Aims: To provide students who have completed at the first term of the second-year compulsory module in microeconomics ECON0013 and in econometrics ECON0019...

Aims: To provide students who have completed at the first term of the second-year compulsory module in microeconomics ECON0013 and in econometrics ECON0019 with a framework for understanding modern ideas in the theory of international trade; to use this framework to analyse the major policy issues of world trade.

Suitable for: Second Year and Final year Economics (L100 / L101 / L102), BSc Economics and Geography (LL17), BSc Economics and Statistics (LG13), BA Philosophy and Economics (VL51), PPE (Philosophy, Politics and Economics (4V86 ) and BASc students subject to satisfying the pre-requisites.

Prerequisites: Completion of the first term of ECON0013 Microeconomics and ECON0019 Quantitative Economic &  Econometrics modules or any of POLS0008: Introduction to Quantitative Research Methods,  POLS0010: Data Analysis, POLS0012: Causal Analysis in Data Science or POLS0013: Measurements in Data Science. Students may also take ECON0019 concurrently.

Assumed knowledge: Students coming into the course should understand concepts relating to profit maximisation under different market structures particularly perfect competition and monopolistic competition, consumer theory, supply and demand analysis, welfare effects of taxes and subsidies and other interventions in the market, basic game theory and the concept of a Nash equilibrium, and an understanding of how to interpret regression models (including with dummy variables and fixed effects).

Description

Education is always political. Throughout your school and university education, teachers and academics have made decisions about curriculum,...

Aims:

The aim of the module is to introduce the students to the principles of quantum mechanics from a computer science perspective, and to the field of...

Aims:

The aim of the module is to introduce the students to the principles of quantum mechanics from a computer science perspective, and to the field of quantum computation and algorithms.

Learning outcomes: 

On successful completion of the module, a student will be able to:

Understand (i.e. be able to describe, analyse and reason about) quantum computation, and how it differs from classical probabilistic computation.
	Analyse the behaviour of simple quantum circuits.
	Understand how quantum superposition and interference can give quantum speedups over classical algorithms in certain cases, and apply these concepts to the design of quantum algorithms.
	Derive the Quantum Fourier Transform, and apply it to the design of quantum algorithms
	Derive Grover’s unstructured search technique, and apply it to the design of quantum algorithms.
Contents:

The module provides a first course on quantum computation. The basic mathematical formalism of quantum mechanics is be introduced from a computer science perspective, assuming no prior knowledge of quantum mechanics or physics. Building on this, the module develops the standard circuit model of quantum computation and basic quantum complexity theory. The majority of the module is devoted to quantum algorithms, including rigorous derivations and algorithm analysis. This section of the course starts from simple examples, and builds up to the major quantum algorithms, such as Shor’s quantum factoring algorithm and Grover’s unstructured search algorithm.

Requisites:

To be eligible to select this module as an optional or elective, a student must be registered on a programme and year of study for which it is a formally available.