181 citations · 216 across the 3 of their papers we have counts for
3 papers
Strategies for running the QAOA at hundreds of qubits
Brandon Augustino, Madelyn Cain, Edward Farhi +5
We explore strategies aimed at reducing the amount of computation, both quantum and classical, required to run the Quantum Approximate Optimization Algorithm (QAOA). First, followi…
Challenges and Opportunities in Quantum Optimization
Amira Abbas, Andris Ambainis, Brandon Augustino +43
Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. As such, a widespread interest in quantum a…
TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Machine Learning
William Won, Midhilesh Elavazhagan, Sudarshan Srinivasan +2
The surge of artificial intelligence, particularly large language models, has driven the rapid development of large-scale machine learning clusters. Executing distributed models on…