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Dive into the research topics where Hsi-Yu Schive is active.

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Featured researches published by Hsi-Yu Schive.


Nature Physics | 2014

Cosmic structure as the quantum interference of a coherent dark wave

Hsi-Yu Schive; Tzihong Chiueh; Tom Broadhurst

A cosmological model treating dark matter as a coherent quantum wave agrees well with conventional dark-matter theory on an astronomical scale. But on smaller scales, the quantum nature of wave-like dark matter can explain dark-matter cores that are observed in dwarf galaxies, which standard theory cannot.


Physical Review Letters | 2014

Understanding the Core-Halo Relation of Quantum Wave Dark Matter from 3D Simulations

Hsi-Yu Schive; Ming-Hsuan Liao; Tak-Pong Woo; Shing-Kwong Wong; Tzihong Chiueh; Tom Broadhurst; W-Y. Pauchy Hwang

We examine the nonlinear structure of gravitationally collapsed objects that form in our simulations of wavelike cold dark matter, described by the Schrödinger-Poisson (SP) equation with a particle mass ∼10(-22)  eV. A distinct gravitationally self-bound solitonic core is found at the center of every halo, with a profile quite different from cores modeled in the warm or self-interacting dark matter scenarios. Furthermore, we show that each solitonic core is surrounded by an extended halo composed of large fluctuating dark matter granules which modulate the halo density on a scale comparable to the diameter of the solitonic core. The scaling symmetry of the SP equation and the uncertainty principle tightly relate the core mass to the halo specific energy, which, in the context of cosmological structure formation, leads to a simple scaling between core mass (Mc) and halo mass (Mh), Mc∝a(-1/2)Mh(1/3), where a is the cosmic scale factor. We verify this scaling relation by (i) examining the internal structure of a statistical sample of virialized halos that form in our 3D cosmological simulations and by (ii) merging multiple solitons to create individual virialized objects. Sufficient simulation resolution is achieved by adaptive mesh refinement and graphic processing units acceleration. From this scaling relation, present dwarf satellite galaxies are predicted to have kiloparsec-sized cores and a minimum mass of ∼10(8)M⊙, capable of solving the small-scale controversies in the cold dark matter model. Moreover, galaxies of 2×10(12)M⊙ at z=8 should have massive solitonic cores of ∼2×10(9)M⊙ within ∼60  pc. Such cores can provide a favorable local environment for funneling the gas that leads to the prompt formation of early stellar spheroids and quasars.


Astrophysical Journal Supplement Series | 2010

GAMER: A GRAPHIC PROCESSING UNIT ACCELERATED ADAPTIVE-MESH-REFINEMENT CODE FOR ASTROPHYSICS

Hsi-Yu Schive; Yu-Chih Tsai; Tzihong Chiueh

We present the newly developed code, GPU-accelerated Adaptive-MEsh-Refinement code (GAMER), which adopts a novel approach in improving the performance of adaptive-mesh-refinement (AMR) astrophysical simulations by a large factor with the use of the graphic processing unit (GPU). The AMR implementation is based on a hierarchy of grid patches with an oct-tree data structure. We adopt a three-dimensional relaxing total variation diminishing scheme for the hydrodynamic solver and a multi-level relaxation scheme for the Poisson solver. Both solvers have been implemented in GPU, by which hundreds of patches can be advanced in parallel. The computational overhead associated with the data transfer between the CPU and GPU is carefully reduced by utilizing the capability of asynchronous memory copies in GPU, and the computing time of the ghost-zone values for each patch is diminished by overlapping it with the GPU computations. We demonstrate the accuracy of the code by performing several standard test problems in astrophysics. GAMER is a parallel code that can be run in a multi-GPU cluster system. We measure the performance of the code by performing purely baryonic cosmological simulations in different hardware implementations, in which detailed timing analyses provide comparison between the computations with and without GPU(s) acceleration. Maximum speed-up factors of 12.19 and 10.47 are demonstrated using one GPU with 40963 effective resolution and 16 GPUs with 81923 effective resolution, respectively.


The Astrophysical Journal | 2016

Contrasting Galaxy Formation from Quantum Wave Dark Matter,

Hsi-Yu Schive; Tzihong Chiueh; Tom Broadhurst; Kuan-Wei Huang

The newly established luminosity functions of high-z galaxies at


ieee international conference on high performance computing data and analytics | 2012

\psi

Hsi-Yu Schive; Ui-Han Zhang; Tzihong Chiueh

4 \lesssim z \lesssim 10


Monthly Notices of the Royal Astronomical Society | 2017

DM, with

Britton D. Smith; Greg L. Bryan; Simon C. O. Glover; Nathan J. Goldbaum; Matthew J. Turk; John A. Regan; John H. Wise; Hsi-Yu Schive; Tom Abel; Andrew Emerick; Brian W. O'Shea; Peter Anninos; Cameron B. Hummels; Sadegh Khochfar

can provide a stringent check on dark matter models that aim to explain the core properties of dwarf galaxies. The cores of dwarf spheroidal galaxies are understood to be too large to be accounted for by free streaming of warm dark matter without overly suppressing the formation of such galaxies. Here we demonstrate with cosmological simulations that wave dark matter,


Monthly Notices of the Royal Astronomical Society | 2017

\Lambda

Shu-Rong Chen; Hsi-Yu Schive; Tzihong Chiueh

\psi


Monthly Notices of the Royal Astronomical Society | 2018

CDM, using Planck and Hubble Data

Hsi-Yu Schive; Tzihong Chiueh

DM, appropriate for light bosons such as axions, does not suffer this problem, given a boson mass of


ieee international conference on high performance computing data and analytics | 2011

Directionally unsplit hydrodynamic schemes with hybrid MPI/OpenMP/GPU parallelization in AMR

Hemant Shukla; Hsi-Yu Schive; Tak-Pong Woo; Tzihong Chiueh

m_{\psi} \ge 1.2 \times 10^{-22}{\,\rm eV}


Monthly Notices of the Royal Astronomical Society | 2018

GRACKLE: a chemistry and cooling library for astrophysics

Hsi-Yu Schive; John A. ZuHone; Nathan J. Goldbaum; Matthew J. Turk; Massimo Gaspari; Chin-Yu Cheng

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Tzihong Chiueh

National Taiwan University

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Tak-Pong Woo

National Taiwan University

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Ui-Han Zhang

National Taiwan University

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Shing-Kwong Wong

National Taiwan University

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Yu-Chih Tsai

National Taiwan University

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Hung-Yu Jian

National Taiwan University

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James H. H. Chan

National Taiwan University

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Kuan-Wei Huang

National Taiwan University

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