Optimum filtering and sensitivity for resonant gravitational-wave antennas View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1979-03

AUTHORS

G. Pizzella

ABSTRACT

The optimum filter algorithm based on the Wiener-Kolmogoroff theory for the linear mean square estimation of signals in the presence of noise is applied to the data which can be supplied by a gravitational-wave antenna. It is shown that the signal-to-noise ratio for the filtered data is independent of the data-sampling time and of the electronic chain. The sensitivity of a gravitational antenna to short bursts of radiation, as derived from the optimum filter, improves with increasingβQ/T, but eventually approaches a limit (already derived for a nonoptimum algorithm by Giffard) which depends only on the intrinsic noise of the electromechanical transducer and on the antenna mass. When the quantum limited noise is reached, the only way to improve the sensitivity of the antenna is to increase its mass. It turns out that, in order to be able to observe the supernovae in the Virgo cluster, a mass larger than 1000 kg might be necessary. More... »

PAGES

209-221

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf02508232

DOI

http://dx.doi.org/10.1007/bf02508232

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1027836223


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/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0906", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Electrical and Electronic Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Istituto di Fisica cell'Universit\u00e0, Roma", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Istituto di Fisica cell'Universit\u00e0, Roma"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pizzella", 
        "givenName": "G.", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf02510106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012917492", 
          "https://doi.org/10.1007/bf02510106"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1979-03", 
    "datePublishedReg": "1979-03-01", 
    "description": "The optimum filter algorithm based on the Wiener-Kolmogoroff theory for the linear mean square estimation of signals in the presence of noise is applied to the data which can be supplied by a gravitational-wave antenna. It is shown that the signal-to-noise ratio for the filtered data is independent of the data-sampling time and of the electronic chain. The sensitivity of a gravitational antenna to short bursts of radiation, as derived from the optimum filter, improves with increasing\u03b2Q/T, but eventually approaches a limit (already derived for a nonoptimum algorithm by Giffard) which depends only on the intrinsic noise of the electromechanical transducer and on the antenna mass. When the quantum limited noise is reached, the only way to improve the sensitivity of the antenna is to increase its mass. It turns out that, in order to be able to observe the supernovae in the Virgo cluster, a mass larger than 1000 kg might be necessary.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/bf02508232", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1358836", 
        "issn": [
          "1124-1896", 
          "1826-9885"
        ], 
        "name": "Il Nuovo Cimento C", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "2"
      }
    ], 
    "keywords": [
      "gravitational-wave antenna", 
      "Wiener-Kolmogoroff theory", 
      "Virgo cluster", 
      "gravitational antennas", 
      "electronic chain", 
      "antenna mass", 
      "short bursts", 
      "linear mean square estimation", 
      "limited noise", 
      "noise ratio", 
      "supernovae", 
      "intrinsic noise", 
      "radiation", 
      "mass", 
      "noise", 
      "bursts", 
      "electromechanical transducers", 
      "antenna", 
      "signals", 
      "optimum filter", 
      "mean square estimation", 
      "clusters", 
      "sensitivity", 
      "limit", 
      "theory", 
      "presence of noise", 
      "optimum filtering", 
      "filter", 
      "ratio", 
      "only way", 
      "order", 
      "transducer", 
      "filtering", 
      "data", 
      "time", 
      "presence", 
      "chain", 
      "way", 
      "estimation", 
      "filter algorithm", 
      "algorithm", 
      "squares estimation", 
      "optimum filter algorithm", 
      "data-sampling time", 
      "increasing\u03b2Q/T", 
      "quantum limited noise", 
      "resonant gravitational-wave antennas"
    ], 
    "name": "Optimum filtering and sensitivity for resonant gravitational-wave antennas", 
    "pagination": "209-221", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1027836223"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/bf02508232"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/bf02508232", 
      "https://app.dimensions.ai/details/publication/pub.1027836223"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:00", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_124.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/bf02508232"
  }
]
 

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/bf02508232'

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/bf02508232'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf02508232'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf02508232'


 

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

108 TRIPLES      22 PREDICATES      74 URIs      65 LITERALS      6 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/bf02508232 schema:about anzsrc-for:09
2 anzsrc-for:0906
3 schema:author N0d26e29aee7b41ffa9b929256df8d161
4 schema:citation sg:pub.10.1007/bf02510106
5 schema:datePublished 1979-03
6 schema:datePublishedReg 1979-03-01
7 schema:description The optimum filter algorithm based on the Wiener-Kolmogoroff theory for the linear mean square estimation of signals in the presence of noise is applied to the data which can be supplied by a gravitational-wave antenna. It is shown that the signal-to-noise ratio for the filtered data is independent of the data-sampling time and of the electronic chain. The sensitivity of a gravitational antenna to short bursts of radiation, as derived from the optimum filter, improves with increasingβQ/T, but eventually approaches a limit (already derived for a nonoptimum algorithm by Giffard) which depends only on the intrinsic noise of the electromechanical transducer and on the antenna mass. When the quantum limited noise is reached, the only way to improve the sensitivity of the antenna is to increase its mass. It turns out that, in order to be able to observe the supernovae in the Virgo cluster, a mass larger than 1000 kg might be necessary.
8 schema:genre article
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf N6542463a0ff844d2b1db7a917e64067d
12 Nb5b25204957c4d6e8d9320cb8d0d09e3
13 sg:journal.1358836
14 schema:keywords Virgo cluster
15 Wiener-Kolmogoroff theory
16 algorithm
17 antenna
18 antenna mass
19 bursts
20 chain
21 clusters
22 data
23 data-sampling time
24 electromechanical transducers
25 electronic chain
26 estimation
27 filter
28 filter algorithm
29 filtering
30 gravitational antennas
31 gravitational-wave antenna
32 increasingβQ/T
33 intrinsic noise
34 limit
35 limited noise
36 linear mean square estimation
37 mass
38 mean square estimation
39 noise
40 noise ratio
41 only way
42 optimum filter
43 optimum filter algorithm
44 optimum filtering
45 order
46 presence
47 presence of noise
48 quantum limited noise
49 radiation
50 ratio
51 resonant gravitational-wave antennas
52 sensitivity
53 short bursts
54 signals
55 squares estimation
56 supernovae
57 theory
58 time
59 transducer
60 way
61 schema:name Optimum filtering and sensitivity for resonant gravitational-wave antennas
62 schema:pagination 209-221
63 schema:productId N19a12cc051214fc0a793f4d8994b2a0e
64 N2f249ddcadeb4737aadc5dd57d51a241
65 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027836223
66 https://doi.org/10.1007/bf02508232
67 schema:sdDatePublished 2022-01-01T18:00
68 schema:sdLicense https://scigraph.springernature.com/explorer/license/
69 schema:sdPublisher N889bdc30a9344852ba47d0017ce85f46
70 schema:url https://doi.org/10.1007/bf02508232
71 sgo:license sg:explorer/license/
72 sgo:sdDataset articles
73 rdf:type schema:ScholarlyArticle
74 N0d26e29aee7b41ffa9b929256df8d161 rdf:first Nc09cce984fa04131a02e51d1ab6fa8a8
75 rdf:rest rdf:nil
76 N19a12cc051214fc0a793f4d8994b2a0e schema:name dimensions_id
77 schema:value pub.1027836223
78 rdf:type schema:PropertyValue
79 N2f249ddcadeb4737aadc5dd57d51a241 schema:name doi
80 schema:value 10.1007/bf02508232
81 rdf:type schema:PropertyValue
82 N6542463a0ff844d2b1db7a917e64067d schema:issueNumber 2
83 rdf:type schema:PublicationIssue
84 N889bdc30a9344852ba47d0017ce85f46 schema:name Springer Nature - SN SciGraph project
85 rdf:type schema:Organization
86 Nb5b25204957c4d6e8d9320cb8d0d09e3 schema:volumeNumber 2
87 rdf:type schema:PublicationVolume
88 Nc09cce984fa04131a02e51d1ab6fa8a8 schema:affiliation grid-institutes:None
89 schema:familyName Pizzella
90 schema:givenName G.
91 rdf:type schema:Person
92 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
93 schema:name Engineering
94 rdf:type schema:DefinedTerm
95 anzsrc-for:0906 schema:inDefinedTermSet anzsrc-for:
96 schema:name Electrical and Electronic Engineering
97 rdf:type schema:DefinedTerm
98 sg:journal.1358836 schema:issn 1124-1896
99 1826-9885
100 schema:name Il Nuovo Cimento C
101 schema:publisher Springer Nature
102 rdf:type schema:Periodical
103 sg:pub.10.1007/bf02510106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012917492
104 https://doi.org/10.1007/bf02510106
105 rdf:type schema:CreativeWork
106 grid-institutes:None schema:alternateName Istituto di Fisica cell'Università, Roma
107 schema:name Istituto di Fisica cell'Università, Roma
108 rdf:type schema:Organization
 




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


...