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This paper presents pyetc_wst, an end-to-end exposure time calculator for the Wide-field Spectroscopic Telescope that simulates the full photon path from source to detector and predicts concrete survey depths for all three spectrograph mode

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A new open-source exposure time calculator simulates the full photon path for the proposed WST telescope's three spectrograph modes and gives provisional signal-to-noise and limiting-magnitude baselines.

T0 review reviewed 2026-08-04 challenge →

load-bearing objection A solid, honestly caveated ETC tool paper for WST whose survey-depth numbers are provisional; the 'validated' claim in the conclusions overreaches, but the code and method deserve refereeing. the 2 major comments →

arxiv 2608.00193 v1 pith:5GUYVUEG submitted 2026-07-31 astro-ph.IM

WST instrument Exposure Time Calculator: full simulation of multi-mode spectrograph performance from source to detector

Matteo Ferro , Matteo Genoni , Henri M. J. Boffin , Jose Schiappacasse-Ulloa , Sofia Randich , Roland Bacon , Vincenzo Mainieri , Alessio Mucciarelli
show 8 more authors
Carmela Lardo Michele Moresco Cristian Vignali Margherita Talia Andrea Scaudo Marco Landoni Roelof S. de Jong Olga Bellido-Tirado
This is my paper
classification astro-ph.IM
keywords Exposure Time CalculatorWide-field Spectroscopic TelescopeIntegral Field SpectroscopyMulti-Object SpectroscopySignal-to-Noise RatioEnd-to-end simulationThroughput modelLimiting magnitude
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The reading

The paper introduces a new exposure time calculator for the proposed Wide-field Spectroscopic Telescope, a 12-meter facility with three simultaneous spectrograph modes. Rather than using simple scaled efficiencies, the calculator simulates the complete photon path: source spectrum, atmospheric transmission, telescope and instrument throughput per channel, fibre coupling, sky emission, and detector noise. From these it produces wavelength-dependent signal-to-noise spectra, noise decompositions, simulated raw spectra, and limiting magnitudes. The headline performance numbers are that the integral-field mode reaches a surface-brightness limit of about 25.4 AB magnitudes per square arcsecond in the blue and 25.5–26.0 in the red, while the low-resolution multi-object mode reaches point-source limits of roughly 22 to 23.4 AB magnitudes, all for one hour of exposure in dark sky. A sympathetic reader would care because such a tool makes the project's survey capabilities concrete and testable before construction.

Core claim

The paper's central claim is that pyetc_wst implements a true end-to-end model of the WST instruments. For each wavelength element, the detected signal is the product of the source flux, telescope area, atmospheric transmission, a wavelength-dependent total instrument throughput table, fibre injection fraction, and exposure time; the noise variance is a sum of source photon noise, sky photon noise, dark current, and read-out noise, with coadding and DIT/NDIT combinations handled explicitly. The tool supports point sources, uniform surface brightness, and Sérsic profiles, and generates Monte Carlo realisations of observed 1D spectra. The author's conclusion, on the basis of this model and the

What carries the argument

The central object is the photon-budget equation S(λ) = F_λ(λ) (λ/hc) A_tel τ_atm(λ) T_ins(λ) f_fib(λ) t_exp, together with the per-pixel noise variance σ² = N_DIT [S_src + S_sky + N_pix (d t_DIT + σ_RON²)]. The instrument throughput tables T_ins(λ), one per channel and currently the only unmeasured input, carry most of the physical content. The fibre injection fraction is computed from a Moffat PSF integrated over a circular aperture, with an object–fibre displacement parameter for pointing errors. Sky emission and atmospheric transmission come from a static table set or a live external sky service. The four computation modes invert these equations to find SNR, exposure time, or the optimal

Load-bearing premise

Everything hinges on the unmeasured, wavelength-dependent instrument throughput tables supplied by the system engineering team; if the as-built optics and detectors underperform those curves, every SNR and limiting magnitude in the paper falls in proportion.

What would settle it

Take one IFS blue channel and one MOS-LR channel, measure their end-to-end throughput on the ground using a calibrated continuum source, and compare the ETC's predicted SNR for a standard star of known flux against the SNR actually recorded on a detector with known read-out noise. A discrepancy larger than the stated detector noise contributions would falsify the model's predictive accuracy; a laboratory measurement of total instrument efficiency at 500 nm would already bound the main limiting-magnitude claims.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • If the model holds, WST's IFS will be able to obtain SNR=3 per resolution element on surface brightness of about 25.4 AB mag/arcsec² in one hour in dark sky, which defines the accessible regime for studies of faint diffuse emission.
  • MOS-LR point-source limits of r≈22–23.4 AB in one hour imply that a single 2-degree pointing can deliver spectroscopy for tens of thousands of targets down to those magnitudes.
  • The noise decomposition at V=19 shows source photon noise dominated below 850 nm and read-out/dark noise below 5%, so those detector assumptions are not currently limiting the predicted performance.
  • The exposure-time inversion modes allow survey planners to convert a target SNR directly into a DIT/NDIT schedule, which is exactly what is needed for designing an observational campaign.

Where Pith is reading between the lines

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

  • Editorial inference: because the throughput tables are the only unmeasured input, the same tool can be rerun with revised tables at every design iteration, turning the ETC into a living survey forecast.
  • Editorial inference: the fibre-injection treatment could be sharpened by adding atmospheric dispersion and 3-D slit losses, which would most affect the blue end of each channel.
  • Editorial inference: making the calculator public invites independent reproduction of the headline depths, which would test the design baseline without needing the telescope.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. The paper presents pyetc_wst, an exposure time calculator for the proposed Wide-field Spectroscopic Telescope, covering IFS, MOS-LR, and MOS-HR. It implements a source-to-detector photon budget (Eq. 1), static and SkyCalc sky backgrounds, PSF/fibre injection, a noise model (Eq. 2), four computation modes, and web/REST/CLI interfaces. Example outputs include SNR spectra, noise decomposition, and limiting magnitudes: IFS surface brightness μ_r ≈ 25.4 AB arcsec^-2 and MOS-LR point-source limits r ≈ 22–23.4 AB for 1 h dark-sky observations.

Significance. The main value of this work is a public, modular ETC implementation built on standard photon-budget and variance equations, with useful features such as SkyCalc integration, a rich SED/template library, flexible computation modes, and noise decomposition. These are concrete strengths that make the tool immediately usable for WST survey planning. However, the quantitative performance predictions are not independent measurements: they scale linearly with preliminary system-engineering throughput tables that are explicitly subject to revision. The paper's claim that the throughput model and performance numbers are 'verified against first-principles expectations' goes beyond what is actually shown and should be tempered or supported by a sensitivity analysis.

major comments (2)
  1. [§5.3, §2.1] The claim that GLAO improves the IFS surface-brightness limit by reducing the sky background per spaxel is physically incorrect for a fixed 0.25″ spaxel. For a uniform extended source, both source and sky counts per spaxel are independent of PSF. If instead the extraction aperture is matched to the PSF, a smaller PSF reduces the aperture area and thus the SNR per resolution element. Fig. 10 and the headline μ_r ≈ 25.4 AB arcsec^-2 rest on this step. Please specify the exact spatial binning/resolution element and provide a derivation; as written, the GLAO-specific SB limiting magnitudes are unsupported.
  2. [§5.1, Fig. 8, §6] All limiting magnitudes and SNR curves scale linearly with the preliminary throughput tables T_ins(λ) in Eq. (1), which are unmeasured engineering estimates ('expected to reach' 79.8%/91.3% telescope throughput, assumed detector RON/dark) with no quoted uncertainty. The paper itself warns in §5.1 that 'all performance numbers reported in this paper should be interpreted accordingly,' yet §6 states the throughput model has been 'verified against first-principles expectations' and presents the limits as confirming WST performance. No verification or sensitivity analysis is shown. Please add an uncertainty propagation or sensitivity study for the headline numbers, or explicitly reframe the conclusions as provisional engineering estimates.
minor comments (5)
  1. [Throughout] The package name is typeset inconsistently as 'pyetc wst' in the text and 'pyetc_wst' in code/URLs; unify the notation.
  2. [Fig. 9 caption] The caption says 'rebinned by 5 Å for display' while the text describes SNR per spectral pixel; clarify whether the values are per native pixel or per rebinned bin.
  3. [§5.3] The definition 'per resolution element of 1.4 Å co-added over 3 spectral pixels' specifies only the spectral bin; the spatial element used for the IFS surface-brightness limit should be stated explicitly (e.g., 1 spaxel, N×N bin, or PSF area).
  4. [References] References [5], [6], and [7] cite 'Proc. SPIE This conference' with paper numbers but no page/article details; if available, add full bibliographic information or a DOI.
  5. [Table 1] The MOS-HR channels are named Blue, Green, Yellow, Red, which may be confused with the MOS-LR channels of the same names in Fig. 8. Consider adding the central wavelengths or a prefix (e.g., HR-Blue) to the channel labels.

Circularity Check

0 steps flagged

No circularity: the ETC results are conditional photon-budget calculations from explicitly preliminary instrument-throughput inputs.

full rationale

The derivation chain is a standard ETC photon budget: Eq. (1) computes detected signal as the product of source flux, telescope area, atmospheric transmission, instrument throughput, fibre fraction, and exposure time; Eq. (2) forms the noise variance and SNR; the limiting magnitudes in §5.3 are obtained by inverting SNR = 3. The instrument throughput T_ins is an input (Fig. 8), explicitly described as 'a preliminary throughput model delivered by the WST system engineering team' that 'will be updated as the design matures' (§5.1). Nothing in the paper defines T_ins in terms of the predicted SNR or limiting magnitudes, and no parameter is fitted to the output curves; the reported numbers are conditional on the stated engineering baseline. The §6 sentence claiming the model has been 'verified against first-principles expectations' is unsupported by the text, but that is a validation/evidence gap, not a circular reduction: nothing shows the prediction being used to construct its own input. The self-references to WST design papers (refs [4]–[7]) provide design parameters such as coating expectations, not a uniqueness theorem or an ansatz, and the central calculation does not collapse into those citations. An ETC can, in principle, be checked against independent end-to-end simulations or future as-built measurements, so the central derivation retains independent content. The appropriate concern—unquantified throughput uncertainty affecting all limiting magnitudes—is a correctness risk, not circularity.

Axiom & Free-Parameter Ledger

6 free parameters · 5 axioms · 0 invented entities

The tool's outputs are a transparent propagation of its inputs: engineering-estimate throughput tables, assumed detector RON/dark values, a Moffat PSF shape, and assumed GLAO performance. No entities are invented; sky and template inputs are external (SkyCalc, MARCS/Phoenix/Kurucz/Pickles). The main honesty feature is the explicit disclosure that the throughput is preliminary, and the main burden is that every headline number inherits that unmeasured input.

free parameters (6)
  • Instrument throughput tables T_ins(λ) per channel = IFS blue ~34% peak, IFS red ~39% peak, MOS-LR 24–34%, MOS-HR 13–19% (Fig. 8)
    Engineering-model values, not measured; enter Eq. 1 and scale every §5 SNR and limiting-magnitude number. Supplied by the WST system engineering team (co-author) and unpublished as data.
  • Telescope throughput 79.8% (IFS) / 91.3% (MOS) = 79.8% / 91.3% (§2.1)
    "Expected to reach" values for advanced coatings under development; assumed, unverified at this conceptual phase.
  • Detector RON and dark current per channel = RON 1.0–1.4 e^-, dark 1–2 e^-/hr (Table 1)
    Assumed scientific-CMOS performance; enters Eq. 2 and the noise decomposition (§5.4).
  • Moffat PSF β = 2.8 = β = 2.8 (§3.2)
    Assumed PSF shape for point-source fibre injection and aperture fractions; a modeling choice, not measured for WST.
  • GLAO image quality 0.5″ FWHM at 650 nm, 40% probability = 0.5″ at 650 nm, 40% probability, 85% sky coverage (§2.1)
    Assumed adaptive-optics performance; drives the IFS surface-brightness limits in §5.3.
  • Static-mode sky brightness levels (dark/grey/bright) = FLI = 0, 0.5, 1.0 (§3.3)
    Tabulated internal sky spectra at three moon phases; assumed representative of the site.
axioms (5)
  • standard math Photon budget: detected electrons = F_λ × (λ/hc) × A_tel × τ_atm × T_ins × f_fib × t_exp (Eq. 1)
    Standard radiometric relation; unproved background assumed throughout §3.1.
  • standard math Noise variance = N_DIT × [S_src + S_sky + N_pix(d t_DIT + σ_RON²)] with Poisson source/sky and Gaussian RON (Eq. 2)
    Standard CCD noise propagation; no independent verification shown in the paper.
  • domain assumption ESO SkyCalc emission/transmission spectra are representative of the WST site observing conditions
    In §3.3 the live SkyCalc query is treated as accurate sky truth; WST site is assumed Paranal-like.
  • ad hoc to paper The system-engineering throughput tables T_ins(λ) describe the as-built instrument
    The entire performance prediction rests on this unpublished internal model (§3.1, Fig. 8); the paper itself flags it as preliminary (§5.1).
  • domain assumption Moffat profile with β = 2.8 models on-sky PSF including seeing wings
    In §3.2/§3.5, fibre injection fractions are computed from this assumed profile shape.

reviewed 2026-08-04 · how reviews work

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Cite this review

Pith. "Pith review of WST instrument Exposure Time Calculator: full simulation of multi-mode spectrograph performance from source to detector." pith.science (2026). https://pith.science/paper/5GUYVUEG

@misc{pith2026260800193,
  author       = {Pith},
  title        = {Pith review of: WST instrument Exposure Time Calculator: full simulation of multi-mode spectrograph performance from source to detector},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/5GUYVUEG}},
  note         = {Machine review of arXiv:2608.00193}
}
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read the original abstract

We present a comprehensive Exposure Time Calculator (ETC) developed for the Wide-field Spectroscopic Telescope (WST) concept. The WST, currently in its conceptual phase, is designed as a next-generation large spectroscopic survey facility featuring three complementary observing modes: an Integral Field Spectrograph (IFS) covering 370-930 nm at R of about 4800; a high-resolution Multi-Object Spectrograph (MOS-HR) with four bands at R of about 40000; and a low-resolution Multi-Object Spectrograph (MOS-LR) with four channels at R of about 3800-4900. The ETC simulates the complete photon-propagation path from astronomical source to detector, incorporating wavelength-dependent system throughput (telescope transmission, instrumental optics, detector quantum efficiency), accurate sky background via ESO SkyCalc integration, and a comprehensive noise treatment (photon noise, sky background, read-out noise, dark current). The computational core is implemented as the "pyetc_wst" Python library built on the MPDAF framework, supporting multiple target spectral energy distributions (stellar templates, blackbody, power-law, emission lines, and user-uploaded spectra with arbitrary redshift) and spatial morphologies (point sources and Sersic extended profiles). Four operational modes enable flexible exposure-time optimization. Full spectral outputs include wavelength-dependent signal-to-noise ratio (SNR), source and sky photon counts, noise decomposition by component, and simulated extracted spectra. An interactive web interface, together with a REST API and a command-line tool, complete the user experience and enable batch survey-design workflows.

Figures

Figures reproduced from arXiv: 2608.00193 by Alessio Mucciarelli, Andrea Scaudo, Carmela Lardo, Cristian Vignali, Henri M. J. Boffin, Jose Schiappacasse-Ulloa, Marco Landoni, Margherita Talia, Matteo Ferro, Matteo Genoni, Michele Moresco, Olga Bellido-Tirado, Roelof S. de Jong, Roland Bacon, Sofia Randich, Vincenzo Mainieri.

Figure 1
Figure 1. Figure 1: WST fields of view compared to other facilities. The MOS covers a 2-degree diameter focal plane (3.1 deg [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Reference telescope optical design. an FWHM of 0.13 to 0.30 arcsec at z < 30◦ over the full 2-degree field of view. Optical fibres are positioned in the MOS focal plane by a dedicated 32,000-unit robotic positioner. The IFS optical path includes a 1-meter deformable mirror providing GLAO correction, conjugated to an altitude of 100 m above the ground. The IFS optical train achieves excellent image quality … view at source ↗
Figure 3
Figure 3. Figure 3: The Sky & Atmosphere tab of the pyetc wst web interface (see Section 4.2). From top to bottom: airmass, precipitable water vapour (PWV, mm), lunar fraction of lunar illumination (FLI, 0–1), moon–target angular separation (degrees), and seeing FWHM at 5000 ˚A. The interface validates the geometric consistency of the airmass and moon altitude in real time (orange feedback line). The GLAO checkbox activates t… view at source ↗
Figure 4
Figure 4. Figure 4: The Target tab of the pyetc wst web interface. Left: spectral energy distribution selector (SED type, template, redshift). Centre: brightness panel (magnitude system, magnitude, and normalisation filter). Right: spatial morphology selector. where Ssrc and Ssky are the source and sky counts coadded over Npix = Nsp × Nxy pixels per DIT, d is the dark-current rate, and σRON is the per-pixel read-out noise. Th… view at source ↗
Figure 5
Figure 5. Figure 5: The SNR & Time tab of the pyetc wst web interface (see Section 4.2). The drop-down menu exposes the four computation modes: DIT & NDIT (compute SNR for fixed exposure parameters), DIT & SNR (find NDIT for a target SNR), NDIT & SNR (find DIT for a target SNR), and Best combination (optimise DIT–NDIT jointly). The Use spectral window for SNR checkbox activates averaging of the SNR over a user-specified wavel… view at source ↗
Figure 6
Figure 6. Figure 6: Simulated 1D raw spectrum for a MARCS cool-giant template, as recorded by the IFS blue and red channels. [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: The Configurations tab of the pyetc wst web interface. Instrument channels are selected individually via colour-coded checkboxes grouped by mode (IFS, MOS-HR, MOS-LR), with Select All and Deselect All shortcuts. Below, the spectral co-adding factor, spatial co-adding aperture (N × N spaxels for IFS), and object–fibre displacement (arcsec, for MOS) are set. All selected channels are computed simultaneously … view at source ↗
Figure 8
Figure 8. Figure 8: Instrument throughput (no atmosphere) for all WST spectral channels as a function of wavelength (preliminary [PITH_FULL_IMAGE:figures/full_fig_p011_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: SNR per spectral pixel (rebinned by 5 ˚A for display) for a V = 19 A0V star, 6×600 s, seeing = 0.8 ′′, AM = 1.2, dark sky, PWV = 3.5 mm. Top left: IFS Blue. Top right: IFS Red. Bottom left: MOS-LR Green. Bottom right: MOS-HR Blue. Horizontal dashed and dotted lines mark SNR = 5 and 10, respectively [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: IFS surface-brightness limiting magnitude (SB AB, [PITH_FULL_IMAGE:figures/full_fig_p012_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: MOS-LR limiting magnitude (AB, r-SDSS; SNR = 3 per resolution element, 3×1200 s, seeing 0.75′′, AM = 1.2) as a function of wavelength for dark (solid), grey (dashed), and bright (dotted) sky. The four channels (blue, green, yellow, red) are shown separately. 650 700 750 800 850 900 950 0 20 40 60 80 T otal n oise (e / spectral pixel) IFS Red V = 19 (A0V), 6×600 s, dark sky, seeing=0.8 00 650 700 750 800 8… view at source ↗
Figure 12
Figure 12. Figure 12: Noise decomposition for IFS Red, V = 19 A0V source, 6 × 600 s, dark sky. Top: total noise in e− per spectral pixel (rebinned by 15 ˚A). Bottom: fractional noise contributions by source, sky, read-out noise (RON), and dark current [PITH_FULL_IMAGE:figures/full_fig_p013_12.png] view at source ↗

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This paper was first reviewed by deepseek-v4-flash on August 4, 2026.