23 citations · 28 across the 10 of their papers we have counts for
6 papers · 1 filter
Quantum Processing Unit (QPU) processing time Prediction with Machine Learning
Lucy Xing, Sanjay Vishwakarma, David Kremer +3
This paper explores the application of machine learning (ML) techniques in predicting the QPU processing time of quantum jobs. By leveraging ML algorithms, this study introduces pr…
AI methods for approximate compiling of unitaries
David Kremer, Victor Villar, Sanjay Vishwakarma +2
This paper explores artificial intelligence (AI) methods for the approximate compiling of unitaries, focusing on the use of fixed two-qubit gates and arbitrary single-qubit rotatio…
Qiskit HumanEval: An Evaluation Benchmark For Quantum Code Generative Models
Sanjay Vishwakarma, Francis Harkins, Siddharth Golecha +7
Quantum programs are typically developed using quantum Software Development Kits (SDKs). The rapid advancement of quantum computing necessitates new tools to streamline this develo…
Qiskit Code Assistant: Training LLMs for generating Quantum Computing Code
Nicolas Dupuis, Luca Buratti, Sanjay Vishwakarma +5
Code Large Language Models (Code LLMs) have emerged as powerful tools, revolutionizing the software development landscape by automating the coding process and reducing time and eff…
Introduction to Topological Superconductivity and Majorana Fermions for Quantum Engineers
Sanjay Vishwakarma, Sai Nandan Morapakula, Shalini D +2
In this tutorial paper, we provide an introduction to the briskly expanding research field of Majorana fermions in topological superconductors. We discuss several aspects of topolo…
Efficient VQE Approach for Accurate Simulations on the Kagome Lattice
Jyothikamalesh S, Kaarnika A, Dr. Mohankumar. M +3
The Kagome lattice, a captivating lattice structure composed of interconnected triangles with frustrated magnetic properties, has garnered considerable interest in condensed matter…