Thermodynamic bound on quantum state discrimination

We show that the second law of thermodynamics poses a restriction on how well we can discriminate between quantum states. By examining an ideal gas with a quantum internal degree of freedom undergoing a cycle based on a proposal by Asher Peres, we establish a non-trivial upper bound on the attainable accuracy of quantum state discrimination. This thermodynamic bound, which relies solely on the linearity of quantum mechanics and the constraint of no work extraction, matches Holevo's bound on accessible information, but is looser than the Holevo-Helstrom bound. The result gives more evidence on the disagreement between thermodynamic entropy and von Neumann entropy, and places potential limitations on proposals beyond quantum mechanics.Comment: 11 pages, 4 figures. RevTeX 4.

Teoría del grado de Brouwer-Kronecker

En este trabajo se estudian los elementos básicos de la teoría del grado de Brouwer-Kronecker. Se demuestran los resultados de existencia de difeotopías y de aproximación de aplicaciones continuas (propias) con homotopía que permiten definir consistentemente el grado de una aplicación suave y su extensión a aplicaciones continuas, respectivamente. La invariancia por homotopía del grado se utiliza para probar varios resultados topológicos profundos incluyendo el teorema de Borsuk-Hirsch sobre el grado de aplicaciones pares e impares en esferas y el de Jordan-Brouwer sobre la desconexión de espacios afines por hipersuperficies

Real time updating of the flood frequency distribution through data assimilation

We explore the memory properties of catchments for predicting the likelihood of floods basing on observations of average flows in pre-flood seasons. Our approach assumes that flood formation is driven by the superimposition of short and long term perturbations. The former is given by the short term meteorological forcing leading to infiltration and/or saturation excess, while the latter is originated 15 by higher-than-usual storage in the catchment. To exploit the above sensitivity to long term perturbations a Meta-Gaussian model is implemented for updating a season in advance the flood frequency distribution, through a data assimilation approach. Accordingly, the peak flow in the flood season is predicted by exploiting its dependence on the average flow in the antecedent seasons. We focus on the Po River at Pontelagoscuro and the Danube river at Bratislava. We found that the shape of 20 the flood frequency distribution is significantly impacted by higher-than-usual flows occurred up to several months earlier. The proposed technique may allow one to reduce the uncertainty associated to the estimation of flood frequenc

Long term prediction of flood occurrence

How long a river remembers its past is still an open question. Perturbations occurring in large catchments may impact the flow regime for several weeks and months, therefore providing a physical explanation for the occasional tendency of floods to occur in clusters. The research question explored in this paper may be stated as follows: can higher than usual river discharges in the low flow season be associated to a higher probability of floods in the subsequent high flow season? The physical explanation for such association may be related to the presence of higher soil moisture storage at the beginning of the high flow season, which may induce lower infiltration rates and therefore higher river runoff. Another possible explanation is persistence of climate, due to presence of long-term properties in atmospheric circulation. We focus on the Po River at Pontelagoscuro, whose catchment area amounts to 71 000 km2. We look at the stochastic connection between average river flows in the pre-flood season and the peak flows in the flood season by using a bivariate probability distribution. We found that the shape of the flood frequency distribution is significantly impacted by the river flow regime in the low flow season. The proposed technique, which can be classified as a data assimilation approach, may allow one to reduce the uncertainty associated to the estimation of the flood probability

Conocimientos puestos en juego por futuros profesores de matemáticas cuando justifican la selección de tareas

En algunos planes de formación de profesores, el profesor aprende a manejar herramientas conceptuales y metodológicas para elaborar propuestas docentes. En este artículo, identificamos los tres tipos de conocimiento que los futuros profesores que participaron en un plan de formación de ese tipo utilizaron cuando justificaron su propuesta docente: uno relacionado con las herramientas, otro con elementos transversales del plan de formación y un tercer tipo de conocimiento ajeno al plan de formación. Constatamos que el conocimiento relacionado con las herramientas es dominante, se entremezcla con los otros dos tipos de conocimiento y se enuncia de forma ajena a la propia matemática

Argumentos que utilizan los futuros profesores cuando seleccionan tareas matemáticas

En algunos planes de formación de profesores de matemáticas se proporciona al profesor herramientas conceptuales y metodológicas, que llamaremos organizadores del currículo, para que analice y seleccione tareas matemáticas. En este artículo, analizamos los argumentos que emplean futuros profesores en un plan de formación de ese tipo cuando seleccionan tareas. Encontramos que sus argumentos hacen referencia a tres tipos de conocimiento: uno directamente relacionado con los organizadores, otro relacionado con elementos transversales incluidos en el plan de formación y un tercero ajeno al plan. Analizando esta clasificación, encontramos que hay un desarrollo muy desigual de los distintos organizadores, que los argumentos relacionados con los organizadores son dominantes pero se entremezclan con los demás y que, aún cuando se refieren a tareas matemáticas concretas, con frecuencia se enuncian en términos generales ajenos a la tarea analizada

Machine learning quantum field theory with local probes

We propose the use of machine learning techniques to address the problem of local measurements in quantum field theory. In particular we discuss how neural networks can efficiently process measurement outcomes from local probes to determine both local and non-local features of the quantum field. As toy examples we show: a) how a particle detector distinguishes boundary conditions imposed on the field without the need of signals propagating from them, and b) how detectors can determine the temperature of the quantum field without thermalizing with it. We discuss how the formalism proposed can be used for any kind of local measurement on a quantum field and, by extension, to local measurements of non-local features in many-body quantum systems.Comment: 9 pages (4 pages of appendices), 2 Figures, RevTeX 4.

Real Decreto 268/2022, de 12 de abril, por el que se modifica el Real Decreto 190/1996, de 9 de febrero, por el que se aprueba el Reglamento Penitenciario [BOE-A-2022-6046]

[ES]Crónica de legislación. Derecho procesa

Comparison between Snow Albedo Obtained from Landsat TM, ETM+ Imagery and the SPOT VEGETATION Albedo Product in a Mediterranean Mountainous Site

Albedo plays an important role in snow evolution modeling quantifying the amount of solar radiation absorbed and reflected by the snowpack, especially in mid-latitude regions with semiarid conditions. Satellite remote sensing is the most extensive technique to determine the variability of snow albedo over medium to large areas; however, scale effects from the pixel size of the sensor source may affect the results of snow models, with different impacts depending on the spatial resolution. This work presents the evaluation of snow albedo values retrieved from (1) Landsat images, L (16-day frequency with 30 30 m pixel size) and (2) SPOT VEGETATION albedo products, SV (10-day frequency with 1 1 km pixel size) in the Sierra Nevada mountain range in South Spain, a Mediterranean site representative of highly heterogeneous conditions. Daily snow albedo map series were derived from both sources, and used as input for the snow module in the WiMMed (Watershed Integrated Management in Mediterranean Environment) hydrological model, which was operational at the study area for snow monitoring for two hydrological years, 2011–2012 and 2012–2013, in the Guadalfeo river basin in Sierra Nevada. The results showed similar albedo trends in both data sources, but with different values, the shift between both sources being distributed in space according to the altitude. This difference resulted in lower snow cover fraction values in the SV-simulations that affected the rest of snow variables included in the simulation. This underestimation, mainly due to the effects of mixed pixels composed by both snow and snow-free areas, produced higher divergences from both sources during the melting periods when the evapo-sublimation and melting fluxes are more relevant. Therefore, the selection of the albedo data source in these areas, where snow evapo-sublimation plays a very important role and the presence of snow-free patches is very frequent, can condition the final accuracy of the simulations of operational models; Landsat is the recommended source if the monitoring of the snowpack is the final goal of the modeling, whereas the SV product may be advantageous when water resource planning in the medium and long term is intended. Applications of large pixel size albedo sources need further assessment for short-term operational objective