Towards "dynamic domains": totally continuous cocomplete Q-categories

It is common practice in both theoretical computer science and theoretical physics to describe the (static) logic of a system by means of a complete lattice. When formalizing the dynamics of such a system, the updates of that system organize themselves quite naturally in a quantale, or more generally, a quantaloid. In fact, we are lead to consider cocomplete quantaloid-enriched categories as fundamental mathematical structure for a dynamic logic common to both computer science and physics. Here we explain the theory of totally continuous cocomplete categories as generalization of the well-known theory of totally continuous suplattices. That is to say, we undertake some first steps towards a theory of "dynamic domains''.Comment: 29 pages; contains a more elaborate introduction, corrects some typos, and has a sexier title than the previously posted version, but the mathematics are essentially the sam

Presenting Computer Science Concepts to High School Students

Computer science at high school often focusses on programming, but a broader view of other areas of computer science has key benefits for both writing programs that are more efficient and making more theoretical concepts more accessible to those who do not find programming intrinsically interesting. With the introduction of computer science at high schools, a lack of coherent resources for teachers and students prompted the development of the NZ Computer Science Field Guide, an open-source, on-line textbook. This paper describes the design of the Field Guide, which has fourteen chapters about various topics of computer science. The design includes written text, videos, classroom activities and interactive applications. The need for a broad view of computer science is discussed, and programming exercises to go with the topics are suggested

An Open Guide to Data Structures and Algorithms

This textbook serves as a gentle introduction for undergraduates to theoretical concepts in data structures and algorithms in computer science while providing coverage of practical implementation (coding) issues. The field of computer science (CS) supports a multitude of essential technologies in science, engineering, and communication as a social medium. The varied and interconnected nature of computer technology permeates countless career paths making CS a popular and growing major program. Mastery of the science behind computer science relies on an understanding of the theory of algorithms and data structures. These concepts underlie the fundamental tradeoffs that dictate performance in terms of speed, memory usage, and programming complexity that separate novice programmers from professional practitioners

A Review Paper: Student Attitude towards Computer Science

The present review study is an attempt to examine the vast literature on student attitude towards computer science. Its main focus is to explore the introduction of student’s attitude towards computer science. Hence, content analysis was performed and important measures vi.objectives, sources of data, major variables, research methodology, and significant findings have been reported.  The study underlined the students’ attitude towards computer science career. Learning difficulties in introductory programming courses are well known to teachers and students. While some types of causes for those complications can be pointed out. In this work we concentrated on student related issues, namely their study methods and attitudes towards learning programs. This study is surely going to help the young researchers who do research in student attitude towards computer science to make a tough theoretical structure through analyzing the descriptive studies from 1997-2015. Keywords:Attitudes Survey – Computer science – Assessment – Learning difficultie

Quantum Computing: Lecture Notes

This is a set of lecture notes suitable for a Master's course on quantum computation and information from the perspective of theoretical computer science. The first version was written in 2011, with many extensions and improvements in subsequent years. The first 10 chapters cover the circuit model and the main quantum algorithms (Deutsch-Jozsa, Simon, Shor, Hidden Subgroup Problem, Grover, quantum walks, Hamiltonian simulation and HHL). They are followed by 2 chapters about complexity, 4 chapters about distributed ("Alice and Bob") settings, and a final chapter about quantum error correction. Appendices A and B give a brief introduction to the required linear algebra and some other mathematical and computer science background. All chapters come with exercises, with some hints provided in Appendix C

Probability around the Quantum Gravity. Part 1: Pure Planar Gravity

In this paper we study stochastic dynamics which leaves quantum gravity equilibrium distribution invariant. We start theoretical study of this dynamics (earlier it was only used for Monte-Carlo simulation). Main new results concern the existence and properties of local correlation functions in the thermodynamic limit. The study of dynamics constitutes a third part of the series of papers where more general class of processes were studied (but it is self-contained), those processes have some universal significance in probability and they cover most concrete processes, also they have many examples in computer science and biology. At the same time the paper can serve an introduction to quantum gravity for a probabilist: we give a rigorous exposition of quantum gravity in the planar pure gravity case. Mostly we use combinatorial techniques, instead of more popular in physics random matrix models, the central point is the famous $\alpha =-7/2$ exponent.Comment: 40 pages, 11 figure