Coming Over the Horizon
Quantum Communication Enters the Mainstream
Communication is the connective tissue of society, weaving individuals into groups and communities and mediating the progress and development of culture. The technology of communications evolves continuously, occasionally undergoing paradigm shifts such as those brought about by the Gutenberg press and broadcast television.
From historical examples such as the proliferation of fast merchant trading ships, to the modern telecommunications networks spread across the world via a web of cables buried under the sea floor and satellites thousands of kilometres high, the need for better communication infrastructure has driven some of our most ambitious technologies to date.
Today, emerging quantum technologies are poised to revolutionise the field of communication once again. They promise new and incredibly valuable opportunities for dependable and secure communications between people, communities, companies, and governments everywhere. Our ability to understand and control quantum systems has opened a new world of exciting possibilities. Soon we might build long-distance quantum communication links and networks, eventually leading to what is known as the quantum internet.
While some embryonic quantum communication systems are already in place, realisation of their full potential will require significant technological advances. With engineering teams around the world working at pace to deliver this promise across industrial sectors, the need to invest in expert knowledge is rising.
NASA has been a pioneer in space-based communication over many decades, and more recently has emerged as a leader in space-based quantum communication, dedicating new resources for scientists, engineers and communication systems experts to learn about the field.
Recently, NASA’s Space Communications and Navigation (SCaN) program commissioned a booklet titled Quantum Communication 101, authored by several of our team at Quantinuum. This will be a go-to resource for the global community of scientists and experts that NASA supports, but importantly it has been written so that it requires almost no prior technical knowledge while providing a rigorous account of the emerging field of quantum communications.
What follows is a taster of what’s in Quantum Communication 101.
What is quantum communication?
For the words I am typing now to reach your computer screen, I need to rely on modern communication networks. My laptop memory, Wi-Fi router and communication channels rely on the physics of things like transistors, currents, and radio waves which obey the more familiar, “classical" laws of physics.
The field of quantum communication, however, relies on the counterintuitive rules of quantum physics. Thanks to incredible feats of engineering, in place of continuous beams of light from diodes, we can now control individual photons to send and receive quantum information. By taking advantage of the peculiar quantum phenomena that they exhibit, like superposition and entanglement, new possibilities are emerging which were previously unimaginable.
Cutting-edge applications
In the growing landscape of potential applications in quantum communication, cybersecurity is already deeply rooted. At Quantinuum, for example, quantum computers are used to generate randomness, the fundamental building block of secure encryption. Elsewhere, prototype quantum networks for secure communications already span metropolitan areas.
As our techniques in quantum communication advance, we may unlock new possibilities in quantum computing, which promises to solve problems too difficult even for supercomputers, and quantum metrology, which will enable measurements at an unprecedented precision. Quantum states of light have already been used in LIGO - a large-scale experiment operated by CalTech and MIT to detect ripples in the fabric of space-time itself.
Connecting the dots: towards a quantum internet
The end goal of quantum communication is what many refer to as the quantum internet, through which we will seamlessly send quantum signals across many quantum networks. This will be an enormous engineering challenge, requiring international collaboration and the evolution of our existing infrastructure.
Although the exact form that this network will take is yet unknown, we can say with confidence that it will need to pass through space. Much like satellites help to globally connect the Internet, the launch of quantum-capable satellites will play a vital role in a global quantum internet.
Building a quantum ecosystem
The path to a quantum internet will depend on growing a diverse and expert workforce. This is well understood by bodies such as the National Science Foundation who recently announced a $5.1M Center for Quantum Networks aimed at architecting the quantum internet. Over the last few years, we have seen growing investment worldwide, such as the $1.1B Quantum Technology Flagship in Europe and the $11B Chinese National Laboratory for Quantum Information Science. Important industrial investments are being made by large corporations such as IBM, Google, Intel, Honeywell, Cisco, Amazon, and Microsoft.
Amongst this surge in interest, NASA’s SCaN program has proposed a series of mission concepts for building and testing infrastructure for space-based quantum communication. These include launching satellites capable of sending and receiving quantum signals between ground stations and eventually other satellites. These quantum signals may be entangled photons – a feature that will play an extremely important role in future networks. One such mission concept is shown below, where a quantum-capable satellite with a source of entangled photons connects an intercontinental quantum network.
The second quantum revolution is at an exciting precipice where our ability to transmit quantum information, both on Earth and in space, will be pivotal. Whilst our evolving quantum technologies already show a great deal of promise, it is perhaps the ground-breaking applications that we are yet to discover which will ultimately determine our success.
It is more important than ever that we support education and collaboration in advancing quantum technologies. Quantum Communication 101 aims to be a starting point for a general audience looking to learn about the topic for the first time, as well as those who wish to explore in detail the technologies that will make the first quantum networks a reality.
If you would like to better understand the exciting prospects of quantum communication, you can find the Quantum Communication 101 booklet on the NASA SCaN website.
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.
In a follow-up to our recent work with Hiverge using AI to discover algorithms for quantum chemistry, we’ve teamed up with Hiverge, Amazon Web Services (AWS) and NVIDIA to explore using AI to improve algorithms for combinatorial optimization.
With the rapid rise of Large Language Models (LLMs), people started asking “what if AI agents can serve as on-demand algorithm factories?” We have been working with Hiverge, an algorithm discovery company, AWS, and NVIDIA, to explore how LLMs can accelerate quantum computing research.
Hiverge – named for Hive, an AI that can develop algorithms – aims to make quantum algorithm design more accessible to researchers by translating high-level problem descriptions in mostly natural language into executable quantum circuits. The Hive takes the researcher’s initial sketch of an algorithm, as well as special constraints the researcher enumerates, and evolves it to a new algorithm that better meets the researcher’s needs. The output is expressed in terms of a familiar programming language, like Guppy or NVIDIA CUDA-Q, making it particularly easy to implement.
The AI is called a “Hive” because it is a collective of LLM agents, all of whom are editing the same codebase. In this work, the Hive was made up of LLM powerhouses such as Gemini, ChatGPT, Claude, Llama, as well as NVIDIA Nemotron, which was accessed through AWS’ Amazon Bedrock service. Many models are included because researchers know that diversity is a strength – just like a team of human researchers working in a group, a variety of perspectives often leads to the strongest result.
Once the LLMs are assembled, the Hive calls on them to do the work writing the desired algorithm; no new training is required. The algorithms are then executed and their ‘fitness’ (how well they solve the problem) is measured. Unfit programs do not survive, while the fittest ones evolve to the next generation. This process repeats, much like the evolutionary process of nature itself.
After evolution, the fittest algorithm is selected by the researchers and tested on other instances of the problem. This is a crucial step as the researchers want to understand how well it can generalize.
In this most recent work, the joint team explored how AI can assist in the discovery of heuristic quantum optimization algorithms, a class of algorithms aimed at improving efficiency across critical workstreams. These span challenges like optimal power grid dispatch and storage placement, arranging fuel inside nuclear reactors, and molecular design and reaction pathway optimization in drug, material, and chemical discovery—where solutions could translate into maximizing operational efficiency, dramatic reduction in costs, and rapid acceleration in innovation.
In other AI approaches, such as reinforcement learning, models are trained to solve a problem, but the resulting "algorithm" is effectively ‘hidden’ within a neural network. Here, the algorithm is written in Guppy or CUDA-Q (or Python), making it human-interpretable and easier to deploy on new problem instances.
This work leveraged the NVIDIA CUDA-Q platform, running on powerful NVIDIA GPUs made accessible by AWS. It’s state-of-the art accelerated computing was crucial; the research explored highly complex problems, challenges that lie at the edge of classical computing capacity. Before running anything on Quantinuum’s quantum computer, the researchers first used NVIDIA accelerated computing to simulate the quantum algorithms and assess their fitness. Once a promising algorithm is discovered, it could then be deployed on quantum hardware, creating an exciting new approach for scaling quantum algorithm design.
More broadly, this work points to one of many ways in which classical compute, AI, and quantum computing are most powerful in symbiosis. AI can be used to improve quantum, as demonstrated here, just as quantum can be used to extend AI. Looking ahead, we envision AI evolving programs that express a combination of algorithmic primitives, much like human mathematicians, such as Peter Shor and Lov Grover, have done. After all, both humans and AI can learn from each other.
As quantum computing power grows, so does the difficulty of error correction. Meeting that demand requires tight integration with high-performance classical computing, which is why we’ve partnered with NVIDIA to push the boundaries of real-time decoding performance.
Realizing the full power of quantum computing requires more than just qubits, it requires error rates low enough to run meaningful algorithms at scale. Physical qubits are sensitive to noise, which limits their capacity to handle calculations beyond a certain scale. To move beyond these limits, physical qubits must be combined into logical qubits, with errors continuously detected and corrected in real time before they can propagate and corrupt the calculation. This approach, known as fault tolerance, is a foundational requirement for any quantum computer intended to solve problems of real-world significance.
Part of the challenge of fault tolerance is the computational complexity of correcting errors in real time. Doing so involves sending the error syndrome data to a classical co-processor, solving a complex mathematical problem on that processor, then sending the resulting correction back to the quantum processor - all fast enough that it doesn’t slow down the quantum computation. For this reason, Quantum Error Correction (QEC) is currently one of the most demanding use-cases for tight coupling between classical and quantum computing.
Given the difficulty of the task, we have partnered with NVIDIA, leaders in accelerated computing. With the help of NVIDIA’s ultra-fast GPUs (and the GPU-accelerated BP-OSD decoder developed by NVIDIA as part of NVIDIA CUDA-Q QEC library), we were able to demonstrate real-time decoding of Helios’ qubits, all in a system that can be connected directly to our quantum processors using NVIDIA NVQLink.
While real-time decoding has been demonstrated before (notably, by our own scientists in this study), previous demonstrations were limited in their scalability and complexity.
In this demonstration, we used Brings’ code, a high-rate code that is possible with our all-to-all connectivity, to encode our physical qubits into noise-resilient logical qubits. Once we had them encoded, we ran gates as well as let them idle to see if we could catch and correct errors quickly and efficiently. We submitted the circuits via both NVIDIA CUDA-Q as well as our own Guppy language, underlining our commitment to accessible, ecosystem-friendly quantum computing.
The results were excellent: we were able to perform low-latency decoding that returned results in the time we needed, even for the faster clock cycles that we expect in future generation machines.
A key part of the achievement here is that we performed something called “correlated” decoding. In correlated decoding, you offload work that would normally be performed on the QPU onto the classical decoder. This is because, in ‘standard’ decoding, as you improve your error correction capabilities, it takes more and more time on the QPU. Correlated decoding elides this cost, saving QPU time for the tasks that only the quantum computer can do.
Stay tuned for our forthcoming paper with all the details.
Every year, APS Global Physics Summit brings together scientific community members from around the world across all disciplines of physics.
Join Quantinuum at this year’s conference, taking place in our backyard, Denver, Colorado, from March 15th – 20th, where we will showcase how our quantum hardware, software, and partnerships are helping define the next era of high-performance and quantum computing.
Find our team at booth #1020 and join our sessions below to discover how we’re advancing quantum technologies and building the bridge between HPC and quantum.
Monday, March 16th
Programmable quantum matter at the frontier of classical computation
Speaker: Andrew Potter
Time: 10:12 – 10:48 am
Benchmarking a 98-qubit trapped-ion quantum computer
Speaker: Charles Baldwin
Time: 12:36 – 12:48 pm
High-Fidelity Quantum operations in the Helios Barium-Ion Processor
Speaker: Anthony Ransford
Time: 4:18 – 4:30 pm
Generative AI Model for Quantum State Preparation
Speaker: Jem Guhit
Time: 4:42 – 4:54 pm
Quantum digital simulations of holographic models using Quantinuum Systems
Speaker: Enrico Rinaldi
Time: 5:54 – 6:30 pm
Tuesday, March 17th
Software-Enabled Innovations that Drive Robust Commercial Operation on Quantinuum Helios
Speaker: Caroline Figgatt
Time: 8:00 – 8:12 am
Improving Clock Speed in the Quantinuum Helios Quantum Computer
Speaker: Adam Reed
Time: 8:12 – 8:24 am
Less Quantum, More Advantage: An End-to-End Quantum Algorithm for the Jones Polynomial
Speaker: Konstantinos Meichanetzidis
Time: 8:48 – 9:00 am
Quantum Operation Pipelining in the Quantinuum Helios Processor
Speaker: Colin Kennedy
Time: 9:00 - 9:12 am
Directly estimating the fidelity of measurement-based quantum computation
Speaker: David Stephen
Time: 9:12 - 9:24 am
Logical algorithms in a quantum error-detecting code on a trapped-ion quantum processor
Speaker: Matthew DeCross
Time: 9:36 - 9:48 am
Separate and efficient characterization of SPAM errors in the presence of leakage
Speaker: Leigh Norris
Time: 10:00 - 10:12 am
Logical benchmarking on a trapped-ion quantum processor
Speaker: Andrew Guo
Time: 12:00 - 12:12 pm
Modelling Actinides Chemistry with Trapped Ion Quantum Computers
Speaker: Carlo Alberto Gaggioli
Time: 3:30 - 3:42 pm
Wednesday, March 18th
Digital quantum magnetism at the frontier of classical simulation
Speaker: Michael Foss-Feig
Time: 8:36 - 9:12 am
Shorter width truncated Taylor series for Hamiltonian dynamics simulations
Speaker: Michelle Wynne Sze
Time: 9:24 - 9:36 am
Quantum-Accelerated DFT+DMFT for Correlated Subspaces in Hemoglobin
Speaker: Juan Pedersen
Time: 9:48 - 10:00 am
Simple logical quantum computation with concatenated symplectic double codes
Speaker: Noah Berthusen
Time: 12:48 - 1:00 pm
When is enough enough? Efficient estimation of quantum properties by stopping early
Speaker: Oliver Hart
Time: 12:48 - 1:00 pm
High-Level Programming of the Quantinuum Helios Processor
Speaker: John Campora
Time: 1:48 - 2:24 pm
Error detection without post-selection in adaptive quantum circuits
Speaker: Eli Chertkov
Time: 4:42 - 4:54 pm
Thursday, March 19th
Below Threshold Logical Quantum Computation at Quantinuum
Speaker: Shival Dasu
Time: 8:00 - 8:36 am
Performing optimal phase measurements with a universal quantum processor
Speaker: Ross Hutson
Time: 8:36 - 8:48 am
Benchmarking with leakage heralded measurements on the Quantinuum Helios processor
Speaker: Victor Colussi
Time: 10:00 am
High-throughput bidirectional microwave-to-optical transduction assessed with a practical quantum capacity
Speaker: Maxwell Urmey
Time: 12:00 - 12:36 pm
Fast quantum state preparation via AI-based Graph Decimation
Speaker: Matteo Puviani
Time: 5:54 - 6:06 pm
Friday, March 20th
2D Tensor Network Methods for Simulation of Spin Models on Quantum Computers
Speaker: Reza Haghshenas
Time: 8:36 - 8:48 am
High-Performance Computing Simulations for Optical Multidimensional Coherent Spectroscopy Studies of Strained Silicon-Vacancy Centers in Diamond
Speaker: Imran Bashir
Time: 10:36 - 10:48 am
High-Performance Statevector Simulation for TKET and Selene with NVIDIA cuStateVec
Speaker: Fabian Finger
Time: 12:36 - 12:48 pm
Part 1: Logic gates on High-rate Quantum LDPC codes using ion trap devices
Speaker: Elijah Durso-Sabina
Time: 12:48 - 1:00 pm
Driving Quantum Computing Forward: QEC, Hardware, and Applications with Quantinuum
Speaker: Natalie Brown
Time: 1:12 - 1:48 pm
A new QCCD computer and new applications
Speaker: Anthony Ransford
Time: 2:24 - 3:00 pm
*All times in MT