TY - JOUR
T1 - The AIverse project
T2 - Simulating, analyzing, and describing galaxies and star clusters with artificial intelligence
AU - Bekki, K.
AU - Diaz, J.
AU - Stanley, N.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - We present our new AIverse project in which several algorithm of artificial intelligence (AI) are used to simulate, analyze, and describe the physical properties of galaxies and star clusters. The three main purposes of the project are to (i) classify the formationand evolution processes of galaxies and star clusters, (ii) perform computer simulations in an automatic way, and (iii) convert the animation produced by the simulation into sentences using AI. Here we focus exclusively on the first component of the project as follows. We use convolutional neural networks (CNNs) to classify the formation and evolution processes of galaxies based on the two-dimensional (2D) images of galactic properties such as mass densities. This new classification method is two-stage as follows. First a large number of the synthesized 2D images of galactic properties from computer simulations are used to train a CNN for the classification. Once the CNN comes to have a very high accuracy, the CNN is then used to classify the real observational data. We discuss the effectiveness of the new classification method using the results of computer simulations on one of key formation processes of galaxies. We also discuss the number of images (Ni) required to generate from computer simulations by investigating the models with different Ni and other parameters. We briefly outline the other two components of the project and discuss their purposes.
AB - We present our new AIverse project in which several algorithm of artificial intelligence (AI) are used to simulate, analyze, and describe the physical properties of galaxies and star clusters. The three main purposes of the project are to (i) classify the formationand evolution processes of galaxies and star clusters, (ii) perform computer simulations in an automatic way, and (iii) convert the animation produced by the simulation into sentences using AI. Here we focus exclusively on the first component of the project as follows. We use convolutional neural networks (CNNs) to classify the formation and evolution processes of galaxies based on the two-dimensional (2D) images of galactic properties such as mass densities. This new classification method is two-stage as follows. First a large number of the synthesized 2D images of galactic properties from computer simulations are used to train a CNN for the classification. Once the CNN comes to have a very high accuracy, the CNN is then used to classify the real observational data. We discuss the effectiveness of the new classification method using the results of computer simulations on one of key formation processes of galaxies. We also discuss the number of images (Ni) required to generate from computer simulations by investigating the models with different Ni and other parameters. We briefly outline the other two components of the project and discuss their purposes.
KW - Artificial intelligence
KW - Galaxy classification systems
KW - Galaxy evolution
UR - http://www.scopus.com/inward/record.url?scp=85070080879&partnerID=8YFLogxK
U2 - 10.1016/j.ascom.2019.05.004
DO - 10.1016/j.ascom.2019.05.004
M3 - Article
AN - SCOPUS:85070080879
SN - 2213-1337
VL - 28
JO - Astronomy and Computing
JF - Astronomy and Computing
M1 - 100286
ER -