Optimization Stability in Excited-State-Specific Variational Monte Carlo
We investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye mole...
Gespeichert in:
| Veröffentlicht in: | Journal of chemical theory and computation 2023-02, Vol.19 (3), p.767-782 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 782 |
|---|---|
| container_issue | 3 |
| container_start_page | 767 |
| container_title | Journal of chemical theory and computation |
| container_volume | 19 |
| creator | Otis, Leon Neuscamman, Eric |
| description | We investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method’s stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance. |
| doi_str_mv | 10.1021/acs.jctc.2c00642 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_osti_</sourceid><recordid>TN_cdi_osti_scitechconnect_2326966</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2783221308</sourcerecordid><originalsourceid>FETCH-LOGICAL-a433t-81ca0719caa6523c206b26c437ad209e5be4aea00de3e6ec2596ca18bd2cb3c33</originalsourceid><addsrcrecordid>eNp1kc1P20AQxVdVUaHAvafKai8c6rA7Y2_sI4qgIIE48HFdjccTdSPHm3o3UuGvxyGBQyVOO1r93puPp9Q3oydGgzkljpMFJ54Aa20L-KQOTFnUeW3Bfn6vTbWvvsa40BqxAPyi9tFaCyVWB-rydpX80j9T8qHP7hI1vvPpKfN9dv6PfZI2Hz-T5HcrYT_3nD3S4F9p6rKb0CfJZjR04UjtzamLcrx7D9XDxfn97DK_vv19NTu7zqlATHllmPTU1ExkS0AGbRuwXOCUWtC1lI0UJKR1KyhWGMraMpmqaYEbZMRD9WPrG2LyLm5G5D8c-l44OUCwtbUjdLKFVkP4u5aY3NJHlq6jXsI6OpjaCrDUhR7Rn_-hi7AexuU2VIUABnU1UnpL8RBiHGTuVoNf0vDkjHabKNwYhdtE4XZRjJLvO-N1s5T2XfB2-xH4tQVepW9NP_R7AbDnk9g</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2783221308</pqid></control><display><type>article</type><title>Optimization Stability in Excited-State-Specific Variational Monte Carlo</title><source>American Chemical Society Journals</source><creator>Otis, Leon ; Neuscamman, Eric</creator><creatorcontrib>Otis, Leon ; Neuscamman, Eric ; Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)</creatorcontrib><description>We investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method’s stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance.</description><identifier>ISSN: 1549-9618</identifier><identifier>EISSN: 1549-9626</identifier><identifier>DOI: 10.1021/acs.jctc.2c00642</identifier><identifier>PMID: 36662538</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Adaptive control ; Algorithms ; Cyanine dyes ; energy ; excited states ; gradient descent ; INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY ; Optimization ; Quantum Electronic Structure ; quantum Monte Carlo ; stability ; wave function ; Wave functions</subject><ispartof>Journal of chemical theory and computation, 2023-02, Vol.19 (3), p.767-782</ispartof><rights>2023 American Chemical Society</rights><rights>Copyright American Chemical Society Feb 14, 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a433t-81ca0719caa6523c206b26c437ad209e5be4aea00de3e6ec2596ca18bd2cb3c33</citedby><cites>FETCH-LOGICAL-a433t-81ca0719caa6523c206b26c437ad209e5be4aea00de3e6ec2596ca18bd2cb3c33</cites><orcidid>0000-0002-4760-8238 ; 0000-0003-4079-8347 ; 0000000340798347 ; 0000000247608238</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.jctc.2c00642$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.jctc.2c00642$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>230,314,780,784,885,2763,27075,27923,27924,56737,56787</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36662538$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/servlets/purl/2326966$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Otis, Leon</creatorcontrib><creatorcontrib>Neuscamman, Eric</creatorcontrib><creatorcontrib>Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)</creatorcontrib><title>Optimization Stability in Excited-State-Specific Variational Monte Carlo</title><title>Journal of chemical theory and computation</title><addtitle>J. Chem. Theory Comput</addtitle><description>We investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method’s stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance.</description><subject>Adaptive control</subject><subject>Algorithms</subject><subject>Cyanine dyes</subject><subject>energy</subject><subject>excited states</subject><subject>gradient descent</subject><subject>INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY</subject><subject>Optimization</subject><subject>Quantum Electronic Structure</subject><subject>quantum Monte Carlo</subject><subject>stability</subject><subject>wave function</subject><subject>Wave functions</subject><issn>1549-9618</issn><issn>1549-9626</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp1kc1P20AQxVdVUaHAvafKai8c6rA7Y2_sI4qgIIE48HFdjccTdSPHm3o3UuGvxyGBQyVOO1r93puPp9Q3oydGgzkljpMFJ54Aa20L-KQOTFnUeW3Bfn6vTbWvvsa40BqxAPyi9tFaCyVWB-rydpX80j9T8qHP7hI1vvPpKfN9dv6PfZI2Hz-T5HcrYT_3nD3S4F9p6rKb0CfJZjR04UjtzamLcrx7D9XDxfn97DK_vv19NTu7zqlATHllmPTU1ExkS0AGbRuwXOCUWtC1lI0UJKR1KyhWGMraMpmqaYEbZMRD9WPrG2LyLm5G5D8c-l44OUCwtbUjdLKFVkP4u5aY3NJHlq6jXsI6OpjaCrDUhR7Rn_-hi7AexuU2VIUABnU1UnpL8RBiHGTuVoNf0vDkjHabKNwYhdtE4XZRjJLvO-N1s5T2XfB2-xH4tQVepW9NP_R7AbDnk9g</recordid><startdate>20230214</startdate><enddate>20230214</enddate><creator>Otis, Leon</creator><creator>Neuscamman, Eric</creator><general>American Chemical Society</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><scope>OIOZB</scope><scope>OTOTI</scope><orcidid>https://orcid.org/0000-0002-4760-8238</orcidid><orcidid>https://orcid.org/0000-0003-4079-8347</orcidid><orcidid>https://orcid.org/0000000340798347</orcidid><orcidid>https://orcid.org/0000000247608238</orcidid></search><sort><creationdate>20230214</creationdate><title>Optimization Stability in Excited-State-Specific Variational Monte Carlo</title><author>Otis, Leon ; Neuscamman, Eric</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a433t-81ca0719caa6523c206b26c437ad209e5be4aea00de3e6ec2596ca18bd2cb3c33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Adaptive control</topic><topic>Algorithms</topic><topic>Cyanine dyes</topic><topic>energy</topic><topic>excited states</topic><topic>gradient descent</topic><topic>INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY</topic><topic>Optimization</topic><topic>Quantum Electronic Structure</topic><topic>quantum Monte Carlo</topic><topic>stability</topic><topic>wave function</topic><topic>Wave functions</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Otis, Leon</creatorcontrib><creatorcontrib>Neuscamman, Eric</creatorcontrib><creatorcontrib>Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><jtitle>Journal of chemical theory and computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Otis, Leon</au><au>Neuscamman, Eric</au><aucorp>Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization Stability in Excited-State-Specific Variational Monte Carlo</atitle><jtitle>Journal of chemical theory and computation</jtitle><addtitle>J. Chem. Theory Comput</addtitle><date>2023-02-14</date><risdate>2023</risdate><volume>19</volume><issue>3</issue><spage>767</spage><epage>782</epage><pages>767-782</pages><issn>1549-9618</issn><eissn>1549-9626</eissn><abstract>We investigate the issue of optimization stability in variance-based state-specific variational Monte Carlo, discussing the roles of the objective function, the complexity of wave function ansatz, the amount of sampling effort, and the choice of minimization algorithm. Using a small cyanine dye molecule as a test case, we systematically perform minimizations using variants of the linear method as both a standalone algorithm and in a hybrid combination with accelerated descent. We demonstrate that adaptive step control is crucial for maintaining the linear method’s stability when optimizing complicated wave functions and that the hybrid method enjoys both greater stability and minimization performance.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>36662538</pmid><doi>10.1021/acs.jctc.2c00642</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0002-4760-8238</orcidid><orcidid>https://orcid.org/0000-0003-4079-8347</orcidid><orcidid>https://orcid.org/0000000340798347</orcidid><orcidid>https://orcid.org/0000000247608238</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1549-9618 |
| ispartof | Journal of chemical theory and computation, 2023-02, Vol.19 (3), p.767-782 |
| issn | 1549-9618 1549-9626 |
| language | eng |
| recordid | cdi_osti_scitechconnect_2326966 |
| source | American Chemical Society Journals |
| subjects | Adaptive control Algorithms Cyanine dyes energy excited states gradient descent INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY Optimization Quantum Electronic Structure quantum Monte Carlo stability wave function Wave functions |
| title | Optimization Stability in Excited-State-Specific Variational Monte Carlo |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-13T02%3A46%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_osti_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Optimization%20Stability%20in%20Excited-State-Specific%20Variational%20Monte%20Carlo&rft.jtitle=Journal%20of%20chemical%20theory%20and%20computation&rft.au=Otis,%20Leon&rft.aucorp=Lawrence%20Berkeley%20National%20Laboratory%20(LBNL),%20Berkeley,%20CA%20(United%20States)&rft.date=2023-02-14&rft.volume=19&rft.issue=3&rft.spage=767&rft.epage=782&rft.pages=767-782&rft.issn=1549-9618&rft.eissn=1549-9626&rft_id=info:doi/10.1021/acs.jctc.2c00642&rft_dat=%3Cproquest_osti_%3E2783221308%3C/proquest_osti_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2783221308&rft_id=info:pmid/36662538&rfr_iscdi=true |