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REVIEW 2 major objections 3 minor 140 references

A search of 465,610 DESI galaxies finds three new tidal-disruption 'light echoes' — galaxies whose extreme coronal emission lines betray a past stellar shredding — and measures a per-galaxy rate consistent with earlier surveys.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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2026-08-03 07:08 UTC pith:4OB4QGOO

load-bearing objection Careful, incremental DESI EDR extension of the SLEIPNIR ECLE search: three new TDE-ECLE candidates and a z≈0.2 rate, with a single-anchor visibility-time calibration that deserves a systematic-error term. the 2 major comments →

arxiv 2601.20964 v2 pith:4OB4QGOO submitted 2026-01-28 astro-ph.HE

Early results in the search for extreme coronal line emitters with the Dark Energy Spectroscopic Instrument

Peter Clark , Joseph Callow , Or Graur , Alexei V. Filippenko , Thomas G. Brink , WeiKang Zheng , Jessica Aguilar , Steven Ahlen
show 39 more authors
Segev BenZvi Davide Bianchi David Brooks Todd Claybaugh Andrei Cuceu Axel de la Macorra Arjun Dey Peter Doel Jaime E. Forero-Romero Enrique Gazta\~naga Satya Gontcho A Gontcho Gaston Gutierrez Victoria Fawcett Mustapha Ishak Jorge Jimenez Dick Joyce Stephanie Juneau Theodore Kisner Anthony Kremin Martin Landriau Laurent Le Guillou Marc Manera Aaron Meisner Ramon Miquel John Moustakas Seshadri Nadathur Will J. Percival Francisco Prada Ignasi P\'erez-R\`afols Graziano Rossi Eusebio Sanchez David Schlegel Michael Schubnell Joseph Harry Silber David Sprayberry Gregory Tarl\'e Benjamin A. Weaver Rongpu Zhou Hu Zou
This is my paper
classification astro-ph.HE
keywords extreme coronal line emitterstidal disruption eventsDESIcoronal linesactive galactic nucleimid-infrared variabilitytransient ratesgalaxy spectroscopy
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.

This paper reports the first systematic search for extreme coronal line emitters (ECLEs) in the Early Data Release of the Dark Energy Spectroscopic Instrument, identifying three galaxies whose strong, high-ionization iron lines likely arise from tidal disruption events (TDEs). Using those three detections and a Monte Carlo visibility-time calculation, the authors measure a galaxy-normalized TDE-linked ECLE rate of 5 (+5/-3) × 10^-6 per galaxy per year at median redshift z ≈ 0.2, broadly consistent with rates from SDSS and BOSS surveys. The search also yields more than 200 coronal-line AGNs, the primary astrophysical contaminants in TDE searches, providing a reference catalogue. The result matters because it demonstrates that DESI can discover these rare nuclear transients and because it tightens the fraction of TDEs that produce coronal-line echoes.

Core claim

The central discovery is that DESI's Early Data Release contains three new TDE-linked ECLEs — Pidgeot, Raticate, and Raichu — identified by the SLEIPNIR pipeline and confirmed through multi-wavelength follow-up, and that the resulting galaxy-normalized rate, R_G = 5 (+5/-3) × 10^-6 galaxy^-1 yr^-1 at z ≈ 0.2, is consistent with previous SDSS Legacy and BOSS LOWZ rates. The paper also strengthens the mid-infrared colour-luminosity relation for coronal-line TDEs: objects with brighter MIR flares show more significant reddening at outburst, now quantified with quadratic and linear fits to the ΔW2 versus ΔW1 and Δ(W1-W2) versus ΔW2 relations.

What carries the argument

SLEIPNIR, a custom Python pipeline that flags ECLE candidates by scoring detections of iron coronal lines ([FeVII], [FeX], [FeXI], [FeXIV]) against strict criteria, with detection efficiency measured by planting simulated coronal lines into 10,000 real DESI spectra. The rate calculation rests on a visibility-time method: TDE peak X-ray luminosities are sampled from a luminosity function, converted to coronal line strengths using a linear scaling anchored to the TDE AT 2017gge (S_max/S_gge = L_max/L_gge), and evolved as power-law declines over 10 years, with cosmological time dilation accounted for per galaxy redshift.

Load-bearing premise

The rate calculation assumes that a TDE's peak coronal line strength scales linearly with its peak X-ray luminosity, using the single object AT 2017gge to set the proportionality; if that scaling is not universal, the visibility times and hence the rate shift systematically.

What would settle it

Measure peak X-ray luminosity and peak coronal line strength for a sample of a dozen coronal-line TDEs; if the ratio S_max/L_max scatters widely around AT 2017gge's value, the linear scaling used in Equation 4 is invalid and the reported rate would need revision. Alternatively, re-running the visibility-time calculation with a nonlinear scaling and comparing the resulting rate to the observed number of detections would settle whether the anchor assumption biases the result.

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

If this is right

  • The full DESI survey is expected to yield roughly 35–50 new TDE-linked ECLEs, enabling rate measurements with much smaller Poisson uncertainties.
  • The new rate point extends the galaxy-normalized ECLE rate versus stellar mass relation and keeps it consistent with the theoretical minimum TDE rate, implying that only a subset (roughly 5–50%) of TDEs produce observable coronal lines.
  • The 205-object CrL-AGN sample provides a reference catalogue of the primary astrophysical contaminants in optical searches for TDE-linked ECLEs.
  • The strengthened Δ(W1-W2) versus ΔW2 relation for coronal-line TDEs offers a mid-infrared colour diagnostic that can help separate TDEs from AGN flares.

Where Pith is reading between the lines

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

  • Because the rate rests on a single anchor object, future samples of a dozen coronal-line TDEs with both X-ray and coronal-line measurements would either validate or break the linear scaling; if the scatter is large, the quoted rate uncertainties are underestimated and the rate itself would need recalibration.
  • The paper notes galaxies with [NeV] but no [FeVII] emission despite nearly identical ionization energies; this suggests the [NeV]/[FeVII] ratio could serve as a sensitive probe of the softness of the X-ray ionizing continuum, a diagnostic worth testing on the full DESI sample.
  • The hint that the volumetric ECLE rate is higher than the BOSS LOWZ rate, if confirmed with complete DESI data, would support the theoretical expectation that TDE rates decline with redshift, tying ECLE rates to the cosmic evolution of tidal disruptions.

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 / 3 minor

Summary. This paper presents a systematic search of the DESI Early Data Release for extreme coronal line emitters (ECLEs) using the SLEIPNIR pipeline. After processing 465,610 galaxies, the authors identify 208 galaxies with Fe coronal lines and, through a multi-wavelength classification involving optical/NIR/MIR photometry, archival spectra, and new follow-up spectroscopy, classify three objects (Pidgeot, Raticate, Raichu) as TDE-linked and the remaining ~205 as AGN-related. Using the visibility-time formalism of Callow et al., calibrated with the Sazonov X-ray TDE luminosity function, the AT 2017gge coronal-line anchor, and a power-law decline over 10 years, they derive a galaxy-normalized TDE-ECLE rate R_G = 5(+5,-3) × 10^-6 galaxy^-1 yr^-1 at median z = 0.2, together with mass-normalized and volumetric rates, and compare these with previous SDSS, BOSS, and literature TDE rates. They also update the MIR colour-luminosity relation for coronal-line TDEs.

Significance. If the rate estimate holds, the paper roughly doubles the known sample of TDE-linked ECLEs and demonstrates that DESI EDR is an effective discovery engine for nuclear transients. The reported rate is broadly consistent with previous ECLE rates and strengthens the conclusion that only a fraction of TDEs produce strong coronal lines. The paper's strengths are its transparency and reproducibility: the search code is public, the detection efficiency is measured with simulated DESI spectra, the false-positive sources are discussed in detail, and the sample is cross-checked against an independent DESI EDR ECLE search. The multi-epoch spectroscopy and WISE/NEOWISE analysis for the three TDE candidates are careful. The main weakness is that the galaxy-normalized rate rests on a single-object, host-independent calibration between X-ray luminosity and coronal-line strength; this calibration is not included in the quoted uncertainty budget and could shift the rate outside the stated errors.

major comments (2)
  1. [§6.2.1, Eq. (4); Table 13] The rate denominator is controlled by Eq. (4), S_max/S_gge = L_max/L_gge, where S is a pseudoequivalent width (pEQW) as used in the detection-efficiency simulation of §3.3. For a fixed line luminosity, pEQW is inversely proportional to the host-galaxy continuum, so Eq. (4) predicts a pEQW from X-ray luminosity with no dependence on the host. The DESI EDR sample spans stellar masses down to ~10^7 M_sun (Fig. 5), and the same TDE would have substantially different visibility times in a faint versus luminous host. Table 13 includes uncertainties on S_gge and L_gge but not this host-continuum systematic. I recommend validating Eq. (4) with the other ~13 known CrL-TDEs, or converting S to line luminosity and applying per-galaxy continua from FastSpecFit, and adding the resulting systematic to the rate budget. A factor-of-two change in the summed visibility time shifts R_G outside the quoted P
  2. [§6.2.1, Eq. (5); Table 13] The visibility-time integral is truncated at 10 years. The power-law index is sampled down to -5/12, for which the decline over 10 years from the 218-day anchor is only a factor of roughly 0.3; a substantial fraction of the simulated population could remain above the ~1.3 Å detection threshold after the truncation. The uncertainty budget in Table 13 does not include the choice of the 10-year cutoff. Please report the sensitivity of R_G to t_max (e.g., 5, 10, and 20 years) and include the cutoff as a systematic uncertainty if it is non-negligible.
minor comments (3)
  1. [§5.1.1, §5.1.2, §5.2.2, §5.2.3; Table 11] Several DESI target IDs in the section headings do not match Table 11. For example, §5.1.1 and §5.1.2 both list DESI 39627794400938039, while Table 11 assigns Pidgeot = 39633332819985805 and Raticate = 39627794400938039. Similar conflicts occur for Charizard and Fearow. Please correct the headings so each object has a unique, consistent ID.
  2. [Section 1, Section 6] The Introduction refers to 'Appendix 5.2' for the CrL-AGN sample; this should likely be Appendix D or a proper section number. There is also a typo in Section 6 ('we disuses') and a repeated word in the caption of Fig. 28 ('x' after Ciii).
  3. [Table 13] The entries 'AT2017gge peak CrL strength' and 'AT2017gge peak luminosity' are propagated from a single object. Clarify in the table notes that these do not include any host-continuum or transferability systematic, and that such a systematic is not yet estimated.

Circularity Check

0 steps flagged

No significant circularity: the ECLE rate is derived from detections and externally anchored visibility-time inputs, not from a fit or self-citation chain.

full rationale

The central rate R_G = N_ECLE / sum t_v,i (Eq. 6) is not an output of any fit that uses the three detections as input parameters. N_ECLE = 3 is a measured count from the DESI EDR search. The visibility-time denominator is constructed independently of those detections: peak X-ray luminosities are sampled from the Sazonov et al. (2021) luminosity function, mapped to coronal-line strengths through the single-object anchor AT2017gge (Eq. 4), evolved with theoretical power-law indices, and convolved with the detection efficiency measured by planting known ECLE lines into 10,000 simulated DESI spectra (Section 3.3). None of these inputs is adjusted to make the resulting rate match previous values; the comparison to SDSS Legacy, BOSS LOWZ, and literature TDE rates is an external consistency check, not a fit. The self-citations to Callow et al. (2024, 2025) describe the SLEIPNIR code and the visibility-time method, but the present paper re-states and re-implements the method with independent anchors, and it does not invoke any self-cited uniqueness theorem or forbid alternatives by citation. The single-object calibration underlying Eq. 4 is a legitimate scientific concern about host-galaxy transferability and calibration uncertainty, but it is not circular: the scaling is not defined in terms of the rate it is used to compute. No load-bearing step reduces by construction to its own inputs.

Axiom & Free-Parameter Ledger

4 free parameters · 4 axioms · 0 invented entities

The rate calculation depends on four hand-chosen or single-object-calibrated parameters and on several domain assumptions about TDE luminosities, coronal-line evolution, and candidate classification. No new physical entities are introduced.

free parameters (4)
  • Power-law index for coronal-line fading = Sampled uniformly from -5/3 to -5/12
    The decline of coronal-line strength after a TDE is modelled as a power law with index drawn from the theoretical range. The choice affects the visibility time and hence the rate.
  • X-ray luminosity to coronal-line strength calibration = Smax/Sgge = Lmax/Lgge (AT 2017gge)
    A single-object calibration is used to convert TDE peak X-ray luminosity to peak coronal line strength; this linear scaling is not derived from physics and is a major source of systematic uncertainty.
  • Visibility time integration limit = 10 yr
    Coronal lines are assumed to fade over 10 years, based on the fading of the Wang et al. (2012) sample. Longer or shorter durations change the denominator in the rate.
  • ECLE score threshold = 7 (or 5 for z > 0.24)
    SLEIPNIR flags candidates with an ECLE score above this hand-set threshold; the detection efficiency simulation partly accounts for it, but the threshold is not derived from first principles.
axioms (4)
  • domain assumption TDE X-ray luminosity function of Sazonov et al. (2021)
    The luminosity function is used as the source of TDE peak X-ray luminosities; it is an external model, not standard mathematics.
  • ad hoc to paper Coronal line strength scales linearly with X-ray luminosity (Eq. 4)
    This linear scaling anchored to AT 2017gge is assumed without physical derivation; it is load-bearing for the visibility time calculation.
  • ad hoc to paper Power-law decline with index in [-5/3, -5/12] over 10 years
    The shape and duration of coronal-line evolution after a TDE are assumed from limited empirical/theoretical guidance; no direct measurement for the three candidates.
  • domain assumption Detected ECLEs are TDE-linked (classification reliability)
    The three candidates are classified as TDEs using multi-wavelength diagnostics, but AGN variability remains a possible alternative for at least some; the authors note the rate may be an upper limit.

pith-pipeline@v1.3.0-alltime-deepseek · 58825 in / 11403 out tokens · 120050 ms · 2026-08-03T07:08:07.430748+00:00 · methodology

0 comments
read the original abstract

Here we present the results of our search through the Early Data Release (EDR) of the Dark Energy Spectroscopic Instrument (DESI) for extreme coronal line emitters (ECLEs) - a rare classification of galaxies displaying strong, high-ionization iron coronal emission lines within their spectra. With the requirement of a strong X-ray continuum to generate the coronal emission, ECLEs have been linked to both active galactic nuclei (AGNs) and tidal disruption events (TDEs). We focus our search on identifying TDE-linked ECLEs. We identify three such objects within the EDR sample, highlighting DESI's effectiveness for discovering new nuclear transients, and determine a galaxy-normalized TDE-linked ECLE rate of $R_\mathrm{G}=5~^{+5}_{-3}\times10^{-6}~\mathrm{galaxy}^{-1}~\mathrm{yr}^{-1}$ at a median redshift of z = 0.2 - broadly consistent with previous works. Additionally, we also identify more than 200 AGNs displaying coronal emission lines, which serve as the primary astrophysical contaminants in searches for TDE-related events. We also include an outline of the custom python code developed for this search.

Figures

Figures reproduced from arXiv: 2601.20964 by Aaron Meisner, Alexei V. Filippenko, Andrei Cuceu, Anthony Kremin, Arjun Dey, Axel de la Macorra, Benjamin A. Weaver, David Brooks, Davide Bianchi, David Schlegel, David Sprayberry, Dick Joyce, Enrique Gazta\~naga, Eusebio Sanchez, Francisco Prada, Gaston Gutierrez, Graziano Rossi, Gregory Tarl\'e, Hu Zou, Ignasi P\'erez-R\`afols, Jaime E. Forero-Romero, Jessica Aguilar, John Moustakas, Jorge Jimenez, Joseph Callow, Joseph Harry Silber, Laurent Le Guillou, Marc Manera, Martin Landriau, Michael Schubnell, Mustapha Ishak, Or Graur, Peter Clark, Peter Doel, Ramon Miquel, Rongpu Zhou, Satya Gontcho A Gontcho, Segev Benzvi, Seshadri Nadathur, Stephanie Juneau, Steven Ahlen, Theodore Kisner, Thomas G. Brink, Todd Claybaugh, Victoria Fawcett, Weikang Zheng, Will J. Percival.

Figure 1
Figure 1. Figure 1: Summary of the workflow involved in the processing and classification of the spectra from DESI EDR. Note 1 prior to this point in the workflow, individual spectra are treated independently, following this point all spectra obtained for a single galaxy are used to provide a single classification. such the full sample redshift distribution is not a simple numeric sum of the individual program redshift distri… view at source ↗
Figure 2
Figure 2. Figure 2: Upper left:The redshift distribution of the SLEIPNIR input object sample including a per observational program breakdown highlighting the numeric dominance of the DESI-BGS sample. Note: Each targeted galaxy can be included in the selection for more than one program and as such the full sample redshift distribution is not a simple numeric sum of the individual program redshift distributions. BGS selected ta… view at source ↗
Figure 3
Figure 3. Figure 3: Left: Comparison of the flagging criteria between the number of spectra flagged by SLEIPNIR before and following full classification. The highest fractions of false positives are seen in the those spectra flagged on general score and single strong features. With this being the result of a combination of low SNR, skyline contamination and the effect of single serendipitously located bright artefacts. Right:… view at source ↗
Figure 4
Figure 4. Figure 4: Comparison of the redshift distributions of the DESI input sample and the SLEIPNIR flagged sample of candidate coronal line galaxies (solid black and dot-dashed purple curves, respectively). We also include the distri￾butions of the coronal line galaxies selected from searches of SDSS Legacy and BOSS LOWZ galaxy samples (red dashed and blue dotted curves, re￾spectively; Callow et al. 2024, 2025). The EDR c… view at source ↗
Figure 6
Figure 6. Figure 6: DESI Legacy Survey grz composite images of each of the EDR ECLE candidates. Top row: Candidates identified as being TDE-related fol￾lowing full classification. Lower rows: Candidates identified as being AGN￾related following full classification. Dashed circle indicates the location of the DESI fibre used to obtain each object’s spectrum. the quality of its line profile and making a definitive detection of … view at source ↗
Figure 7
Figure 7. Figure 7: MIR evolution of the EDR-ECLE candidates. Top row: Candidates linked to TDE activity following full classification. Bottom row: Candidates linked to AGN activity following full classification. Left panels: Relative change in W1 compared to observed W1 peak. Middle panels: Relative change in W2 compared to observed W2 peak. Right panels: W1–W2 colour evolution. The dashed horizontal line shown is the AGN/no… view at source ↗
Figure 8
Figure 8. Figure 8: 2MASS photometric diagnostic plot for the DESI EDR TDE-ECLE candidates. Filled markers indicate candidates linked to TDEs following over￾all classification. Hollow markers indicate candidates which have been ruled out as being TDE linked following overall classification. NIR classification based on Hyland & Allen (1982) and Komossa et al. (2009). As described by Clark et al. (2024), whilst NIR classificati… view at source ↗
Figure 9
Figure 9. Figure 9: In all panels spectra have been rebinned to a shared 2 Å wavelength regime, but have not otherwise been smoothed. Top row: Spectral evolution of Pidgeot. Second and third rows: Comparison between the spectral features of most interest between the DESI and Keck+LRIS spectra. Clear reductions in [Fe vii] λ5722Å, [Fe vii] λ6088Å and [Ne v] λ3427Å line strength are observed, in contrast to increasing [O iii] λ… view at source ↗
Figure 10
Figure 10. Figure 10: Photometric evolution of Pidgeot. Top left: ZTF forced photometry difference magnitude light curve. Bottom left: ATLAS forced photometry light curve presented in flux space. Right: LT absolute magnitude light curve. nificant changes, with the Fe CrLs well recovered in Gemini+GMOS spectrum and remaining unchanged. Likewise, photometric follow￾up with the LT (later supplemented with analysis of ATLAS and ZT… view at source ↗
Figure 11
Figure 11. Figure 11: In all panels spectra have been rebinned to a shared 2 Å wavelength regime, but have not otherwise been smoothed. Top row: Spectral evolution of Raticate. Second and third rows: Comparison between the spectral features of most interest between the DESI and Keck+LRIS spectra. Bottom row: BPT diagnostic diagrams for the DESI spectrum. The NOT+ALFSOC spectrum is not included in these subplots due to a wavele… view at source ↗
Figure 12
Figure 12. Figure 12: Photometric evolution of Raticate. Top left: ZTF forced photometry difference magnitude light curve. Bottom left: ATLAS forced photometry light curve presented in flux space. Right: LT absolute magnitude light curve. radio sources are observed in either VLA-FIRST or VLASS. The lack of long-term spectral variability of the coronal lines, optical emission line diagnostics an both NIR and MIR photometric dia… view at source ↗
Figure 13
Figure 13. Figure 13: In all panels spectra have been rebinned to a shared 2 Å wavelength regime, but have not otherwise been smoothed. Top row: Spectral evolution of Raichu. Second and third rows: Comparison between the spectral features of most interest between the DESI and Keck+LRIS spectra. Bottom row: BPT diagnostic diagrams for the DESI and Keck+LRIS spectra. The NOT+ALFSOC spectrum is not included in these subplots due … view at source ↗
Figure 14
Figure 14. Figure 14: Photometric evolution of Raichu. Top left: ZTF forced photometry difference magnitude light curve. Bottom left: ATLAS forced photometry light curve presented in flux space. Right: LT absolute magnitude light curve [PITH_FULL_IMAGE:figures/full_fig_p024_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: In all panels spectra have been rebinned to a shared 2 Å wavelength regime, but have not otherwise been smoothed. Top row: Spectral observations of Venusaur from both DESI and Gemini+GMOS. Prominent emission lines are labelled (coloured by element). Spectra have been normalised relative to the flux of the strongest feature and then offset from each other for ease of interpretation. Middle row: Comparison … view at source ↗
Figure 16
Figure 16. Figure 16: Photometric evolution of Venusaur. Top left: ZTF forced photometry difference magnitude light curve. Bottom left: ATLAS forced photometry light curve presented in flux space. Right: LT absolute magnitude light curve. MNRAS 000, 1–43 (2025) [PITH_FULL_IMAGE:figures/full_fig_p026_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: In all panels, both spectra have been rebinned to a resolution of 2 Å prior to display. Top row: Spectral observations of Charizard from both DESI and Gemini+GMOS. Prominent emission lines are labelled (coloured by element). Spectra have been normalised relative to the flux of the strongest feature and then offset from each other for ease of interpretation. Middle row: Comparison between the strongest Fe … view at source ↗
Figure 18
Figure 18. Figure 18: Photometric evolution of Charizard. Top left: ZTF forced photometry difference magnitude light curve. Bottom left: ATLAS forced photometry light curve presented in flux space. Right: LT absolute magnitude light curve. 3100 3350 3600 3850 4100 4350 4600 4850 5100 5350 5600 5850 6100 6350 6600 6850 7100 7350 7600 7850 8100 8350 Rest Wavelength (Å) 0 2 4 6 8 Flu x (1 0 1 7 e r g / c m 2 / s / Å) Object ID: 3… view at source ↗
Figure 19
Figure 19. Figure 19: Top: DESI spectrum of Fearow, showing at the erroneous redshift determined by REDROCK (z = 0.152, compared to correct z = 3.928), a strong N v feature appears as [Fe xiv]. Emission lines displayed are shown if the REDROCK determined redshift was accurate. In reality, these features are (in order of increasing wavelength) Ly𝛼, N v, C iv and a broad blueshifted C iii featurex. Bottom: Region local to the ‘[… view at source ↗
Figure 20
Figure 20. Figure 20: Photometric evolution of Fearow. Top: ZTF forced photometry difference magnitude light curve. Bottom: ATLAS forced photometry light curve presented in flux space. 2500 2750 3000 3250 3500 3750 4000 4250 4500 4750 5000 5250 5500 5750 6000 6250 6500 6750 7000 7250 Rest Wavelength (Å) Scaled Flux + Offset SDSS MJD:55480 DESI MJD:59282 [FeVII] [FeX] [FeXIV] [FeVII] [FeVII] [FeVII] HeII HeI HeII H H H H [SII] … view at source ↗
Figure 21
Figure 21. Figure 21 [PITH_FULL_IMAGE:figures/full_fig_p029_21.png] view at source ↗
Figure 22
Figure 22. Figure 22: Photometric evolution of Arbok. Observational time frame used to re-reference the forced photometry are shown by the thick dashed purple lines. Observation time frame chosen to select the ‘low-state’ as the baseline for comparison. Top: ZTF forced photometry difference magnitude light curve. Bottom: ATLAS forced photometry light curve presented in flux space. MNRAS 000, 1–43 (2025) [PITH_FULL_IMAGE:figur… view at source ↗
Figure 23
Figure 23. Figure 23: In all panels, both spectra have been rebinned to a resolution of 2 Å prior to display. Top row: Spectral observations of Sandslash from both SDSS-Legacy and DESI. Prominent emission lines are labelled (coloured by element). Spectra have been normalised relative to the flux of the strongest feature and then offset from each other for ease of interpretation. Middle row: Comparison between the spectra lines… view at source ↗
Figure 24
Figure 24. Figure 24: Photometric evolution of Sandslash. Top: ZTF forced photometry difference magnitude light curve. Bottom: ATLAS forced photometry light curve presented in flux space. MNRAS 000, 1–43 (2025) [PITH_FULL_IMAGE:figures/full_fig_p032_24.png] view at source ↗
Figure 25
Figure 25. Figure 25: In all panels spectra have been rebinned to a shared 2 Å wavelength regime, but have not otherwise been smoothed. Top row: Spectral observations of Nidoqueen from both SDSS-Legacy and DESI. Prominent emission lines are labelled (coloured by element). Spectra have been normalised relative to the flux of the strongest feature and then offset from each other for ease of interpretation. Middle row: Comparison… view at source ↗
Figure 26
Figure 26. Figure 26: Photometric evolution of Nidoqueen. Top: ZTF forced photometry difference magnitude light curve. Bottom: ATLAS forced photometry light curve presented in flux space. 0 1 2 3 4 5 6 W2 - W3 0.0 0.5 1.0 1.5 2.0 2.5 W1 - W2 DESI EDR Candidates Pidgeot Raticate Raichu Ellipticals Spirals LIRGS ULIRGs / LINERS / Starburst Obscured AGN Seyferts QSOs Stern et al. (2012) Mateos et al. (2012) TDE-ECLEs SDSS J0748 S… view at source ↗
Figure 27
Figure 27. Figure 27: AllWISE colour-colour plot showing the DESI EDR TDE-ECLE candidates (circles) in comparison to the Wang et al. (2012) sample of TDE-ECLEs (diamonds). Regions have been sourced from Wright et al. (2010). The AGN identification cuts from Stern et al. (2012) and Mateos et al. (2012) are included as a green dashed line and purple dotted lines, respectively. Uncertainties in both axes are included but are gene… view at source ↗
Figure 28
Figure 28. Figure 28: Left: Comparison between the maximum change in W1 and W2 between the DESI EDR TDE-ECLEs (black circles) and a range of comparison objects. Dashed black line shows a 1-to-1 relation. Dotted line shows the orthogonal distance regression (ODR) best fitting quadratic for the CL-TDEs excluding objects with only upper limits, with the shaded region displaying the 1 𝜎 fitting uncertainty region. A quadratic fit … view at source ↗
Figure 30
Figure 30. Figure 30: Mass-normalized ECLE rates as a function of galaxy stellar mass for SDSS Legacy (red squares), BOSS LOWZ (blue square) and DESI EDR (black square). Vertical error bars show the statistical errors on the rates derived using the Monte Carlo simulations detailed above; and the horizontal error bars denote the range within each mass bin that 68 per cent of the galaxies fall. The points marked with downward ar… view at source ↗
Figure 31
Figure 31. Figure 31: Top: Mass-normalized ECLE rates as a function of galaxy SFR (left) and sSFR (right) for SDSS Legacy (red squares), BOSS LOWZ (blue circle), and DESI EDR (black triangle). Vertical error bars show the statistical errors on the rates, while the horizontal error bars denote the SFR and sSFR ranges comprising 68 per cent of the galaxies in each bin. The points marked with downward arrows are 2σ upper limits o… view at source ↗
Figure 32
Figure 32. Figure 32: Comparisons of our galaxy-normalized (left) and volumetric (right) ECLE rates with TDE and ECLE rates from the literature. TDE rates derived from X-ray surveys are shown as crosses (Donley et al. 2002; Esquej et al. 2008; Maksym et al. 2010; Khabibullin & Sazonov 2014; Sazonov et al. 2021), those from optical/UV surveys are shown as circles (van Velzen & Farrar 2014; Holoien et al. 2016; van Velzen 2018; … view at source ↗

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