Colin Burdine

Colin Burdine

A renegade computer scientist interested in quantum computing, machine learning, and mathematics.

Publications

Efficient Simulation of Open Quantum Systems on NISQ Trapped-Ion Hardware

Published in Advanced Quantum Technologies, 2025

This paper demonstrates an efficient framework for simulating open quantum systems on NISQ hardware using a Kraus operator-based approach, avoiding the computational overhead of Trotterization. The method is applied to simulate quantum channels, including the continuous-time Pauli channel and damped harmonic oscillators, on trapped-ion quantum devices such as IonQ Harmony and Quantinuum H1-1. The results, enhanced by tailored error mitigation techniques, show strong agreement with exact solutions, highlighting the feasibility of accurate and scalable quantum simulations on current hardware.

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Trotterless Simulation of Open Quantum Systems for NISQ Quantum Devices

Published in Advanced Quantum Technologies, 2024

This paper introduces a new method for simulating open quantum systems on NISQ (noisy intermediate-scale quantum) devices using a time-perturbative Kraus operator series, which enables simulation with circuits of time-independent depth. This approach offers a potential alternative to Trotterization, addressing its poor scaling with simulation time and system size. This proposed method improves the efficiency of quantum simulations for certain types of systems on near-term hardware.

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Discovery of Novel Superconducting Materials with Deep Learning

Published in 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), 2023

In this paper, we present ongoing work in the autonomous discovery of conventional, unconventional, and exotic superconductors with deep learning methods. Using experimental data from over 36,000 superconducting materials, we demonstrate that graph neural network models trained on raw crystalline structure can be used to discover superconductors with desirable properties such as high $T_c$

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