calibration and new extraction algorithm deliver better results than the previous version across all slits and modes.

What would settle it

A side-by-side comparison on identical raw frames showing no reduction in wavelength residuals or no improvement in spectral feature recovery when using the new pipeline versus the old one.

read the original abstract

TIFR-ARIES Near-Infrared Spectrometer (TANSPEC) is a spectrograph-cum-imager operating over the wavelength range $0.55 - 2.5~\mu$m. The instrument is mounted on the 3.6-m Devasthal Optical Telescope (3.6-m DOT). It offers two resolution modes: Low Resolution (LR) with $R\sim100-350$ and Cross-Dispersed (XD) via various slits of different widths (0.5", 0.75", 1.0", 1.5", 2.0" and 4.0"). The LR mode provides a resolving power ($R$) of $\sim 100-350$, while the XD mode achieves $R\sim2500$ using the 0.5" slit. The previous version of the data reduction pipeline supported only wavelength-calibrated XD mode spectra and was limited to two slits (S-0.5 and S-1.0). In this work, we present an upgraded version of pyTANSPEC. The upgraded pipeline not only improves the data extraction algorithm but also introduces several new features for users. It now enables the reduction of spectra from all available slits for both LR and XD modes. The upgraded version also implements a template-matching method for more precise wavelength calibration. Additionally, a step for flux calibration is also included. Alongside pyTANSPEC, we upgraded HxRGproc, a Python package for cleaning and generating slope images from Non-Destructive Readout (NDR) frames taken with H1RG and H2RG detectors. The package performs non-linearity correction, flags saturated pixels, removes pink noise, and eliminates cosmic ray events. HxRGproc is updated to work for the H2RG detector of TANSPEC and is set up on the TANSPEC server, ensuring users receive data that are pre-cleaned and non-linearity corrected.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 0 minor

Summary. The paper announces the release of pyTANSPEC v1.0, an upgraded Python pipeline for reducing TANSPEC spectrograph data from the 3.6-m DOT, together with updates to the HxRGproc package for cleaning H2RG detector frames. It claims that the new version extends support to all available slits in both low-resolution (LR) and cross-dispersed (XD) modes, implements a template-matching approach for wavelength calibration, adds a flux-calibration step, improves the extraction algorithm, and provides server-side pre-cleaned, non-linearity-corrected data products.

Significance. If the described features operate as stated, the updated packages would constitute a practical advance for TANSPEC users by enabling reduction of the full range of slit configurations and modes and by incorporating flux calibration, thereby increasing the usability of data from the 3.6-m DOT. The server integration for pre-processed frames is a clear operational benefit.

major comments (2)
  1. [Abstract] Abstract: the claim that the template-matching method delivers 'more precise' wavelength calibration is not accompanied by any quantitative validation (e.g., RMS residuals, line-position accuracy tables, or direct comparison with the prior pipeline).
  2. [Abstract] Abstract: the statement that the data extraction algorithm has been improved and now supports all slits in LR and XD modes lacks before/after performance metrics, error budgets, or example reduced spectra that would demonstrate the claimed gains.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which help clarify how to better present the capabilities of the updated pyTANSPEC and HxRGproc packages. We address each major comment below and will revise the manuscript to incorporate the requested quantitative support.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the claim that the template-matching method delivers 'more precise' wavelength calibration is not accompanied by any quantitative validation (e.g., RMS residuals, line-position accuracy tables, or direct comparison with the prior pipeline).

    Authors: We agree that the abstract's phrasing requires supporting metrics to substantiate the improvement. The current manuscript describes the template-matching approach but does not include explicit RMS residuals or direct comparisons in the abstract. In the revised version we will add a concise quantitative statement to the abstract (e.g., typical RMS improvement) and reference a new or expanded table/figure in the main text that shows line-position accuracy and residuals for the new versus previous pipeline across representative slits and modes. revision: yes

  2. Referee: [Abstract] Abstract: the statement that the data extraction algorithm has been improved and now supports all slits in LR and XD modes lacks before/after performance metrics, error budgets, or example reduced spectra that would demonstrate the claimed gains.

    Authors: We acknowledge that the abstract would be strengthened by explicit performance indicators. The manuscript text notes the expanded slit support and algorithmic updates, yet the abstract itself provides no metrics or examples. We will revise the abstract to include brief references to before/after extraction metrics, error budgets, and example spectra (with figure numbers) that are either already present or will be added to the main body during revision. revision: yes

Circularity Check

0 steps flagged

No circularity in software update announcement

full rationale

The paper is a descriptive announcement of upgrades to the pyTANSPEC and HxRGproc packages. It details new capabilities such as support for all slits in LR and XD modes, a template-matching wavelength calibration step, and flux calibration, along with updates to HxRGproc for non-linearity correction and cosmic ray removal. No mathematical derivations, equations, fitted parameters, predictions, or uniqueness theorems are present. There are no self-citations invoked as load-bearing premises, no ansatzes smuggled in, and no renaming of known results. The content is self-contained as a practical software release note with no internal reduction of claims to inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

No mathematical model, physical derivation, or new entities; the work consists entirely of software engineering updates to prior packages.

pith-pipeline@v0.9.0 · 5696 in / 990 out tokens · 41632 ms · 2026-05-07T17:35:14.558207+00:00 · methodology

discussion (0)

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Reference graph

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