Vz-GAL Dusty Star-Forming Galaxies: Revisiting the CO-H2 Conversion Factor Tension
Prachi Prajapati, Axel Weiss, Dominik Riechers, Tom J. L. C. Bakx, Leindert A. Boogaard, Diana Ismail, Pierre Cox, Andrew J. Baker, Roberto Neri, Matthew Lehnert, Chentao Yang, Emilio Romano-Diaz, Hiddo S. B. Algera, Stefano Berta, Edoardo Borsato, Kirsty M. Butler, Asantha Cooray, Bethany Jones, Amelie Saintonge, Paul van der Werf
https://arxiv.org/abs/2607.18440 https://arxiv.org/pdf/2607.18440 https://arxiv.org/html/2607.18440
arXiv:2607.18440v1 Announce Type: new
Abstract: The CO luminosity-to-H$_2$ mass conversion factor ($\alpha_{CO}$) remains a debated uncertainty in determining molecular gas masses of high-redshift dusty star-forming galaxies (DSFGs). Dynamical mass constraints have often favored $\alpha_{CO}=0.8$~$M_{\odot}~{(K~km~{s}^{-1}~{pc}^{2})}^{-1}$, whereas dust- and radiative-transfer-based methods imply higher values. We revisit this ``tension" using the largest homogeneous sample of 21 unlensed $z\sim1-4$ DSFGs, with securely measured \coonezero luminosities from the VLA \vzgal survey and resolved ($\sim{0.1}^{\prime\prime}$) ALMA 1~mm dust continuum imaging. For 12 galaxies with robust modeling constraints, we derive molecular gas masses using dust spectral energy distribution modeling and the TUNER LVG framework, adopting a solar-metallicity gas-to-dust mass ratio of 100. Although not fully independent due to shared assumptions on dust properties, these approaches yield mutually consistent gas masses corresponding to $\alpha_{CO}\sim1.5-11.5$, with a median near the Galactic $\alpha_{CO}=4.3$. Isotropic virial dynamical masses agree with these gas masses when realistic molecular gas sizes are adopted, while our proposed ``mixed" (rotating, pressure-supported, thick-disk) estimator systematically underestimates dynamical masses, producing low $\alpha_{CO}$ limits. Using GN20 ($z=4.055$) as a case study, we show that resolved gas geometry and kinematics reconcile the discrepancy with LVG-derived $\alpha_{CO}$. Our results suggest that current data do not require $\alpha_{CO}=0.8$, and intermediate to near-Galactic values remain dynamically viable given uncertainties in gas geometry, dust properties, and gas-to-dust ratios. Further progress in calibrating $\alpha_{CO}$ in the early universe will require resolved molecular gas observations, physically motivated ISM modeling, and stringent constraints on dust properties.
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RE: https://flipboard.com/@theeconomist/leaders-g74q8sgvz/-/a-Pi2jMVORQnKek1GT_IkLYA:a:3199507-/0
quote reposting this not because I agree with it, but because it may single-handedly be the most hilario…
RE: https://flipboard.com/@theeconomist/leaders-g74q8sgvz/-/a-Pi2jMVORQnKek1GT_IkLYA:a:3199507-/0
quote reposting this not because I agree with it, but because it may single-handedly be the most hilario…
Fisher Forecasting for the DESC with $\texttt{Augur}$
Paul Rogozenski, Sankarshana Srinivasan, Javier S\'anchez, Nora Elisa Chisari, Arthur Loureiro, Marc Paterno, Rebekah Polen, Heather Prince, Biancamaria Sersante, An\v{z}e Slosar, Sandro Vitenti, Carlos Garc\'ia-Garc\'ia, Eric Gawiser, Christos Georgiou, C. Danielle Leonard, Ayan Mitra, Jeremy Neveu, The LSST Dark Energy Science Collaboration
https://arxiv.org/abs/2608.03876 https://arxiv.org/pdf/2608.03876 https://arxiv.org/html/2608.03876
arXiv:2608.03876v1 Announce Type: new
Abstract: The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurements, computationally inexpensive investigations of modeling choices must be made to gauge the performance of proposed cosmological analyses. In this paper, we introduce the $\texttt{Augur}$ tool of the Dark Energy Science Collaboration (DESC), which provides Fisher forecasts for cosmological inference for the LSST using software frameworks designed for DESC science. We test the pipeline by comparing it to forecasts produced by external code and direct sampling of the posterior via nested sampling methods, finding good agreement between all methods. We additionally investigate a range of modeling and hyperparameter choices for a 3$\times$2pt investigation in harmonic space, providing users with diagnostics to obtain reliable forecasts. $\texttt{Augur}$ will be continually updated to be compatible with the other tools in the DESC software ecosystem as additional probes and functionality become available.
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Terminei de imprimir todas as provas. Agora estou almoçando correndo e daqui a pouco sair daqui. Foi bom ter feito esses gabaritos e revisado, acabei trocando uma das questões.
Crosslisted article(s) found for cs.GT. https://arxiv.org/list/cs.GT/new
[1/1]:
- Insurance of Agentic AI
Quanyan Zhu
https://arxiv.org/abs/2606.05449 https://mastoxiv.page/@arXiv_csAI_bot/116696535801623005
- Bitcoin After Block Rewards
Junhyuk Lee
https://arxiv.org/abs/2606.05503 https://mastoxiv.page/@arXiv_csCR_bot/116696457548098249
- Online Min-Cost Matching with General Arrivals
Josh Ascher, Eric Balkanski, Jason Chatzitheodorou, Vasilis Gkatzelis
https://arxiv.org/abs/2606.05546 https://mastoxiv.page/@arXiv_csDS_bot/116696483136717005
- Measuring Concentration of Power in Approval Voting Games
Takaaki Abe
https://arxiv.org/abs/2606.05655 https://mastoxiv.page/@arXiv_econTH_bot/116696378312014137
- Learning to Contest: Decentralized Robust Fairness in Cooperative MARL via Cross-Attention
Can Savc{\i}
https://arxiv.org/abs/2606.06162 https://mastoxiv.page/@arXiv_csMA_bot/116696376542763270
- Regret Minimization with Adaptive Opponents in Repeated Games
Mingyang Liu, Asuman Ozdaglar, Tiancheng Yu, Kaiqing Zhang
https://arxiv.org/abs/2606.06486
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