Nicolas Macris

INN 134 (Bâtiment INN)
Station 14
CH-1015 Lausanne

INR 130 (Bâtiment INR)
Station 14
CH-1015 Lausanne

Web site:  Web site:

INN 112 (Bâtiment INN)
Station 14
CH-1015 Lausanne

Web site:  Web site:

INR 134 (Bâtiment INR)
Station 14
CH-1015 Lausanne

RLC D1 740 (Rolex Learning Center)
Station 20
CH-1015 Lausanne

Web site:  Web site:

Administrative data


Selected publications


Teaching & PhD


Communication Systems

Computer Science

PhD Programs

Doctoral program in computer and communication sciences

Lecture notes

N-body methods in condensed matter, Lecture notes of the troisième cycle de la physique en Suisse Romande, 160 pp, first version (2002), second revised version (2009), D. Baeriswyl and N. Macris,

Statistical Physics for Communications, Signal Processing, and Computer Science, 364 pp, Lecture notes in progress, doctoral class (2017 edition) N. Macris and R. Urbanke 


Quantum information processing

Information is processed in physical devices. In the quantum regime the concept of classical bit is replaced by the quantum bit. We introduce quantum principles, and then quantum communications, key distribution, quantum entropy, and spin dynamics. No prior knowledge of quantum physics is required.

Markov chains and algorithmic applications

The study of random walks finds many applications in computer science and communications. The goal of the course is to get familiar with the theory of random walks, and to get an overview of some applications of this theory to problems of interest in communications, computer and network science.

Quantum Information Theory and Computation

Today one is able to manipulate matter at the nanoscale were quantum behavior becomes important and possibly information processing will have to take into account laws of quantum physics. We introduce concepts developed in the last 25 years to take advantage of quantum resources.

Statistical Physics for Communication and Computer Science

The course introduces the student to notions of statistical physics which have found applications in communications and computer science. We focus on graphical models with the emergence of phase transitions, and their relation to the behavior of efficient algorithms.

Quantum computation

The course introduces teh paradigm of quantum computation in an axiomatic way. We introduce the notion of quantum bit, gates, circuits and we treat the most important quantum algorithms. We also touch upon error correcting codes. This course is independent of COM-309.

Learning theory

Machine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning.

Introduction to quantum science and technology

This course provides all students with a broad view of the diverse aspects of the field: quantum physics, communication, computation, simulation, quantum hardware technologies, quantum sensing and metrology. The course will be an overview of frontiers of the domain and taught by multiple instructors