Publications

in 2021



  1. Cuceu, A et al.,
    Cosmology beyond BAO from the 3D distribution of the Lyman-alpha forest,
    Monthly Notices Of The Royal Astronomical Society. 506 (4): 5439-5450 (2021) [DOI] [ARXIV]
  2. Manera, M et al.,
    Obtaining nonlinear galaxy bias constraints from galaxy-lensing phase differences,
    Monthly Notices Of The Royal Astronomical Society. 506 (4): 5878-5887 (2021) [DOI] [ARXIV]
  3. Cabayol, L et al.,
    The PAU survey: Estimating galaxy photometry with deep learning,
    Monthly Notices Of The Royal Astronomical Society. 506 (3): 4048-4069 (2021) [DOI] [ARXIV]
  4. Jeffrey, N et al.,
    Dark Energy Survey Year 3 results: Curved-sky weak lensing mass map reconstruction,
    Monthly Notices Of The Royal Astronomical Society. 505 (3): 4626-4645 (2021) [DOI] [ARXIV]
  5. Soo, JYH et al.,
    The PAU Survey: narrowband photometric redshifts using Gaussian processes,
    Monthly Notices Of The Royal Astronomical Society. 503 (3): 4118-4135 (2021) [DOI] [ARXIV]
  6. Pedersen, C et al.,
    An emulator for the Lyman-$\alpha$ forest in beyond-$\Lambda$CDM cosmologies,
    Journal Of Cosmology And Astroparticle Physics. (5): 33- (2021) [DOI] [ARXIV]
  7. Turner, S et al.,
    Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning,
    Monthly Notices Of The Royal Astronomical Society. 503 (2): 3010-3031 (2021) [DOI] [ARXIV]
  8. Alarcon, A et al.,
    The PAU Survey: An improved photo-z sample in the COSMOS field,
    Monthly Notices Of The Royal Astronomical Society. 501 (4): 6103-6122 (2021) [DOI] [ARXIV]
  9. Vielzeuf, P et al.,
    Dark energy survey year 1 results: The lensing imprint of cosmic voids on the cosmic microwave background,
    Monthly Notices Of The Royal Astronomical Society. 500 (1): 464-480 (2021) [DOI] [ARXIV]
  10. Jimenez J et al.,
    Integration of a testbench for the optical and thermal characterization of near-infrared detectors used in ground and space-based astronomy,
    Ieee Transactions On Instrumentation And Measurement. 70 (2021) [DOI]
  11. Tortorelli, L et al.,
    The PAU survey: measurement of narrow-band galaxy properties with approximate bayesian computation,
    Journal Of Cosmology And Astroparticle Physics. (12): 13- (2021) [DOI] [ARXIV]
  12. Gatti, M et al.,
    Dark Energy Survey Year 3 Results: Weak Lensing Shape Catalogue,
    Monthly Notices Of The Royal Astronomical Society. 504 (3): 4312-4336 (2021) [DOI] [ARXIV]
  13. Alam, S et al.,
    Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological implications from two decades of spectroscopic surveys at the Apache Point Observatory,
    Physical Review d. 103 (8): 83533- (2021) [DOI] [ARXIV]
  14. Ferrero, I et al.,
    Dark Energy Survey Year 3 Results: Galaxy mock catalogs for BAO analysis,
    Astronomy & Astrophysics. 656 A106- (2021) [DOI] [ARXIV]
  15. Adhikari, S et al.,
    Probing Galaxy Evolution in Massive Clusters Using ACT and DES: Splashback as a Cosmic Clock,
    Astrophysical Journal Letters. 923 (1): 37- (2021) [DOI] [ARXIV]
  16. Pocino, A et al.,
    Euclid preparation XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses,
    Astronomy & Astrophysics. 655 A44- (2021) [DOI] [ARXIV]
  17. Cheng, TY et al.,
    Galaxy morphological classification catalogue of the Dark Energy Survey Year 3 data with convolutional neural networks,
    Monthly Notices Of The Royal Astronomical Society. 507 (3): 4425-4444 (2021) [DOI] [ARXIV]
  18. Yu, ZF et al.,
    OzDES Reverberation Mapping Programme: the first Mg II lags from 5 yr of monitoring,
    Monthly Notices Of The Royal Astronomical Society. 507 (3): 3771-3788 (2021) [DOI] [ARXIV]
  19. Shin, T et al.,
    The mass and galaxy distribution around SZ-selected clusters,
    Monthly Notices Of The Royal Astronomical Society. 507 (4): 5758-5779 (2021) [DOI] [ARXIV]
  20. Bernardinelli, PH et al.,
    C/2014 UN271 (Bernardinelli-Bernstein): The Nearly Spherical Cow of Comets,
    Astrophysical Journal Letters. 921 (2): L37- (2021) [DOI] [ARXIV]
  21. Martinelli, M et al.,
    Euclid: Constraining dark energy coupled to electromagnetism using astrophysical and laboratory data,
    Astronomy & Astrophysics. 654 A148- (2021) [DOI] [ARXIV]
  22. Friedrich, O et al.,
    Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit,
    Monthly Notices Of The Royal Astronomical Society. 508 (3): 3125-3165 (2021) [DOI] [ARXIV]
  23. Vega-Ferrero, J et al.,
    Pushing automated morphological classifications to their limits with the Dark Energy Survey,
    Monthly Notices Of The Royal Astronomical Society. 506 (2): 1927-1943 (2021) [DOI] [ARXIV]
  24. Wiseman, P et al.,
    Rates and delay times of Type Ia supernovae in the Dark Energy Survey,
    Monthly Notices Of The Royal Astronomical Society. 506 (3): 3330-3348 (2021) [DOI] [ARXIV]
  25. Fortino, WF et al.,
    Reducing Ground-based Astrometric Errors with Gaia and Gaussian Processes,
    Astronomical Journal. 162 (3): 106- (2021) [DOI] [ARXIV]
  26. Stanford, SA et al.,
    Euclid Preparation. XIV. The Complete Calibration of the Color-Redshift Relation (C3R2) Survey: Data Release 3,
    Astrophysical Journal Supplement Series. 256 (1): 9- (2021) [DOI] [ARXIV]
  27. Munoz, AJ et al.,
    Euclid: Estimation of the Impact of Correlated Readout Noise for Flux Measurements with the Euclid NISP Instrument,
    Publications Of The Astronomical Society Of The Pacific. 133 (1027): 94502- (2021) [DOI] [ARXIV]
  28. Davies, LJM et al.,
    Deep Extragalactic VIsible Legacy Survey (DEVILS): consistent multiwavelength photometry for the DEVILS regions (COSMOS, XMMLSS, and ECDFS),
    Monthly Notices Of The Royal Astronomical Society. 506 (1): 256-287 (2021) [DOI] [ARXIV]
  29. Fumagalli, A et al.,
    Euclid: Effects of sample covariance on the number counts of galaxy clusters,
    Astronomy & Astrophysics. 652 A21- (2021) [DOI] [ARXIV]
  30. Lemos, P et al.,
    Assessing tension metrics with dark energy survey and Planck data,
    Monthly Notices Of The Royal Astronomical Society. 505 (4): 6179-6194 (2021) [DOI] [ARXIV]
  31. Andrade-Oliveira, F et al.,
    Galaxy clustering in harmonic space from the dark energy survey year 1 data: compatibility with real-space results,
    Monthly Notices Of The Royal Astronomical Society. 505 (4): 5714-5724 (2021) [DOI] [ARXIV]
  32. Cantu, SA et al.,
    A Deeper Look at des Dwarf Galaxy Candidates: Grus i and Indus ii,
    Astrophysical Journal Letters. 916 (2): 81- (2021) [DOI] [ARXIV]
  33. Abbott, TMC et al.,
    The Dark Energy Survey Data Release 2,
    Astrophysical Journal Supplement Series. 255 (2): 20- (2021) [DOI] [ARXIV]
  34. Grayling, M et al.,
    Understanding the extreme luminosity of DES14X2fna,
    Monthly Notices Of The Royal Astronomical Society. 505 (3): 3950-3967 (2021) [DOI] [ARXIV]
  35. Myles, J et al.,
    Dark Energy Survey Year 3 results: redshift calibration of the weak lensing source galaxies,
    Monthly Notices Of The Royal Astronomical Society. 505 (3): 4249-4277 (2021) [DOI] [ARXIV]
  36. Vincenzi, M et al.,
    The Dark Energy Survey supernova programme: modelling selection efficiency and observed core-collapse supernova contamination,
    Monthly Notices Of The Royal Astronomical Society. 505 (2): 2819-2839 (2021) [DOI] [ARXIV]
  37. Knabenhans, M et al.,
    Euclid preparation: IX. EuclidEmulator2-power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations,
    Monthly Notices Of The Royal Astronomical Society. 505 (2): 2840-2869 (2021) [DOI] [ARXIV]
  38. Chen, A et al.,
    Constraints on dark matter to dark radiation conversion in the late universe with DES-Y1 and external data,
    Physical Review d. 103 (12): 123528- (2021) [DOI] [ARXIV]
  39. Sevilla-Noarbe, I et al.,
    Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology,
    Astrophysical Journal Supplement Series. 254 (2): 24- (2021) [DOI] [ARXIV]
  40. Grandis, S et al.,
    Exploring the contamination of the DES-Y1 cluster sample with SPT-SZ selected clusters,
    Monthly Notices Of The Royal Astronomical Society. 504 (1): 1253-1272 (2021) [DOI] [ARXIV]
  41. Inserra, C et al.,
    The first Hubble diagram and cosmological constraints using superluminous supernovae,
    Monthly Notices Of The Royal Astronomical Society. 504 (2): 2535-2549 (2021) [DOI] [ARXIV]
  42. Martinelli, M et al.,
    Euclid: Impact of non-linear and baryonic feedback prescriptions on cosmological parameter estimation from weak lensing cosmic shear,
    Astronomy & Astrophysics. 649 A100- (2021) [DOI] [ARXIV]
  43. Doux, C et al.,
    Dark Energy Survey internal consistency tests of the joint cosmological probes analysis with posterior predictive distributions,
    Monthly Notices Of The Royal Astronomical Society. 503 (2): 2688-2705 (2021) [DOI] [ARXIV]
  44. Doux, C et al.,
    Consistency of cosmic shear analyses in harmonic and real space,
    Monthly Notices Of The Royal Astronomical Society. 503 (3): 3796-3817 (2021) [DOI] [ARXIV]
  45. Koushan, S et al.,
    GAMA/DEVILS: Constraining the cosmic star-formation history from improved measurements of the 0.3-2.2 micron Extragalactic Background Light,
    Monthly Notices Of The Royal Astronomical Society. 503 (2): 2033-2052 (2021) [DOI] [ARXIV]
  46. To, C et al.,
    Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations,
    Physical Review Letters. 126 (14): 141301- (2021) [DOI] [ARXIV]
  47. Manzoni, G et al.,
    Modelling the quenching of star formation activity from the evolution of the colour-magnitude relation in VIPERS,
    New Astronomy. 84 101515- (2021) [DOI] [ARXIV]
  48. Mucesh, S et al.,
    A machine learning approach to galaxy properties: joint redshift-stellar mass probability distributions with Random Forest,
    Monthly Notices Of The Royal Astronomical Society. 502 (2): 2770-2786 (2021) [DOI] [ARXIV]
  49. Huang, HJ et al.,
    Dark Energy Survey Year 1 Results: Constraining Baryonic Physics in the Universe,
    Monthly Notices Of The Royal Astronomical Society. 502 (4): 6010-6031 (2021) [DOI] [ARXIV]
  50. Aguena, M et al.,
    The WaZP galaxy cluster sample of the Dark Energy Survey Year 1,
    Monthly Notices Of The Royal Astronomical Society. 502 (3): 4435-4456 (2021) [DOI] [ARXIV]
  51. Stringer, KM et al.,
    Identifying RR Lyrae Variable Stars in Six Years of the Dark Energy Survey,
    Astrophysical Journal Letters. 911 (2): 109- (2021) [DOI] [ARXIV]
  52. Napier, KJ et al.,
    No evidence for orbital clustering in the extreme trans-Neptunian objects,
    Planetary Science Journal. 2 (2): 59- (2021) [DOI] [ARXIV]
  53. Ilbert, O et al.,
    Euclid preparation: XI. Mean redshift determination from galaxy redshift probabilities for cosmic shear tomography,
    Astronomy & Astrophysics. 647 A117- (2021) [DOI] [ARXIV]
  54. Renard, P et al.,
    The PAU survey: Ly ? intensity mapping forecast,
    Monthly Notices Of The Royal Astronomical Society. 501 (3): 3883-3899 (2021) [DOI] [ARXIV]
  55. Kelsey, L et al.,
    The effect of environment on Type Ia supernovae in the Dark Energy Survey three-year cosmological sample,
    Monthly Notices Of The Royal Astronomical Society. 501 (4): 4861-4876 (2021) [DOI] [ARXIV]
  56. Hilton, M et al.,
    The Atacama Cosmology Telescope: A Catalog of >4000 Sunyaev-Zel'dovich Galaxy Clusters,
    Astrophysical Journal Supplement Series. 253 (1): 3- (2021) [DOI] [ARXIV]
  57. Nadler, EO et al.,
    Milky Way Satellite Census. III. Constraints on Dark Matter Properties from Observations of Milky Way Satellite Galaxies,
    Physical Review Letters. 126 (9): 91101- (2021) [DOI] [ARXIV]
  58. Costanzi, M et al.,
    Cosmological constraints from des Y1 cluster abundances and SPT multiwavelength data,
    Physical Review d. 103 (4): 43522- (2021) [DOI] [ARXIV]
  59. Shajib AJ et al.,
    Erratum: Is every strong lens model unhappy in its own way? Uniform modelling of a sample of 13 quadruply+ imaged quasars(Monthly Notices of the Royal Astronomical Society (2019) 483:4 (5649–5671) DOI: 10.1093/mnras/sty3397),
    Monthly Notices Of The Royal Astronomical Society. 501 (2): 2833-2835 (2021) [DOI] [ARXIV]
  60. Tanoglidis, D et al.,
    Shadows in the Dark: Low-surface-brightness Galaxies Discovered in the Dark Energy Survey,
    Astrophysical Journal Supplement Series. 252 (2): 18- (2021) [DOI] [ARXIV]
  61. Jarvis, M et al.,
    Dark Energy Survey year 3 results: point spread function modelling,
    Monthly Notices Of The Royal Astronomical Society. 501 (1): 1282-1299 (2021) [DOI] [ARXIV]
  62. Sampaio-Santos, H et al.,
    Is diffuse intracluster light a good tracer of the galaxy cluster matter distribution?,
    Monthly Notices Of The Royal Astronomical Society. 501 (1): 1300-1315 (2021) [DOI] [ARXIV]
  63. Porredon, A et al.,
    Dark Energy Survey Year 3 results: Optimizing the lens sample in a combined galaxy clustering and galaxy-galaxy lensing analysis,
    Physical Review d. 103 (4): 43503- (2021) [DOI] [ARXIV]
  64. Muir, J et al.,
    DES Y1 results: Splitting growth and geometry to test ΛcDM,
    Physical Review d. 103 (2): 23528- (2021) [DOI] [ARXIV]
  65. Yang, Q et al.,
    Spectral Variability of a Sample of Extreme Variability Quasars and Implications for the MgII Broad-line Region,
    Monthly Notices Of The Royal Astronomical Society. 493 (4): 5773-5787 (2021) [DOI] [ARXIV]
  66. Mawdsley, B et al.,
    Dark Energy Survey Year 1 Results: Wide Field Mass Maps via Forward Fitting in Harmonic Space,
    Monthly Notices Of The Royal Astronomical Society. 493 (4): 5662-5679 (2021) [DOI] [ARXIV]
  67. Henghes, B et al.,
    Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects,
    Publications Of The Astronomical Society Of The Pacific. 133 (1019): 14501- (2021) [DOI] [ARXIV]
  68. Liao, WT et al.,
    Discovery of a candidate binary supermassive black hole in a periodic quasar from circumbinary accretion variability,
    Monthly Notices Of The Royal Astronomical Society. 500 (3): 4025-4041 (2021) [DOI] [ARXIV]
  69. Johnston, H et al.,
    The PAU Survey: Intrinsic alignments and clustering of narrow-band photometric galaxies,
    Astronomy & Astrophysics. 646 A147- (2021) [DOI] [ARXIV]