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Computer simulations have become indispensable in numerous science and engineering disciplines, both in industry and academia. The list of disciplines that make extensive use of computer simulations has grown to include materials science, biology, astrophysics, economics, social science, and architecture, among others. It has become one of the most quantitative and reproducible methods that has been used to interrogate countless empirical and interdisciplinary questions from nano to macro scales in a fast- evolving scientific and social environment.Ìý

As much as computer simulations are successful, they are also methods that fail in their purpose of inquiring about the world, and as much as researchers make use of them, computer simulations raise important questions that are at the heart of contemporary science and engineering practice. In this perspective, studies on computer simulations touch upon many different facets, including not only scientific and engineering research aspects but also discussion on their methodology, their epistemology, and the possibilities of an ethical framework, among other issues.

This module will start with a historical and philosophical overviewÌý of computer simulations in science and engineering and an introduction to the epistemic challenges and technological opportunities in connecting simulations, theory, and experiments. We will address the core concepts essential to understand and interpret computer simulations in science and engineering, including the fundamentals of statistical physics, interaction potentials, Monte Carlo simulations, cellular automata, agent-based simulations, equation-based simulations, and the concept of enhanced sampling techniques and neural network. This module will also explore the development of simulation methods and scientific software packages that can be used on different computational infrastructures, from personal workstations to high performance computing clusters and distributed network, such as blockchain

A series of real-world applications discussed in this module will enable students to understand the fundamentals of computer simulations, gain knowledge on selecting appropriate simulation methods and in interpreting the simulation outputs. Examples of applications from various disciplines will be used to illustrate the strengths and limitations of the computational methods and infrastructures. This includes physics, chemistry, astrophysics, biology, social science, architecture, and engineering finance, among others.

This module combines lectures, seminars, group work and hands-on practical. Students will develop critical thinking, gain skills to implement various simulation techniques and use different computational infrastructures, and draw conclusions from the results.Ìý

Teaching Delivery

The module will be divided into lectures, group seminars, and practical workshop sessions. Each of them will emphasise a different aspect of the impact of computational simulations in science and engineering. For instance, the group seminars would focus on the social implications and challenges of computational simulations and the workshops will focus on the development of practical skills through guided examples.Ìý

Indicative Topics *Based on module content in 2023/24, subject to possible changes.Ìý

• Universe of Computer SimulationsÌý
• Computer Simulations and Scientific ModelsÌý
• Computer Simulations and ExperimentsÌý
• Trusting Computer SimulationsÌý
• Technological Paradigms, Computer Simulations, Big Data and AIÌý
• Ethics and Computer SimulationsÌý
• Monte Carlo SimulationsÌý
• Cellular Automata SimulationsÌý
• Agent Based SimulationsÌý
• Equation-Based SimulationsÌý
• Relation to Statistical MechanicsÌý
• Enhanced Sampling and Computer SimulationsÌý
• Neural Networks and Computer SimulationsÌý
• Blockchain and Computer SimulationsÌý

Module aims and objectives

To this end, this module has been conceived for an interdisciplinary audience interested in fundamental, technical, and philosophical aspects raised by the theory and practice of computer simulations. The aim of this module is not to engage in deep philosophical discussions. Rather, it seeks to explore the synergy between the fundamental and technical aspects of computer simulations, and the philosophical value emerging. In this respect, this module targets students with an interest in working with computer simulations across disciplines and holding philosophical inclinations; the latter being essential to communicate with scientists, engineers, policy makers, and the general public.