Time-frequency Imprints of Extreme Mass-Ratio Inspirals in Confusion Gravitational Wave Background

Detecting individual extreme-mass-ratio inspirals (EMRIs) is a major science goal of future space-based gravitational wave observatories such as Laser Interferometer Space Antenna (LISA) and TianQin. However, matched-filtering can be challenging as waveform templates are required to be accurate over tens of thousands of orbits. We introduce the time-frequency spectrum as an alternative observable that can be exploited to reveal the chirping of EMRIs at the population level. We analytically calculate this spectrum and its correlators for parameterized populations of slowly chirping sources on quasi-circular orbits, assuming a simplified model of the antenna response for a proof of concept. We then exploit this observable to distinguish between Galactic white dwarf binaries and a possible EMRI population, and quantify the precision at which EMRI population parameters can be determined through a Fisher analysis. We explore several scenarios of EMRI populations and find that this new method may allow us to determine EMRI population parameters at an accuracy level of several percent. Since white dwarf binaries have much longer chirping timescales than the EMRIs do, EMRI population properties can still be determined even if their stochastic gravitational wave background has a power spectrum two orders of magnitude weaker than that of the Galactic white dwarf binaries.

Publication Details

Journal
ArXiv.org
Published
2025-06-20
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Time-frequency Imprints of Extreme Mass-Ratio Inspirals in Confusion Gravitational Wave Background

ArXiv.org
Pulsars and Gravitational Waves Research
article

Time-frequency Imprints of Extreme Mass-Ratio Inspirals in Confusion Gravitational Wave Background

article en

Abstract

Detecting individual extreme-mass-ratio inspirals (EMRIs) is a major science goal of future space-based gravitational wave observatories such as Laser Interferometer Space Antenna (LISA) and TianQin. However, matched-filtering can be challenging as waveform templates are required to be accurate over tens of thousands of orbits. We introduce the time-frequency spectrum as an alternative observable that can be exploited to reveal the chirping of EMRIs at the population level. We analytically calculate this spectrum and its correlators for parameterized populations of slowly chirping sources on quasi-circular orbits, assuming a simplified model of the antenna response for a proof of concept. We then exploit this observable to distinguish between Galactic white dwarf binaries and a possible EMRI population, and quantify the precision at which EMRI population parameters can be determined through a Fisher analysis. We explore several scenarios of EMRI populations and find that this new method may allow us to determine EMRI population parameters at an accuracy level of several percent. Since white dwarf binaries have much longer chirping timescales than the EMRIs do, EMRI population properties can still be determined even if their stochastic gravitational wave background has a power spectrum two orders of magnitude weaker than that of the Galactic white dwarf binaries.

ArXiv.org
Openalex Percentile: Top 56%
Pulsars and Gravitational Waves Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Time-frequency Imprints of Extreme Mass-Ratio Inspirals in Confusion Gravitational Wave Background · ArXiv.org (2025) | TGRS Research Map | TGRS