Browsing by Autor "M Ishak"

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DESI 2024: Constraints on physics-focused aspects of dark energy using DESI DR1 BAO data
(American Physical Society, 2025) K. Lodha; A. Shafieloo; R. Calderón; E. Linder; Wuhyun Sohn; Jorge L. Cervantes–Cota; Arnaud de Mattia; J. García-Bellido; M Ishak; William L. Matthewson
Baryon acoustic oscillation data from the first year of the Dark Energy Spectroscopic Instrument (DESI) provide near percent-level precision of cosmic distances in seven bins over the redshift range $z=0.1--4.2$. This paper is the follow-up to the original DESI BAO cosmology paper [A. G. Adame et al. (DESI Collaboration), arXiv:2404.03002], which considered the conventional ${w}_{0}{w}_{a}$ cold dark matter (CDM) model. We use the novel DESI data, together with other cosmic probes, to constrain the background expansion history using some well-motivated physical classes of dark energy. In particular, we explore three physics-focused behaviors of dark energy from the equation of state and energy density perspectives: the thawing class (matching many simple quintessence potentials), emergent class (where dark energy comes into being recently, as in phase transition models), and mirage class [where phenomenologically the distance to cosmic microwave background (CMB) last scattering is close to that from a cosmological constant $\mathrm{\ensuremath{\Lambda}}$ despite dark energy dynamics]. All three classes fit the data at least as well as $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$, and indeed can improve on it by $\mathrm{\ensuremath{\Delta}}{\ensuremath{\chi}}^{2}\ensuremath{\approx}\ensuremath{-}5$ to $\ensuremath{-}17$ for the combination of DESI BAO with CMB and supernova data while having one more parameter. The mirage class does essentially as well as ${w}_{0}{w}_{a}\mathrm{CDM}$ and exhibits moderate to strong Bayesian evidence preference with respect to $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$. These classes of dynamical behaviors highlight worthwhile avenues for further exploration into the nature of dark energy.
Extended dark energy analysis using DESI DR2 BAO measurements
(American Physical Society, 2025) K. Lodha; R. Calderón; William L. Matthewson; Arman Shafieloo; M Ishak; Jian Pan; C. García-Quintero; D Huterer; Georgios Valogiannis; Luís Alfonso Ureña López
We conduct an extended analysis of dark energy constraints, in support of the findings of the Dark Energy Spectroscopic Instrument (DESI) second data release cosmology key paper, including DESI data, Planck cosmic microwave background observations, and three different supernova compilations. Using a broad range of parametric and nonparametric methods, we explore the dark energy phenomenology and find consistent trends across all approaches, in good agreement with the <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:msub><a:mi>w</a:mi><a:mn>0</a:mn></a:msub><a:msub><a:mi>w</a:mi><a:mi>a</a:mi></a:msub><a:mi>CDM</a:mi></a:math> (cold dark matter) key paper results. Even with the additional flexibility introduced by nonparametric approaches, such as binning and Gaussian processes, we find that extending <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" display="inline"><c:mi mathvariant="normal">Λ</c:mi><c:mi>CDM</c:mi></c:math> to include a two-parameter <f:math xmlns:f="http://www.w3.org/1998/Math/MathML" display="inline"><f:mi>w</f:mi><f:mo stretchy="false">(</f:mo><f:mi>z</f:mi><f:mo stretchy="false">)</f:mo></f:math> is sufficient to capture the trends present in the data. Finally, we examine three dark energy classes with distinct dynamics, including quintessence scenarios satisfying <j:math xmlns:j="http://www.w3.org/1998/Math/MathML" display="inline"><j:mi>w</j:mi><j:mo>≥</j:mo><j:mo>−</j:mo><j:mn>1</j:mn></j:math>, to explore what underlying physics can explain such deviations. The current data indicate a clear preference for models that feature a phantom crossing; although alternatives lacking this feature are disfavored, they cannot yet be ruled out. Our analysis confirms that the evidence for dynamical dark energy, particularly at low redshift (<l:math xmlns:l="http://www.w3.org/1998/Math/MathML" display="inline"><l:mi>z</l:mi><l:mo>≲</l:mo><l:mn>0.3</l:mn></l:math>), is robust and stable under different modeling choices.