Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem”
Kirkpatrick et al . (Reports, 9 December 2021, p. 1385) trained a neural network–based DFT functional, DM21, on fractional-charge (FC) and fractional-spin (FS) systems, and they claim that it has outstanding accuracy for chemical systems exhibiting strong correlation. Here, we show that the ability...
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| Veröffentlicht in: | Science (American Association for the Advancement of Science) 2022-08, Vol.377 (6606), p.eabq3385-eabq3385 |
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| container_issue | 6606 |
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| container_title | Science (American Association for the Advancement of Science) |
| container_volume | 377 |
| creator | Gerasimov, Igor S. Losev, Timofey V. Epifanov, Evgeny Yu Rudenko, Irina Bushmarinov, Ivan S. Ryabov, Alexander A. Zhilyaev, Petr A. Medvedev, Michael G. |
| description | Kirkpatrick
et al
. (Reports, 9 December 2021, p. 1385) trained a neural network–based DFT functional, DM21, on fractional-charge (FC) and fractional-spin (FS) systems, and they claim that it has outstanding accuracy for chemical systems exhibiting strong correlation. Here, we show that the ability of DM21 to generalize the behavior of such systems does not follow from the published results and requires revisiting. |
| doi_str_mv | 10.1126/science.abq3385 |
| format | Article |
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et al
. (Reports, 9 December 2021, p. 1385) trained a neural network–based DFT functional, DM21, on fractional-charge (FC) and fractional-spin (FS) systems, and they claim that it has outstanding accuracy for chemical systems exhibiting strong correlation. Here, we show that the ability of DM21 to generalize the behavior of such systems does not follow from the published results and requires revisiting.</description><identifier>ISSN: 0036-8075</identifier><identifier>EISSN: 1095-9203</identifier><identifier>DOI: 10.1126/science.abq3385</identifier><language>eng</language><publisher>Washington: The American Association for the Advancement of Science</publisher><ispartof>Science (American Association for the Advancement of Science), 2022-08, Vol.377 (6606), p.eabq3385-eabq3385</ispartof><rights>Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c217t-1f0a54a102537d76c7149028a533dedf44cadcba6cb5a69c7dbf759aad1e822a3</citedby><cites>FETCH-LOGICAL-c217t-1f0a54a102537d76c7149028a533dedf44cadcba6cb5a69c7dbf759aad1e822a3</cites><orcidid>0000-0001-6953-8317 ; 0000-0001-9111-975X ; 0000-0003-1553-9984 ; 0000-0001-7070-4052 ; 0000-0001-8392-8661 ; 0000-0001-8699-4736 ; 0000-0002-6534-4133</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,2884,2885,27924,27925</link.rule.ids></links><search><creatorcontrib>Gerasimov, Igor S.</creatorcontrib><creatorcontrib>Losev, Timofey V.</creatorcontrib><creatorcontrib>Epifanov, Evgeny Yu</creatorcontrib><creatorcontrib>Rudenko, Irina</creatorcontrib><creatorcontrib>Bushmarinov, Ivan S.</creatorcontrib><creatorcontrib>Ryabov, Alexander A.</creatorcontrib><creatorcontrib>Zhilyaev, Petr A.</creatorcontrib><creatorcontrib>Medvedev, Michael G.</creatorcontrib><title>Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem”</title><title>Science (American Association for the Advancement of Science)</title><description>Kirkpatrick
et al
. (Reports, 9 December 2021, p. 1385) trained a neural network–based DFT functional, DM21, on fractional-charge (FC) and fractional-spin (FS) systems, and they claim that it has outstanding accuracy for chemical systems exhibiting strong correlation. 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et al
. (Reports, 9 December 2021, p. 1385) trained a neural network–based DFT functional, DM21, on fractional-charge (FC) and fractional-spin (FS) systems, and they claim that it has outstanding accuracy for chemical systems exhibiting strong correlation. Here, we show that the ability of DM21 to generalize the behavior of such systems does not follow from the published results and requires revisiting.</abstract><cop>Washington</cop><pub>The American Association for the Advancement of Science</pub><doi>10.1126/science.abq3385</doi><orcidid>https://orcid.org/0000-0001-6953-8317</orcidid><orcidid>https://orcid.org/0000-0001-9111-975X</orcidid><orcidid>https://orcid.org/0000-0003-1553-9984</orcidid><orcidid>https://orcid.org/0000-0001-7070-4052</orcidid><orcidid>https://orcid.org/0000-0001-8392-8661</orcidid><orcidid>https://orcid.org/0000-0001-8699-4736</orcidid><orcidid>https://orcid.org/0000-0002-6534-4133</orcidid></addata></record> |
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| title | Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem” |
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