Program Synthesis of Sparse Algorithms for Wave Function and Energy Prediction in Grid-Based Quantum Simulations
We have recently shown how program synthesis (PS), or the concept of “self-writing code”, can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resu...
        Saved in:
      
    
          | Published in | Journal of chemical theory and computation Vol. 18; no. 4; pp. 2462 - 2478 | 
|---|---|
| Main Author | |
| Format | Journal Article | 
| Language | English | 
| Published | 
        United States
          American Chemical Society
    
        12.04.2022
     | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 1549-9618 1549-9626 1549-9626  | 
| DOI | 10.1021/acs.jctc.2c00035 | 
Cover
| Abstract | We have recently shown how program synthesis (PS), or the concept of “self-writing code”, can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resulting algorithms use a grid-based representation of the underlying wave function ψ(x) and PES V(x), providing codes which represent approximations to standard discrete variable representation (DVR) methods. In this Article, we show how this inductive PS strategy can be improved and modified to enable prediction of both vibrational wave functions and energy eigenvalues of representative model PESs (both 1-D and multidimensional). We show that PS can generate algorithms that offer some improvements in energy eigenvalue accuracy over standard DVR schemes; however, we also demonstrate that PS can identify accurate numerical methods that exhibit desirable computational features, such as employing very sparse (tridiagonal) matrices. The resulting PS-generated algorithms are initially developed and tested for 1-D vibrational eigenproblems, before solution of multidimensional problems is demonstrated; we find that our new PS-generated algorithms can reduce calculation times for grid-based eigenvector computation by an order of magnitude or more. More generally, with further development and optimization, we anticipate that PS-generated algorithms based on effective Hamiltonian approximations, such as those proposed here, could be useful in direct simulations of quantum dynamics via wave function propagation and evaluation of molecular electronic structure. | 
    
|---|---|
| AbstractList | We have recently shown how program synthesis (PS), or the concept of “self-writing code”, can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resulting algorithms use a grid-based representation of the underlying wave function ψ(x) and PES V(x), providing codes which represent approximations to standard discrete variable representation (DVR) methods. In this Article, we show how this inductive PS strategy can be improved and modified to enable prediction of both vibrational wave functions and energy eigenvalues of representative model PESs (both 1-D and multidimensional). We show that PS can generate algorithms that offer some improvements in energy eigenvalue accuracy over standard DVR schemes; however, we also demonstrate that PS can identify accurate numerical methods that exhibit desirable computational features, such as employing very sparse (tridiagonal) matrices. The resulting PS-generated algorithms are initially developed and tested for 1-D vibrational eigenproblems, before solution of multidimensional problems is demonstrated; we find that our new PS-generated algorithms can reduce calculation times for grid-based eigenvector computation by an order of magnitude or more. More generally, with further development and optimization, we anticipate that PS-generated algorithms based on effective Hamiltonian approximations, such as those proposed here, could be useful in direct simulations of quantum dynamics via wave function propagation and evaluation of molecular electronic structure. We have recently shown how program synthesis (PS), or the concept of "self-writing code", can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resulting algorithms use a grid-based representation of the underlying wave function ψ( ) and PES ( ), providing codes which represent approximations to standard discrete variable representation (DVR) methods. In this Article, we show how this inductive PS strategy can be improved and modified to enable prediction of both vibrational wave functions energy eigenvalues of representative model PESs (both 1-D and multidimensional). We show that PS can generate algorithms that offer some improvements in energy eigenvalue accuracy over standard DVR schemes; however, we also demonstrate that PS can identify accurate numerical methods that exhibit desirable computational features, such as employing very sparse (tridiagonal) matrices. The resulting PS-generated algorithms are initially developed and tested for 1-D vibrational eigenproblems, before solution of multidimensional problems is demonstrated; we find that our new PS-generated algorithms can reduce calculation times for grid-based eigenvector computation by an order of magnitude or more. More generally, with further development and optimization, we anticipate that PS-generated algorithms based on effective Hamiltonian approximations, such as those proposed here, could be useful in direct simulations of quantum dynamics via wave function propagation and evaluation of molecular electronic structure. We have recently shown how program synthesis (PS), or the concept of "self-writing code", can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resulting algorithms use a grid-based representation of the underlying wave function ψ(x) and PES V(x), providing codes which represent approximations to standard discrete variable representation (DVR) methods. In this Article, we show how this inductive PS strategy can be improved and modified to enable prediction of both vibrational wave functions and energy eigenvalues of representative model PESs (both 1-D and multidimensional). We show that PS can generate algorithms that offer some improvements in energy eigenvalue accuracy over standard DVR schemes; however, we also demonstrate that PS can identify accurate numerical methods that exhibit desirable computational features, such as employing very sparse (tridiagonal) matrices. The resulting PS-generated algorithms are initially developed and tested for 1-D vibrational eigenproblems, before solution of multidimensional problems is demonstrated; we find that our new PS-generated algorithms can reduce calculation times for grid-based eigenvector computation by an order of magnitude or more. More generally, with further development and optimization, we anticipate that PS-generated algorithms based on effective Hamiltonian approximations, such as those proposed here, could be useful in direct simulations of quantum dynamics via wave function propagation and evaluation of molecular electronic structure.We have recently shown how program synthesis (PS), or the concept of "self-writing code", can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resulting algorithms use a grid-based representation of the underlying wave function ψ(x) and PES V(x), providing codes which represent approximations to standard discrete variable representation (DVR) methods. In this Article, we show how this inductive PS strategy can be improved and modified to enable prediction of both vibrational wave functions and energy eigenvalues of representative model PESs (both 1-D and multidimensional). We show that PS can generate algorithms that offer some improvements in energy eigenvalue accuracy over standard DVR schemes; however, we also demonstrate that PS can identify accurate numerical methods that exhibit desirable computational features, such as employing very sparse (tridiagonal) matrices. The resulting PS-generated algorithms are initially developed and tested for 1-D vibrational eigenproblems, before solution of multidimensional problems is demonstrated; we find that our new PS-generated algorithms can reduce calculation times for grid-based eigenvector computation by an order of magnitude or more. More generally, with further development and optimization, we anticipate that PS-generated algorithms based on effective Hamiltonian approximations, such as those proposed here, could be useful in direct simulations of quantum dynamics via wave function propagation and evaluation of molecular electronic structure. We have recently shown how program synthesis (PS), or the concept of "self-writing code", can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resulting algorithms use a grid-based representation of the underlying wave function ψ(x) and PES V(x), providing codes which represent approximations to standard discrete variable representation (DVR) methods. In this Article, we show how this inductive PS strategy can be improved and modified to enable prediction of both vibrational wave functions and energy eigenvalues of representative model PESs (both 1-D and multidimensional). We show that PS can generate algorithms that offer some improvements in energy eigenvalue accuracy over standard DVR schemes; however, we also demonstrate that PS can identify accurate numerical methods that exhibit desirable computational features, such as employing very sparse (tridiagonal) matrices. The resulting PS-generated algorithms are initially developed and tested for 1-D vibrational eigenproblems, before solution of multidimensional problems is demonstrated; we find that our new PS-generated algorithms can reduce calculation times for grid-based eigenvector computation by an order of magnitude or more. More generally, with further development and optimization, we anticipate that PS-generated algorithms based on effective Hamiltonian approximations, such as those proposed here, could be useful in direct simulations of quantum dynamics via wave function propagation and evaluation of molecular electronic structure. We have recently shown how program synthesis (PS), or the concept of “self-writing code”, can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resulting algorithms use a grid-based representation of the underlying wave function ψ(x) and PES V(x), providing codes which represent approximations to standard discrete variable representation (DVR) methods. In this Article, we show how this inductive PS strategy can be improved and modified to enable prediction of both vibrational wave functions and energy eigenvalues of representative model PESs (both 1-D and multidimensional). We show that PS can generate algorithms that offer some improvements in energy eigenvalue accuracy over standard DVR schemes; however, we also demonstrate that PS can identify accurate numerical methods that exhibit desirable computational features, such as employing very sparse (tridiagonal) matrices. The resulting PS-generated algorithms are initially developed and tested for 1-D vibrational eigenproblems, before solution of multidimensional problems is demonstrated; we find that our new PS-generated algorithms can reduce calculation times for grid-based eigenvector computation by an order of magnitude or more. More generally, with further development and optimization, we anticipate that PS-generated algorithms based on effective Hamiltonian approximations, such as those proposed here, could be useful in direct simulations of quantum dynamics via wave function propagation and evaluation of molecular electronic structure.  | 
    
| Author | Habershon, Scott | 
    
| AuthorAffiliation | Department of Chemistry | 
    
| AuthorAffiliation_xml | – name: Department of Chemistry | 
    
| Author_xml | – sequence: 1 givenname: Scott orcidid: 0000-0001-5932-6011 surname: Habershon fullname: Habershon, Scott email: S.Habershon@warwick.ac.uk  | 
    
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35293216$$D View this record in MEDLINE/PubMed | 
    
| BookMark | eNqNkUtv1DAUhSNURB-wZ4UssWFBBr-TbJBK1QdSJYoKYmndOM6MR4md2knR_Pt6mmmBSiBWtuzvHJ177mG257wzWfaa4AXBlHwAHRdrPeoF1RhjJp5lB0TwKq8klXuPd1LuZ4cxrhPBOGUvsn0maMUokQfZcBX8MkCPrjduXJloI_Ituh4gRIOOu6UPdlz1EbU-oB9wa9DZ5PRovUPgGnTqTFhu0FUwjZ1frUPnwTb5J4imQV8ncOOUzG0_dbAF4svseQtdNK9251H2_ez028lFfvnl_PPJ8WUOrJAir6CmQhghSsK44ZyUNWgsCspIUeFacBCsrRuexihEU4BhTBIjW46hMLJs2FFGZt_JDbD5CV2nhmB7CBtFsNq2p1J7atue2rWXNB9nzTDVvWm0cWOAXzoPVv354-xKLf2tqjCucMmSwbudQfA3k4mj6m3UpuvAGT9FRSXHmMu0h4S-fYKu_RRcqiRRgpKSYLJN9Ob3RI9RHhaYADwDOvgYg2n_Z0r5RKLteL-cNJPt_iV8Pwvvfx7S_hW_Axwg0W0 | 
    
| CitedBy_id | crossref_primary_10_1021_acs_jctc_4c01312 | 
    
| Cites_doi | 10.1063/1.5024869 10.1088/0953-8984/26/18/183001 10.3390/math6010013 10.7551/mitpress/3242.001.0001 10.1038/s41586-020-2649-2 10.1016/j.cplett.2017.01.063 10.3390/molecules26247418 10.1016/S0010-4655(97)00054-4 10.1039/C8SC04228D 10.1088/2632-2153/ab7d30 10.1007/978-3-642-17310-3 10.1002/jcc.24764 10.1038/s41598-021-91035-3 10.1016/0009-2614(92)85330-D 10.1063/1.1560636 10.1002/9783527627400 10.1103/PhysRevLett.108.253002 10.1103/PhysRevB.88.054104 10.1038/s41586-018-0337-2 10.1002/anie.201709686 10.1063/1.462100 10.1038/s41592-020-0772-5 10.1016/0041-5553(67)90144-9 10.1063/5.0062497 10.1103/PhysRevLett.108.058301 10.1016/j.coisb.2017.07.006 10.1039/C9SC02834J 10.1007/BF00175355 10.1063/1.445574 10.1063/1.465576 10.1021/acs.jpca.0c06125 10.1098/rsta.2015.0403 10.1145/2863701 10.1063/1.3617249 10.1021/acs.jctc.7b00507 10.1063/5.0032362 10.1007/s10462-009-9108-7 10.1063/1.4964902 10.1021/acs.jctc.7b00021 10.1063/1.3140272 10.1039/C6CP00415F 10.1016/S0747-7171(85)80010-9 10.1146/annurev-physchem-042018-052331 10.1021/acs.accounts.1c00665 10.1021/acs.jctc.8b00819 10.1038/s41929-018-0056-y 10.1063/1.3077130 10.1063/1.1863935 10.1039/D0SC05765G 10.1063/5.0006498 10.1016/S0370-1573(99)00047-2 10.1021/acs.jpclett.9b03664 10.1063/1.448462 10.1063/1.451245 10.1038/s41597-020-0460-4 10.1007/3-540-45307-5_21  | 
    
| ContentType | Journal Article | 
    
| Copyright | 2022 American Chemical Society Copyright American Chemical Society Apr 12, 2022 2022 American Chemical Society 2022 American Chemical Society  | 
    
| Copyright_xml | – notice: 2022 American Chemical Society – notice: Copyright American Chemical Society Apr 12, 2022 – notice: 2022 American Chemical Society 2022 American Chemical Society  | 
    
| DBID | AAYXX CITATION NPM 7SC 7SR 7U5 8BQ 8FD JG9 JQ2 L7M L~C L~D 7X8 5PM ADTOC UNPAY  | 
    
| DOI | 10.1021/acs.jctc.2c00035 | 
    
| DatabaseName | CrossRef PubMed Computer and Information Systems Abstracts Engineered Materials Abstracts Solid State and Superconductivity Abstracts METADEX Technology Research Database Materials Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts  Academic Computer and Information Systems Abstracts Professional MEDLINE - Academic PubMed Central (Full Participant titles) Unpaywall for CDI: Periodical Content Unpaywall  | 
    
| DatabaseTitle | CrossRef PubMed Materials Research Database Engineered Materials Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest Computer Science Collection Computer and Information Systems Abstracts Solid State and Superconductivity Abstracts Advanced Technologies Database with Aerospace METADEX Computer and Information Systems Abstracts Professional MEDLINE - Academic  | 
    
| DatabaseTitleList | PubMed MEDLINE - Academic Materials Research Database  | 
    
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: UNPAY name: Unpaywall url: https://proxy.k.utb.cz/login?url=https://unpaywall.org/ sourceTypes: Open Access Repository  | 
    
| DeliveryMethod | fulltext_linktorsrc | 
    
| Discipline | Chemistry | 
    
| EISSN | 1549-9626 | 
    
| EndPage | 2478 | 
    
| ExternalDocumentID | 10.1021/acs.jctc.2c00035 PMC9009083 35293216 10_1021_acs_jctc_2c00035 a815908256  | 
    
| Genre | Journal Article | 
    
| GroupedDBID | 4.4 53G 55A 5GY 5VS 7~N AABXI ABFRP ABMVS ABUCX ACGFS ACIWK ACS AEESW AENEX AFEFF AHGAQ ALMA_UNASSIGNED_HOLDINGS AQSVZ CS3 D0L DU5 EBS ED F5P GGK GNL IH9 J9A JG P2P RNS ROL UI2 VF5 VG9 W1F AAYXX ABBLG ABJNI ABLBI ABQRX ADHLV BAANH CITATION CUPRZ ED~ JG~ NPM 7SC 7SR 7U5 8BQ 8FD JG9 JQ2 L7M L~C L~D 7X8 5PM ADTOC EJD IHE LG6 UNPAY  | 
    
| ID | FETCH-LOGICAL-a3765-9ab255e558134e4418bac057231790b54a53fbd493275d7ae3361e6f40a7e68d3 | 
    
| IEDL.DBID | UNPAY | 
    
| ISSN | 1549-9618 1549-9626  | 
    
| IngestDate | Sun Oct 26 04:14:56 EDT 2025 Tue Sep 30 16:07:14 EDT 2025 Wed Oct 01 14:08:21 EDT 2025 Mon Jun 30 13:08:11 EDT 2025 Thu Jan 02 22:54:08 EST 2025 Tue Jul 01 02:03:24 EDT 2025 Thu Apr 24 23:04:12 EDT 2025 Fri Apr 15 03:57:32 EDT 2022  | 
    
| IsDoiOpenAccess | true | 
    
| IsOpenAccess | true | 
    
| IsPeerReviewed | true | 
    
| IsScholarly | true | 
    
| Issue | 4 | 
    
| Language | English | 
    
| License | https://creativecommons.org/licenses/by/4.0 Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). cc-by  | 
    
| LinkModel | DirectLink | 
    
| MergedId | FETCHMERGED-LOGICAL-a3765-9ab255e558134e4418bac057231790b54a53fbd493275d7ae3361e6f40a7e68d3 | 
    
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23  | 
    
| ORCID | 0000-0001-5932-6011 | 
    
| OpenAccessLink | https://proxy.k.utb.cz/login?url=https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.2c00035 | 
    
| PMID | 35293216 | 
    
| PQID | 2652181015 | 
    
| PQPubID | 2048741 | 
    
| PageCount | 17 | 
    
| ParticipantIDs | unpaywall_primary_10_1021_acs_jctc_2c00035 pubmedcentral_primary_oai_pubmedcentral_nih_gov_9009083 proquest_miscellaneous_2640046033 proquest_journals_2652181015 pubmed_primary_35293216 crossref_primary_10_1021_acs_jctc_2c00035 crossref_citationtrail_10_1021_acs_jctc_2c00035 acs_journals_10_1021_acs_jctc_2c00035  | 
    
| ProviderPackageCode | CITATION AAYXX  | 
    
| PublicationCentury | 2000 | 
    
| PublicationDate | 2022-04-12 | 
    
| PublicationDateYYYYMMDD | 2022-04-12 | 
    
| PublicationDate_xml | – month: 04 year: 2022 text: 2022-04-12 day: 12  | 
    
| PublicationDecade | 2020 | 
    
| PublicationPlace | United States | 
    
| PublicationPlace_xml | – name: United States – name: Washington  | 
    
| PublicationTitle | Journal of chemical theory and computation | 
    
| PublicationTitleAlternate | J. Chem. Theory Comput | 
    
| PublicationYear | 2022 | 
    
| Publisher | American Chemical Society | 
    
| Publisher_xml | – name: American Chemical Society | 
    
| References | ref9/cit9 Poli R. (ref44/cit44) 2008 ref45/cit45 ref3/cit3 ref27/cit27 ref63/cit63 ref56/cit56 Press W. H. (ref42/cit42) 1992 ref16/cit16 Tannor D. J. (ref35/cit35) 2007 ref52/cit52 Miller J. F. (ref7/cit7) 2011 ref23/cit23 ref8/cit8 ref59/cit59 ref2/cit2 ref34/cit34 ref37/cit37 ref20/cit20 ref48/cit48 ref60/cit60 ref17/cit17 ref10/cit10 ref53/cit53 ref19/cit19 ref21/cit21 ref46/cit46 ref49/cit49 ref13/cit13 Koza J. R. (ref6/cit6) 1992 ref24/cit24 ref38/cit38 Meyer H.-D. (ref61/cit61) 2009 ref50/cit50 ref54/cit54 ref36/cit36 ref18/cit18 ref11/cit11 ref25/cit25 ref29/cit29 Koza J. R. (ref43/cit43) 1996 ref32/cit32 ref39/cit39 ref14/cit14 ref57/cit57 ref5/cit5 ref51/cit51 ref28/cit28 ref40/cit40 ref26/cit26 ref55/cit55 ref12/cit12 ref15/cit15 ref62/cit62 ref41/cit41 ref58/cit58 ref22/cit22 ref33/cit33 ref4/cit4 ref30/cit30 ref47/cit47 ref1/cit1 Koza J. R. (ref31/cit31) 1994; 17  | 
    
| References_xml | – ident: ref52/cit52 doi: 10.1063/1.5024869 – ident: ref10/cit10 doi: 10.1088/0953-8984/26/18/183001 – ident: ref46/cit46 doi: 10.3390/math6010013 – start-page: 132 volume-title: Genetic Programming 1996: Proceedings of the First Annual Conference year: 1996 ident: ref43/cit43 doi: 10.7551/mitpress/3242.001.0001 – ident: ref45/cit45 doi: 10.1038/s41586-020-2649-2 – ident: ref51/cit51 doi: 10.1016/j.cplett.2017.01.063 – ident: ref56/cit56 doi: 10.3390/molecules26247418 – volume-title: A Field Guide to Genetic Programming year: 2008 ident: ref44/cit44 – ident: ref14/cit14 doi: 10.1016/S0010-4655(97)00054-4 – ident: ref17/cit17 doi: 10.1039/C8SC04228D – ident: ref58/cit58 – ident: ref26/cit26 doi: 10.1088/2632-2153/ab7d30 – volume: 17 volume-title: Genetic Programming II year: 1994 ident: ref31/cit31 – volume-title: Cartesian Genetic Programming year: 2011 ident: ref7/cit7 doi: 10.1007/978-3-642-17310-3 – ident: ref13/cit13 doi: 10.1002/jcc.24764 – ident: ref8/cit8 doi: 10.1038/s41598-021-91035-3 – ident: ref41/cit41 doi: 10.1016/0009-2614(92)85330-D – ident: ref60/cit60 doi: 10.1063/1.1560636 – volume-title: Multidimensional quantum dynamics: MCTDH theory and applications year: 2009 ident: ref61/cit61 doi: 10.1002/9783527627400 – ident: ref29/cit29 doi: 10.1103/PhysRevLett.108.253002 – ident: ref27/cit27 doi: 10.1103/PhysRevB.88.054104 – ident: ref11/cit11 doi: 10.1038/s41586-018-0337-2 – ident: ref12/cit12 doi: 10.1002/anie.201709686 – ident: ref34/cit34 doi: 10.1063/1.462100 – ident: ref57/cit57 doi: 10.1038/s41592-020-0772-5 – ident: ref63/cit63 doi: 10.1016/0041-5553(67)90144-9 – ident: ref33/cit33 doi: 10.1063/5.0062497 – ident: ref28/cit28 doi: 10.1103/PhysRevLett.108.058301 – ident: ref4/cit4 doi: 10.1016/j.coisb.2017.07.006 – ident: ref16/cit16 doi: 10.1039/C9SC02834J – ident: ref30/cit30 doi: 10.1007/BF00175355 – ident: ref36/cit36 doi: 10.1063/1.445574 – ident: ref39/cit39 doi: 10.1063/1.465576 – volume-title: SIntroduction to Quantum Mechanics: A Time-Dependent Perspective year: 2007 ident: ref35/cit35 – ident: ref54/cit54 doi: 10.1021/acs.jpca.0c06125 – ident: ref3/cit3 doi: 10.1098/rsta.2015.0403 – ident: ref9/cit9 doi: 10.1145/2863701 – ident: ref49/cit49 doi: 10.1063/1.3617249 – ident: ref32/cit32 – ident: ref19/cit19 doi: 10.1021/acs.jctc.7b00507 – ident: ref21/cit21 doi: 10.1063/5.0032362 – ident: ref5/cit5 doi: 10.1007/s10462-009-9108-7 – ident: ref50/cit50 doi: 10.1063/1.4964902 – ident: ref59/cit59 doi: 10.1021/acs.jctc.7b00021 – ident: ref48/cit48 doi: 10.1063/1.3140272 – ident: ref15/cit15 doi: 10.1039/C6CP00415F – ident: ref2/cit2 doi: 10.1016/S0747-7171(85)80010-9 – ident: ref22/cit22 doi: 10.1146/annurev-physchem-042018-052331 – ident: ref55/cit55 doi: 10.1021/acs.accounts.1c00665 – ident: ref53/cit53 doi: 10.1021/acs.jctc.8b00819 – volume-title: Genetic Programming: On the Programming of Computers by Means of Natural Selection year: 1992 ident: ref6/cit6 – volume-title: Numerical Recipes in Fortran 77: The Art of Scientific Computing year: 1992 ident: ref42/cit42 – ident: ref25/cit25 doi: 10.1038/s41929-018-0056-y – ident: ref40/cit40 doi: 10.1063/1.3077130 – ident: ref47/cit47 doi: 10.1063/1.1863935 – ident: ref18/cit18 doi: 10.1039/D0SC05765G – ident: ref20/cit20 doi: 10.1063/5.0006498 – ident: ref62/cit62 doi: 10.1016/S0370-1573(99)00047-2 – ident: ref23/cit23 doi: 10.1021/acs.jpclett.9b03664 – ident: ref37/cit37 doi: 10.1063/1.448462 – ident: ref38/cit38 doi: 10.1063/1.451245 – ident: ref24/cit24 doi: 10.1038/s41597-020-0460-4 – ident: ref1/cit1 doi: 10.1007/3-540-45307-5_21  | 
    
| SSID | ssj0033423 | 
    
| Score | 2.384113 | 
    
| Snippet | We have recently shown how program synthesis (PS), or the concept of “self-writing code”, can generate novel algorithms that solve the vibrational Schrödinger... We have recently shown how program synthesis (PS), or the concept of "self-writing code", can generate novel algorithms that solve the vibrational Schrödinger... We have recently shown how program synthesis (PS), or the concept of “self-writing code”, can generate novel algorithms that solve the vibrational Schrödinger...  | 
    
| SourceID | unpaywall pubmedcentral proquest pubmed crossref acs  | 
    
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher  | 
    
| StartPage | 2462 | 
    
| SubjectTerms | Algorithms Approximation Digital video recorders Eigenvalues Eigenvectors Electronic structure Mathematical analysis Molecular structure Numerical methods Optimization Potential energy Representations Schrodinger equation Spectroscopy and Excited States Synthesis Wave functions Wave propagation  | 
    
| SummonAdditionalLinks | – databaseName: ACS Publications dbid: ACS link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3db9MwELdgPIwXGN-BgYwEDyClaxI7jh9LtTIhgYbKxN6i80dZti6tmgY0_vqdnTSjFI29RY7txOez72fd-XeEvEn6Co2SlKEGBiEDIcNMMRWaDB-ZElpH7oLz5y_pwRH7dMyPr2hy_vbgx9Ee6Kp3qh3doPZ-r9vkTpwK4cL3BsPxatdNHJOd50ZljnEyylqX5L96cIZIV-uGaANdbgZJbtflHC5-wXT6hwUa3W9SGVWeuNAFnpz16qXq6d-btI43GNwOudcCUTpoNOcBuWXLh2R7uMr_9ojMD5vQLTq-KBElVkVFZxM6nuNJ2NLB9MdsUSxPziuKqJd-h5-WjtBEummmUBq67-8U0sOFcwT50qKkHxeFCT-g3TT0a41TWmPnxXmbQKx6TI5G-9-GB2GbnyEE3JZ4KEHhgcRynkUJs4irMgUa8R9CRiH7ijPgyUQZhhBRcCPAJkka2XTC-iBsmpnkCdkqZ6V9RihPpZBYKowEtJAGDDMpi2LoZwBcy4C8RVHl7fqqcu86j6PcF6L88lZ-AdlbTWquW5Jzl2tjek2Ld12LeUPwcU3d3ZWeXP1KnHIHkxBWBeR19xrnynleoLSz2tVh_pZukgTkaaNW3ccQAaOAojQgYk3hugqOAHz9TVmceCJwiQAZIXRA3neq-d8xPL-hJF-Qu7G76eFpLXfJ1nJR25eIv5bqlV94l_j8K_s priority: 102 providerName: American Chemical Society  | 
    
| Title | Program Synthesis of Sparse Algorithms for Wave Function and Energy Prediction in Grid-Based Quantum Simulations | 
    
| URI | http://dx.doi.org/10.1021/acs.jctc.2c00035 https://www.ncbi.nlm.nih.gov/pubmed/35293216 https://www.proquest.com/docview/2652181015 https://www.proquest.com/docview/2640046033 https://pubmed.ncbi.nlm.nih.gov/PMC9009083 https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.2c00035  | 
    
| UnpaywallVersion | publishedVersion | 
    
| Volume | 18 | 
    
| hasFullText | 1 | 
    
| inHoldings | 1 | 
    
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVABC databaseName: American Chemical Society Journals customDbUrl: eissn: 1549-9626 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0033423 issn: 1549-9626 databaseCode: ACS dateStart: 20050101 isFulltext: true titleUrlDefault: https://pubs.acs.org/action/showPublications?display=journals providerName: American Chemical Society  | 
    
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9NAEB6V9FAuvCmGUi0SHEByG9u7tvcYooYKiSooBMrJ2leoIXWsOAaVX8_sxjaEoqLerNmH9zHr-daz8y3A86gv0Shx7itBhU9Fwv1UUunrFB-pTJQKbIDzu5P4eErfnrLTLWBtLAw2osKaKufEt6u61LOGYSA4tPKvyjIPKucCuwHbMUMI3oPt6cl48Nlxo1LLOOn-6zXPYeue_FcV1iipatMoXUKalw9M7tRFKS5-iPn8D2s0ug0fu364QyjfDuqVPFA__6J4vHZH78CtBp-SwVqh7sKWKe7BzrC9Fu4-lOP1iS4yuSgQPFZ5RRYzMilxg2zIYP5lscxXZ-cVQTBMPonvhozQctrZJ6LQ5MiFGpLx0vqHnDQvyJtlrv3XaE41eV_jTNdYeX7e3CtWPYDp6OjD8Nhvrm3wBX6tmM-FxH2KYSwNImoQbqVSKISFiCQT3peMChbNpKaIHBOmE2GiKA5MPKN9kZg41dFD6BWLwjwCwmKecJQmmgs0nFpoqmMahKKfCsEU9-AFDlXWLLsqcx71MMicEMcva8bPg8N2fjPVcJ_bKzjmV5R42ZUo17wfV-Tda1Xmd1PCmFn0hGjLg2ddMs6VdciIwixqm4e64N0o8mB3rWHdyxAY4wAFsQfJhu51GSwv-GZKkZ85fnCOuBmRtQevOi39bx8eXyfzE7gZ2igQR3m5B73VsjZPEZut5D7uTYaT_WY9_gLg7Tgh | 
    
| linkProvider | Unpaywall | 
    
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3db9MwED-N8VBexjcEBhgJHkDK1jR2Ej-WaqXANg26ib1F_uqWrUurpgFtf_3ObpJRhga8RY7t2Hfn3M86388Ab8K2RKfEua8EFT4VMfcTSaWvE3ykMlYqsAnOO7vR4IB-PmSHKxDUuTA4iAJ7KlwQ_4pdINi0ZSfKsg4qF_66BbdZRAO73-r2hvXPN7SEdo4ilVriySCpIpN_6sH6I1Us-6NrIPP6WclWmU_F-U8xHv_iiPp34VszBXf-5HSjnMsNdfEbu-N_zfEerFWwlHQXdnQfVkz-AFq9-ja4hzDdWxzkIsPzHDFjkRVkMiLDKe6LDemOjyazbH58VhDEwOS7-GFIHx2mVToRuSZbLsOQ7M1sWMiVZjn5OMu0_wG9qCZfS1RwiZ1nZ9V1YsUjOOhv7fcGfnVbgy_wJ8V8LiRuTwxjSRBSgygrkUIhGkQAGfO2ZFSwcCQ1RcAYMx0LE4ZRYKIRbYvYRIkOH8NqPsnNUyAs4jHH0lhzgf5SC0016roj2okQTHEP3qKo0mq1FakLpHeC1BWi_NJKfh5s1rpNVUV5bm_eGN_Q4l3TYrqg-7ih7nptLldD6UTMgiYEWR68bl6jrmwcRuRmUto61OXshqEHTxbW1XwM8TAKKIg8iJfsrqlg6cCX3-TZsaMF5wiXEVB78L6x0L_O4dk_SvIVtAb7O9vp9qfdL8_hTsfmgDjCy3VYnc9K8wKR2Vy-dGvxErrqNF0 | 
    
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1bb9MwFD4aQ2K8cL8EBhgJHkDK1jS2Ez-OsjJuU1EZ7C3yrSzQpVHTgMav59hNAmVowFvkW-zjY5_POj6fAR7FPYVGSYhQSypDKhMRpoqq0KT4SVWideQCnN_u870D-uqQHa4Ba2NhsBMVtlR5J75b1aWZNAwD0bZL_6wd86D2LrBzcJ5xXOkOEQ3G7QYcO1I7T5NKHflklDbeyT-14GySrlZt0imgefq-5EZdlPLkm5xOfzFGw8vwoRuGv4PyZateqC39_TeGx_8e5xW41MBTsrPUp6uwZotrsDFoX4W7DuVoeaGLjE8KxI5VXpHZhIxLPB9bsjP9NJvni6PjiiAWJh_lV0uGaDjd5BNZGLLrIw3JaO7cQz41L8iLeW7CZ2hNDXlX40TX2Hh-3DwrVt2Ag-Hu-8Fe2LzaEErcrFgopMJjimUsjWJqEW2lSmpEhQgkE9FTjEoWT5ShCBwTZhJp45hHlk9oTyaWpya-CevFrLC3gTAuEoGpiRES7aaRhhpOo77spVIyLQJ4jKLKmlVXZd6h3o8yn4jyyxr5BbDdzm-mG-pz9wLH9IwaT7oa5ZL244yym63K_OxKnzMHnhBsBfCwy8a5cv4YWdhZ7cpQH7sbxwHcWmpY9zPExSigiAeQrOheV8DRgq_mFPmRpwcXCJsRWAfwtNPSv47hzj9K8gFcGD0fZm9e7r--Cxf7LhTE815uwvpiXtt7CNAW6r5fjj8AixY24A | 
    
| linkToUnpaywall | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB6V7aFcypsGSmUkOICUdpPYSXxcqi4VEtWislBOkV9L026z0WYDKr-esTdJWYqKeovGj_gxznzOeD4DvIr6Eo0S574SVPhUJNxPJZW-TvGRykSpwAY4fzyKD8f0wwk7WQPWxsJgIyqsqXJOfLuqSz1pGAaCPSs_U5Z5UDkX2B1YjxlC8B6sj49Gg2-OG5Vaxkn3X695Dlv35L-qsEZJVatG6RrSvH5gcqMuSnH5U0ynf1ij4T340vXDHUI5360Xclf9-ovi8dYdvQ-bDT4lg6VCPYA1UzyEjf32WrhHUI6WJ7rI8WWB4LHKKzKbkOMSN8iGDKbfZ_N8cXpREQTD5Kv4YcgQLaedfSIKTQ5cqCEZza1_yEnzgryf59p_h-ZUk081znSNlecXzb1i1WMYDw8-7x_6zbUNvsCvFfO5kLhPMYylQUQNwq1UCoWwEJFkwvuSUcGiidQUkWPCdCJMFMWBiSe0LxITpzp6Ar1iVpgtICzmCUdporlAw6mFpjqmQSj6qRBMcQ9e41BlzbKrMudRD4PMCXH8smb8PNhr5zdTDfe5vYJjekOJN12Jcsn7cUPe7VZlrpoSxsyiJ0RbHrzsknGurENGFGZW2zzUBe9GkQdPlxrWvQyBMQ5QEHuQrOhel8Hygq-mFPmp4wfniJsRWXvwttPS__bh2W0yP4e7oY0CcZSX29BbzGvzArHZQu40K_E3lew3KQ | 
    
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Program+Synthesis+of+Sparse+Algorithms+for+Wave+Function+and+Energy+Prediction+in+Grid-Based+Quantum+Simulations&rft.jtitle=Journal+of+chemical+theory+and+computation&rft.au=Habershon%2C+Scott&rft.date=2022-04-12&rft.issn=1549-9626&rft.eissn=1549-9626&rft.volume=18&rft.issue=4&rft.spage=2462&rft_id=info:doi/10.1021%2Facs.jctc.2c00035&rft.externalDBID=NO_FULL_TEXT | 
    
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1549-9618&client=summon | 
    
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1549-9618&client=summon | 
    
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1549-9618&client=summon |