MétaCan
Menu
Back to cohort
Record W1997589253 · doi:10.1142/s0218126611007797

A NOVEL REVERSIBLE ZS GATE AND ITS APPLICATION FOR OPTIMIZATION OF QUANTUM ADDER CIRCUITS

2011· article· en· W1997589253 on OpenAlexaff
Ri‐Gui Zhou, Yang Shi, Manqun Zhang, Hui’an Wang

Bibliographic record

VenueJournal of Circuits Systems and Computers · 2011
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsCarleton University
Fundersnot available
KeywordsAdderCarry (investment)Computer scienceCarry-save adderArithmeticLogic gateElectronic circuitQuantumQuantum circuitToffoli gateQuantum computerQuantum gateMathematicsAlgorithmQuantum error correctionPhysicsQuantum mechanicsTelecommunications

Abstract

fetched live from OpenAlex

The key of optimizing quantum reversible logic lies in automatically constructing quantum reversible logic circuits with the minimal quantum cost. This paper constructs a 4 × 4 reversible gate called ZS gate to build quantum full adder. At the same time, a novel reversible No-Wait-Carry adder (or carry skip adder) by using ZSCGPD based on ZS gate with the least cost is also designed. The adder circuit using the proposed ZSCGPD is much better and optimized than other researchers' counterparts both in terms of garbage outputs, number and kind of reversible gates, and quantum cost. In order to show the efficiency of the proposed designs, lower bounds of the reversible carry skip adder in terms of garbage outputs and quantum cost are proposed as well.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.026
GPT teacher head0.226
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations13
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Circuits Systems and ComputersSame topicQuantum Computing Algorithms and ArchitectureFrench-language works237,207