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Record W4416748690 · doi:10.1039/d5dd00377f

Chemically motivated simulation problems are efficiently solvable on a quantum computer

2025· article· en· W4416748690 on OpenAlex
Philipp Schleich, Lasse Bjørn Kristensen, J. M. Angulo, Abdulrahman Aldossary, Davide Avagliano, Mohsen Bagherimehrab, Christoph Gorgulla, Joe Fitzsimons, Alán Aspuru‐Guzik

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDigital Discovery · 2025
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsVector InstituteUniversity of Toronto
FundersOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaU.S. NavyDefense Advanced Research Projects AgencyCanadian Institute for Advanced ResearchNovo Nordisk FondenKing Abdullah University of Science and TechnologyU.S. Department of DefenseCarlsbergfondetNational Institute of Advanced Industrial Science and TechnologyAdvanced Research Projects AgencyGovernment of CanadaNovo Nordisk
KeywordsQuantum computerQuantumQuantum chemicalScatteringQuantum systemQuantum algorithmScheme (mathematics)

Abstract

fetched live from OpenAlex

Preparing molecular states for chemical simulations by circumventing the need for ground-state preparation through scattering constituents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.639
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.224
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it