Gaussian processes for machine learning (GPML) toolbox

The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library of simple mean and covariance functions and mechanisms to compose more complex ones. Several likelihood functions are supported including Gaussian and heavy-tailed for regression as well as others suitable for classification. Finally, a range of inference methods is provided, including exact and variational inference, Expectation Propagation, and Laplace’s method dealing with non-Gaussian likelihoods and FITC for dealing with large regression tasks.

Quantum Simulation of Dissipative Processes without Reservoir Engineering

We present a quantum algorithm to simulate general finite dimensional Lindblad master equations without the requirement of engineering the system-environment interactions. The proposed method is able to simulate both Markovian and non-Markovian quantum dynamics. It consists in the quantum computation of the dissipative corrections to the unitary evolution of the system of interest, via the reconstruction of the response functions associated with the Lindblad operators. Our approach is equally applicable to dynamics generated by effectively non-Hermitian Hamiltonians. We confirm the quality of our method providing specific error bounds that quantify its accuracy.

River Lune processes. A study of change in the River Lune catchment and recommendations for flood defence management

There has been a perception of increasing river channel instability in north west rivers and the River Lune in particular in recent decades. This has been attributed variously to: (a) long-term trends in precipitation-runoff regime; (b) changes in land-use such as moor-draining and sub-soil draining such that the river is more flashy than previously, and (c) a change in the magnitude-frequency relationships of flow such that high discharges are occurring with increased frequency. Resources are available in the form of rainfall and runoff records, archived information on channel planform, land use statistics and local engineering experience which have not been jointly and fully evaluated. Effective interpretation of the nature of channel change through time with respect to this resource may enhance the Environment Agency's ability to manage the river channel efficiently in the future and will aid the development of effective policy. The results of this study will for the first time, provide robust guidance with respect to long-term channel adjustment and the appropriate management options. The research provides suggestions as to how policy might be developed taking account of other pertinent factors.