106 citations · 407 across the 25 of their papers we have counts for
25 papers
Data-Efficient Quantum Noise Modeling via Machine Learning
Yanjun Ji, Marco Roth, David A. Kreplin +2
Maximizing the computational utility of near-term quantum processors requires predictive noise models that inform robust, noise-aware compilation and error mitigation. Conventional…
Synergistic Dynamical Decoupling and Circuit Design for Enhanced Algorithm Performance on Near-Term Quantum Devices
Yanjun Ji, Ilia Polian
Dynamical decoupling (DD) is a promising technique for mitigating errors in near-term quantum devices. However, its effectiveness depends on both hardware characteristics and algor…
Large Language Models to Generate System-Level Test Programs Targeting Non-functional Properties
Denis Schwachhofer, Peter Domanski, Steffen Becker +4
System-Level Test (SLT) has been a part of the test flow for integrated circuits for over a decade and still gains importance. However, no systematic approaches exist for test prog…
Improving the Performance of Digitized Counterdiabatic Quantum Optimization via Algorithm-Oriented Qubit Mapping
Yanjun Ji, Kathrin F. Koenig, Ilia Polian
This paper presents strategies to improve the performance of digitized counterdiabatic quantum optimization algorithms by cooptimizing gate sequences, algorithm parameters, and qub…
Algorithm-Oriented Qubit Mapping for Variational Quantum Algorithms
Yanjun Ji, Xi Chen, Ilia Polian +1
Quantum algorithms implemented on near-term devices require qubit mapping due to noise and limited qubit connectivity. In this paper we propose a strategy called algorithm-oriented…
Optimal Partitioning of Quantum Circuits using Gate Cuts and Wire Cuts
Sebastian Brandhofer, Ilia Polian, Kevin Krsulich
A limited number of qubits, high error rates, and limited qubit connectivity are major challenges for effective near-term quantum computations. Quantum circuit partitioning divides…