[PulsarMAP] Pulsar Mode-changing And Polarization: mapping out a connected picture of neutron star evolution
Ente: European Commission
Scadenza: 2031-08-31
Importo max: 1.447.903 EUR
Paese: EU
Descrizione
Why is pulsar radio emission time-variable? How does the pulsar magnetic field evolve over its lifetime? The answers will change the landscape of fundamental physics, advancing our understanding of the universe’s most extreme environments and transforming the search for gravitational waves with pulsar timing arrays. Pulsars are spinning magnetized neutron stars emitting a beam of radio waves, and this radio beam is our direct observational link to an environment with some of the highest densities and gravitational field strengths imaginable. The key to answering those two questions is that they are connected: time-variability originates in the pulsar magnetosphere and is affected by the magnetic field. I will exploit this connection to understand neutron star evolution as a whole.
I propose three work packages to map the evolution of neutron stars, capitalising on surveys, statistics and machine-learning. Their objectives, and the impact of the results, are as follows:
1. GalaxyMap: I will prove or disprove the existence of compact anisotropic structures in the interstellar medium, transforming our knowledge of galactic structure and evolution.
2. ModingMap: I will map out how mode-changing and nulling affect the pulsar population, radically advancing pulsar timing accuracy for gravitational wave searches.
3. PopulationMap: I will capture the origins of radio pulsar time-variability in the magnetosphere by linking it to polarization, revolutionising our understanding of extreme neutron star physics, and the connection to magnetars and Fast Radio Bursts.
I will address these objectives with my unique combined expertise in ISM physics, pulsar polarization and large-scale data science. I will apply my Partial Coherence model, develop new simulations to model the impact of scattering on polarization, and exploit unsupervised machine-learning, to characterize pulsar variability and advance fundamental physics with the largest radio pulsar data sets in the world.
Settori: Pulsars, Neutron stars, Interstellar medium, Polarization, Time-variability, Fast Radio Bursts
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