Paper Citation Record · LEDGER

Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2404.09452.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2404.09452 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:01:22.958087Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T07:39:38.810888Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4448fc44-c3d9-4699-ad84-78ba83d13b80 · inbound

OpenMM-Python-Force: Deploying Accelerated Python Modules in Molecular Dynamics Simulation cites this paper.

OpenMM-Python-Force: Deploying Accelerated Python Modules in Molecular Dynamics Simulation Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T04:53:32.034955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c239378-e9f7-41db-abf3-117fe5bf71bb · inbound

Enabling Multireference Calculations on Multi-Metallic Systems with Graphic Processing Units cites this paper.

Enabling Multireference Calculations on Multi-Metallic Systems with Graphic Processing Units Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-16T12:01:22.958087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9dad0f0-add0-47f2-b95e-f3aa3f31c905 · inbound

HORM: A Large Scale Molecular Hessian Database for Optimizing Reactive Machine Learning Interatomic Potentials cites this paper.

HORM: A Large Scale Molecular Hessian Database for Optimizing Reactive Machine Learning Interatomic Potentials Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T20:38:46.876671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0d9493d-444d-48ca-a126-a0acc2db5dc6 · inbound

Machine Learning Hamiltonians are Accurate Energy-Force Predictors cites this paper.

Machine Learning Hamiltonians are Accurate Energy-Force Predictors Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework

Reference 2005

Resolution: malformed identifier; no resolver link, observed 2026-08-02T22:29:23.780693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12cc47e8-1859-424a-9ca2-caeeec48cf2f · inbound

TDDFT Gradients and Nonadiabatic Couplings with Minimal Auxiliary Basis Set Approximation for Fewest-Switches Surface Hopping Dynamics cites this paper.

TDDFT Gradients and Nonadiabatic Couplings with Minimal Auxiliary Basis Set Approximation for Fewest-Switches Surface Hopping Dynamics Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:30.166760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 423b8d87-8567-4866-96c6-bbf753767496 · inbound

A Unified Generative Framework for Scalable Chemical Reaction Network Exploration cites this paper.

A Unified Generative Framework for Scalable Chemical Reaction Network Exploration Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:39:38.812470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.