Seminars | Quantum Computing

Quantum Formal Methods: From Languages to Verification


Rajagopal Nagarajan

Abstract:
The novel field of quantum computation and quantum
information has gathered significant impetus in the last few
years, and it has the potential to radically impact the future of
information technology. While the successful construction of a
large-scale quantum computer may be some years away, 
equipment for quantum cryptography is commercially available
and a satellite has been launched by China to provide secure 
quantum communication. However, it is well known from experience 
with classical systems that it is notoriously difficult to achieve robust and
reliable implementations. Techniques based on
formal verification are now widely used by industry to ensure that
classical systems meet their specifications.
In this talk, I will introduce quantum programming/specification languages and give an overview of our ongoing work on formal methods for modelling and analysis of quantum protocols and, eventually, their implementations.

Date: Wednesday, September 27, 2017 at 4:00 PM

Supervised Discriminative Classification in Quantum Machine Learning


David Windridge

Abstract:
Quantum Machine Learning is a recent area of research initiated by the demonstrations of quantised variants of standard machine learning algorithms such as the Quantum Support Vector Machine (SVM) by Rebentrost, Mohseni & Lloyd and the Quantum K-Means algorithm of Aïmeur, Brassard and Gambs. The development of the quantum SVM can be regarded as particularly significant in that the classical SVM constitutes the exemplar instance of a  supervised binary classifier, i.e. an entity capable of learning an optimal discriminative decision hyperplane from labeled vectors. We explore this classifier in detail along with its Kernelised variants, as well as investigating an ensemble-based enhancement to enable variance-resilient quantum machine learning.

Date: Thursday, September 28, 2017 at 4:00 PM