Quantum computers - A look at future technologies

Although quantum computing technology is still in its infancy, it may be only a few years until it radically alters IT-based systems. This includes logistics applications, since quantum computers (QCs) make it possible to solve complex combinatorial tasks much faster. In logistics, for example, they can optimize route planning and material flows, but also complex database searches or machine learning processes with their computing power.

A QC is an entirely new kind of microprocessor that works according to the physical laws of quantum mechanics. These laws describe the properties of states of matter on an atomic and subatomic level. Far from easy to understand, the theory emerged back in 1925 and was further developed by several physicists, including Werner Heisenberg and Erwin Schrödinger. The latter made the theory somewhat easier to grasp through his famous thought experiment “Schrödinger’s cat”, details of which can be found online.

Qubits unlock new computing power

In addition to a change in hardware, QCs require a different kind of IT that uses different mathematical approaches. A conventional computer stores data as bits, which can assume one of two states: zero or one. The more processors a computer has, the faster it can perform computations and successively evaluate bit sequences. A QC stores data in quantum bits, or qubits. Instead of being limited to a single state (zero or one), qubits can assume both states simultaneously. This is known as superposition. This means that a QC can perform many more computational operations than a conventional computer, because it can evaluate all possible combinations simultaneously rather than sequentially. For example, a QC with 50 qubits can simultaneously assume 2 to the power of 50—or over 1 quadrillion—different states. Experts predict that such a QC would be more powerful than today’s supercomputers. Until now, QCs have been operated only under strictly controlled environmental conditions in specially designed data centers. Paramount among these conditions are an ambient temperature of minus 273°C and safeguards against any kind of interaction with the outside world. The systems are very sensitive and susceptible to error, which makes them currently unsuitable for widespread commercial use. But QCs with 20 qubits—and experimental QCs with 50—are already on the market as cloud services. These are known as quantum gate systems or universal QCs. One well-known example is the IBM Q System One.

A special type of QC—known either as a quantum annealing system or an adiabatic QC—is of particular interest to the logistics sector. These computers and their processes are especially good for solving route planning problems. They provide a different way of defining qubit values so that these values cannot be compared with those used by universal QCs. Among the best known is the D-Wave 2000Q system with 2048 qubits made by Canadian company D-Wave. In addition to “real” QCs, quantum annealing also uses mathematical simulation based on conventional chip technology. For instance, Fujitsu offers just such a cloud-based computation service that uses a specially designed binary chip.

The performance and practicality of both real and simulated annealing computers is still not advanced enough to map all the conditions and restrictions of DACHSER’s route planning problems in a way that would be practical and affordable. But in the next five years, we can expect the range of annealing services to expand and pave the way for achieving a new level of quality and route optimization.