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A Novel Causal Method to Blend the DC and AC Solution over the Entire Frequency Band

2024· article· en· W4401110963 on OpenAlexaff
Peng Liu, W. Thiel, Xiangjun Xin, Kevin Zhu, Eric Bracken

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsAnsys (Canada)
Fundersnot available
KeywordsMaterials scienceComputer scienceElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

This paper proposes a novel DC correction method to correct the inaccurate low-frequency S-parameters obtained from an electromagnetic simulator so that S-parameters have an exact DC-point and the electromagnetic transient analysis using the S-parameters is accurate and reliable in signal integrity, power integrity, and power electronics applications. The new method can correct the low-frequency region of S-parameters to the given reference DC-point by adding a causal and rational correction function over the entire frequency band. The method ensures that the corrected S-parameters have a precise DC-point while preserving the original AC solution's causality, passivity, and high-frequency accuracy.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.276
Teacher spread0.267 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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