ASCL.net

Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Zhang, Hao'

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[ascl:1804.001] ASERA: A Spectrum Eye Recognition Assistant

ASERA, ASpectrum Eye Recognition Assistant, aids in quasar spectral recognition and redshift measurement and can also be used to recognize various types of spectra of stars, galaxies and AGNs (Active Galactic Nucleus). This interactive software allows users to visualize observed spectra, superimpose template spectra from the Sloan Digital Sky Survey (SDSS), and interactively access related spectral line information. ASERA is an efficient and user-friendly semi-automated toolkit for the accurate classification of spectra observed by LAMOST (the Large Sky Area Multi-object Fiber Spectroscopic Telescope) and is available as a standalone Java application and as a Java applet. The software offers several functions, including wavelength and flux scale settings, zoom in and out, redshift estimation, and spectral line identification.

[ascl:1809.007] surfinBH: Surrogate final black hole properties for mergers of binary black holes

surfinBH predicts the final mass, spin and recoil velocity of the remnant of a binary black hole merger. Trained directly against numerical relativity simulations, these models are extremely accurate, reproducing the results of the simulations at the same level of accuracy as the simulations themselves. Fits such as these play a crucial role in waveform modeling and tests of general relativity with gravitational waves, performed by LIGO.

[ascl:2107.028] TRINITY: Dark matter halos, galaxies and supermassive black holes empirical model

TRINITY statistically connects dark matter halos, galaxies and supermassive black holes (SMBHs) from z=0-10. Constrained by multiple galaxy (0 < z < 10) and SMBH datasets (0 < z < 6.5), the empirical model finds the posterior probability distributions of the halo-galaxy-SMBH connection and SMBH properties, all of which are allowed to evolve with redshift. TRINITY can predict many observational data, such as galaxy stellar mass functions and quasar luminosity functions, and underlying galaxy and SMBH properties, including SMBH Eddington average Eddington ratios. These predictions are made by different code files. There are basically two types of prediction codes: the first type generates observable data given input redshift or redshift invertals; the second type generates galaxy or SMBH properties as a function of host halo mass and redshift.