Loading…

Atomic Data Assessment with PyNeb

PyNeb is a Python package widely used to model emission lines in gaseous nebulae. We take advantage of its object-oriented architecture, class methods, and historical atomic database to structure a practical environment for atomic data assessment. Our aim is to reduce the uncertainties in the parame...

Full description

Saved in:
Bibliographic Details
Published in:Atoms 2020-12, Vol.8 (4), p.66
Main Authors: Morisset, Christophe, Luridiana, Valentina, García-Rojas, Jorge, Gómez-Llanos, Verónica, Bautista, Manuel, Mendoza, Claudio
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c367t-88db1c191a1c6ff92adf75e4385d87a1971a0bbdad47d85bdb12254aae00d74a3
cites cdi_FETCH-LOGICAL-c367t-88db1c191a1c6ff92adf75e4385d87a1971a0bbdad47d85bdb12254aae00d74a3
container_end_page
container_issue 4
container_start_page 66
container_title Atoms
container_volume 8
creator Morisset, Christophe
Luridiana, Valentina
García-Rojas, Jorge
Gómez-Llanos, Verónica
Bautista, Manuel
Mendoza, Claudio
description PyNeb is a Python package widely used to model emission lines in gaseous nebulae. We take advantage of its object-oriented architecture, class methods, and historical atomic database to structure a practical environment for atomic data assessment. Our aim is to reduce the uncertainties in the parameter space (line ratio diagnostics, electron density and temperature, and ionic abundances) arising from the underlying atomic data by critically selecting the PyNeb default datasets. We evaluate the questioned radiative-rate accuracy of the collisionally excited forbidden lines of the N- and P-like ions (O ii, Ne iv, S ii, Cl iii, and Ar iv), which are used as density diagnostics. With the aid of observed line ratios in the dense NGC 7027 planetary nebula and careful data analysis, we arrive at emissivity ratio uncertainties from the radiative rates within 10%, a considerable improvement over a previously predicted 50%. We also examine the accuracy of an extensive dataset of electron-impact effective collision strengths for the carbon isoelectronic sequence recently published. By estimating the impact of the new data on the pivotal [N ii] and [O iii] temperature diagnostics and by benchmarking the collision strength with a measured resonance position, we question their usefulness in nebular modeling. We confirm that the effective-collision-strength scatter of selected datasets for these two ions does not lead to uncertainties in the temperature diagnostics larger than 10%.
doi_str_mv 10.3390/atoms8040066
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_d097e2b1a3ff443a88bfdeabf3240097</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_d097e2b1a3ff443a88bfdeabf3240097</doaj_id><sourcerecordid>2524459514</sourcerecordid><originalsourceid>FETCH-LOGICAL-c367t-88db1c191a1c6ff92adf75e4385d87a1971a0bbdad47d85bdb12254aae00d74a3</originalsourceid><addsrcrecordid>eNpNkE1LAzEQhoMoWGpv_oAVr67mc5McS_0qFPWg5zDZJLqlbWqyRfrvja5I5zLD8Mw7My9C5wRfM6bxDfRxnRXmGDfNERpRSlRNMebHB_UpmuS8xCU0YYrQEbqYlrGurW6hh2qas8957Td99dX1H9XL_snbM3QSYJX95C-P0dv93evssV48P8xn00Xdskb2tVLOkpZoAqRtQtAUXJDCc6aEUxKIlgSwtQ4cl04JW2hKBQfwGDvJgY3RfNB1EZZmm7o1pL2J0JnfRkzvBlLftStvHNbSU0uAhcA5A6VscB5sYLS8r2XRuhy0til-7nzuzTLu0qacb6ignAstCC_U1UC1KeacfPjfSrD58dQcesq-AX6iaDU</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2524459514</pqid></control><display><type>article</type><title>Atomic Data Assessment with PyNeb</title><source>Publicly Available Content Database</source><source>Free Full-Text Journals in Chemistry</source><creator>Morisset, Christophe ; Luridiana, Valentina ; García-Rojas, Jorge ; Gómez-Llanos, Verónica ; Bautista, Manuel ; Mendoza, Claudio</creator><creatorcontrib>Morisset, Christophe ; Luridiana, Valentina ; García-Rojas, Jorge ; Gómez-Llanos, Verónica ; Bautista, Manuel ; Mendoza, Claudio</creatorcontrib><description>PyNeb is a Python package widely used to model emission lines in gaseous nebulae. We take advantage of its object-oriented architecture, class methods, and historical atomic database to structure a practical environment for atomic data assessment. Our aim is to reduce the uncertainties in the parameter space (line ratio diagnostics, electron density and temperature, and ionic abundances) arising from the underlying atomic data by critically selecting the PyNeb default datasets. We evaluate the questioned radiative-rate accuracy of the collisionally excited forbidden lines of the N- and P-like ions (O ii, Ne iv, S ii, Cl iii, and Ar iv), which are used as density diagnostics. With the aid of observed line ratios in the dense NGC 7027 planetary nebula and careful data analysis, we arrive at emissivity ratio uncertainties from the radiative rates within 10%, a considerable improvement over a previously predicted 50%. We also examine the accuracy of an extensive dataset of electron-impact effective collision strengths for the carbon isoelectronic sequence recently published. By estimating the impact of the new data on the pivotal [N ii] and [O iii] temperature diagnostics and by benchmarking the collision strength with a measured resonance position, we question their usefulness in nebular modeling. We confirm that the effective-collision-strength scatter of selected datasets for these two ions does not lead to uncertainties in the temperature diagnostics larger than 10%.</description><identifier>ISSN: 2218-2004</identifier><identifier>EISSN: 2218-2004</identifier><identifier>DOI: 10.3390/atoms8040066</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>astrophysical software ; atomic data assessment ; atomic databases ; Atomic structure ; Data analysis ; Datasets ; Electron density ; Electron impact ; Energy ; Historical structures ; Isoelectronic sequence ; nebular modeling ; Planetary nebulae ; Plasma ; plasma diagnostics ; Position measurement ; Temperature ; Uncertainty</subject><ispartof>Atoms, 2020-12, Vol.8 (4), p.66</ispartof><rights>2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c367t-88db1c191a1c6ff92adf75e4385d87a1971a0bbdad47d85bdb12254aae00d74a3</citedby><cites>FETCH-LOGICAL-c367t-88db1c191a1c6ff92adf75e4385d87a1971a0bbdad47d85bdb12254aae00d74a3</cites><orcidid>0000-0002-1825-8267 ; 0000-0001-6837-3055 ; 0000-0002-6138-1869 ; 0000-0001-5801-6724 ; 0000-0002-2854-4806</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2524459514/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2524459514?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,25734,27905,27906,36993,44571,74875</link.rule.ids></links><search><creatorcontrib>Morisset, Christophe</creatorcontrib><creatorcontrib>Luridiana, Valentina</creatorcontrib><creatorcontrib>García-Rojas, Jorge</creatorcontrib><creatorcontrib>Gómez-Llanos, Verónica</creatorcontrib><creatorcontrib>Bautista, Manuel</creatorcontrib><creatorcontrib>Mendoza, Claudio</creatorcontrib><title>Atomic Data Assessment with PyNeb</title><title>Atoms</title><description>PyNeb is a Python package widely used to model emission lines in gaseous nebulae. We take advantage of its object-oriented architecture, class methods, and historical atomic database to structure a practical environment for atomic data assessment. Our aim is to reduce the uncertainties in the parameter space (line ratio diagnostics, electron density and temperature, and ionic abundances) arising from the underlying atomic data by critically selecting the PyNeb default datasets. We evaluate the questioned radiative-rate accuracy of the collisionally excited forbidden lines of the N- and P-like ions (O ii, Ne iv, S ii, Cl iii, and Ar iv), which are used as density diagnostics. With the aid of observed line ratios in the dense NGC 7027 planetary nebula and careful data analysis, we arrive at emissivity ratio uncertainties from the radiative rates within 10%, a considerable improvement over a previously predicted 50%. We also examine the accuracy of an extensive dataset of electron-impact effective collision strengths for the carbon isoelectronic sequence recently published. By estimating the impact of the new data on the pivotal [N ii] and [O iii] temperature diagnostics and by benchmarking the collision strength with a measured resonance position, we question their usefulness in nebular modeling. We confirm that the effective-collision-strength scatter of selected datasets for these two ions does not lead to uncertainties in the temperature diagnostics larger than 10%.</description><subject>astrophysical software</subject><subject>atomic data assessment</subject><subject>atomic databases</subject><subject>Atomic structure</subject><subject>Data analysis</subject><subject>Datasets</subject><subject>Electron density</subject><subject>Electron impact</subject><subject>Energy</subject><subject>Historical structures</subject><subject>Isoelectronic sequence</subject><subject>nebular modeling</subject><subject>Planetary nebulae</subject><subject>Plasma</subject><subject>plasma diagnostics</subject><subject>Position measurement</subject><subject>Temperature</subject><subject>Uncertainty</subject><issn>2218-2004</issn><issn>2218-2004</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkE1LAzEQhoMoWGpv_oAVr67mc5McS_0qFPWg5zDZJLqlbWqyRfrvja5I5zLD8Mw7My9C5wRfM6bxDfRxnRXmGDfNERpRSlRNMebHB_UpmuS8xCU0YYrQEbqYlrGurW6hh2qas8957Td99dX1H9XL_snbM3QSYJX95C-P0dv93evssV48P8xn00Xdskb2tVLOkpZoAqRtQtAUXJDCc6aEUxKIlgSwtQ4cl04JW2hKBQfwGDvJgY3RfNB1EZZmm7o1pL2J0JnfRkzvBlLftStvHNbSU0uAhcA5A6VscB5sYLS8r2XRuhy0til-7nzuzTLu0qacb6ignAstCC_U1UC1KeacfPjfSrD58dQcesq-AX6iaDU</recordid><startdate>20201201</startdate><enddate>20201201</enddate><creator>Morisset, Christophe</creator><creator>Luridiana, Valentina</creator><creator>García-Rojas, Jorge</creator><creator>Gómez-Llanos, Verónica</creator><creator>Bautista, Manuel</creator><creator>Mendoza, Claudio</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7U5</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-1825-8267</orcidid><orcidid>https://orcid.org/0000-0001-6837-3055</orcidid><orcidid>https://orcid.org/0000-0002-6138-1869</orcidid><orcidid>https://orcid.org/0000-0001-5801-6724</orcidid><orcidid>https://orcid.org/0000-0002-2854-4806</orcidid></search><sort><creationdate>20201201</creationdate><title>Atomic Data Assessment with PyNeb</title><author>Morisset, Christophe ; Luridiana, Valentina ; García-Rojas, Jorge ; Gómez-Llanos, Verónica ; Bautista, Manuel ; Mendoza, Claudio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-88db1c191a1c6ff92adf75e4385d87a1971a0bbdad47d85bdb12254aae00d74a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>astrophysical software</topic><topic>atomic data assessment</topic><topic>atomic databases</topic><topic>Atomic structure</topic><topic>Data analysis</topic><topic>Datasets</topic><topic>Electron density</topic><topic>Electron impact</topic><topic>Energy</topic><topic>Historical structures</topic><topic>Isoelectronic sequence</topic><topic>nebular modeling</topic><topic>Planetary nebulae</topic><topic>Plasma</topic><topic>plasma diagnostics</topic><topic>Position measurement</topic><topic>Temperature</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Morisset, Christophe</creatorcontrib><creatorcontrib>Luridiana, Valentina</creatorcontrib><creatorcontrib>García-Rojas, Jorge</creatorcontrib><creatorcontrib>Gómez-Llanos, Verónica</creatorcontrib><creatorcontrib>Bautista, Manuel</creatorcontrib><creatorcontrib>Mendoza, Claudio</creatorcontrib><collection>CrossRef</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Aerospace Database</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Atoms</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Morisset, Christophe</au><au>Luridiana, Valentina</au><au>García-Rojas, Jorge</au><au>Gómez-Llanos, Verónica</au><au>Bautista, Manuel</au><au>Mendoza, Claudio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Atomic Data Assessment with PyNeb</atitle><jtitle>Atoms</jtitle><date>2020-12-01</date><risdate>2020</risdate><volume>8</volume><issue>4</issue><spage>66</spage><pages>66-</pages><issn>2218-2004</issn><eissn>2218-2004</eissn><abstract>PyNeb is a Python package widely used to model emission lines in gaseous nebulae. We take advantage of its object-oriented architecture, class methods, and historical atomic database to structure a practical environment for atomic data assessment. Our aim is to reduce the uncertainties in the parameter space (line ratio diagnostics, electron density and temperature, and ionic abundances) arising from the underlying atomic data by critically selecting the PyNeb default datasets. We evaluate the questioned radiative-rate accuracy of the collisionally excited forbidden lines of the N- and P-like ions (O ii, Ne iv, S ii, Cl iii, and Ar iv), which are used as density diagnostics. With the aid of observed line ratios in the dense NGC 7027 planetary nebula and careful data analysis, we arrive at emissivity ratio uncertainties from the radiative rates within 10%, a considerable improvement over a previously predicted 50%. We also examine the accuracy of an extensive dataset of electron-impact effective collision strengths for the carbon isoelectronic sequence recently published. By estimating the impact of the new data on the pivotal [N ii] and [O iii] temperature diagnostics and by benchmarking the collision strength with a measured resonance position, we question their usefulness in nebular modeling. We confirm that the effective-collision-strength scatter of selected datasets for these two ions does not lead to uncertainties in the temperature diagnostics larger than 10%.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/atoms8040066</doi><orcidid>https://orcid.org/0000-0002-1825-8267</orcidid><orcidid>https://orcid.org/0000-0001-6837-3055</orcidid><orcidid>https://orcid.org/0000-0002-6138-1869</orcidid><orcidid>https://orcid.org/0000-0001-5801-6724</orcidid><orcidid>https://orcid.org/0000-0002-2854-4806</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2218-2004
ispartof Atoms, 2020-12, Vol.8 (4), p.66
issn 2218-2004
2218-2004
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_d097e2b1a3ff443a88bfdeabf3240097
source Publicly Available Content Database; Free Full-Text Journals in Chemistry
subjects astrophysical software
atomic data assessment
atomic databases
Atomic structure
Data analysis
Datasets
Electron density
Electron impact
Energy
Historical structures
Isoelectronic sequence
nebular modeling
Planetary nebulae
Plasma
plasma diagnostics
Position measurement
Temperature
Uncertainty
title Atomic Data Assessment with PyNeb
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T17%3A12%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Atomic%20Data%20Assessment%20with%20PyNeb&rft.jtitle=Atoms&rft.au=Morisset,%20Christophe&rft.date=2020-12-01&rft.volume=8&rft.issue=4&rft.spage=66&rft.pages=66-&rft.issn=2218-2004&rft.eissn=2218-2004&rft_id=info:doi/10.3390/atoms8040066&rft_dat=%3Cproquest_doaj_%3E2524459514%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c367t-88db1c191a1c6ff92adf75e4385d87a1971a0bbdad47d85bdb12254aae00d74a3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2524459514&rft_id=info:pmid/&rfr_iscdi=true