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Related Concept Videos

Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
Flame Photometry: Overview01:02

Flame Photometry: Overview

Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Continuous -time Fourier Transform01:11

Continuous -time Fourier Transform

The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
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Related Experiment Video

Updated: May 16, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
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Published on: August 19, 2021

[An automated method to fit stellar continuum based on statistic windows].

Jing-chang Pan1, Xing-xing Wang, Peng Wei

  • 1School of Mechanical, Electrical & Information Engineering, Shandong University at Weihai, Weihai 264209, China. pjc@sdu.edu.cn

Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|November 20, 2012
PubMed
Summary

A new statistical window method accurately fits stellar continuum in spectra. This robust technique improves stellar continuum fitting for astronomical surveys like SDSS and LAMOST.

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Area of Science:

  • Astronomy and Astrophysics
  • Spectroscopy
  • Stellar Astrophysics

Context:

  • Accurate stellar continuum fitting is crucial for analyzing astronomical spectra.
  • Existing methods may struggle with noise and spectral variations.
  • Large astronomical surveys generate vast amounts of spectral data requiring efficient processing.

Purpose:

  • To introduce a novel statistical window-based method for stellar continuum fitting.
  • To enhance the accuracy and robustness of continuum determination in stellar spectra.
  • To provide a reliable method applicable to diverse spectral types.

Summary:

  • A new method divides stellar spectra into statistical windows, selecting flux points based on signal-to-noise ratio.
  • Low-order polynomial iteration fitting is applied to these selected points to derive the stellar continuum.
  • The proposed method demonstrates superior accuracy and robustness compared to existing techniques, particularly for SDSS and LAMOST spectra.

Impact:

  • The method offers improved practical applicability and robustness across various spectral types (excluding M-type).
  • It provides a more accurate stellar continuum, aiding in detailed spectral analysis.
  • Enhances data processing capabilities for large-scale spectroscopic surveys.