University of Manchester-ko ikertzaileekin lankidetzan egindako argitalpenak (63)

2024

  1. Euclid preparation XLI. Galaxy power spectrum modelling in real space

    Astronomy and Astrophysics, Vol. 687

  2. Euclid preparation XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning

    Astronomy and Astrophysics, Vol. 689

  3. Euclid preparation XLVI. The near-infrared background dipole experiment with Euclid

    Astronomy and Astrophysics, Vol. 689

  4. Euclid preparation XLVIII. The pre-launch Science Ground Segment simulation framework

    Astronomy and Astrophysics, Vol. 690

  5. Euclid preparation XXXVI. Modelling the weak lensing angular power spectrum

    Astronomy and Astrophysics, Vol. 684

  6. Euclid preparation XXXVII. Galaxy colour selections with Euclid and ground photometry for cluster weak-lensing analyses

    Astronomy and Astrophysics, Vol. 684

  7. Euclid preparation: XL. Impact of magnification on spectroscopic galaxy clustering

    Astronomy and Astrophysics, Vol. 685

  8. Euclid preparation: XLII. A unified catalogue-level reanalysis of weak lensing by galaxy clusters in five imaging surveys

    Astronomy and Astrophysics, Vol. 689

  9. Euclid preparation: XLIV. Modelling spectroscopic clustering on mildly nonlinear scales in beyond-ΛCDM models

    Astronomy and Astrophysics, Vol. 689

  10. Euclid preparation: XLVII. Improving cosmological constraints using a new multi-tracer method with the spectroscopic and photometric samples

    Astronomy and Astrophysics, Vol. 690

  11. Euclid preparation: XXXI. The effect of the variations in photometric passbands on photometric-redshift accuracy

    Astronomy and Astrophysics, Vol. 681

  12. Euclid preparation: XXXII. Evaluating the weak-lensing cluster mass biases using the Three Hundred Project hydrodynamical simulations

    Astronomy and Astrophysics, Vol. 681

  13. Euclid preparation: XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong-lensing events

    Astronomy and Astrophysics, Vol. 681

  14. Euclid preparation: XXXIX. The effect of baryons on the halo mass function

    Astronomy and Astrophysics, Vol. 685

  15. Euclid preparation: XXXV. Covariance model validation for the two-point correlation function of galaxy clusters

    Astronomy and Astrophysics, Vol. 683

  16. Euclid preparation: XXXVIII. Spectroscopy of active galactic nuclei with NISP

    Astronomy and Astrophysics, Vol. 685

  17. Euclid: Identifying the reddest high-redshift galaxies in the Euclid Deep Fields with gradient-boosted trees

    Astronomy and Astrophysics, Vol. 685

  18. Euclid: Testing photometric selection of emission-line galaxy targets?

    Astronomy and Astrophysics, Vol. 689

2023

  1. Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

    Monthly Notices of the Royal Astronomical Society, Vol. 520, Núm. 3, pp. 3529-3548

  2. Euclid preparation: XXII. Selection of quiescent galaxies from mock photometry using machine learning

    Astronomy and Astrophysics, Vol. 671