KAGRA Data Analysis Subsystem Activities in Feb. – Aug. 2013
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1 重力波実験 データ解析 伊藤洋介東京大学ビッグバン宇宙国際研究センター ポスト ニュートン運動方程式 LIGO 連続重力波データ解析 KAGRA データ解析チーム ( 連続波 ) 柏 2013 年 12 月 25 日 -27 日 1
2 注意 : 特定の団体 (KAGRA, LIGO,VIRGO) を代表して話すのではありません 2
3 Part 0: 重力波の存在 3
4 重力波は存在する! Hulse-Taylor 連星パルサーが間接的に重力波の存在の証拠を与えている ( 軌道半径の減少が 一般相対論の予言と 0.2% の精度で一致している ) Binary Pulsar Gravitational wave Nobelprize.org The Nobel Prize in Physics 1993 C. M. Will Liv. Rev. Rel (2006)
5 Gravitational Wave sources for KAGRA/LIGO/VIRGO SNe, GRBs in local universe. Nearby pulsars in Milkyway NS/NS binaries coalescence within 200 Mpc. Steller mass BH/BH within z~ 0.1. Stochastic background Probably not primordial one. Images are taken from NASA and hubblesite.
6 Part1: 地上重力波検出器 ( 直接見たい ) 6
7 世界の km- クラス地上重力波検出器 LIGO Hanford 4 km, desert Taken and modified from Prof. C. M. Will s slide. LIGO India?? LIGO Livingston 4 km, forest Virgo Cascina 3 km KAGRA Kamioka, 3 km, cryogenic, underground
8 地上重力波検出器の感度 レーザー干渉計 長さの変化を測る Joshua Smith GWPAW2013 8
9 地上検出器と期待される波源 とても小さい Sathyaprakash & Schutz Liv. Rev. Rel. (2009) 9
10 実際やってる (iligo). 観測開始から 4 年かかっている
11 前史 1990: LIGO approval 1993: VIRGO approval 1994: LHO construction started June: LLO construction started May: TAMA operation started 2000: LIGO Detector installation completed Oct. : 1 st operation, commissioning started Aug. : 1 st Science run (S1) 2006 June : Design Sensitivity (S5) 6 obs runs of iligo and 4 obs runs of VIRGO till (Cf. CLIO) 2010 June KAGRA (LCGT) approval. Ref: Detector Description and Performance for the First Coincidence Observations between LIGO and GEO The LIGO Scientific Collaboration(2004) 2013/6/29 11
12 Cost LIGO is the largest single enterprise undertaken by NSF, with capital investments of nearly $300 million and operating costs of more than $30 million/year. (NSF Fact sheet Feb ) 78 Observational and LSC instrument papers (+ papers under review now) from S1 (2002) (first paper appears at 2004) to 2013, excluding conference proceedings. LVC : 400 (S1) (2013) authors Advanced LIGO : 197 million dollar が の運転資金 NSF より認められている ( 要求よりも 20 million dollar 低い ) 2010 年度最先端研究基盤事業として KAGRA 建設の予算 98 億円が認められる ( その後概算要求を含め総額 156 億円が措置 ) Advanced VIRGO approved end 2009 (~ 2 years after aligo) with budget ~ 23 Meuro (investiments).
13 Part2: 今後 10 年 13
14 Timelines Y. Saito s 2015 ~1month obs. FY 2017bKAGRA start 4 イベント検出後 C. Messenger s 14
15 GWPAW 2013 ( 先週 ) の Lisa Barsotti のスライド 15
16 GWPAW 2013 ( 先週 ) の Benoit Mours スライド 16
17 KAGRA 2013 年 12 月 5 日 :Y-arm トンネル掘削終了! ( 年春 +: 地上建屋建設完了 トンネル掘削完了 ikagra データ転送系導入 (2013 年が最先端 トンネル掘削費最終年度 ) 17
18 aligo/avirgo の期待感度曲線 Arxiv:
19 LV 検出可能性 Arxiv: e-8 ~ 1e-5 /Mpc^3/yr, 80 % duty cycle として計算 Cf: Initial LIGO: 平均 ~ 15 Mpc (up to the VIRGO cluster), Rate: ~1/50 years を期待していた 19
20 方向決定精度 (90 % CL) Arxiv: Mpc ただし 最初の 1~2 年は LIGO2 台のみなので 方向決定精度は数百平方度程度 さらに 4 台無いと方向を 1 つに絞れない KAGRA/LIGO-India の重要性 20
21 21
22 22
23 Part3: 検出方法 23
24 マッチドフィルター 信号対雑音比を最大化するという意味で最適な線形フィルター ノイズ分布がガウシアンのときには 最尤推定法による検出法と一致するという意味で 最適な方法の 1 つ
25 マッチドフィルターを使えないとき 計算資源が足りないため使えない場合 : 未知の高速自転コンパクト星の探索など Incoherent 探索をおこなう 波形予測が難しいとき 超新星爆発 GRB など 現象論的波形モデルを使う Excess power などを使う 多くの検出器との同時検出を狙う νγ 望遠鏡との同時検出を狙う 数値計算の人にがんばってもらう 25
26 Part3: 今までの結果と課題 26
27 連続重力波 27
28 連続波 ( 既知の単独パルサーからの重力波 ) Arxiv:
29 連続波 ( 既知の単独パルサーからの重力波 ) Crab Vela Arxiv:
30 連続波 ( 既知の単独パルサーからの重力波 ) Crab Vela パルサー外殻の物性による Arxiv:
31 2013/7/1 31
32 ではどうする? 1. LMXBなどの連星は大振幅の重力波を放射する可能性がある (Bildsten 1998 scenario) ATNF の1890 個のパルサーのうち 140 個は連星系にある 2. パルサーの半径や距離の不定性は無視できない 3. 電磁波で見えない近傍パルサー 高速自転コンパクト星 Blind Search 4. ハイブリッド星 強磁場星 クォーク星など 32
33 既知の降着中性子星からの重力波探索 : best case scenario Single template search 2 years integration quadrupole mode long-term average flux Perfect balance Open: frequency not known for sure. No limitation on computing power khz QPOs are marginally detectable. Watts et al. (2008) 33
34 既知の降着中性子星からの重力波探索 : 現実的シナリオ Watt et al. (2008) Multi templates search: look-elsewhere effect and computational limitation are taken into account. 2 years integration quadrupole mode long-term average flux Perfect balance Open: frequency not known for sure. 50 times faster computers for AdLIGO, 100 times faster for ET. SCO-X1 is marginally detectable. 34
35 既知の降着中性子星からの重力波探索 : テンプレート数 Detectable if long-term average flux is larger than 1e-8. 1e15 templates data can be analyzed by LIGO today. Watt and Krishnan (2009) 35
36 SCO-X1 khz QPO source: Distance known by parallax: kpc Proper motion detected. No pulsations found (= no spin frequency measurement). No spin down measurement. Orbital motion moderately well determined. 36
37 Can we infer spin frequency from khz QPO? Watts et al. (2008) 37
38 降着中性子星 GW まとめ khz QPOs would be marginally detectable by KLV if we have 50 x (current LSC computing power). Sco-X1 is most promising. Obstacles against possible detection are: Computing power Poor knowledge on the pulsar properties, especially spin frequency (and binary motion information). Need to find a relationship between khz QPO freq. and spin freq. Need to have more precise and accurate measurements of pulsar and binary properties. 38
39 連続波 ( 未発見の単独高速自転コンパクト星からの重力波 ) Application of a Hough search for continuous gravitational waves on data from the 5th LIGO science run 2013arXiv T Einstein@Home all-sky search for periodic gravitational waves in LIGO S5 data 2013PhRvD..87d2001A パルサーの空間存在密度から考えると 40pc ぐらいのところにビームがこちらに向いていないパルサーが存在していても良い (ATNF catalogue で 300pc 以内に存在するパルサーは 10 個程度 ) 別の言い方で Blandford-Cutler argument によると 最大で 4x1e-24 程度の重力波振幅を期待できる これは Blind search で検出できる Knispel & Allen (2008) も参照 39
40 連続波 ( 未発見の単独高速自転コンパクト星からの重力波 ) Incoherent search (Hough search) arxiv なんですが 40
41 Comp. Cost & Amplitude(KAGRA) 10T Sn detector noise powerspectral density. hth: threshold GW amplitude for detection. 10G 1-year integration, 1-year analy All-Sky, up to 1kHz, 10-15% FA
42 計算コスト (KAGRA)
43 # over 500 TFLOPS # アレシボ電波 /Fermi LAT データ解析にも利用 電波 γ 線パルサーを発見した Science 329 pp (2010), ApJL 779 L11 (2013) など 43
44 Compact Binary Coalescence S6/VSR2,3 search 44
45 Multi-messenger Astronomy BNS, NS/BH, SNe, GRB では νγ 対応天体が期待される 特に CBC, Burst (SNe, GRB) で研究 / 協力が進んでいる Low-latency 探索が重要 なるべく短い時間 (1 分以内程度 ) に GW νγ 望遠鏡で警報をやりとりする LIGO-VIRGO は GW 検出からのアラート発行システムの運用実績を持っている Arxiv:
46 Low latency search 1 分程度を目標にしている Multi-messenger Astronomy のために νγ 天文学とイベントアラートのやりとりをおこなう FAR を下げること 方向決定精度の向上 計算速度が課題 もちろん Middle latency search, off-line search もおこなう Middle latency search (1 day): Detchar チームへの feedback. 計算資源の必要な探索 Off-line search (1 week 1month): 計算資源の必要な探索 精度の高いパラメータ探索 GR のテストなど 様々な物理 46
47 Multi-messenger Astronomy Arxiv:
48 CBC S6/VSR2 the big dog Arxiv:
49 L. Cadonati s GWPAW
50 EM triger search Coincidence analysis against 154 GRBs reported by GCN, SWIFT, Fermi, MAXI, IPN, SuperAGILE, INTEGRAL. 50
51 Part4:KAGRA のデータ解析 51
52 活動資金
53 Data Management and Data Analysis 文科省新学術科研費 重力波天体 (FY) KAKENHI, Grant-in-Aid for Scientific Research on Innovative Areas, Titie: "New development in astrophysics through multi-messenger observation of gravitational wave sources or GW Astronomy in short. Period: (FY) PI: Takashi Nakamura (Kyoto U) There are five subgroups: A01: X/gamma-ray (PI: N.Kawai, Tokyo Tech.) A02: Optical/Infrared (PI: M. Yoshida, Hiroshima) A03: Neutrino (PI: M. Vagins, ICRR) A04: Data analysis (PI: N.Kanda) A05: Theory (PI: T. Tanaka, YITP) 53
54 データ解析 プラットフォーム
55 Data Management Amount of Data TiB = 2 40 bytes = 1,099,511,627,776 bytes TB = bytes = 1,000,000,000,000 bytes duty: The fraction of the observation period in which we have to transfer data at the specified transfer rate. 100% = need to transfer data continuously during observation. From Kamioka to Kashiwa, we plan to use a facility that can transfer data at 40 MB/s. 55
56 Data Management Computing platform at ICRR ICRR s computer system will be replaced in this December. The system will be used for offline GW searches. New system will be available from January ~3000 cores A single core performance > 32 SPECintbase2006 ~4PiB Note : these resources are shared by ICRR all groups. KAGRA is not the only user of this system. NB: SPECint:
57 Data Analysis KAGRA data analysis schedule pipeline development Adv. pipeline pipeline test End to end test obs pipeline test End to end test obs. ikagra bkagra ikagra target Operation of the whole analysis pipeline which includes analysis of data and production of the scientific results. Discovery of a local fortuitous GW event. bkagra target Detection of GW signals Joint data analysis with LV GW astronomy 57
58 Data Analysis Status of the relation to the LSC and VIRGO N. Kanda and H. Tagoshi are assigned to liaison persons between LSC/Virgo and KAGRA. Since October 2013, they are participating the meeting of the Data Analysis Council of LSC/Virgo. (Every Friday at 24 or 25 p.m. (in the Japanese Standard Time)) This will be an important first step toward the collaboration on the data analysis with LSC and Virgo. N. Kanda and H. Tagoshi are also visiting Milwaukee for the meeting of the LSC data analysis software working group during this week to obtain various information. 58
59 解析チーム
60 Data Analysis Data Analysis Subsystem (DAS) Chief: 田越 Sub-chiefs: 伊藤, 高橋 Core members: 神田, 大原, 端山 Korean subgroup Leader: Hyung Won Lee Osaka Univ : H. Tagoshi, K.Ueno, T.Narikawa Osaka City Univ : N.Kanda, K.Hayama, T.Yokozawa, H.Yuzurihara, T.Yamamoto, K.Tanaka, Mitsuhiro Asano, Masato Toritani Univ Tokyo : Y.Itoh, J. Yokoyama Nagaoka Tech : H.Takahashi, Niigaka Univ : K.Oohara, Y.Hiranuma, M. Kaneyama, T. Wakamatsu Toyama Univ : S. Hirobayashi Inje Univ. : Hyung Won Lee Jeongcho Kim Seoul Nat. U.: Chunglee Kim 合計 22 名 ( 大学院生含む ) NB: 新学術 A04 公募研究で 辰巳さん (NAOJ) 廣林さん ( 富山大 ) 横山さん ( 東大 ) とも連携 インドグループとも 2 国間事業などを通して密接に連携 60
61 Data Analysis Data Analysis Subsystem (DAS) Chief: 田越 Sub-chiefs: 伊藤, 高橋 Core members: 神田, 大原, 端山 Korean subgroup Leader: Hyung Won Lee Osaka Univ : H. Tagoshi, K.Ueno, T.Narikawa Osaka City Univ : N.Kanda, K.Hayama, T.Yokozawa, H.Yuzurihara, T.Yamamoto, K.Tanaka, Mitsuhiro Asano, Masato Toritani Univ Tokyo : Y.Itoh, J. Yokoyama Nagaoka Tech : H.Takahashi, Niigaka Univ : K.Oohara, Y.Hiranuma, M. Kaneyama, T. Wakamatsu Toyama Univ : S. Hirobayashi Inje Univ. : Hyung Won Lee Jeongcho Kim Seoul Nat. U.: Chunglee Kim コアメンバー NB: インドグループとも 2 国間事業などを通して密接に連携 61
62 Data Analysis Data Analysis Subsystem (DAS) 新学術予算による新メンバー 横澤 ( 阪市大 ): 元 SK メンバーで 現在 SKE の立ち上げ主要メンバー A03 ニュートリノ EGADS 班との連携でニュートリノ 重力波同時観測を目指す 上野 ( 阪大 ): 元 SK メンバーで 現在 low latency 探索を田越らとおこなう SVD を駆使して 必要計算資源を 2 桁落とした 成川 ( 阪大 ): 重力波で重力理論の検証をおこなうべく A05 理論班とともに研究中 62
63 戦力比 K:V:L = 1:5:25 KAGRA Tagoshi, Kanda, Oohara Itoh, Hayama, Takahashi Narikawa, Yokozawa, Ueno,. LSC
64 Data Analysis Data Analysis School Sponser: RESCEU U. of Tokyo, MEXT Grant-in-Aid Shin-Gakujyutsu 1st KAGRA data analysis school Sept. 3-5, 2012 at RESCEU, U. of Tokyo Number of participants: about 70 Basics of matched filtering (Tagoshi, Takahashi) Overview (Kanda), Statistics (Itoh) Management: KAGRA DAS Supported by KAGRA 3rd KAGRA data analysis school Sep , 2013 at RESCEU, U. of Tokyo Number of participants:about 73 Continuous wave search (Itoh) Pulsar timing (van Haasteren, JPL), Stellar Oscillation (Kojima) 2nd KAGRA data analysis school Feb , 2013 at NAOJ, Mitaka, Tokyo Number of participants: about 60 Gravitational wave burst search (Hayama) Spectral analysis (Mio), Interferometer (Aso), SN (Kotake), Beam pattern function (Kanda) Special thanks to Nakamura (NAOJ) 64
65 データ解析チームへの参加を 歓迎します!!!! 65
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