Quantum Computing

Quantum computing is a fundamentally different approach to computation that uses the properties of quantum mechanics — superposition and entanglement — to process certain types of problems in ways that classical computers, no matter how powerful, cannot efficiently replicate. Where a classical computer's basic unit of information (a bit) is always either a 0 or a 1, a quantum bit ("qubit") can exist in a combination of both states simultaneously, and multiple qubits can become "entangled" so that their states are linked in ways with no classical analog — properties that, for the right class of problems, allow quantum computers to explore a vastly larger solution space than classical machines can.

For most of its history, quantum computing has been defined more by its promise than by practical results, held back by the extreme fragility of qubits: they lose their quantum properties ("decohere") from even tiny amounts of environmental noise, producing high error rates that limited quantum computers to research demonstrations rather than useful, reliable computation. 2026 has marked a genuine inflection point on that specific problem. Several companies have now demonstrated working "logical qubits" — arrangements of multiple physical qubits combined with error-correction code to behave as a single, much more reliable qubit — at meaningful scale: QuEra Computing, working with Harvard, demonstrated 96 logical qubits built from 448 physical qubits using an advanced error-correction code, while other firms have shown logical qubits actually outperforming raw physical qubits on real computational tasks for the first time, a milestone the field has worked toward for years.

Hardware progress has come from multiple, genuinely different physical approaches competing in parallel — a sign the field hasn't yet converged on one clearly superior technology. Microsoft reported a major materials-science advance in its topological qubit approach, improving the stability of its quantum states roughly a thousand-fold. Rigetti's superconducting-qubit systems cut error rates roughly in half within a single year. Quantinuum's trapped-ion approach continues to deliver higher gate fidelities than superconducting rivals achieve at comparable qubit counts, while IBM has laid out a public roadmap toward systems combining multiple processing modules to scale toward thousands of gates per circuit over the next several years. That diversity of competing hardware approaches — superconducting circuits, trapped ions, neutral atoms, and topological qubits among them — means it remains genuinely unclear which underlying technology will ultimately scale most successfully to commercially useful quantum computers.

Commercially, the industry crossed a symbolically important threshold in 2025 when IonQ became the first pure-play quantum computing company to exceed $100 million in annual GAAP revenue, and further signs of maturation followed in 2026 with additional quantum companies reaching public markets. Real, near-term commercial applications remain concentrated in a fairly narrow set of domains where quantum computers' specific mathematical advantages actually apply — materials science simulation, certain optimization problems, and some cryptographic applications — rather than the general-purpose computing quantum computers are sometimes popularly imagined to eventually replace. For most businesses, quantum computing in 2026 remains a research-and-development bet on a technology with a genuinely uncertain but potentially transformative timeline, rather than a technology ready for broad commercial deployment today.