Paper Citation Record · LEDGER

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations

As of 23 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2606.23548.

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

pith.paper-citation-record.v1
2606.23548 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T05:51:20.150462Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

verified exact1
verified fuzzy0
unresolved18
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malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8a42c60-058f-4baa-b77c-c211a5f332c8 · outbound

This paper cites Quench Detection and Protection for High-Temperature Superconductor Accelerator Magnets,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Quench Detection and Protection for High-Temperature Superconductor Accelerator Magnets,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation f290bffd-d7d1-4d24-87d6-9b0b13cdd315 · outbound

This paper cites Digital Twin: Values, Challenges and Enablers From a Modeling Perspective,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Digital Twin: Values, Challenges and Enablers From a Modeling Perspective,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation 31ccbc45-d4c2-45be-8f63-d0aaddb878a4 · outbound

This paper cites An Electric-Circuit Model on the Inter-Tape Contact Resistance and Current Sharing for REBCO Cable and Magnet Applications,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations An Electric-Circuit Model on the Inter-Tape Contact Resistance and Current Sharing for REBCO Cable and Magnet Applications,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation 7d56f434-7cd7-4ee3-9c74-9de35022ed0f · outbound

This paper cites The Current Unbalance in Stacked REBCO Tapes — Simulations Based on a Circuit Grid Model,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations The Current Unbalance in Stacked REBCO Tapes — Simulations Based on a Circuit Grid Model,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation 71fb7700-de77-46ba-9b0d-11f5f67ba9fb · outbound

This paper cites Experimental and Model Based Studies on Current Distribution in Superconducting DC Cables,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Experimental and Model Based Studies on Current Distribution in Superconducting DC Cables,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation bb41473e-e619-4ce8-bdb9-a8b75d94b89c · outbound

This paper cites Effect of variations in terminal contact resistances on the current distribution in high-temperature superconducting cables,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Effect of variations in terminal contact resistances on the current distribution in high-temperature superconducting cables,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74d555d5-8c02-4129-af8c-bd0a445baeb6 · outbound

This paper cites Stability of superconducting cables with twisted stacked YBCO coated conductors,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Stability of superconducting cables with twisted stacked YBCO coated conductors,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation 385c7168-6b53-4da5-8be0-bf51cdc65596 · outbound

This paper cites CUSPICE The revolutionary NGSPICE on CUDA Platforms,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations CUSPICE The revolutionary NGSPICE on CUDA Platforms,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

Source-reported events for the cited work

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Observation b408e6cd-7ed6-42c2-a677-5a4d9cb9c123 · outbound

This paper cites Experimental Investigation of CNN-Based V oltage Prediction for REBCO Pancake Coil Protection,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Experimental Investigation of CNN-Based V oltage Prediction for REBCO Pancake Coil Protection,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation 74d19af0-c11c-4088-8c2f-b215bc9c4e66 · outbound

This paper cites A Weakly Supervised Machine Learning Procedure for Acoustic Emission Quench Diagnostics,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations A Weakly Supervised Machine Learning Procedure for Acoustic Emission Quench Diagnostics,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation acb1efec-f1b8-43ce-b924-426f2d909f78 · outbound

This paper cites A Surrogate model for High Temperature Superconducting Magnets to Predict Current Distribution with Neural Network,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations A Surrogate model for High Temperature Superconducting Magnets to Predict Current Distribution with Neural Network,

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:49:52.851017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1c668f12-5319-4e1f-b47b-5c7791376438 · outbound

This paper cites Numerical investiga- tion of current distributions around defects in high temperature superconducting CORC® cables,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Numerical investiga- tion of current distributions around defects in high temperature superconducting CORC® cables,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation f4ebc3ca-2240-410a-8aa9-f917ea175402 · outbound

This paper cites Graph neural networks at the Large Hadron Collider,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Graph neural networks at the Large Hadron Collider,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation d6942949-2b85-4247-80df-ce7e1b066e44 · outbound

This paper cites Circuit topology aware GNN-based multi-variable model for DC-DC converters dynamics prediction in CCM and DCM,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Circuit topology aware GNN-based multi-variable model for DC-DC converters dynamics prediction in CCM and DCM,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation 6bad09c4-19cf-48f8-b0aa-beb415483d18 · outbound

This paper cites Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Design,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Design,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation fb9dc787-d14f-4b6f-aaf9-247b4ff14233 · outbound

This paper cites Ngspice, the open source Spice circuit simulator - Intro.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Ngspice, the open source Spice circuit simulator - Intro

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Observation 2b40c158-5f3a-45f7-95cd-98f002490ec2 · outbound

This paper cites Experimental Studies on Quench Behavior Mea- surements of HTS Tapes With Various Heater Configurations,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Experimental Studies on Quench Behavior Mea- surements of HTS Tapes With Various Heater Configurations,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Unavailable: canonical work link unavailable.

Observation a87e17bd-1817-4d86-bd22-13a8dd51bb7b · outbound

This paper cites Graph Theory-Based Programmable Topology Derivation of Multiport DC–DC Converters With Reduced Switches,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Graph Theory-Based Programmable Topology Derivation of Multiport DC–DC Converters With Reduced Switches,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c1e7f50-c9b3-4104-b5c8-b3ad11b0507f · outbound

This paper cites Learning Mesh-Based Simulation with Graph Networks.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Learning Mesh-Based Simulation with Graph Networks

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T12:49:52.848594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 157d1725-665f-476e-b2bb-12d7e1d6f16d · outbound

This paper cites Optuna: A Next-generation Hyperparameter Optimization Framework,.

SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations Optuna: A Next-generation Hyperparameter Optimization Framework,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-26T05:51:20.150462Z

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Pith citing papers

No inbound Pith citation observations are available.