prediction   8711

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Local causal states and discrete coherent structures (Rupe and Crutchfield, 2018)
"Coherent structures form spontaneously in nonlinear spatiotemporal systems and are found at all spatial scales in natural phenomena from laboratory hydrodynamic flows and chemical reactions to ocean, atmosphere, and planetary climate dynamics. Phenomenologically, they appear as key components that organize the macroscopic behaviors in such systems. Despite a century of effort, they have eluded rigorous analysis and empirical prediction, with progress being made only recently. As a step in this, we present a formal theory of coherent structures in fully discrete dynamical field theories. It builds on the notion of structure introduced by computational mechanics, generalizing it to a local spatiotemporal setting. The analysis’ main tool employs the local causal states, which are used to uncover a system’s hidden spatiotemporal symmetries and which identify coherent structures as spatially localized deviations from those symmetries. The approach is behavior-driven in the sense that it does not rely on directly analyzing spatiotemporal equations of motion, rather it considers only the spatiotemporal fields a system generates. As such, it offers an unsupervised approach to discover and describe coherent structures. We illustrate the approach by analyzing coherent structures generated by elementary cellular automata, comparing the results with an earlier, dynamic-invariant-set approach that decomposes fields into domains, particles, and particle interactions."

--- *ahem* *cough* https://arxiv.org/abs/nlin/0508001 *ahem*
to:NB  have_read  pattern_formation  complexity  prediction  stochastic_processes  spatio-temporal_statistics  cellular_automata  crutchfield.james_p.  modesty_forbids_further_comment 
10 days ago by cshalizi
An adaptability limit to climate change due to heat stress
Despite the uncertainty in future climate-change impacts, it is often assumed that humans would be able to adapt to any possible warming. Here we argue that heat stress imposes a robust upper limit to such adaptation. Peak heat stress, quantified by the wet-bulb temperature TW, is surprisingly similar across diverse climates today. TW never exceeds 31 °C. Any exceedence of 35 °C for extended periods should induce hyperthermia in humans and other mammals, as dissipation of metabolic heat becomes impossible. While this never happens now, it would begin to occur with global-mean warming of about 7 °C, calling the habitability of some regions into question. With 11–12 °C warming, such regions would spread to encompass the majority of the human population as currently distributed. Eventual warmings of 12 °C are possible from fossil fuel burning. One implication is that recent estimates of the costs of unmitigated climate change are too low unless the range of possible warming can somehow be narrowed. Heat stress also may help explain trends in the mammalian fossil record.

Trajectories of the Earth System in the Anthropocene: http://www.pnas.org/content/early/2018/07/31/1810141115
We explore the risk that self-reinforcing feedbacks could push the Earth System toward a planetary threshold that, if crossed, could prevent stabilization of the climate at intermediate temperature rises and cause continued warming on a “Hothouse Earth” pathway even as human emissions are reduced. Crossing the threshold would lead to a much higher global average temperature than any interglacial in the past 1.2 million years and to sea levels significantly higher than at any time in the Holocene. We examine the evidence that such a threshold might exist and where it might be.
study  org:nat  environment  climate-change  humanity  existence  risk  futurism  estimate  physics  thermo  prediction  temperature  nature  walls  civilization  flexibility  rigidity  embodied  multi  manifolds  plots  equilibrium  phase-transition  oscillation  comparison  complex-systems  earth 
10 days ago by nhaliday
[1705.08105] FRK: An R Package for Spatial and Spatio-Temporal Prediction with Large Datasets
"FRK is an R software package for spatial/spatio-temporal modelling and prediction with large datasets. It facilitates optimal spatial prediction (kriging) on the most commonly used manifolds (in Euclidean space and on the surface of the sphere), for both spatial and spatio-temporal fields. It differs from many of the packages for spatial modelling and prediction by avoiding stationary and isotropic covariance and variogram models, instead constructing a spatial random effects (SRE) model on a fine-resolution discretised spatial domain. The discrete element is known as a basic areal unit (BAU), whose introduction in the software leads to several practical advantages. The software can be used to (i) integrate multiple observations with different supports with relative ease; (ii) obtain exact predictions at millions of prediction locations (without conditional simulation); and (iii) distinguish between measurement error and fine-scale variation at the resolution of the BAU, thereby allowing for reliable uncertainty quantification. The temporal component is included by adding another dimension. A key component of the SRE model is the specification of spatial or spatio-temporal basis functions; in the package, they can be generated automatically or by the user. The package also offers automatic BAU construction, an expectation-maximisation (EM) algorithm for parameter estimation, and functionality for prediction over any user-specified polygons or BAUs. Use of the package is illustrated on several spatial and spatio-temporal datasets, and its predictions and the model it implements are extensively compared to others commonly used for spatial prediction and modelling."
to:NB  to_read  R  heard_the_talk  prediction  spatial_statistics  spatio-temporal_statistics  to_teach:data_over_space_and_time 
13 days ago by cshalizi
2010 Baccalaureate Remarks
he [grandfather of Jeff Bezos] gently and calmly said, “Jeff, one day you’ll understand that it’s harder to be kind than clever.”
for-m  for-d  for-s  for-k  clever  gift  gifts  choice  choices  2018-08-07  jeff  bezos  amazon  trillionaire  prediction  today  now  tomorrow  daily  story  life  0 
13 days ago by bekishore
Modeling Religion Project
The Center for Mind and Culture, Inc. (CMAC) is a non-profit organization in Boston, Massachusetts dedicated to non-partisan research.
research  prediction  modeling 
14 days ago by ruzel

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