A machine learning approach for fighting the curse of dimensionality in global optimization

Finding global optima in high-dimensional optimization problems is extremely challenging since the number of function evaluations required to sufficiently explore the search space increases exponentially with its dimensionality. Furthermore, multimodal cost functions render local gradient-based search techniques ineffective. To overcome these difficulties, we propose to trim uninteresting regions of the search space where global optima are unlikely to be found by means of autoencoders, exploiting the lower intrinsic dimensionality of certain cost functions; optima are then searched over lower-dimensional latent spaces. The methodology is tested on benchmark functions and on multiple variations of a structural topology optimization problem, where we show that we can estimate this intrinsic lower dimensionality and based thereon obtain the global optimum at best or superior results compared to established optimization procedures at worst.Comment: Main text 36 pages, 6 figures, currently submitted to science advance

Conformal mapping of ultrasonic crystals: confining ultrasound and cochlear-like wave guiding

Conformal mapping of a slab of a two-dimensional ultrasonic crystal generate a closed geometrical arrangement of ultrasonic scatterers with appealing acoustic properties. This acoustic shell is able to confine ultrasonic modes. Some of these internal resonances can be induced from an external wave source. The mapping of a linear defect produces a wave-guide that exhibits a spatial-frequency selection analogous to that characteristic of a synthetic "cochlea". Both, experimental and theoretical results are reported here.Comment: 4 pages, 4 figure

Data driven flavour model

A bottom-up approach has been adopted to identify a flavour model that agrees with present experimental measurements. The charged fermion mass hierarchies suggest that only the top Yukawa term should be present at the renormalisable level. Similarly, describing the lightness of the active neutrinos through the type-I Seesaw mechanism, right-handed neutrino mass terms should also be present at the renormalisable level. The flavour symmetry of the Lagrangian including the fermionic kinetic terms and only the top Yukawa is then a combination of U(2) and U(3) factors. Once considering the Majorana neutrino terms, the associated symmetry is O(3). Lighter charged fermion and active neutrino masses and quark and lepton mixings arise considering specific spurion fields à la Minimal Flavour Violation. The associated phenomenology is investigated and the model turns out to have almost the same flavour protection as the Minimal Flavour Violation in both quark and lepton sectors. Promoting the spurions to dynamical fields, the associated scalar potential is also studied and a minimum is identified such that fermion masses and mixings are correctly reproduced. Very precise predictions for the Majorana phases follow from the minimisation of the scalar potential and thus the neutrinoless-double-beta decay may represent a smoking gun for the model

Estudio de tendencias de mercado - Mango

En un contexto donde la demanda por el mango está en crecimiento y la productividad sufre una contracción motivada por la pandemia del COVID-19 y factores climáticos, es necesario establecer las pautas para direccionar los esfuerzos de los productores y el Estado, articular estrategias conjuntas y promover la investigación e innovación que permitan atender las nuevas tendencias del mercado en el cultivo del mango. Estas tendencias se ven influenciadas por los cambios en el entorno y los procesos que buscan satisfacer las necesidades de los consumidores desde todas sus posibles perspectivas. En ese sentido, el desafío de los empresarios, productores y el gobierno es identificar y analizar dichas tendencias para poder adecuarse a ellas

Addressing Practical Issues in Designing Weather Insurance Contracts for Risk Management Applications in Developing Countries

In this dissertation we address practical issues in designing weather insurance contracts for risk management in developing countries in three different scenarios. First, we develop an innovative contract design strategy based on agronomic considerations that can be implemented in situations where only short and/or aggregate data series are available. We attempt to mitigate both the aggregate nature of yield data and the need for data-demanding analysis by looking at areas sharing the same growing conditions and using agronomic requirements to specify contract parameters. We find that the proposed contracts do not achieve the same degree of risk reduction as the contracts that can be constructed using no data limitations, but they do provide meaningful risk protection and typically at lower premiums. The implication is that the proposed methodology can be used to design weather derivatives for developing countries, where paucity of data often renders the conventional design approaches unworkable. The second essay aims to derive a general-form optimal payoff of an index contract that takes into account potentially nonlinear dependence between the index underlying the contract and the loss that is insured. We find that the quasi-linear contract payoff structure may not be the optimal choice if the dependence between the index and the yield/revenue is nonlinear. The implication is that the proposed methodology can help to improve risk-reducing capabilities of weather derivatives particularly in situations where the effect of weather on yield is complex and not obvious. The third essay analyzes the use of weather derivatives in managing water supply risk arising in making water allocation decisions. The specific application is developed for the Alto Rio Lerma Irrigation District (ARLID) in the state of Guanajuato in Mexico. We argue that incorporation of weather derivatives in water allocation decisions can improve overall well-being of producers and allow shift water allocations from the wet to the dry season with the assumption that the wet season farmers can cope with the risk of water shortages by using weather derivatives. We find that use of weather derivatives does lead to better water allocation policies that allow the representative farmer to reach higher levels of utility. The implication is that introduction of weather derivatives can help to improve water management decisions in developing countries where agriculture heavily depends on irrigation and can be severely affected by extreme weather events