A high-bias, low-variance introduction to machine learning for physicists
Abstract Machine Learning (ML) is one of the most exciting and dynamic areas of modern
research and application. The purpose of this review is to provide an introduction to the core …
research and application. The purpose of this review is to provide an introduction to the core …
Machine learning for observational cosmology
An array of large observational programs using ground-based and space-borne telescopes
is planned in the next decade. The forthcoming wide-field sky surveys are expected to …
is planned in the next decade. The forthcoming wide-field sky surveys are expected to …
CMB-S4 science case, reference design, and project plan
CMB-S4 Science Case, Reference Design, and Project Plan Page 1 CMB-S4 Science Case,
Reference Design, and Project Plan CMB-S4 Collaboration July 9, 2019 arxiv:1907.04473v1 …
Reference Design, and Project Plan CMB-S4 Collaboration July 9, 2019 arxiv:1907.04473v1 …
Learning to predict the cosmological structure formation
Matter evolved under the influence of gravity from minuscule density fluctuations.
Nonperturbative structure formed hierarchically over all scales and developed non …
Nonperturbative structure formed hierarchically over all scales and developed non …
LiteBIRD science goals and forecasts: improving sensitivity to inflationary gravitational waves with multitracer delensing
Measuring the polarization of the cosmic microwave background (CMB) anisotropies will be
at the forefront of observational cosmology in the next decade. In particular, measurements …
at the forefront of observational cosmology in the next decade. In particular, measurements …
The benefits of CMB delensing
SC Hotinli, J Meyers, C Trendafilova… - … of Cosmology and …, 2022 - iopscience.iop.org
The effects of gravitational lensing of the cosmic microwave background (CMB) have been
measured at high significance with existing data and will be measured even more precisely …
measured at high significance with existing data and will be measured even more precisely …
Denoising diffusion delensing: reconstructing the non-Gaussian CMB lensing potential with diffusion models
T Flöss, WR Coulton, AJ Duivenvoorden… - Monthly Notices of …, 2024 - academic.oup.com
Optimal extraction of cosmological information from observations of the cosmic microwave
background (CMB) critically relies on our ability to accurately undo the distortions caused by …
background (CMB) critically relies on our ability to accurately undo the distortions caused by …
What can Machine Learning tell us about the background expansion of the Universe?
R Arjona, S Nesseris - Physical Review D, 2020 - APS
Machine learning (ML) algorithms have revolutionized the way we interpret data in
astronomy, particle physics, biology, and even economics, since they can remove biases …
astronomy, particle physics, biology, and even economics, since they can remove biases …
DeepMerge: Classifying high-redshift merging galaxies with deep neural networks
We investigate and demonstrate the use of convolutional neural networks (CNNs) for the
task of distinguishing between merging and non-merging galaxies in simulated images, and …
task of distinguishing between merging and non-merging galaxies in simulated images, and …
Applications of machine learning to predicting core-collapse supernova explosion outcomes
Most existing criteria derived from progenitor properties of core-collapse supernovae are not
very accurate in predicting explosion outcomes. We present a novel look at identifying the …
very accurate in predicting explosion outcomes. We present a novel look at identifying the …