87945 - Software and Computing for Nuclear and Subnuclear Physics

Learning outcomes

At the end of the course the student will learn the basic concepts of programming and modern scientific computation, as they are currently used in several physics fields. He/she will have an understanding of the major software development techniques and strategies and an understanding of the various computational frameworks, database, data maintenance and collection. By the end of the course, the student will be able to solve advanced problems in scientific software design for nuclear and subnuclear physics that will be developed as small group projects.

Course contents

• From data taking to a published research paper.
• The programming view: programming languages.
• Hands-on on Unix and c.l., Python (and most commonly used third-party libraries), Jupiter, Google Colab(oratory), and more.
• The data view: data, databases, big data, data-intensive science
• The resources view: distributed computing, grid(s), cloud(s), grid- and cloud-compliant computing models in HEP.
• The data science view: a glance at machine learning and deep learning, and AI applications in HEP.
• Hands-on on (basic) ML/DL frameworks and neural network architectures.
• (Basic) introduction to explainable AI, ethical AI, green AI, quantum computing and quantum ML.

Readings/Bibliography

Details in the first lecture of the course.

Teaching methods

Slides and interactive notebooks, plus additional material/activities in innovative/blended learning.

Assessment methods

A written exam plus a coding project.

Teaching tools

See above.

Office hours

See the website of Daniele Bonacorsi

See the website of Alessandra Fanfani

See the website of Tommaso Diotalevi