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Deployment, operation and maintenance of large IT systems becomes increasingly complex and puts human experts under extreme stress when problems occur. Therefore, utilization of machine learning (ML) and artificial intelligence (AI) is…

Machine Learning · Computer Science 2021-07-30 Dominik Scheinert , Alexander Acker

We present the new ARTEMIS Emulator suite of high resolution (baryon mass of $2.23 \times 10^{4}$ $h^{-1}$M$_{\odot}$) zoom-in simulations of Milky Way mass systems. Here, three haloes from the original ARTEMIS sample have been rerun…

Astrophysics of Galaxies · Physics 2024-08-23 Shaun T. Brown , Azadeh Fattahi , Ian G. McCarthy , Andreea S. Font , Kyle A. Oman , Alexander H. Riley

Accurately determining the properties of stars is of prime importance for characterizing stellar populations in our Galaxy. The field of asteroseismology has been thought to be particularly successful in such an endeavor for stars in…

We present the Bayesian Asteroseismology data Modeling (BAM) pipeline, an automated asteroseismology pipeline that returns global oscillation parameters and granulation parameters from the analysis of photometric time-series. BAM also…

Solar and Stellar Astrophysics · Physics 2019-11-21 Joel C. Zinn , Dennis Stello , Daniel Huber , Sanjib Sharma

Approximate Graph Pattern Mining (AGPM) is essential for analyzing large-scale graphs where exact counting is computationally prohibitive. While there exist numerous sampling-based AGPM systems, they all rely on uniform sampling and…

Data Structures and Algorithms · Computer Science 2026-01-06 Seoyong Lee , Jinho Lee

Star formation is a multi-scale problem, and only global simulations that account for the connection from the molecular cloud scale gas flow to the accreting protostar can reflect the observed complexity of protostellar systems.…

Astrophysics of Galaxies · Physics 2023-07-28 Rami Al-Belmpeisi , Vito Tuhtan , Mikkel Bregning Christensen , Rajika L Kuruwita , Troels Haugbølle

Constraining parameters such as the initial mass function high-mass slope and the frequency of type Ia supernovae is of critical importance in the ongoing quest to understand galactic physics and create realistic hydrodynamical simulations.…

Astrophysics of Galaxies · Physics 2020-01-08 Oliver Henry Edward Philcox , Jan Rybizki

The technique of intensity mapping (IM) has emerged as a powerful tool to explore the universe at $z < 6$. IM measures the integrated emission from sources over a broad range of frequencies, unlocking significantly more information than…

Cosmology and Nongalactic Astrophysics · Physics 2019-11-01 Hamsa Padmanabhan

Accurate specification of a likelihood function is becoming increasingly difficult in many inference problems in astronomy. As sample sizes resulting from astronomical surveys continue to grow, deficiencies in the likelihood function lead…

Instrumentation and Methods for Astrophysics · Physics 2019-04-26 Jessi Cisewski-Kehe , Grant Weller , Chad Schafer

In applications of Gaussian processes where quantification of uncertainty is a strict requirement, it is necessary to accurately characterize the posterior distribution over Gaussian process covariance parameters. Normally, this is done by…

Computation · Statistics 2016-04-01 Xiaoyu Xiong , Václav Šmídl , Maurizio Filippone

Asteroseismic measurements of the internal rotation rate in evolved stars pointed out to a lack of angular momentum (AM) transport in stellar evolution models. Several physical processes in addition to hydrodynamical ones were proposed as…

Solar and Stellar Astrophysics · Physics 2023-05-17 F. D. Moyano , P. Eggenberger , B. Mosser , F. Spada

The high redshift 21-cm signal promises to be a crucial probe of the state of the intergalactic medium (IGM). Understanding the connection between the observed 21-cm power spectrum and the physical quantities intricately associated with the…

We propose Adaptive Incremental Mixture Markov chain Monte Carlo (AIMM), a novel approach to sample from challenging probability distributions defined on a general state-space. While adaptive MCMC methods usually update a parametric…

Methodology · Statistics 2018-06-01 Florian Maire , Nial Friel , Antonietta Mira , Adrian Raftery

I outline a method for estimating astrophysical parameters (APs) from multidimensional data. It is a supervised method based on matching observed data (e.g. a spectrum) to a grid of pre-labelled templates. However, unlike standard machine…

Astrophysics · Physics 2007-11-29 C. A. L. Bailer-Jones

Current stellar model predictions of adiabatic oscillation frequencies differ significantly from the corresponding observed frequencies due to the non-adiabatic and poorly understood near-surface layers of stars. However, certain…

Solar and Stellar Astrophysics · Physics 2022-07-20 Kuldeep Verma , Jakob L. Rørsted , Aldo M. Serenelli , Víctor Aguirre Børsen-Koch , Mark L. Winther , Amalie Stokholm

Pre-main sequence (PMS) models provide invaluable tools for the study of star forming regions as they allow to assign masses and ages to young stars. Thus it is of primary importance to test the models against observations of PMS stars with…

Solar and Stellar Astrophysics · Physics 2015-05-30 Mario Gennaro , Pier Giorgio Prada Moroni , Emanuele Tognelli

Massive stars condition the evolution of the interstellar medium by the amount of energy released during their lives and especially by their deaths as supernova explosions. The vast amounts of spectroscopic data for massive stars provided…

Solar and Stellar Astrophysics · Physics 2024-01-11 Klaus Rubke , Amparo Marco , Ignacio Negueruela , Artemio Herrero , Sergio Simon-Diaz , Hugo Tabernero , Lee Patrick

Recent work has pointed out the potential existence of a tight relation between the cosmological parameter $\Omega_{\rm m}$, at fixed $\Omega_{\rm b}$, and the properties of individual galaxies in state-of-the-art cosmological hydrodynamic…

This paper introduces Adaptive Mixture Importance Sampling (AMIS) as a novel approach for optimizing key performance indicators (KPIs) in large-scale recommender systems, such as online ad auctions. Traditional importance sampling (IS)…

Machine Learning · Computer Science 2024-09-23 Yimeng Jia , Kaushal Paneri , Rong Huang , Kailash Singh Maurya , Pavan Mallapragada , Yifan Shi