Quantum Computing Explained

A quantum computer can exist in many computational states at once—something a classical computer simply cannot do. This is your VocaCast briefing on Quantum Computing Explained for Saturday, May 02.

The difference lies in how information is stored. A classical computer processes information using bits that must be either 0 or 1 at any given moment. Quantum computing, by contrast, uses quantum bits—or qubits—as the fundamental units of information. ^[1] A qubit is a linear combination of two distinct states and can simultaneously be 0, 1, or in a superposition of both until measured. ^[1] This capability isn't just a technical tweak—it reshapes what becomes computationally possible.

That simultaneous existence of multiple states is called superposition, and it unlocks something remarkable: quantum parallelism. ^[2] When a qubit exists in superposition, representing both 0 and 1 at the same time, a quantum computer can perform many calculations in parallel. ^[2] A classical computer, working with bits locked into definite states, can perform only one computation at a time. The quantum system explores multiple solution paths simultaneously—a genuine computational advantage for certain types of problems. But qubits don't work in isolation. When multiple qubits interact, something even stranger happens.

They can form a collective superposition, creating a special connection known as entanglement, where the outcome of measurement on one qubit will always be correlated to the measurement on another, even if those qubits are physically separated by distance. This correlation allows entangled qubits to be manipulated in many qubits in a single operation, rather than manipulating each one individually as classical computing requires. ^[2] These three quantum principles—superposition, entanglement, and a third property called interference—work together to enable quantum computers to process information in fundamentally different ways than their classical counterparts.

There is, however, a critical fragility at the heart of quantum computing. The moment a qubit is measured, it ceases to be in superposition and becomes subject to classical rules through a process called decoherence. ^[3] To maintain qubits in their quantum state and prevent this collapse, they must be controlled using specialized methods like magnetic fields and laser beams, each precisely calibrated to avoid triggering decoherence. ^[3] This requirement for extreme control and isolation is one reason quantum computers demand exotic engineering conditions—cold temperatures, electromagnetic shielding, and careful timing.

One last puzzle remains — now that you understand how quantum computers work, what are they actually for? The answer isn't abstract. Quantum computers are being actively explored for use in healthcare innovation, cryptography, material science, and artificial intelligence. ^[4] These sectors face computational problems that classical computers simply cannot solve efficiently, no matter how fast they become. In Life Sciences and Materials, quantum computing offers solutions for lead compound search, pharma analysis, and formulation analysis. ^[5] That's not a distant promise. It's a current focus for companies racing to turn quantum hardware into practical tools.

The bottleneck has always been speed and scale. Google demonstrated its quantum computer solved a problem in 200 seconds that would take the world's fastest supercomputer 10,000 years. ^[4] This gap, measured in millennia, compressed to a third of a minute, highlights the advantage that emerges from superposition—testing thousands of possibilities simultaneously, rather than one after another. But raw speed alone doesn't win the race. Qubits can be implemented using various physical systems including trapped ions, photons, real or artificial atoms, or quasiparticles, depending on the quantum computing architecture. ^[5] Different approaches trade off stability against scalability, which means the design choice shapes what each quantum computer does best.

Those trade-offs are exactly what the world's largest tech companies are now solving in real time. IBM, Google, and Microsoft are advancing quantum computing technology, each betting on different physical systems and approaches. ^[6] In February 2025, Microsoft announced the creation of the first chip powered by topological qubits, built around particles called Majorana fermions. ^[6] That's not just an incremental improvement. It represents a fundamentally different way to encode and protect quantum information from decoherence — the noise that causes qubits to lose their quantum properties.

The competition is fierce because the stakes are global. Significant investment in quantum computing is driven by the pursuit of breakthroughs and competitive advantage. ^[6] Governments and research institutions are also involved in advancing quantum computing technology, with the UN International Year of Quantum Science and Technology celebrated in 2025 to highlight progress and potential. ^[6] The numbers reflect the momentum. In 2026, the global quantum computing market exceeded ten billion dollars, with industry leaders actively developing the technology. ^[7] That's venture capital, government funding, and corporate R and D converging on a single conviction: the quantum advantage is real, and whoever builds it reliably first will reshape computing itself.

Remember the entangled pair from the fundamentals section—the state where two qubits exist in perfect correlation, inseparable even when measured? An entangled pair can be created using quantum computers by starting with two qubits in state zero, applying a Hadamard gate to the first qubit and using it as control on a CNOT gate, resulting in a final entangled state where individual qubit states cannot be determined. ^[8] That delicate dance of gates and superposition isn't just theoretical anymore. It's the foundation of machines now being built and tested by the companies reshaping technology.