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.