A Forecast of the Sensitivity of the DALI Experiment to Galactic Axion Dark Matter

Bibcode
2024Symm...16..163H
DOI
10.3390/sym16020163
Hernández-Cabrera, Juan F.; De Miguel, Javier; Joven Álvarez, Enrique; Hernández-Suárez, E.; Rubiño-Martín, J. Alberto; Otani, Chiko
Bibliographical reference

Symmetry

Advertised on:
1
2024
Number of authors
6
IAC number of authors
5
Citations
4
Refereed citations
2
Description
The axion is a long-postulated boson that can simultaneously solve two fundamental problems of modern physics: the charge–parity symmetry problem in the strong interaction and the enigma of dark matter. In this work, we estimate, by means of Monte Carlo simulations, the sensitivity of the Dark-photons & Axion-Like particles Interferometer (DALI), a new-generation Fabry–Pérot haloscope proposed to probe axion dark matter in the 25–250 μeV band.
Type
Refereed
Dark matter

It may interest you

  • Refereed
    An ultra-short-period super-Earth with an extremely high density and an outer companion
    We present the discovery and characterization of a new multi-planetary system around the Sun-like star K2-360 (EPIC 201595106). K2-360 was first identified in K2 photometry as the host of an ultra-short-period (USP) planet candidate with a period of 0.88 d. We obtained follow-up transit photometry, confirming the star as the host of the signal
    Livingston, John H. et al.

    Advertised on:

    11
    2024
    Bibcode
    2024NatSR..1427219L
    Citations
    0
  • Refereed
    Neural calibration of imaging Stokes polarimeters
    Current polarimetric calibration techniques derive the instrument modulation matrix by numerically fitting an instrumental model to measurements of a set of calibration Stokes vectors. These techniques are typically limited to an error on the retrieved normalized Stokes Q, U and V parameters, in the $1\times10^{-2}$ to $1\times10^{-3}$ range. This
    Iglesias, F. A. et al.

    Advertised on:

    8
    2024
    Bibcode
    2024BAAA...65..281I
    Citations
    0
  • Refereed
    Model-based identification of solar coronal mass ejections using deep neural networks
    Coronal mass ejections (CMEs) are a major driver of space weather and thus can have important negative technological and social impacts. To assess their geoeffectiveness once they are ejected, it is crucial their prompt identification in coronagraph images. In the last decade, deep neural networks (DNN) have experienced enormous improvements in
    Iglesias, F. A. et al.

    Advertised on:

    8
    2024
    Bibcode
    2024BAAA...65...17I
    Citations
    0