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20212024
most citedGraph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm

3 citations · 7 across the 7 of their papers we have counts for

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quant-ph20243 cited

Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm

Zhiding Liang, Gang Liu, Zheyuan Liu +8

In recent years, quantum computing has emerged as a transformative force in the field of combinatorial optimization, offering novel approaches to tackling complex problems that hav…

quant-ph2023

Enhancing Virtual Distillation with Circuit Cutting for Quantum Error Mitigation

Peiyi Li, Ji Liu, Hrushikesh Pramod Patil +2

Virtual distillation is a technique that aims to mitigate errors in noisy quantum computers. It works by preparing multiple copies of a noisy quantum state, bridging them through a…

quant-ph2023

Superstaq: Deep Optimization of Quantum Programs

Colin Campbell, Frederic T. Chong, Denny Dahl +21

We describe Superstaq, a quantum software platform that optimizes the execution of quantum programs by tailoring to underlying hardware primitives. For benchmarks such as the Berns…

quant-ph20232 cited

Tackling the Qubit Mapping Problem with Permutation-Aware Synthesis

Ji Liu, Ed Younis, Mathias Weiden +3

We propose a novel hierarchical qubit mapping and routing algorithm. First, a circuit is decomposed into blocks that span an identical number of qubits. In the second stage permuta…

quant-ph20231 cited

Efficient Quantum Circuit Cutting by Neglecting Basis Elements

Daniel T. Chen, Ethan H. Hansen, Xinpeng Li +7

Quantum circuit cutting has been proposed to help execute large quantum circuits using only small and noisy machines. Intuitively, cutting a qubit wire can be thought of as classic…