Before we get to the IBM solution to these hurdles, let's look at the problem they were solving. IBM was simulating the Ising model, a "mathematical description of ferromagnetism consisting of discrete variables that represent magnetic dipole moments of atomic "spins" that can be in one of two states (+1 or ?1)." They hoped to calculate the average magnetization of this system. Such a complex and interconnected problem is ideal for quantum computers to handle, since it can be efficiently mapped onto a quantum computer's qubits. The Ising model has been used to study a wide variety of physical phenomena, including ferromagnetism, antiferromagnetism, liquid-gas phase transitions, and protein folding. It has also been used in computer science to study problems such as optimization and machine learning.