Simultaneous analysis of large INTEGRAL/SPI11Based on observations with INTEGRAL, an ESA project with instruments and science data center funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Spain, and Switzerland), Czech Republic and Poland with participation of Russia and the USA. datasets: Optimizing the computation of the solution and its variance using sparse matrix algorithms
Nowadays, analyzing and reducing the ever larger astronomical datasets is becoming a crucial challenge, especially for long cumulated observation times. The INTEGRAL/SPI X/γ-ray spectrometer is an instrument for which it is essential to process many exposures at the same time in order to increase t...
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| Vydáno v: | Astronomy and computing Ročník 1; s. 59 - 69 |
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Elsevier B.V
01.02.2013
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| ISSN: | 2213-1337, 2213-1345 |
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| Abstract | Nowadays, analyzing and reducing the ever larger astronomical datasets is becoming a crucial challenge, especially for long cumulated observation times. The INTEGRAL/SPI X/γ-ray spectrometer is an instrument for which it is essential to process many exposures at the same time in order to increase the low signal-to-noise ratio of the weakest sources. In this context, the conventional methods for data reduction are inefficient and sometimes not feasible at all. Processing several years of data simultaneously requires computing not only the solution of a large system of equations, but also the associated uncertainties. We aim at reducing the computation time and the memory usage. Since the SPI transfer function is sparse, we have used some popular methods for the solution of large sparse linear systems; we briefly review these methods. We use the Multifrontal Massively Parallel Solver (MUMPS) to compute the solution of the system of equations. We also need to compute the variance of the solution, which amounts to computing selected entries of the inverse of the sparse matrix corresponding to our linear system. This can be achieved through one of the latest features of the MUMPS software that has been partly motivated by this work. In this paper we provide a brief presentation of this feature and evaluate its effectiveness on astrophysical problems requiring the processing of large datasets simultaneously, such as the study of the entire emission of the Galaxy. We used these algorithms to solve the large sparse systems arising from SPI data processing and to obtain both their solutions and the associated variances. In conclusion, thanks to these newly developed tools, processing large datasets arising from SPI is now feasible with both a reasonable execution time and a low memory usage.
•INTEGRAL/SPI X/γ-ray spectrometer data analysis.•Large astronomical datasets arising from the simultaneous analysis of years of data.•Resolution of a large sparse system of equations; the solution and its variance.•The Multifrontal Massively Parallel Solver (MUMPS) to solve the equations.•MUMPS A−1 feature to compute selected inverse entries (variance of the solution etc.). |
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| AbstractList | Nowadays, analyzing and reducing the ever larger astronomical datasets is becoming a crucial challenge, especially for long cumulated observation times. The INTEGRAL/SPI X/γ-ray spectrometer is an instrument for which it is essential to process many exposures at the same time in order to increase the low signal-to-noise ratio of the weakest sources. In this context, the conventional methods for data reduction are inefficient and sometimes not feasible at all. Processing several years of data simultaneously requires computing not only the solution of a large system of equations, but also the associated uncertainties. We aim at reducing the computation time and the memory usage. Since the SPI transfer function is sparse, we have used some popular methods for the solution of large sparse linear systems; we briefly review these methods. We use the Multifrontal Massively Parallel Solver (MUMPS) to compute the solution of the system of equations. We also need to compute the variance of the solution, which amounts to computing selected entries of the inverse of the sparse matrix corresponding to our linear system. This can be achieved through one of the latest features of the MUMPS software that has been partly motivated by this work. In this paper we provide a brief presentation of this feature and evaluate its effectiveness on astrophysical problems requiring the processing of large datasets simultaneously, such as the study of the entire emission of the Galaxy. We used these algorithms to solve the large sparse systems arising from SPI data processing and to obtain both their solutions and the associated variances. In conclusion, thanks to these newly developed tools, processing large datasets arising from SPI is now feasible with both a reasonable execution time and a low memory usage.
•INTEGRAL/SPI X/γ-ray spectrometer data analysis.•Large astronomical datasets arising from the simultaneous analysis of years of data.•Resolution of a large sparse system of equations; the solution and its variance.•The Multifrontal Massively Parallel Solver (MUMPS) to solve the equations.•MUMPS A−1 feature to compute selected inverse entries (variance of the solution etc.). |
| Author | Chauvin, M. Amestoy, P. Bouchet, L. Buttari, A. Rouet, F.-H. |
| Author_xml | – sequence: 1 givenname: L. surname: Bouchet fullname: Bouchet, L. email: lbouchet@irap.omp.eu organization: Université de Toulouse, UPS-OMP, IRAP, Toulouse, France – sequence: 2 givenname: P. surname: Amestoy fullname: Amestoy, P. organization: Université de Toulouse, INPT-ENSEEIHT-IRIT, France – sequence: 3 givenname: A. surname: Buttari fullname: Buttari, A. organization: CNRS-IRIT, France – sequence: 4 givenname: F.-H. surname: Rouet fullname: Rouet, F.-H. organization: Université de Toulouse, INPT-ENSEEIHT-IRIT, France – sequence: 5 givenname: M. surname: Chauvin fullname: Chauvin, M. organization: Université de Toulouse, UPS-OMP, IRAP, Toulouse, France |
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| Cites_doi | 10.1007/BF02592099 10.1051/0004-6361:20031482 10.1007/s10107-004-0559-y 10.1086/156922 10.1145/47917.47918 10.1093/comjnl/7.4.308 10.1016/j.parco.2005.07.004 10.1137/0611010 10.1109/SUPERC.1990.129995 10.1145/992200.992202 10.1051/0004-6361:20031173 10.1007/3-540-61142-8_588 10.1088/0004-637X/739/1/29 10.1137/0710033 10.1109/JSTSP.2008.2005337 10.1051/0004-6361:20031501 10.1063/1.1699114 10.1137/100799411 10.1137/S0895479899358194 10.1111/j.1365-2966.2005.08675.x 10.1051/0004-6361:20031224 10.1088/0004-637X/720/2/1772 10.1007/BFb0120949 10.1093/biomet/57.1.97 |
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| References | Amestoy, Duff, Koster, L’Excellent (br000005) 2001; 23 Conn, Gould, Toint (br000060) 1996; 73 Jensen, Clausen, Cassi (br000105) 2003; 411 Metropolis, Rosenbluth, Rosenbluth, Teller, Teller (br000120) 1953; 21 Wächter, Biegler (br000185) 2006; 106 Duff, Erisman, Reid (br000080) 1989 Amestoy, Guermouche, L’Excellent, Pralet (br000010) 2006; 32 Stewart (br000160) 1998 Slavova, T., 2009. Parallel triangular solution in an out-of-core multifrontal approach for solving large sparse linear systems. PhD Thesis, Institut National Polytechnique de Toulouse, France. Bai, Demmel, Dongarra, Ruhe, van der Vorst (br000025) 2000 Bouchet, L., Amestoy, P.R., Buttari, A., Rouet, F.-H., Chauvin, M., 2013. Astronomy and Astrophysics (in press). Hastings (br000095) 1970; 57 Dubath, Knödlseder, Skinner (br000070) 2005; 357 Amestoy, Duff, L’Excellent, Robert, Rouet, Uçar (br000015) 2012; 34 Puglisi, C., 1993. QR factorization of large sparse matrix overdetermined and square matrices with the multifrontal method in a multiprocessing environment. PhD Thesis, Institut National Polytechnique de Toulouse, Toulouse, France. Takahashi, K., Fagan, J., Chen, M.S., 1973. Formation of a sparse bus impedance matrix and its application to short circuit study. In: Power Industry Computer Applications Conference, pp. 63–69. Kirkpatrick, Gelatt, Vecchi (br000110) 1983; 220 Nelder, Mead (br000135) 1965; 7 Gill, Murray, Saunders (br000090) 1997 Vedrenne, Roques, Schonfelder (br000180) 2003; 411 Bouchet, Roques, Jourdain (br000035) 2010; 720 Roques, Schanne, Von Kienlin (br000145) 2003; 411 Tang, Saad (br000170) 2009 Duff, Reid (br000085) 2004; 30 Duff, Erisman, Gear, Reid (br000075) 1988; 23 Neal (br000130) 1993 Liu (br000115) 1990; 11 Murtagh, Saunders (br000125) 1982; 16 (Constrained Optimization) Saad (br000150) 1996 Bobin, Starck, Ottensamer (br000030) 2008; 2 Anderson, E., Bai, Z., Dongarra, J., Greenbaum, A., McKenney, A., Du Croz, J., Hammerling, S., Demmel, J., Bischof, C., Sorensen, D., 1990. LAPACK: a portable linear algebra library for high-performance computers. In: Proceedings of the 1990 ACM/IEEE Conference on Supercomputing, pp. 2–11. Wiaux, Jacques, Puy, Scaife, Vandergheynst (br000190) 2009; 395 Bouchet, Strong, Porter (br000040) 2011; 739 Hoffman, Martin, Rose (br000100) 1973; 10 Campbell, Davis (br000050) 1995 Davis (br000065) 2005 Ubertini, Lebrun, Di Cocco (br000175) 2003; 411 Cash (br000055) 1979; 228 Gill (10.1016/j.ascom.2013.03.002_br000090) 1997 10.1016/j.ascom.2013.03.002_br000020 Wächter (10.1016/j.ascom.2013.03.002_br000185) 2006; 106 10.1016/j.ascom.2013.03.002_br000140 Tang (10.1016/j.ascom.2013.03.002_br000170) 2009 Hoffman (10.1016/j.ascom.2013.03.002_br000100) 1973; 10 10.1016/j.ascom.2013.03.002_br000165 Amestoy (10.1016/j.ascom.2013.03.002_br000010) 2006; 32 Bouchet (10.1016/j.ascom.2013.03.002_br000040) 2011; 739 10.1016/j.ascom.2013.03.002_br000045 Liu (10.1016/j.ascom.2013.03.002_br000115) 1990; 11 Amestoy (10.1016/j.ascom.2013.03.002_br000005) 2001; 23 Nelder (10.1016/j.ascom.2013.03.002_br000135) 1965; 7 Dubath (10.1016/j.ascom.2013.03.002_br000070) 2005; 357 Neal (10.1016/j.ascom.2013.03.002_br000130) 1993 Roques (10.1016/j.ascom.2013.03.002_br000145) 2003; 411 Amestoy (10.1016/j.ascom.2013.03.002_br000015) 2012; 34 Bouchet (10.1016/j.ascom.2013.03.002_br000035) 2010; 720 Davis (10.1016/j.ascom.2013.03.002_br000065) 2005 Kirkpatrick (10.1016/j.ascom.2013.03.002_br000110) 1983; 220 Vedrenne (10.1016/j.ascom.2013.03.002_br000180) 2003; 411 Campbell (10.1016/j.ascom.2013.03.002_br000050) 1995 Ubertini (10.1016/j.ascom.2013.03.002_br000175) 2003; 411 Bobin (10.1016/j.ascom.2013.03.002_br000030) 2008; 2 Conn (10.1016/j.ascom.2013.03.002_br000060) 1996; 73 Metropolis (10.1016/j.ascom.2013.03.002_br000120) 1953; 21 10.1016/j.ascom.2013.03.002_br000155 Duff (10.1016/j.ascom.2013.03.002_br000075) 1988; 23 Hastings (10.1016/j.ascom.2013.03.002_br000095) 1970; 57 Cash (10.1016/j.ascom.2013.03.002_br000055) 1979; 228 Wiaux (10.1016/j.ascom.2013.03.002_br000190) 2009; 395 Duff (10.1016/j.ascom.2013.03.002_br000080) 1989 Bai (10.1016/j.ascom.2013.03.002_br000025) 2000 Jensen (10.1016/j.ascom.2013.03.002_br000105) 2003; 411 Murtagh (10.1016/j.ascom.2013.03.002_br000125) 1982; 16 (Constrained Optimization) Saad (10.1016/j.ascom.2013.03.002_br000150) 1996 Stewart (10.1016/j.ascom.2013.03.002_br000160) 1998 Duff (10.1016/j.ascom.2013.03.002_br000085) 2004; 30 |
| References_xml | – volume: 411 start-page: L63 year: 2003 ident: br000180 publication-title: A&A – volume: 106 start-page: 25 year: 2006 end-page: 57 ident: br000185 publication-title: Mathematical Programming – volume: 34 start-page: 1975 year: 2012 end-page: 1999 ident: br000015 article-title: On computing inverse entries of a sparse matrix in an out-of-core environment publication-title: SIAM Journal on Scientific Computing – volume: 411 start-page: L131 year: 2003 ident: br000175 publication-title: A&A – volume: 11 start-page: 134 year: 1990 end-page: 172 ident: br000115 article-title: The role of elimination trees in sparse factorization publication-title: SIAM Journal on Matrix Analysis and Applications – year: 1993 ident: br000130 article-title: Probabilistic inference using Markov chain Monte Carlo methods. Technical Report CRG-TR-93-1 – volume: 7 start-page: 308 year: 1965 end-page: 313 ident: br000135 publication-title: Computer Journal – year: 1996 ident: br000150 article-title: Iterative Methods for Sparse Linear Systems – volume: 32 start-page: 136 year: 2006 end-page: 156 ident: br000010 article-title: Hybrid scheduling for the parallel solution of linear systems publication-title: Parallel Computing – year: 2000 ident: br000025 article-title: Templates for the Solution of Eigenvalue Problems: A Practical Guide – volume: 23 start-page: 15 year: 2001 end-page: 41 ident: br000005 article-title: A fully asynchronous multifrontal solver using distributed dynamic scheduling publication-title: SIAM Journal of Matrix Analysis and Applications – volume: 10 start-page: 364 year: 1973 end-page: 369 ident: br000100 article-title: Complexity bounds for regular finite difference and finite element grids publication-title: SIAM Journal on Numerical Analysis – volume: 411 start-page: L91 year: 2003 ident: br000145 publication-title: A&A – reference: Slavova, T., 2009. Parallel triangular solution in an out-of-core multifrontal approach for solving large sparse linear systems. PhD Thesis, Institut National Polytechnique de Toulouse, France. – start-page: 2009 year: 2009 ident: br000170 article-title: A probing method for computing the diagonal of the matrix inverse. Tech. Report umsi-2010-42 – volume: 73 start-page: 73 year: 1996 end-page: 110 ident: br000060 article-title: Numerical experiments with the LANCELOT package (Release A) for large-scale nonlinear optimization publication-title: Mathematical Programming – volume: 220 start-page: 671 year: 1983 end-page: 680 ident: br000110 publication-title: Science, New Series – volume: 57 start-page: 97 year: 1970 end-page: 109 ident: br000095 publication-title: Biometrika – volume: 411 start-page: L7 year: 2003 ident: br000105 publication-title: A&A – volume: 228 start-page: 939 year: 1979 ident: br000055 publication-title: Astrophysical Journal – volume: 357 start-page: 420 year: 2005 ident: br000070 publication-title: Monthly Notices of the RAS – volume: 23 start-page: 2 year: 1988 end-page: 8 ident: br000075 article-title: Sparsity structure and Gaussian elimination publication-title: ACM SIGNUM Newsletter – reference: Puglisi, C., 1993. QR factorization of large sparse matrix overdetermined and square matrices with the multifrontal method in a multiprocessing environment. PhD Thesis, Institut National Polytechnique de Toulouse, Toulouse, France. – start-page: 1998 year: 1998 ident: br000160 article-title: Matrix Algorithms – volume: 30 start-page: 118 year: 2004 ident: br000085 article-title: MA57—a code for the solution of indefinite sparse symmetric linear systems publication-title: ACM Transactions on Mathematical Software – volume: 720 start-page: 177 year: 2010 ident: br000035 publication-title: Astrophysical Journal – start-page: 1997 year: 1997 ident: br000090 article-title: SNOPT: an SQP algorithm for large-scale constrained optimization. Technical Report SOL97-3 – year: 1995 ident: br000050 article-title: Computing the sparse inverse subset: an inverse multifrontal approach. Tech. Rep. TR-95-021 – year: 1989 ident: br000080 article-title: Direct Methods for Sparse Matrices – reference: Takahashi, K., Fagan, J., Chen, M.S., 1973. Formation of a sparse bus impedance matrix and its application to short circuit study. In: Power Industry Computer Applications Conference, pp. 63–69. – year: 2005 ident: br000065 article-title: User guide for LDL, a concise sparse Cholesky package. Tech. Rep. – volume: 739 start-page: 29 year: 2011 ident: br000040 publication-title: Astrophysical Journal – volume: 395 start-page: 1733 year: 2009 ident: br000190 publication-title: A&A – volume: 16 (Constrained Optimization) start-page: 84 year: 1982 end-page: 117 ident: br000125 article-title: A projected Lagrangian algorithm and its implementation for sparse nonlinear constraints publication-title: Mathematical Programming Study – reference: Anderson, E., Bai, Z., Dongarra, J., Greenbaum, A., McKenney, A., Du Croz, J., Hammerling, S., Demmel, J., Bischof, C., Sorensen, D., 1990. LAPACK: a portable linear algebra library for high-performance computers. In: Proceedings of the 1990 ACM/IEEE Conference on Supercomputing, pp. 2–11. – volume: 2 start-page: 718 year: 2008 ident: br000030 publication-title: IEEE Selected Topics in Signal Processing – volume: 21 start-page: 1087 year: 1953 end-page: 1092 ident: br000120 publication-title: Journal of Chemical Physics – reference: Bouchet, L., Amestoy, P.R., Buttari, A., Rouet, F.-H., Chauvin, M., 2013. Astronomy and Astrophysics (in press). – volume: 73 start-page: 73 issue: 1 year: 1996 ident: 10.1016/j.ascom.2013.03.002_br000060 article-title: Numerical experiments with the LANCELOT package (Release A) for large-scale nonlinear optimization publication-title: Mathematical Programming doi: 10.1007/BF02592099 – volume: 411 start-page: L63 year: 2003 ident: 10.1016/j.ascom.2013.03.002_br000180 publication-title: A&A doi: 10.1051/0004-6361:20031482 – volume: 106 start-page: 25 issue: 1 year: 2006 ident: 10.1016/j.ascom.2013.03.002_br000185 publication-title: Mathematical Programming doi: 10.1007/s10107-004-0559-y – volume: 228 start-page: 939 year: 1979 ident: 10.1016/j.ascom.2013.03.002_br000055 publication-title: Astrophysical Journal doi: 10.1086/156922 – volume: 23 start-page: 2 issue: 2 year: 1988 ident: 10.1016/j.ascom.2013.03.002_br000075 article-title: Sparsity structure and Gaussian elimination publication-title: ACM SIGNUM Newsletter doi: 10.1145/47917.47918 – volume: 7 start-page: 308 issue: 4 year: 1965 ident: 10.1016/j.ascom.2013.03.002_br000135 publication-title: Computer Journal doi: 10.1093/comjnl/7.4.308 – year: 1996 ident: 10.1016/j.ascom.2013.03.002_br000150 – start-page: 1998 year: 1998 ident: 10.1016/j.ascom.2013.03.002_br000160 – volume: 32 start-page: 136 issue: 2 year: 2006 ident: 10.1016/j.ascom.2013.03.002_br000010 article-title: Hybrid scheduling for the parallel solution of linear systems publication-title: Parallel Computing doi: 10.1016/j.parco.2005.07.004 – volume: 11 start-page: 134 issue: 1 year: 1990 ident: 10.1016/j.ascom.2013.03.002_br000115 article-title: The role of elimination trees in sparse factorization publication-title: SIAM Journal on Matrix Analysis and Applications doi: 10.1137/0611010 – ident: 10.1016/j.ascom.2013.03.002_br000020 doi: 10.1109/SUPERC.1990.129995 – volume: 30 start-page: 118 year: 2004 ident: 10.1016/j.ascom.2013.03.002_br000085 article-title: MA57—a code for the solution of indefinite sparse symmetric linear systems publication-title: ACM Transactions on Mathematical Software doi: 10.1145/992200.992202 – volume: 395 start-page: 1733 year: 2009 ident: 10.1016/j.ascom.2013.03.002_br000190 publication-title: A&A – volume: 411 start-page: L7 year: 2003 ident: 10.1016/j.ascom.2013.03.002_br000105 publication-title: A&A doi: 10.1051/0004-6361:20031173 – ident: 10.1016/j.ascom.2013.03.002_br000165 doi: 10.1007/3-540-61142-8_588 – volume: 739 start-page: 29 year: 2011 ident: 10.1016/j.ascom.2013.03.002_br000040 publication-title: Astrophysical Journal doi: 10.1088/0004-637X/739/1/29 – ident: 10.1016/j.ascom.2013.03.002_br000140 – volume: 10 start-page: 364 issue: 2 year: 1973 ident: 10.1016/j.ascom.2013.03.002_br000100 article-title: Complexity bounds for regular finite difference and finite element grids publication-title: SIAM Journal on Numerical Analysis doi: 10.1137/0710033 – ident: 10.1016/j.ascom.2013.03.002_br000045 – volume: 220 start-page: 671 issue: 4598 year: 1983 ident: 10.1016/j.ascom.2013.03.002_br000110 publication-title: Science, New Series – volume: 2 start-page: 718 year: 2008 ident: 10.1016/j.ascom.2013.03.002_br000030 publication-title: IEEE Selected Topics in Signal Processing doi: 10.1109/JSTSP.2008.2005337 – volume: 411 start-page: L91 year: 2003 ident: 10.1016/j.ascom.2013.03.002_br000145 publication-title: A&A doi: 10.1051/0004-6361:20031501 – ident: 10.1016/j.ascom.2013.03.002_br000155 – year: 1989 ident: 10.1016/j.ascom.2013.03.002_br000080 – year: 1993 ident: 10.1016/j.ascom.2013.03.002_br000130 – year: 2005 ident: 10.1016/j.ascom.2013.03.002_br000065 – volume: 21 start-page: 1087 issue: 6 year: 1953 ident: 10.1016/j.ascom.2013.03.002_br000120 publication-title: Journal of Chemical Physics doi: 10.1063/1.1699114 – start-page: 1997 year: 1997 ident: 10.1016/j.ascom.2013.03.002_br000090 – volume: 34 start-page: 1975 issue: 4 year: 2012 ident: 10.1016/j.ascom.2013.03.002_br000015 article-title: On computing inverse entries of a sparse matrix in an out-of-core environment publication-title: SIAM Journal on Scientific Computing doi: 10.1137/100799411 – volume: 23 start-page: 15 issue: 1 year: 2001 ident: 10.1016/j.ascom.2013.03.002_br000005 article-title: A fully asynchronous multifrontal solver using distributed dynamic scheduling publication-title: SIAM Journal of Matrix Analysis and Applications doi: 10.1137/S0895479899358194 – year: 2000 ident: 10.1016/j.ascom.2013.03.002_br000025 – volume: 357 start-page: 420 year: 2005 ident: 10.1016/j.ascom.2013.03.002_br000070 publication-title: Monthly Notices of the RAS doi: 10.1111/j.1365-2966.2005.08675.x – start-page: 2009 year: 2009 ident: 10.1016/j.ascom.2013.03.002_br000170 – volume: 411 start-page: L131 year: 2003 ident: 10.1016/j.ascom.2013.03.002_br000175 publication-title: A&A doi: 10.1051/0004-6361:20031224 – volume: 720 start-page: 177 year: 2010 ident: 10.1016/j.ascom.2013.03.002_br000035 publication-title: Astrophysical Journal doi: 10.1088/0004-637X/720/2/1772 – volume: 16 (Constrained Optimization) start-page: 84 year: 1982 ident: 10.1016/j.ascom.2013.03.002_br000125 article-title: A projected Lagrangian algorithm and its implementation for sparse nonlinear constraints publication-title: Mathematical Programming Study doi: 10.1007/BFb0120949 – year: 1995 ident: 10.1016/j.ascom.2013.03.002_br000050 – volume: 57 start-page: 97 issue: 1 year: 1970 ident: 10.1016/j.ascom.2013.03.002_br000095 publication-title: Biometrika doi: 10.1093/biomet/57.1.97 |
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| SubjectTerms | Gamma-rays: general Methods: data analysis Methods: numerical Techniques: imaging spectroscopy Techniques: miscellaneous |
| Title | Simultaneous analysis of large INTEGRAL/SPI11Based on observations with INTEGRAL, an ESA project with instruments and science data center funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Spain, and Switzerland), Czech Republic and Poland with participation of Russia and the USA. datasets: Optimizing the computation of the solution and its variance using sparse matrix algorithms |
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