Quantum Computing and Information Extraction for Dynamical Quantum Systems View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2004-10

AUTHORS

Giuliano Benenti, Giulio Casati, Simone Montangero

ABSTRACT

We discuss the simulation of complex dynamical systems on a quantum computer. We show that a quantum computer can be used to efficiently extract relevant physical information. It is possible to simulate the dynamical localization of classical chaos and extract the localization length with quadratic speed up with respect to any known classical computation. We can also compute with algebraic speed up the diffusion coefficient and the diffusion exponent, both in the regimes of Brownian and anomalous diffusion. Finally, we show that it is possible to extract the fidelity of the quantum motion, which measures the stability of the system under perturbations, with exponential speed up. The so-called quantum sawtooth map model is used as a test bench to illustrate these results. PACS: 03.67.Lx, 05.45.Mt More... »

PAGES

273-293

Journal

TITLE

Quantum Information Processing

ISSUE

1-5

VOLUME

3

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11128-004-0415-2

DOI

http://dx.doi.org/10.1007/s11128-004-0415-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021694727


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/2008/0101", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Pure Mathematics", 
        "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": {
          "name": [
            "Center for Nonlinear and Complex Systems, Istituto Nazionale per la Fisica della Materia, Universit\u00e0 degli Studi dell'Insubria, Unit\u00e0 di Como, Via Valleggio 11, 22100, Como, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Benenti", 
        "givenName": "Giuliano", 
        "id": "sg:person.01044467120.71", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01044467120.71"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "INFN Sezione di Milano", 
          "id": "https://www.grid.ac/institutes/grid.470206.7", 
          "name": [
            "Center for Nonlinear and Complex Systems, Istituto Nazionale per la Fisica della Materia, Universit\u00e0 degli Studi dell'Insubria, Unit\u00e0 di Como, Via Valleggio 11, 22100, Como, Italy", 
            "Istituto Nazionale per la Fisica Nucleare, Sezione di Milano, Via Celoria 16, 20133, Milano, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Casati", 
        "givenName": "Giulio", 
        "id": "sg:person.01345652512.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01345652512.96"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "NEST-INFM & Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126, Pisa, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Montangero", 
        "givenName": "Simone", 
        "id": "sg:person.0761227611.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0761227611.56"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1103/physreva.67.052312", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000019081"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.67.052312", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000019081"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.89.284102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003022978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.89.284102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003022978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.87.227901", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005824246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.87.227901", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005824246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.86.2490", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008640012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.86.2490", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008640012"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0370-1573(94)00093-i", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009411032"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.91.210403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011769051"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.91.210403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011769051"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature00801", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013107082", 
          "https://doi.org/10.1038/nature00801"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature00801", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013107082", 
          "https://doi.org/10.1038/nature00801"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.86.2162", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013529267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.86.2162", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013529267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0021757", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015361753", 
          "https://doi.org/10.1007/bfb0021757"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.86.2890", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035518637"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.86.2890", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035518637"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.57.1634", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035648526"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.57.1634", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035648526"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02650179", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038336282", 
          "https://doi.org/10.1007/bf02650179"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature01336", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038501989", 
          "https://doi.org/10.1038/nature01336"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature01336", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038501989", 
          "https://doi.org/10.1038/nature01336"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.89.157902", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040030659"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.89.157902", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040030659"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.79.4790", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041493735"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.79.4790", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041493735"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.64.022319", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044651141"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.64.022319", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044651141"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.88.054103", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048642669"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.88.054103", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048642669"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/414883a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050528624", 
          "https://doi.org/10.1038/414883a"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/414883a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050528624", 
          "https://doi.org/10.1038/414883a"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.30.1610", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060472631"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreva.30.1610", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060472631"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.49.509", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060787963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.49.509", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060787963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.53.2187", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060790731"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.53.2187", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060790731"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.62.233", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060798769"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.62.233", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060798769"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.75.4598", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060812343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.75.4598", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060812343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.273.5278.1073", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062553940"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2004-10", 
    "datePublishedReg": "2004-10-01", 
    "description": "We discuss the simulation of complex dynamical systems on a quantum computer. We show that a quantum computer can be used to efficiently extract relevant physical information. It is possible to simulate the dynamical localization of classical chaos and extract the localization length with quadratic speed up with respect to any known classical computation. We can also compute with algebraic speed up the diffusion coefficient and the diffusion exponent, both in the regimes of Brownian and anomalous diffusion. Finally, we show that it is possible to extract the fidelity of the quantum motion, which measures the stability of the system under perturbations, with exponential speed up. The so-called quantum sawtooth map model is used as a test bench to illustrate these results. PACS: 03.67.Lx, 05.45.Mt", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11128-004-0415-2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1052742", 
        "issn": [
          "1570-0755", 
          "1573-1332"
        ], 
        "name": "Quantum Information Processing", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1-5", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "3"
      }
    ], 
    "name": "Quantum Computing and Information Extraction for Dynamical Quantum Systems", 
    "pagination": "273-293", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "675d09b0a1076b306c5ad2ca2d7a692cae0eab74f786c761cba395b37dab9d72"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11128-004-0415-2"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1021694727"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11128-004-0415-2", 
      "https://app.dimensions.ai/details/publication/pub.1021694727"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T21:39", 
    "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_8687_00000521.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs11128-004-0415-2"
  }
]
 

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/s11128-004-0415-2'

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/s11128-004-0415-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11128-004-0415-2'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11128-004-0415-2'


 

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

157 TRIPLES      21 PREDICATES      51 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11128-004-0415-2 schema:about anzsrc-for:01
2 anzsrc-for:0101
3 schema:author Nfc55198d57f24c0d8ed6496e6b5cf17b
4 schema:citation sg:pub.10.1007/bf02650179
5 sg:pub.10.1007/bfb0021757
6 sg:pub.10.1038/414883a
7 sg:pub.10.1038/nature00801
8 sg:pub.10.1038/nature01336
9 https://doi.org/10.1016/0370-1573(94)00093-i
10 https://doi.org/10.1103/physreva.30.1610
11 https://doi.org/10.1103/physreva.57.1634
12 https://doi.org/10.1103/physreva.64.022319
13 https://doi.org/10.1103/physreva.67.052312
14 https://doi.org/10.1103/physrevlett.49.509
15 https://doi.org/10.1103/physrevlett.53.2187
16 https://doi.org/10.1103/physrevlett.62.233
17 https://doi.org/10.1103/physrevlett.75.4598
18 https://doi.org/10.1103/physrevlett.79.4790
19 https://doi.org/10.1103/physrevlett.86.2162
20 https://doi.org/10.1103/physrevlett.86.2490
21 https://doi.org/10.1103/physrevlett.86.2890
22 https://doi.org/10.1103/physrevlett.87.227901
23 https://doi.org/10.1103/physrevlett.88.054103
24 https://doi.org/10.1103/physrevlett.89.157902
25 https://doi.org/10.1103/physrevlett.89.284102
26 https://doi.org/10.1103/physrevlett.91.210403
27 https://doi.org/10.1126/science.273.5278.1073
28 schema:datePublished 2004-10
29 schema:datePublishedReg 2004-10-01
30 schema:description We discuss the simulation of complex dynamical systems on a quantum computer. We show that a quantum computer can be used to efficiently extract relevant physical information. It is possible to simulate the dynamical localization of classical chaos and extract the localization length with quadratic speed up with respect to any known classical computation. We can also compute with algebraic speed up the diffusion coefficient and the diffusion exponent, both in the regimes of Brownian and anomalous diffusion. Finally, we show that it is possible to extract the fidelity of the quantum motion, which measures the stability of the system under perturbations, with exponential speed up. The so-called quantum sawtooth map model is used as a test bench to illustrate these results. PACS: 03.67.Lx, 05.45.Mt
31 schema:genre research_article
32 schema:inLanguage en
33 schema:isAccessibleForFree true
34 schema:isPartOf N3878d0d5fc5640908bb132ab1b218bfc
35 Ne7b2f0956fd749d6a494e1b75dbe1fd4
36 sg:journal.1052742
37 schema:name Quantum Computing and Information Extraction for Dynamical Quantum Systems
38 schema:pagination 273-293
39 schema:productId N143dbf3600cf489fbeab69b7a57e9fc0
40 N85d1eae4b5554828bbce7e14ad1b05e7
41 Na65592a8b5e8494eb32b32e3a4715d1e
42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021694727
43 https://doi.org/10.1007/s11128-004-0415-2
44 schema:sdDatePublished 2019-04-10T21:39
45 schema:sdLicense https://scigraph.springernature.com/explorer/license/
46 schema:sdPublisher Ndac8955abf8f4cc19724ad5a42b1d4b0
47 schema:url http://link.springer.com/10.1007%2Fs11128-004-0415-2
48 sgo:license sg:explorer/license/
49 sgo:sdDataset articles
50 rdf:type schema:ScholarlyArticle
51 N143dbf3600cf489fbeab69b7a57e9fc0 schema:name dimensions_id
52 schema:value pub.1021694727
53 rdf:type schema:PropertyValue
54 N2712a3467b4940d08200451cd039c500 rdf:first sg:person.01345652512.96
55 rdf:rest N5a0b63d49faa4d03b2ba9c7026f7e123
56 N3878d0d5fc5640908bb132ab1b218bfc schema:volumeNumber 3
57 rdf:type schema:PublicationVolume
58 N5a0b63d49faa4d03b2ba9c7026f7e123 rdf:first sg:person.0761227611.56
59 rdf:rest rdf:nil
60 N85d1eae4b5554828bbce7e14ad1b05e7 schema:name readcube_id
61 schema:value 675d09b0a1076b306c5ad2ca2d7a692cae0eab74f786c761cba395b37dab9d72
62 rdf:type schema:PropertyValue
63 N8a3b0b251c3c49eda471b3d7f72fa52a schema:name NEST-INFM & Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126, Pisa, Italy
64 rdf:type schema:Organization
65 Na65592a8b5e8494eb32b32e3a4715d1e schema:name doi
66 schema:value 10.1007/s11128-004-0415-2
67 rdf:type schema:PropertyValue
68 Ncfc24a5f981f41b6bc51d74d2075f1e1 schema:name Center for Nonlinear and Complex Systems, Istituto Nazionale per la Fisica della Materia, Università degli Studi dell'Insubria, Unità di Como, Via Valleggio 11, 22100, Como, Italy
69 rdf:type schema:Organization
70 Ndac8955abf8f4cc19724ad5a42b1d4b0 schema:name Springer Nature - SN SciGraph project
71 rdf:type schema:Organization
72 Ne7b2f0956fd749d6a494e1b75dbe1fd4 schema:issueNumber 1-5
73 rdf:type schema:PublicationIssue
74 Nfc55198d57f24c0d8ed6496e6b5cf17b rdf:first sg:person.01044467120.71
75 rdf:rest N2712a3467b4940d08200451cd039c500
76 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
77 schema:name Mathematical Sciences
78 rdf:type schema:DefinedTerm
79 anzsrc-for:0101 schema:inDefinedTermSet anzsrc-for:
80 schema:name Pure Mathematics
81 rdf:type schema:DefinedTerm
82 sg:journal.1052742 schema:issn 1570-0755
83 1573-1332
84 schema:name Quantum Information Processing
85 rdf:type schema:Periodical
86 sg:person.01044467120.71 schema:affiliation Ncfc24a5f981f41b6bc51d74d2075f1e1
87 schema:familyName Benenti
88 schema:givenName Giuliano
89 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01044467120.71
90 rdf:type schema:Person
91 sg:person.01345652512.96 schema:affiliation https://www.grid.ac/institutes/grid.470206.7
92 schema:familyName Casati
93 schema:givenName Giulio
94 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01345652512.96
95 rdf:type schema:Person
96 sg:person.0761227611.56 schema:affiliation N8a3b0b251c3c49eda471b3d7f72fa52a
97 schema:familyName Montangero
98 schema:givenName Simone
99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0761227611.56
100 rdf:type schema:Person
101 sg:pub.10.1007/bf02650179 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038336282
102 https://doi.org/10.1007/bf02650179
103 rdf:type schema:CreativeWork
104 sg:pub.10.1007/bfb0021757 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015361753
105 https://doi.org/10.1007/bfb0021757
106 rdf:type schema:CreativeWork
107 sg:pub.10.1038/414883a schema:sameAs https://app.dimensions.ai/details/publication/pub.1050528624
108 https://doi.org/10.1038/414883a
109 rdf:type schema:CreativeWork
110 sg:pub.10.1038/nature00801 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013107082
111 https://doi.org/10.1038/nature00801
112 rdf:type schema:CreativeWork
113 sg:pub.10.1038/nature01336 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038501989
114 https://doi.org/10.1038/nature01336
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1016/0370-1573(94)00093-i schema:sameAs https://app.dimensions.ai/details/publication/pub.1009411032
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1103/physreva.30.1610 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060472631
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1103/physreva.57.1634 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035648526
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1103/physreva.64.022319 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044651141
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1103/physreva.67.052312 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000019081
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1103/physrevlett.49.509 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060787963
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1103/physrevlett.53.2187 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060790731
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1103/physrevlett.62.233 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060798769
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1103/physrevlett.75.4598 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060812343
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1103/physrevlett.79.4790 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041493735
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1103/physrevlett.86.2162 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013529267
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1103/physrevlett.86.2490 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008640012
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1103/physrevlett.86.2890 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035518637
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1103/physrevlett.87.227901 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005824246
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1103/physrevlett.88.054103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048642669
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1103/physrevlett.89.157902 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040030659
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1103/physrevlett.89.284102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003022978
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1103/physrevlett.91.210403 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011769051
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1126/science.273.5278.1073 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062553940
153 rdf:type schema:CreativeWork
154 https://www.grid.ac/institutes/grid.470206.7 schema:alternateName INFN Sezione di Milano
155 schema:name Center for Nonlinear and Complex Systems, Istituto Nazionale per la Fisica della Materia, Università degli Studi dell'Insubria, Unità di Como, Via Valleggio 11, 22100, Como, Italy
156 Istituto Nazionale per la Fisica Nucleare, Sezione di Milano, Via Celoria 16, 20133, Milano, Italy
157 rdf:type schema:Organization
 




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


...