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Your search keyword '"Freundlich, J"' showing total 13 results
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13 results on '"Freundlich, J"'

1. Predicting HCN, HCO$^+$, multi-transition CO, and dust emission of star-forming galaxies -- Extension to luminous infrared galaxies and the role of cosmic ray ionization

Author

Vollmer, B., Freundlich, J., Gratier, P., Lizee, Th., Lendrin, M., Braine, J., and Soida, M.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The specific star-formation rate of star-forming `main sequence' galaxies significantly decreased since z~1.5, due to the decreasing molecular gas fraction and star formation efficiency. However, the radio-infrared (IR) correlation has not changed significantly since z~1.5. The theory of turbulent clumpy starforming gas disks together with the scaling relations of the interstellar medium describes the large and small-scale properties of galactic gas disks. Here we extend our previous work on infrared, multi-transition molecular line, and radio continuum emission of local and high-z starforming and starburst galaxies to local and z~0.5 luminous infrared galaxies. The model reproduces the IR luminosities, CO, HCN, and HCO+ line luminosities, and the CO spectral line energy distributions of these galaxies. We derive CO(1-0) and HCN(1-0) conversion factors for all galaxy samples. The relation between the star formation rate per unit area and H2 surface density cannot be fit simply for all redshifts. There is a tight correlation between the star formation efficiency and the product of the gas turbulent velocity dispersion and the angular velocity of the galaxies. Galaxies of lower stellar masses can in principle compensate their gas consumption via star formation by radial viscous gas accretion. The limiting stellar mass increases with redshift. Whereas the radio continuum emission is directly proportional to the density of cosmic ray (CR) electrons, the molecular line emission depends on the CR ionization rate via the gas chemistry. The normalization of the CR ionization rate found for the different galaxy samples is about a factor of three to five higher than the normalization for the Solar neighborhood. This means that the mean yield of low energy CR particles for a given star formation rate per unit area is about three to ten times higher in external galaxies than observed by Voyager I., Comment: accepted for publication by A&A

Published
2024

2. YOLO-CIANNA: Galaxy detection with deep learning in radio data. I. A new YOLO-inspired source detection method applied to the SKAO SDC1

Author

Cornu, D., Salomé, P., Semelin, B., Marchal, A., Freundlich, J., Aicardi, S., Lu, X., Sainton, G., Mertens, F., Combes, F., and Tasse, C.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

The upcoming Square Kilometer Array (SKA) will set a new standard regarding data volume generated by an astronomical instrument, which is likely to challenge widely adopted data-analysis tools that scale inadequately with the data size. The aim of this study is to develop a new source detection and characterization method for massive radio astronomical datasets based on modern deep-learning object detection techniques. For this, we seek to identify the specific strengths and weaknesses of this type of approach when applied to astronomical data. We introduce YOLO-CIANNA, a highly customized deep-learning object detector designed specifically for astronomical datasets. In this paper, we present the method and describe all the elements introduced to address the specific challenges of radio astronomical images. We then demonstrate the capabilities of this method by applying it to simulated 2D continuum images from the SKA observatory Science Data Challenge 1 (SDC1) dataset. Using the SDC1 metric, we improve the challenge-winning score by +139% and the score of the only other post-challenge participation by +61%. Our catalog has a detection purity of 94% while detecting 40 to 60% more sources than previous top-score results, and exhibits strong characterization accuracy. The trained model can also be forced to reach 99% purity in post-process and still detect 10 to 30% more sources than the other top-score methods. It is also computationally efficient, with a peak prediction speed of 500 images of 512x512 pixels per second on a single GPU. YOLO-CIANNA achieves state-of-the-art detection and characterization results on the simulated SDC1 dataset and is expected to transfer well to observational data from SKA precursors., Comment: 42 pages. Custom layout edit of the corresponding in press A&A paper

Published
2024
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3. The ALMA-ALPINE [CII] survey: Kennicutt-Schmidt relation in four massive main-sequence galaxies at z~4.5

Author

Béthermin, M., Accard, C., Guillaume, C., Dessauges-Zavadsky, M., Ibar, E., Cassata, P., Devereaux, T., Faisst, A., Freundlich, J., Jones, G. C., Kraljic, K., Algera, H., Amorin, R. O., Bardelli, S., Boquien, M., Buat, V., Donghia, E., Dubois, Y., Ferrara, A., Fudamoto, Y., Ginolfi, M., Guillard, P., Giavalisco, M., Gruppioni, C., Gururajan, G., Hathi, N., Hayward, C. C., Koekemoer, A. M., Lemaux, B. C., Magdis, G. E., Molina, J., Narayanan, D., Mayer, L., Pozzi, F., Rizzo, F., Romano, M., Tasca, L., Theulé, P., Vergani, D., Vallini, L., Zamorani, G., Zanella, A., and Zucca, E.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The Kennicutt-Schmidt (KS) relation between the gas and the star formation rate (SFR) surface density ($\Sigma_{\rm gas}$-$\Sigma_{\rm SFR}$) is essential to understand star formation processes in galaxies. So far, it has been measured up to z~2.5 in main-sequence galaxies. In this letter, we aim to put constraints at z~4.5 using a sample of four massive main-sequence galaxies observed by ALMA at high resolution. We obtained ~0.3"-resolution [CII] and continuum maps of our objects, which we then converted into gas and obscured SFR surface density maps. In addition, we produced unobscured SFR surface density maps by convolving Hubble ancillary data in the rest-frame UV. We then derived the average $\Sigma_{\rm SFR}$ in various $\Sigma_{\rm gas}$ bins, and estimated the uncertainties using a Monte Carlo sampling. Our galaxy sample follows the KS relation measured in main-sequence galaxies at lower redshift and is slightly lower than predictions from simulations. Our data points probe the high end both in terms of $\Sigma_{\rm gas}$ and $\Sigma_{\rm gas}$, and gas depletion timescales (285-843 Myr) remain similar to z~2 objects. However, three of our objects are clearly morphologically disturbed, and we could have expected shorter gas depletion timescales (~100 Myr) similar to merger-driven starbursts at lower redshifts. This suggests that the mechanisms triggering starbursts at high redshift may be different than in the low- and intermediate-z Universe., Comment: 9 pages, 7 figures, 2 tables, accepted by A&A (letter)

Published
2023

4. SKA Science Data Challenge 2: analysis and results

Author

Hartley, P., Bonaldi, A., Braun, R., Aditya, J. N. H. S., Aicardi, S., Alegre, L., Chakraborty, A., Chen, X., Choudhuri, S., Clarke, A. O., Coles, J., Collinson, J. S., Cornu, D., Darriba, L., Veneri, M. Delli, Forbrich, J., Fraga, B., Galan, A., Garrido, J., Gubanov, F., Håkansson, H., Hardcastle, M. J., Heneka, C., Herranz, D., Hess, K. M., Jagannath, M., Jaiswal, S., Jurek, R. J., Korber, D., Kitaeff, S., Kleiner, D., Lao, B., Lu, X., Mazumder, A., Moldón, J., Mondal, R., Ni, S., Önnheim, M., Parra, M., Patra, N., Peel, A., Salomé, P., Sánchez-Expósito, S., Sargent, M., Semelin, B., Serra, P., Shaw, A. K., Shen, A. X., Sjöberg, A., Smith, L., Soroka, A., Stolyarov, V., Tolley, E., Toribio, M. C., van der Hulst, J. M., Sadr, A. Vafaei, Verdes-Montenegro, L., Westmeier, T., Yu, K., Yu, L., Zhang, L., Zhang, X., Zhang, Y., Alberdi, A., Ashdown, M., Bom, C. R., Brüggen, M., Cannon, J., Chen, R., Combes, F., Conway, J., Courbin, F., Ding, J., Fourestey, G., Freundlich, J., Gao, L., Gheller, C., Guo, Q., Gustavsson, E., Jirstrand, M., Jones, M. G., Józsa, G., Kamphuis, P., Kneib, J. -P., Lindqvist, M., Liu, B., Liu, Y., Mao, Y., Marchal, A., Márquez, I., Meshcheryakov, A., Olberg, M., Oozeer, N., Pandey-Pommier, M., Pei, W., Peng, B., Sabater, J., Sorgho, A., Starck, J. L., Tasse, C., Wang, A., Wang, Y., Xi, H., Yang, X., Zhang, H., Zhang, J., Zhao, M., and Zuo, S.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarise the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterise 233245 neutral hydrogen (Hi) sources in a simulated data product representing a 2000~h SKA MID spectral line observation from redshifts 0.25 to 0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, `reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy -- which combined predictions from two independent machine learning techniques to yield a 20 percent improvement in overall performance -- underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical datasets., Comment: Under review by MNRAS; 28 pages, 16 figures

Published
2023
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5. MusE GAs FLOw and Wind (MEGAFLOW) IX. The impact of gas flows on the relations between the mass, star formation rate and metallicity of galaxies

Author

Langan, I., Zabl, J., Bouche, N. F., Ginolfi, M., Popping, G., Schroetter, I., Wendt, M., Schaye, J., Boogaard, L., Freundlich, J., Richard, J., Matthee, J., Mercier, W., Contini, T., Guo, Y., and Cherrey, M.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We study the link between gas flow events and key galaxy scaling relations: the relations between star formation rate (SFR) and stellar mass (the main sequence, MS), gas metallicity and stellar mass (the mass-metallicity relation, MZR) and gas metallicity, stellar mass and SFR (the fundamental metallicity relation, FMR). Using all star-forming galaxies (SFGs) in the 22 MUSE fields of the MusE GAs FLOw and Wind (MEGAFLOW) survey, we derive the MS, MZR and FMR scaling relations for 385 SFGs with $M = 10^8 - 10^{11.5}$ $M_\odot$ at redshifts 0.35 < z < 0.85. Using the MUSE data and complementary X-Shooter spectra at 0.85 < z < 1.4, we determine the locations of 21 SFGs associated with inflowing or outflowing circumgalactic gas (i.e. with strong MgII absorption in background quasar spectra) relative to these scaling relations. Compared to a control sample of galaxies without gas flows (i.e., without MgII absorption within 70 kpc of the quasar), SFGs with inflow events (i.e., MgII absorption along the major axis) are preferentially located above the MS, while SFGs with ouflow events (i.e., MgII absorption along the minor axis) are preferentially more metal rich. Our observations support the scenario in which gas accretion increases the SFR while diluting the metal content and where circumgalactic outflows are found in more metal-rich galaxies., Comment: 13 pages, 8 figures

Published
2023
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6. The ALMA-ALPINE [CII] survey: Kennicutt-Schmidt relation in four massive main-sequence galaxies at z ∼ 4.5

Author

Béthermin, M., primary, Accard, C., additional, Guillaume, C., additional, Dessauges-Zavadsky, M., additional, Ibar, E., additional, Cassata, P., additional, Devereaux, T., additional, Faisst, A., additional, Freundlich, J., additional, Jones, G. C., additional, Kraljic, K., additional, Algera, H., additional, Amorín, R. O., additional, Bardelli, S., additional, Boquien, M., additional, Buat, V., additional, Donghia, E., additional, Dubois, Y., additional, Ferrara, A., additional, Fudamoto, Y., additional, Ginolfi, M., additional, Guillard, P., additional, Giavalisco, M., additional, Gruppioni, C., additional, Gururajan, G., additional, Hathi, N., additional, Hayward, C. C., additional, Koekemoer, A. M., additional, Lemaux, B. C., additional, Magdis, G. E., additional, Molina, J., additional, Narayanan, D., additional, Mayer, L., additional, Pozzi, F., additional, Rizzo, F., additional, Romano, M., additional, Tasca, L., additional, Theulé, P., additional, Vergani, D., additional, Vallini, L., additional, Zamorani, G., additional, Zanella, A., additional, and Zucca, E., additional

Published
2023
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7. Dusty Starbursts Masquerading as Ultra-high Redshift Galaxies in JWST CEERS Observations

Author

Zavala, JA, Buat, V, Casey, CM, Finkelstein, SL, Burgarella, D, Bagley, MB, Ciesla, L, Daddi, E, Dickinson, M, Ferguson, HC, Franco, M, Jiménez-Andrade, EF, Kartaltepe, JS, Koekemoer, AM, Bail, AL, Murphy, EJ, Papovich, C, Tacchella, S, Wilkins, SM, Aretxaga, I, Behroozi, P, Champagne, JB, Fontana, A, Giavalisco, M, Grazian, A, Grogin, NA, Kewley, LJ, Kocevski, DD, Kirkpatrick, A, Lotz, JM, Pentericci, L, Pérez-González, PG, Pirzkal, N, Ravindranath, S, Somerville, RS, Trump, Yang, G, Aaron Yung, LY, Almaini, O, Amorín, RO, Annunziatella, M, Haro, PA, Backhaus, BE, Barro, G, Bell, EF, Bhatawdekar, R, Bisigello, L, Buitrago, F, Calabrò, A, Castellano, M, Chávez Ortiz, ÓA, Chworowsky, K, Cleri, NJ, Cohen, SH, Cole, JW, Cooke, KC, Cooper, MC, Cooray, AR, Costantin, L, Cox, IG, Croton, D, Davé, R, Vega, ADL, Dekel, A, Elbaz, D, Estrada-Carpenter, V, Fernández, V, Finkelstein, KD, Freundlich, J, Fujimoto, S, García-Argumánez, Á, Gardner, JP, Gawiser, E, Gómez-Guijarro, C, Guo, Y, Hamilton, TS, Hathi, NP, Holwerda, BW, Hirschmann, M, Huertas-Company, M, Hutchison, TA, Iyer, KG, Jaskot, AE, Jha, SW, Jogee, S, Juneau, S, Jung, I, Kassin, SA, Kurczynski, P, Larson, RL, Leung, GCK, Long, AS, Lucas, RA, Magnelli, B, Mantha, KB, Matharu, J, McGrath, EJ, McIntosh, DH, Medrano, A, Merlin, E, Zavala, JA [0000-0002-7051-1100], Buat, V [0000-0003-3441-903X], Casey, CM [0000-0002-0930-6466], Finkelstein, SL [0000-0001-8519-1130], Burgarella, D [0000-0002-4193-2539], Bagley, MB [0000-0002-9921-9218], Ciesla, L [0000-0003-0541-2891], Daddi, E [0000-0002-3331-9590], Dickinson, M [0000-0001-5414-5131], Ferguson, HC [0000-0001-7113-2738], Franco, M [0000-0002-3560-8599], Jiménez-Andrade, EF [0000-0002-2640-5917], Kartaltepe, JS [0000-0001-9187-3605], Koekemoer, AM [0000-0002-6610-2048], Bail, AL [0000-0002-9466-2763], Murphy, EJ [0000-0001-7089-7325], Papovich, C [0000-0001-7503-8482], Tacchella, S [0000-0002-8224-4505], Wilkins, SM [0000-0003-3903-6935], Aretxaga, I [0000-0002-6590-3994], Behroozi, P [0000-0002-2517-6446], Champagne, JB [0000-0002-6184-9097], Fontana, A [0000-0003-3820-2823], Giavalisco, M [0000-0002-7831-8751], Grazian, A [0000-0002-5688-0663], Grogin, NA [0000-0001-9440-8872], Kewley, LJ [0000-0001-8152-3943], Kocevski, DD [0000-0002-8360-3880], Kirkpatrick, A [0000-0002-5537-8110], Lotz, JM [0000-0003-3130-5643], Pentericci, L [0000-0001-8940-6768], Pérez-González, PG [0000-0003-4528-5639], Pirzkal, N [0000-0003-3382-5941], Ravindranath, S [0000-0002-5269-6527], Somerville, RS [0000-0002-6748-6821], Trump, JR [0000-0002-1410-0470], Yang, G [0000-0001-8835-7722], Aaron Yung, LY [0000-0003-3466-035X], Almaini, O [0000-0001-9328-3991], Amorín, RO [0000-0001-5758-1000], Annunziatella, M [0000-0002-8053-8040], Haro, PA [0000-0002-7959-8783], Backhaus, BE [0000-0001-8534-7502], Barro, G [0000-0001-6813-875X], Bell, EF [0000-0002-5564-9873], Bhatawdekar, R [0000-0003-0883-2226], Bisigello, L [0000-0003-0492-4924], Buitrago, F [0000-0002-2861-9812], Calabrò, A [0000-0003-2536-1614], Castellano, M [0000-0001-9875-8263], Chávez Ortiz, ÓA [0000-0003-2332-5505], Chworowsky, K [0000-0003-4922-0613], Cleri, NJ [0000-0001-7151-009X], Cohen, SH [0000-0003-3329-1337], Cole, JW [0000-0002-6348-1900], Cooke, KC [0000-0002-2200-9845], Cooper, MC [0000-0003-1371-6019], Cooray, AR [0000-0002-3892-0190], Costantin, L [0000-0001-6820-0015], Cox, IG [0000-0002-1803-794X], Croton, D [0000-0002-5009-512X], Davé, R [0000-0003-2842-9434], Vega, ADL [0000-0002-6219-5558], Dekel, A [0000-0003-4174-0374], Elbaz, D [0000-0002-7631-647X], Estrada-Carpenter, V [0000-0001-8489-2349], Fernández, V [0000-0003-0531-5450], Finkelstein, KD [0000-0003-0792-5877], Freundlich, J [0000-0002-5245-7796], Fujimoto, S [0000-0001-7201-5066], García-Argumánez, Á [0000-0002-8365-5525], Gardner, JP [0000-0003-2098-9568], Gawiser, E [0000-0003-1530-8713], Gómez-Guijarro, C [0000-0002-4085-9165], Guo, Y [0000-0002-4162-6523], Hamilton, TS [0000-0002-9753-1769], Hathi, NP [0000-0001-6145-5090], Holwerda, BW [0000-0002-4884-6756], Hirschmann, M [0000-0002-3301-3321], Huertas-Company, M [0000-0002-1416-8483], Hutchison, TA [0000-0001-6251-4988], Iyer, KG [0000-0001-9298-3523], Jaskot, AE [0000-0002-6790-5125], Jha, SW [0000-0001-8738-6011], Jogee, S [0000-0002-1590-0568], Juneau, S [0000-0002-0000-2394], Jung, I [0000-0003-1187-4240], Kassin, SA [0000-0002-3838-8093], Kurczynski, P [0000-0002-8816-5146], Larson, RL [0000-0003-2366-8858], Leung, GCK [0000-0002-9393-6507], Long, AS [0000-0002-7530-8857], Lucas, RA [0000-0003-1581-7825], Magnelli, B [0000-0002-6777-6490], Matharu, J [0000-0002-7547-3385], McGrath, EJ [0000-0001-8688-2443], Merlin, E [0000-0001-6870-8900], and Apollo - University of Cambridge Repository

Subjects
5101 Astronomical Sciences, 5109 Space Sciences, 51 Physical Sciences, Galaxies and Cosmology
Abstract

Lyman-break galaxy (LBG) candidates at z ≳ 10 are rapidly being identified in James Webb Space Telescope (JWST)/NIRCam observations. Due to the (redshifted) break produced by neutral hydrogen absorption of rest-frame UV photons, these sources are expected to drop out in the bluer filters while being well detected in redder filters. However, here we show that dust-enshrouded star-forming galaxies at lower redshifts (z ≲ 7) may also mimic the near-infrared (near-IR) colors of z > 10 LBGs, representing potential contaminants in LBG candidate samples. First, we analyze CEERS-DSFG-1, a NIRCam dropout undetected in the F115W and F150W filters but detected at longer wavelengths. Combining the JWST data with (sub)millimeter constraints, including deep NOEMA interferometric observations, we show that this source is a dusty star-forming galaxy (DSFG) at z ≈ 5.1. We also present a tentative 2.6σ SCUBA-2 detection at 850 μm around a recently identified z ≈ 16 LBG candidate in the same field and show that, if the emission is real and associated with this candidate, the available photometry is consistent with a z ∼ 5 dusty galaxy with strong nebular emission lines despite its blue near-IR colors. Further observations on this candidate are imperative to mitigate the low confidence of this tentative submillimeter emission and its positional uncertainty. Our analysis shows that robust (sub)millimeter detections of NIRCam dropout galaxies likely imply z ∼ 4–6 redshift solutions, where the observed near-IR break would be the result of a strong rest-frame optical Balmer break combined with high dust attenuation and strong nebular line emission, rather than the rest-frame UV Lyman break. This provides evidence that DSFGs may contaminate searches for ultra-high redshift LBG candidates from JWST observations.

Published
2023

8. SKA science data challenge 2: analysis and results

Author

Hartley, P, primary, Bonaldi, A, additional, Braun, R, additional, Aditya, J N H S, additional, Aicardi, S, additional, Alegre, L, additional, Chakraborty, A, additional, Chen, X, additional, Choudhuri, S, additional, Clarke, A O, additional, Coles, J, additional, Collinson, J S, additional, Cornu, D, additional, Darriba, L, additional, Veneri, M Delli, additional, Forbrich, J, additional, Fraga, B, additional, Galan, A, additional, Garrido, J, additional, Gubanov, F, additional, Håkansson, H, additional, Hardcastle, M J, additional, Heneka, C, additional, Herranz, D, additional, Hess, K M, additional, Jagannath, M, additional, Jaiswal, S, additional, Jurek, R J, additional, Korber, D, additional, Kitaeff, S, additional, Kleiner, D, additional, Lao, B, additional, Lu, X, additional, Mazumder, A, additional, Moldón, J, additional, Mondal, R, additional, Ni, S, additional, Önnheim, M, additional, Parra, M, additional, Patra, N, additional, Peel, A, additional, Salomé, P, additional, Sánchez-Expósito, S, additional, Sargent, M, additional, Semelin, B, additional, Serra, P, additional, Shaw, A K, additional, Shen, A X, additional, Sjöberg, A, additional, Smith, L, additional, Soroka, A, additional, Stolyarov, V, additional, Tolley, E, additional, Toribio, M C, additional, van der Hulst, J M, additional, Sadr, A Vafaei, additional, Verdes-Montenegro, L, additional, Westmeier, T, additional, Yu, K, additional, Yu, L, additional, Zhang, L, additional, Zhang, X, additional, Zhang, Y, additional, Alberdi, A, additional, Ashdown, M, additional, Bom, C R, additional, Brüggen, M, additional, Cannon, J, additional, Chen, R, additional, Combes, F, additional, Conway, J, additional, Courbin, F, additional, Ding, J, additional, Fourestey, G, additional, Freundlich, J, additional, Gao, L, additional, Gheller, C, additional, Guo, Q, additional, Gustavsson, E, additional, Jirstrand, M, additional, Jones, M G, additional, Józsa, G, additional, Kamphuis, P, additional, Kneib, J-P, additional, Lindqvist, M, additional, Liu, B, additional, Liu, Y, additional, Mao, Y, additional, Marchal, A, additional, Márquez, I, additional, Meshcheryakov, A, additional, Olberg, M, additional, Oozeer, N, additional, Pandey-Pommier, M, additional, Pei, W, additional, Peng, B, additional, Sabater, J, additional, Sorgho, A, additional, Starck, J L, additional, Tasse, C, additional, Wang, A, additional, Wang, Y, additional, Xi, H, additional, Yang, X, additional, Zhang, H, additional, Zhang, J, additional, Zhao, M, additional, and Zuo, S, additional

Published
2023
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9. Dark Matter Fraction in Disk-Like Galaxies Over the Past 10 Gyr

Author

Sharma, G., Freundlich, J., van de Ven, G., Famaey, B., Salucci, P., Martorano, M., Renaud, F., Sharma, G., Freundlich, J., van de Ven, G., Famaey, B., Salucci, P., Martorano, M., and Renaud, F.

Abstract

We present an observational study of the dark matter fraction in star-forming disk-like galaxies up to redshift $z \sim 2.5$, selected from publicly available integral field spectroscropic surveys, namely KMOS3D}, KGES, and KROSS. We provide novel observational evidence, showing that at a fixed redshift, the dark matter fraction gradually increases with radius, indicating that the outskirts of galaxies are dark matter dominated, similarly to local star-forming disk galaxies. This observed dark matter fraction exhibits a decreasing trend with increasing redshift. However, on average, the fraction within the effective radius (upto outskirts) remains above 50\%, similar to locals. Furthermore, we investigated the relationships between the dark matter, baryon surface density, and circular velocity of galaxies. We observe a decreasing trend in the dark matter fraction as baryon surface densities increase, which is consistent across all stellar masses, redshift ranges, and radii, with a scatter of 0.13 dex. On the other hand, the correlation between the circular velocity at the outermost radius and the dark matter fraction within this radius has a relatively low scatter (0.11 dex), but its slope varies with stellar mass and with redshift, providing observational evidence of the dynamical evolution of the interplay between the baryonic and dark matter distributions with cosmic time. We observe that low stellar mass galaxies ($\log(M_{\star}/\mathrm{M_\odot}) \leq 10.0$) undergo a higher degree of evolution, which may be attributed to the hierarchical merging of galaxies., Comment: Comments are welcome

Published
2023

10. The ALMA-ALPINE [CII] survey:Kennicutt-Schmidt relation in four massive main-sequence galaxies at z ∼ 4.5

Author

Béthermin, M., Accard, C., Guillaume, C., Dessauges-zavadsky, M., Ibar, E., Cassata, P., Devereaux, T., Faisst, A., Freundlich, J., Jones, G. C., Kraljic, K., Algera, H., Amorín, R. O., Bardelli, S., Boquien, M., Buat, V., Donghia, E., Dubois, Y., Ferrara, A., Fudamoto, Y., Ginolfi, M., Guillard, P., Giavalisco, M., Gruppioni, C., Gururajan, G., Hathi, N., Hayward, C. C., Koekemoer, A. M., Lemaux, B. C., Magdis, G. E., Molina, J., Narayanan, D., Mayer, L., Pozzi, F., Rizzo, F., Romano, M., Tasca, L., Theulé, P., Vergani, D., Vallini, L., Zamorani, G., Zanella, A., Zucca, E., Béthermin, M., Accard, C., Guillaume, C., Dessauges-zavadsky, M., Ibar, E., Cassata, P., Devereaux, T., Faisst, A., Freundlich, J., Jones, G. C., Kraljic, K., Algera, H., Amorín, R. O., Bardelli, S., Boquien, M., Buat, V., Donghia, E., Dubois, Y., Ferrara, A., Fudamoto, Y., Ginolfi, M., Guillard, P., Giavalisco, M., Gruppioni, C., Gururajan, G., Hathi, N., Hayward, C. C., Koekemoer, A. M., Lemaux, B. C., Magdis, G. E., Molina, J., Narayanan, D., Mayer, L., Pozzi, F., Rizzo, F., Romano, M., Tasca, L., Theulé, P., Vergani, D., Vallini, L., Zamorani, G., Zanella, A., and Zucca, E.

Published
2023

11. A Long Time Ago in a Galaxy Far, Far Away: A Candidate z ~ 12 Galaxy in Early JWST CEERS Imaging

Author

Finkelstein, SL, Bagley, MB, Haro, PA, Dickinson, M, Ferguson, HC, Kartaltepe, JS, Papovich, C, Burgarella, D, Kocevski, DD, Huertas-Company, M, Iyer, KG, Koekemoer, AM, Larson, RL, Pérez-González, PG, Rose, C, Tacchella, S, Wilkins, SM, Chworowsky, K, Medrano, A, Morales, AM, Somerville, RS, Aaron Yung, LY, Fontana, A, Giavalisco, M, Grazian, A, Grogin, NA, Kewley, LJ, Kirkpatrick, A, Kurczynski, P, Lotz, JM, Pentericci, L, Pirzkal, N, Ravindranath, S, Ryan, RE, Trump, Yang, G, Almaini, O, Amorín, RO, Annunziatella, M, Backhaus, BE, Barro, G, Behroozi, P, Bell, EF, Bhatawdekar, R, Bisigello, L, Bromm, V, Buat, V, Buitrago, F, Calabrò, A, Casey, CM, Castellano, M, Chávez Ortiz, ÓA, Ciesla, L, Cleri, NJ, Cohen, SH, Cole, JW, Cooke, KC, Cooper, MC, Cooray, AR, Costantin, L, Cox, IG, Croton, D, Daddi, E, Davé, R, De La Vega, A, Dekel, A, Elbaz, D, Estrada-Carpenter, V, Faber, SM, Fernández, V, Finkelstein, KD, Freundlich, J, Fujimoto, S, García-Argumánez, Á, Gardner, JP, Gawiser, E, Gómez-Guijarro, C, Guo, Y, Hamblin, K, Hamilton, TS, Hathi, NP, Holwerda, BW, Hirschmann, M, Hutchison, TA, Jaskot, AE, Jha, SW, Jogee, S, Juneau, S, Jung, I, Kassin, SA, Le Bail, A, Leung, GCK, Lucas, RA, Magnelli, B, Mantha, KB, Matharu, J, McGrath, EJ, McIntosh, DH, Merlin, E, Mobasher, B, Finkelstein, SL [0000-0001-8519-1130], Bagley, MB [0000-0002-9921-9218], Haro, PA [0000-0002-7959-8783], Dickinson, M [0000-0001-5414-5131], Ferguson, HC [0000-0001-7113-2738], Kartaltepe, JS [0000-0001-9187-3605], Papovich, C [0000-0001-7503-8482], Burgarella, D [0000-0002-4193-2539], Kocevski, DD [0000-0002-8360-3880], Huertas-Company, M [0000-0002-1416-8483], Iyer, KG [0000-0001-9298-3523], Koekemoer, AM [0000-0002-6610-2048], Larson, RL [0000-0003-2366-8858], Pérez-González, PG [0000-0003-4528-5639], Rose, C [0000-0002-8018-3219], Tacchella, S [0000-0002-8224-4505], Wilkins, SM [0000-0003-3903-6935], Chworowsky, K [0000-0003-4922-0613], Morales, AM [0000-0003-4965-0402], Somerville, RS [0000-0002-6748-6821], Aaron Yung, LY [0000-0003-3466-035X], Fontana, A [0000-0003-3820-2823], Giavalisco, M [0000-0002-7831-8751], Grazian, A [0000-0002-5688-0663], Grogin, NA [0000-0001-9440-8872], Kewley, LJ [0000-0001-8152-3943], Kirkpatrick, A [0000-0002-1306-1545], Kurczynski, P [0000-0002-8816-5146], Lotz, JM [0000-0003-3130-5643], Pentericci, L [0000-0001-8940-6768], Pirzkal, N [0000-0003-3382-5941], Ravindranath, S [0000-0002-5269-6527], Ryan, RE [0000-0003-0894-1588], Trump, JR [0000-0002-1410-0470], Yang, G [0000-0001-8835-7722], Almaini, O [0000-0001-9328-3991], Amorín, RO [0000-0001-5758-1000], Annunziatella, M [0000-0002-8053-8040], Backhaus, BE [0000-0001-8534-7502], Behroozi, P [0000-0002-2517-6446], Bell, EF [0000-0002-5564-9873], Bhatawdekar, R [0000-0003-0883-2226], Bisigello, L [0000-0003-0492-4924], Bromm, V [0000-0003-0212-2979], Buat, V [0000-0003-3441-903X], Buitrago, F [0000-0002-2861-9812], Calabrò, A [0000-0003-2536-1614], Casey, CM [0000-0002-0930-6466], Castellano, M [0000-0001-9875-8263], Chávez Ortiz, ÓA [0000-0003-2332-5505], Ciesla, L [0000-0003-0541-2891], Cleri, NJ [0000-0001-7151-009X], Cohen, SH [0000-0003-3329-1337], Cole, JW [0000-0002-6348-1900], Cooke, KC [0000-0002-2200-9845], Cooper, MC [0000-0003-1371-6019], Cooray, AR [0000-0002-3892-0190], Costantin, L [0000-0001-6820-0015], Cox, IG [0000-0002-1803-794X], Croton, D [0000-0002-5009-512X], Daddi, E [0000-0002-3331-9590], Davé, R [0000-0003-2842-9434], De La Vega, A [0000-0002-6219-5558], Dekel, A [0000-0003-4174-0374], Elbaz, D [0000-0002-7631-647X], Estrada-Carpenter, V [0000-0001-8489-2349], Fernández, V [0000-0003-0531-5450], Finkelstein, KD [0000-0003-0792-5877], Freundlich, J [0000-0002-5245-7796], Fujimoto, S [0000-0001-7201-5066], García-Argumánez, Á [0000-0002-8365-5525], Gardner, JP [0000-0003-2098-9568], Gawiser, E [0000-0003-1530-8713], Gómez-Guijarro, C [0000-0002-4085-9165], Guo, Y [0000-0002-4162-6523], Hamblin, K [0000-0002-6292-4589], Hamilton, TS [0000-0002-9753-1769], Hathi, NP [0000-0001-6145-5090], Holwerda, BW [0000-0002-4884-6756], Hirschmann, M [0000-0002-3301-3321], Hutchison, TA [0000-0001-6251-4988], Jaskot, AE [0000-0002-6790-5125], Jha, SW [0000-0001-8738-6011], Jogee, S [0000-0002-1590-0568], Juneau, S [0000-0002-0000-2394], Jung, I [0000-0003-1187-4240], Kassin, SA [0000-0002-3838-8093], Le Bail, A [0000-0002-9466-2763], Leung, GCK [0000-0002-9393-6507], Lucas, RA [0000-0003-1581-7825], Magnelli, B [0000-0002-6777-6490], Matharu, J [0000-0002-7547-3385], McGrath, EJ [0000-0001-8688-2443], Merlin, E [0000-0001-6870-8900], and Apollo - University of Cambridge Repository

Subjects
5101 Astronomical Sciences, 5109 Space Sciences, 51 Physical Sciences, Galaxies and Cosmology
Abstract

We report the discovery of a candidate galaxy with a photo-z of z ∼ 12 in the first epoch of the James Webb Space Telescope (JWST) Cosmic Evolution Early Release Science Survey. Following conservative selection criteria, we identify a source with a robust z phot = 11.8 − 0.2 + 0.3 (1σ uncertainty) with m F200W = 27.3 and ≳7σ detections in five filters. The source is not detected at λ < 1.4 μm in deep imaging from both Hubble Space Telescope (HST) and JWST and has faint ∼3σ detections in JWST F150W and HST F160W, which signal a Lyα break near the red edge of both filters, implying z ∼ 12. This object (Maisie’s Galaxy) exhibits F115W − F200W > 1.9 mag (2σ lower limit) with a blue continuum slope, resulting in 99.6% of the photo-z probability distribution function favoring z > 11. All data-quality images show no artifacts at the candidate’s position, and independent analyses consistently find a strong preference for z > 11. Its colors are inconsistent with Galactic stars, and it is resolved (r h = 340 ± 14 pc). Maisie’s Galaxy has log M */M ⊙ ∼ 8.5 and is highly star-forming (log sSFR ∼ −8.2 yr−1), with a blue rest-UV color (β ∼ −2.5) indicating little dust, though not extremely low metallicity. While the presence of this source is in tension with most predictions, it agrees with empirical extrapolations assuming UV luminosity functions that smoothly decline with increasing redshift. Should follow-up spectroscopy validate this redshift, our universe was already aglow with galaxies less than 400 Myr after the Big Bang.

Published
2022
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13. Dynamic PET Reveals Compartmentalized Brain and Lung Tissue Antibiotic Exposures.

Author

Jain S, Chen X, Arun B, Meza ON, Sarhan M, Singh M, Jeon B, Mane K, Shah M, Tucker E, Carroll L, Freundlich J, Peloquin C, and Ivaturi V

Abstract

Tuberculosis (TB) remains a leading cause of death, but antibiotic treatments for tuberculous meningitis, the deadliest form of TB, are based on those developed for pulmonary TB and not optimized for brain penetration. Here, we performed first-in-human dynamic 18 F-pretomanid positron emission tomography (PET) studies in eight human subjects for three-dimensional, multi-compartmental in situ visualization of antibiotic concentration-time exposures (area under the curve - AUC), demonstrating preferential brain (AUC tissue/plasma 2.25) versus lung (AUC tissue/plasma 0.97) tissue partitioning. Preferential, antibiotic-specific partitioning into brain or lung tissues of antibiotics active against MDR strains were confirmed in experimentally-infected mice and rabbits, using dynamic PET with chemically identical antibiotic radioanalogs, and postmortem mass spectrometry measurements. PET-facilitated pharmacokinetic modeling predicted human dosing necessary to attain therapeutic brain exposures in human subjects. These data were used to design optimized, pretomanid-based regimens which were evaluated at human equipotent dosing in a mouse model of TB meningitis, demonstrating excellent bactericidal activity without an increase in intracerebral inflammation or brain injury. Importantly, several antibiotic regimens demonstrated discordant activities in brain and lung tissues in the same animal, correlating with the compartmentalized tissue exposures of the component antibiotics. These data provide a mechanistic basis for the compartmentalized activities of antibiotic regimens, with important implications for the development of antimicrobial regimens for meningitis and other infections in compartments with unique antibiotic penetration., Competing Interests: Competing interests Vijay Ivaturi is a co-founder and Vijay Ivaturi and Bhavatharini Arun are employees of Pumas-AI, which commercializes Pumas and Lyv software. All other authors declare that they have no competing interests. Additional Declarations: Yes there is potential Competing Interest. Vijay Ivaturi is a co-founder and Vijay Ivaturi and Bhavatharini Arun are employees of Pumas-AI, which commercializes Pumas and Lyv software. All other authors declare that they have no competing interests.

Published
2024
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