Time-delay interferometry without delays
- Resource Type
- Authors
- Michele Vallisneri; Antoine Petiteau; Jean-Baptiste Bayle; Stanislav Babak
- Source
- Phys.Rev.D
Phys.Rev.D, 2021, 103 (8), pp.082001. ⟨10.1103/PhysRevD.103.082001⟩
Physical Review D
Physical Review D, American Physical Society, 2021, 103 (8), pp.082001. ⟨10.1103/PhysRevD.103.082001⟩
- Subject
- Phase (waves)
detector: noise
01 natural sciences
law.invention
cosmic rays
Observatory
law
wave: propagation
0103 physical sciences
Experiments in gravity
Limit (mathematics)
[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]
Linear combination
Representation (mathematics)
010303 astronomy & astrophysics
orbit
Physics
time delay: interferometer
LISA
010308 nuclear & particles physics
gravitational radiation
Observable
Laser
gravitational radiation detector
laser
Interferometry
[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]
time dependence
Algorithm
cosmology
- Language
- English
- ISSN
- 1550-7998
1550-2368
International audience; The space-based gravitational-wave observatory LISA relies on a form of synthetic interferometry (time-delay interferometry, or TDI) where the otherwise overwhelming laser phase noise is canceled by linear combinations of appropriately delayed phase measurements. These observables grow in length and complexity as the realistic features of the LISA orbits are taken into account. In this paper we outline an implicit formulation of TDI where we write the LISA likelihood directly in terms of the basic phase measurements, and we marginalize over the laser phase noises in the limit of infinite laser-noise variance. Equivalently, we rely on TDI observables that are defined numerically (rather than algebraically) from a discrete-filter representation of the laser propagation delays. Our method generalizes to any time dependence of the armlengths; it simplifies the modeling of gravitational-wave signals; and it allows a straightforward treatment of data gaps and missing measurements.