Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms

Recent work has shown that the end-to-end approach using convolutional neural network (CNN) is effective in various types of machine learning tasks. For audio signals, the approach takes raw waveforms as input using an 1-D convolution layer. In this paper, we improve the 1-D CNN architecture for music auto-tagging by adopting building blocks from state-of-the-art image classification models, ResNets and SENets, and adding multi-level feature aggregation to it. We compare different combinations of the modules in building CNN architectures. The results show that they achieve significant improvements over previous state-of-the-art models on the MagnaTagATune dataset and comparable results on Million Song Dataset. Furthermore, we analyze and visualize our model to show how the 1-D CNN operates.Comment: Accepted for publication at ICASSP 201

The New Horizon Run Cosmological N-Body Simulations

We present two large cosmological N-body simulations, called Horizon Run 2 (HR2) and Horizon Run 3 (HR3), made using 6000^3 = 216 billions and 7210^3 = 374 billion particles, spanning a volume of (7.200 Gpc/h)^3 and (10.815 Gpc/h)^3, respectively. These simulations improve on our previous Horizon Run 1 (HR1) up to a factor of 4.4 in volume, and range from 2600 to over 8800 times the volume of the Millennium Run. In addition, they achieve a considerably finer mass resolution, down to 1.25x10^11 M_sun/h, allowing to resolve galaxy-size halos with mean particle separations of 1.2 Mpc/h and 1.5 Mpc/h, respectively. We have measured the power spectrum, correlation function, mass function and basic halo properties with percent level accuracy, and verified that they correctly reproduce the LCDM theoretical expectations, in excellent agreement with linear perturbation theory. Our unprecedentedly large-volume N-body simulations can be used for a variety of studies in cosmology and astrophysics, ranging from large-scale structure topology, baryon acoustic oscillations, dark energy and the characterization of the expansion history of the Universe, till galaxy formation science - in connection with the new SDSS-III. To this end, we made a total of 35 all-sky mock surveys along the past light cone out to z=0.7 (8 from the HR2 and 27 from the HR3), to simulate the BOSS geometry. The simulations and mock surveys are already publicly available at http://astro.kias.re.kr/Horizon-Run23/.Comment: 18 pages, 10 figures. Added clarification on Fig 6. Published in the Journal of the Korean Astronomical Society (JKAS). The paper with high-resolution figures is available at http://jkas.kas.org/journals/2011v44n6/v44n6.ht

Topology of Luminous Red Galaxies from the Sloan Digital Sky Survey

We present measurements of the genus topology of luminous red galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS) Data Release 7 catalog, with unprecedented statistical significance. To estimate the uncertainties in the measured genus, we construct 81 mock SDSS LRG surveys along the past light cone from the Horizon Run 3, one of the largest N-body simulations to date that evolved 7210^3 particles in a 10815 Mpc/h size box. After carefully modeling and removing all known systematic effects due to finite pixel size, survey boundary, radial and angular selection functions, shot noise and galaxy biasing, we find the observed genus amplitude to reach 272 at 22 Mpc/h smoothing scale with an uncertainty of 4.2%; the estimated error fully incorporates cosmic variance. This is the most accurate constraint of the genus amplitude to date, which significantly improves on our previous results. In particular, the shape of the genus curve agrees very well with the mean topology of the SDSS LRG mock surveys in the LCDM universe. However, comparison with simulations also shows small deviations of the observed genus curve from the theoretical expectation for Gaussian initial conditions. While these discrepancies are mainly driven by known systematic effects such as those of shot noise and redshift-space distortions, they do contain important cosmological information on the physical effects connected with galaxy formation, gravitational evolution and primordial non-Gaussianity. We address here the key role played by systematics on the genus curve, and show how to accurately correct for their effects to recover the topology of the underlying matter. In a forthcoming paper, we provide an interpretation of those deviations in the context of the local model of non-Gaussianity.Comment: 23 pages, 18 figures. APJ Supplement Series 201