# Alejandro Lage-CastellanosUniversity of Havana · Group of Complex Systems

Alejandro Lage-Castellanos

PhD in Physics

Statistical mechanics, inference, Systems biology, Big Data and population mobility, epidemics, game theory.

## About

36

Publications

8,714

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423

Citations

Introduction

Working on statistical inference and statistical mechanics. Recently also researching on human mobility and epidemiology.

Additional affiliations

September 2005 - present

Education

January 2013 - January 2014

December 2008 - July 2012

September 2005 - April 2008

## Publications

Publications (36)

With social media, the flow of uncertified information is constantly increasing, with the risk that more people will trust low-credible information sources. To design effective strategies against this phenomenon, it is of paramount importance to understand how people end up believing one source rather than another. To this end, we propose a realist...

Population mobility can be studied readily and cheaply using cellphone data, since people's mobility can be approximately mapped into tower-mobile registries. We model people moving in a grid-like city, where edges of the grid are weighted and paths are chosen according to overall weights between origin and destination. Cellphone users leave sparse...

Introduction.
This paper summarizes the contribution by the Technical Group for Modelling and Epidemiology to face COVID-19. The objective was to create knowledge and scientific evidence to support the Government’s decision making, the health system and other sectors.
Methods
. Implementation research from a transdisciplinary perspective was carri...

We apply the recently introduced cavity master equation (CME) to epidemic models and compare it to previously known approaches. We show that CME seems to be the formal way to derive (and correct) dynamic message passing (rDMP) equations that were previously introduced in an intuitive ad hoc manner. CME outperforms rDMP in all cases studied. Both ap...

The ancestral sequence reconstruction problem is the inference, back in time, of the properties of common sequence ancestors from the measured properties of contemporary populations. Standard algorithms for this problem assume independent (factorized) evolution of the characters of the sequences, which is generally wrong (e.g. proteins and genome s...

For the first time in Cuba, we use Location Update records from the mobile phone network to generate origin-destination matrices in Havana. We used 15-days telecom anonymized data from 2020 to approximate trips identified as sequences of cellphone towers. We projected these trips over transport areas and municipalities, and showed the plausibility...

The ancestral sequence reconstruction problem is the inference, back in time, of the properties of common sequence ancestors from measured properties of contemporary populations. Standard algorithms for this problem assume independent (factorized) evolution of the characters of the sequences, which is generally wrong (e.g. proteins and genome seque...

Inverse statistical physics aims at inferring models compatible with a set of empirical averages estimated from a high-dimensional dataset of independently distributed equilibrium configurations of a given system. However, in several applications, such as biology, data result from stochastic evolutionary processes, and configurations are related th...

Inverse statistical physics aims at inferring models compatible with a set of empirical averages estimated from a high-dimensional dataset of independently distributed equilibrium configurations of a given system. However, in several applications such as biology, data result from stochastic evolutionary processes, and configurations are related thr...

We adapt the hybrid mechanistic-statistical approach of Ref. [1] to estimate the total number of undocumented Covid-19 infections in Cuba. This scheme is based on the maximum likelihood estimation of a SIR-like model parameters for the infected population, assuming that the detection process matches a Bernoulli trial. Our estimations show that (a)...

We apply the cavity master equation (CME) approach to epidemics models. We explore mostly the susceptible-infectious-susceptible (SIS) model, which can be readily treated with the CME as a two-state. We show that this approach is more accurate than individual based and pair based mean field methods, and a previously published dynamic message passin...

We present a Bayesian approach for the Contamination Source Detection problem in water distribution networks. Assuming that contamination is a rare event (in space and time), we try to locate the most probable source of such events after reading contamination patterns in few sensed nodes. The method relies on strong simplifications considering bina...

Improved mean-field techniques are a central theme of statistical physics methods applied to inference and learning. We revisit here some of these methods using high-temperature expansions for disordered systems initiated by Plefka, Georges and Yedidia. We derive the Gibbs free entropy and the subsequent self-consistent equations for a generic clas...

Improved mean-field technics are a central theme of statistical physics methods applied to inference and learning. We revisit here some of these methods using high-temperature expansions for disordered systems initiated by Plefka, Georges and Yedidia. We derive the Gibbs free entropy and the subsequent self-consistent equations for a generic class...

We present a Bayesian approach for the Contamination Source Detection problem in Water Distribution Networks. Given an observation of contaminants in one or more nodes in the network, we try to give probable explanation for it assuming that contamination is a rare event. We introduce extra variables to characterize the place and pattern of the firs...

We study the inference of the origin and the pattern of contamination in water distribution networks. We assume a simplified model for the dyanmics of the contamination spread inside a water distribution network, and assume that at some random location a sensor detects the presence of contaminants. We transform the source location problem into an o...

The search of binary sequences with low auto-correlations (LABS) is a discrete combinatorial optimization problem contained in the NP-hard computational complexity class. We study this problem using Warning Propagation (WP) , a message passing algorithm, and compare the performance of the algorithm in the original problem and in two different disor...

We present a new implementation of the Cluster Variational Method (CVM) as a message passing algorithm. The kind of message passing algorithms used for CVM, usually named Generalized Belief Propagation, are a generalization of the Belief Propagation algorithm in the same way that CVM is a generalization of the Bethe approximation for estimating the...

We study two free energy approximations (Bethe and plaquette-CVM) for the
Random Field Ising Model in two dimensions. We compare results obtained by
these two methods in single instances of the model on the square grid, showing
the difficulties arising in defining a robust critical line. We also attempt
average case calculations using a replica-sym...

In these two lectures we shall discuss how the cavity approach can be used
efficiently to study optimization problems with global (topological)
constraints and how the same techniques can be generalized to study inverse
problems in irreversible dynamical processes. These two classes of problems are
formally very similar: they both require an effici...

Mean field-like approximations (including naive mean field, Bethe and Kikuchi
and more general Cluster Variational Methods) are known to stabilize ordered
phases at temperatures higher than the thermodynamical transition. For example,
in the Edwards-Anderson model in 2-dimensions these approximations predict a
spin glass transition at finite $T$. H...

We study several Bayesian inference problems for irreversible stochastic epidemic models on networks from a statistical physics viewpoint. We derive equations which allow us to accurately compute the posterior distribution of the time evolution of the state of each node given some observations. At difference with most existing methods, we allow ver...

Video showing the experimental setup to observe the upstream contamination phenomena. Experiments were carried out in University of Havana, Cuba and Rutgers, New Jersey, USA. Also at http://www.youtube.com/watch?v=Jk-qAIcZk74

It has been known at least since the work of Reynolds and Marangoni in the 1880s that floating particulates strongly affect water surface behaviour, and research involving particle–fluid interactions continues in modern applications ranging from microfluidics and cellular morphogenesis to colloidal dynamics and self-assembly. Here, we report and an...

Dispersion and migration of bacteria under flow in confined structures is related to a large spectrum of practical interests, and lacks a fully satisfactory understanding. We introduce a simple bidimensional continuous model trying to describe the main characteristics of the movement of E. coli along a microchannel. Their convective transport, late...

We study the role played by the dilution in the average behavior of a
perceptron model with continuous coupling with the replica method. We analyze
the stability of the replica symmetric solution as a function of the dilution
field for the generalization and memorization problems. Thanks to a Gardner
like stability analysis we show that at any fixe...

We present and solve the Replica Symmetric equations in the context of the
Replica Cluster Variational Method for the 2D random bond Ising model
(including the 2D Edwards-Anderson spin glass model). First we solve a
linearized version of these equations to obtain the phase diagrams of the model
on the square and triangular lattices. In both cases t...

We study the performance of different message passing algorithms in the two
dimensional Edwards Anderson model. We show that the standard Belief
Propagation (BP) algorithm converges only at high temperature to a paramagnetic
solution. Then, we test a Generalized Belief Propagation (GBP) algorithm,
derived from a Cluster Variational Method (CVM) at...

Starting from a cluster variational method, and inspired by the correctness of the paramagnetic ansatz [at high temperatures in general, and at any temperature in the two-dimensional (2D) Edwards-Anderson (EA) model] we propose a message-passing algorithm--the dual algorithm--to estimate the marginal probabilities of spin glasses on finite-dimensio...

We report the observation of upstream transport of floating particles when
clear water is poured on the surface of a flat water surface on which mate or
chalk particles are sprinkled. As a result, particles originally located only
at the surface of the lower container can contaminate the upper water source by
"riding" on vorticial water currents. W...

We present a general formalism to make the Replica-Symmetric and Replica-Symmetry-Breaking ansatz in the context of Kikuchi’s Cluster Variational Method (CVM). Using replicas and the message-passing formulation of CVM we obtain a variational expression of the replicated free energy of a system with quenched disorder, both averaged and on a single s...

One of the crucial tasks in many inference problems is the extraction of an underlying sparse graphical model from a given number of high-dimensional measurements. In machine learning, this is frequently achieved using, as a penalty term, the Lp norm of the model parameters, with p≤1 for efficient dilution. Here we propose a statistical mechanics a...

We solve the Edwards-Anderson model (EA) in different Husimi lattices. We show that, at T=0, the structure of the solution space depends on the parity of the loop sizes. Husimi lattices with odd loop sizes have always a trivial paramagnetic solution stable under 1RSB perturbations while, in Husimi lattices with even loop sizes, this solution is abs...

We study the stable marriage problem from different points of view. We proposed a microscopic dynamic that led the system to a stationary state that we are able to characterize analytically. Then, we derive a thermodynamical description of the Nash equilibrium states of the system that agree very well with the results of Monte Carlo simulations. Fi...

Sumario. Se presenta el Problema de los Matrimonios junto a algunos resultados y algoritmos. Se define el problema con información incompleta G(c) y se demuestran algunos teoremas que lo hacen equivalente a un problema con información incompleta G'(c=1). Basados en eso calculamos la probabilidad) (c P es de encontrar al menos un estado estable en e...