Accuracy Is the Foundation of Meaningful Quantum Computing
Recently, industry peers—including Quantinuum’s Startup Program Partners Qedma and BlueQubit, as well as our partner RIKEN—published a paper exploring quantum magnetism that “extends beyond the reach of the state-of-the-art classical methods considered;” evidence of a quantum advantage result. Interestingly, the team validated their results on Quantinuum machines (both Helios and System Model H2).
In 2025, we published a paper (now in Nature), exploring a similar system - also at scales that frustrate classical computation. This got us thinking: with more successes like this in the literature, what does this mean for the ecosystem at large? What are the key lessons to learn from these early demonstrations? And, perhaps most importantly, what’s next?
We Are Entering the Era of ‘What’, Not ‘When’
The answer to the first question, ‘what does this mean for the ecosystem at large’, is a delight to answer. After decades of promises, we are finally in the era where quantum computing is matched with, if not outright exceeding, classical HPC and supercomputing.
Examples of (complexity-theory proven) quantum advantage are already common, usually in the form of Random Circuit Sampling. This was extended to generating certified randomness, which was one of the earliest commercial applications of quantum computing.
Since then, we have seen a number of results from different groups that push the limits of classical computing while exploring ‘real’ problems; these range from papers exploring quantum magnetism (as mentioned above), to papers exploring things like superconductivity or peaked circuits.
Whether or not these are definitively ‘quantum advantage’ results is almost beside the point. They mark a distinct place on the path towards broad scale quantum utility, when quantum computers will be widely useful for researchers and industry alike. More importantly, these papers all speak to a certain level of ‘technological readiness’, showing that quantum computers are now proven to work on problems that are relevant (to some people, at least), at scales that aren’t easily reproduced elsewhere.
Accuracy is a Baseline Requirement
One of the key lessons we can learn from all these demonstrations is that hardware accuracy is paramount. Without accuracy, quantum computers are very expensive noise generators, unable to move the needle beyond HPC. Happily, we are finding that current generation machines are still capable of quite a lot, thanks to baseline physical accuracy, optionally coupled with clever error mitigation on top.
In general, we are very pleased to see how error mitigation can significantly reduce the impact of hardware errors and improve the quality of computed results by applying sophisticated post-processing techniques. However, error mitigation is not free. As hardware noise increases, mitigation becomes increasingly computationally expensive, and the techniques themselves can skew the results. If the underlying hardware is insufficiently accurate, it becomes more difficult to distinguish genuine physical phenomena from artifacts introduced via mitigation.
This is precisely where hardware quality matters. The validation on Quantinuum systems provided an important independent confirmation that the mitigated results from another vendor reflected real physical behavior rather than bias introduced through the mitigation process. Because Quantinuum's hardware operates with substantially lower native error rates, it served as a high-confidence reference point for validating scientific results. Importantly, this validation was about confirming the underlying physics, not validating a claim of quantum advantage.
Hardware Accuracy Improves Computational Efficiency
All the above reflects our systems' strong native performance: when hardware begins with exceptionally high fidelity, there is simply less error to overcome. However, error mitigation remains an interesting and valuable approach: high-quality hardware establishes the baseline, and software extends what is possible.
However, native accuracy affects more than scientific confidence—it also influences computational efficiency. As program complexity and size increases, hardware error rates increase, and successful error mitigation generally requires more sampling, more processing, and more computational resources. The lower the physical fidelity, the greater the overhead required before arriving at trustworthy results.
By starting with significantly lower native error rates, Quantinuum systems reduce the amount of mitigation needed to achieve comparable scientific outcomes. This creates a practical advantage in computational cost while helping to preserve confidence in the resulting data.
Accuracy is the Foundation for Fault Tolerance
Finally, we can answer the question of what comes next. This may seem obvious, but it’s multifaceted. What’s next is large-scale fault tolerant quantum computing. But the real question is, what does that look like?
A truly large-scale fault tolerant quantum computer will operate with error correction embedded into the workflow, working on the ‘logical’ level. That means that programmers will write their code to operate on logical qubits, with all the mechanisms of error correction hidden under the hood. The result will be error rates low enough to run some truly behemoth workflows.
We are well along the path to realizing this at scale: we have demonstrated all the necessary primitives, have world-leading logical error rates, and have a platform flexible enough to use new codes as they are invented; a crucial advantage in a quickly-evolving landscape. All of this is enabled by our high native accuracy; the accomplishments listed would be impossible without hardware that wasn’t ultra-low error to begin with.
However, even with the full force of error correction, error mitigation may still play an important role in the post fault-tolerance era. While error correction will be applied broadly to all workflows, there will still be some special cases where error mitigation may stretch the hardware further, always ensuring we stay on our front foot as computational power grows.
Progress Is the Real Milestone
Scientific breakthroughs matter because they move the field forward. But lasting enterprise value will come from quantum computers that consistently deliver results organizations can trust.
With Helios—the world's most accurate commercial quantum computer[1]—and a growing ecosystem of partners building complementary technologies, Quantinuum is creating the accurate, scalable foundation needed to transform scientific achievements into practical quantum computing.
[1] Based on two qubit gate fidelity, as of December 31, 2025.
About Quantinuum
Quantinuum, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. Quantinuum’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, Quantinuum leads the quantum computing revolution across continents.
Progressing your organization along the five levels of quantum maturity
Quantum computing has moved from a bet on the future to a race already underway. Early adopters are locking in strategic partnerships, building proprietary IP, and positioning themselves years ahead of competitors who are still watching from the sidelines. For executives, the question isn't whether to engage with quantum computing. It's how far along that journey your organization actually is, and what it takes to move forward.
That's a harder question to answer than it sounds. Quantum maturity isn't a single milestone you either hit or miss. It's a progression, built across talent, technology access, workflow integration, partnerships, and value realization, and most organizations aren't entirely sure where they currently stand and what to do next.
Our new paper, A Roadmap for Quantum Maturity, is built to answer exactly that.
A Framework for Where You Stand, and Where to Go Next
Drawing on extensive client experience, the paper lays out five distinct levels of quantum maturity, from early awareness through full transformation, along with the leadership actions that move an organization from one level to the next.
- Awareness — early conversations, but no clear ownership or use cases yet
- Exploration — exploring partnerships and prioritizing use cases with limited budget
- Experimentation — quantum roadmap established and guiding dedicated teams, funding, and partners to execute pilot use case projects
- Integration — quantum computing applications are being embedded into business unit workflows, and the quantum roadmap is integrated with broader digital technology strategy, including AI, HPC, and data
- Transformation — quantum capabilities are embedded in core products and decision-making, with differentiated, proprietary advantage
Most industry leaders today sit at the exploration or experimentation stages, with clear ambitions to reach transformation within the next several years. The paper breaks down what separates organizations that progress from those that stall out at proof-of-concept.
The Advantage Is Built, Not Bought
One of the paper's central takeaways is one many executives underestimate: investing in quantum technology alone isn't enough. Organizations that advance fastest pair that investment with a deliberate strategy, building quantum literacy across leadership and technical teams, honestly assessing capability gaps, focusing on a small number of high-impact use cases tied to real business metrics, and defining a clear roadmap that connects research to business advantage.
How Quantinuum Can Help
Achieving quantum maturity is a journey, not a single step, and most organizations don't need to make that journey alone. Quantinuum's consulting services are built to support every stage of it, from advisory and use-case identification, to capability building, technology access, and the co-development of scalable quantum solutions.
Whether your organization is just starting to build awareness or already scaling toward transformation, our team can help you identify exactly where you stand today, and what it takes to move to the next level.
- SoftBank Corp. and Quantinuum articulated a roadmap connecting quantum algorithms, hardware evolution, and commercial applications, helping organizations understand when quantum computing can address real-world challenges.
- The analysis demonstrates that quantum value will emerge in stages, with early opportunities in data analysis and longer-term breakthroughs in scientific computing as fault-tolerant systems mature.
- The work provides a practical planning framework for enterprises preparing to integrate quantum computing alongside AI and classical high-performance computing infrastructure in quantum-AI data centers.
Quantum computing is increasingly moving from exploratory discussion to structured enterprise planning. As organizations begin to assess where and when quantum technologies may deliver real business impact, a new class of work is emerging: integrated roadmaps that connect algorithmic feasibility, hardware development, and commercial opportunity.
A recent white paper from SoftBank Corp. and Quantinuum represents one of the most comprehensive examples of this approach to date. Rather than treating quantum computing as a distant, abstract capability, the study constructs a detailed, quantitative framework for understanding how real-world use cases evolve as hardware matures—and what this means for enterprise strategy.
A Comprehensive Roadmap
The SoftBank–Quantinuum white paper is broad in scope. It attempts to answer a fundamental question:
Which real-world problems can benefit from quantum computation, at what scale, with what accuracy requirements, and under what hardware conditions?
To address this, the study adopts a structured methodology that connects:
- Algorithmic resource estimates (logical qubits, circuit depth, gate counts)
- Explicit error correction assumptions and overhead models
- Hardware roadmaps across multiple generations
- Timelines for when specific classes of problems may become feasible
Two representative domains anchor the analysis:
- Quantum chemistry, particularly excited-state dynamics and photochemical processes
- Topological data analysis (TDA), including graph-based structure and anomaly detection
These domains were selected because they combine industrial relevance with computational structures that scale poorly on classical systems but map naturally onto quantum approaches.
Quantum chemistry is closely tied to materials science, energy systems, and the development of sustainable technologies. TDA, by contrast, offers tools for understanding complex data structures in networks, finance, and large-scale systems—where identifying structure and anomalies is increasingly critical.
Together, they illustrate how quantum computing may create value across both deep scientific domains and high-impact data applications.
An important caveat is that the resulting roadmap assumes a widely-studied but inefficient error correcting code. As more error correcting codes come online, the resources required to run algorithms will shrink. That means that the timelines detailed in this work can be thought of as “worst case” scenarios, which adds to the value by setting out a clear limit.
A distinguishing feature of the work is its emphasis on implementation over abstraction. Rather than relying solely on theoretical models, the study explicitly constructs quantum circuits and executes them on Quantinuum’s Helios and H2 system.
Parallel Paths to Value
A notable insight from the study is that quantum value creation will not follow a single linear path.
Instead, two complementary regimes are expected to emerge:
- In quantum chemistry, the focus is on fault-tolerant, logical-qubit-based computation, where error correction is essential for scaling toward meaningful scientific and industrial outcomes.
- In TDA, value can emerge earlier, where partial quantum advantage may already support useful computational tasks without full error correction.
This dual-track structure is important: it shows that quantum computing is not a single “threshold technology,” but a spectrum of capabilities that unlock value at different stages of maturity.
The Vision for Quantum Industrialization
The framework ultimately supports a broader strategic vision: the evolution of Quantum AI Data Centers—hybrid infrastructures where quantum processors operate alongside AI and classical HPC systems.
For enterprises, the implication is clear: quantum computing readiness is no longer about speculation. It is about structured preparation, disciplined modeling, and early engagement with the full stack of capabilities that will define the next generation of computational infrastructure.
Every year, The IEEE International Conference on Quantum Computing and Engineering – or IEEE Quantum Week – brings together engineers, scientists, researchers, students, and others to learn about advancements in quantum computing. This year’s conference, from September 13th - 18th in Toronto, Canada, will focus on translating research into real-world impact through the convergence of generative AI, distributed quantum systems, and quantum software engineering.
Throughout IEEE Quantum Week, our quantum experts will be on-site to share insights on upgrades to our hardware, enhancements to our software stack, our path to error correction, and more.
Meet our team at Booth #501 and join the below sessions to discover how Quantinuum is forging the path to fault-tolerant quantum computing with our integrated full-stack.
Keynote with Quantinuum's CEO, Dr. Rajeeb Hazra
September 14th
5:00 – 6:30pm | 800 Hall G
Quantum computing has passed the point where error correction is theoretical. What comes next depends on systems that hold logical performance steady and do real work at scale. On September 14th, join Quantinuum’s CEO Dr. Rajeeb Hazra for his keynote session on “Logically Speaking: The Next Era of Error Correction” where he will explore what the next era of quantum computing requires: shared definitions of logical performance, and benchmarks built on real workloads.
Speaking Sessions
September 13th
11:00 – 11:12am | Location: 601A/B
Workshop: QGenAI: Synergies between Quantum Computing and Generative Artificial Intelligence
Finding Compatible Datasets for Quantum Generative Modeling
Presenting Author: Chen-Yu Liu
September 14th
1:00 – 1:20pm | Location: 701B
Workshop: Q3-Control: Integrated Systems for Quantum Computing, Sensing, and Networking
Cryo-ASICs for Scalable Control
Speaker: Dr. Patty Lee
September 15th
2:30 – 3:30pm | Exhibit Hall (informal event)
Workshop: Q3-Control: Integrated Systems for Quantum Computing, Sensing, and Networking
The Quantum Spectrum
Speaker: Dr. Patty Lee
3:00 – 4:30pm | Location: 801A
Where Quantum-HPC Integration Actually Stands in 2026
Panelist: Neal Erickson
3:00 – 4:30pm | Location: 718A
From Research to Commercialization: Defining the Quantum Workforce for the Next Five Years
Panelist: Kortny Rolston-Duce
September 16th
10:00 – 11:30am | Location: 801B
Who Will Turn Quantum Computing into Value? Specialists, Domain Experts, and the Workforce Gap
Panelist: Enrico Rinaldi
September 17th
10:00 – 11:30am | Location: 701B
International Workshop on Quantum Computing for Power Systems: From Optimization Algorithms to Grid-Scale Applications | Session 1
Organizer: Kortny Rolston-Duce
10:00 – 11:30am | Location: 714A
openQSE: Co-Designing the Quantum-HPC Software Stack from Applications to Control Systems | Session 1
Speaker: Neal Erickson
10:00 – 11:30am
The Impact of Qubit Connectivity on Quantum Advantage in Noisy IQP Circuits
Presenting Author: Leonardo Placidi
10:15 – 11:00 am | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Automated near-term quantum algorithm discovery
Speaker: Konstantinos Meichanetzidis
11:00 – 11:15am | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Fast Stabilizer State Preparation via AI-Optimized Graph Decimation
Presenting Author: Jasmine Brewer
1:00 – 1:15pm | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Reinforcement Learning for Adaptive Composition of Quantum Circuit Optimisation Passes
Speaker: Gabriel Matos
1:00 – 1:20am | 718B
Quantum Software 2.6: current challenges and headways in quantum software | Session 1
Quantum compilation and hybrid compilation
Speaker: Ross Duncan
1:00 – 2:30pm | Location: 714A
openQSE: Co-Designing the Quantum-HPC Software Stack from Applications to Control Systems | Session 2
Speaker: Phillipp Seitz
1:45 – 2:00pm | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Graph-Theoretic Quantum Circuit Optimization with the ZX-Calculus and Gumbel AlphaZero
Speaker: Alexander Koziell-Pipe
2:00 – 2:15pm | Location: 601A/B
Workshop: AI for Circuit Synthesis, Optimization, and Discovery
Reusable Equivariant Neural Compilers for Matrix-Group Quantum Circuit Synthesis
Speaker: Richie Yeung
3:30 - 4:00pm | Location: 715B
Workshop: 4th Workshop on Quantum Computing for Natural Sciences: Technology and Applications
Quantum Algorithms
Speaker: Setso Metodi
September 18th
10:00 – 11:30am | Location: 801B
Scalable QPU architectures
Panelist: Setso Metodi