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Gdbm database as a semaphor
Gdbm database as a semaphor





gdbm database as a semaphor gdbm database as a semaphor

  • The problem persists if I use GammaRegularized(n,0,2ix) to work with smaller numbers.
  • However, since it does not return any error I do not know if this is the issue.
  • The integrand oscillates more and more the higher $n$ is, and I believe NIntegrate may have problems getting the right answer for highly oscillatory integrands.
  • From external arguments, the values that I am most inclined to trust are those from exact integration for arbitrary a>0 and then numerical evaluation at a=0.1 (the second set of numbers).
  • Assumptions->a>0 is necessary, since for arbitrary $a$ the default solution mathematica returns is valid in the complex plane of $a$ minus the positive real axis.
  • The integral is real, as the imaginary part of the integrand is an odd function of x.
  • What is happening here? Which values are the correct ones? TT = Table/(1 + I a x)^n, Īll these evaluations occur without mathematica returning any errors. If I can get a nice fit that will cover at least 1.5 eV to 3.3 eV in this range, at least it will work. Note that the data received has an energy value between 1.5 eV and 5 eV. But I could not reach a satisfactory result. Worked partially on Tauc-Lorentz approximation. That's why I used a real part of the model.Īs a result, I hoped that the python curve fitting function would give the initial values for the best fit. The reason for this may be that I could not define the Lorentz oscillator formula properly. Then I applied the curve fitting function, but the result was meaningless.

    gdbm database as a semaphor

    For this, I first digitized the received data. In the supplementary material I shared the link of, they said that they could find the nk values of the same material with the 'Gaussian-broadened Lorentz oscillators ("Voigt")' model, but they did not go into details.Īt this point, I first tried to find the best fit using the curve-fitting function in python, but the initial R square value was too high for the PbS-i material. (The brown line represents the fit taken according to the initial values entered.)

    Gdbm database as a semaphor how to#

    I tried the Lorentz oscillator model, but because I didn't know how to determine the initial conditions, I made random trials of initial values for hours, but I couldn't get a result. But I could not succeed in any kind of modeling of the PbS-i material. For example, for ZnO, the Cauchy fit and the data matched and the least square value was below 1. In addition, the function to be fitted varies greatly according to the received data. But the main thing is determining the initial condotions.

    gdbm database as a semaphor

    I need to be able to extract the n and k values from the graph created by these data points.įor this, I use the application of ellipsometry called EllyReg. But ellipsometry gives me data of psi and delta parameters or dielectric function. Halil İbrahim Çetin Asks: How can I determine the initial conditions for the fit applied to the data obtained from the ellipsometry measurement?įor thin film solar cells, I need to know the refractive and extinction coeffiecients of these materials in order to make optical calculations of some materials on the computer.įor this I had to use the ellipsometry device.







    Gdbm database as a semaphor