2 citations · 3 across the 7 of their papers we have counts for
7 papers
QTurbo: A Robust and Efficient Compiler for Analog Quantum Simulation
Junyu Zhou, Yuhao Liu, Shize Che +5
Analog quantum simulation leverages native hardware dynamics to emulate complex quantum systems with great efficiency by bypassing the quantum circuit abstraction. However, convent…
Making Neural Networks More Suitable for Approximate Clifford+T Circuit Synthesis
Mathias Weiden, Justin Kalloor, John Kubiatowicz +1
Machine Learning with deep neural networks has transformed computational approaches to scientific and engineering problems. Central to many of these advancements are precisely tune…
AC/DC: Automated Compilation for Dynamic Circuits
Siyuan Niu, Efekan Kokcu, Anupam Mitra +6
Dynamic quantum circuits incorporate mid-circuit measurements and feed-forward operations originally intended to realize Quantum Error Correction. This paradigm has recently been u…
Quantum Hardware Roofline: Evaluating the Impact of Gate Expressivity on Quantum Processor Design
Justin Kalloor, Mathias Weiden, Ed Younis +3
The design space of current quantum computers is expansive with no obvious winning solution. This leaves practitioners with a clear question: "What is the optimal system configurat…
Improving Quantum Circuit Synthesis with Machine Learning
Mathias Weiden, Ed Younis, Justin Kalloor +2
In the Noisy Intermediate Scale Quantum (NISQ) era, finding implementations of quantum algorithms that minimize the number of expensive and error prone multi-qubit gates is vital t…
SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics
Arash Ardakani, Altan Haan, Shangyin Tan +4
Transformer-based models, such as BERT and ViT, have achieved state-of-the-art results across different natural language processing (NLP) and computer vision (CV) tasks. However, t…