A primary difference between classical and quantum computers is that quantum computers use qubits instead of bits to store exponentially more information. While quantum computing does use binary code, qubits process information differently from classical computers. But what are qubits and where do they come from? 

Generally, qubits are created by manipulating and measuring quantum particles (the smallest known building blocks of the physical universe), such as photons, electrons, trapped ions and atoms. Qubits can also engineer systems that behave like a quantum particle, as in superconducting circuits.

To manipulate such particles, qubits must be kept extremely cold to minimize noise and prevent them from providing inaccurate results or errors resulting from unintended decoherence. 

There are many different types of qubits used in quantum computing today, with some better suited for different types of tasks. 

A few of the more common types of qubits in use are as follows:

• Superconducting qubits: Made from superconducting materials operating at extremely low temperatures, these qubits are favored for their speed in performing computations and fine-tuned control. 

• Trapped ion qubits: Trapped ion particles can also be used as qubits and are noted for long coherence times and high-fidelity measurements. 

• Quantum dots: Quantum dots are small semiconductors that capture a single electron and use it as a qubit, offering promising potential for scalability and compatibility with existing semiconductor technology. 

• Photons: Photons are individual light particles used to send quantum information across long distances through optical fiber cables and are currently being used in quantum communication and quantum cryptography. 

• Neutral atoms: Commonly occurring neutral atoms charged with lasers are well suited for scaling and performing operations.

When processing a complex problem, such as factoring large numbers, classical bits become bound up by holding large quantities of information. Quantum bits behave differently. Because qubits can hold a superposition, a quantum computer that uses qubits can approach the problem in ways different from classical computers.

As a helpful analogy for understanding how quantum computers use qubits to solve complicated problems, imagine you are standing in the center of a complicated maze. To escape the maze, a traditional computer would have to “brute force” the problem, trying every possible combination of paths to find the exit. This kind of computer would use bits to explore new paths and remember which ones are dead ends.

Comparatively, a quantum computer might derive a bird’s-eye view of the maze, testing multiple paths simultaneously and using quantum interference to reveal the correct solution. However, qubits don't test multiple paths at once; instead, quantum computers measure the probability amplitudes of qubits to determine an outcome. These amplitudes function like waves, overlapping and interfering with each other. When asynchronous waves overlap, it effectively eliminates possible solutions to complex problems, and the realized coherent wave or waves present the solution. 

When discussing quantum computers, it is important to understand that quantum mechanics is not like traditional physics. The behaviors of quantum particles often appear to be bizarre, counterintuitive or even impossible. Yet the laws of quantum mechanics dictate the order of the natural world.

Describing the behaviors of quantum particles presents a unique challenge. Most common-sense paradigms for the natural world lack the vocabulary to communicate the surprising behaviors of quantum particles. 

To understand quantum computing, it is important to understand a few key terms:

• Superposition
• Entanglement
• Decoherence
• Interference.

A qubit itself isn't very useful. But it can place the quantum information it holds into a state of superposition, which represents a combination of all possible configurations of the qubit. Groups of qubits in superposition can create complex, multidimensional computational spaces. Complex problems can be represented in new ways in these spaces.

This superposition of qubits gives quantum computers their inherent parallelism, allowing them to process many inputs simultaneously.

Entanglement is the ability of qubits to correlate their state with other qubits. Entangled systems are so intrinsically linked that when quantum processors measure a single entangled qubit, they can immediately determine information about other qubits in the entangled system. 

When a quantum system is measured, its state collapses from a superposition of possibilities into a binary state, which can be registered like binary code as either a zero or a one. 

Decoherence is the process in which a system in a quantum state collapses into a nonquantum state. It can be intentionally triggered by measuring a quantum system or by other environmental factors (sometimes these factors trigger it unintentionally). Decoherence allows quantum computers to provide measurements and interact with classical computers. 

An environment of entangled qubits placed into a state of collective superposition structures information in a way that looks like waves, with amplitudes associated with each outcome. These amplitudes become the probabilities of the outcomes of a measurement of the system. These waves can build on each other when many of them peak at a particular outcome, or cancel each other out when peaks and troughs interact. Amplifying a probability or canceling out others are both forms of interference.

To better understand quantum computing, consider that two counterintuitive ideas can both be true. The first is that objects that can be measured—qubits in superposition with defined probability amplitudes—behave randomly. The second is that objects too distant to influence each other—entangled qubits—can still behave in ways that, though individually random, are somehow strongly correlated. 

A computation on a quantum computer works by preparing a superposition of computational states. A quantum circuit, prepared by the user, uses operations to generate entanglement, leading to interference between these different states, as governed by an algorithm. Many possible outcomes are canceled out through interference, while others are amplified. The amplified outcomes are the solutions to the computation.

Quantum computing is built on the principles of quantum mechanics, which describe how subatomic particles behave differently from macrolevel physics. But because quantum mechanics provides the foundational laws for our entire universe, on a subatomic level, every system is a quantum system.

For this reason, we can say that while conventional computers are also built on top of quantum systems, they fail to take full advantage of the quantum mechanical properties during their calculations. Quantum computers take better advantage of quantum mechanics to conduct calculations that even high-performance computers cannot. 

From antiquated punch-card adders to modern supercomputers, traditional (or classical) computers essentially function in the same way. These machines generally perform calculations sequentially, storing data by using binary bits of information. Each bit represents either a 0 or 1.

When combined into binary code and manipulated by using logic operations, we can use computers to create everything from simple operating systems to the most advanced supercomputing calculations. 

Quantum computers function similarly to classical computers, but instead of bits, quantum computing uses qubits. These qubits are special systems that act like subatomic particles made of atoms, superconducting electric circuits or other systems that data in a set of amplitudes applied to both 0 and 1, rather than just two states (0 or 1). This complicated quantum mechanical concept is called a superposition. Through a process called quantum entanglement, those amplitudes can apply to multiple qubits simultaneously.

Classical computing

• Used by common, multipurpose computers and devices.
• Stores information in bits with a discrete number of possible states, 0 or 1.
• Processes data logically and sequentially. 

Quantum computing

• Used by specialized and experimental quantum mechanics-based quantum hardware.
• Stores information in qubits as 0, 1 or a superposition of 0 and 1.
• Processes data with quantum logic at parallel instances, relying on interference.

Quantum processors do not perform mathematical equations the same way classical computers do. Unlike classical computers that must compute every step of a complicated calculation, quantum circuits made from logical qubits can process enormous datasets simultaneously with different operations, improving efficiency by many orders of magnitude for certain problems.

Quantum computers have this capability because they are probabilistic, finding the most likely solution to a problem, while traditional computers are deterministic, requiring laborious computations to determine a specific singular outcome of any inputs. 

While traditional computers commonly provide singular answers, probabilistic quantum machines typically provide ranges of possible answers. This range might make quantum seem less precise than traditional computation; however, for the kinds of incredibly complex problems quantum computers might one day solve, this way of computing could potentially save hundreds of thousands of years of traditional computations. 

While fully realized quantum computers would be far superior to classical computers for certain kinds of problems requiring large data sets or for completing other problems like advanced prime factoring, quantum computing is not ideal for every, or even most problems.

Realistically, classical computers will continue to be used for the majority of their current applications. However, cloud-connected quantum computers or hybrid ecosystems are already being implemented to explore a wide array of advanced applications. As quantum computing continues to progress, we can expect this advanced technology to not only impact existing industries, but potentially unlock entire new ones as well.  

While no longer simply theoretical, quantum computing is still under development. As scientists around the world strive to discover new techniques to improve the speed, power and efficiency of quantum machines, technology is approaching a turning point. We understand the evolution of useful quantum computing using the concepts of quantum advantage and quantum utility.

Quantum utility refers to any quantum computation that provides reliable, accurate solutions to problems that are beyond the reach of brute force classical computing quantum-machine simulators. Previously, these problems were accessible only to classical approximation methods—usually problem-specific approximation methods carefully crafted to exploit the unique structures of a given problem.

Broadly defined, the term quantum advantage refers to a hypothetical quantum computer capable of outperforming all classical supercomputer methods for some problem, even approximate methods. A quantum computer capable of achieving the quantum advantage should be able to deliver a significant, practical benefit beyond all known classical computing methods—calculating solutions in a way that is cheaper, faster or more accurate than any available classical alternatives.

Because quantum computing now offers a viable alternative to classical approximation for certain problems, researchers say it is a useful tool for scientific exploration, or that it has utility. Quantum utility does not constitute a claim that quantum methods have achieved a proven speed-up over all known classical methods. This is a key difference from the concept of quantum advantage.

In 2019, leading researchers on the IBM Quantum team invented a metric known as quantum volume to assign a singular, calculable measurement of a quantum computer’s ability.

Quantum volume measures the largest quantum circuit that can pass a quantum volume test. The quantum volume test asks the quantum computer to run circuit with random gates and measures how often the circuits output the expected outcomes. However, as we continue scaling up quantum processors, it’s becoming clear that we need more than just quantum volume to fully encapsulate the performance of utility-scale quantum computers. 

While quantum volume is still one of a few ways in which we can measure errors within a quantum system, the IBM team introduced two additional metrics to better benchmark quantum computers, layer fidelity and circuit layer operations per second (CLOPS). 

An extremely valuable benchmark, layer fidelity provides a way to encapsulate the entire quantum processor’s ability to run circuits while revealing information about individual qubits, gates and crosstalk. By running the layer fidelity protocol, researchers can qualify the overall quantum device, while also gaining access to granular performance and error information about individual components. 

In addition to layer fidelity, IBM also defined a speed metric, circuit layer operations per second (CLOPS). Currently, CLOPS is a measure of how quickly our processors can run quantum volume circuits in series, acting as a measure of holistic system speed incorporating quantum and classical computing.

Together, layer fidelity and CLOPS provide a new way to benchmark systems that’s more meaningful to the people trying to improve and use our hardware. These metrics will make it easier to compare systems to one another, to compare our systems to other architectures, and to reflect performance gains across scales.

An IBM quantum processor is a wafer not much bigger than the silicon chips found in a laptop. However, modern quantum hardware systems, used to keep the instruments at an ultracold temperature, and the extra room-temperature electronic components to control the system and process quantum data, are about the size of an average car.

While the large footprint of a complete quantum hardware system makes most quantum computers anything but portable, researchers and computer scientists are still able to access off-site quantum computing capabilities through cloud computing. The main hardware components of a quantum computer are as follows:

Composed of qubits laid out in various configurations to allow for communication, quantum chips—also known as the quantum data plane—act as the brain of the quantum computer.

As the core component in a quantum computer, a quantum processor contains the system’s physical qubits and the structures required to hold them in place. Quantum processing units (QPUs) include the quantum chip, control electronics and classical compute hardware required for input and output.

Your desktop computer likely uses a fan to get cold enough to work. Quantum processors need to be very cold—about a hundredth of a degree above absolute zero—to minimize noise and avoid decoherence to retain their quantum states. This ultra-low temperature is achieved with supercooled superfluids. At these temperatures, certain materials exhibit an important quantum mechanical effect: electrons move through them without resistance. This effect makes them superconductors.  

When materials become superconductors, their electrons match up, forming Cooper pairs. These pairs can carry a charge across barriers, or insulators, through a process known as quantum tunneling. Two superconductors placed on either side of an insulator form a Josephson junction, a crucial piece of quantum computing hardware.

Quantum computers use circuits with capacitors and Josephson junctions as superconducting qubits. By firing microwave photons at these qubits, we can control their behavior and get them to hold, change and read out individual units of quantum information.