On the self-consistency of evolutionary synthesis models
نویسنده
چکیده
Evolutionary synthesis models have been used to study the physical properties of unresolved populations in a wide range of scenarios. Unfortunately, their self-consistency are difficult to test and there are some theoretical open questions without an answer: (1) The change of the homology relations assumed in the computation of isochrones due to the effect of stellar winds (or rotation) and the discontinuities in the stellar evolution are not considered. (2) There is no a consensus about how the isochrones must be integrated. (3) The discreteness of the stellar populations (that produce an intrinsic statistical dispersion) usually are not taken into account, and model results are interpreted in a deterministic way instead a statistical one... The objective of this contribution is to present some inconsistencies in the computation and some cautions in the application of the results of such codes.
منابع مشابه
Optimization of sediment rating curve coefficients using evolutionary algorithms and unsupervised artificial neural network
Sediment rating curve (SRC) is a conventional and a common regression model in estimating suspended sediment load (SSL) of flow discharge. However, in most cases the data log-transformation in SRC models causing a bias which underestimates SSL prediction. In this study, using the daily stream flow and suspended sediment load data from Shalman hydrometric station on Shalmanroud River, Guilan Pro...
متن کاملPopulation Synthesis and the Diagnostics of High-redshift Galaxies
The effect of redshift on the observation of distant galaxies is briefly discussed emphasizing the possible sources of bias in the interpretation of high-z data. A general energetic criterion to assess physical self-consistency of evolutionary population synthesis models is also proposed, for a more appropriate use of this important tool to investigate distinctive properties of primeval galaxies.
متن کاملSoft Computing Methods based on Fuzzy, Evolutionary and Swarm Intelligence for Analysis of Digital Mammography Images for Diagnosis of Breast Tumors
Soft computing models based on intelligent fuzzy systems have the capability of managing uncertainty in the image based practices of disease. Analysis of the breast tumors and their classification is critical for early diagnosis of breast cancer as a common cancer with a high mortality rate between women all around the world. Soft computing models based on fuzzy and evolutionary algorithms play...
متن کاملVerification of an Evolutionary-based Wavelet Neural Network Model for Nonlinear Function Approximation
Nonlinear function approximation is one of the most important tasks in system analysis and identification. Several models have been presented to achieve an accurate approximation on nonlinear mathematics functions. However, the majority of the models are specific to certain problems and systems. In this paper, an evolutionary-based wavelet neural network model is proposed for structure definiti...
متن کاملPredicting ε50 for Lateral Behavior of Piles in Marine Clay Using an Evolutionary Based Approach
Analyzing piles subjected to lateral loads significantly depends on soil resistance at any point along the pile as a function of pile deflection, known as p-y curve. On the other hand, the deformation characteristics of soil defined as “the soil strain at 50% of maximum deviatoric stress (ε50)” has considerable effect on the generated p-y curve. In this research, several models are proposed to ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002