Causal Discovery in High-Dimensional Point Process Networks with Hidden Nodes

Thanks to technological advances leading to near-continuous time observations, emerging multivariate point process data offer new opportunities for causal discovery. However, a key obstacle in achieving this goal is that many relevant processes may not be observed in practice. Naïve estimation approaches that ignore these hidden variables can generate misleading results because of the unadjusted confounding. To plug this gap, we propose a deconfounding procedure to estimate high-dimensional point process networks with only a subset of the nodes being observed. Our method allows flexible connections between the observed and unobserved processes. It also allows the number of unobserved processes to be unknown and potentially larger than the number of observed nodes. Theoretical analyses and numerical studies highlight the advantages of the proposed method in identifying causal interactions among the observed processes.

Environment, Demographics, and Economy in Qing China

The Manchu rulers of the Qing dynasty (1644–1912), China’s last, ruled an ethnic diversity of peoples throughout both Inner Asia and China proper. In the process, networks of environmental relationships were formed across Mongolian steppes, Tibetan and Southeast Asian highlands, Manchurian forests, and alluvial plains in the empire’s core, China proper. The dynasty’s main environmental efforts were devoted to the lowland agrarian concentration of water and grain. Yet the empire’s sheer extent also required management of agro-pastoral, pastoral, foraging, and swiddening relations—pursued under conditions of global cooling in the Northern Hemisphere, known as the Little Ice Age. Mineral inputs from foreign and domestic sources, as well as New World crops, were critical not only for the dynasty’s material development, but also entailed debilitating costs—most particularly deforestation and soil erosion. As it adapted to dynamic demographic and ecological conditions, the dynasty developed many structures for the maintenance and resiliency of its environmental relations, which included existential interactions with select animals and plants, to produce the world’s largest population of its time. The Qing achievement can be evaluated differently according to timescales and wide-ranging criteria that transcend crude Malthusian parameters. However, its political and demographic accomplishments must be qualified from an environmental perspective in light of the mid-19th-century breakdown of many of its environmental networks that directly contributed to its demise and that of the 2,000-year-old imperial system.

Toward a Lingua Franca for Deterministic Concurrent Systems

Many programming languages and programming frameworks focus on parallel and distributed computing. Several frameworks are based on actors, which provide a more disciplined model for concurrency than threads. The interactions between actors, however, if not constrained, admit nondeterminism. As a consequence, actor programs may exhibit unintended behaviors and are less amenable to rigorous testing. We show that nondeterminism can be handled in a number of ways, surveying dataflow dialects, process networks, synchronous-reactive models, and discrete-event models. These existing approaches, however, tend to require centralized control, pose challenges to modular system design, or introduce a single point of failure. We describe “reactors,” a new coordination model that combines ideas from several of these approaches to enable determinism while preserving much of the style of actors. Reactors promote modularity and allow for distributed execution. By using a logical model of time that can be associated with physical time, reactors also provide control over timing. Reactors also expose parallelism that can be exploited on multicore machines and in distributed configurations without compromising determinacy.