Computation techniques for magnetic resonance, ranging from the basics of 1D spectra to many-spin systems and machine learning methods

Computation simulation of spin systems has a rich history in magnetic resonance, and is a powerful tool for predicting behavior, interpreting data, and discovering new experimental techniques. In this section, blogs will present functions for simulating basic magnetic resonance experiments in multiple  coding languages, techniques for developing more complex algorithms, and introduce a framework for utilizing machine learning to approach problems in spin physics. 

#include <stdio.h>

int main() {
    for(int i = 1; i <= 10; i++) {
        printf("%d\n", i);
    }
    return 0;
}

#include <iostream>

int main() {
    for(int i = 1; i <= 10; i++) {
        std::cout << i << std::endl;
    }
    return 0;
}

for i in 1..10
  puts i
end

<?php
for ($i = 1; $i <= 10; $i++) {
    echo $i . "\n";
}
?>

for (let i = 1; i <= 10; i++) {
    console.log(i);
}