Quantum Computing Explained: What Is It, and Why Is It Different?

Quantum computing is a type of computing that leverages the rules of quantum mechanics – the physics that describes nature at the atomic and particle level. It may sound abstract, but the idea is simple: If information is stored and processed in a “quantum way,” it can provide a significant advantage over classical computers for certain very specific tasks. Quantum computers are not “magical supercomputers” that make everything faster. They are specialists, and they require the problem to fit their way of computing.

First: What does a regular computer actually do?

A classical computer – your laptop, your phone, and most servers – computes using bits. A bit can have the value 0 or 1. Inside the processor, bits are moved around and combined through logical operations. Even when a computer seems incredibly advanced, it is still enormous amounts of “0 or 1” processed at very high speed.

This is a powerful and flexible system that works for almost everything in everyday life: text, images, streaming, spreadsheets, databases, and artificial intelligence. But there are types of problems where a classical computer quickly hits a wall, because the number of possible combinations grows explosively. A typical example is finding the best solution among extremely many possibilities – or simulating nature at the quantum level with high precision.

Bits vs. qubits: The most important difference

A quantum computer works with qubits (quantum bits). Instead of only being 0 or 1, a qubit can be in a superposition: a mixture of “0-like” and “1-like” at the same time. This does not mean that the qubit is “half 0 and half 1” in a classical sense. It means that the quantum-mechanical state contains information about probabilities – and, more importantly, about how those probabilities can influence each other.

This is where many people misunderstand quantum computing. You often hear that a quantum computer “tries all solutions at once.” It is a tempting shortcut, but it is inaccurate. A better intuition is: A quantum computer can shape a probability pattern so that the correct solution has a higher chance of appearing when you measure the result. The entire art lies in designing the computation so that the probabilities “work together” in the right way.

Superposition – an image without mysticism

Imagine a coin lying on the table. It is either heads or tails – that corresponds to a classical bit: 0 or 1. Now imagine a coin that is spinning. While it is spinning, it does not make sense to say that it “is heads” or “is tails” in the same way. But when you stop it and look, you get a very concrete outcome. The picture is not perfect (quantum physics is not mechanics), but it helps: Before the measurement, the qubit can be in a state that does not correspond to a fixed 0/1 answer. At the measurement, you get a concrete outcome.

Measurement: Why “looking” changes the game

In the quantum world, measurement is not just “reading” something without affecting it. When you measure a qubit, you get a classical answer (0 or 1), but the act of measurement also causes the qubit’s time in superposition to end for that measurement. In practice, this means that quantum computing is often about keeping qubits stable long enough to perform the computation, and only at the very end measuring to obtain a result that can be used in the classical world.

Entanglement: When qubits are inseparably linked

The second key idea is entanglement. When qubits are entangled, they can no longer be described as independent “small units.” Instead, they are best described as one shared state. If you measure one, it has consequences for what you can expect to see when measuring the other – even if they are separated.

It sounds like telepathy, but it is not. Entanglement can create strong statistical correlations between measurement outcomes, but it does not provide a simple way to send secret messages faster than light. For quantum computing, the point is that entanglement makes it possible to build computations where many qubits “work” as a single, coordinated state. This is one of the reasons quantum computers can be so powerful for the right tasks.

A practical example of entanglement

Imagine two qubits, A and B, that are created in a specific entangled state and then sent far away from each other.

They are prepared so that:

• When you measure them, they will always give opposite results
• But before the measurement, no one – not even the system itself – knows which one will be 0 and which one will be 1

Step by step

1. Qubit A and B are created together
   They are made in an entangled state where the system only “knows” one thing: "The results must be opposite"
   Not which results – only the relationship between them.
   
   
2. They are separated
   Qubit A is sent to Copenhagen.
   Qubit B is sent to Aarhus.
   
   
3. You measure qubit A
   You measure A and get the result 0.
   
   
4. The consequence
   At the same moment, you now know something about qubit B:
   If you measure B, it will give 1
   Not because a signal was sent, but because the two qubits were always one shared quantum state.
   
   
5. Important: No one can control the outcome
   You could not choose for A to become 0.
   If A had become 1, B would have become 0.

Why can quantum computing be faster?

A classical computer can be extremely fast, but it still has to handle many possibilities by representing them explicitly or by using clever heuristics. In some algorithms, a quantum computer can exploit superposition and entanglement to create interference: some probabilities are amplified, others are canceled out. If the problem fits a known quantum algorithm, this can result in a dramatic improvement in runtime or resource usage.

It is important to be specific: The advantage does not apply to “everything.” Many tasks do not become faster on a quantum computer, and some even become more cumbersome. Quantum computing is most interesting where there are well-defined mathematical structures that quantum algorithms can exploit.

What can quantum computers be used for?

Although the technology is still under development, there are three areas of application that are almost always mentioned, because they align well with the strengths of quantum computing.

1) Simulation of chemistry and materials

Chemical reactions and material properties are governed by quantum mechanics. Simulating larger molecules and complex materials on classical computers quickly becomes very demanding, because the number of quantum states grows dramatically. Quantum computers are, in principle, well suited to exactly this type of simulation, because they themselves are quantum systems. The perspective is better design of catalysts, new materials, and more precise models in chemistry and physics.

In practice, many of the most exciting results are still in the research and development phase, but the direction is clear: If quantum hardware becomes stable and scalable enough, chemical simulation is one of the areas where the payoff could be particularly large.

2) Cryptography and security

One of the most well-known quantum algorithms (Shor’s algorithm) can, in principle, factor large numbers much faster than the best known classical methods. This is relevant because parts of modern encryption have historically been based on the fact that certain mathematical problems are very difficult for classical computers in practice.

This does not mean that “all encryption collapses” overnight. First, it requires quantum computers with many, very stable qubits and efficient error correction. Second, there is already extensive work on post-quantum cryptography – cryptographic methods designed to be robust even if large quantum computers become a reality.

3) Optimization and planning

Many companies want to optimize routes, inventory, staffing, portfolios, or production schedules. The problem is often that there are so many combinations that you can rarely guarantee the absolute best solution within a reasonable time. Quantum computing is being explored here because certain quantum methods may be good at exploring large solution spaces.

At the same time, this is an area where honesty is important: There are many claims, and quantum computing does not always outperform classical methods in practice – especially not with today’s noisy hardware. Therefore, quantum optimization is often seen as a “potential” area, where the value may grow in step with better quantum hardware and better hybrid methods.

What can quantum computers not be used for?

A quantum computer does not inherently make ordinary tasks such as email, video editing, or web server operation better. There is also no reason to replace classical computers in data centers with quantum computers as a standard. Quantum computers are typically specialized devices used for selected computations – often together with classical systems.

Another important limitation is that quantum computing does not remove the need for good data or good problem formulations. If a problem is unclear, or if the input data is of low quality, the result does not automatically improve just because you use a quantum computer.

Why is it so difficult to build a quantum computer?

Qubits are extremely sensitive. Small influences from the environment – heat, vibrations, electromagnetic noise, and other effects – can disturb the state of the qubits. When that happens, errors occur in the computation. People often talk about noise and decoherence: the quantum state “drifts” or is destroyed before the computation is finished.

This is why quantum hardware requires very controlled environments. Some types of quantum computers use extreme cooling, others use traps for ions, photons, or other technologies. There are multiple approaches, and the field is evolving rapidly, but the common denominator is the same: It is difficult to keep many qubits stable, precise, and uniform – at the same time.

Error correction: The key to scale

If you want to build large, reliable quantum computers, quantum error correction becomes central. The idea is that you cannot “copy” an unknown quantum state in the same way you copy bits, but you can still protect information by encoding it across multiple physical qubits and measuring certain auxiliary signals that reveal errors without destroying the computation itself. This is demanding and typically requires many physical qubits to create one robust “logical” qubit.

Where are we today? Realistic expectations

Today’s quantum computers are often described as being in an “intermediate phase”: They can perform real quantum operations and demonstrate exciting effects, but they are still characterized by noise and limitations. They are well suited for research, learning, and testing algorithms – and in some cases for very specialized experiments – but they are not general replacements for classical high-performance computers.

The most realistic picture right now is therefore that quantum computing will typically be used as a specialized engine alongside classical systems: Classical computers handle data, control, and the parts of the problem that fit best with classical logic, while the quantum component is used where quantum effects make sense.

A simple way to remember it

• Classical computing: bits are 0 or 1, and computation is robust and practical for most things.
• Quantum computing: qubits can be in superposition and entanglement, which can provide large advantages for selected problem types.
• Measurement gives a classical answer, which is why the computation must be designed so that the likely outcome is the desired one.
• The challenge is noise and errors – and the long-term solution largely involves error correction and scaling.

Conclusion: Why does quantum computing matter?

Quantum computing is interesting because it expands our “toolbox” for computation. It does not promise to make everything faster, but it can potentially change what is practically possible in areas such as chemical simulation, selected optimization problems, and certain cryptographic scenarios. At the same time, it is a technology that requires patience: There is great progress, but also real physical and engineering challenges that cannot be waved away.

If you take one thing away from this, let it be this: Quantum computers are not “better computers” in the ordinary sense. They are a different type of computer that can be dramatically better when the problem fits the way nature computes in the quantum world.

Read more about quantum computing at the American government institution: National Institute of Standards and Technology (NIST)