Searh results

Copertina volume box-s-2

From Dark Matter to Machine Learning: A collection of EAS 2022 proceedings from the S3 and S11 symposia

Volume 94, n. 3, 2023


S3: The dark matter multi-messenger challenge

S. CebriánDirect Detection of Dark Matter
Raghuveer GaraniStellar probes of dark matter
Sisk-Reynes et al.Current and Future constraints on Very-Light Axion-Like Particles from X-ray observations of cluster-hosted Active Galaxies
Gauri Sharma and Jonathan FreundlichDark Matter Halos of Disk-like Galaxies at z ∼ 1
L. CiottiRotation curves of galaxies in General Relativity
Bílek et al.Imprint of the galactic acceleration scale on globular cluster systems: Galaxies in the Fornax Cluster
Lucas M. ValenzuelaLights in the Dark: Globular clusters as dark matter tracers
Oliver Manzanilla Carretero, Adriana Bariego-Quintana, and Felipe J. Llanes-EstradaDark Matter Cigars
Marcel S. PawlowskiWhat new observations tell us about Planes of Satellite Galaxies
Lucas C. KimmigAnd Yet There is Mass: How Projection Effects Can Solve the Apparent Lack of Mass in Substructures of Simulated Galaxy Clusters
G. Granata et al.Investigating the discrepancy in sub-halo compactness between observed and simulated galaxy clusters with improved strong lensing modelling
M. Meneghetti et al.Too many galaxy-galaxy strong lenses observed in galaxy clusters

S11: Machine Learning, a giant leap towards space discovery in the era of peta and exabyte scale surveys

Yun Cheng et al.CNN Lesson Learned from Two Largest Galaxy Morphological Classification Catalogues
Domínguez Sánchez et al.Revisiting the SFR-Mass relation at z = 0 with detailed deep learning based morphologies
Tohill et al.Exploring the Morphologies of High Redshift Galaxies with Machine Learning
Buitrago et al.Machine Learning disclosing the edges of galaxies
Pearson et al.Pitfalls of AI classification of rare objects Galaxy Mergers
A. Lavrukhina and K. MalanchevPerformant feature extraction for photometric time series
Sheng et al.Stochastic Recurrent Neural Networks for Modelling Astronomical Time Series: Advantages and Limitations
Nemani et al.Reconstructing blended galaxies with Machine Learning
Diego-Palazuelos et al.Machine learning approach to the detection of point sources in maps of the CMB temperature anisotropies
C. HenekaLearning the Radio 21cm Signal – From Dawn till Dusk, from Tomography to Sources
Yun Cheng et al.Harvesting the Lyman alpha forest with convolutional neural networks
Dubois et al.Clustering of galaxy spectra: an unsupervised approach with Fisher-EM
Kyritsis et al.A versatile classification tool for galactic activity using optical and infrared colors
Awad et al.Swarm Intelligence-based Extraction and Manifold Crawling along the Large Scale Structure