11 research outputs found
Joint cosmological and gravitational-wave population inference using dark sirens and galaxy catalogues
In the absence of numerous gravitational-wave detections with confirmed
electromagnetic counterparts, the "dark siren" method has emerged as a leading
technique of gravitational-wave cosmology. The method allows redshift
information of such events to be inferred statistically from a catalogue of
potential host galaxies. Due to selection effects, dark siren analyses
necessarily depend on the mass distribution of compact objects and the
evolution of their merger rate with redshift. Informative priors on these
quantities will impact the inferred posterior constraints on the Hubble
constant (). It is thus crucial to vary these unknown distributions during
an inference. This was not possible in earlier analyses due to the high
computational cost, restricting them to either excluding galaxy catalogue
information, or fixing the gravitational-wave population mass distribution and
risking introducing bias to the measurement. This paper introduces a
significantly enhanced version of the Python package GWCOSMO, which allows
joint estimation of cosmological and compact binary population parameters. This
thereby ensures the analysis is now robust to a major source of potential bias.
The gravitational-wave events from the Third Gravitational-Wave Transient
Catalogue are reanalysed with the GLADE+ galaxy catalogue, and an updated, more
reliable measurement of km s Mpc is found
(maximum a posteriori probability and 68% highest density interval). This
improved method will enable cosmological analyses with future
gravitational-wave detections to make full use of the information available
(both from galaxy catalogues and the compact binary population itself), leading
to promising new independent bounds on the Hubble constant.Comment: 30 pages, 11 figure
Science with the Einstein Telescope: a comparison of different designs
The Einstein Telescope (ET), the European project for a third-generation
gravitational-wave detector, has a reference configuration based on a
triangular shape consisting of three nested detectors with 10 km arms, where in
each arm there is a `xylophone' configuration made of an interferometer tuned
toward high frequencies, and an interferometer tuned toward low frequencies and
working at cryogenic temperature. Here, we examine the scientific perspectives
under possible variations of this reference design. We perform a detailed
evaluation of the science case for a single triangular geometry observatory,
and we compare it with the results obtained for a network of two L-shaped
detectors (either parallel or misaligned) located in Europe, considering
different choices of arm-length for both the triangle and the 2L geometries. We
also study how the science output changes in the absence of the low-frequency
instrument, both for the triangle and the 2L configurations. We examine a broad
class of simple `metrics' that quantify the science output, related to compact
binary coalescences, multi-messenger astronomy and stochastic backgrounds, and
we then examine the impact of different detector designs on a more specific set
of scientific objectives.Comment: 197 pages, 72 figure
Characterization of the mono-s di-Higgs signal in ïŹnal states with four b-jets and missing transverse momentum
This report presents a study of a signal characterized by di-Higgs production and Missing Trans- verse Momentum (MET) due to dark matter (DM) pair production. This signature is predicted by a dark Higgs model with additional scalar and vector gauge bosons acting as mediators between the dark sector and Standard Model (SM) particles. Truth level event samples at a pp center-of-mass energy of âs = 13 TeV are generated for comparison of two signal grids, where either the DM candidate or the dark Higgs boson is the lightest particle in the dark sector. The diïŹering mass hierarchies lead to clear distinctions in both the kinematic distributions and cross sections, partly due to the new DM annihilation channel in the latter grid. The associated DM relic abundances are calculated and compared with the observed value, as well as with results from previous searches
Een studie van Higgs boson productie in associatie met top quarks door middel van Machine Learning algoritmes bij CMS /
Master of Science in de fysica en de sterrenkund
Joint cosmological and gravitational-wave population inference using dark sirens and galaxy catalogues
International audienceIn the absence of numerous gravitational-wave detections with confirmed electromagnetic counterparts, the "dark siren" method has emerged as a leading technique of gravitational-wave cosmology. The method allows redshift information of such events to be inferred statistically from a catalogue of potential host galaxies. Due to selection effects, dark siren analyses necessarily depend on the mass distribution of compact objects and the evolution of their merger rate with redshift. Informative priors on these quantities will impact the inferred posterior constraints on the Hubble constant (). It is thus crucial to vary these unknown distributions during an inference. This was not possible in earlier analyses due to the high computational cost, restricting them to either excluding galaxy catalogue information, or fixing the gravitational-wave population mass distribution and risking introducing bias to the measurement. This paper introduces a significantly enhanced version of the Python package GWCOSMO, which allows joint estimation of cosmological and compact binary population parameters. This thereby ensures the analysis is now robust to a major source of potential bias. The gravitational-wave events from the Third Gravitational-Wave Transient Catalogue are reanalysed with the GLADE+ galaxy catalogue, and an updated, more reliable measurement of km s Mpc is found (maximum a posteriori probability and 68% highest density interval). This improved method will enable cosmological analyses with future gravitational-wave detections to make full use of the information available (both from galaxy catalogues and the compact binary population itself), leading to promising new independent bounds on the Hubble constant
Joint cosmological and gravitational-wave population inference using dark sirens and galaxy catalogues
International audienceIn the absence of numerous gravitational-wave detections with confirmed electromagnetic counterparts, the "dark siren" method has emerged as a leading technique of gravitational-wave cosmology. The method allows redshift information of such events to be inferred statistically from a catalogue of potential host galaxies. Due to selection effects, dark siren analyses necessarily depend on the mass distribution of compact objects and the evolution of their merger rate with redshift. Informative priors on these quantities will impact the inferred posterior constraints on the Hubble constant (). It is thus crucial to vary these unknown distributions during an inference. This was not possible in earlier analyses due to the high computational cost, restricting them to either excluding galaxy catalogue information, or fixing the gravitational-wave population mass distribution and risking introducing bias to the measurement. This paper introduces a significantly enhanced version of the Python package GWCOSMO, which allows joint estimation of cosmological and compact binary population parameters. This thereby ensures the analysis is now robust to a major source of potential bias. The gravitational-wave events from the Third Gravitational-Wave Transient Catalogue are reanalysed with the GLADE+ galaxy catalogue, and an updated, more reliable measurement of km s Mpc is found (maximum a posteriori probability and 68% highest density interval). This improved method will enable cosmological analyses with future gravitational-wave detections to make full use of the information available (both from galaxy catalogues and the compact binary population itself), leading to promising new independent bounds on the Hubble constant
Joint cosmological and gravitational-wave population inference using dark sirens and galaxy catalogues
International audienceIn the absence of numerous gravitational-wave detections with confirmed electromagnetic counterparts, the "dark siren" method has emerged as a leading technique of gravitational-wave cosmology. The method allows redshift information of such events to be inferred statistically from a catalogue of potential host galaxies. Due to selection effects, dark siren analyses necessarily depend on the mass distribution of compact objects and the evolution of their merger rate with redshift. Informative priors on these quantities will impact the inferred posterior constraints on the Hubble constant (). It is thus crucial to vary these unknown distributions during an inference. This was not possible in earlier analyses due to the high computational cost, restricting them to either excluding galaxy catalogue information, or fixing the gravitational-wave population mass distribution and risking introducing bias to the measurement. This paper introduces a significantly enhanced version of the Python package GWCOSMO, which allows joint estimation of cosmological and compact binary population parameters. This thereby ensures the analysis is now robust to a major source of potential bias. The gravitational-wave events from the Third Gravitational-Wave Transient Catalogue are reanalysed with the GLADE+ galaxy catalogue, and an updated, more reliable measurement of km s Mpc is found (maximum a posteriori probability and 68% highest density interval). This improved method will enable cosmological analyses with future gravitational-wave detections to make full use of the information available (both from galaxy catalogues and the compact binary population itself), leading to promising new independent bounds on the Hubble constant
Joint cosmological and gravitational-wave population inference using dark sirens and galaxy catalogues
International audienceIn the absence of numerous gravitational-wave detections with confirmed electromagnetic counterparts, the "dark siren" method has emerged as a leading technique of gravitational-wave cosmology. The method allows redshift information of such events to be inferred statistically from a catalogue of potential host galaxies. Due to selection effects, dark siren analyses necessarily depend on the mass distribution of compact objects and the evolution of their merger rate with redshift. Informative priors on these quantities will impact the inferred posterior constraints on the Hubble constant (). It is thus crucial to vary these unknown distributions during an inference. This was not possible in earlier analyses due to the high computational cost, restricting them to either excluding galaxy catalogue information, or fixing the gravitational-wave population mass distribution and risking introducing bias to the measurement. This paper introduces a significantly enhanced version of the Python package GWCOSMO, which allows joint estimation of cosmological and compact binary population parameters. This thereby ensures the analysis is now robust to a major source of potential bias. The gravitational-wave events from the Third Gravitational-Wave Transient Catalogue are reanalysed with the GLADE+ galaxy catalogue, and an updated, more reliable measurement of km s Mpc is found (maximum a posteriori probability and 68% highest density interval). This improved method will enable cosmological analyses with future gravitational-wave detections to make full use of the information available (both from galaxy catalogues and the compact binary population itself), leading to promising new independent bounds on the Hubble constant
The Hitchhiker's guide to the galaxy catalog approach for gravitational wave cosmology
We outline the ``dark siren'' galaxy catalog method for cosmological inference using gravitational wave (GW) standard sirens, clarifying some common misconceptions in the implementation of this method. When a confident transient electromagnetic counterpart to a GW event is unavailable, the identification of a unique host galaxy is in general challenging. Instead, as originally proposed by Schutz (1986), one can consult a galaxy catalog and implement a dark siren statistical approach incorporating all potential host galaxies within the localization volume. Trott & Hunterer 2021 recently claimed that this approach results in a biased estimate of the Hubble constant, , when implemented on mock data, even if optimistic assumptions are made. We demonstrate explicitly that, as previously shown by multiple independent groups, the dark siren statistical method leads to an unbiased posterior when the method is applied to the data correctly. We highlight common sources of error possible to make in the generation of mock data and implementation of the statistical framework, including the mismodeling of selection effects and inconsistent implementations of the Bayesian framework, which can lead to a spurious bias
The Hitchhiker's guide to the galaxy catalog approach for gravitational wave cosmology
We outline the ``dark siren'' galaxy catalog method for cosmological inference using gravitational wave (GW) standard sirens, clarifying some common misconceptions in the implementation of this method. When a confident transient electromagnetic counterpart to a GW event is unavailable, the identification of a unique host galaxy is in general challenging. Instead, as originally proposed by Schutz (1986), one can consult a galaxy catalog and implement a dark siren statistical approach incorporating all potential host galaxies within the localization volume. Trott & Hunterer 2021 recently claimed that this approach results in a biased estimate of the Hubble constant, , when implemented on mock data, even if optimistic assumptions are made. We demonstrate explicitly that, as previously shown by multiple independent groups, the dark siren statistical method leads to an unbiased posterior when the method is applied to the data correctly. We highlight common sources of error possible to make in the generation of mock data and implementation of the statistical framework, including the mismodeling of selection effects and inconsistent implementations of the Bayesian framework, which can lead to a spurious bias