Quantum computing is still in its infancy, even though the idea of a quantum computer was developed some thirty years ago. But there are a whole load of pioneering organizations (like Google) that are exploring how this potentially revolutionary technology could help them solve complex problems that modern-day computers just aren’t capable of doing at any useful speed.
One such organization is NASA, whose use of D-Wave Systems quantum computing machines is helping it research better and safer methods of space travel, air traffic controls and missions involving sending robots to far-off places, explained Davide Venturelli, a science operations manager at NASA Ames Research Center, Universities Space Research Association. I’ll be speaking with Venturelli on stage at Structure Data 2015 from March 18-19 in New York City and we’ll be sure to cover how NASA envisions the future of quantum computing.
The basic idea of quantum computing is that quantum bits, or qubits — which can exist in more than two states and be represented as both a 0 and 1 simultaneously — can be used to greatly boost computing power compared to even today’s most powerful super computers. This contrasts with the modern-day binary computing model, in which the many transistors contained in silicon chips can be either switched on or off and can thus only exist in two states, expressed as a 0 or 1.
With the development of D-Wave Systems machines that have quantum computing capabilities (although researchers argue they are not true quantum computers along the lines of the ones dreamed up on pen and paper in the early 1980s), scientists and engineers can now attempt to solve much more complex tasks without having to perform the type of experiments used to generate quantum phenomena, explained Venturelli. However, these machines are just the tip of the quantum iceberg, and Venturelli still pays attention to ground-breaking research that may lead to better quantum devices.
NASA hopes to use the machines to solve optimization problems, which in its most basic terms means finding the best solution out of many solutions. One such example of an optimization problem NASA has focussed on deals with air-traffic management in which scientists try to “optimize the routes” of planes in order to “make sure the landing and taking off of airplanes in terminals are as efficient as possible,” said Venturelli. If the scientists are able to route air traffic in the best possible way, there’s a good chance they can reduce the dangers of congested skies.
NASA also wants to use quantum computing to help with automated planning and scheduling, a subset of artificial intelligence that NASA uses to plan out robotic missions to other planets. NASA typically plans out these type of endeavors ten years in advance, said Venturelli.
The goal is to plan out the mission of the robots far in advance because realtime communication with the robots just isn’t feasible given how far away other planets are from the Earth. Using quantum optimization, NASA scientists will have new tools to basically forecast what may occur during the mission and what would be the best possible plan of attack for the robots to do their work.
“We have some missions where we imagine sending multiple robots to planets and these robots will need to coordinate and will need to do operations like landing and such without realtime communication,” said Venturelli.
Scientists need to “maximize the lifetime of the batteries” used by the robots as they perform tasks on the planets that may include drilling or using infrared thermometers to record temperatures, so careful planning of how the robots do their tasks is needed in order to ensure that no time is wasted. This all involves a lot of variables that normal computers just aren’t up-to-speed to process and could be a fit for quantum computing.
“[The robot] has to figure out what is the best schedule and figure out if he can recharge and when to go in a region where it is dark and a region where there is water,” said Venturelli. “We need to preplan the mission.”