Menu

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 is an expert in quantum technologies with 40+ years of experience. He is the accomplished author of the quantum computing book Dancing with Qubits, Second Edition. Bob is dedicated to evolving quantum to help solve society's critical computational problems.

Related Insights
Synopsys and GlobalFoundries Reshape Physical AI Through Processor IP Unbundling
January 16, 2026

Synopsys and GlobalFoundries Reshape Physical AI Through Processor IP Unbundling

Brendan Burke, Research Director at Futurum, evaluates GlobalFoundries’ acquisition of Synopsys’ Processor IP to lead in specialized silicon for Physical AI. Synopsys pivots to a neutral ecosystem strategy, prioritizing foundation...
Qualcomm Unveils Future of Intelligence at CES 2026, Pushes the Boundaries of On-Device AI
January 16, 2026

Qualcomm Unveils Future of Intelligence at CES 2026, Pushes the Boundaries of On-Device AI

Olivier Blanchard, Research Director at Futurum, shares his/her insights on Qualcomm’s CES 2026 announcements, which highlight both the breadth of Qualcomm’s Snapdragon and Dragonwing portfolios, and the velocity with which...
TSMC Q4 FY 2025 Results and FY 2026 Outlook Signal AI-Led Growth
January 16, 2026

TSMC Q4 FY 2025 Results and FY 2026 Outlook Signal AI-Led Growth

Futurum Research analyzes TSMC’s Q4 FY 2025 update, highlighting AI-led demand, advanced-node mix, tight capacity, and a higher FY 2026 capex plan to scale N2 and advanced packaging while sustaining...
SiFive and NVIDIA Rewriting the Rules of AI Data Center Design
January 15, 2026

SiFive and NVIDIA: Rewriting the Rules of AI Data Center Design

Brendan Burke, Research Director at Futurum, analyzes the groundbreaking integration of NVIDIA NVLink Fusion into SiFive’s RISC-V IP, a move that signals the end of the proprietary CPU’s stranglehold on...
Will QAI Moon Beat Hyperscalers in GPU Latency
January 15, 2026

Will QAI Moon Beat Hyperscalers in GPU Latency?

The need for edge AI inference is being met by QAI Moon, a new joint venture formed by Moonshot Energy, QumulusAI, and IXP.us to pair carrier-neutral internet exchange points with...
SiMa.ai and Synopsys Unveil Automotive AI SoC Blueprint. Is Pre-Silicon the New Baseline
January 15, 2026

SiMa.ai and Synopsys Unveil Automotive AI SoC Blueprint. Is Pre-Silicon the New Baseline?

Olivier Blanchard, Research Director at Futurum, shares his insights on the joint SiMa.ai–Synopsys blueprint, which targets earlier architecture exploration and software development for ADAS and IVI SoCs....

Book a Demo

Newsletter Sign-up Form

Get important insights straight to your inbox, receive first looks at eBooks, exclusive event invitations, custom content, and more. We promise not to spam you or sell your name to anyone. You can always unsubscribe at any time.

All fields are required






Thank you, we received your request, a member of our team will be in contact with you.