Quantum computing is the next big thing. Experts are convinced of this. But it will still be a few years before this future technology leaves the labs. So, should we wait, and see? That would be a mistake. T-Systems offers quantum-inspired optimization as a bridging technology so that companies can benefit from quantum computing and gain a competitive advantage.
Quantum computers can solve some of the most complex industrial problems more efficiently than traditional digital computers. Conventional computers use bits as the basic unit of data. They process the data in binary form, writing the code as 1 or 0. They perform their arithmetic operations successively. This means, one operation must be completed before another can follow. This is called serial processing. Quantum computers are different: they use qubits as a data unit. The qubits can assume several states; either the value is 0 or 1 or, in the so-called ‘superposition’, also superimposed states between 0 and 1. In this way, quantum computers can execute completely new types of algorithms. This explains why the technology can solve more complex computing tasks than conventional computers and is much faster.
In the digital working world, we have to deal with an incredible number of systems that are interconnected and interdependent. If you intervene in one system, it has consequences for others. Simulating this is difficult for conventional computers. They reach their limits especially when combinatorial optimization problems are involved, and the computer has to juggle many variables. This is because the possible combinations grow exponentially with each variable. The result: the computer calculates and calculates.
Combinatorial optimization problems can be found everywhere: for example, when it comes to determining the optimum traffic flow by optimizing the traffic light circuit. Or in a car factory that wants to determine the best routes for its robots. It is precisely here — where classic computers reach their limits in combinatorial optimization problems — that quantum computers bring new momentum. Their functional principle is fundamentally different. This provides the opportunity to find new solutions for problems with many variables and exponentially growing possibilities. In addition to optimization, this also applies above all to materials and molecular research — which opens up great potential in medicine. But the technology also harbors risks. The so-called ‘Shor Algorithm’ can efficiently break current encryption methods. We should therefore start thinking today about how we can make our IT security quantum-resistant.
Although we have been talking about quantum computing for decades, it is not yet in industrial use. Why is that?
Admittedly, it will be several years before the technology is ready for practical use. The discrepancy between expectations and the real possibilities that can be realized in the short to medium term is huge. Nevertheless, not only scientists, but also companies should start looking at quantum computing now. Only those who understand the technology and the research into classic bridging technologies can categorize and seize the opportunities offered by quantum computing at an early stage. Quantum computing requires a new way of thinking. That takes practice. We take a pragmatic approach: quantum-inspired optimization already allows us to use the input models for quantum algorithms and solve existing problems with conventional, scalable chips.
Our customers can already prepare for the methods of quantum computing today and remain independent of actual hardware developments.
Our solution is not yet ‘real’ quantum technology; the computer is not in a quantum state. So, how do we proceed? In preparation for the quantum-inspired method, we translate the optimization problem into a mathematical formulation called ‘QUBO’ (Quadratic Unconstrained Binary Optimization). Such QUBO models can handle a high degree of complexity – even on conventional computers. These models also no longer need to be modified if they are to be used later as input for real quantum algorithms. Many complex problems can be modelled in QUBO form. And anyone who deals with QUBO will later know what is important when preparing the algorithms or during the modelling phase.
In our mobile communications planning tests, the bridge technology worked up to 37 times faster than conventional methods. When planning mobile communications, our specialists are faced with the questions such as: where we can place a new tower, where the radio tower will interfere with a neighboring base station, and at what angle the antennas must be aligned to each other. A perfectly suited combinatorial optimization model with exponentially growing possibilities: you are literally looking for ‘the needle in the haystack’. We have pitted the quantum-inspired optimization process against the existing planning model. The quantum-inspired technology only took 10 minutes instead of six hours. The actual strength of the solution did not even come into play in the test case: it is particularly suitable for dynamic optimization problems and scores especially well when conditions change quickly.
