A unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

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{
  "metadata": {
    "edited_by": 576, 
    "owner": 658, 
    "description": "Dynamical potentials appear in many advanced electronic-structure methods, including self-energies from many-body perturbation theory, dynamical mean-field theory, electronic-transport formulations, and many embedding approaches. Here, we propose a novel treatment for the frequency dependence, introducing an algorithmic inversion method that can be applied to dynamical potentials expanded as sum-over-poles. This approach allows for an exact solution of Dyson-like equations at all frequencies via a mapping to a matrix diagonalization, and provides simultaneously frequency-dependent (spectral) and frequency-integrated (thermodynamic) properties of the Dyson-inverted propagators.\nThe transformation to a sum-over-poles is performed introducing n-th order generalized Lorentzians as an improved basis set to represent the spectral function of a propagator.\nNumerical results for the homogeneous electron gas at the G0W0 level are provided to argue for the accuracy and efficiency of such unified approach.\nIn this record, we provide the input and outputs of the AGWX suite (see article) used in the work. Also, we add the plots of the obtained Green's function for all densities, k-points, and frequencies.", 
    "keywords": [
      "computational materials science", 
      "many-body perturbation theory (GW)", 
      "homogeneous electron gas", 
      "SNSF", 
      "MARVEL", 
      "MaX"
    ], 
    "is_last": true, 
    "title": "A unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials", 
    "status": "published", 
    "license_addendum": null, 
    "doi": "10.24435/materialscloud:mx-3a", 
    "conceptrecid": "1228", 
    "_files": [
      {
        "checksum": "md5:e460c055bdd97a2cff9e88bdc1f6fabb", 
        "description": "Tar archive providing the used inputs and the calculated outputs and data. See README.txt for further details.", 
        "key": "archive.tar", 
        "size": 715683840
      }
    ], 
    "references": [
      {
        "citation": "T. Chiarotti, N. Marzari, and A. Ferretti, arXiv preprint arXiv:2109.07972 (2021)", 
        "doi": "", 
        "url": "https://arxiv.org/abs/2109.07972", 
        "type": "Preprint"
      }
    ], 
    "contributors": [
      {
        "givennames": "Tommaso", 
        "affiliations": [
          "Theory and Simulations of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Chiarotti", 
        "email": "tommaso.chiarotti@epfl.ch"
      }, 
      {
        "givennames": "Nicola", 
        "affiliations": [
          "Theory and Simulations of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Marzari", 
        "email": "nicola.marzari@epfl.ch"
      }, 
      {
        "givennames": "Andrea", 
        "affiliations": [
          "Centro S3, CNR--Istituto Nanoscienze, 41125 Modena, Italy"
        ], 
        "familyname": "Ferretti", 
        "email": "andrea.ferretti@nano.cnr.it"
      }
    ], 
    "_oai": {
      "id": "oai:materialscloud.org:1230"
    }, 
    "publication_date": "Jan 28, 2022, 08:23:36", 
    "mcid": "2022.15", 
    "version": 2, 
    "id": "1230", 
    "license": "Creative Commons Attribution 4.0 International"
  }, 
  "revision": 2, 
  "created": "2022-01-27T23:23:03.458821+00:00", 
  "id": "1230", 
  "updated": "2022-01-28T07:23:36.975345+00:00"
}