Orbital-free Bond Breaking via Machine Learning

Machine learning is used to approximate the kinetic energy of one dimensional diatomics as a functional of the electron density. The functional can accurately dissociate a diatomic, and can be systematically improved with training. Highly accurate self-consistent densities and molecular forces are found, indicating the possibility for ab-initio molecular dynamics simulations

The future of social is personal: the potential of the personal data store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges

The Political Economy of Infrastructure Investment: Competition, Collusion and Uncertainty

Infrastructure, as it impacts transport costs, is crucial in determining equilibrium outcomes in spatial competition; however, infrastructure investment is typically exogenous. Our political economy analysis of infrastructure choice is based upon consumer preferences derived from Salop’s circular city model. In this setting, infrastructure investment has two effects: it directly lowers costs to consumers and indirectly affects market power. We show how political support for infrastructure investments depends crucially on the details of the market. Competition boosts popular support for infrastructure — often excessively so — while collusion leads to underinvestment. The uncertainty produced by infrastructure induced entry leads to traps and thresholds.