7 citations · 10 across the 12 of their papers we have counts for
12 papers
Aligning Quantum Operators with Large Language Models
Rogerio Feris, Yunchao Liu, Pengyuan Li +2
Can Large Language Models (LLMs) understand and reason about quantum operators? Despite their remarkable capabilities in mathematics and symbolic reasoning, LLMs remain inherently…
Evolutionary Discovery of Bivariate Bicycle Codes with LLM-Guided Search
Juan Cruz-Benito, Andrew W. Cross, David Kremer +1
Quantum LDPC code discovery requires searching large algebraic design spaces while reliably certifying the parameters and equivalence classes of any candidates found. We introduce…
Efficient Classical Simulation of Heuristic Peaked Quantum Circuits
David Kremer, Nicolas Dupuis
Peaked quantum circuits, whose output distribution is sharply concentrated on a single bitstring, have emerged as a promising candidate for verifiable quantum advantage, as the cor…
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 Permutation Circuit Synthesis Across Generic Topologies
Victor Villar, Juan Cruz-Benito, Ismael Faro +1
This paper investigates artificial intelligence (AI) methodologies for the synthesis and transpilation of permutation circuits across generic topologies. Our approach uses Reinforc…
Optimizing the non-Clifford-count in unitary synthesis using Reinforcement Learning
David Kremer, Ali Javadi-Abhari, Priyanka Mukhopadhyay
In this paper we study the potential of using reinforcement learning (RL) in order to synthesize quantum circuits, while optimizing the T-count and CS-count, of unitaries that are…
Quantum Verifiable Rewards for Post-Training Qiskit Code Assistant
Nicolas Dupuis, Adarsh Tiwari, Youssef Mroueh +3
Qiskit is an open-source quantum computing framework that allows users to design, simulate, and run quantum circuits on real quantum hardware. We explore post-training techniques f…
Pauli Network Circuit Synthesis with Reinforcement Learning
Ayushi Dubal, David Kremer, Simon Martiel +3
We introduce a Reinforcement Learning (RL)-based method for re-synthesis of quantum circuits containing arbitrary Pauli rotations alongside Clifford operations. By collapsing each…
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…