Lukas Burgholzer

Lukas Burgholzer

PhD Student

Johannes Kepler University Linz

Biography

I am a PhD student with a Master’s degree in Mathematics and a Bachelor’s degree in Computer Science. In my work, I am combining my expertise from both domains to develop design automation methods and tools for quantum computing. My research focuses on classical simulation, compilation and, in particular, verification methods for quantum circuits.

Interests
  • Design Automation Methods and Tools for Quantum Computing
  • Equivalence Checking of Quantum Circuits
  • Efficient Datastructures for Quantum Computing (Decision Diagrams, Tensor Networks, ZX-calculus, etc.)
Education
  • Bachelor's Degree in Computer Science, 2019

    Johannes Kepler University Linz

  • Master's Degree in Industrial Mathematics, 2018

    Johannes Kepler University Linz

  • Bachelor's Degree in Mathematics, 2016

    Johannes Kepler University Linz

Published Open-Source Software

developed as part of the Munich Quantum Toolkit (MQT—formerly known as JKQ) at the Technical University of Munich and the Johannes Kepler University Linz

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MQT Bench
Benchmarking Software and Design Automation Tools for Quantum Computing
MQT Bench
MQT DDVis
Visualizing Decision Diagrams for Quantum Computing
MQT DDVis
MQT QCEC
Quantum Circuit Equivalence Checking
$ pip install mqt.qcec
MQT QCEC
MQT QMAP
Quantum Circuit Mapping
$ pip install mqt.qmap
MQT QMAP
MQT DDSIM
Classical Quantum Circuit Simulation
$ pip install mqt.ddsim
MQT DDSIM
MQT QFR
Quantum Functionality Representation
$ pip install mqt.qfr
MQT QFR
MQT DDPackage
Decision Diagram Package for Quantum Computing
MQT DDPackage

Accomplish­ments

2nd Place at the 10th annual NYUAD Hackathon for Social Good in the Arab World
Mentored a team of 8 people from all over the world at the 10th annual NYUAD Hackathon for Social Good in the Arab World. The resulting project, qVerified – a tool for verified quantum circuit compilation, achieved 2nd place.
Completed the 2021 Qiskit Global Summer School on Quantum Machine Learning
Completed the two-week intensive course provided by IBM Quantum, completing all graded lab work assignments with a final cumulative score above 75%, demonstrating applied understanding and comfort with and about Quantum Computing and Quantum Machine Learning using Qiskit
See certificate
IBM Certified Associate Developer - Quantum Computation using Qiskit v0.2X
See certificate
Invitation to IBM Qiskit Camp 2020
postponed due to COVID-19