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A current quantum of a reality check for optimization

Quantagonia macht alte Software fit für Quantencomputer. Würde Frank Thelen investieren?

Jul 3, 2024
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Here’s a secret most quantum computing companies don’t want you to know: there is no advantage in running a calculation on a current quantum computer compared to a classical computer for any business-relevant application … well, for any optimization problem at least … and at this very moment. How do we know? Let’s just say If anybody should know, it should be us at Quantagonia. Let me elaborate.

Cost, Utility, and Advantages of Quantum Computers

First off, there is the price tag. Every computation a company makes has a price. Ideally, a computation with a big bill has a large gain somewhere down the road. Unfortunately, performing a quantum computation compared to a classical computation is very costly today. That's not to say that there aren't quantum calculations that are worth those prices, but most likely, that's not the case for your business problems. Of course, this can and will change as soon as quantum computers aren’t that rare and cheaper to operate.

Second, classical computers are awesome. Currently, quantum memory is immature, and the gate operation rate of quantum computers is prohibitively slow compared to classical processing units like GPUs. This doesn’t mean a quantum processor can’t outpace a classical processing unit for a computational problem, but it does mean operating with a few hundred or thousand (Q)bits on a quantum processing unit is not a fruitful path for most algorithms… without some form of quantum memory, at least. Fortunately, versions of quantum memory are being developed.

Third, special properties require special care. Ever wondered why quantum computers are faster or so much more powerful? A quantum computer is more powerful if it can solve a problem by executing a quantum algorithm that requires fewer queries or steps to find the solution to the same problem than its (best) classical alternative algorithm. Quantum advantage is possible due to the ability of quantum computers to exploit useful quantum phenomena for computation. This unlocks steps (or queries) in algorithms that classical computers can't access because these are trapped within their classical worlds. These special properties allow a quantum computer to do more in fewer steps and thereby solve a problem faster. This means that these special properties have to be maintained and operated throughout the computation, and this is where harmful noise enters the picture. Noise just happens. Similar to how friction stops a moving object bit by bit, the physical computational states of quantum computers are corrupted qubit by qubit. Meaning that special properties turn out not that special anymore when left untreated. Though it comes with a large overhead, that’s why quantum error correction is needed and being developed.

So why do we at Quantagonia bother about quantum computing?

Well, a currently big bill on quantum computations for us leads to a large gain somewhere down the road. We integrate them into our other classical algorithms and tune them so we know when there is a benefit and how we can exploit it. In the end, you, as users, shouldn’t care whether you should use a quantum computer for your computation or not. CPUs are no longer general-purpose processing units. For example, processing units like GPUs have been accelerating specific applications for years. Similarly, quantum computers won’t be suited for many problems and will be highly problem-type dependent. This is why, for an end-to-end solution, we at Quantagonia focus on hardware-agnostic and hybrid quantum-classical computing, specifically in optimization solutions. This distinctly differs from so-called quantum-inspired solutions, i.e., quantum solutions executed on classical computers. Although these can be interesting for the development of other algorithms, they offer no practical quantum advantage as they do not utilize any quantum resources (simply put: 'Where no quantum hardware is used, there is no quantum advantage').

In our hybrid quantum-classical approach, we develop and implement both pure quantum and pure classical algorithms on different types of hardware accelerators, which we then integrate and orchestrate. This allows them to enhance each other. This integration isn’t easy, and many challenges must be addressed for a complete end-to-end solution. This is also why we must start now; we can’t build quantum computers without knowing what we gain and how to integrate them best. We want our users to focus on implementing the solutions to their problems and realizing their benefits instead of dealing with which problems are solved best with which algorithm on which hardware. That way, we provide real value on both the classical and quantum fronts. The magic happens by dynamically matching algorithms and hardware types, ensuring the true optimal solution to your application problem without you knowing what steps must be taken to provide the best solution.

This also enabled us to provide our customers with the leading and fastest HybridSolver. It is also the most accessible solver everyone can directly use over the cloud (don’t believe it—register for free and run your first job within a few seconds here). Together with many other features, it is revolutionizing the optimization sector… but more on that soon.

What is a quantum computer? How does a quantum computer work?

A quantum computer operates on the principles of quantum mechanics with the computational states being qubits (or qudits), which, unlike classical bits, can exist in multiple states simultaneously (superposition), can be interlinked across distances (entanglement), and interact in a special constructive or destructive way (interference). This allows quantum computers to perform some computational tasks, with a dramatic increase in computational power. The number of qubits indicates a quantum computer's problem size that can be solved, and with it its potential capability. Quantum computing promises to revolutionize business use cases, particularly in fields requiring complex calculations like in optimization or AI, by the potential of solving problems infeasible for classical computers.

Why is quantum computing faster or so much more powerful?

First, what does faster or powerful mean? Problems are solved with algorithms. A faster or more powerful algorithm solves a problem with fewer resources than another. Such a resource usually is how many queries or steps an algorithm needs to solve the problem. Each query or step within the algorithm takes time; thus, one says, " This algorithm is powerful; it finds the solution to a problem faster." A quantum computer is thus more powerful and finds a solution much faster if it can solve one problem by executing a quantum algorithm requiring fewer queries or steps to find a solution than its alternative running on a classical computer. This is possible due to the ability of Quantum computers to exploit quantum phenomena within their algorithm steps (or queries) that classical computers can't access because these are trapped within their classical worlds. Three such vital quantum phenomena are superposition, interference, and entanglement. These allow a quantum computer to do more in fewer steps and thereby solve a problem faster. The extent of the performance difference depends on the specific problem instance and can range from none to an exponential advantage. Therefore, it is crucial to have both a classical and a quantum computing solution.

Is there currently a quantum advantage or quantum supremacy?

Mostly no and some yes, depending on the context. "Quantum advantage" refers to the point where quantum computers can solve certain problems faster or more efficiently than any current classical computer. Some quantum computers have shown promising results in specific types of problems, suggesting they are approaching or have reached quantum advantage in those areas (e.g. boson sampling, Google’s supremacy experiment in 2019). However, this achievement is specific to a particular type of problem that doesn't have practical applications yet, and as of this moment (January 2024), it is still a subject of ongoing research and debate if quantum advantage or supremacy has been reached in a practical application (e.g. IBM’s utility experiment). However, since the superiority of quantum computers for practical applications has been proven on the theoretical side (e.g., Shor's Algorithm, Quantum Fourier Transformation, Grover's Algorithm) and developments in practical implementation are advancing rapidly, it is crucial for certain areas to be Quantum-Ready. To do this and always provide the best available solution, we choose a hybrid quantum-classical approach, as in our HybridSolver.

What problems can be solved by a quantum computer?

The applications of quantum computers are diverse. Quantum computers are well-suited for solving complex problems currently challenging or impractical for classical computers. However, they are not a "magic box" that solves all of these computational problems. For the different application problems, some are more suited to be solved via quantum computing than others. These application problems include cryptography, such as breaking encryption algorithms like RSA; solving large-scale optimization problems found in logistics, finance, and manufacturing (e.g., our optimization cases); simulating molecular structures and reactions for drug discovery and materials science; and certain types of algorithms in artificial intelligence and machine learning. Since particularly in the short term not all quantum approaches will surpass classical ones, and some algorithms will continue to be more sensibly computed with classical computers, it is crucial to consider and integrate both. Only if you can address both the quantum and the classical algorithms, can one provide a solution that delivers a genuinely optimal solution and advantage to an application problem.

What is meant by a hybrid quantum-classical approach?

At Quantagonia, we take a hybrid quantum-classical approach, specifically in optimization solutions. This distinctly differs from so-called quantum-inspired solutions, i.e., quantum solutions executed on classical computers. Although these are interesting for the development of algorithms, they offer no practical quantum advantage as they do not utilize any quantum resources (simply put: 'Where no quantum hardware is used, there is no quantum advantage'). In our hybrid quantum-classical approach, we develop and implement both pure quantum and pure classical algorithms, which we then integrate and interlink. This allows them to enhance and benefit from each other. Thus, we can provide real value on both the classical and quantum fronts, dynamically adjusting to the algorithm and hardware type, and ensuring the true optimal solution to the application problem at hand.

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