Guppy: Programming the Next Generation of Quantum Computers
Today, the ԹϺ software team is excited to announce Guppy, a new quantum programming language for the next generation of quantum computing—designed to work with upcoming hardware like Helios, our most powerful system yet. You can download Guppy today and start experimenting with it using our custom-built Selene emulator. Both Guppy and Selene are open source and are capable of handling everything from traditional circuits to dynamic, measurement-dependent programs such as quantum error correction protocols.
What is Guppy?
Guppy is a quantum-first programming language designed from the ground up to meet the needs of state-of-the-art quantum computers. Embedded in Python, it uses syntax that closely resembles Python, making it instantly familiar to developers. Guppy also provides powerful abstractions and compile-time safety that go far beyond traditional circuit builders like pytket or Qiskit.
Key Features
- Pythonic & Embedded
Guppy integrates seamlessly with existing Python codebases and libraries, offering a concise and expressive alternative to imperative builder patterns. Its source language approach supports higher levels of abstraction—unlocking algorithmic innovations that may not be discovered otherwise.
- Safety by Design
Quantum computers are scarce, and access is limited—often involving long queues to run programs. Debugging runtime errors on real hardware isn't just time-consuming; it's costly. Guppy is statically compiled and strongly typed, helping catch bugs early in development. It enforces principles like no-cloning, prevents qubit memory leaks, and offers clear, actionable error messages.
- Beyond Circuits: The Quantum Kernel
Guppy programs are more than circuit descriptions—they are quantum kernels, supporting rich control flow based on measurement outcomes, function calls, and complex data types. This is essential for implementing adaptive quantum algorithms.
Example Program
Guppy is designed to be readable and expressive, while enabling precise, low-level quantum programming.
This example implements the gate V3 = (I + 2iZ)/√5 using a probabilistic repeat-until-success scheme[1].
If both X-basis measurements on the top two qubits return 0, the V3 gate is successfully applied to the input state |ψ⟩; otherwise, the identity is applied. Since this succeeds with a probability of 5/8, we can repeat the procedure until success.
Let’s implement this in Guppy.
First, we’ll define a helper function to prepare a scratch qubit in the |+⟩ state:
@guppy
def plus_q() -> qubit:
"""Allocate and prepare a qubit in the |+> state"""
q = qubit()
h(q)
return qNext, a function for performing X-basis measurement:
@guppy
def x_measure(q: qubit @ owned) -> bool:
"""Measure the qubit in the X basis and return the result."""
h(q)
return measure(q)The @owned annotation tells the Guppy compiler that we’re taking ownership of the qubit, not just borrowing it—a concept familiar to Rust programmers. This is required because measurement deallocates the qubit, and the compiler uses this information to track lifetimes and prevent memory leaks.
The @guppy decorator marks functions as Guppy source code. Oustide these functions, we can use regular Python - like setting a maximum attempt limit:
MAX_ATTEMPTS = 1000With these pieces in place, we can now implement the full protocol:
@guppy
def v3_rus(q: qubit) -> int:
attempt = 0
while attempt < comptime(MAX_ATTEMPTS):
attempt += 1
a, b = plus_q(), plus_q()
toffoli(a, b, q)
s(q)
toffoli(a, b, q)
a_x, b_x = x_measure(a), x_measure(b)
if not (a_x or b_x):
break
z(q)
return attemptWhat’s happening here?
Learn More
There's a lot more to Guppy, including:
- Polymorphism and generics
- Linear typing and ownership tracking
- Statically sized arrays and custom data types
- Compile-time metaprogramming via Python
Why We Built Guppy for Helios
Helios represents a major leap forward for ԹϺ hardware—with more qubits, lower error rates, and advanced runtime features that require a new class of programming tools. Guppy provides the expressive power needed to fully harness Helios's capabilities—features that traditional circuit-building tools simply can't support.
See our latest roadmap update for more on Helios and what's coming.
Simulate Today with Selene
Quantum hardware access is limited—but development shouldn't be. Selene is our new open-source emulator, designed to run compiled Guppy programs accurately—including support for noise modeling. Unlike generic simulators, Selene models advanced runtime behavior unique to Helios, such as measurement-dependent control flow and hybrid quantum-classical logic.
Selene supports multiple simulation backends:
- Statevector simulation (via Quest)
- Stabilizer simulation (via Stim)
- Classical replay: replay simple programs by providing measurement outcomes
- More plugins coming soon.
Whether you're prototyping new algorithms or testing low-level error correction, Selene offers a realistic, flexible environment to build and iterate.
Get Started
Guppy is available now on GitHub and PyPi under the Apache 2 license. Try it out with Selene, read the docs, and start building for the future of quantum computing today.
👉
1. Paetznick, A., & Svore, K. M. (2014). Repeat-Until-Success: Non-deterministic decomposition of single-qubit unitaries. arXiv preprint ↩
About ԹϺ
ԹϺ, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. ԹϺ’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, ԹϺ leads the quantum computing revolution across continents.
- ԹϺ continues its progress toward fault-tolerant quantum computing, with a series of peer-reviewed breakthroughs in fault-tolerant operations.
- Our progress is not only scientific; it is commercial. By improving logical-qubit reliability and encoding efficiency, ԹϺ is reducing the resource overhead required to scale its quantum computers toward commercially useful workloads.
- These results were achieved on commercial ԹϺ hardware, reinforcing that our architecture is not just setting new standards, but building a practical foundation for customers, partners, and researchers preparing for the fault-tolerant era.
Fault-tolerant quantum computing is the threshold the industry must cross before quantum computers can solve the hardest, highest-value problems with confidence. To be commercially useful at scale, the question is not simply who can build more qubits. It is who can build reliable, efficient, scalable systems that reduce technical risk and accelerate the path to commercial usefulness.
ԹϺ is progressing on that path.
Last year, in partnership with Microsoft, we published a breakthrough in logical computing, demonstrating logical qubits that outperformed their physical counterparts by a factor of 800. We are proud to announce that this work is now being published in Nature, one of the most highly regarded scientific journals in the world.
This work highlights our leading fidelities, as shown in Table 1:
Since then, we’ve accelerated our efforts to reach large-scale fault tolerance and advanced what we believe to be the core building blocks of fault-tolerant quantum computing, from logical-qubit teleportation and multiple error-correction breakthroughs to one of the first meaningful computations using logical qubits. Importantly, these results were achieved on commercial ԹϺ hardware, demonstrating not just scientific progress, but a practical and efficient path toward scalable, customer-ready fault tolerance.
A Recap of Our Recent Technical Progress
Since the work with Microsoft, we achieved a milestone years ahead of schedule, demonstrating high-fidelity teleportation of a logical qubit, which was published in one of the world’s most prestigious journals. Later, we beat our own record in this crucial fault tolerance milestone, thanks to continued improvements to our System Model H2’s fidelity.
Then, a series of results demonstrating more error-correcting milestones (and codes):
- Better than physical results in a ,
- (which significantly reduces resource requirements) in 4 dimensions
- with a concatenated code
- Observed with concatenated codes
- High fidelity magic states and a fully fault tolerant universal gate set in two
Recently, we topped ourselves yet again by performing one of the first meaningful computations with logical qubits – exploring key questions in materials and magnetism, using . This result also includes a leading “encoding rate” squeezing 48 logical qubits out of just 98 physical qubits, emphasizing how our architecture helps to support large scale fault tolerance without enormous resource costs.
It is worth noting that all these results were achieved on our commercial hardware, not on one-off laboratory test-stands – reflecting the performance that we are able to deliver to our customers.
We also did crucial theoretical work, exploring that can reduce resource requirements, time to solution, and shorten the timeline to large scale fault tolerance.
Commercial Implications and the Road Ahead
We believe the commercial implication is clear: ԹϺ is reducing the uncertainty around the path to fault-tolerant quantum computing. Our architecture, hardware fidelity, full-stack control, and error-correction progress are converging into a practical roadmap for systems that can support valuable scientific and commercial workloads.
For those evaluating when quantum computing will become strategically relevant, we believe the signal is also increasingly clear: the fault-tolerant era is no longer a distant concept. It is becoming an engineering reality, and ԹϺ is leading the way.
- University of Southern Denmark (SDU) to use ԹϺ Helios, supported by the Danish e-Infrastructure Consortium (DeiC)
- Access to Helios enables SDU to test and refine fault-tolerant algorithms and error-correction codes under realistic hardware conditions
- The collaboration supports at a scale of 48 logical qubits, positioning Denmark at the forefront of scalable, practical quantum computing
- Researchers exploring the scientific foundations for future development of applications in fields including pharmaceuticals, finance, and defense
Progress in quantum computing is measured by hardware advances plus the algorithms and quantum error-correction codes that turn quantum systems into useful computational tools.
Thanks to recent hardware advances, researchers are increasingly sharpening their tools to probe the performance of quantum algorithms and understand how they behave in realistic conditions – where stability, system architecture and algorithm design all shape performance.
A new Denmark-based collaboration between the University of Southern Denmark (SDU), ԹϺ, and the Danish e-Infrastructure Consortium (DeiC) will utilize ԹϺ Helios. Researchers at the SDU’s Centre for Quantum Mathematics, led by Jørgen Ellegaard Andersen, will use Helios to pursue research into topological quantum computing.
Their work could help explain how and why successful quantum algorithms perform as they do, informing the development of high-performance algorithms suited to emerging quantum systems. They’re exploring the scientific foundations that support future quantum applications across areas including pharmaceuticals, finance, and defense.
“We are thrilled to gain access to ԹϺ’s high-fidelity Helios system. This collaboration gives us a unique opportunity to test the limits of our algorithms and evaluate system performance, while advancing fundamental research and laying the foundation for future applications.”
— Professor Jørgen Ellegaard Andersen, Director of the Centre for Quantum Mathematics at University of Southern Denmark
Why topological methods matter
Topological quantum computing is an area of research that connects quantum computation with deep mathematical structures. It includes the study of error correcting codes known as surface codes that encode quantum information in the global properties of systems of logical qubits.
The research team will explore how these codes behave, and how they may support the development of fault-tolerant quantum algorithms in practical implementations under realistic conditions.
This distinction between theory and practical implementation matters. In theory, topological approaches offer a rich framework for designing algorithms and error-correcting codes. In practice, researchers need to understand how those ideas perform when implemented on real systems, where questions of noise, stability, overhead, and scaling become central. The collaboration will allow the SDU team to investigate these questions directly.
New ways to benchmark quantum processors
Beyond individual algorithms and codes, the research will also develop tools for benchmarking quantum processors. The goal is to develop new ways to characterize fidelity and stability in regimes that can be difficult to access.
The team will also explore hybrid quantum–classical approaches, including machine-learning techniques assisted by quantum hardware, to study the mathematical structures at the heart of topological quantum computing. This work reflects a broader field of research in which quantum and classical methods are used together, each contributing to parts of a computational problem.
Strengthening Denmark’s quantum ecosystem
The collaboration reflects the growing role of national quantum infrastructure in supporting research and talent development. Denmark has a long tradition of scientific innovation, and this collaboration is intended to support the country’s continued development in quantum technology.
The initiative is supported by DeiC, which played a central role in securing funding and enabling access to ԹϺ’s systems. DeiC has been assigned a particular role in developing and coordinating quantum infrastructure initiatives for the benefit of universities and industry, operating without its own commercial, sectoral, or geographical interests. This includes securing dedicated access to quantum computers, producing advisory services and supporting the development of new talent in the Danish quantum sector.
“DeiC’s special effort to secure funding and access for this research initiative is rooted in our organization’s role in relation to the Danish Government’s strategy for quantum technology.”
— Henrik Navntoft Sønderskov, Head of Quantum at Danish e-Infrastructure Consortium
This collaboration promises to accelerate the development of practical algorithms. It is grounded in fundamental science – but its focus is practical: discovering and testing mathematical approaches to topological quantum computing that can be implemented, evaluated, and improved on real quantum hardware.
That work requires both theoretical insight and access to a system such as Helios capable of supporting meaningful scientific work.
This month, ԹϺ welcomed its global user community to the first-ever Q-Net Connect, an annual forum designed to spark collaboration, share insights, and accelerate innovation across our full-stack quantum computing platforms. Over two days, users came together not only to learn from one another, but to build the relationships and momentum that we believe will help define the next chapter of quantum computing.
Q-Net Connect 2026 drew over 170 attendees from around the world to Denver, Colorado, including representatives from commercial enterprises and startups, academia and research institutions, and the public sector and non-profits - all users of ԹϺ systems.
The program was packed with inspiring keynotes, technical tracks, and customer presentations. Attendees heard from leaders at ԹϺ, as well as our partners at NVIDIA, JPMorganChase and BlueQubit; professors from the University of New Mexico, the University of Nottingham and Harvard University; national labs, including NIST, Oak Ridge National Laboratory, Sandia National Laboratories and Los Alamos National Laboratory; and other distinguished guests from across the global quantum ecosystem.
Congratulations to Q-Net Connect 2026 Award Recipients!
The mission of the ԹϺ Q-Net user community is to create a space for shared learning, collaboration and connection for those who adopt ԹϺ’s hardware, software and middleware platform. At this year’s Q-Net Connect, we awarded four organizations who made notable efforts to champion this effort.
- JPMorganChase received the ‘Guppy Adopter Award’ for their exemplary adoption of our quantum programming language, Guppy, in their research workflows.
- Phasecraft, a UK and US-based quantum algorithms startup, received the ‘Rising Star’ award for demonstrating exceptional early impact and advancing science using ԹϺ hardware, which they published in a December 2025 .
- Qedma, a quantum software startup, received the ‘Startup Partner Engagement’ award for their sustained engagement with ԹϺ platforms dating back to our first commercially deployed quantum computer, H1.
- Anna Dalmasso from the University of Nottingham received our ‘New Student Award’ for her impressive debut project on ԹϺ hardware and for delivering outstanding results as a new Q-Net student user.
Congratulations, again, and thank you to everyone who contributed to the success of the first Q-Net Connect!
Become a Q-Net Member
Q-Net offers year‑round support through user access, developer tools, documentation, trainings, webinars, and events. Members enjoy many exclusive benefits, including being the first to hear about exclusive content, publications and promotional offers.
By joining the community, you will be invited to exclusive gatherings to hear about the latest breakthroughs and connect with industry experts driving quantum innovation. Members also get access to Q‑Net Connect recordings and stay connected for future community updates.