Related papers: Negro and Danube are mirror rivers
Solar forcing on climate has been reported in several studies although the evidence so far remains inconclusive. Here, we analyze the stream flow of one of the largest rivers in the world, the Parana in southeastern South America. For the…
We study the thermodynamic features of static, spherically-symmetric Schwarzschild black holes adopting different types of Barrow entropy. Specifically, in addition to the standard Barrow entropy, we consider a logarithmic-corrected type of…
We provide measurements of the absolute reflectivity of Jupiter and Saturn along their central meridians in filters covering a wide range of visible and near-infrared wavelengths (from 0.38 to 1.7 $\mu$m) that are not often presented in the…
The global ocean model NEMO is run in a series of stand-alone configurations (2015-2022) to investigate the potential for improving global medium-range storm surge forecasts by including the inverse barometer effect. The analysis focus on…
The structure of a river network may be seen as a discrete set of nested sub-networks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method.…
We consider a harmonic chain in contact with thermal reservoirs at different temperatures and subject to bulk noises of different types: velocity flips or self-consistent reservoirs. While both systems have the same covariances in the…
We examine the continuous-time counterpart of mirror descent, namely mirror flow, on classification problems which are linearly separable. Such problems are minimised `at infinity' and have many possible solutions; we study which solution…
Over the last decade there has been increasing concern about the biases embodied in traditional evaluation methods for Natural Language Processing/Learning, particularly methods borrowed from Information Retrieval. Without knowledge of the…
We present a deep learning model for high-resolution probabilistic precipitation forecasting over an 8-hour horizon in Europe, overcoming the limitations of radar-only deep learning models with short forecast lead times. Our model…
In the hydrodynamic regime of field theories the entropy is upgraded to a local entropy current. The entropy current is constructed phenomenologically order by order in the derivative expansion by requiring that its divergence is…
Using molecular dynamics simulations we investigate the ability of an analytical three-dimensional double well in reproducing static and dynamic anomalies found experimentally in liquid water. We find anomalous behavior in the stable region…
Parallel tempering, also known as replica exchange Monte Carlo, is studied in the context of two simple free energy landscapes. The first is a double well potential defined by two macrostates separated by a barrier. The second is a `golf…
River networks serve as a paradigmatic example of all branching networks. Essential to understanding the overall structure of river networks is a knowledge of their detailed architecture. Here we show that sub-branches are distributed…
The two key characteristics of a normalizing flow is that it is invertible (in particular, dimension preserving) and that it monitors the amount by which it changes the likelihood of data points as samples are propagated along the network.…
We introduce a geometry on the cone of positive closed currents of bidegree (p,p) and apply it to define the intersection of such currents. We also construct and study the Green currents and the equilibrium measure for horizontal-like…
Detailed models are compared to recent infrared observations of the nearby extrasolar planet, HD 189733b. It is demonstrated that atmospheric water is present and that the planet's day side has a non-isothermal structure down to gas…
Variational inference relies on flexible approximate posterior distributions. Normalizing flows provide a general recipe to construct flexible variational posteriors. We introduce Sylvester normalizing flows, which can be seen as a…
Normalizing flows are powerful non-parametric statistical models that function as a hybrid between density estimators and generative models. Current learning algorithms for normalizing flows assume that data points are sampled…
Analogical thinking is a valuable tool in theoretical physics, since it allows us to take the understanding we have developed in one system and apply it to another. In this thesis, we study the analogy between two seemingly unlikely…
There are currently two main, continuum models of entropy: a 'reversible', Clausius entropy model and an 'irreversible', Onsager-Prigogine entropy model. It is shown that the equations of the 'reversible' and the 'irreversible' entropy…