2025/07/09 by Thomas Bakx, Bakx, Thomas, Toshiki Kurita +7 · 1 voice · 1 citation
Physics and Astronomy · #Cosmology and Gravitation Theories #Dark Matter and Cosmic Phenomena #Galaxies: Formation, Evolution, Phenomena
paper · doi:10.33232/001c.156361
openalex publication_date 2026/02/06 · openalex created_date 2026/02/07 · openalex updated_date 2026/02/08
We measure three-dimensional bispectra of halo intrinsic alignments (IA) and dark matter overdensities in real space from N-body simulations for halos of mass <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:msup> <mml:mn>10</mml:mn> <mml:mn>12</mml:mn> </mml:msup> <mml:mo>−</mml:mo> <mml:msup> <mml:mn>10</mml:mn> <mml:mn>12.5</mml:mn> </mml:msup> <mml:msub> <mml:mi>M</mml:mi> <mml:mo>⊙</mml:mo> </mml:msub> <mml:mi>/</mml:mi> <mml:mi>h</mml:mi> </mml:mrow> </mml:math> . We show that their multipoles with respect to the line of sight can be accurately described by a tree-level perturbation theory model on large scales ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mo>≲</mml:mo> <mml:mn>0.11</mml:mn> <mml:mspace width="0.167em"/> <mml:mi>h</mml:mi> </mml:mrow> </mml:math> /Mpc) at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>z</mml:mi> <mml:mo>=</mml:mo> <mml:mn>0</mml:mn> </mml:mrow> </mml:math> . For these scales and in a simulation volume of 1 (Gpc/ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>h</mml:mi> <mml:msup> <mml:mo stretchy="false" form="postfix">)</mml:mo> <mml:mn>3</mml:mn> </mml:msup> </mml:mrow> </mml:math> , we detect the bispectrum monopole <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msubsup> <mml:mi>B</mml:mi> <mml:mrow> <mml:mi>δ</mml:mi> <mml:mi>δ</mml:mi> <mml:mi>E</mml:mi> </mml:mrow> <mml:mn>00</mml:mn> </mml:msubsup> </mml:math> at . We also report similar for the lowest order multipoles of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>B</mml:mi> <mml:mrow> <mml:mi>δ</mml:mi> <mml:mi>E</mml:mi> <mml:mi>E</mml:mi> </mml:mrow> </mml:msub> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>B</mml:mi> <mml:mrow> <mml:mi>E</mml:mi> <mml:mi>E</mml:mi> <mml:mi>E</mml:mi> </mml:mrow> </mml:msub> </mml:math> , although these are largely driven by stochastic contributions. We show that the first and second order EFT parameters are consistent with those obtained from fitting the IA power spectrum analysis at next-to-leading order, without requiring any priors to break degeneracies for the quadratic bias parameters. Moreover, the inclusion of higher multipole moments of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>B</mml:mi> <mml:mrow> <mml:mi>δ</mml:mi> <mml:mi>δ</mml:mi> <mml:mi>E</mml:mi> </mml:mrow> </mml:msub> </mml:math> greatly reduces the errors on second order bias parameters, by factors of 5 or more. The IA bispectrum thus provides an effective means of determining higher order shape bias parameters, thereby characterizing the scale dependence of the IA signal. We also detect parity-odd bispectra such as <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>B</mml:mi> <mml:mrow> <mml:mi>δ</mml:mi> <mml:mi>δ</mml:mi> <mml:mi>B</mml:mi> </mml:mrow> </mml:msub> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>B</mml:mi> <mml:mrow> <mml:mi>δ</mml:mi> <mml:mi>E</mml:mi> <mml:mi>B</mml:mi> </mml:mrow> </mml:msub> </mml:math> at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mo>∼</mml:mo> <mml:mn>10</mml:mn> <mml:mi>σ</mml:mi> </mml:mrow> </mml:math> significance or more for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mo><</mml:mo> <mml:mn>0.15</mml:mn> <mml:mspace width="0.167em"/> <mml:mi>h</mml:mi> </mml:mrow> </mml:math> /Mpc and they are consistent with the parity-even sector. Furthermore, we check that the Gaussian covariance approximation works reasonably well on the scales we consider here. These results lay the groundwork for using the bispectrum of IA in cosmological analyses.