Quantum in Context: Extreme Software Optimization with Superstaq

Quantum in Context: Extreme Software Optimization with Superstaq

The News: On March 21, I hosted a webinar panel with several Infleqtion quantum computing software team leaders to discuss the application optimizations critical for reaching Practical Quantum Advantage. They highlighted recent wins, customers, and some software optimizations they deploy in their Superstaq product. See the replay on YouTube.

The Quantum Software Experts:

  • Dr. Pranav Gokhale, Vice President of Quantum Software, Infleqtion
  • Victory Omole, Senior Quantum Software Engineer, Infleqtion
  • Stephanie Lee, Quantum Software Manager, Infleqtion

Quantum in Context: Extreme Software Optimization with Superstaq

Analyst Take: Although quantum computing hardware gets much of the attention in the media and at conferences, it will ultimately be the software that delivers the applications and solutions currently intractable using classical approaches. Infleqtion’s Superstaq tool optimizes the quantum code written by developers to run much faster on different vendor and research lab hardware platforms. Without this kind of optimization provided by Infleqtion or its competitors, quantum computing cannot fulfill its promised breakthroughs in areas such as AI, chemistry, and financial services.

The Quantum Software Stack

Developers build software in layers, from low-level code directly controlling the hardware to high-level applications that implement solutions, solve problems, and interact with users. It’s not hard to find many good representations of the layered quantum software stack on the web. Inflection’s simplified stack shows five levels:

Quantum in Context: Extreme Software Optimization with Superstaq
The Infleqtion Superstaq Quantum Computing Stack. (Image Source: Infleqtion)

A quantum software developer implements code, often in Python and frequently using a software development kit (SDK) such as Qiskit or Cirq, at the Application and Algorithm levels. This code then goes to the compiler for translation into the instructions passed to the Control level and, finally, the Hardware level.

Both quantum and classical compilers perform some optimizations themselves or provide hooks for third-party extensions. For example, the quantum Hadamard gate is its own inverse, meaning that if you see two such consecutive instructions, you can usually remove them both because the second one undoes the effect of the first.

A quantum software developer plugs Superstaq into the sequence that compiles and then executes the code.

Quantum in Context: Extreme Software Optimization with Superstaq
Superstaq does require some knowledge of quantum computing but no hardware expertise. (Image Source: Infleqtion)

Superstaq understands quantum hardware, knows how it is controlled at the lowest level, and can greatly improve the developer’s code to run as efficiently as possible.

Example Code Optimizations with Superstaq

The Infleqtion team shared several examples of how their tool performs better than out-of-the-box quantum SDKs. Admittedly, these are pretty technical, but that’s because they are optimizations at the lowest level:

  • A 15-times advantage using dynamic decoupling on IBM Quantum superconducting hardware running the Greenberger–Horne–Zeilinger (GHZ) entanglement circuit on 15 qubits
  • A 17% reduction in pulse amplitude, resulting in fewer errors on the Sandia QSCOUT trapped-ion system
  • Significantly better methods to characterize, verify, and validate quantum computer computations compared to quantum tomography

Regarding the last point, many people discuss the exponential advantages that quantum computing might offer. However, if you choose the wrong method for a task, the result can get exponentially worse as you use more qubits. Superstaq’s characterization approach avoids this pitfall.

Infleqtion uses Superstaq with its own Sqorpius neutral atom quantum computer. The company noted that it can work with any quantum hardware system provider and that it carefully firewalls work with one partner or customer from another.

Next on the Quantum Horizon: Error Correction

Today’s physical qubits and quantum operations acquire too many errors to implement large enough use cases that we care about. No one needs a quantum computer to solve small problems. We need many more qubits with low enough error rates to implement logical qubits and operations that can detect and fix mistakes or faults during processing. We cannot fix very bad qubits. They must be good enough and over a numeric quality threshold to allow us to use error correction techniques. Superstaq can optimize user code operating close to but below this threshold to exceed the level needed for error correction.

Superstaq Customers and Partners

During the webinar, Infleqtion announced that it had won a $1.2 million US Department of Energy Small Business Innovation Research (SBIR) award to accelerate the development of Superstaq.

The team also listed US government partners

  • Argonne National Lab, including Q-NEXT,
  • Lawrence Berkeley National Lab, and
  • Sandia National Lab

and commercial collaborations with

  • AWS,
  • IBM Quantum, and
  • JP Morgan Chase.

Key Takeaway

Superstaq should be strongly considered by any quantum hardware system provider or user to generate code that runs optimally.

Practical Quantum Advantage will occur when quantum and classical computing systems work together to solve problems in a significantly better manner than classical systems alone. Quantum software has an immense role in helping us get to this point as soon as possible. With Superstaq, Infleqtion is a strong competitor among companies seeking to gain every last bit of performance from our evolving quantum computing hardware.

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 equity positions in each company.

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: Quantum Software Development Kit Qiskit Turns 1.0

Quantum in Context: Pasqal Is the Latest to Publish a Roadmap

Quantum in Context: Rigetti Q4 2023 Earnings and Other Numbers


Author Information

Dr. Bob Sutor

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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