{"id":"https://openalex.org/W7212007768","doi":"https://doi.org/10.48550/arxiv.2609.05904","title":"Boundary-Canceled Score-Hamiltonian Sampling","display_name":"Boundary-Canceled Score-Hamiltonian Sampling","publication_year":2026,"publication_date":"2026-09-05","ids":{"openalex":"https://openalex.org/W7212007768","doi":"https://doi.org/10.48550/arxiv.2609.05904"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.05904","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.05904","pdf_url":"https://arxiv.org/pdf/2609.05904","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.05904","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035163865","display_name":"Masayuki Ohzeki","orcid":"https://orcid.org/0000-0001-9151-2914","observed_orcids":["https://orcid.org/0000-0001-9151-2914"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ohzeki, Masayuki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5035163865"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9887999892234802,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9887999892234802,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.00139999995008111,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0006000000284984708,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/diffusive-sampling","display_name":"diffusion sampling","score":0.8140000104904175},{"id":"https://openalex.org/keywords/hellinger-distance","display_name":"Hellinger distance","score":0.7710000276565552},{"id":"https://openalex.org/keywords/schrodinger-equation","display_name":"Schr\u00f6dinger equation","score":0.6079999804496765}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6796000003814697},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5891000032424927},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.5530999898910522},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.478300005197525},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4268999993801117},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38339999318122864},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.3693999946117401},{"id":"https://openalex.org/C153024298","wikidata":"https://www.wikidata.org/wiki/Q3030678","display_name":"Hellinger distance","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.3490999937057495},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.3379000127315521},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.33009999990463257},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30880001187324524},{"id":"https://openalex.org/C75438885","wikidata":"https://www.wikidata.org/wiki/Q3403615","display_name":"Large deviations theory","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C130787639","wikidata":"https://www.wikidata.org/wiki/Q5645293","display_name":"Hamiltonian (control theory)","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.2621000111103058},{"id":"https://openalex.org/C128747166","wikidata":"https://www.wikidata.org/wiki/Q7881414","display_name":"Umbrella sampling","level":3,"score":0.26030001044273376},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C2777317252","wikidata":"https://www.wikidata.org/wiki/Q18393516","display_name":"Rare events","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C18747219","wikidata":"https://www.wikidata.org/wiki/Q620994","display_name":"Standard error","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.05904","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.05904","pdf_url":"https://arxiv.org/pdf/2609.05904","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.05904","doi":"https://doi.org/10.48550/arxiv.2609.05904","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.05904","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.05904","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.05904","pdf_url":"https://arxiv.org/pdf/2609.05904","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7212007768.pdf","grobid_xml":"https://content.openalex.org/works/W7212007768.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W7133193464","https://openalex.org/W7133244780","https://openalex.org/W7163696952","https://openalex.org/W7168267961"],"related_works":["https://openalex.org/W7163696952","https://openalex.org/W7118999563","https://openalex.org/W7167733924","https://openalex.org/W7167904967","https://openalex.org/W7221076341","https://openalex.org/W7125783481","https://openalex.org/W7223083882","https://openalex.org/W4296957262","https://openalex.org/W4399401039","https://openalex.org/W4378508771"],"abstract_inverted_index":{"Diffusion":[0],"sampling":[1],"is":[2],"related":[3],"to":[4,41],"imaginary-time":[5,80],"quantum":[6],"annealing":[7],"through":[8],"a":[9,20,48,67],"forward/backward":[10],"Schr\u00f6dinger":[11],"equation":[12],"pair":[13],"and":[14,75,90],"its":[15],"one-sided":[16],"counterdiabatic":[17],"connection.":[18],"For":[19],"smooth,":[21],"gapped":[22],"Score-Hamiltonian":[23],"path,":[24],"the":[25,29,52,59,71,97,106],"exact":[26],"connection":[27,46],"transports":[28],"target":[30],"density":[31],"at":[32],"any":[33],"evolution":[34,81],"time.":[35],"We":[36],"apply":[37],"quantum-annealing":[38],"performance":[39],"analysis":[40],"residuals":[42],"from":[43],"approximating":[44],"this":[45],"with":[47,66,82],"trained":[49],"score.":[50],"If":[51],"first":[53],"$r$":[54],"terminal":[55,72],"schedule":[56,93],"derivatives":[57],"vanish,":[58],"squared":[60],"Hellinger":[61],"error":[62],"scales":[63],"as":[64],"$T^{-2r-2}$,":[65],"prefactor":[68],"determined":[69],"by":[70],"learning":[73,103],"residual":[74],"inverse":[76],"gaps.":[77],"Direct":[78],"two-dimensional":[79],"one":[83],"fixed":[84],"neural":[85],"score":[86,102],"reproduces":[87],"these":[88],"powers":[89],"prefactors.":[91],"Terminal":[92],"design":[94],"thus":[95],"suppresses":[96],"distributional":[98],"effect":[99],"of":[100],"imperfect":[101],"without":[104],"retraining":[105],"network.":[107]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-09-10T00:00:00"}