Speaker
Description
The Distributed Data Processing Centre (DDPC) is developing the data analysis methods and pipelines required to fully exploit the unique observational capabilities of LISA, opening access to the millihertz band and enabling precision gravitational-wave astronomy. This may provide a pathway to probing physics beyond the last scattering surface. However, the associated data analysis challenges are substantial. To address them, the DDPC is producing a suite of common datasets of increasing complexity, designed to reflect the richness of signals expected in LISA data streams.
The Mojito Heavy dataset will include three cosmological stochastic background components (provided as configurable options), spanning representative spectral morphologies: (1) a broken power-law spectrum characteristic of first-order phase transitions, (2) a double-peaked spectrum arising from scalar-induced gravitational waves, and (3) an approximately flat in-band spectrum representative of cosmic string signals. In addition, the dataset incorporates an extragalactic astrophysical foreground from compact binaries (double white dwarfs).
All components are generated as isotropic in the CMB rest frame and propagated through the full LISA response, including realistic spacecraft orbits, second-generation time-delay interferometry (TDI), and representative instrumental noise.
In this talk, I will present the current status of the dataset generation, planned for release in October 2026, as well as strategies for its exploitation beyond the DDPC. In particular, I will discuss approaches to cosmological signal extraction that leverage distinctive features of the signal, including Doppler-induced anisotropies, as part of a newly proposed collaborative project within the LISA Consortium Working Group.