A quantum computer is a machine that uses the principles of quantum mechanics — superposition, entanglement, and interference — to process information in ways that classical computers fundamentally cannot. Where a classical computer stores information as bits that are either 0 or 1, a quantum computer uses quantum bits, or qubits, which can exist as 0, 1, or any combination of both simultaneously. This allows a quantum processor to explore many solutions to a problem at the same time, rather than working through them one by one.
For decades, that definition described a theoretical ambition. In 2026, it describes a working technology. According to research published across IBM, Google, and Microsoft in late 2025 and early 2026, quantum computing has crossed from experimental curiosity into practical capability — with processors performing tasks that the world’s most powerful classical supercomputers cannot replicate in any reasonable timeframe.
This article explains how quantum computing works, what has actually been achieved, and what it means for medicine, cryptography, climate science, and the future of computing itself.
How Quantum Computing Actually Works
To understand quantum computing, it helps to start with what classical computing does — and where it hits a wall.
A classical computer performs calculations by manipulating bits — tiny electrical switches that are either on (1) or off (0). Everything a classical computer does, from loading a webpage to simulating a protein molecule, is ultimately a sequence of these binary operations. This works extraordinarily well for most tasks. But for certain categories of problems — ones that involve enormous numbers of possible combinations — it reaches a hard limit. Scientists have calculated that simulating the behaviour of a molecule with 300 atoms would require a classical computer to consider more possible states than there are atoms in the observable universe. No amount of additional processing power resolves this problem. The architecture itself is the constraint.
Quantum computers approach computation differently. A qubit can be in a superposition of 0 and 1 simultaneously. Two qubits in superposition can represent four states at once. Ten qubits can represent 1,024 states simultaneously. According to research from IBM, a 1,000-qubit processor can in principle represent more states simultaneously than there are particles in the known universe.
This does not mean a quantum computer is simply faster. It means it can approach certain categories of problems — optimisation, simulation, cryptography — in a way that is structurally different from classical computation, exploring many possibilities simultaneously rather than sequentially.
Superposition and Entanglement: The Two Core Principles
Superposition
Superposition is the quantum property that allows a qubit to exist in multiple states at once. The analogy most physicists use is a coin spinning in the air — it is neither heads nor tails until it lands. A qubit in superposition is similarly undecided until it is measured. Before measurement, it contributes to a calculation as if all its possible values exist simultaneously.
This property is what gives quantum computers their computational power — but it is also what makes them fragile. Any interaction with the environment — heat, vibration, electromagnetic interference — can collapse a qubit’s superposition prematurely, introducing errors. This phenomenon is called decoherence, and managing it is one of the central engineering challenges of quantum computing.
Entanglement
Entanglement is the quantum property — described in detail in our article on quantum entanglement — by which two qubits become correlated such that the state of one instantly determines the state of the other, regardless of the distance between them. In a quantum computer, entanglement is used to link qubits so that operations on one affect others in coordinated ways, allowing complex relationships between variables to be processed simultaneously.
Together, superposition and entanglement are what give quantum computers their advantage over classical machines for specific problem types. They are not magic — they are precise physical phenomena, mathematically well understood, that happen to be extraordinarily useful for computation.
What IBM, Google and Microsoft Have Achieved in 2025 and 2026
The past eighteen months have produced milestones that the quantum computing field has been working toward for decades.
Google Willow and the Quantum Echoes Breakthrough
In December 2024, Google unveiled its Willow quantum chip — a 105-qubit superconducting processor that represented a significant advance in quantum error correction. According to Google’s published research, Willow performed a benchmark calculation in under five minutes that would take the world’s fastest classical supercomputers 10 septillion years to complete. That is a number with 25 zeros.
In 2026, Google followed this with the Quantum Echoes algorithm breakthrough, demonstrating the first verifiable quantum advantage on a practically relevant algorithm — the out-of-order time correlator — running 13,000 times faster on Willow than on classical supercomputers. This was not a contrived benchmark designed to favour quantum hardware. It was a calculation relevant to materials science and quantum chemistry research.
IBM Nighthawk and the Path to Fault Tolerance
IBM has pursued a strategy of systematic scaling with a publicly stated roadmap. According to IBM’s Quantum Computing Report, the company’s Flamingo processor — a 1,386-qubit multi-chip system launched in 2024 — leverages quantum communication links to connect multiple processors, enabling parallelisation at a scale not previously achieved.
In 2026, IBM’s Nighthawk processor — a 120-qubit system focused on error correction rather than raw qubit count — achieved a 10x speedup in error correction performance one year ahead of its published roadmap. IBM is targeting verified quantum advantage by the end of 2026, and its partnership with Cisco is aimed at building networked distributed quantum infrastructure by 2030.
Microsoft and the Majorana Connection
Microsoft has taken a fundamentally different approach to quantum hardware, based on a type of particle called the Majorana fermion — a particle that is its own antiparticle, first theorised by the physicist whose story we told in our article on Ettore Majorana.
In February 2025, Microsoft announced its Majorana 1 chip — the first quantum processor built using topological qubits derived from Majorana fermion physics. According to Microsoft’s research, topological qubits are inherently more resistant to decoherence than conventional superconducting qubits because the quantum information is stored in the global topology of the system rather than in any single physical location. This makes them significantly harder to disturb with environmental noise.
Studies from the Microsoft-Quantinuum collaboration have demonstrated logical qubit error rates significantly below the threshold needed for practical fault-tolerant computation — a milestone researchers have pursued for over two decades.
Real-World Example: Drug Discovery in Minutes
In March 2025, a quantum computing research team used an IBM quantum system to perform a medical simulation that illustrated the technology’s practical potential with unusual clarity.
The simulation modelled the quantum behaviour of a small protein relevant to a specific disease pathway — a calculation that classical computers had been unable to perform accurately because the quantum interactions between electrons in the protein are too complex for classical methods to capture precisely. The quantum processor completed the simulation in a time that would have been practically impossible for classical hardware.
This is the application that justifies most of the investment in quantum computing: pharmaceutical research. According to McKinsey research published in 2025, quantum computing could accelerate drug discovery timelines by 30 to 50 percent for specific classes of molecular simulation problems, potentially reducing the average cost of bringing a new drug to market by hundreds of millions of dollars.
The same principle applies to materials science — designing new superconductors, batteries, and catalysts — where the quantum behaviour of electrons is precisely what determines a material’s properties, and precisely what classical computers cannot simulate accurately at scale.
Where Quantum Computing Will Change the World
Cryptography and Cybersecurity
The most urgent near-term implication of quantum computing is cryptographic. Most internet security today relies on the fact that factoring very large numbers into their prime components is computationally infeasible for classical computers. A sufficiently powerful quantum computer running Shor’s algorithm could break this encryption. According to research from the National Institute of Standards and Technology (NIST), which finalised post-quantum cryptographic standards in 2024, organisations should already be migrating to quantum-resistant encryption protocols. Vodafone and IBM announced a collaboration in March 2025 specifically to develop quantum-safe cryptography for smartphone networks.
Climate and Energy
Quantum chemistry simulations could dramatically accelerate the design of new catalysts for carbon capture, more efficient solar cells, and better electrolysers for green hydrogen production. Scientists have observed that the key bottleneck in many clean energy technologies is not a lack of investment but a lack of understanding of the precise quantum chemistry involved — understanding that quantum computers are uniquely positioned to provide.
Artificial Intelligence
Quantum machine learning — using quantum processors to train and run AI models — remains early-stage, but researchers have identified specific classes of optimisation problems in AI training where quantum approaches show theoretical advantage. According to studies from Google Quantum AI, quantum-enhanced optimisation could reduce the energy cost of training large AI models, which currently consume electricity at a scale comparable to small countries.
The Honest Picture: What Quantum Computing Cannot Yet Do
It is important to be accurate about where quantum computing actually stands in 2026, because the field has a long history of overpromising.
Current quantum processors — even the most advanced — are what researchers call NISQ devices: Noisy Intermediate-Scale Quantum machines. They are real quantum computers, but they are imperfect ones. Error rates remain significant. According to analysis from Riverlane, a quantum error correction software company, practical fault-tolerant quantum computing will require processors with tens of thousands to millions of physical qubits — a scale that current hardware, which tops out around 1,000 to 2,000 qubits, falls far short of.
The 2025 and 2026 milestones are genuine and significant. They validate that the physics works and that the engineering path is tractable. They do not mean that quantum computers will replace classical computers, or that they are ready for general commercial use. For most computational tasks — including most of what businesses and individuals do with computers every day — classical computers remain far superior.
The realistic near-term picture is hybrid systems: quantum processors handling specific subroutines for which they provide a genuine advantage, integrated with classical computing infrastructure that handles everything else.
Legacy: Why Feynman’s 1981 Idea Is Now Reality
In 1981, the physicist Richard Feynman gave a lecture at MIT in which he argued that because classical computers could not efficiently simulate quantum systems, the solution was obvious: build a computer that is itself quantum. He sketched the conceptual outline of what such a machine would require. At the time, it was treated as an interesting theoretical observation by a characteristically provocative thinker.
Forty-five years later, the machines Feynman imagined exist. They are imperfect and limited compared to what the field’s long-term roadmaps envision. But they are real, they are operational, and they are already producing results that no classical computer can reproduce. The idea has become engineering. The engineering is becoming technology.
According to market research from McKinsey, the quantum computing industry is expected to generate between $450 billion and $850 billion in value by 2040 across pharmaceuticals, chemicals, finance, and logistics. That projection is speculative — timelines in quantum computing have repeatedly slipped — but it reflects the genuine consensus in the scientific and commercial communities that the technology’s eventual impact will be transformative.
What Scientists and Researchers Say
Hartmut Neven, founder and director of Google Quantum AI, described the Willow chip results as crossing a threshold that researchers had been working toward for a decade. “We are now entering a new era,” he said in comments accompanying the December 2024 announcement, “where quantum computers can do things that classical computers simply cannot.”
Jay Gambetta, IBM’s Vice President of Quantum Computing, has consistently emphasised the importance of the roadmap approach over individual headline-grabbing claims. “What matters,” he has said, “is not any single benchmark result but consistent, reproducible progress along a defined technical trajectory.” IBM’s 2026 targets — verified quantum advantage by year-end — represent that measured approach applied to a decade of hardware development.
Scientists have observed that the most significant recent development is not any single processor or algorithm, but the convergence of multiple independent approaches — superconducting qubits at Google and IBM, topological qubits at Microsoft, trapped ions at IonQ and Quantinuum — all showing meaningful progress simultaneously. This convergence suggests the field is approaching its breakthroughs from multiple directions at once, reducing the risk that any single technical obstacle can halt progress entirely.
Frequently Asked Questions
What is a qubit and how is it different from a classical bit?
A classical bit is a binary switch — it is either 0 or 1 at any given moment. A qubit is a quantum mechanical system — such as the spin of an electron or the polarisation of a photon — that can exist in a superposition of 0 and 1 simultaneously until it is measured. This property, combined with entanglement between multiple qubits, is what gives quantum computers their computational advantage for specific problem types.
When will quantum computers be widely available?
Access to quantum computing is already available through cloud platforms — IBM Quantum, Google Quantum AI, Microsoft Azure Quantum, and Amazon Braket all offer quantum computing as a service that researchers and businesses can access today. Fully fault-tolerant quantum computers capable of broad general-purpose use are projected to require hardware advances that most researchers place in the early-to-mid 2030s, though the timeline remains uncertain.
Will quantum computers break internet encryption?
A sufficiently large fault-tolerant quantum computer running Shor’s algorithm could break the RSA encryption that currently underpins most internet security. According to NIST, which published post-quantum cryptographic standards in 2024, current quantum hardware is far from this capability — but organisations should begin transitioning to quantum-resistant encryption now, because data encrypted today could be stored and decrypted later once capable quantum hardware exists. This threat is sometimes called “harvest now, decrypt later.”
Is quantum computing the same as artificial intelligence?
No. Quantum computing is a hardware paradigm — a different way of building and operating computing processors, based on quantum mechanical principles. Artificial intelligence is a software paradigm — a set of algorithms and techniques for pattern recognition, learning, and decision-making. The two are distinct fields, though researchers are actively exploring how quantum hardware might accelerate specific AI computations in the future.
What is quantum supremacy and has it been achieved?
Quantum supremacy — also called quantum advantage — refers to demonstrating that a quantum computer can perform a specific task faster than the best available classical computer. Google first claimed quantum supremacy in 2019 with its Sycamore processor. That claim was contested. In 2026, Google’s Quantum Echoes result — running 13,000 times faster than classical hardware on a practically relevant algorithm — represents a more robust and less disputed demonstration of genuine quantum advantage.
Further Reading
Recommended Reading
- Google Quantum AI — Learning Resources — Official educational materials from Google’s quantum research division
- IBM Quantum Learning — Free courses and documentation on quantum computing from IBM
- Quantum Computing: An Applied Approach by Jack Hidary — The most practical and accessible technical introduction to the field
- The Quantum Age by John Preskill — A clear overview of where quantum technology is heading from one of the field’s founding researchers
Sources
- Technerdo — Quantum Computing Milestones 2025-2026: IBM, Google, IonQ, Quantinuum (April 2026)
- SpinQ — Quantum Computers: The Revolutionary Technology Transforming Computing in 2026 (February 2026)
- SpinQ — Quantum Computing Companies: Global Leaders in 2026 (February 2026)
- Programming Helper — Quantum Computing Commercial Breakthrough 2026: IBM, Google, and Microsoft (January 2026)
- Programming Helper — The Quantum Computing Race Heats Up: IBM, Google, Microsoft Breakthroughs (January 2026)
- The Quantum Insider — Quantum Computing Roadmaps and Leading Players in 2025 (December 2025)
- Wissen Research — Evolution of Quantum Computing till 2026: Trends and Breakthroughs
- Wikipedia — Quantum Computing
- Wikipedia — Qubit
About the Author
Baryon is the writer and editor behind Web News For Us. Fascinated by big unanswered questions in physics and cosmology — from the arrow of time to the nature of consciousness and the possibility of parallel universes — he also deeply explores the lives, wisdom, and timeless teachings of legendary thinkers, mystics, and spiritual figures through the Books and Legends category. He writes to make complex scientific concepts and profound spiritual insights accessible, accurate, and deeply engaging for curious minds everywhere.
Baryon is the writer and editor behind Web News For Us. Fascinated by big unanswered questions in physics and cosmology — from the arrow of time to the nature of consciousness and the possibility of parallel universes — he also deeply explores the lives, wisdom, and timeless teachings of legendary thinkers, mystics, and spiritual figures through the Books & Legends category.
He writes to make complex scientific concepts and profound spiritual insights accessible, accurate, and deeply engaging for curious minds everywhere.
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