Unfortunately, the continuing uncertainty with coronavirus situation forces us to cancel Durham Symposium on Mathematics of Constraint Satisfaction scheduled for this summer. We may return to the idea of organising a CSP meeting in Durham in a few years' time. Thank you for your interest in our meeting, and, hopefully, we will all be able to meet face to face somewhere sooner rather than later.
Mathematics symposia have been held in Durham every year since 1974, and have since become an established and recognised series of international research meetings, with over 100 symposia to date. They provide an excellent opportunity to explore an area of research in depth, to learn of new developments, and to instigate links between different branches. The format is designed to allow substantial time for interaction and research. The week-long meetings are held in July or August, with about 50 participants, roughly half of whom will come from the UK. Lectures and seminars take place in the Department of Mathematical Sciences, Durham University.
The symposium will explore mathematical, algorithmic and complexity-theoretic aspects of constraint satisfaction problems (CSPs). In the past decade, deep mathematical theories have been developed with the aim to explain what makes CSPs hard or easy to solve, either exactly or approximately. Some spectacular progress has been made, but many central problems are still open. The symposium will bring together specialists using algebraic, logical, combinatorial, and analytical approaches to the CSP. One particular topic of the symposium will be the recently discovered area of the promise CSPs, which was previously studied mostly in the special case of approximate graph and hypergraph colouring. This new direction links together all the existing approaches, from universal algebra to probabilistically checkable proofs, and it already uncovered new connections, e.g. to algebraic topology and topological combinatorics. The main aim of the symposium is to foster further synergy between different approaches in the rich area of mathematics of constraint satisfaction.