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Assessing astrophysical foreground subtraction in DECIGO using compact binary populations inferred from the first part of the LIGO-Virgo-KAGRA's fourth observation run

Takahiro S. Yamamoto

TL;DR

The study tackles detecting a primordial stochastic GW background with DECIGO by foreground subtraction of astrophysical CBC signals inferred from LVK GWTC-4 populations. It evaluates two subtraction approaches—direct best-fit removal and the Cutler–Harms projection—collecting the astrophysical foreground $Ω_ ext{fg}(f)$ via redshift integration using a population model that includes BBH and BNS merger rates and mass distributions. The results demonstrate that projecting out first-order parameter-deviation effects reduces subtraction residuals by about two orders of magnitude, enabling primordial levels $Ω_{gw} o 10^{-16}$ to be detectable in DECIGO's band when combined with a reasonable SNR threshold; unres and subthreshold components are kept under control with the projection. The work highlights the necessity of the projection technique for DECIGO's primordial SGWB searches and discusses practical considerations, including computational demands and unresolved foregrounds (e.g., white-dwarf binaries) that warrant further investigation.

Abstract

Detecting the stochastic gravitational wave background (SGWB) from our Universe under the inflationary era is one of the primary scientific objectives of DECIGO, a space-borne gravitational wave detector sensitive in the 0.1 Hz frequency band. This frequency band is dominated by the gravitational waves from inspiraling compact object binaries. Subtracting these signals is necessary to search for the primordial SGWB. In this paper, we assess the feasibility of the subtraction of such binary signals by employing the population model inferred from the latest gravitational wave event catalogue of the LIGO-Virgo-KAGRA Collaboration. We find that the projection scheme, which was originally proposed by Cutler & Harms (2005), is necessary to reduce the binary signals to the level where DECIGO can detect the primordial background.

Assessing astrophysical foreground subtraction in DECIGO using compact binary populations inferred from the first part of the LIGO-Virgo-KAGRA's fourth observation run

TL;DR

The study tackles detecting a primordial stochastic GW background with DECIGO by foreground subtraction of astrophysical CBC signals inferred from LVK GWTC-4 populations. It evaluates two subtraction approaches—direct best-fit removal and the Cutler–Harms projection—collecting the astrophysical foreground via redshift integration using a population model that includes BBH and BNS merger rates and mass distributions. The results demonstrate that projecting out first-order parameter-deviation effects reduces subtraction residuals by about two orders of magnitude, enabling primordial levels to be detectable in DECIGO's band when combined with a reasonable SNR threshold; unres and subthreshold components are kept under control with the projection. The work highlights the necessity of the projection technique for DECIGO's primordial SGWB searches and discusses practical considerations, including computational demands and unresolved foregrounds (e.g., white-dwarf binaries) that warrant further investigation.

Abstract

Detecting the stochastic gravitational wave background (SGWB) from our Universe under the inflationary era is one of the primary scientific objectives of DECIGO, a space-borne gravitational wave detector sensitive in the 0.1 Hz frequency band. This frequency band is dominated by the gravitational waves from inspiraling compact object binaries. Subtracting these signals is necessary to search for the primordial SGWB. In this paper, we assess the feasibility of the subtraction of such binary signals by employing the population model inferred from the latest gravitational wave event catalogue of the LIGO-Virgo-KAGRA Collaboration. We find that the projection scheme, which was originally proposed by Cutler & Harms (2005), is necessary to reduce the binary signals to the level where DECIGO can detect the primordial background.
Paper Structure (11 sections, 48 equations, 6 figures)

This paper contains 11 sections, 48 equations, 6 figures.

Figures (6)

  • Figure 1: Configuration of DECIGO. In this work, we assume two triangle-shaped consterations and one six-pointed star consteration.
  • Figure 2: PSD of DECIGO that is taken from Yagi & Seto Yagi:2011wg
  • Figure 3: Three components of the foreground. The cross-hatched region is the unresolvable part contributing to $\Omega_\mathrm{unres}$. Binaries in the region hatched by the diagonal lines generate the subthreshold component, $\Omega_\mathrm{subth}$. The region hatched by the horizontal lines corresponds to the detectable part, in which binaries can be detected as individual events. The errors in parameter estimation for these binaries contribute $\Omega_\mathrm{err}$. The blue line shows $z_\mathrm{upper}$ defined by Eq \ref{['eq: zupper']}. The green line is $\mathfrak{z}$ that is defined by Eq. \ref{['eq: mathfrak z']}. The orange dashed line is the upper bound of the detectable region. The right blank region indicates that there are no BNS because it is a frequency band above the last stable orbit, and we ignore the merger and the post-merger part.
  • Figure 4: Astrophysical foreground of BNS and the subtracted residuals. We assume the SNR threshold of 10. The black thin line shows the total foreground. The blue thin line is the unresolvable component. The red thick and purple thick lines are the subtraction residual and the projected one, respectively. The green dotted line is the subthreshold component, which is too small to appear in this plot. The gray line is the minimum amplitude of $\Omega_\mathrm{gw}(f)$ that can be detectable by DECIGO with the SNR larger than unity. The magenta dashed line shows the fiducial value e-16 of the primordial GW background.
  • Figure 5: Foreground estimation for BBH. The legends are the same as Fig. \ref{['fig: bns snrth10']}, while the plot ranges of the frequency and $\Omega_\mathrm{gw}(f)$ are broader than those of Fig. \ref{['fig: bns snrth10']}.
  • ...and 1 more figures