What is a quantum processing unit (QPU)?

How do QPUs work in quantum computing?

Processors based on classical digital electronics will process and calculate using bits representing programmatic instructions and data.

By contrast, QPUs operate using the advanced concepts of quantum physics. They are based on qubits that involve superposition and entanglement principles. This allows a qubit to represent a logical 1, a logical 0, or any quantum value between the two. The data within a qubit is presented through its subatomic particles' alignment or spin.

Think of a qubit as a sphere, and the data within the qubit is a line -- or a vector -- extending from the sphere's center to some point on the circumference of the sphere. As the vector changes, the position of that line changes, representing different data.

The QPU can hold and manage 100 or more qubits, and is responsible for maintaining, managing and handling errors for each incredibly sensitive qubit. QPU designs can create qubits using electronics or light. For example, qubits based on electronics use Josephson Junctions to create superconducting qubits. Qubits based on light will use photons of laser light. The varied types of qubits created in QPUs include the following:

• Neutral atoms can be charged with lasers and are suited for scaling and performing operations.
• Photons are light particles that can be harnessed to send quantum information across long distances through optical fiber cables. These kinds of particles are used in quantum communication and quantum cryptography.
• Quantum dots are small semiconductors that work with a single electron as a qubit. These offer scalability and compatibility with existing semiconductor technology, enabling simpler interfaces.
• Superconducting qubits are built from superconducting materials operating at temperatures near absolute zero. These qubits allow high-performance calculations and granular control.
• Trapped ion qubits are atoms with electrical charge. These qubits offer long coherence times and allow highly detailed measurements.

Ultimately, the choice of qubit will depend on the computing tasks and the QPU manufacturer's design direction.

QPUs will typically include an array of quantum logic gates used to operate on qubit data. There are many kinds of quantum gates, each forming a building block that provides a different processing outcome for the qubit and its data. In effect, quantum gates offer more of a mathematical process than a simple logical result. This enables many quantum gates to be assembled into sophisticated arrays representing complex mathematical algorithms. It is these algorithms that are primarily responsible for performing calculations on qubits. Resulting outputs can be measured and represented through traditional circuitry, where traditional computers can record and describe the resulting information.

QPUs vs. GPUs and other processors: A conceptual comparison

The QPU has a place in the spectrum of varied processors, including CPUs, GPUs and NPUs. Each processor type can support various specialized processing tasks within different computer designs. The key attributes of each processor include the following:

• CPU. The traditional central processing unit (CPU) is a general-purpose architecture focused on processing sequential data and performing linear tasks such as moving data and managing control or input/output. CPU designs have evolved and become highly complex to support changing demands, such as multimedia and virtualization optimizations. However, CPUs are not typically designed as computational devices, and their math capabilities are limited, creating the need for specialized processors.
• GPU. The graphics processing unit (GPU) emerged with the demands for greater visualization, such as 3D gaming and business data visualization, such as AutoCAD. GPUs offer specialized math optimizations and parallel processing capabilities ideal for performing math tasks for graphics, scientific calculations and several machine learning (ML) tasks. GPUs can be employed in quantum computing systems to offload some fundamental tasks from QPUs.
• NPU. The neural processing unit (NPU) is designed to handle complex tasks with specific types of mathematical computations in ways that mimic the function of the human brain. NPUs are primarily employed with ML and AI processing systems. Although there is no notable NPU use in quantum systems now, there is no reason why quantum systems designed for ML and AI tasks might not employ NPUs to offload some tasks from the QPU.
• QPU. The QPU is designed to process large-scale quantum algorithms using quantum information based on qubits. A processor designed to operate with quantum principles can perform more complex and probabilistic calculations than the most powerful supercomputers using traditional processors.

It's important to note that QPUs are not intended to replace CPUs or other specialized processor types. Instead, QPUs provide a powerful tool to tackle the most complex and demanding computational problems. Consequently, QPUs can be used with other processor types and are often integrated into high-performance computing platforms with GPUs and CPUs.

Potential QPU use cases and applications

When considered objectively alongside traditional processor types, QPUs are simply another type of specialized processor intended to address specific computing problems better than other processor types. The principal benefit of QPUs is their ability to resolve highly complex mathematical problems that can be almost impossible (or at least impractical) for computers based on other processor types. This makes QPUs suitable for some of the most challenging computing use cases and applications, including the following:

• Quantum simulation. Modeling and simulating complex quantum particle systems enables researchers to predict quantum behaviors and outcomes before designing and building real-life quantum devices.
• Quantum cryptography. QPUs can develop and implement powerful new cryptographic algorithms to secure data and protect businesses and users.
• Pharmaceutical and chemical research. QPUs in quantum computers can simulate the behaviors of complex molecules and biochemical reactions. This can vastly accelerate new drug development and validate the effectiveness of new medical treatments. In chemical research, QPUs can look for dangerous or destructive chemical reactions, improve processes for mitigating carbon breakdown and perform tasks too complex for traditional computers.
• Materials research. QPUs can be used to research and comprehend the nuances of physical matter to solve sophisticated problems in areas such as creating new and lighter aircraft materials, improving solar power collection and building superior batteries.
• ML and AI. ML and AI models are already evolving into complex entities with substantial computing demands and significant power consumption. QPUs can run quantum algorithms that vastly accelerate ML and help AI consider alternative solutions for complex learning problems.

What is the current state of QPU development?

QPU development is advancing rapidly in 2025. This advancement is largely driven by the escalating demands on traditional computing systems and the potential for further advancement in complex research endeavors.

QPU hardware is getting better. Leading technology companies such as D-Wave Systems, Google, IBM, Intel, IQM, Nvidia, QuEra, Pasqal and Rigetti Computing are developing QPUs that can run quantum algorithms. QuantWare launched the world's first commercially available superconducting processor. In addition, the software and development platforms used to build quantum software are advancing and working toward standardizing quantum programming languages.

Despite the advances, significant challenges remain in QPU development. Early QPUs are noisy, resulting in high error rates and limited qubit coherence. QPU scalability is also limited, restricting the practical applications possible for QPU technology. Software tools needed to develop, debug, test and implement quantum algorithms also need greater advancement to use the evolving market QPUs.

When will QPUs become widely available?

Commercial QPUs are appearing, but the journey to commercial devices will likely be long and arduous.

The nature of quantum computing demands carefully controlled laboratory conditions involving vacuums, powerful magnetic containment fields and liquid refrigeration capable of lowering the qubit temperatures near absolute zero. These current environmental requirements will likely restrict QPU use to quantum computers relegated to dedicated facilities such as government laboratories and major public cloud providers, where quantum computing can be offered to the commercial public as a service.

Similarly, QPUs are specialized processor types intended to solve a narrow range of sophisticated problems. Just as commercial devices would not be based on a GPU or NPU alone, it is impractical to expect QPUs to appear in home computers or smartphones -- there is no personal need for the computing that QPUs provide. Even deployment in business data centers poses an enormous cost and a serious operational challenge for any organization.

Ultimately, while QPUs and other components used to build quantum computers are appearing today, their presence and capabilities are expected to remain limited for the foreseeable future.