A qubit can be simultaneously 0 and 1 due to superposition. How they are built, what types exist, and why temperatures near absolute zero are required.
📖 Read more: Quantum Superposition: Particles Existing in Two Places
🔬 From bit to qubit
A classical computer stores information in bits — binary units that take the value 0 or 1. Every transistor in a processor acts as a microscopic switch: on or off, current or no current. The entire digital era — from smartphones to data centers — relies on this binary logic.
A qubit (quantum bit) is something radically different. Instead of being strictly 0 or 1, a qubit can exist in superposition — a linear combination of both states simultaneously. Mathematically, a qubit’s state is written as |ψ⟩ = α|0⟩ + β|1⟩, where α and β are complex numbers (amplitudes) satisfying |α|² + |β|² = 1. This does not mean the qubit “is both 0 and 1 at the same time” in the everyday sense — it means that before measurement, the information is encoded in the amplitudes.
Classical bit vs Qubit: A classical bit is like a coin showing heads or tails. A qubit is like a coin spinning in the air — until it lands (measurement), the final state is undetermined, but the probability amplitudes determine what we will observe.
🌀 Superposition: the heart of the qubit
Superposition is the fundamental property that makes the qubit so powerful. When a qubit is in a state of superposition, the amplitudes α and β can be positive, negative, or complex. This allows interference phenomena: contributions from different computational paths can reinforce each other (constructive interference) or cancel each other out (destructive interference).
The goal of every quantum algorithm is exactly this: to choreograph an interference pattern so that wrong results cancel out and the correct answer is amplified. Shor’s algorithm (1994) for decryption and Grover’s algorithm (1996) for database search follow precisely this logic. They don’t “try all answers simultaneously” — they exploit the mathematical structure of the problem through interference.
🔗 Entanglement: the quantum connection
Equally important to superposition is quantum entanglement. When two qubits are entangled, measuring one immediately determines the state of the other — regardless of the distance between them. Einstein called this phenomenon “spooky action at a distance,” but Bell-type experiments since the 1980s have confirmed that entanglement is real.
📖 Read more: Quantum Teleportation: Real Science or Pure Fiction?
In a quantum computer, entanglement allows qubits to cooperate in ways impossible for classical bits. Two entangled qubits are not described as two separate states but as one joint state in a four-dimensional space. With n qubits, the state space has 2n dimensions — exponential growth that makes classical simulation of large quantum systems impossible.
“Nature isn’t classical, dammit, and if you want to simulate nature, you’d better use quantum mechanics.”
— Richard Feynman, 1982🏗️ How a qubit is built
There are multiple ways to implement a qubit, and each technology has advantages and disadvantages.
Superconducting qubits (Transmon)
The most popular approach, used by IBM, Google, and Rigetti. It relies on superconducting circuits cooled near absolute zero (approximately 15 millikelvin — colder than outer space). At this temperature, electrons flow without resistance, creating quantum states that can be controlled via microwaves. Google used 53 superconducting qubits in the Sycamore processor in 2019, while the newer Willow (2024) achieved logical qubits with lower error rates.
Trapped ions
Companies like IonQ and Quantinuum use individual ions (e.g., ytterbium or barium) held in electromagnetic traps. Qubits are controlled with laser beams. Trapped ions have exceptionally long coherence times — tens of seconds, compared to microseconds for superconducting qubits — but gate operations are slower.
Photonic qubits
Xanadu and PsiQuantum are developing quantum computers based on photons. Photonic qubits operate at room temperature, but measurement destroys the photon, making repeated operations challenging. Pan Jianwei’s team at USTC used 113 photons in Jiuzhang 2.0 for Gaussian boson sampling.
Topological qubits
Microsoft is investing in topological qubits based on Majorana fermions — particles that theoretically provide built-in error protection. The technology is still in early research stages, but if successful it would require far fewer physical qubits for error correction.
Operating temperature of superconducting qubits
Two-qubit gate fidelity (state of the art)
⚡ Decoherence: the greatest enemy
Quantum information is extremely fragile. Decoherence — the unwanted interaction between a qubit and its environment — can destroy superposition within microseconds or less. Nearby electric fields, thermal radiation, even cosmic rays can corrupt the state of qubits.
The solution is quantum error correction: encoding each logical qubit across many physical qubits so that errors can be detected and corrected in real time. In December 2024, Google announced that the Willow processor achieved, for the first time, logical qubits with lower error rates than the physical qubits comprising them — a milestone on the path toward fault-tolerant quantum computers.
🎯 Why qubits change the rules
With 300 fully functional qubits, a quantum computer could theoretically handle more states than the number of atoms in the observable universe. This does not mean it would solve every problem faster — as Scott Aaronson, computer science professor at the University of Texas, explains, “quantum computers will not revolutionize everything.” Their superiority appears in specific problems: simulating molecular structures for drug design, optimizing complex logistics, and analyzing cryptographic codes.
Today we are in the NISQ era (Noisy Intermediate-Scale Quantum) — quantum computers with tens to hundreds of noisy qubits. But each new processor — Sycamore, Eagle, Condor, Willow — brings the world closer to practical quantum advantage. The question is no longer “if” but “when.”