Probabilistic Numerics and Uncertainty in Computations

We deliver a call to arms for probabilistic numerical methods: algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data has led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimisers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.Comment: Author Generated Postprint. 17 pages, 4 Figures, 1 Tabl

Practical Bayesian Optimization for Variable Cost Objectives

We propose a novel Bayesian Optimization approach for black-box functions with an environmental variable whose value determines the tradeoff between evaluation cost and the fidelity of the evaluations. Further, we use a novel approach to sampling support points, allowing faster construction of the acquisition function. This allows us to achieve optimization with lower overheads than previous approaches and is implemented for a more general class of problem. We show this approach to be effective on synthetic and real world benchmark problems.Comment: 8 pages, 7 figure

Crystallographic phase changes and damage thresholds of CsPbI3 microwire waveguides through continuous wave photoablation

We investigate waveguide efficiency of CsPbI3 microwire waveguides and their photodegradation over a range of continuous wave laser excitation energies and intensities. Under modest laser input intensities <1 kW cm−2 we observe a wavelength dependent efficiency of light propagation in the waveguides. At increased power densities and wavelengths of 473 nm or shorter, microwires undergo photoablation into discrete fragments. Use of diffraction-limited excitation allowed localised cleavage of the microwires with observation of transient photoluminescence from degradation products. TEM analysis of the microwires revealed transformation from the yellow δ-phase to amorphous phases in the region of the photodamage with a degraded morphology consistent with efficient thermal transfer and induced melting

Measurement of ligand coverage on cadmium selenide nanocrystals and its influence on dielectric dependent photoluminescence intermittency

Photoluminescent quantum dots are used in a range of applications that exploit the unique size tuneable emission, light harvesting and quantum efficient properties of these semiconductor nanocrystals. However, optical instabilities such as photoluminescence intermittency, the stochastic switching between bright, emitting states and dark states, can hinder quantum dot performance. Correlations between this blinking of emission and the dielectric properties of the nanoenvironment between the quantum dot interface and host medium, suggest surface ligands play a role in modulating on-off switching rates. Here we elucidate the nature of the cadmium selenide nanocrystal surface, by combining magic angle spinning NMR and x-ray photoelectron spectroscopy to determine ligand surface densities, with molecular dynamics simulation to assess net ligand filling at the nanocrystal interface. Results support a high ligand coverage and are consistent with photoluminescence intermittency measurements that indicate a dominant contribution from surface ligand to the dielectric properties of the local quantum dot environment

HD-CNV: hotspot detector for copy number variants.

SUMMARY: Copy number variants (CNVs) are a major source of genetic variation. Comparing CNVs between samples is important in elucidating their potential effects in a wide variety of biological contexts. HD-CNV (hotspot detector for copy number variants) is a tool for downstream analysis of previously identified CNV regions from multiple samples, and it detects recurrent regions by finding cliques in an interval graph generated from the input. It creates a unique graphical representation of the data, as well as summary spreadsheets and UCSC (University of California, Santa Cruz) Genome Browser track files. The interval graph, when viewed with other software or by automated graph analysis, is useful in identifying genomic regions of interest for further study. AVAILABILITY AND IMPLEMENTATION: HD-CNV is an open source Java code and is freely available, with tutorials and sample data from http://daleylab.org. CONTACT: [email protected]

Sixteen years of Collaborative Learning through Active Sense-making in Physics (CLASP) at UC Davis

This paper describes our large reformed introductory physics course at UC Davis, which bioscience students have been taking since 1996. The central feature of this course is a focus on sense-making by the students during the five hours per week discussion/labs in which the students take part in activities emphasizing peer-peer discussions, argumentation, and presentations of ideas. The course differs in many fundamental ways from traditionally taught introductory physics courses. After discussing the unique features of CLASP and its implementation at UC Davis, various student outcome measures are presented showing increased performance by students who took the CLASP course compared to students who took a traditionally taught introductory physics course. Measures we use include upper-division GPAs, MCAT scores, FCI gains, and MPEX-II scores.Comment: Also submitted to American Journal of Physic