high level analysis of lat data use level analysis of lat
play

High- -Level Analysis of LAT Data: Use Level Analysis of LAT Data: - PowerPoint PPT Presentation

Dec 07, 2022 •263 likes •474 views

GLAST LAT Project Science Tools Workshop, June 12-14, 2002 High- -Level Analysis of LAT Data: Use Level Analysis of LAT Data: Use High Cases Cases S. W. Digel (SU/HEPL) for the SSC- S. W. Digel (SU/HEPL) for the SSC -LAT Working Group

  1. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 High- -Level Analysis of LAT Data: Use Level Analysis of LAT Data: Use High Cases Cases S. W. Digel (SU/HEPL) for the SSC- S. W. Digel (SU/HEPL) for the SSC -LAT Working Group LAT Working Group SSC-LAT Science Tools Workshop June 12-14, 2002, SLAC 1

  2. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Plan of the talk Plan of the talk Introduce the tools and databases of the standard analysis • environment Show how they fit together into a sensible environment for • high-level analysis Make the case for completeness with Use Cases • 2

  3. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Who put the T in LAT? Who put the T in LAT? The design of the high-level analysis environment that is the • subject of this meeting treats the LAT as an astronomical instrument Implicit in this assumption is that the high-level analysis can • proceed with the instrument response functions – IRFs are defined from beam tests and MC instrument simulations and monitored in flight Also implicit is that background rejection is well in hand (i.e., • meets performance requirements) – Routine scientific analysis will not require modeling the charged particle background or making cuts to select ‘good times’ by geomagnetic quantities 3

  4. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Standard Analysis Environment Standard Analysis Environment Flow is generally left to right, from Level ~1 to Level 2+ • Image/plot display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 4

  5. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Walk through Walk through Event display • – to be inherited from instrument simulation – no path to higher-level analysis – reference by event ID, useful for sanity check Image/plot display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 5

  6. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Walk through (2) Walk through (2) Connection to Level 1 processing • intermediate utilities stand between the Level 1 data and the analysis tools – exposure calculation is separate as well; it doesn’t care about the source of – the pointing/livetime information exposure calculation must match Level 1 extraction parameters – Image/plot U1 can work on previously-extracted gamma rays – display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 6

  7. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Walk through (3) Walk through (3) Known pulsars • – D5 represents timing information (radio) maintained during the mission – after phase assignment, analysis can proceed as usual, or periodicity tests applied Image/plot display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 7

  8. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Walk through (4) Walk through (4) Other databases as input to high-level analysis • – Instrument response functions – PSF, Aeff, Eng. res. (RMF) – Interstellar emission model (tool or database?) is unavoidable Image/plot display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 8

  9. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Walk through (5) Walk through (5) Image/plot display • – Not actually free floating, resource for analysis tools – Interstellar emission model (tool or database?) is unavoidable Image/plot display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 9

  10. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Walk through (6) Walk through (6) Source model definition tool • – specification of models (point sources, extended sources, diffuse) for likelihood analysis and for observation simulation (not shown) – probably should indicate that the source model definitions can be written in files Image/plot – also uses A8 display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 10

  11. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Walk through (7) Walk through (7) Core analysis tools • – likelihood analysis – characterization of point and extended sources – map generation for visualization, export; any binning required for likelihood analysis will be internal to analysis Image/plot display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 11

  12. GLAST LAT Project Science Tools Workshop, June 12-14, 2002 Walk through (8) Walk through (8) Beyond Level 2 • – LAT source catalog is related to likelihood analysis, but not connected by a standard analysis tool – astronomical catalogs may be external resources Image/plot display (U8) Pulsar ephem (D5) Source model def. tool (U7) Level 0.5 Event display Pulsar phase assign (A3) Point source catalog (D3) Likelihood (A1) Data extract Level 1 (D1) 1 (U1) GRB spectral/temporal Catalog Src. ID (A2) analysis (A6) Access (U5) Exposure Pt.ing/livetime Pointing/livetime history (D2) 1 calc. (U3) extractor (U2) GRB physical modeling (A7) Astronomicalcatalogs (incl. D4) IRFs (D6) Map gen (U4) Interstellar emission model (A8) Pulsar Pulsar period search (A5) profiles (A4) 12

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Microarray analysis at a glance from low-level data processing to data analysis Olga

Microarray analysis at a glance from low-level data processing to data analysis Olga

Microarray analysis at a glance from low-level data processing to data analysis Olga Troyanskaya Many of the slides about SMD borrowed/modified from Gavin Sherlock et al. (Stanford) Admin Slides, readings, announcements are at:

847 views • 46 slides
When and how should I combine patient- level data and literature data in a meta- analysis?

When and how should I combine patient- level data and literature data in a meta- analysis?

When and how should I combine patient- level data and literature data in a meta- analysis? Jonathan L French, ScD Patanjali Ravva, MS PAGE 2010, Berlin 10 June 2010 Global Pharmacometrics Meta-analysis is one of the key pillars of

621 views • 34 slides
Mark Ryan del Moral Talabis Secure-DNA High-level overview of the analysis techniques out

Mark Ryan del Moral Talabis Secure-DNA High-level overview of the analysis techniques out

Alternatives in Analysis Mark Ryan del Moral Talabis Secure-DNA High-level overview of the analysis techniques out there To help you get started with YOUR analysis and research by introducing you to existing tools Tip of the

526 views • 38 slides
High Level Data Link Control (HDLC) Analysis 818 West Diamond Avenue - Third Floor, Gaithersburg,

High Level Data Link Control (HDLC) Analysis 818 West Diamond Avenue - Third Floor, Gaithersburg,

High Level Data Link Control (HDLC) Analysis 818 West Diamond Avenue - Third Floor, Gaithersburg, MD 20878 Phone: (301) 670-4784 Fax: (301) 670-9187 Email: info@gl.com Website: http://www.gl.com 1 1 HDLC A Brief Overview HDLC is an

367 views • 23 slides
Big Data Analytics 1. Rapid development: HEP at new level of Big Data Analysis 2. Education:

Big Data Analytics 1. Rapid development: HEP at new level of Big Data Analysis 2. Education:

deep learning in particle & astroparticle physics Big Data Analytics 1. Rapid development: HEP at new level of Big Data Analysis 2. Education: Anchoring machine learning in curriculum 3. Funding: Competence networks of various disciplines

542 views • 24 slides
OCR Geography A-Level 4.0 & 5.0 : Data Presentation and Analysis Essential Notes

OCR Geography A-Level 4.0 & 5.0 : Data Presentation and Analysis Essential Notes

OCR Geography A-Level 4.0 & 5.0 : Data Presentation and Analysis Essential Notes www.pmt.education Introduction In Area 3 of your NEA, your data is collated and presented through a range of presentational techniques

505 views • 22 slides
Shape Co-analysis and constrained clustering Daniel Cohen-Or Tel-Aviv University 1 High-level

Shape Co-analysis and constrained clustering Daniel Cohen-Or Tel-Aviv University 1 High-level

Shape Co-analysis and constrained clustering Daniel Cohen-Or Tel-Aviv University 1 High-level Shape analysis [Mehra et al. 08] [Fu et al. 08] [Kalograkis et al. 10] Shape abstraction Upright orientation Learning segmentation [Kim et al.

1.03k views • 81 slides
Lexical Analysis Aslan Askarov aslan@cs.au.dk acknowledgments: E. Ernst Lexical analysis

Lexical Analysis Aslan Askarov aslan@cs.au.dk acknowledgments: E. Ernst Lexical analysis

Compilation 2016 Lexical Analysis Aslan Askarov aslan@cs.au.dk acknowledgments: E. Ernst Lexical analysis High-level source code Lexing Parsing Elaboration Low-level target code Lexical analysis First phase in the compilation

339 views • 23 slides
Stakeholder Engagement Logical Analysis DBI(O) Vendor High-level Design Selection UKL

Stakeholder Engagement Logical Analysis DBI(O) Vendor High-level Design Selection UKL

OCT JAN JAN JAN NOV DEC FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC FEB MAR 2013 2014 2015 2016 Stakeholder Engagement Logical Analysis DBI(O) Vendor High-level Design

238 views • 4 slides
Introduction to Python Python: very high level language, has high-level data structures built-in

Introduction to Python Python: very high level language, has high-level data structures built-in

Introduction to Python Python: very high level language, has high-level data structures built-in (such as dynamic arrays and dictionaries). easy to use and learn. Can be used for scripting (instead of Perl, awk), or for general programming.

414 views • 14 slides
Data Analysis at CMS Level-1 Trigger Zhenbin Wu (University of

Data Analysis at CMS Level-1 Trigger Zhenbin Wu (University of

Data Analysis at CMS Level-1 Trigger Zhenbin Wu (University of Illinois at Chicago) -- On behalf of the CMS Collaboration 8/2/17 DPF 2017 1 CMS Trigger

771 views • 14 slides
ELS: A Word-Level Method for Entity-Level Sentiment Analysis Nikos Engonopoulos Angeliki

ELS: A Word-Level Method for Entity-Level Sentiment Analysis Nikos Engonopoulos Angeliki

Introduction Method Experiments Conclusion ELS: A Word-Level Method for Entity-Level Sentiment Analysis Nikos Engonopoulos Angeliki Lazaridou Georgios Paliouras Konstantinos Chandrinos University of Athens, NCSR Demokritos, i-sieve

2.32k views • 20 slides
REPPORT Sixth Short Course on Sea Level Data Quality Control, Analysis and Applications for the

REPPORT Sixth Short Course on Sea Level Data Quality Control, Analysis and Applications for the

REPPORT Sixth Short Course on Sea Level Data Quality Control, Analysis and Applications for the Tsunami and other Coastal Hazards Warning System for the Caribbean and Adjacent Regions (CARIBE-EWS) 1. Date of report:

382 views • 3 slides
Shape from X: perspective, texture, shading Thurs. Feb. 15, 2018 1 Level of Analysis in

Shape from X: perspective, texture, shading Thurs. Feb. 15, 2018 1 Level of Analysis in

COMP 546 Lecture 11 Shape from X: perspective, texture, shading Thurs. Feb. 15, 2018 1 Level of Analysis in Perception high - behavior: what is the task ? what problem is being solved? - brain areas and pathways - neural coding -

638 views • 42 slides
Thread-level Analysis over Technical User Forum Data Li Wang, Su Nam Kim and Timothy Baldwin

Thread-level Analysis over Technical User Forum Data Li Wang, Su Nam Kim and Timothy Baldwin

Thread-level Analysis over Technical User Forum Data Li Wang, Su Nam Kim and Timothy Baldwin NICTA VRL Department of Computer Science and Software Engineering University of Melbourne VIC 3010 Australia December 9, 2010 Introduction 2 / 23

606 views • 33 slides
Experimental design for multi-level data: Improving our approach to power analysis using Monte

Experimental design for multi-level data: Improving our approach to power analysis using Monte

Experimental design for multi-level data: Improving our approach to power analysis using Monte Carlo simulation-based parameter recovery estimation Chadwick, S. 1 , & Davies, R. 1 International Multilevel Conference 2019 1 Department of

657 views • 30 slides
Fermi-LAT Observations of the Vela-X PWN Stefan Funk Marie-Helene Grondin Marianne

Fermi-LAT Observations of the Vela-X PWN Stefan Funk Marie-Helene Grondin Marianne

Fermi-LAT Observations of the Vela-X PWN Stefan Funk Marie-Helene Grondin Marianne Lemoine-Goumard Roger Romani Adam Van Etten on behalf of the Fermi-LAT Collaboration and the Pulsar Timing Consortium Fermi Symposium 4 th November 2009 1

607 views • 11 slides
The PRISM project Akira SATO Osaka University Project X Physics Workshop at FNAL 9-10 November

The PRISM project Akira SATO Osaka University Project X Physics Workshop at FNAL 9-10 November

The PRISM project Akira SATO Osaka University Project X Physics Workshop at FNAL 9-10 November 2009 Outline Limits for the COMET and Mu2e experiment signal sensitivity high-Z stopping material PRISM concept R&Ds

813 views • 21 slides
Visualizing Heart Data Visualizing Heart Data of a living entity by analyzing time- -series data

Visualizing Heart Data Visualizing Heart Data of a living entity by analyzing time- -series data

What do researchers seek? What do researchers seek? To achieve a better understanding of the state To achieve a better understanding of the state Visualizing Heart Data Visualizing Heart Data of a living entity by analyzing time-

59 views • 3 slides
Simulation tools for Imaging Atmospheric Cherenkov Telescopes Federico Di Pierro INAF - IFSI,

Simulation tools for Imaging Atmospheric Cherenkov Telescopes Federico Di Pierro INAF - IFSI,

Simulation tools for Imaging Atmospheric Cherenkov Telescopes Federico Di Pierro INAF - IFSI, Torino MeraTev 05.10.2011 F. Di Pierro Outline Tools for: 1. Extensive Air Showers simulation 2. Telescope simulation MeraTev 05.10.2011 2 F.

780 views • 31 slides
Exploiting Exploiting Back-End Back-End APIs APIs fo for Feasible easible Ontology-Based

Exploiting Exploiting Back-End Back-End APIs APIs fo for Feasible easible Ontology-Based

Simon Simon Schiff Schiff, zgr zgr L. L. zep zep Exploiting Exploiting Back-End Back-End APIs APIs fo for Feasible easible Ontology-Based Ontology-Based Stream Stream Access cess Fourth Stream Reasoning Workshop,

260 views • 22 slides
Topology-Guided Vis isual Exploratory ry Analysis Harish Doraiswamy NYU Center for Data

Topology-Guided Vis isual Exploratory ry Analysis Harish Doraiswamy NYU Center for Data

Topology-Guided Vis isual Exploratory ry Analysis Harish Doraiswamy NYU Center for Data Science Scan All Fish 2 Scan All Fish 3 TopoAngler 4 Data Exhaust from Cities 5 Data Exhaust from Cities Infrastructure Environment People 6

861 views • 38 slides
Machine Learning Intro 3/15/17 Recall: The Agent Function We can think of the entire agent, or

Machine Learning Intro 3/15/17 Recall: The Agent Function We can think of the entire agent, or

Machine Learning Intro 3/15/17 Recall: The Agent Function We can think of the entire agent, or some portion of it as implementing a function. inputs: the agents internal state and what it perceives outputs: the agents actions We

473 views • 20 slides
Muonic news Muonic hydrogen and deuterium Randolf Pohl Randolf Pohl JGU, Mainz MPQ, Garching

Muonic news Muonic hydrogen and deuterium Randolf Pohl Randolf Pohl JGU, Mainz MPQ, Garching

Shrinking the Proton Exotic and not-so-exotic atoms for nuclear physics and fundamental constants Muonic news Muonic hydrogen and deuterium Randolf Pohl Randolf Pohl JGU, Mainz MPQ, Garching for the CREMA collaboration 1 Collaborators

1.58k views • 135 slides

More recommend