The EQuS Workshop on Python for Quantum Information Science is dedicated to a harassment-free workshop experience for everyone. Our anti-harassment policy can be found here.
November 17 & 18, 2016. Due to space constraints, registration is now closed.
Two-day workshop as an introduction to Python for scientific computing. Please bring your own computer to this event.
| Thursday | Friday | ||
|---|---|---|---|
| 9am to 10:30am | Tools for Scientific Computing 0 Sarah Kaiser |
9am to 10:30am | Open Systems w/ QuTiP Chris Granade |
| 10:30am to 11am | Coffee | 10:30am to 11am | Coffee |
| 11m to 12:30pm | Tools for Scientific Computing 1 Chris Granade |
11m to 12:30pm | Data Analysis w/ QInfer Chris Ferrie |
| 12:30pm to 1:30pm | Lunch | 12:30pm to 1:30pm | Lunch |
| 1:30pm to 3:00pm | Python for General Use Sarah Kaiser |
1:30pm to 3:00pm | Instrument Control Sarah Kaiser |
| 3:00pm to 3:30pm | Coffee | 3:00pm to 3:15pm | Coffee |
| 3:30pm to 5:00pm | Python for Scientific Computing Yuval Sanders |
3:15pm to 4:00pm | Interoperability Chris Grande |
| 4:00pm– | Post-workshop social gathering |
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Tools for Scientific Computing 0
- Learn what a shell is and how to interact with the command line
- Install and learn about package managers
- Install and explore two great examples of modern text editors
- Install and set up Python for the following lectures
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Tools for Scientific Computing 1
- Secure shell (SSH) for remote and HPC computing
- Version control with Git
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- Introduction to the Python language via an interactive interpreter
- Learn about types, indexing, functions, and classes in Python
- Python 2 vs. 3
- Stylistic guidelines for keeping collaborators happy (incl. future you)
- Learn about coding interface called Jupyter Notebook
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Python for Scientific Computing
- Storing, representing, and manipulating tensors of numeric data with the NumPy and SciPy packages
- R-style data analysis with the Pandas package
- publication-quality plotting and with Matplotlib, and statistics plotting with Seaborn
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Open Quantum Systems Simulation with QuTiP
- Install and configure compilers for use with Python
- Install QuTiP and learn how to represent quantum states, measurements, unitaries, and superoperators
- Use QuTiP to examine properties of norms
- See an example of unit testing in action
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- Estimate the bias of a classical coin
- Learn how to use QInfer to perform:
- quantum state tomography
- phase estimation
- randomized benchmarking
- Specify custom models to use with QInfer
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Instrument Control with InstrumentKit
- Learn about unit support for calculations in Python via two packages (Quantities and Pint)
- Go deeper into classes in Python and how they can be useful for designing interfaces to communicate to instruments
- Design a driver for a demo instrument
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Interoperability with Modern and Legacy Environments
- Connecting Python to C, MATLAB, and Julia
- Please help us save time by downloading the following files, depending on your operating system.
- Windows 7 or later
- OS X 10.7 or later
- Ubuntu 16.04
- Style Guides and Best Practices
- PEP 8: documents how to write clear and legible Python code.
- GitHub Flow: Suggestions and cultural practices for managing Git branches and merges.
- Good Enough Practices in Scientific Computing: Suggestions on how to make the data you want to see in the world.
- EPQIS16 Cheatsheet: Custom cheatsheet detailing topics covered in this workshop.
Below, we list some blog posts and lecture notes that may be useful as references, or in digging deeper into the topics presented at the EPQIS workshop.
- SSH and Git Configuration
- Python
- Text Editors
The Git logo by Jason Long is used under the Creative Commons BY 3.0 license.