WASHINGTON, July 8 — The journey from a physicist’s thought experiment to a machine that could reshape computing has taken just over four decades. And the practical upshot, for anyone who uses a credit card or searches the internet, is that the rules of the game are about to change. It all started in 1982, when physicist Richard Feynman proposed using quantum systems to simulate other quantum systems.
A classical computer, he reasoned, would always struggle to keep up. Three years later, in 1985, David Deutsch at the University of Oxford took Feynman’s concept and gave it a concrete form.
He described the first universal quantum computer — a theoretical machine that could, in principle, perform any calculation that a classical computer could, but far faster for certain problems. For a decade, quantum computing remained a largely theoretical pursuit. Then came two breakthroughs that turned it into a practical concern.
In 1994, Peter Shor developed an algorithm — now known as Shor’s algorithm — that could factor large numbers exponentially faster than any known classical algorithm. Here’s what it means: the security of much of the world’s encrypted data, including the RSA encryption that protects online banking and email, relies on the fact that factoring large numbers is incredibly hard for classical computers.
Shor’s algorithm showed that a sufficiently powerful quantum computer could crack that code. Two years later, in 1996, Lov Grover created Grover’s algorithm, which offered a dramatic speedup for searching unsorted databases.
From Theory to Laboratory
The first experimental quantum algorithm was run in 1998. Isaac Chuang, then at IBM, used a 2-qubit nuclear magnetic resonance (NMR) quantum computer to demonstrate that the theory could actually work. Two qubits is not much — it is the quantum equivalent of two bits — but it was proof that the concept was more than just equations on a blackboard.
In 2001, IBM took a significant step forward by demonstrating Shor’s algorithm on a 7-qubit system. It was the first time a quantum computer had performed a calculation that had real-world cryptographic implications.
The field moved from academic labs to commercial reality in 2011, when D-Wave Systems announced the D-Wave One, the first commercial quantum annealer, with 128 qubits. A quantum annealer is a specialized type of quantum computer designed for optimization problems.
The Supremacy Milestone
The biggest headline came in 2019, when Google announced that its Sycamore processor had achieved quantum supremacy. Sycamore performed a specific, carefully chosen calculation in 200 seconds. Google estimated that the same calculation would take the world’s most powerful classical supercomputer approximately 10,000 years to complete.
In plain terms, quantum supremacy means that a quantum computer has done something that a classical computer simply cannot do in any practical amount of time. It was a watershed moment — not because the calculation itself was useful, but because it proved that the quantum advantage was real.
Most recently, in 2023, IBM unveiled a 1,121-qubit processor called Condor. That is a huge leap from the 7-qubit system of 2001. But qubit count alone is not the whole story.
Qubits are notoriously fragile — they are easily disturbed by heat, electromagnetic radiation, and even cosmic rays. The challenge is not just building more qubits, but building them in a way that allows for error correction and reliable computation.
So where does that leave us today, in July 2026? The history of quantum computing is a story of steady, incremental progress punctuated by sudden leaps. Feynman planted the seed in 1982.
Deutsch gave it a blueprint in 1985. Shor and Grover showed what it could do. Chuang and IBM proved it could work.
D-Wave commercialized it. Google showed it could outperform classical machines.
And IBM is now building processors with thousands of qubits. The practical upshot for ordinary readers is this: quantum computing is no longer a distant future. It is a present reality, albeit one that is still in its early stages.
The algorithms that could break encryption, discover new drugs, and optimize global supply chains exist. The hardware is getting closer to being able to run them at scale.
What to watch next is the race to build a fault-tolerant quantum computer — one that can run Shor’s algorithm on a meaningful scale. That is the finish line. And based on the pace of the last four decades, it may not be as far off as it seems.
