The document contains MATLAB code that processes experimental data to solve equations related to roots of polynomials. It loads data files, performs interpolation, and fits a polynomial to the data using least squares fitting. The results are then plotted to visually analyze the roots found for two types of equations over a specified range.

1. %consts
vtransverse=590;
%origin
gamma=1;
%experimental data
load('C:Program FilesMatlabdatadata1Bb.dat');
load('C:Program FilesMatlabdatadata1rb.dat');
load('C:Program FilesMatlabdatadata1R.dat');
time=clock;starttime=(60*time(5)+time(6));
dr=0.001;%new advanced bracket
r = 0:dr:R;
n=(R/dr)+1;
root1=zeros(1,n);
root2=zeros(1,n);
M=10; %max degree of fitted polynom B
Bint=interp1(rb,Bb,r,'spline');
B=polyfit(r,Bint,M); %It ain't a simple MASSIVE
A=zeros(1,M+2);
for i=1:1:M+1
A(i)=B(i)/(M-i+3);
end
A(M+2)=0;
C=zeros(1,M+3);
for i=1:1:M+1
C(i)=gamma*A(i);
end
C(M+2)=-1;
%Solving the first kind equation (root1)
for i=1:1:n
rcur=r(i);
Acur=polyval(A,rcur);
const=rcur*(gamma*Acur+1);
C(M+3)=-const;
preroot=roots(C);
for j=1:1:numel(preroot)
if ((real(preroot(j))>0) && (real(preroot(j))<R) &&
(imag(preroot(j))==0))
root1(i)=preroot(j);
end
end
if (root1(i)==0)
root1(i)=R;
end
end
%Solving the second kind equation (root2)
for i=1:1:n
rcur=r(i);
Acur=polyval(A,rcur);
const=rcur*(gamma*Acur-1);
C(M+3)=-const;
preroot=roots(C);

2. for j=1:1:numel(preroot)
if ((real(preroot(j))>0) && (real(preroot(j))<R) &&
(imag(preroot(j))==0) && (real(preroot(j))>r(i)))
if (root2(i)<real(preroot(j)))
root2(i)=preroot(j);
end
end
end
if (root2(i)==0)
root2(i)=r(i);
end
end
time=clock;endtime=60*time(5)+time(6);
figure(5);plot(r,root1,'bluex',r,root2,'redx');grid on;title(num2str(endtime-
starttime));