Learn About Building Quantum Computers Today

What Are Quantum Computers and How Do They Differ from Regular Computers

Quantum computers represent a fundamentally different approach to processing information compared to the computers most people use daily. Traditional computers, whether laptops, smartphones, or servers, process information using bits. A bit is the basic unit of information and can exist in one of two states: 0 or 1. Everything your computer does—from displaying this text to running complex calculations—comes down to manipulating billions of these 0s and 1s very rapidly.

Quantum computers work with quantum bits, or "qubits." The key difference is that a qubit can exist in a state called superposition, meaning it can be 0, 1, or both simultaneously until it is measured. This property allows quantum computers to explore many possible solutions to a problem at the same time, rather than checking solutions one after another like traditional computers do. For certain types of problems, this parallel processing capability could be dramatically faster.

Another important quantum property is entanglement. When qubits become entangled, the state of one qubit becomes connected to the state of another, even across distances. This means that measuring one entangled qubit instantly affects the others. This property enables quantum computers to process information in ways that traditional computers cannot replicate.

The difference in speed can be substantial for specific problems. For example, current supercomputers might take thousands of years to factor a very large number into its prime components. A sufficiently powerful quantum computer could potentially solve the same problem in hours or days. However, quantum computers are not faster at everything—they excel at particular categories of problems like optimization, cryptography, and simulating molecular behavior.

As of 2024, companies like IBM, Google, and others have built quantum computers with 100 to over 1,000 qubits. Google announced in 2023 that their Willow chip demonstrated "quantum advantage" on specific mathematical problems. These machines still require extreme conditions to operate, such as temperatures colder than outer space, making them expensive and complex to maintain.

Practical takeaway: Quantum computers solve different types of problems than regular computers. Understanding this distinction helps explain why they matter for certain fields but won't replace your laptop or phone.

The Physics Behind Quantum Computing

Building a quantum computer requires deep knowledge of quantum mechanics, the science that describes how particles behave at the smallest scales. At the quantum level, particles don't follow the same rules as objects in the everyday world. This unusual behavior is what makes quantum computing possible, but it also makes quantum computers extraordinarily difficult to build and maintain.

Superposition is one of the core principles. In classical physics, a coin is either heads or tails. In quantum mechanics, a particle can be in a superposition of multiple states simultaneously. A qubit can represent 0 and 1 at the same time, and this state persists until the qubit is measured. The moment you measure it, the superposition collapses into either 0 or 1. This counterintuitive behavior is real and has been verified countless times in laboratory experiments.

Entanglement is the second crucial principle. When two or more qubits become entangled, their quantum states become correlated in a way that has no classical equivalent. If you measure one entangled qubit and find it to be 0, the state of its entangled partner is instantly determined. Einstein famously called this "spooky action at a distance." While this doesn't allow faster-than-light communication, it does enable quantum computers to process information in parallel in ways classical computers cannot.

Interference is the third key principle. Quantum algorithms are designed so that wrong answers interfere destructively with each other and cancel out, while correct answers interfere constructively and amplify. This is why quantum computers can be faster at certain problems—the algorithm design guides the quantum system toward the right answer.

However, quantum systems are fragile. Environmental factors like heat, electromagnetic radiation, and vibrations cause what's called decoherence, which destroys the quantum properties that make the computer useful. This is why quantum computers need to be kept at temperatures near absolute zero (around -273 degrees Celsius) and isolated from external interference. Most quantum computers operate at about 0.015 Kelvin, which is colder than the vacuum of space.

Practical takeaway: The physics enabling quantum computing relies on principles that seem strange by everyday standards, but these principles allow quantum computers to tackle problems in new ways. Understanding the basic concepts helps explain why maintaining a quantum computer is so challenging.

Different Types of Quantum Computing Approaches

Researchers and companies are pursuing several different approaches to building quantum computers. There is no single consensus on which method will ultimately prove most practical or powerful. Each approach has different advantages and challenges. Learning about the main types provides insight into where the field is headed.

Superconducting qubits are currently the most developed approach. Companies like IBM and Google use this method. Superconducting qubits are tiny circuits cooled to near absolute zero where electrical resistance disappears. These qubits use the quantum properties of electromagnetic waves flowing through the circuits. IBM's quantum computers, for instance, use superconducting qubits and currently have systems with up to 433 qubits. The main advantage is that superconducting qubits can be manufactured using existing semiconductor technology. The main challenge is maintaining the extremely cold temperatures and dealing with decoherence.

Trapped ion qubits represent a second major approach. Companies like IonQ and Honeywell pursue this method. In this approach, individual ions (electrically charged atoms) are trapped using electric or magnetic fields and manipulated with lasers. Trapped ions can maintain their quantum state for relatively longer periods compared to some other approaches, which is advantageous. However, scaling up to very large numbers of qubits while maintaining control precision remains technically difficult.

Photonic quantum computing uses photons (particles of light) as qubits. Companies like Xanadu are developing this approach. Photonic systems can potentially operate at room temperature, which is a significant practical advantage over superconducting or trapped ion systems. The challenge is that photons interact weakly with each other, making it difficult to create the entanglement needed for computation.

Topological qubits are a more theoretical approach still under development. These would be based on exotic quantum states called anyons. The potential advantage is that topological qubits might be more resistant to decoherence naturally. However, creating and manipulating topological qubits remains largely experimental. Microsoft and others are investing in this long-term approach.

Neutral atom qubits are an emerging approach where individual atoms are trapped in optical tweezers (focused laser beams). Companies like Atom Computing and QuEra are advancing this technology. This method can potentially scale to many qubits and is being actively developed.

Practical takeaway: Multiple paths are being pursued to build quantum computers. No single approach has definitively won out, meaning the field remains in active development with room for different technologies to contribute.

Current Capabilities and Limitations of Today's Quantum Computers

As of 2024, quantum computers exist and are functional, but they remain in an early stage sometimes called the "NISQ era" (Noisy Intermediate-Scale Quantum). This means current quantum computers are not error-free and not yet large enough to solve most real-world problems better than classical computers. Understanding current capabilities and limitations is essential for realistic expectations about quantum computing today.

Current quantum computers excel at specific narrow problems. IBM's quantum computers have been used to simulate molecular behavior, optimize certain types of problems, and perform mathematical calculations that would be difficult for classical computers. Google's Willow chip demonstrated quantum advantage by solving a specific mathematical problem faster than the world's fastest classical supercomputer could. However, these demonstrations involve highly specialized problems rather than practical, everyday applications.

The number of qubits has grown significantly. In 2019, Google announced a 53-qubit processor. By 2024, IBM had systems with over 400 qubits, and other companies were approaching or exceeding 1,000 qubits. However, the number of qubits alone does not determine computational power because of error rates. Currently, quantum computers have error rates of about 0.1% to 1% per operation, meaning mistakes accumulate quickly. A classical computer has error rates millions of times lower.

Quantum error correction is a major focus of current research. To solve this problem, researchers use multiple physical q