{"id":"https://openalex.org/W7153103418","doi":"https://doi.org/10.48550/arxiv.2604.07423","title":"OpenPRC: A Unified Open-Source Framework for Physics-to-Task Evaluation in Physical Reservoir Computing","display_name":"OpenPRC: A Unified Open-Source Framework for Physics-to-Task Evaluation in Physical Reservoir Computing","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7153103418","doi":"https://doi.org/10.48550/arxiv.2604.07423"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.07423","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07423","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.07423","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133374086","display_name":"Yogesh Phalak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Phalak, Yogesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133367941","display_name":"Wen Sin Lor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lor, Wen Sin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034350392","display_name":"Apoorva Khairnar","orcid":"https://orcid.org/0000-0001-7640-865X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khairnar, Apoorva","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061555779","display_name":"Benjamin C. Jantzen","orcid":"https://orcid.org/0000-0001-9040-679X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jantzen, Benjamin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058205547","display_name":"Noel Naughton","orcid":"https://orcid.org/0000-0002-5553-4718"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naughton, Noel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133316988","display_name":"Suyi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Suyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9473999738693237,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9473999738693237,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.028300000354647636,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.006899999920278788,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6359000205993652},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6233999729156494},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.5985000133514404},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.45969998836517334},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.42010000348091125},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.41769999265670776},{"id":"https://openalex.org/keywords/cyberinfrastructure","display_name":"Cyberinfrastructure","score":0.39899998903274536},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.3817000091075897},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.3458000123500824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6654999852180481},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6359000205993652},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6233999729156494},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5985000133514404},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.41769999265670776},{"id":"https://openalex.org/C2776397876","wikidata":"https://www.wikidata.org/wiki/Q1450531","display_name":"Cyberinfrastructure","level":2,"score":0.39899998903274536},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.39489999413490295},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.3458000123500824},{"id":"https://openalex.org/C135796866","wikidata":"https://www.wikidata.org/wiki/Q7315328","display_name":"Reservoir computing","level":4,"score":0.32589998841285706},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.3199999928474426},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C37789001","wikidata":"https://www.wikidata.org/wiki/Q782543","display_name":"Graphical user interface","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C147358964","wikidata":"https://www.wikidata.org/wiki/Q1200992","display_name":"Abstraction layer","level":3,"score":0.2890999913215637},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.2833000123500824},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26989999413490295},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.26019999384880066},{"id":"https://openalex.org/C37785467","wikidata":"https://www.wikidata.org/wiki/Q385325","display_name":"Modelica","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.25600001215934753},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.07423","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07423","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.07423","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07423","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.7593145966529846}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Physical":[0],"Reservoir":[1],"Computing":[2],"(PRC)":[3],"leverages":[4],"the":[5,32,51,82,162,206],"intrinsic":[6],"nonlinear":[7],"dynamics":[8],"of":[9,50,172],"physical":[10,180],"substrates,":[11],"mechanical,":[12],"optical,":[13],"spintronic,":[14],"and":[15,27,37,77,90,95,138,142,152,156,182,192,217],"beyond,":[16],"as":[17,54,201],"fixed":[18],"computational":[19],"reservoirs,":[20],"offering":[21],"a":[22,67,110,118,125,131,179,183,202],"compelling":[23],"paradigm":[24],"for":[25,35,186,205],"energy-efficient":[26],"embodied":[28],"machine":[29],"learning.":[30],"However,":[31],"practical":[33],"workflow":[34,165],"developing":[36],"evaluating":[38],"PRC":[39,188,207],"systems":[40],"remains":[41],"fragmented:":[42],"existing":[43],"tools":[44,140],"typically":[45],"address":[46],"only":[47],"isolated":[48],"parts":[49],"pipeline,":[52],"such":[53],"substrate-specific":[55],"simulation,":[56],"digital":[57],"reservoir":[58],"benchmarking,":[59,189],"or":[60],"readout":[61],"training.":[62],"What":[63],"is":[64,66,198],"missing":[65],"unified":[68],"framework":[69,104],"that":[70,105],"can":[71],"represent":[72],"both":[73],"high-fidelity":[74],"simulated":[75],"trajectories":[76,159],"real":[78],"experimental":[79,127],"measurements":[80],"through":[81,109],"same":[83,163],"data":[84,96],"interface,":[85],"enabling":[86],"reproducible":[87],"evaluation,":[88],"analysis,":[89],"physics-aware":[91,143],"optimization":[92,144],"across":[93],"substrates":[94],"sources.":[97],"We":[98],"present":[99],"OpenPRC,":[100],"an":[101],"open-source":[102],"Python":[103],"fills":[106],"this":[107],"gap":[108],"schema-driven":[111],"physics-to-task":[112],"pipeline":[113],"built":[114],"around":[115],"five":[116],"modules:":[117],"GPU-accelerated":[119],"hybrid":[120],"RK4-PBD":[121],"physics":[122,212],"engine":[123],"(demlat),":[124],"video-based":[126,175],"ingestion":[128],"layer":[129,134,204],"(openprc.vision),":[130],"modular":[132],"learning":[133],"(reservoir),":[135],"information-theoretic":[136],"analysis":[137],"benchmarking":[139],"(analysis),":[141],"(optimize).":[145],"A":[146],"universal":[147],"HDF5":[148],"schema":[149],"enforces":[150],"reproducibility":[151],"interoperability,":[153],"allowing":[154],"GPU-simulated":[155],"experimentally":[157],"acquired":[158],"to":[160,199],"enter":[161],"downstream":[164],"without":[166],"modification.":[167],"Demonstrated":[168],"capabilities":[169],"include":[170],"simulations":[171],"Origami":[173],"tessellations,":[174],"trajectory":[176],"extraction":[177],"from":[178],"reservoir,":[181],"common":[184],"interface":[185],"standardized":[187],"correlation":[190],"diagnostics,":[191],"capacity":[193],"analysis.":[194],"The":[195],"longer-term":[196],"vision":[197],"serve":[200],"standardizing":[203],"community,":[208],"compatible":[209],"with":[210],"external":[211],"engines":[213],"including":[214],"PyBullet,":[215],"PyElastica,":[216],"MERLIN.":[218]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-11T00:00:00"}
