Guo Chin Liu on Behave of TGWG Group Members

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Data Management and data analysis in Taiwan Guo Chin Liu on behave of TGWG Group Members http://taipeigravitationalwavegroup.weebly.com/members.html ‧ Faculty: C. Chen(TKU), T. Chiu(NTU, NTNU), S. Haino (AS), C. Lin (NCHC), F. Lin (NTNU), G. Liu(TKU) ‧ Post Doc.: D. Chiou, Y. Inoue, S. Ko ‧ Student: B. Chen, Y. Chu, W. Hsu, M. Lin, Y. Pu, J. Peng, C. Yang, U. Zaman, Y. Zheng Supported by NCTS 2-year seed group grant Plans for the Group ‧ Short term: Data analysis −21 10 - C. Lin(NCHC), G. Liu(TKU), students(NTNU) −22 10 - focus on CBC Hz] √ −23 ‧ Long term: physics with gravitational wave 10 Strain [1/ −24 initial Virgo - BBH of Brans-Dicke model (F. Lin, D. 10 initial LIGO Adv LIGO KAGRA (VRSE) Chiou) Adv Virgo LIGO III −25 Einstein Telescope (ET−D) 10 0 1 2 3 10 10 10 10 - Dark stars(C. Chen) Frequency [Hz] Adhikari et al. 2014 - Numerical relativity or PN to generate Waveform - physics in KAGRA’s sensitive window Mini Summer School http://taipeigravitationalwavegroup.weebly.com/mini-school.html ‧ Date: July 13-15 ‧ Invited speakers: H. Tagoshi, L. Baiotti, S. Kuroyanagi, T. Li, Y. Itoh Data Management ‧ Mirror data storage in ASGC ‧ possibility to mirror (Proc.) data from AS to NCHC? Computing Power ‧ NCHC(National Center for High-performance Computing) - 25 K cores (shared) - 100kNTD/year for 100 cores ‧ Prototype: two servers (12 cores with 400GB MEM; 4cores with 64GB MEM and two GPUs), one workstation (6 cores, 64GB MEM and K80 GPU) ‧ Production: server with 400 cores and 200 GPUs Pipeline Construction based on matched filtering, with tools provided by Kagali or LALsuite ‧ MCMC: C. Lin ‧ Construct waveform catalogs: G. Liu + NTNU - GPU, model reduction technique GPU(graphics processing unit ) ‧ FFTW, LAPACK included in CUDA ‧ experience: gomoku game (Hance and Guozhang) ‧ set up a training schedule in near future Model Reduction Techniques Singular Value Decomposition/ Principal Component Analysis ‧ decompose the waveform into a set of orthogonal basis vectors. ‧ reduce the computation costs ‧ applied on - stellar core-collapse wave form(PCA: Heng. 2009) - CBC templates (SVD: Cannon et al 2010) Model Reduction Techniques Reduced basis: ‧ construction of a reduced basis catalog(Field. et al 2011, Caudill et al. 2014 ) ‧ searching the points in parameter space by greedy sweep algorithm ‧ seek an N dimensional linear space to accurately represent the space for considered sources Welcome to Join Us.

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