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Exploring quantum localization with machine learning
No full textWe introduce an efficient neural network (NN) architecture for classifying wave functions in terms of their localization (probability concentration) in a specific region of the quantum phase space. Our approach integrates a versatile quantum phase space parametrization leading to a custom "quantum" NN, with the pattern recognition capabilities of a modified convolutional model. This design accepts wave functions of any dimension as inputs and makes accurate predictions at an affordable computational cost. This scalability becomes crucial to explore the localization rate at the semiclassical limit -i.e. at large Hilbert space dimensions = (2ℏ)−1– a long standing question in the quantum scattering field. Moreover, the physical meaning built in the model allows for the interpretation of the learning process.This research has also been partially funded by the Spanish Ministry of Science, Innovation and Universities, Gobierno de España under Contract No. PID 2021-122711NB-C21
Hacia un nuevo diccionario monolingüe en ELE
No full textPrograma de Doctorado en Humanidades por la Universidad Carlos III de MadridPresidenta: María Pilar Garcés Gómez.- Secretario: Antoni Nomdedeu Rull.- Vocal: Cecilio Garriga Escriban
Los Bardem. Sagas y estudios de familia en el cine español de la democracia
No full textMención Internacional en el título de doctorLas sagas familiares del espectáculo han circulado en el debate social y cultural de los últimos años, tanto en el panorama nacional como internacional. Apodados a veces como nepo babies o “hijos del nepotismo”, no son pocas las publicaciones del ámbito periodístico que han tratado de abordar el comentario sobre las familias de la escena. Entiéndase, varias generaciones de una familia que han trabajado en oficios similares dentro del campo de las industrias culturales. A pesar de constituirse como una columna vertebral del teatro y cine y remontarse al menos dos siglos atrás, la literatura académica no ha abordado en profundidad el fenómeno de las sagas o dinastías familiares como objeto cultural y simbólico. En este sentido, este estudio propone el análisis social y cultural de las sagas familiares del teatro y cine españoles del siglo XX a partir del caso concreto de la familia Bardem-Muñoz. Juan Antonio, Pilar y Javier Bardem son tres de los profesionales más laureados de nuestra industria. No obstante, existe una realidad mayor que los identifica y que pasa por reconocerlos como parte de una saga familiar del espectáculo que se remonta al siglo XIX y que consta de más de diez miembros y tres ramificaciones dedicadas a la escena. Este trabajo pretende abordar el estudio de la saga Bardem-Muñoz a partir del cruce de los estudios fílmicos con otras disciplinas como la sociología y la historiografía. Tomando como referencia las teorías sobre la movilidad social de Pierre Bourdieu y las últimas aportaciones sobre memoria familiar colectiva, se concibe a la saga como una entidad capaz de legar una serie de capitales de índole económico, cultural, social y simbólico para reproducirse en un oficio determinado a lo largo de generaciones. Además de rastrear la historia profesional de los Bardem y las Muñoz Sampedro, se pretende analizar la manera en la que la familia ha construido una suerte de memoria identitaria o marca de su apellido que, en último término, funciona como activo simbólico en el que legitimarse. En este sentido, esta investigación pretende aportar nuevas miradas a los estudios de intercambios e hibridaciones en el ámbito de las industrias culturales, en especial a las interrelaciones entre el teatro y cine del siglo XX. Las sagas familiares y el caso de estudio concreto suponen un eje transversal más que ha configurado la realidad de la escena y el espectáculo españoles del último siglo.Family dynasties of the show business have been circulating in the social and cultural debate in recent years, both on the national and international scene. Sometimes referred to as nepo babies or ‘children of nepotism’, not a few publications in the field of journalism have tried to address the commentary on the families of the stage. That is, several generations of a family that have worked in related crafts within the field of cultural industries. Despite constituting a central backbone of theatre and cinema and going back at least two centuries, the academic literature has not dealt in depth with the phenomenon of family dynasties as a cultural and symbolic object. In this sense, this study proposes a social and cultural analysis of family dynasties in 20th century Spanish theatre and cinema based on the specific case of the Bardem Muñoz family. Juan Antonio, Pilar and Javier Bardem are three of the most successful professionals in our industry. However, there is a greater reality that identifies them and that involves acknowledging them as part of a family dynasty of show business that dates back to the 19th century and consists of more than ten members and three branches dedicated to the stage. This work aims to approach the study of the Bardem-Muñoz dynasty by crossing film studies with other disciplines such as sociology and historiography. Taking as a reference Pierre Bourdieu’s theory on social mobility and the latest contributions on collective family memory, the dynasty is conceived as an entity capable of bequeathing a series of economic, cultural, social and symbolic capitals in order to reproduce itself in a given craft over the course of generations. In addition to tracing the professional history of the Bardem and Muñoz Sampedro families, the objective is to analyse the way in which the family has constructed a form of identity memory or brand of their surname which, ultimately, functions as a symbolic asset to legitimise themselves. In this sense, this research aims to provide new insights into studies of exchanges and hybridisations in the field of cultural industries, especially the interrelations between theatre and cinema in the twentieth century. The family dynasties and the specific case study represent one more transversal axis that has shaped the reality of the Spanish stage and the entertainment business of the last century.Programa de Doctorado en Investigación en Medios de Comunicación por la Universidad Carlos III de MadridPresidente: Joaquín Tomás Cánovas Belchi.- Secretaria: María Carmen Ciller Tenreiro.- Vocal: Ralf Junkerjürge
Correction-to-scaling exponent for percolation and the Fortuin-Kasteleyn Potts model in two dimensions
Full text linkThe number ns of clusters (per site) of size s, a central quantity in percolation theory, displaysat criticality an algebraic scaling behavior of the form ns ≃ s−τ A(1 + Bs−Ω). For the Fortuin–Kasteleyn representation of the Q-state Potts model in two dimensions, the Fisher exponent τ is known as a function of the real parameter 0 ≤ Q ≤ 4, and, for bond percolation (the Q → 1 limit), the correction-to-scaling exponent is derived as Ω = 72/91. We derive theoretically the exact formula for the correction-to-scaling exponent Ω = 8/[(2g + 1)(2g + 3)] as a function of the Coulomb-gas coupling strength g, which is related to Q by Q = 2 + 2 cos(2πg). Using an efficient Monte Carlo cluster algorithm, we study the O(n) loop model on the hexagonal lattice, which is in the same universality class as the Q = n2 Potts model, and has significantly suppressed finite-size corrections and critical slowing-down. The predictions of the above formula include the exact value for percolation as a special case and agree well with the numerical estimates of Ω for both the critical and tricritical branches of the Potts model.This work has been supported by the National Natural Science Foundation of China (under Grant No. 12275263), the Innovation Program for Quantum Science and Technology (under grant No. 2021ZD0301900), the Natural Science Foundation of Fujian Province of China (under Grant No. 2023J02032)
Upper-tail sampling correction technique for engineering design
Full text linkEngineering design must fulfill various requirements to guarantee the safety and functionality of structures. Often, critical conditions are associated with extreme events, such as floods or extreme winds. Therefore, a thorough analysis of these extreme conditions is essential to ensure structural reliability. Typically, designing structures involves generating sampled data based on historical records. However, it is frequent that this sampled data does not accurately represent the extreme-event regime observed historically. To address this issue, it is necessary to introduce an upper-tail sampling correction technique that effectively models extreme regimes, thereby reducing associated risks. This paper proposes a straightforward correction method and demonstrates its application through various examples, illustrating how the methodology aligns sampled extreme values more closely with historical data
Simulations for the precise modeling of exercises including time, grades and number of attempts
Full text linkStudents interactions with exercises can reveal interesting features that can be used to redesign or effectively use the exercises during the learning process. The precise modeling of exercises includes how grades can evolve,depending on the number of attempts and time spent on the exercises. A missing aspect is how a precise relationship among grades, number of attempts,and time spent can be inferred from student interactions with exercises using machine learning methods and how it differs depending on different factors. In this paper, we analyzed the application of different machine learning methods for modeling different scenarios: varying the probability of answering correctly, dataset sizes, and distributions. The results showed that the model converged when the probability of random guessing was not high. For exercises with an average of 2 attempts, the model converged to 200 interactions. However, as the number of attempts required increased;interactions also increased the different behaviors of the simulated students did not affect the accuracy of the model.This work was supported in part by the FEDER/Ministerio de Ciencia, Innovación y Universidades–Agencia Estatal de Investigación, through the Smartlet Project under Grant TIN2017-85179-C3-1-R and the H2O Learn Project under Grant PID2020-112584 RB-C31, in part by the Madrid Regional Government through the e-Madrid-CM Project under Grant S2018/TCS-4307 a project which is co-funded by the European Structural Funds (FSE and FEDER)
From Podcasts to Protests: Examining the Influence of Podcasts and Misinformation on Contentious Political Participation
No full textAs distrust in mainstream media rises, audiences increasingly turn toward alternative news sources. This study examines the impact of alternative non-mainstream podcast news use on contentious political participation through misinformation belief and sharing. Findings from a sample of US adults (N = 797) indicate that alternative nonmainstream podcast news use is significantly associated with misinformation belief and sharing. In addition, alternative non-mainstream podcast news use is related to an increase in contentious political participation through misinformation sharing only. Ultimately, we find that political identity strength moderates the relationship between alternative non-mainstream podcast news use and contentious political participation only through misinformation belief
Aluminum and Inorganic Natural Pigment Colored Composites by Powder Metallurgy Forming
No full textAluminum powder, along with other powders such as steel or stainless steel, is extensively used in powder metallurgy (PM) to produce complex samples with irregular geometric shapes. PM enables the incorporation of fillers to modify the physical, mechanical, or wear properties of aluminum without melting, thereby preventing phase segregation. The novelty of this work lies in the use of inorganic natural pigments (INPs). The primary goal of this study is to produce colored aluminum samples via PM without compromising their mechanical properties. INPs are first characterized to select those with the highest heat resistance. The composites are fabricated with different pigments (10 wt%), formed through uniaxial compaction at 500 MPa, and sintered in a nitrogen atmosphere at 610 degrees C for 30 min. Density, color, bending strength, and wear are evaluated to identify the most suitable pigment for gas kitchen burners. Mars red, Cobalt blue, and Chrome green pigments provide the best coloration. Dimensional variation is generally less than 1%. The pigments increase the material's brittleness by 41% to 77%, resulting in a bending modulus increase of up to 160% and deformation reduction of up to 70%. In some cases, intermetallic compounds improve bending strength, as in Al-Chrome green, by 30%. Al¿Chrome green exhibits wear resistance comparable to aluminum, with a 40% lower friction coefficient. X-ray diffraction and SEM-EDX confirm AlCr and AlCo intermetallic particles. Thermal stability is verified after 160 heating and cooling cycles without significant material degradation
Forecasting the yield curve: the role of additional and time-varying decay parameters, conditional heteroscedasticity, and macro-economic factors
Full text linkIn this article, we analyse the forecasting performance of several parametric extensions of the popular Dynamic Nelson Siegel (DNS) model for the yield curve. Our focus is on the role of additional and time-varying decay parameters, conditional heteroscedasticity, and macroeconomic variables. We also consider the role of several popular restrictions on the dynamics of the factors. Using a novel dataset of end-of-month continuously compounded Treasury yields on US zero-coupon bonds and frequentist estimation based on the extended Kalman filter, we show that a second decay parameter does not contribute to better forecasts. In concordance with the preferred habitat theory, we also show that the best forecasting model depends on the maturity. For short maturities, the best performance is obtained in a heteroscedastic model with a time-varying decay parameter. However, for long maturities, neither the time-varying decay nor the heteroscedasticity plays any role, and the best forecasts are obtained in the basic DNS model with the shape of the yield curve depending on macroeconomic activity. Finally, we find that assuming non-stationary factors is helpful in forecasting at long horizons.Joao Caldeira gratefully acknowledges support provided by CNPq under Grant 309448/2022-0. Esther Ruiz acknowledges financial support from the Spanish Agencia Estatal de Investigación through project PID2022-139614NB-C22. André Santos acknowledges the financial support from the Comunidad de Madrid Government through project 2022-T1/SOC-24167 and Spanish Agencia Estatal de Investigación through project PID2022-138289NB-I00
Novel Methodology for Integrated Actuator and Sensors Fault Detection and Estimation in an Active Suspension System
No full textIn recent years, there has been a great deal of interest in the development of fault detection and isolation (FDI) techniques because they have been found to be important in road transport systems to ensure safe operation, reliability, and maintainability. Active suspension systems (ASSs) play an important role in passengers vehicles, especially in autonomous vehicles, because they can adapt based on the information provided by on-board sensors, thereby improving passengers' comfort and safety. However, the possible occurrence of faults in critical components, such as actuators and sensors requires robust fault diagnosis schemes to ensure good system performance and reliability. Numerous investigations exist on identification and estimation of sensor and actuator faults in ASSs, but faults in both types of components are never considered. This article proposes a new fault diagnosis scheme that allows integrated detection and estimation of actuator and sensors faults in ASSs. The proposed methodology uses two unknown input observers (UIOs) to estimate actuator faults and sensor faults separately. To avoid coupling between the estimations, it is also proposed a switch off mechanism for the actuator so that the coupled deflection sensor and actuator faults can be distinguished and isolated. Finally, signal flags are generated to distinguish the faulty suspension component and refine the UIO estimations.This work was supported in part by MCIN/AEI/
10.13039/501100011033 under Grant [PID2022-136468OB-I00] and in part by the “ERDF A way of making Europe.