Weekly issue

Week 2, 2025

Jan 6–12, 2025

Week 2, 2025 includes 5 curated papers, centered on spectroscopy, high-z, LRD.

2501.04912v1

Another piece to the puzzle: radio detection of a JWST detected AGN candidate

Anniek J. Gloudemans, Kenneth J. Duncan, Anna-Christina Eilers, Emanuele Paolo Farina, Yuichi Harikane, Kohei Inayoshi, Erini Lambrides, Eleni Vardoulaki

Theme match 5/5

Digest

Deep 0.144–3 GHz maps across COSMOS, GOODS-N, and GOODS-S are mined for radio counterparts to ~700 JWST-selected AGN candidates (including LRDs). Only PRIMER-COS 3866 at z=4.66 is individually detected; its spectrum (α=−0.76+0.11−0.09), modest radio-loudness (R≈0.5), and Tb≳10^3 K remain consistent with either AGN or star-formation power. Stacks of spectroscopic and photometric subsamples yield non-detections with 3σ limits L1.4GHz<8.6×10^39 erg s−1 and L1.3GHz<1.3×10^39 erg s−1, still compatible with local L_X–L_Hα and L_X–L_R relations. The authors argue present radio depths are insufficient to label the population radio-weak and forecast SKA/ngVLA detections within hours to enable brightness-temperature tests that separate AGN from starbursts.

Open paper page arXiv abstract arXiv PDF Highlighted PDF

Key figures to inspect

Figure 1: Examine the F115W stamp with VLA contours and the multi-band (144 MHz/1.3/3 GHz) cutouts of PRIMER-COS 3866 to verify the positional match and compactness; the radio SED fit (with GMRT upper limits) shows α≈−0.76 and hints of curvature possibly from SSA/FFA.
Figure 2: The COSMOS/GOODS stacked images all show non-detections; read the panel rms values to translate into average luminosity limits and appreciate how stacking pushes below single-image depths yet still finds no mean signal.
Figure 3: Black-hole mass vs Hα luminosity with predicted radio output: locate the median of the GOODS sources and the locus implied by PRIMER-COS 3866; compare the overplotted 3σ radio limits (GN single, GN stack, COSMOS stack) to see that the null results are not in tension with expectations.
Figure 4: Examples of false radio associations illustrate how nearby bright galaxies can mimic detections; use the contours, beam sizes, and offsets to understand the team’s visual-vetting criteria and why many SNR “hits” were rejected.

Tags

2501.03309v1

Little Red Dots are Tidal Disruption Events in Runaway-Collapsing Clusters

Jillian Bellovary

Theme match 5/5

Digest

Proposes that Little Red Dots are recurrent tidal disruption events triggered during runaway collapse of the first dense star clusters, forming intermediate-mass black hole seeds. Matching JWST LRD number densities to seed-formation predictions implies a required TDE rate of ~10^-4 yr^-1; analytic (loss-cone) and simulation-based scalings show this rate is feasible in dense clusters. The scenario naturally explains compact, UV-bright emission with broad H-alpha and links LRDs to early black-hole growth. A top-heavy IMF may be needed to satisfy ΛCDM mass-function limits, and the hypothesis is testable via TDE-like variability in JWST follow-up.

Open paper page arXiv abstract arXiv PDF Highlighted PDF

Key figures to inspect

Figure 1: Compare LRD comoving number densities against analytic and simulation seed-formation curves to see the ~4 dex shortfall that motivates a TDE duty cycle of ~10^-4 yr^-1.
Figure 2 (top): TDE rate versus black hole mass at fixed σ; identify the IMBH mass range where both Stone+2017 and Rizzuto+2023 prescriptions achieve ~10^-4 yr^-1 under the adopted dense-cluster conditions.
Figure 2 (bottom): TDE rate versus stellar velocity dispersion at fixed MBH; check that σ≈100–150 km s^-1 yields the target ~10^-4 yr^-1, supporting feasibility in compact, high-density clusters.

Tags

2501.05512v1

JWST NIRCam simulations and observations of AGN ionization cones in cosmic noon galaxies

Sophie Lebowitz, Kevin Hainline, Stéphanie Juneau, Jianwei Lyu, Christina Williams, Stacey Alberts, Xiaohui Fan, Marcia Rieke

Theme match 4/5

Digest

Simulating JWST/NIRCam narrow- and medium-band [O III] maps at z≈2–3 using MUSE datacubes of nine nearby AGN, the authors show NIRCam can recover classic ionization-cone morphologies. They then apply this to 27 known AGN in GOODS-S (z=2.4–3.4), identifying six systems with [O III]+Hβ morphologies consistent with cones and characteristic NLR sizes of 1–2.5 kpc. The simulations quantify how cosmological dimming and instrument noise bias high‑z NLR size measurements low, depressing the local NLR size–AGN luminosity relation by about a factor of two. This establishes a practical medium-band imaging path to select cone candidates and calibrate NLR size trends at cosmic noon.

Open paper page arXiv abstract arXiv PDF Highlighted PDF

Key figures to inspect

Figure 1 (SED scaling for F182M/F210M): Check how the continuum color terms are derived per redshift bin and how the scaling factors control residuals in the [O III]+Hβ map after subtraction.
Figure 2 (NGC 2992 at z=2.3, PSF/oversampling tests): Compare no-PSF vs WebbPSF and oversampling cases to see how cone edges, opening angle, and asymmetries survive beam smearing in the narrow-band [O III] and the continuum-subtracted map.
Figure 3 (Narrow vs medium band [O III]): Directly compare F164N- and F162M-based [O III] maps to assess morphology fidelity versus throughput—key for deciding when medium bands can robustly reveal cones.
Figure 4 (Noise and continuum subtraction): Contrast noiseless and noisy simulations using F182M ([O III]+cont) minus F210M (cont) to gauge detection limits and how noise drives underestimates of NLR size at z≈2–3.

Tags

2501.04770v1

Lyman Alpha Forest - Halo Cross-Correlations in Effective Field Theory

Anton Chudaykin, Mikhail M. Ivanov

Theme match 2/5

Digest

This paper develops a redshift-space EFT for Lyα forest cross-correlations with biased tracers and delivers one-loop full-shape power-spectrum predictions. Tested on Sherwood hydrodynamic simulations at z=2.8 with massive and light halo catalogs, the model jointly fits the Lyα auto, halo auto, and Lyα–halo cross spectra. Adding the cross term significantly tightens constraints on Lyα and halo EFT parameters relative to auto-only fits. The combined model attains percent-level accuracy for the cross-spectrum up to k_max=1 h Mpc^{-1}, improving over prior analytic approaches and enabling precision DESI-era Lyα–quasar analyses.

Open paper page arXiv abstract arXiv PDF Highlighted PDF

Key figures to inspect

Figure 1: Compare posteriors across k_max choices to see where EFT parameters stabilize for the massive-halo sample, guiding a safe scale cut.
Figure 2: Inspect the size of one-loop corrections versus linear theory for massive halos to identify the k,μ regime where nonlinearity is essential and why k_max≈1 h Mpc^{-1} is reachable.
Figure 3: Contrast nuisance-parameter posteriors from Lyα-only, halo-only, and the combined Lyα–halo analysis (diagonal covariance) to visualize how the cross-spectrum breaks degeneracies and sharpens constraints across different k_max.
Figure 4: Check best-fit model versus simulated spectra and the residuals for the massive-halo 3-spectra fit; verify percent-level residuals to k≈1 h Mpc^{-1} after shot-noise subtraction.

Tags

2501.04085v1

The Cosmic Evolution Early Release Science Survey (CEERS)

Steven L. Finkelstein, Micaela B. Bagley, Pablo Arrabal Haro, Mark Dickinson, Henry C. Ferguson, Jeyhan S. Kartaltepe, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Casey Papovich, Pablo G. Perez-Gonzalez, Nor Pirzkal, Rachel S. Somerville, Jonathan R. Trump, Guang Yang, L. Y. Aaron Yung, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Lisa J. Kewley, Allison Kirkpatrick, Rebecca L. Larson, Laura Pentericci, Swara Ravindranath, Stephen M. Wilkins, Omar Almaini, Ricardo O. Amorin, Guillermo Barro, Rachana Bhatawdekar, Laura Bisigello, Madisyn Brooks, Fernando Buitrago, Antonello Calabro, Marco Castellano, Yingjie Cheng, Nikko J. Cleri, Justin W. Cole, M. C. Cooper, Olivia R. Cooper, Luca Costantin, Isa G. Cox, Darren Croton, Emanuele Daddi, Kelcey Davis, Avishai Dekel, David Elbaz, Vital Fernandez, Seiji Fujimoto, Giovanni Gandolfi, Jonathan P. Gardner, Eric Gawiser, Mauro Giavalisco, Carlos Gomez-Guijarro, Yuchen Guo, Ansh R. Gupta, Nimish P. Hathi, Santosh Harish, Aurelien Henry, Michaela Hirschmann, Weida Hu, Taylor A. Hutchison, Kartheik G. Iyer, Anne E. Jaskot, Saurabh W. Jha, Intae Jung, Vasily Kokorev, Peter Kurczynski, Gene C. K. Leung, Mario Llerena, Arianna S. Long, Ray A. Lucas, Shiying Lu, Elizabeth J. McGrath, Daniel H. McIntosh, Emiliano Merlin, Alexa M. Morales, Lorenzo Napolitano, Fabio Pacucci, Viraj Pandya, Marc Rafelski, Giulia Rodighiero, Caitlin Rose, Paola Santini, Lise-Marie Seille, Raymond C. Simons, Lu Shen, Amber N. Straughn, Sandro Tacchella, Brittany N. Vanderhoof, Jesus Vega-Ferrero, Benjamin J. Weiner, Christopher N. A. Willmer, Peixin Zhu, Eric F. Bell, Stijn Wuyts, Benne W. Holwerda, Xin Wang, Weichen Wang, Jorge A. Zavala

Theme match 2/5

Digest

CEERS is a 77.2 hr ERS survey in the EGS that uses coordinated, overlapping NIRCam/MIRI imaging, NIRSpec low–medium resolution spectroscopy, and NIRCam slitless grism data to validate efficient extragalactic mapping. From ~90 arcmin^2 of NIRCam imaging it uncovered large samples of z ≳ 10 galaxies and secured >1000 spectra, including dozens at 6<z<10, enabling redshifts and rest‑optical line diagnostics that probe star formation and supermassive black hole growth. The program also quantifies the first bulge, bar, and disk structures at z>3 and leverages MIRI mid‑IR emission to trace dust‑obscured star formation and black‑hole accretion at z~1–3. As a legacy, CEERS releases processed data with detailed reduction notes and reproducible notebooks.

Open paper page arXiv abstract arXiv PDF Highlighted PDF

Key figures to inspect

Survey footprint/tiling over the EGS showing NIRCam, NIRSpec, and MIRI coverage and their overlaps—useful for planning cross‑instrument AGN searches and understanding depth variations across the field.
Representative NIRSpec R~1000 spectra for 6<z<10 galaxies highlighting rest‑optical lines (e.g., [O III], Hβ, Hα when accessible) and example line‑ratio diagnostics used to separate star formation from accretion.
NIRCam high‑z yield figure: sky distribution and number counts/photometric‑redshift distribution of z ≳ 10 candidates from ~90 arcmin^2, clarifying selection limits and contamination control.
MIRI mid‑IR diagnostic plot (colors or SED fits) at z~1–3 illustrating separation of dust‑obscured star formation from SMBH-heated emission and the redshift leverage of the filter set.
Morphology results at z>3: examples and fractions of bars/bulges/disks from NIRCam rest‑optical imaging, showing how early structural assembly correlates with stellar mass/redshift.