IBM Quantum technology
The fleet of IBM® quantum computers, all with at least 127 qubits, is the largest in the world. These quantum computers use superconducting transmon qubits, which are not the only kind of qubit, but which have many advantages. Combining our world-class quantum computers with Qiskit enables our users to explore how quantum computing can be useful in the world, today. Industry partners and researchers are using IBM Quantum® technology to explore meaningful computations and realistic applications. Let's explore the breadth of programs and services IBM Quantum offers partners.
If you are part of an institution that is a member of the IBM Quantum Network, make sure to reach out to your institution's quantum computing group to determine what benefits you have access to.
Learning objectives
By the end of this module, you should be able to:
- Recognize that solving meaningful problems will involve a combination of quantum and classical resources.
- Identify the hardware, software, and services available to solve meaningful problems.
- Describe how quantum computing performance is measured using scale, quality, and speed metrics. Recognize supporting benchmark metrics commonly used throughout the industry.
IBM Quantum Platform
IBM Quantum Platform provides a suite of quantum computing tools that brings together all of the research and development resources that users need to do great work, in one place. Users can create an account and sign in to get access to IBM quantum computers, view computer details, track workloads, and access enablement material in Documentation and Learning.
- Home page serves as the primary starting point for the product ecosystem, where users can get their API keys, view a summary of their instances and usage information, view recent job details, and access helpful links to other places across platform.
- Documentation aggregates Qiskit documentation, service documentation, and API reference information into one location, organized in a way that supports users' natural workflows.
- Learning is the home for educational material including courses and teaching modules, and the interactive Circuit Composer (coming soon). This combination graphical and code editor allows users to prototype, simulate, and debug circuits visually, and then run them on IBM quantum computers.
IBM Quantum Compute Service (formerly the Qiskit Runtime Service)
IBM Quantum Compute Service is a portable, secure, containerized architecture that runs quantum programs on a classical computing unit tightly integrated with the quantum processor. Quantum Compute allows the quantum computer to become a part of any computing environment to accelerate computation—similar to a graphics processing unit (GPU)—and handles the job orchestration and data transfer to the quantum processing unit, maximizing efficiency.
Qiskit and Quantum Compute make it simple to quickly orchestrate programs across compute resources on the cloud. IBM builds middleware for quantum to maximize the performance of quantum applications running across parallelized, cloud-based, quantum and classical computational resources. This middleware includes the circuit knitting toolbox and our quantum serverless architecture.
The circuit cutting Qiskit addon allows developers to cut large circuits into smaller circuits suitable for current quantum computers. Circuit knitting uses classical computation to take on some of the computational burden of a quantum circuit to exceed what we can achieve with either alone. Additional tools help reconstruct circuits with classical resources and stitch together final results.
Quantum Serverless is a multi-cloud orchestration toolkit to connect elastic classical resources with IBM Quantum Compute Service. Quantum serverless allows developers to focus on the code, rather than resource provisioning.
IBM superconducting quantum computers
IBM quantum processors use a physical type of qubit called a superconducting transmon qubit, which is made from superconducting materials patterned on a silicon substrate. Other quantum processors might use photonic qubits, which are made from single photons of light, or trapped-ion qubits, which store information in charged atomic particles. To facilitate the flow of electrical current, superconducting qubits need to be maintained at extremely low temperatures—close to absolute zero.
IBM 127-qubit processor
Quantum computing performance
Measuring quantum computing performance
A universal fault-tolerant quantum computer remains one of the grand challenges of modern computing. Today's quantum computers are not yet fully fault tolerant, so understanding their performance requires consideration of multiple factors beyond qubit count alone.
IBM Quantum characterizes quantum-computing performance using three fundamental dimensions:
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Scale: measured by programmable qubits, the qubits that users can directly control and incorporate into quantum algorithms.
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Quality: measured by qubit operations (QuOps), which indicate how many of the most computationally demanding operations a quantum computer can reliably execute before errors overwhelm the computation.
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Speed measured by maximum circuits per second, which describes a system's circuit throughput and the amount of useful computation it can perform over time.
Together, these metrics provide a high-level view of the computational capability, scalability, and efficiency of a quantum computer across hardware technologies and implementation approaches.
In addition to these primary metrics, a number of supporting benchmark metrics are widely used throughout the industry:
Check your understanding
True or false: The power of a quantum computer is determined by the number of qubits it has.
False. If a quantum computer has many qubits, but low circuit throughput and poor quality, then the information stored on any number of qubits will degrade before useful results can be obtained. The power of a quantum computer depends on scale, quality and speed.
What's next in quantum computing
Today’s quantum computers, and those expected for the foreseeable future, are noisy. This means they are sensitive to environmental disturbances that can impact the fidelity of results. In much the same way that classical computing evolved through the modular scaling of processors, efficient computation, and parallelization, we see quantum computing evolving to realize its full potential. As we work toward fully fault-tolerant quantum computers, we want to solve useful problems with the hardware and software we possess today.
Quantum utility
IBM Quantum and the University of California, Berkeley presented evidence that quantum computers can provide value sooner than expected thanks to advances in IBM Quantum hardware and error mitigation methods. Beyond just a proof of concept, we delivered results accurate enough to be useful. The model of computation we explored with this work is a core facet of many algorithms designed for near-term quantum computers.
The feedback loop between quantum and classical is key to advancing quantum technologies. With a focus on quantum utility, we use quantum to probe complex problems that challenge existing high-performance compute frameworks, then check the results classically. This continued back-and-forth of quantum running a complex circuit and classical computers verifying the quantum results will improve both computational domains and provide users confidence in the abilities of near-term quantum computers.
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In this experiment, we used all 127 qubits of our IBM Quantum Eagle processor to simulate the changing behavior of a system that naturally maps to a quantum computer, called the quantum Ising model. Ising models are simplifications of nature that represent interacting atoms as a lattice of interacting quantum two-choice systems in an energy field. These systems look a lot like the two-state qubits that make up our quantum computers, making them a good fit for testing the abilities of our methods. We used ZNE to try and accurately calculate a property of the system called its expectation value — essentially a weighted average of the possible outcomes of the circuit.
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Simultaneously, the Berkeley team attempted to simulate the same system using tensor network methods with the help of advanced supercomputers located at Lawrence Berkeley National Lab's National Energy Research Scientific Computing Center (NERSC) and at Purdue University.
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The quantum methods continued to agree with the exact methods. But eventually, the classical approximation methods started to falter as the difficulty was turned up.
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Finally, we asked both computers to run calculations beyond what could be calculated exactly — and the quantum computer returned an answer we were more confident to be correct. And while we can't prove whether that answer was actually correct, Eagle's success on the previous runs of the experiment gave us confidence that they were.
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Error Correction
Error correction has been a key area of research for decades. But for most of that time, theoretical error correction techniques have been impractical to implement on real quantum computers, most often due to the very large number of qubits needed. Indeed, many experts predict that practical fault tolerant quantum computing (FTQC) will require millions of physical qubits. But in a recent paper published on the cover of Nature, researchers from IBM introduced a new code, which we call the Gross code, that overcomes that limitation.
The paper High-threshold and low-overhead fault-tolerant quantum memory describes the new quantum error-correcting code that is roughly 10 times more efficient than previous methods at protecting delicate quantum data from accumulating errors. To consider how much closer we are now to the beginning of error correction, consider that using the Gross code, you can protect 12 logical qubits for roughly a million cycles of error checks using 288 qubits.
It is not expected that error correction will suddenly replace error mitigation and error suppression. Rather, over the next few years, error mitigation and suppression will continue to play a pivotal role, alongside increasing numbers of error-corrected qubits.
IBM Quantum Development Roadmap
We are now firmly in the era of quantum utility. That means quantum computers are better at quantum computing than classical computers, and can be leveraged by our users to discover new algorithms and search for quantum advantages. Our roadmap outlines our historic milestones and plans to achieve near-term quantum advantage by 2026.
By 2029, we will deliver Starling—a large-scale fault-tolerant quantum computer capable of running quantum circuits comprising 100 million quantum gates on 200 logical qubits. We are building this system right now at our historic facility in Poughkeepsie, New York. Learn more about our progress in the Guided Roadmap PDF.
Read more about the IBM Quantum development roadmap here.
5k challenge
IBM works together with the quantum research community to find potential use cases that could benefit from quantum computing. We provide increasingly powerful tools so users can explore pressing problems with quantum. In 2024, we released a tool capable of calculating unbiased observables of long, high-quality circuits. Finding what can be done with this combination of 100+ qubits and deep circuits was at one time called the "100x100 challenge". But the precise number of qubits and depth on each is less important than leveraging the power of the combination. Imagine what is possible with 5,000 quantum gates in a single computation. Users can run quantum circuits with complexity and runtime beyond the capabilities of the best classical computers today. We are excited to see what the quantum community will build to help us harness the power of quantum and solve important problems.
Quantum-centric supercomputers
Going beyond single chip processors is the key to solving problems at scale. In 2024, we introduced Crossbill, the first single processor made from multiple chips. These are the first steps to ushering in a new era of scaling, providing a clear path to 100,000 qubits and beyond with quantum-centric supercomputing. This is a modular computing architecture which enables scaling. It combines quantum communication and computation to increase computational capacity, while employing hybrid cloud middleware to seamlessly integrate quantum and classical workflows.
Solving the world’s most complex problems will require a combination of classical and quantum resources. Furthermore, it will depend on the continued collaboration between industry and academia.
Key takeaways
You can keep these key takeaways in mind:
- Today’s quantum computers are not fault tolerant.
- Three primary dimensions for evaluating quantum-computing performance are: scale (programmable qubits), quality (qubit operations), and speed (maximum circuits per second).
- Additional benchmarks such as Quantum Volume, CLOPS, and EPLG remain useful for understanding specific hardware characteristics and workloads.
- A joint IBM Quantum-UC Berkeley experiment presented evidence of IBM quantum computers delivering reliable, accurate results for challenging simulation problems at a scale of 127 qubits.
- Quantum-centric supercomputing means treating quantum as one piece of a broader HPC paradigm with classical and quantum working as one computational unit.