Not All Fluctuations Are Created Equal: Spontaneous Variations in Thermodynamic Function.

We identify macroscopic functioning arising during a thermodynamic system's typical and atypical behaviors, thereby describing system operations over the entire set of fluctuations. We show how to use the information processing second law to determine functionality for atypical realizations and how to calculate the probability of distinct modalities occurring via the large-deviation rate function, extended to include highly correlated, memoryful environments and systems. Altogether, the results complete a theory of functional fluctuations for complex thermodynamic nanoscale systems operating over finite periods.

Classification framework to identify similar visual scan paths using multiple similarity metrics.

Analyzing visual scan paths, the time-ordered sequence of eye fixations and saccades, can help us understand how operators visually search the environment before making a decision. To analyze and compare visual scan paths, prior studies have used metrics such as string edit similarity, which considers the order used to inspect areas of interest (AOIs), as well as metrics that consider the AOIs shared between visual scan paths. However, to identify similar visual scan paths, particularly in tasks and environments in which operators may apply variations of a common underlying visual scanning behavior, using solely one similarity metric might not be sufficient.

Complexity-calibrated benchmarks for machine learning reveal when prediction algorithms succeed and mislead.

Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form of recurrent neural network. Recently, a "next-generation" reservoir computer was introduced in which the memory trace involves only a finite number of previous symbols.

Maximum Geometric Quantum Entropy.

Any given density matrix can be represented as an infinite number of ensembles of pure states. This leads to the natural question of how to uniquely select one out of the many, apparently equally-suitable, possibilities. Following Jaynes' information-theoretic perspective, this can be framed as an inference problem.

Thermodynamic uncertainty theorem.

Thermodynamic uncertainty relations (TURs) express a fundamental lower bound on the precision (inverse scaled variance) of any thermodynamic charge-e.g., work or heat-by functionals of the average entropy production.