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REVIEW 3 major objections 4 minor 7 cited by

TiDES: The 4MOST Time Domain Extragalactic Survey

T0 review · 3 major / 4 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read The planned TiDES survey could build a 143,000-supernova Hubble diagram and pin dark energy's equation-of-state parameter to 1.2 per cent.

desk verdict A transparent, well-built survey-design forecast; the sub-2% w headline is statistical-only and assumes perfect photometric typing, but the paper states both assumptions clearly. read the letter →

arxiv 2501.16311 v2 pith:V27TNA3R submitted 2025-01-27 astro-ph.HE astro-ph.COastro-ph.GA

C. Frohmaier , M. Vincenzi , M. Sullivan , S.F. Hönig , M. Smith , H. Addison , T. Collett , G. Dimitriadis
show 19 more authors
R. S. Ellis P. Gandhi O. Graur I. Hook L. Kelsey Y. L. Kim C. Lidman K. Maguire L. Makrygianni B. Martin A. Möller R. C. Nichol M. Nicholl P. Schady B. D. Simmons S. J. Smartt E. Tempel P. Wiseman the LSST Dark Energy Science Collaboration
This is my paper · ORCID
classification astro-ph.HEastro-ph.COastro-ph.GA
keywords surveystypeIasupernovaedarkenergycosmologyspectroscopicfollow-upreverberationmappingactivegalacticnuclei4MOST
topics Dark Energy
open problems Dark Energy
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

TiDES is a planned five-year spectroscopic follow-up survey on the 4MOST facility, designed to turn the Rubin Observatory's LSST transient stream into the largest ever sample of cosmologically useful type Ia supernovae. The paper simulates both surveys end to end and argues that TiDES will assemble a Hubble diagram of at least 143,000 SNe Ia—about 12,600 with live TiDES spectra and roughly 131,000 photometrically typed SNe Ia with host-galaxy redshifts—and measure the dark-energy equation-of-state parameter $w$ to a statistical-only precision of $\sigma(w)=0.012$ in a flat $w$CDM model with a CMB prior. That is a factor of ten tighter than the DES-SN5YR forecast the paper uses as its benchmark. The same survey is projected to obtain more than 30,000 live transient spectra, covering core-collapse, superluminous, and rare fast/faint classes, and to run a reverberation-mapping campaign on 700–1,000 AGN that extends an independent Hubble diagram to $z\sim2.5$. A sympathetic reader would care because the paper is a test of whether a modest, fixed fibre allocation can unlock the cosmological and astrophysical potential of the LSST alert stream.

What carries the argument

The argument is carried by an end-to-end catalogue-level simulation pipeline rather than by a single analytic identity. LSST OpSim observing patterns are converted into SNANA inputs, which generate realistic light curves from spectral templates and a host-galaxy library; a TiDES selection function mimics real-time triggering of live transients and faded-host targets; the 4MOST Facility Simulator (4FS) allocates fibres and schedules a mock five-year survey alongside other 4MOST programmes; and mock spectra are produced with the 4MOST exposure-time calculator and judged against per-survey Spectral Success Criteria—mean SNR of 5 per 15 Å for live SN classification, SNR of 3 per Å for host-galaxy redshifts, and SNR of 10 per 15 Å for AGN. For cosmology, the surviving SNe Ia are fit with SALT2, distances are estimated with the Tripp formula, selection effects are corrected with BBC, and parameters are extracted with the wfit minimiser in SNANA. This chain converts fibre-hour accounting into a predicted $\sigma(w)$.

What would settle it

A concrete calculation that would settle the claim: pass the simulated LSST light curves through a realistic photometric classifier with a measured confusion matrix, re-run the same bias-correction and cosmological fit, and compare the recovered uncertainty on $w$ with the paper's 0.012; if realistic contamination pushes $\sigma(w)$ above 2 per cent, the headline forecast depends on the perfect-typing assumption.

Watch

Extended reading notes

Core claim

The paper's central claim is that the TiDES fibre budget—roughly 30–35 low-resolution fibres per 4MOST pointing, about 250,000 fibre-hours over five years—is sufficient to create a SN Ia sample an order of magnitude larger than today's best surveys. In the simulations, the live-transient programme yields about 18,000 SNe Ia with spectra at SNR per 15 Å of at least 3 (12,600 of them pass the SALT2 'cosmologically useful' cuts), while the host-galaxy programme yields about 131,000 photometrically identified SNe Ia with host spectroscopic redshifts. Combining these with a low-redshift sample of 2,400 SNe Ia and a Planck prior, the paper forecasts $\sigma(w)=0.012$ for a flat $w$CDM model, quoting this as a sub-2 per cent measurement and a factor-of-ten improvement over a DES-SN5YR-like simulation; for a flat $w_0w_a$CDM model the figure of merit is 85, or 99 when combined with a DESI BAO Y1 prior, and is 15 times larger than the DES-SN5YR figure of merit. The paper also claims this one survey will enlarge the spectroscopically confirmed transient population by an order of magnitude, including over 9,000 core-collapse SNe and about 3,000 hydrogen-poor superluminous SNe, and will deliver one of the largest reverberation-mapped AGN samples over $0.1<z<2.5$, with 700–1,000 targets across the four deep fields.

Load-bearing premise

The 131,000-host supernova sample—the bulk of the Hubble diagram—is assumed to be perfectly classified as standard type Ia supernovae from their light curves alone; if even a small fraction of those events are actually a different kind of explosion, the distance estimates and the sub-2 per cent dark-energy claim would not hold.

Editorial extensions

If this is right

  • If the forecast holds, SN Ia cosmology becomes statistics-limited far below current systematic budgets, shifting the field's bottleneck to photometric typing purity, bias corrections, and distance-estimator systematics.
  • The roughly 12,600 live SN Ia spectra will form a large, homogeneous training set for photometric classifiers, potentially extending the cosmological sample beyond TiDES hosts to the full LSST SN Ia population.
  • The order-of-magnitude expansion of spectroscopically confirmed transients, including rare classes such as calcium-strong transients and tidal disruption events, would sharpen measured rates and map the luminosity–timescale plane far more completely than current samples.
  • The AGN reverberation-mapping sample provides a second, independent standardisable candle out to $z\sim2.5$, allowing a cross-check of the SN Ia dark-energy measurement and dynamical supermassive black hole masses at cosmic noon.
  • Host-galaxy spectroscopy will tie SN Ia distances to environmental properties such as stellar mass, metallicity, and star-formation rate, enabling tests of whether environment-dependent corrections reduce Hubble residuals.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The paper's headline forecast treats the 131,000-object host-redshift sample as perfectly typed from light curves; a natural next calculation is to inject a realistic classifier confusion matrix into the BBC pipeline and quantify how much of $\sigma(w)=0.012$ is carried by that assumption.
  • Once real data arrive, the overlap between TiDES-Live and TiDES-Hosts provides a built-in empirical check of photometric typing purity—spectroscopically classified SNe within the host-selected sample can be used to measure contamination directly and re-weight the Hubble diagram.
  • The AGN programme's yield depends on maintaining the simulated 14-day cadence and season lengths in the deep fields; if the actual 4MOST schedule delivers shorter baselines, the number of recovered lags and the reach of the $z\sim2.5$ Hubble diagram will shrink accordingly.
  • Because other 4MOST surveys will observe millions of galaxies, many SN hosts will acquire redshifts without TiDES fibre-hours, so the effective host sample may be larger or cheaper than simulated, which would justify re-optimising the fibre split among the three TiDES programmes.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. The paper introduces TiDES, the 4MOST Time Domain Extragalactic Survey, and uses end-to-end catalogue-level simulations of LSST and 4MOST to forecast the survey's yields and cosmological reach. Three programmes are described: TiDES-Live (spectroscopy of live transients), TiDES-Hosts (host-galaxy redshifts for photometrically classified SNe), and TiDES-RM (reverberation mapping of AGN in the LSST deep drilling fields). The cosmology forecast combines ~12,600 spectroscopically confirmed SNe Ia with ~131,000 photometric SNe Ia having host-galaxy redshifts and an external low-z sample of 2,400 SNe, then applies SALT2 light-curve fits, BBC bias corrections, and wfit to derive constraints. In a flat wCDM model with a CMB prior, the authors report a statistical-only uncertainty of sigma(w)=0.012, a factor of 10 smaller than their DES-SN5YR comparison, and a w0-wa Figure of Merit of 85 (99 with a DESI-BAO-Y1-like prior).

Significance. If the forecast is realized, TiDES would deliver a Hubble diagram of order 143,000 SNe Ia, an order-of-magnitude leap over current SN Ia samples. The paper's strengths are its transparent simulation chain, the use of the 4MOST facility simulator and exposure-time calculator to produce mock spectra, the explicit inclusion of multiple non-Ia transient classes in the simulation, and the clear statement in Section 5.3 that the quoted constraints are statistical-only. The central claim, however, rests on several assumptions that are acknowledged but not stress-tested, most importantly perfect photometric typing of the 131,000-host sample that dominates the cosmological forecast. The abstract also presents the headline precision without the statistical-only caveat. The result is a useful survey description and a defensible first forecast, but the sub-2% w claim is not yet established as robust against realistic classification contamination.

major comments (3)
  1. [§5 (first paragraph) and §5.2] The assumption of perfect photometric typing for the ~131,000 host-sample SNe Ia is load-bearing. The forecast pipeline in Sections 5.1-5.3 applies SALT2 quality cuts and BBC bias corrections but includes no contamination term: the simulated non-Ia populations of Table 1 are removed perfectly by construction, as stated in the opening of Section 5. Realistic photometric classifiers have a few per cent contamination, dominated by core-collapse SNe at z>0.3 and by 91bg/Iax events at low z; even 1% contamination of the 131,000-host sample would inject ~1,300 non-Ia events with biased distance estimates that the 1D BBC corrections, estimated from the same contamination-free simulation, cannot remove. The paper should include a contamination-inclusive forecast or an analytic degradation estimate before claiming sub-2% w precision; as written, the claim is an upper limit under a perfect-classification scenario.
  2. [Abstract and §6] The abstract's claim of being 'capable of a sub-2 per cent measurement of the equation-of-state of dark energy' omits the qualifier that this is a statistical-only uncertainty, even though Section 5.3 and the final bullet of Section 6 explicitly describe the result as 'statistical-only precision.' Section 1 itself notes that current SN samples have a systematic error budget comparable to the statistical uncertainty. The abstract and the first paragraph of Section 6 should state the statistical-only caveat, otherwise the headline claim is materially stronger than the forecast supports.
  3. [§5 (external low-z sample)] The forecast includes an external low-z sample of 2,400 SNe, but the text immediately notes that this sample size 'will only be achieved towards the end of 10-years of LSST operations, even though TiDES is expected to conclude after the first five years of LSST.' The contours in Figures 12 and 13 therefore do not represent a standalone 5-year TiDES projection; they assume a post-TiDES external sample whose availability is itself a scheduling assumption. The paper should present this explicitly as a scenario with an external low-z sample and, ideally, show how the constraints degrade without it.
minor comments (4)
  1. [§4.2] There is a typo in the sentence 'we assume every galaxy reaching our SSC has had a redshift sucessfully measured': 'sucessfully' should be 'successfully'.
  2. [§5.3] The code name 'wfit.exe' should be formatted as a code/software name without the '.exe' suffix, or the suffix should be explained if it is intentional.
  3. [Table 1 caption] The table caption contains a stray space in 'T able 1'; it should read 'Table 1'.
  4. [§6 and Figure 12 caption] In the Section 6 bullet, 'equations-of-state parameter' should be 'equation-of-state parameter', and 'at-least 143 000 objects' should be 'at least 143 000 objects'; in Figure 12, 'dotted-dashed contours' is more conventionally rendered as 'dot-dashed contours'.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: TiDES's sub-2% w forecast is a self-contained simulation projection, not a fitted result.

full rationale

The paper's central claim, a statistical-only uncertainty of 0.012 on w, is a forecast derived from an explicit end-to-end simulation pipeline described in Sections 3 through 5, not a measurement fitted to the quantity it claims to predict. SNe Ia are simulated with SALT2 using assumed cosmology, rates, and templates; LSST and 4MOST strategies are simulated; light curves are fit with SALT2; BBC bias corrections are estimated from the same simulated survey and applied; and the final covariance is computed with wfit. Estimating selection corrections from the same simulation is self-referential in the sense that the forecast inherits all simulation assumptions, but it is not definitionally circular: the output uncertainty is computed from the statistical covariance of the simulated sample, not assumed as an input, and no fitted parameter is renamed as a prediction. The assumption of perfect photometric typing for the 131,000-host sample is a strong limitation on the realism of the forecast, and the abstract's 'sub-2 per cent' phrasing drops the 'statistical-only' caveat stated in Section 5.3, but these are accuracy and robustness concerns, not circularity. Self-citations in the paper, such as V19 templates and Frohmaier et al. rates, supply externally anchored empirical inputs rather than the target result. The comparison against a DES-SN5YR-like simulation and the external low-z sample provides an external benchmark. Therefore, no specific circular step can be quoted, and the score is 0.

Assumptions & free parameters 6 free parameters · 7 assumptions · 0 invented entities

The simulation forecast depends on a large number of input parameters and modeling assumptions inherited from prior literature, most of which are not fitted in this paper. Key adopted parameters are listed as free parameters, and the most load-bearing modeling assumptions are listed as axioms.

free parameters (6)
  • SN Ia stretch-luminosity coefficient alpha = 0.14
    Adopted in Eq. 1; determines simulated SN Ia brightness. Not fitted in this paper.
  • SN Ia colour-luminosity coefficient beta = 3.1
    Adopted in Eq. 1; controls colour correction in simulated distances.
  • SN Ia absolute magnitude M_B = -19.365 mag
    Adopted in Eq. 1; sets the zero-point of the simulated Hubble diagram.
  • SN Ia volumetric rate normalization = Frohmaier et al. (2019) Eq. 6
    Sets the number and redshift distribution of simulated SNe Ia.
  • AGN lag-luminosity relation parameters = Bentz et al. (2009) with 0.9 Mg II scaling; Penton et al. (2022) for C IV
    Used in Section 3.1.3 to estimate lags and build the TiDES-RM target catalog.
  • Target selection thresholds = r < 22.5, SNR15A >= 3 or 5, host r <= 24, etc.
    Hand-chosen in Section 3.5; directly determines which simulated transients and hosts are followed.
assumptions (7)
  • domain assumption Flat wCDM cosmology with Omega_M = 0.315 and H0 = 70 km/s/Mpc
    Baseline cosmology stated in Section 1 and used for all distance calculations.
  • domain assumption SALT2 SED model accurately represents SN Ia spectra and light curves
    Used in Section 3.1.1 to generate SN Ia photometry and in Section 5.1 to fit light curves.
  • domain assumption LSST OpSim v3.4 baseline and the 4MOST mock strategy are representative of the real surveys
    The whole forecast depends on these simulated observing strategies; Section 3 notes neither LSST nor 4MOST strategy is final.
  • ad hoc to paper Perfect photometric typing for host-sample SNe Ia
    Section 5 assumes all host-galaxy SNe without live spectra are correctly typed; this underpins the 131,000-object Hubble diagram.
  • ad hoc to paper Every galaxy reaching the SNR>=3 per Angstrom criterion has a reliable redshift
    Section 4.2 states this; it converts the host galaxy SSC into a guaranteed redshift measurement.
  • ad hoc to paper The external low-z sample (2,400 SNe) will be available during TiDES analysis
    Section 5 states this sample may only be complete after 10 years of LSST, longer than TiDES's 5-year campaign, yet it is included in the forecast.
  • domain assumption AGN reverberation mapping will recover lags for the selected targets
    Section 3.1.3 assumes lag recovery for lags shorter than 600 days and that SNR15A=10 in single visits every ~14 days suffices; no RM simulation is presented.

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Cite this review

Pith. "Pith review of TiDES: The 4MOST Time Domain Extragalactic Survey." pith.science (2026). https://pith.science/paper/V27TNA3R

@misc{pith2026250116311,
  author       = {Pith},
  title        = {Pith review of: TiDES: The 4MOST Time Domain Extragalactic Survey},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/V27TNA3R}},
  note         = {Machine review of arXiv:2501.16311}
}
abstract

The Time Domain Extragalactic Survey (TiDES) conducted on the 4-metre Multi-Object Spectroscopic Telescope (4MOST) will perform spectroscopic follow-up of extragalactic transients discovered in the era of the NSF-DOE Vera C. Rubin Observatory. TiDES will conduct a 5-year survey, covering ${>}14\,000\,\mathrm{square\, degrees}$, and use around 250 000 fibre hours to address three main science goals: (i) spectroscopic observations of ${>}$30 000 live transients, (ii) comprehensive follow-up of ${>}$200 000 host galaxies to obtain redshift measurements, and (iii) repeat spectroscopic observations of Active Galactic Nuclei to enable reverberation mapping studies. The live spectra from TiDES will be used to reveal the diversity and astrophysics of both normal and exotic supernovae across the luminosity-timescale plane. The extensive host-galaxy redshift campaign will allow exploitation of the larger sample of supernovae and improve photometric classification, providing the largest-ever sample of type Ia supernovae, capable of a sub-2 per cent measurement of the equation-of-state of dark energy. Finally, the TiDES reverberation mapping experiment of 700-1,000 AGN will complement the SN Ia sample and extend the Hubble diagram to $z\sim2.5$.

Figures

Figures reproduced from arXiv: 2501.16311 by the authors.

Figure 1
Figure 1. Flowchart of our end-to-end simulation framework. We begin with a database input of a LSST OpSim realisation that is transformed into an snana SIMLIB file. Along with transient spectral templates and a host-galaxy library to draw from, we use snana to create realistic light curves of transient phenomena. The resulting database of events is then queried as if data were flowing in real-time, such that we can trigger f… view at source ↗
Figure 2
Figure 2. The overlap in footprints of the 4MOST and LSST surveys. The heatmap represents the number of visits in the wide-fast-deep LSST program under the baseline v3.4 survey strategy during the overlap with 4MOST operations. Due to the non-uniform sky coverage of LSST over this time period, relics of the rolling cadence seasons can be see as density difference along declination stripes. The dashed blue lines represents the… view at source ↗
Figure 3
Figure 3. Mock 4MOST spectra based on the 4MOST ETC output. A typical maximum-light SN Ia template spectrum at several different redshifts (red line) and r-band magnitudes is shown. The template is ‘observed’ by 4MOST with the raw data shown in light grey and then rebinned to 15˚A (black line). The mock spectra are calculated assuming a typical 4MOST exposure time of 2700s, conditions of seeing of 0.8”, airmass 1.4, in grey t… view at source ↗
Figures from the paper (8 more)
Figure 4
Figure 4. Figure 4: The observed 4MOST redshift distribution for all simulated transient types after five years of 4MOST opera￾tions. The solid lines show the expected number of transients with a SNR15˚A ≥5, while the dashed lines show the expec￾tation for a SNR15˚A ≥ 3 in the spectrum’s …
Figure 6
Figure 6. Figure 6: Example observer-frame light curves of SNe Ia from LSST are shown. Each row presents light curves over different redshift ranges, with the dotted line showing the depth of 4MOST after 1-hour integrated exposure (the maximum exposure for a single visit). The pink arrows…
Figure 7
Figure 7. Figure 7: For the live-SNe Ia observed by 4MOST, we compare the phase at which we trigger follow-up requests to the phase the first spectrum was eventually taken in the rest-frame. In our simulations, the vast majority of our SNe Ia were identified and sent to 4MOST before maxim…
Figure 8
Figure 8. Figure 8: The distribution of the SNR15˚A parameter for SNe Ia is shown and split across several different redshifts bins. The shape of the distribution is dictated both by the supernova phase at which the spectrum was acquired and by the exposure time of the 4MOST observation. …
Figure 9
Figure 9. Figure 9: The fraction of spectra, split by SNR15˚A ≥ 3 (red) and ≥ 5 (blue), as a function of the object’s redshift is shown for our SNe Ia sample. In the top panel, we show the efficiency for all SNe Ia 4MOST attempted to observe. In the bottom panel we show the fraction of al…
Figure 11
Figure 11. Figure 11: The TiDES Hubble Diagram made up of the final SN Ia sample presented in Section 5. The upper panel shows the redshift distribution of the TiDES-Live, TiDES-Hosts, and low-z sample (D. O. Jones et al. 2019). The lower panel shows the residuals in the redshift bins from…
Figure 12
Figure 12. Figure 12: ΩM − w contours for the simulated LSST+TiDES-Live and LSST+TiDES-Host combined (filled contours). For comparison, we present the cosmological con￾tours from a DES-SN5YR-like simulation (dotted-dashed contours). Only statistical uncertainties are included in both the L…
Figure 14
Figure 14. Figure 14: The distribution of light curve trigger phases and the phase of spectroscopic follow up by 4MOST is shown, broken down into transient sub-types. All phases are measured relative to the light curve peak. The methodology used to generate this figure is identical to that…

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Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.