Why quantum computing?
So-called classical computing uses the binary data unit of a bit whose value can only be 0 or 1. In the early 1980s, Nobel laureate Richard Feynman pictured the idea of imitating complex physical systems such as molecules and materials using simpler artificial systems based on qubits instead of bits. Thus, quantum computing was born. By varying all the parameters (a distance of atoms, the force of interactions, level of energy) that are not adjustable in real systems, we can model the dynamics of these systems and thus better understand them.
In quantum computing, machines work with the physical properties of matter, for example, superposition or entanglement, which means that calculations can be performed on several states of matter at the same time, reducing drastically the computation time. In theory, therefore, much more information can be processed simultaneously, which would allow computers with quantum processors to solve eminently more complex problems. At least, that’s the promise!
In this race for the realization of the quantum computer, many interesting applications offer intriguing perspectives with the existing quantum prototypes:
- Cryptography: Finding the famous factorization in prime numbers of a given integer
- Optimization: Instant optimization of a set of satellites facing a solar flare, analyzing data management to circulate autonomous cars, piloting electronics onboard a fighter plane in a combat situation, or management of a complex network of buses in a megalopolis
- Medicine: The discovery of new drugs and the construction of molecular structures
- Material Sciences: The design of quantum materials whose unusual properties (e.g., superconductivity) cannot be understood by simple models involving only one atom or one electron at a time, but which require taking into account the collective effects of a large number of electrons in constant interaction
Electric vehicles are part of the quantum revolution. To take advantage of quantum computing power, carmakers have started using quantum computers to solve different automotive problems.
Solving the traffic routing problem
In the automotive context, artificial intelligence (AI) requires the analysis in real-time of an extraordinary amount of data in order to come up with optimal responses to constantly changing situations. Mining the real-time data of car locations requires both computing power and speed. The latter property is the decisive advantage of quantum machines.
This is why German carmaker Volkswagen decided to partner with D-Wave Systems to lay the groundwork for the automobile of tomorrow. D-Wave Systems is one of the leaders in the development and delivery of quantum computing systems, and the collaboration aims to improve traffic routing in Beijing, the most populous capital city in the world, with a population size of 21.5 million. The system can determine the most efficient route for 418 cars heading to the airport so that congestion wouldn’t even occur. The hope is that quantum machines can solve optimization problems related to public and private transport services in terms of the deployment of their fleets to limit the waiting time for users.
Another promising quantum routing application for the automotive industry is to solve the problem of diesel delivery to vehicles by jointly reducing their harmful pollutants and ensuring that their drive cycles are optimal. In July 2018, Ford Motor Company started exploration in this direction with the next-gen annealing technology, using NASA’s quantum computers in its autonomous car research in accordance with a Space Act Agreement.
The next generation of automotive technology could be quantum
In November 2017, Volkswagen Group and Google’s parent company Alphabet announced three new projects to develop quantum computing for automotive technology. With the promise of the autonomous car, one of the challenges is to be able to predict the state of traffic with enough precision to avoid any accident, a task that requires significant computer capacity.
Simulating the behavior of electrical components such as new active materials for a battery’s electrolyte or electrodes, as well as creating artificial intelligence in each car, are the other two spheres of collaboration between the two multinationals. And the use of advanced technologies in the automotive sector is not limited to Volkswagen. For example, Toyota is also using artificial intelligence systems to accelerate research in materials science in order to find new approaches to reducing polluting emissions from its vehicles.
Quantum computers for safe connected cars
Quantum computers will be able to break data encryption algorithms. As today’s vehicles are designed to regularly update software automatically, it is possible that the risk of their vulnerabilities to hackers will be present in the coming decades. Therefore, if we want cars to become smarter and more connected, data security must be a top priority for car manufacturers. It would be wise to start preparing migration plans for quantum security cars now.
The cars being developed today must be ready to incorporate quantum technology within the time frame that we expect from a practical quantum computer. A recent car demonstration of the Karma Revero GT at the Consumer Electronics Show (CES) 2020 showed how a vehicle sends and receives data without a quantum-enabled adversary thanks to the quantum security technology developed by the ISARA Corporation, one of the world’s leading quantum security providers.
Vehicle-to-vehicle (V2V) and vehicle-to-cloud (V2C) communication
The next generations of self-driving cars will have the ability to communicate with the cloud to both download data (updates of their on-board AI system, traffic information) and upload their driving data. Such communication is possible using over-the-air communication where quantum chips can play a major role in the processing and encryption of data locally in the self-driving car, and in the cloud to solve cryptographic and optimization problems related to the traffic routing, as described in the first section of this article.
The same type of communication can be performed between vehicles where the quantum electronic technology in self-driving cars enables a decentralized communication between cars to solve distributed optimization problems such as the dynamic speed adjustment of nearby cars to minimize fuel consumption.
V2V communication systems are not only reserved for autonomous cars. Vehicles with drivers will also benefit. A driver can be warned hundreds of meters away from the existence of an obstacle on his or her way.
Google, which is working on such a project, announced in October 2019 that its quantum processor Sycamore had successfully completed in 200 seconds a mathematical calculation that a conventional computer would have taken 10,000 years to solve. This performance, which is more than impressive, has no useful application at the moment, but it could only be a matter of time.
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