Tong-Jie Zhang

Four new observational H(z) data from luminous red galaxies in the Sloan Digital Sky Survey data release seven

By adopting the differential age method, we select 17 832 luminous red galaxies from the Sloan Digital Sky Survey Data Release Seven covering redshift 0 < z < 0.4 to measure the Hubble parameter. Using the full spectrum fitt ing package UlySS, these spectra are reduced with single stellar population m odels and optimal age information from our selected sample is derived. With the decreasing age-redshift relation, four new observational H(z) data (OHD) points are obtained, which are H(z) = 69.0±19.6 km s 1 Mpc 1 at z = 0.07, H(z) = 68.6±26.2 km s 1 Mpc 1 at z = 0.12, H(z)=72.9±29.6 km s 1 Mpc 1 at z = 0.2 and H(z)=88.8±36.6 km s 1 Mpc 1 at z = 0.28, respectively. Combined with 21 other available OHD data points, the performance of the constraint on both flat and non -flatCDM models is presented.

Method for Direct Measurement of Cosmic Acceleration by 21-cm Absorption Systems

So far there is only indirect evidence that the Universe is undergoing an accelerated expansion. The evidence for cosmic acceleration is based on the observation of different objects at different distances and requires invoking the Copernican cosmological principle and Einsteins equations of motion. We examine the direct observability using recession velocity drifts (Sandage-Loeb effect) of 21-cm hydrogen absorption systems in upcoming radio surveys. This measures the change in velocity of the same objects separated by a time interval and is a model-independent measure of acceleration. We forecast that for a CHIME-like survey with a decade time span, we can detect the acceleration of a ΛCDM universe with 5σ confidence. This acceleration test requires modest data analysis and storage changes from the normal processing and cannot be recovered retroactively.

Cosmological neutrino simulations at extreme scale

Constraining neutrino mass remains an elusive challenge in modern physics. Precision measurements are expected from several upcoming cosmological probes of large-scale structure. Achieving this goal relies on an equal level of precision from theoretical predictions of neutrino clustering. Numerical simulations of the non-linear evolution of cold dark matter and neutrinos play a pivotal role in this process. We incorporate neutrinos into the cosmological N-body code CUBEP 3 M and discuss the challenges associated with pushing to the extreme scales demanded by the neutrino problem. We highlight code optimizations made to exploit modern high performance computing architectures and present a novel method of data compression that reduces the phase-space particle footprint from 24 bytes in single precision to roughly 9 bytes. We scale the neutrino problem to the Tianhe-2 supercomputer and provide details of our production run, named TianNu, which uses 86% of the machine (13 824 compute nodes). With a total of 2.97 trillion particles, TianNu is currently the world’s largest cosmological N-body simulation and improves upon previous neutrino simulations by two orders of magnitude in scale. We finish with a discussion of the unanticipated computational challenges that were encountered during the TianNu runtime.

Simulating the cold dark matter-neutrino dipole with TianNu

Derek Inman, 2, ∗ Hao-Ran Yu, 3, 4 Hong-Ming Zhu, J.D. Emberson, Ue-Li Pen, 7, 8, 9, † Tong-Jie Zhang, 10, 11, ‡ Shuo Yuan, Xuelei Chen, and Zhi-Zhong Xing 14 Canadian Institute for Theoretical Astrophysics, University of Toronto, M5S 3H8, Ontario, Canada Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada Kavli Institute for Astronomy & Astrophysics, Peking University, Beijing 100871, China Department of Astronomy, Beijing Normal University, Beijing 100875, China Key Laboratory for Computational Astrophysics, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China ALCF Division, Argonne National Laboratory, Lemont, IL 60439, USA Dunlap Institute for Astronomy and Astrophysics, University of Toronto, Toronto, ON M5S 3H4, Canada Canadian Institute for Advanced Research, Program in Cosmology and Gravitation Perimeter Institute for Theoretical Physics, Waterloo, ON, N2L 2Y5, Canada Shandong Provincial Key Laboratory of Biophysics, School of Physics and Electric Information, Dezhou University, Dezhou 253023, China National Supercomputer Center in Guangzhou, Sun Yat-Sen University, Guangzhou, 510275, China Department of Astronomy, Peking University, Beijing 100871, China School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China

Nonparametric reconstruction of dynamical dark energy via observational Hubble parameter data

We study the power of current and future observational Hubble parameter data (OHD) on non-parametric estimations of the dark energy equation of state,

Direct reconstruction of dynamical dark energy from observational Hubble parameter data

w(z)

Differential neutrino condensation onto cosmic structure

. We propose a new method by conjunction of principal component analysis (PCA) and the criterion of goodness of fit (GoF) criterion to reconstruct

Optical observations of the broad-lined type Ic supernova SN 2012ap

w(z)

Blind search for 21-cm absorption systems using a new generation of Chinese radio telescopes

, ensuring the sensitivity and reliability of the extraction of features in the EoS. We also give an new error model to simulate future OHD data, to forecast the power of future OHD on the EoS reconstruction. The result shows that current OHD, despite in less quantity, give not only a similar power of reconstruction of dark energy compared to the result given by type Ia supernovae, but also extend the constraint on

Estimation of transition redshift based on Reinsch splines

w(z)