48 citations · 60 across the 6 of their papers we have counts for
6 papers
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…
Practical and efficient quantum circuit synthesis and transpiling with Reinforcement Learning
David Kremer, Victor Villar, Hanhee Paik +3
This paper demonstrates the integration of Reinforcement Learning (RL) into quantum transpiling workflows, significantly enhancing the synthesis and routing of quantum circuits. By…
Systematic Literature Review: Quantum Machine Learning and its applications
David Peral García, Juan Cruz-Benito, Francisco José García-Peñalvo
Quantum computing is the process of performing calculations using quantum mechanics. This field studies the quantum behavior of certain subatomic particles for subsequent use in pe…
Automated Source Code Generation and Auto-completion Using Deep Learning: Comparing and Discussing Current Language-Model-Related Approaches
Juan Cruz-Benito, Sanjay Vishwakarma, Francisco Martin-Fernandez +1
In recent years, the use of deep learning in language models gained much attention. Some research projects claim that they can generate text that can be interpreted as human-writin…