Non-linear parallel solver for detecting point sources in CMB maps using Bayesian techniques View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-04

AUTHORS

P. Alonso, F. Argüeso, R. Cortina, J. Ranilla, A. M. Vidal

ABSTRACT

In this work we present a suitable computational tool to deal with large matrices and solve systems of non-linear equations. This technique is applied to a very interesting problem: the detection and flux estimation of point sources in Cosmic Microwave Background (CMB) maps, which allows a good determination of CMB primordial fluctuations and leads to a better knowledge of the chemistry at the early stages of the Universe. The method uses previous information about the statistical properties of the sources, so that this knowledge is incorporated in a Bayesian scheme. Simulations show that our approach allows the detection of more sources than previous non-Bayesian techniques, with a small computation time. More... »

PAGES

1153-1163

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10910-012-0078-7

DOI

http://dx.doi.org/10.1007/s10910-012-0078-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022582909


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Oviedo", 
          "id": "https://www.grid.ac/institutes/grid.10863.3c", 
          "name": [
            "Department of Mathematics, University of Oviedo, 33203, Gij\u00f3n, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alonso", 
        "givenName": "P.", 
        "id": "sg:person.010447163440.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010447163440.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Oviedo", 
          "id": "https://www.grid.ac/institutes/grid.10863.3c", 
          "name": [
            "Department of Mathematics, University of Oviedo, 33203, Gij\u00f3n, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Arg\u00fceso", 
        "givenName": "F.", 
        "id": "sg:person.013454247655.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013454247655.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Oviedo", 
          "id": "https://www.grid.ac/institutes/grid.10863.3c", 
          "name": [
            "Department of Computer Science, University of Oviedo, 33203, Gij\u00f3n, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cortina", 
        "givenName": "R.", 
        "id": "sg:person.011672701577.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011672701577.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Oviedo", 
          "id": "https://www.grid.ac/institutes/grid.10863.3c", 
          "name": [
            "Department of Computer Science, University of Oviedo, 33203, Gij\u00f3n, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ranilla", 
        "givenName": "J.", 
        "id": "sg:person.011017130042.09", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011017130042.09"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Polytechnic University of Valencia", 
          "id": "https://www.grid.ac/institutes/grid.157927.f", 
          "name": [
            "Department of Computer Systems and Computation, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022, Valencia, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vidal", 
        "givenName": "A. M.", 
        "id": "sg:person.015260331465.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015260331465.48"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1088/0067-0049/180/2/296", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014422135"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10910-011-9936-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027855709", 
          "https://doi.org/10.1007/s10910-011-9936-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2966.2008.14016.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035993552"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2966.2011.18398.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037098771"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2012/410965", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041024130"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11227-012-0824-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042268539", 
          "https://doi.org/10.1007/s11227-012-0824-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1051/0004-6361:20042108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056934153"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1051/0004-6361:200809861", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056940447"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/148307", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058479598"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/173993", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058505283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/186504", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058516013"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/377226", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058670318"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/msp.2009.934716", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061423322"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tassp.1983.1164208", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061519310"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2013-04", 
    "datePublishedReg": "2013-04-01", 
    "description": "In this work we present a suitable computational tool to deal with large matrices and solve systems of non-linear equations. This technique is applied to a very interesting problem: the detection and flux estimation of point sources in Cosmic Microwave Background (CMB) maps, which allows a good determination of CMB primordial fluctuations and leads to a better knowledge of the chemistry at the early stages of the Universe. The method uses previous information about the statistical properties of the sources, so that this knowledge is incorporated in a Bayesian scheme. Simulations show that our approach allows the detection of more sources than previous non-Bayesian techniques, with a small computation time.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10910-012-0078-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1026076", 
        "issn": [
          "0259-9791", 
          "1572-8897"
        ], 
        "name": "Journal of Mathematical Chemistry", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "51"
      }
    ], 
    "name": "Non-linear parallel solver for detecting point sources in CMB maps using Bayesian techniques", 
    "pagination": "1153-1163", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6b96de36331cd5c2431f7fbf6bfd7dbba0ec4dcfd1484c7c6c4508df208b5d00"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10910-012-0078-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1022582909"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10910-012-0078-7", 
      "https://app.dimensions.ai/details/publication/pub.1022582909"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T16:42", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8669_00000512.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10910-012-0078-7"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10910-012-0078-7'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10910-012-0078-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10910-012-0078-7'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10910-012-0078-7'


 

This table displays all metadata directly associated to this object as RDF triples.

137 TRIPLES      21 PREDICATES      41 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10910-012-0078-7 schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author Naecb87d43e9c43b08fe0727e9d3bf352
4 schema:citation sg:pub.10.1007/s10910-011-9936-y
5 sg:pub.10.1007/s11227-012-0824-4
6 https://doi.org/10.1051/0004-6361:20042108
7 https://doi.org/10.1051/0004-6361:200809861
8 https://doi.org/10.1086/148307
9 https://doi.org/10.1086/173993
10 https://doi.org/10.1086/186504
11 https://doi.org/10.1086/377226
12 https://doi.org/10.1088/0067-0049/180/2/296
13 https://doi.org/10.1109/msp.2009.934716
14 https://doi.org/10.1109/tassp.1983.1164208
15 https://doi.org/10.1111/j.1365-2966.2008.14016.x
16 https://doi.org/10.1111/j.1365-2966.2011.18398.x
17 https://doi.org/10.1155/2012/410965
18 schema:datePublished 2013-04
19 schema:datePublishedReg 2013-04-01
20 schema:description In this work we present a suitable computational tool to deal with large matrices and solve systems of non-linear equations. This technique is applied to a very interesting problem: the detection and flux estimation of point sources in Cosmic Microwave Background (CMB) maps, which allows a good determination of CMB primordial fluctuations and leads to a better knowledge of the chemistry at the early stages of the Universe. The method uses previous information about the statistical properties of the sources, so that this knowledge is incorporated in a Bayesian scheme. Simulations show that our approach allows the detection of more sources than previous non-Bayesian techniques, with a small computation time.
21 schema:genre research_article
22 schema:inLanguage en
23 schema:isAccessibleForFree false
24 schema:isPartOf Ne8cf9ccb2a374af28f3574fd1e985dff
25 Neb887b7369974f5992c3a524b0312858
26 sg:journal.1026076
27 schema:name Non-linear parallel solver for detecting point sources in CMB maps using Bayesian techniques
28 schema:pagination 1153-1163
29 schema:productId N62538adb2cb041cfad78ce110b9bf08e
30 N739fb6d8659041de9b438877718df8f3
31 Nf1ed47ed6c444fc6b09771381d003b5f
32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022582909
33 https://doi.org/10.1007/s10910-012-0078-7
34 schema:sdDatePublished 2019-04-10T16:42
35 schema:sdLicense https://scigraph.springernature.com/explorer/license/
36 schema:sdPublisher N18cf25d445a544fd861e44d6a44ee96f
37 schema:url http://link.springer.com/10.1007%2Fs10910-012-0078-7
38 sgo:license sg:explorer/license/
39 sgo:sdDataset articles
40 rdf:type schema:ScholarlyArticle
41 N18cf25d445a544fd861e44d6a44ee96f schema:name Springer Nature - SN SciGraph project
42 rdf:type schema:Organization
43 N2a3744d1687f4af586f7ac4fbf662b42 rdf:first sg:person.011672701577.00
44 rdf:rest N3e6f46943ed14716b195025602fa8af5
45 N2b58feeb4dfb49f7965d04a852f7a83b rdf:first sg:person.013454247655.13
46 rdf:rest N2a3744d1687f4af586f7ac4fbf662b42
47 N3e6f46943ed14716b195025602fa8af5 rdf:first sg:person.011017130042.09
48 rdf:rest Nbdc768a92cf74a76a2e48fc41f100410
49 N62538adb2cb041cfad78ce110b9bf08e schema:name doi
50 schema:value 10.1007/s10910-012-0078-7
51 rdf:type schema:PropertyValue
52 N739fb6d8659041de9b438877718df8f3 schema:name readcube_id
53 schema:value 6b96de36331cd5c2431f7fbf6bfd7dbba0ec4dcfd1484c7c6c4508df208b5d00
54 rdf:type schema:PropertyValue
55 Naecb87d43e9c43b08fe0727e9d3bf352 rdf:first sg:person.010447163440.01
56 rdf:rest N2b58feeb4dfb49f7965d04a852f7a83b
57 Nbdc768a92cf74a76a2e48fc41f100410 rdf:first sg:person.015260331465.48
58 rdf:rest rdf:nil
59 Ne8cf9ccb2a374af28f3574fd1e985dff schema:issueNumber 4
60 rdf:type schema:PublicationIssue
61 Neb887b7369974f5992c3a524b0312858 schema:volumeNumber 51
62 rdf:type schema:PublicationVolume
63 Nf1ed47ed6c444fc6b09771381d003b5f schema:name dimensions_id
64 schema:value pub.1022582909
65 rdf:type schema:PropertyValue
66 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
67 schema:name Mathematical Sciences
68 rdf:type schema:DefinedTerm
69 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
70 schema:name Statistics
71 rdf:type schema:DefinedTerm
72 sg:journal.1026076 schema:issn 0259-9791
73 1572-8897
74 schema:name Journal of Mathematical Chemistry
75 rdf:type schema:Periodical
76 sg:person.010447163440.01 schema:affiliation https://www.grid.ac/institutes/grid.10863.3c
77 schema:familyName Alonso
78 schema:givenName P.
79 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010447163440.01
80 rdf:type schema:Person
81 sg:person.011017130042.09 schema:affiliation https://www.grid.ac/institutes/grid.10863.3c
82 schema:familyName Ranilla
83 schema:givenName J.
84 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011017130042.09
85 rdf:type schema:Person
86 sg:person.011672701577.00 schema:affiliation https://www.grid.ac/institutes/grid.10863.3c
87 schema:familyName Cortina
88 schema:givenName R.
89 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011672701577.00
90 rdf:type schema:Person
91 sg:person.013454247655.13 schema:affiliation https://www.grid.ac/institutes/grid.10863.3c
92 schema:familyName Argüeso
93 schema:givenName F.
94 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013454247655.13
95 rdf:type schema:Person
96 sg:person.015260331465.48 schema:affiliation https://www.grid.ac/institutes/grid.157927.f
97 schema:familyName Vidal
98 schema:givenName A. M.
99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015260331465.48
100 rdf:type schema:Person
101 sg:pub.10.1007/s10910-011-9936-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1027855709
102 https://doi.org/10.1007/s10910-011-9936-y
103 rdf:type schema:CreativeWork
104 sg:pub.10.1007/s11227-012-0824-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042268539
105 https://doi.org/10.1007/s11227-012-0824-4
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1051/0004-6361:20042108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056934153
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1051/0004-6361:200809861 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056940447
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1086/148307 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058479598
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1086/173993 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058505283
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1086/186504 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058516013
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1086/377226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058670318
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1088/0067-0049/180/2/296 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014422135
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1109/msp.2009.934716 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061423322
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1109/tassp.1983.1164208 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061519310
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1111/j.1365-2966.2008.14016.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1035993552
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1111/j.1365-2966.2011.18398.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1037098771
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1155/2012/410965 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041024130
130 rdf:type schema:CreativeWork
131 https://www.grid.ac/institutes/grid.10863.3c schema:alternateName University of Oviedo
132 schema:name Department of Computer Science, University of Oviedo, 33203, Gijón, Spain
133 Department of Mathematics, University of Oviedo, 33203, Gijón, Spain
134 rdf:type schema:Organization
135 https://www.grid.ac/institutes/grid.157927.f schema:alternateName Polytechnic University of Valencia
136 schema:name Department of Computer Systems and Computation, Universitat Politècnica de València, 46022, Valencia, Spain
137 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...