Reconstructing the spectral shape of a stochastic gravitational wave background with LISA (1906.09244v1)

Abstract: We present a set of tools to assess the capabilities of LISA to detect and reconstruct the spectral shape and amplitude of a stochastic gravitational wave background (SGWB). We first provide the LISA power-law sensitivity curve and binned power-law sensitivity curves, based on the latest updates on the LISA design. These curves are useful to make a qualitative assessment of the detection and reconstruction prospects of a SGWB. For a quantitative reconstruction of a SGWB with arbitrary power spectrum shape, we propose a novel data analysis technique: by means of an automatized adaptive procedure, we conveniently split the LISA sensitivity band into frequency bins, and fit the data inside each bin with a power law signal plus a model of the instrumental noise. We apply the procedure to SGWB signals with a variety of representative frequency profiles, and prove that LISA can reconstruct their spectral shape. Our procedure, implemented in the code SGWBinner, is suitable for homogeneous and isotropic SGWBs detectable at LISA, and it is also expected to work for other gravitational wave observatories.

• The paper introduces an adaptive reconstruction technique that segments LISA's frequency band with binned power-law fits to extract SGWB signals.
• It employs detailed noise modeling and Monte Carlo simulations to distinguish gravitational wave signals from instrumental noise.
• The findings enhance detection strategies and provide crucial insights into cosmic and early universe processes influencing SGWB profiles.

Reconstructing the Spectral Shape of a Stochastic Gravitational Wave Background with LISA

The paper titled "Reconstructing the spectral shape of a stochastic gravitational wave background with LISA" addresses a fundamental challenge in gravitational wave astronomy: the detection and characterization of a Stochastic Gravitational Wave Background (SGWB) using the Laser Interferometer Space Antenna (LISA). The authors provide a comprehensive methodological framework for the reconstruction of the spectral shape of SGWBs, offering a data analysis technique apt for this task.

Gravitational waves (GWs) provide a unique lens through which to explore cosmic events and conditions not accessible through traditional electromagnetic observations. SGWBs can originate from both cosmological (e.g., inflationary processes, cosmic strings) and astrophysical (e.g., binary mergers, supernovae) sources. The challenge lies in the fact that these backgrounds are often stochastic and their spectral shapes are complex and not immediately apparent from observational data.

The paper focuses on reconstructing the spectral shape of a SGWB using a rigorous method tailored for LISA, which ESA (European Space Agency) has approved and is scheduled to probe the mHz frequency band. The authors introduce a novel adaptive procedure that divides the LISA sensitivity band into frequency bins, employing a power-law fit within each bin. This method allows for the assessment of the spectral profile of GWs amidst the instrumental noise, specifically in the presence of variance across the sensitivity band.

The innovation in their approach lies in the adaptability and specificity of the power-law sensitivity curves for LISA, including the so-called "binned PLS", which considers the segmentation of the frequency domain. The procedure is implemented in the SGWBinner code, optimized for LISA but adaptable for other observatories, expanding its utility across platforms.

Key contributions of the paper include:

1. Noise Model and Sensitivity Curve: The modeling of LISA's instrumental noise is addressed by considering both the optical metrology system and mass acceleration noise. The noise model forms the foundation for generating the sensitivity curves fundamental for the SGWB analysis.
2. Power-Law Sensitivity (PLS): The authors construct PLS curves, which graphically depict LISA's capability to detect a power-law spectrum of gravitational waves across varying slopes, ensuring a minimum signal-to-noise ratio (SNR). The binned PLS further assists in handling SGWBs with complex frequency profiles.
3. Signal Reconstruction: The heart of the paper lies in the signal reconstruction algorithm, which employs Monte Carlo simulations to validate their methodology. Results demonstrate the ability to reconstruct SGWB signals with various profiles, from single power laws to more exotic shapes (e.g., peaked or oscillatory spectra).

The paper holds implications for both theoretical predictions and practical applications. It not only aids the detection strategy for SGWBs but also offers a framework for distinguishing between physical processes that produce different spectral signatures. The ability to effectively reconstruct SGWB profiles can shed light on early universe conditions and source-specific characteristics, informing both cosmology and gravitational physics.

In terms of future developments, the approach may be extended to other frequency bands and GW observatories, potentially providing a unified framework for SGWB analysis. Moreover, continued refinement of noise models and sensitivity predictions will be crucial for enhancing detection capabilities and accuracy.

In sum, this work provides vital progress towards the quantitative analysis of SGWBs, offering a robust methodological tool for LISA and illustrating the complex yet promising nature of gravitational wave background research.