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In this work, we introduce Variational Umbrella Seeding, a novel technique for computing nucleation barriers. This new method, a refinement of the original seeding approach, is independent on the choice of order parameter for measuring the size of a nucleus. Consequently, it surpasses seeding in accuracy, and Umbrella Sampling in computational speed. We test the method extensively and demonstrate excellent accuracy for crystal nucleation of nearly hard spheres and of two distinct models of water: mW and TIP4P/ICE. This method can easily be extended to calculate nucleation barriers for homogeneous melting, condensation, and cavitation.

In this work, we study by means of simulations of hard spheres the equilibrium between a spherical solid cluster and the fluid. In the NVT ensemble we observe stable/metastable clusters of the solid phase in equilibrium with the fluid, representing configurations that are global/local minima of the Helmholtz free energy. Then, we run NpT simulations of the equilibrated system at the average pressure of the NVT run and observe that the clusters are critical because they grow/shrink with a probability of 1/2. Therefore, a crystal cluster equilibrated in the NVT ensemble corresponds to a Gibbs free energy maximum where the nucleus is in unstable equilibrium with the surrounding fluid, in accordance with what has been recently shown for vapor bubbles in equilibrium with the liquid. Then, within the Seeding framework, we use Classical Nucleation Theory to obtain both the interfacial free energy {\gamma} and the nucleation rate. The latter is in very good agreement with independent estimates using techniques that do not rely on Classical Nucleation Theory when the mislabeling criterion is used to identify the molecules of the solid cluster. We therefore argue that the radius obtained from the mislabeling criterion provides a good approximation for the radius of tension, Rs. We obtain an estimate of the Tolman length by extrapolating the difference between Re (the Gibbs dividing surface) and Rs to infinite radius. We show that such definition of the Tolman length coincides with that obtained by fitting {\gamma} versus 1/Rs to a straight line as recently applied to hard spheres [Montero de Hijes et al., J. Chem. Phys. 151, 155401, 2019]

Ice nucleation is a phenomenon that, despite the relevant implications for life, atmospheric sciences, and technological applications, is far from being completely understood, especially under extreme thermodynamic conditions. In this work we present a computational investigation of the homogeneous ice nucleation at negative pressures. By means of the seeding technique we estimate the size of the ice critical nucleus Nc for the TIP4P/Ice water model. This is done along the isotherms 230, 240, and 250 K, from positive to negative pressures until reaching the liquid-gas kinetic stability limit (where cavitation cannot be avoided). We find that Nc is nonmonotonic upon depressurization, reaching a minimum at negative pressures in the doubly metastable region of water. According to classical nucleation theory we establish the nucleation rate J and the surface tension gamma, revealing a retracing behavior of both when the liquid-gas kinetic stability limit is approached. We also predict a reentrant behavior of the homogeneous nucleation line. The reentrance of these properties is related to the reentrance of the coexistence line at negative pressure, revealing new anomalies of water. The results of this work suggest the possibility of having metastable samples of liquid water for long times at negative pressure provided that heterogeneous nucleation is suppressed.

By using the direct coexistence method, we have calculated the melting points of ice Ih at normal pressure for three recently proposed water models, namely, TIP3P-FB, TIP4P-FB, and TIP4P-D. We obtained Tm = 216 K for TIP3P-FB, Tm = 242 K for TIP4P-FB, and Tm = 247 K for TIP4P-D. We revisited the melting point of TIP4P/2005 and TIP5P obtaining Tm = 250 and 274 K, respectively. We summarize the current situation of the melting point of ice Ih for a number of water models and conclude that no model is yet able to simultaneously reproduce the melting temperature of ice Ih and the temperature of the maximum in density at room pressure. This probably points toward our both still incomplete knowledge of the potential energy surface of water and the necessity of incorporating nuclear quantum effects to describe both properties simultaneously.

In this work, an extension of the Madrid-2019 force field is presented. We have added the cations Rb + and Cs + and the anions F$^-$, Br$^-$ and I$^-$. These ions were the remaining alkaline and halogen ions not previously considered in the Madrid-2019 force field. The force field, denoted as Madrid-2019-Extended, does not include polarizability, and uses the TIP4P/2005 model of water and scaled charges for the ions. A charge of 0.85 e is assigned to monovalent ions. The force field developed provides an accurate description of the aqueous solution densities over a wide range of concentrations up to the solubility limit of each salt studied. Good predictions of viscosity and diffusion coefficients are obtained for concentrations below 2 m. Structural properties obtained with this force field are also in reasonable agreement with the experiment. The number of contact ion pairs has been controlled to be low so as to avoid precipitation of the system at concentrations close to the experimental solubility limit. A comprehensive comparison of the performance for aqueous solutions of alkaline halides of force fields of electrolytes using scaled and integer charges is now possible. This comparison will help in the future to learn about the benefits and limitations of the use of scaled charges to describe electrolyte solutions.

This contribution shows how an appropriate image pre-processing can improve a deep-learning based 3D reconstruction of colon parts. The assumption is that, rather than global image illumination corrections, local under- and over-exposures should be corrected in colonoscopy. An overview of the pipeline including the image exposure correction and a RNN-SLAM is first given. Then, this paper quantifies the reconstruction accuracy of the endoscope trajectory in the colon with and without appropriate illumination correction, Comment: This article has been submitted to GRESTI 2023 for review

Topological insulators feature a number of topologically protected boundary modes linked to the value of their bulk invariant. While in one-dimensional systems the boundary modes are zero dimensional and localized, in two-dimensional topological insulators the boundary modes are chiral, one-dimensional propagating modes along the edges of the system. Thus, topological photonic insulators with large Chern numbers naturally display a topologically protected multimode waveguide at their edges. Here, we show how to take advantage of these topologically protected propagating modes by interfacing them with quantum emitters. In particular, using a Harper-Hofstadter lattice, we find situations in which the emitters feature quasiquantized decay rates due to the increasing number of edge modes, and where their spontaneous emission spatially separates in different modes. We also show how using a single $\pi$-pulse the combination of such spatial separation and the interacting character of the emitters leads to the formation of a single-photon time-bin entangled state with no classical analog, which we characterize computing its entanglement entropy. Finally, we also show how the emitters can selectively interact with the different channels using nonlocal light-matter couplings such as the ones that can be obtained with giant atoms. Such capabilities pave the way for generating quantum gates among topologically protected photons as well as generating more complex entangled states of light in topological channels., Comment: 18 pages, 14 figures. Code available at https://github.com/Carlos-Vega-97/Topological-multi-mode-waveguide-QED

In this contribution we use an ensemble deep-learning method for combining the prediction of two individual one-stage detectors (i.e., YOLOv4 and Yolact) with the aim to detect artefacts in endoscopic images. This ensemble strategy enabled us to improve the robustness of the individual models without harming their real-time computation capabilities. We demonstrated the effectiveness of our approach by training and testing the two individual models and various ensemble configurations on the "Endoscopic Artifact Detection Challenge" dataset. Extensive experiments show the superiority, in terms of mean average precision, of the ensemble approach over the individual models and previous works in the state of the art.