Michael Broughton
Programmer at Advanis
Edmonton, Alberta, Canada
Summary
🤩
Rockstar🎓
Top SchoolMichael Broughton is a pragmatic software engineer with more than a decade of hands-on experience building mission-critical systems spanning VOIP applications, embedded and real-time software, and networked device drivers. He specializes in low-level C, Python and Lua development on Linux/FreeBSD/OpenBSD platforms, with deep expertise in PostgreSQL, performance tuning and IP networking. At Advanis he designs bespoke VOIP solutions for market research, and earlier work includes predictive energy-pricing systems and wireless device firmware—showing a rare blend of telecom, embedded and market-facing software. An active open-source contributor to notable quantum projects like Cirq, qsim and TensorFlow Quantum, he has implemented noise models and unitary simulation features that bridge algorithm design and efficient back-end engineering. Colleagues rely on his analytical rigor, independent learning habit, and steady delivery under constrained, real-time environments.
11 years of coding experience
2 years of employment as a software developer
Electrical and Electronics Engineering, Electrical and Electronics Engineering at University of AlbertaEngineering, Engineering at Grant Macewan College
Github Skills (20)
circuit10
simulation10
algorithms10
c-language10
quantum-algorithms10
python10
simulator10
simulations10
cirq10
numpy10
quantum-computing10
cprogramming-language10
linear-algebra10
documentation10
data-structure9
Programming languages (3)
Github contributions (5)
tensorflow/quantum
Feb 2020 - Jul 2022
An open-source Python framework for hybrid quantum-classical machine learning.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:9 releases, 258 reviews, 334 commits in 2 years 6 months
Contributions summary:Michael's commits primarily focus on modifying and updating documentation files, specifically related to tutorials and guides within the tensorflow/quantum repository. These changes involve updating the contents, including latex and documentation rendering of the tutorials as well as examples. The user also added support to serialize and deserialize channels for cirq elements as well as fix for an empty circuit.
quantum-computingquantum-algorithmsquantum-classicalmachine-learningprototype
quantumlib/Cirq
Nov 2018 - Sep 2022
An open-source Python framework for creating, editing, and invoking Noisy Intermediate-Scale Quantum (NISQ) circuits.
Role in this project:Back-end Developer & Algorithm Engineer
Back-end Developer & Algorithm EngineerContributions:4 releases, 682 reviews, 127 commits in 3 years 10 months
Contributions summary:Michael contributed several noise channels to the `cirq` library, which is a framework for creating and manipulating quantum circuits. These contributions include the implementation of various noise models such as the AsymmetricDepolarizingChannel, DepolarizingChannel, and AmplitudeDampingChannel. They also modified existing code to incorporate new functions such as density matrix and bloch vector calculations within the `TrialResult` class. Furthermore, the user implemented the ability to slice the sweeps, which made combining work of smaller jobs easier.
pythonquantum-circuitsquantum-computingcircuitsquantum-algorithms
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