Cannot interpret pca results

Hello everyone. I have generated a code which transforms a stochastic process making it dependant on uncorrelated random variables. However, the result doesn't look like the input at all. Can someone tell me why my score coefficient doesn't look like my input argument S?

if true
  V = unifrnd(1,2,1,10000);
A = betarnd(2,2,1,10000);
t=50;
for i=1:t
  S(i,:)=V*i+0.5*A*i^2;
  theoreticalmeanS(i)=3/2*i+1/4*i^2;
  meanS(i)=mean(S(i));
end
[coeff, score, latent]=pca(S');
scoreT=score';
figure('Name', 'coeff, principal component eigenvectors')
hold on
for i=1:t
  plot(coeff(:,i))
end
figure
hold on
plot(S)
figure
hold on
plot(scoreT)

end

Thanks for reading.