Quantum in Context: The Case for On-Premises Quantum Computers

Quantum in Context: The Case for On-Premises Quantum Computers

The News: IBM and Rensselaer Polytechnic Institute (RPI) announced on April 5 that they had installed a 127-qubit IBM Quantum System One at the university’s campus in Troy, New York. This installation marks the first time IBM has placed such a system on a campus for education, research, and workforce development. See the press release on the IBM website and the RPI article.

Quantum in Context: The Case for On-Premises Quantum Computers

Analyst Take: It’s not unusual for university faculty and students to use quantum computing systems, though most of that activity has been on the cloud. Cloud access is part of the so-called, overused, clichéd “democratization of quantum computing.” Why bother having your own quantum computing system when you can access one from anywhere? Though I used to be skeptical of on-premises installations, the nature of quantum computing has changed, so it sometimes makes sense to have dedicated, local machines.

Cloud Access to Quantum Computing Systems

IBM first put a 5-qubit quantum computer on the cloud on May 4, 2016. Since then, the company has made dozens of machines available to the public and to paid users through its IBM Quantum Network. As it developed more powerful systems, IBM took down old machines and upgraded its hardware on the cloud. Tens of thousands of users have run billions of quantum circuits on IBM’s cloud quantum computers.

Microsoft and Amazon Web Services (AWS) also provide cloud access to quantum computers, though the hardware is not currently theirs. Microsoft Azure Quantum has many excellent resources for learning and using quantum computing. Developers can code using the Q#, Cirq, and Qiskit quantum software development kits (SDKs). Its cloud platform gives access to IonQ, Pasqal, qci, Quantinuum, and Rigetti systems.

Amazon Braket provides the Braket SDK for developers in addition to the Pennylane and Qiskit SDKs. Braket users can access IonQ, Oxford Quantum Circuits (OQC), QuEra, and Rigetti systems. As an aside, mathematician and quantum physicist Paul Dirac invented the “bra-ket” notation for representing quantum states, hence Amazon’s name for its quantum service.

IonQ is also available on Google Cloud. Individual quantum computing vendors such as Infleqtion may also make their systems privately available via the web or cloud through special arrangements.

Why Have Your Own Quantum Computer?

Important questions to ask any quantum computing vendor or cloud provider include:

  • How many systems do you have available on the cloud?
  • How often are your systems available, and what are their average uptimes?
  • What are the average and maximum times my quantum computing job will be waiting in a queue before it runs? Is it seconds, minutes, or hours?

When I developed quantum circuits for my books Dancing with Qubits and Dancing with Python, I often had to run them many times. Sometimes, it was because I had made a mistake, and other times, it was because I was developing or changing a circuit. To get around this, I frequently used a quantum simulator. While this approach is useful, I ultimately needed to test the circuit on actual quantum hardware. If the wait time was too long, it slowed my development process to an unacceptably slow pace.

If I had my own quantum computer, and a quantum simulator is not a quantum computer, I could run my circuits as often as I wanted without queue delay. Even if I had to share the system with colleagues in my lab or university, the dedicated system would typically have a much faster turnaround than anything on the cloud. In an academic setting, quantum computing systems are used for scientific research and education. Even though the systems are noisy and not error-corrected, they still have great value in extending our knowledge and teaching the next generation of quantum scientists, engineers, and technicians.

If I were a financial institution, dedicated fast access would mean that my quantum algorithm developers could develop circuits and test them faster than if they had to wait in a cloud queue. Many such institutions might quickly recoup the cost of having private systems if they can eventually demonstrate Practical Quantum Advantage.

Security is another crucial consideration. Only you can see your data and quantum computations if the quantum computing system is on your secure network with controlled access. If the system provider has access, ensure you know what they can see and when.

Finally, prestige is an undeniable factor. Having that shiny system in a very visible location allows others to see how important you are and how seriously you take quantum computing now and in the future. For a university, this could mean extra grants for your faculty and increased enrollments of STEM students. For a state or region, it could accelerate getting additional government funds for quantum technology development.

IBM previously installed systems in Germany, Japan, Korea, and the Cleveland Clinic, in addition to its managed systems in the US. IonQ and Anyon Systems have reported selling quantum computers for on-premises installations.

What Are the Downsides to Having Your Own Quantum Computing System?

You must decide whether you require an on-premises quantum computing system or can use one in the cloud. Factors to consider include:

  • The cost of the system, maintenance, and support staff
  • The space and power needs of the system
  • The extra physical security and cybersecurity requirements
  • The speed of fixes, repairs, and updates to the installation
  • The use of the system ending up small enough that a cloud solution would have been more economical

Key Takeaway: Installing a quantum computer locally is becoming more viable if you need secure, fast, dedicated access compared with the cloud. Cost, sustainability, and upgrade path are key points to consider.

Do you really need that fancy quantum computer on your site for everyone to see? The answer might be yes if your research or educational needs surpass what you can get from cloud-based systems. Think about how much use the system will get and at what cost. Measure cost in terms of money, security, energy, and support needs.

Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author is a former employee of IBM and Infleqtion and holds an equity position in each company. The author holds a small equity position in Google. The author does not hold any equity positions with any other company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.

Other Insights from The Futurum Group:

Quantum in Context: A Qubit Primer

Quantum in Context: Quantum Software Development Kit Qiskit Turns 1.0

Quantum in Context: Microsoft & Quantinuum Create Real Logical Qubits

Author Information

Dr. Bob Sutor has been a technical leader and executive in the IT industry for over 40 years.Bob’s industry role is to advance quantum and AI technologies by building strong business, partner, technical, and educational ecosystems. The singular goal is to evolve quantum and AI to help solve some of the critical computational problems facing society today. Bob is widely quoted in the press, delivers conference keynotes, and works with industry analysts and investors to accelerate understanding and adoption of quantum technologies.Bob is the Vice President and Practice Lead for Emerging Technologies at The Futurum Group. He helps clients understand sophisticated technologies in order to make the best use of them for success in their organizations and industries. He is also an Adjunct Professor in the Department of Computer Science and Engineering at the University at Buffalo, New York, USA.More than two decades of Bob’s career were spent in IBM Research in New York. During his time there, he worked on or led efforts in symbolic mathematical computation, optimization, AI, blockchain, and quantum computing. He was also an executive on the software side of the IBM business in areas including middleware, software on Linux, mobile, open source, and emerging industry standards. He was the Vice President of Corporate Development and, later, Chief Quantum Advocate, at Infleqtion, a quantum computing and quantum sensing company based in Boulder, Colorado USA.Bob is a theoretical mathematician by training, has a Ph.D. from Princeton University, and an undergraduate degree from Harvard College.

He’s the author of a book about quantum computing called Dancing with Qubits which was published in 2019, with the Second Edition scheduled for release in April, 2024. He is also the author of the 2021 book Dancing with Python, an introduction to Python coding for classical and quantum computing.Areas in which he’s worked: quantum computing, AI, blockchain, mathematics and mathematical software, Linux, open source, standards management, product management and marketing, computer algebra, and web standards.


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