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Classical computers are still the practical choice for everyday computing. Quantum computers use qubits and quantum effects that could help with specific problems—especially simulating quantum systems and running certain algorithms—but today’s machines are noisy and limited. They are best understood as specialized machines that may complement classical computers, not replace them.
What is the difference between quantum and classical computing?
A classical computer processes information using bits, ordinarily represented as 0 or 1. A quantum computer uses qubits, which can be in a superposition of states and can be entangled with other qubits. Those properties give quantum algorithms a different way to process information, but they do not make every possible answer available to read at once.
Measurement yields limited information about a quantum state. Algorithms must use operations such as interference to make a useful result more likely or reveal a useful property before measurement. That is why a quantum computer is not simply a classical computer that tries every answer simultaneously and hands back the winner. NIST quotes quantum researcher Stephen Jordan: “But contrary to popular belief, this doesn’t allow quantum computers to do an efficient ‘brute force’ search over all the potential solutions.” NIST’s quantum computing explainer discusses the distinction.
What can a quantum computer do that a classical computer cannot?
There is no general-purpose task list on which quantum computers have been shown to beat classical computers across the board. The potential advantage depends on the problem, the algorithm, the device’s error rate, and the best available classical approach.
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Simulate quantum systems
Quantum systems such as molecules and materials are themselves governed by quantum mechanics. A quantum computer may represent and simulate aspects of those systems more naturally than a classical computer can. This is a central motivation for quantum computing, though practical value depends on building systems capable of performing useful, reliable calculations.
Run particular algorithms
Shor’s algorithm provides a theoretical way to factor large numbers efficiently. That matters because factoring is relevant to some public-key cryptography. The result is a potential future application, not evidence that current quantum computers can break ordinary internet encryption.
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Explore optimization problems
Researchers are investigating quantum approaches to optimization, but broad practical superiority over classical optimization methods has not been established. A promising algorithm or theoretical speedup does not by itself show that a real quantum device will solve a useful instance faster or better than the strongest classical method.
Are quantum computers faster than regular computers?
Not in general. “Faster” only makes sense when comparing a defined task, a specific quantum device and algorithm, and a strong classical method under comparable conditions. Quantum computers are not a faster replacement for routine uses such as running applications, browsing the web, or handling ordinary business workloads.
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IBM and the University of Chicago announced on July 30, 2026, that a reported computation met what they called “the fundamental criteria for quantum advantage.” Their announcement describes a specific computation, including results beyond leading classical simulation methods and a way to establish trust in the result. That is a claim about the reported demonstration, not proof that quantum computers are generally faster or more useful than classical computers. Read the organizations’ announcement.
There is no single performance number that fairly compares quantum and classical computing across workloads. A useful comparison asks what was computed, what output was required, how errors were controlled, and whether the result beats the best classical method for that task. Qubit count alone does not answer those questions.
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Why are current quantum computers limited?
Qubits are fragile: environmental influences can disturb them and introduce errors. Those errors limit the complexity, or depth, of circuits that current devices can run usefully. A large-scale machine must control errors while keeping many qubits operating coherently.
Quantum error correction and fault-tolerant computing are major engineering goals, not features that can be assumed for present-day systems. NIST notes that a large machine for applications such as Shor’s algorithm may require millions of reliably operating qubits. That figure describes the scale discussed for such a future application; it is not a current device benchmark. The U.S. Department of Energy’s December 2024 roadmap likewise identifies noise-limited circuit complexity and the need for progress in error correction, hardware, architecture, algorithms, software, and applications. Read the DOE roadmap.
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Can quantum computers break encryption today?
The cited sources do not establish that current quantum computers can break ordinary internet encryption. Shor’s algorithm is a theoretical concern for some public-key cryptography if a sufficiently large, fault-tolerant quantum computer is built. Current machines’ noise and limited useful circuit depth are important barriers between that theoretical capability and a practical attack.
Will quantum computers replace classical computers?
No. Classical computers are mature, reliable general-purpose systems, while quantum computers are specialized and error-prone. The likely relationship is complementary: a classical computer handles ordinary computing and can work alongside a quantum processor for a task where a suitable quantum algorithm offers an advantage. The quantum device does not remove the need for classical systems to prepare, control, and use computation.
How to judge a claim of quantum advantage
Before treating a headline or product claim as evidence of a practical advantage, check the comparison itself:
- Task: What exact problem or computation was performed?
- Classical baseline: Which classical method was used, and was it a leading method for that task?
- Output: Did the computation produce a useful answer or property, rather than merely a large or difficult-to-simulate quantum state?
- Error control: How were noise and errors handled, and how was the result checked?
- Practical value: Does the result help with an application, or demonstrate a capability without establishing broader usefulness?
For readers who want to study algorithms, IBM Quantum Learning offers a course on quantum query algorithms.
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