I recently finished reviewing the first three finalized post-quantum cryptography standards that the National Institute of Standards and Technology (NIST) released in August 2024. These standards, known as FIPS 203, 204, and 205, are a direct response to a major threat. Quantum computers use Qubits to process data in a way that will eventually break the asymmetric encryption we use to protect web traffic and financial records. If an attacker captures your encrypted traffic today, they can store that data and wait for a machine powerful enough to run Shor’s algorithm. This is a problem for long-term data security. You need to understand how these systems operate to build a defense strategy that lasts.
What are Qubits?
A qubit is the base unit of information in a quantum system. You are likely used to classical bits that stay as a 1 or a 0. Qubits are different. They exist in a probabilistic state that represents more information than a binary switch. While a classical transistor is either on or off, a quantum processor uses physical objects like electrons or photons to hold information. I use linear algebra and complex numbers to define the state of these units.
This is where most people get confused. The state of a qubit is not just a lack of knowledge about whether it is a 0 or a 1. It is a physical property where the unit exists as a vector in a two-dimensional Hilbert space. When you measure the system, the wave function collapses into one of the two basis states. Before that measurement happens, the system exists in a state that combines both possibilities. This allows a computer to maintain a vast computational space. A system with only 50 of these units can represent over one quadrillion states at the same time. This massive scaling is exactly why this technology threatens our current cryptographic protocols.
How Qubits Work
Quantum computation relies on three particular physical properties. They are superposition, entanglement, and interference. One has to be aware of them to appreciate how quantum computers can surpass classical supercomputers in operations such as integer factorization.
Superposition gives a computer the ability to store several states at once. When dealing with just one unit, it represents a mathematical mixture of 0 and 1. That is, it is a physical property of the subatomic particle. In case I do some operation on a superpositioned unit, my computer will do it with all the states at once. It means parallel computations.
Entanglement refers to the connection between the particles. The condition is that the state of one unit depends on the state of another. This happens regardless of the distance between them. Once I measure the state of one entangled particle and discover that it is equal to 1, it immediately becomes clear what the state of another particle is. Thus, qubits can interact with each other as one whole system. Entanglement helps qubits achieve computational power twice higher than that of a regular unit.
Interference is the tool we use to get a result. Quantum algorithms use constructive interference to make the probability of the correct answer higher. They use destructive interference to cancel out the wrong paths. The computer manipulates the phases of the qubits so that the wrong solutions essentially vanish. This is how the system reaches a mathematical result without checking every possibility one by one.
Technical Flow and Architecture
You do not just load a file and wait for an output when you use a quantum computer. You have to manage the environment to prevent the quantum state from decaying. This decay is called decoherence. I usually find that the architecture requires more effort to keep the system stable than to run the actual code.
In real environments, it doesn’t work this cleanly, but the logical sequence follows these steps:
- You reset the system by putting all units into a known ground state, which is usually 0.
- You apply quantum gates to put the units into a state of superposition.
- You run the algorithm logic by performing operations that entangle the units.
- You use interference to bias the system toward the correct mathematical answer.
- You measure the final state, which collapses the superposition into a bit string.
This flow requires high-fidelity control electronics. For example, the Willow chip from Google has 105 qubits and can complete a benchmark in under five minutes. A classical supercomputer would need 10 septillion years for that same task. The architecture must also handle errors. Because these units are sensitive, even a small vibration causes an error. We use quantum error correction (QEC) to spread information across many physical units to create one reliable logical unit. I see this as the main engineering hurdle for the next five years.
Key Components of Qubits
Different hardware manufacturers use different physical objects to build their processors. The material you choose changes the speed and the error rate of the machine.
Superconducting circuits are the leading approach right now. IBM and Google use tiny loops of wire cooled to near absolute zero. These circuits use current flow to hold data. Because they are made on silicon chips, we can use existing factory techniques to build them. But they need massive dilution refrigerators to stay at 10 millikelvin.
Trapped ions are a different method. Companies like IonQ use individual atoms of Ytterbium or Barium. They hold these atoms in a vacuum using electromagnetic fields and use lasers to change their state. This provides high fidelity. In 2025, IonQ reached a 99.99% gate fidelity. These units are perfect because every atom of the same element is identical.
Here is a list of the main qubit modalities in use today:
- Superconducting circuits (used by IBM and Google)
- Trapped ions (used by IonQ and Quantinuum)
- Photonic systems (used by Xanadu and PsiQuantum)
- Neutral atoms (used by QuEra and Pasqal)
- Silicon spin qubits (used by Intel)
Photonic systems use light. They send photons through fiber optic cables and mirrors. These units can stay stable at room temperature, though the sensors still need cooling. Photons do not interact with each other easily, so they are hard to entangle but very resistant to noise. Topological qubits are the most experimental. Microsoft is trying to braid particles to protect the information. If you shake the system, the knot stays tied. This would solve the error problem at the hardware level, but it is very difficult to build.
Real-World Example: Factoring RSA-2048
The most famous use for these systems in cybersecurity is breaking RSA-2048. This encryption depends on the fact that finding the prime factors of a 617-digit number takes billions of years on a classical computer.
Now here’s where it gets interesting: Shor’s algorithm can find those factors in hours if the computer is powerful enough. In 2021, researchers Gidney and Ekerå calculated that you would need 20 million noisy physical units to break RSA-2048 in eight hours. But by early 2026, new methods have lowered that number. Alice & Bob, a team in France, showed that their cat qubit architecture could do this with 99,000 units. They achieved this by using a design that naturally stops bit-flip errors.
Adversaries are already using a “Harvest Now, Decrypt Later” strategy. They are collecting your encrypted traffic today so they can read it when these machines are ready. If you want to know more about how to manage identities during this shift, for more on Zero Trust, see our IAM guide to build a foundation for post-quantum security. You cannot wait for the hardware to be perfect before you act.
Advantages and Limitations
The main advantage of these units is how they handle complex math. In chemistry, simulating a molecule like FeMoco is impossible for a supercomputer. Qubits can simulate quantum bonds directly. This could help us find a more efficient way to make ammonia, which might reduce global carbon emissions by 3%.
But the limitations are still a major factor. The error rate is the biggest wall. A classical bit fails once in a quintillion operations. A physical qubit often fails once every 1,000 operations. To build a useful computer, we need millions of physical units just to get a few thousand stable logical ones.
Cost is the second limitation. Building a large machine needs a billion-dollar investment. You need specialized cooling, low-noise power supplies, and cryogenic wiring. For example, the PsiQuantum facility in Australia is a massive project that only a few organizations can afford. Most of us will use these machines through a cloud provider rather than buying the hardware.
Conclusion
Quantum technology is moving out of the physics lab. Recent breakthroughs show that machines can solve problems faster than any classical supercomputer. You have to realize that Qubits are a real threat to our current security models.
You should start an inventory of your cryptographic assets today. Find every system that uses RSA or Elliptic Curve Cryptography. Moving to the new NIST standards will take years of work. By understanding how Qubits work now, you can prepare for the decryption risks of the future. Follow the NIST updates and start your migration plan before the first large-scale quantum computer is finished. Your data security depends on how well you adapt to this change.
Reference: wikipedia
If you want to understand the basics, read our guide on quantum computing: Technaga
If you are new to this field, start with our beginner-friendly guide on what is cyber security to understand the bigger picture. what is cyber security
