Breakthrough Simulation on Quantum Annealing Computer

As we see Moore’s law coming to an end, the next big leap in hardware innovation would appear to come from the quantum computer realm. Though there is a good amount of hype around universal gate quantum computers, it is still at it’s infancy as the best quantum chip is still at 49 qubits, developed by Google. But we do see qubit counts developing in leaps and bounds in the case with quantum annealer computers. D Wave, a Canadian quantum computer company, has the world’s largest commercially available quantum computer with a 2048 qubit count computer. This month, D Wave hits the news again with a breakthrough in quantum simulation on their platforms, paving the way for hybrid systems.
 
D Wave’s quantum computer simulated the 2016 Nobel prize winning equation called the “Kosterlitz–Thouless transition.” This equation basically explains the new state of matter (states of matter being solid, liquid, gas etc.). The importance of this achievement is that it demonstrates how the capabilities of D Waves quantum computers in being able to simulate quantum systems on a large scale. What was once impossible to show on classical computers can now be simulated. This gives chances for other scientific findings that were only provable by paper to be simulated or calculated. 
 
Though this shows the potential of quantum computers, it is important to note that D Wave’s systems are not universal quantum gate computers but rather a quantum annealer. A quantum annealer runs specialized quantum computing algorithms which are used to find solutions to optimization problems as fast as possible. There’s a lot to unpack with that statement so let’s first start with some background. With classical computers, they take a set of inputs (such as ax^2+bx+c) and find a solution (= y). But with quantum computers, they take all the possible inputs or all possible scenarios and outputs all possible outcomes or possibilities.
 
Quantum computers also take bits of information that can be either a 1 or 0 in circulating currents that have corresponding magnetic fields and utilizing the properties of quantum computers, it can be in a superposition of both 1 and 0. In a quantum annealer, the qubit in a superposition will go into either the 1 or 0 state at the end of the calculation. Without annealing, the qubit could go into either state at a 50/50 chance. But by applying a magnetic field to it, it can cause the qubit to bias toward a state, essentially allowing us to control its state.
 
D Waves quantum computer are able to entangle two qubits together by using a coupler. A coupler is going to determine how qubits influence each other. For example you have one qubit be 1 when the other qubit is 1. Or you can even have one qubit be 0 when the other qubit is 1. This give 4 possible states for the qubits(1 and 1, 0 and 0, 1 and 0, 0 and 1). When programming quantum computers, you have a whole set of these qubits coupled in various arrangements, and this will describe an energy landscape. The quantum annealer will find the minimum energy state of that energy landscape.
 
This basically means that its very good a finding a local minimum of a system. So don’t expect quantum annealers to be able to solve Shor’s algorithms. But it is demonstrating the wider range of potential and applications for quantum annealer computers as well as the potential for the universal quantum gate computers (which will have the capability to solve Shor’s algorithms). The achievement also builds the ground work for quantum/classical hybrid algorithms which combine optimization with quantum state calculations. As Andrew King, a researcher at D-Wave reports, “We will soon be in a situation where quantum processors will be used as co-processors in simulations and hybrid algorithms. We have shown a new technique where we can make a chain of computations by putting a classical input state into the quantum processor and performing a quantum evolution on it.”

Original Article: https://www.nextplatform.com/2018/08/23/quantum-simulation-work-blazes-trail-for-hybrid-systems/