Labrador is a domain-optimized neural posterior estimation tool achieving 1% median importance-sampling efficiency and first extensive coverage of long-duration low-mass gravitational wave signals through equivariance and a stable procedure for differing priors.
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Proposes APTA with 6 satellites and 10^{-18} relative clock uncertainty at 1s averaging to achieve sensitivity for observing 10^3-10^4 solar-mass black hole mergers in the decihertz band.
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labrador: A domain-optimized machine-learning tool for gravitational wave inference
Labrador is a domain-optimized neural posterior estimation tool achieving 1% median importance-sampling efficiency and first extensive coverage of long-duration low-mass gravitational wave signals through equivariance and a stable procedure for differing priors.
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Artificial Precision Timing Array: bridging the decihertz gravitational-wave sensitivity gap with clock satellites
Proposes APTA with 6 satellites and 10^{-18} relative clock uncertainty at 1s averaging to achieve sensitivity for observing 10^3-10^4 solar-mass black hole mergers in the decihertz band.