0% Complete
Home
/
15th International Conference on Computer and Knowledge Engineering
Minimizing Quantum Overhead: A Fault-Tolerant ALU Design with Reduced T Metrics
Authors :
Sarallah Keshavarz
1
Shekoofeh Moghimi
2
Mohammad Reza Reshadinezhad
3
1- Computer Engineering Department, University of Isfahan, Iran
2- Computer Engineering Department, University of Isfahan, Iran
3- Faculty Member of Computer Engineering Department, University of Isfahan, Iran
Keywords :
Quantum ALU،Fault Tolerant،Clifford+ T Group Gates،T-depth،T-count
Abstract :
Quantum Arithmetic Logic Units (ALUs) serve as critical components in quantum processors, enabling both arithmetic and logical operations on qubits. However, the fragile nature of quantum systems makes them susceptible to errors and decoherence, necessitating fault-tolerant designs. In this work, we propose a fault-tolerant quantum ALU architecture constructed using the Clifford+ T gate set, which is widely recognized for its compatibility with error-correcting codes. The proposed design minimizes quantum resource overhead while maintaining computational accuracy under fault-prone conditions. Notably, the architecture requires zero ancilla and generates a single garbage output, optimizing the qubit space. Performance evaluations demonstrate significant improvements, achieving a 31.8% reduction in T-count and a 33.3% reduction in T-depth compared to existing designs. These enhancements contribute to more efficient and reliable quantum computation, paving the way for scalable quantum processor development.
Papers List
List of archived papers
Emotion Recognition In Persian Speech Using Deep Neural Networks
Ali Yazdani - Hossein Simchi - Yasser Shekofteh
A 2D-CNN Architecture for Improving the Classification Accuracy of an Electronic Nose with Different Sensor Positions
Hannaneh Mahdavi - Reza Goldoust - Saeideh Rahbarpour
Predicting cascading failure with machine learning methods in the interdependent networks
Mohamad Hossein Maghsoodi - Mohamad Khansari
A New Application of Machine Learning Based Methods for Disk Space Variation Fault Diagnosis in Transformer Windings
Reza Behkam - Amir Lotfi - Gevork B. Gharehpetian
BioBERT-based SNP-traits Associations Extraction from Biomedical Literature
Mohammad Dehghani - Behrouz Bokharaeian - Zahra Yazdanparast
Analysis of Address Lifespans in Bitcoin and Ethereum
Amir Mohammad Karimi Mamaghan - Amin Setayesh - Behnam Bahrak
Crack Segmentation in Civil Structure Images Using a Deep Learning Based Multi-Classifier System
Mohammadreza Asadi - Seyedeh Sogand Hashemi - Mohammad Taghi Sadeghi
Evaluation of Efficient Electrocardiomatrix-based Identification Using Deep Learning Methods
Amirhossein Safari - Narges Mokhtari - Mohsen Hooshmand - Sadegh Sadeghi - Peyman Pahlevani
An Attention-Based Model for Clinical Time Series Prediction: Enhancing ICU Readmission Prediction
Hananeh Sadat Madinei - Mohammad Reza Keyvanpour - Seyed Vahab Shojaedini
A Vision-Based Method for Human Activity Recognition Using Local Binary Pattern
Babak Goodarzi - Reza Javidan - Mohammad Sadegh Rezaei
more
Samin Hamayesh - Version 44.5.0