相关论文: Population synthesis modeling of the X-ray backgro…

We present synthesis models of the X-ray background where the available X-ray observational constraints are used to derive information on the AGN population properties. We show the need for luminous X-ray absorbed AGNs, the QSO2s, in…

X-ray surveys of active galactic nuclei (AGNs) provide direct constraints on the properties of individual AGNs, such as their emission, obscuration, and accretion rate. Previous AGN population synthesis models have not addressed such…

The genetic algorithm is an optimization procedure motivated by biological evolution and is successfully applied to optimization problems in different areas. A statistical mechanics model for its dynamics is proposed based on the…

We have constrained the extragalactic source count distributions over a broad range of X-ray fluxes and in various energy bands to test whether the predictions from X-ray background synthesis models agree with the observational constraints…

In agent-based simulations, synthetic populations of agents are commonly used to represent the structure, behaviour, and interactions of individuals. However, generating a synthetic population that accurately reflects real population…

We will briefly examine the following three issues related to the AGN synthesis models for X-ray background: 1) the possibility that absorbed AGNs evolve faster than unabsorbed ones; 2) the existence of the still debated population of…

Gravitational-wave detection strategies are based on a signal analysis technique known as matched filtering. Despite the success of matched filtering, due to its computational cost, there has been recent interest in developing deep…

Genetic algorithms are modeled after the biological evolutionary processes that use natural selection to select the best species to survive. They are heuristics based and low cost to compute. Genetic algorithms use selection, crossover, and…

The cosmic X-ray background (CXB) is produced by the emission of unresolved active galactic nuclei (AGN), thus providing key information about the properties of the primary and reprocessed X-ray emission components of the AGN population.…

A genetic algorithm (GA) is a search method that optimises a population of solutions by simulating natural evolution. Good solutions reproduce together to create better candidates. The standard GA assumes that any two solutions can mate.…

Evolutionary algorithms, inspired by natural evolution, aim to optimize difficult objective functions without computing derivatives. Here we detail the relationship between population genetics and evolutionary optimization and formulate a…

We propose a genetic algorithm (GA) for hyperparameter optimization of artificial neural networks which includes chromosomal crossover as well as a decoupling of parameters (i.e., weights and biases) from hyperparameters (e.g., learning…

This study proposes a data condensation method for multivariate kernel density estimation by genetic algorithm. First, our proposed algorithm generates multiple subsamples of a given size with replacement from the original sample. The…

This paper presents an optimization technique for the multi-pass face milling process. Genetic algorithm (GA) is used to obtain the optimum cutting parameters by minimizing the unit production cost for a given amount of material removal.…

X-ray spectra of active galactic nuclei (AGN) consist of several different emission and absorption components, which are often fitted manually with models chosen on a case-by-case basis. However, it becomes very hard for a survey with a…

Several computer vision and artificial intelligence projects are nowadays exploiting the manifold data distribution using, e.g., the diffusion process. This approach has produced dramatic improvements on the final performance thanks to the…

We discuss the constraints on the AGN evolution from the cosmic X-ray background and source counts. A synthesis model to fit the X-ray background is presented. In the model, the spectrum of type 2 AGN has been modeled including Compton…

We introduce a Genetic Algorithm (GA) based, open-source project to solve multi-objective optimization problems of materials characterization data analysis including EXAFS, XPS and nanoindentation. The modular design and multiple crossover…

We apply a stochastic method of minimizing the ground state energy in variational calculations of light nuclei using the Refined Resonating Group Model (RRGM). The method utilizes a bit representation of the width parameters to be varied.…

An ideal synthetic population, a key input to activity-based models, mimics the distribution of the individual- and household-level attributes in the actual population. Since the entire population's attributes are generally unavailable,…