Quantum Volume reaches 5 digits for the first time
夜色直播鈥檚 H-Series team has hit the ground running in 2023, achieving a new performance milestone. The H1-1 trapped ion quantum computer has achieved a Quantum Volume (QV) of 32,768 (215), the highest in the industry to date.
The team previously increased the QV to 8,192 (or 213) for the System Model H1 system in September, less than six months ago. The next goal was a QV of 16,384 (214). However, continuous improvements to the H1-1's controls and subsystems advanced the system enough to successfully reach 214 as expected, and then to go one major step further, and reach a QV of 215.
The Quantum Volume test is a full-system benchmark that produces a single-number measure of a quantum computer鈥檚 general capability. The benchmark takes into account qubit number, fidelity, connectivity, and other quantities important in building useful devices.聽While other measures such as gate fidelity and qubit count are significant and worth tracking, neither is as comprehensive as Quantum Volume which better represents the operational ability of a quantum computer.
Dr. Brian Neyenhuis, Director of Commercial Operations, credits reductions in the phase noise of the computer鈥檚 lasers as one key factor in the increase.
"We've had enough qubits for a while, but we've been continually pushing on reducing the error in our quantum operations, specifically the two-qubit gate error, to allow us to do these Quantum Volume measurements,鈥 he said.聽
The 夜色直播 team improved memory error and elements of the calibration process as well.聽
鈥淚t was a lot of little things that got us to the point where our two-qubit gate error and our memory error are both low enough that we can pass these Quantum Volume circuit tests,鈥 he said.聽
The work of increasing Quantum Volume means improving all the subsystems and subcomponents of the machine individually and simultaneously, while ensuring all the systems continue to work well together. Such a complex task takes a high degree of orchestration across the 夜色直播 team, with the benefits of the work passed on to H-Series users.聽
To illustrate what this 5-digit Quantum Volume milestone means for the H-Series, here are 5 perspectives that reflect 夜色直播 teams and H-Series users.
Perspective #1:聽How a higher QV impacts algorithms
Dr. Henrik Dreyer is Managing Director and Scientific Lead at 夜色直播鈥檚 office in Munich, Germany. In the context of his work, an improvement in Quantum Volume is important as it relates to gate fidelity.聽
鈥淎s application developers, the signal-to-noise ratio is what we're interested in,鈥 Henrik said. 鈥淚f the signal is small, I might run the circuits 10 times and only get one good shot. To recover the signal, I have to do a lot more shots and throw most of them away. Every shot takes time."
鈥淭he signal-to-noise ratio is sensitive to the gate fidelity. If you increase the gate fidelity by a little bit, the runtime of a given algorithm may go down drastically,鈥 he said. 鈥淔or a typical circuit, as the plot shows, even a relatively modest 0.16 percentage point improvement in fidelity, could mean that it runs in less than half the time.鈥
To demonstrate this point, the 夜色直播 team has been benchmarking the System Model H1 performance on circuits relevant for near-term applications. The graph below shows repeated benchmarking of the runtime of these circuits before and after the recent improvement in gate fidelity. The result of this moderate change in fidelity is a 3x change in runtime.聽The runtimes calculated below are based on the number of shots required to obtain accurate results from the benchmarking circuit 鈥 the example uses 430 arbitrary-angle two-qubit gates and an accuracy of 3%.
Perspective #2:聽Advancing quantum error correction
Dr. Natalie Brown and Dr, Ciaran Ryan-Anderson both work on quantum error correction at 夜色直播. They see the QV advance as an overall boost to this work.聽
鈥淗itting a Quantum Volume number like this means that you have low error rates, a lot of qubits, and very long circuits,鈥 Natalie said. 鈥淎nd all three of those are wonderful things for quantum error correction. A higher Quantum Volume most certainly means we will be able to run quantum error correction better. Error correction is a critical ingredient to large-scale quantum computing. The earlier we can start exploring error correction on today鈥檚 small-scale hardware, the faster we鈥檒l be able to demonstrate it at large-scale.鈥
Ciaran said that H1-1's low error rates allow scientists to make error correction better and start to explore decoding options.
鈥淚f you can have really low error rates, you can apply a lot of quantum operations, known as gates,鈥 Ciaran said. "This makes quantum error correction easier because we can suppress the noise even further and potentially use fewer resources to do it, compared to other devices.鈥
Perspective #3: Meeting a high benchmark
鈥淭his accomplishment shows that gate improvements are getting translated to full-system circuits,鈥 said Dr. Charlie Baldwin, a research scientist at 夜色直播.聽
Charlie specializes in quantum computing performance benchmarks, conducting research with the Quantum Economic Development Consortium (QED-C).
鈥淥ther benchmarking tests use easier circuits or incorporate other options like post-processing data. This can make it more difficult to determine what part improved,鈥 he said. 鈥淲ith Quantum Volume, it鈥檚 clear that the performance improvements are from the hardware, which are the hardest and most significant improvements to make.鈥澛
鈥淨uantum Volume is a well-established test. You really can鈥檛 cheat it,鈥 said Charlie.
Perspective #4:聽Implications for quantum applications
Dr. Ross Duncan, Head of Quantum Software, sees Quantum Volume measurements as a good way to show overall progress in the process of building a quantum computer.
鈥淨uantum Volume has merit, compared to any other measure, because it gives a clear answer,鈥 he said.聽
鈥淭his latest increase reveals the extent of combined improvements in the hardware in recent months and means researchers and developers can expect to run deeper circuits with greater success.鈥澛
Perspective #5:聽H-Series users
夜色直播鈥檚 business model is unique in that the H-Series systems are continuously upgraded through their product lifecycle. For users, this means they continually and immediately get access to the latest breakthroughs in performance. The reported improvements were not done on an internal testbed, but rather implemented on the H1-1 system which is commercially available and used extensively by users around the world.
鈥淎s soon as the improvements were implemented, users were benefiting from them,鈥 said Dr. Jenni Strabley, Sr. Director of Offering Management. 鈥淲e take our Quantum Volume measurement intermixed with customers鈥 jobs, so we know that the improvements we鈥檙e seeing are also being seen by our customers.鈥
Jenni went on to say, 鈥淐ontinuously delivering increasingly better performance shows our commitment to our customers鈥 success with these early small-scale quantum computers as well as our commitment to accuracy and transparency. That鈥檚 how we accelerate quantum computing.鈥
Supporting data from 夜色直播鈥檚 215 QV milestone
This latest QV milestone demonstrates how the 夜色直播 team continues to boost the performance of the System Model H1, making improvements to the two-qubit gate fidelity while maintaining high single-qubit fidelity, high SPAM fidelity, and low cross-talk.
The average single-qubit gate fidelity for these milestones was 99.9955(8)%, the average two-qubit gate fidelity was 99.795(7)% with fully connected qubits, and state preparation and measurement fidelity was 99.69(4)%.
For both tests, the 夜色直播 team ran 100 circuits with 200 shots each, using standard QV optimization techniques to yield an average of 219.02 arbitrary angle two-qubit gates per circuit on the 214 test, and 244.26 arbitrary angle two-qubit gates per circuit on the 215 test.
The 夜色直播 H1-1 successfully passed the quantum volume 16,384 benchmark, outputting heavy outcomes 69.88% of the time, and passed the 32,768 benchmark, outputting heavy outcomes 69.075% of the time. The heavy output frequency is a simple measure of how well the measured outputs from the quantum computer match the results from an ideal simulation. Both results are above the two-thirds passing threshold with high confidence. More details on the Quantum Volume test can be found .
Heavy output frequency for H1-1 at 215 (QV 32,768)
Heavy output frequency for H1-1 at 214 (QV 16,384)聽
Quantum Volume data and analysis code can be accessed on . Contemporary benchmarking data can be accessed at .
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About 夜色直播
夜色直播,聽the world鈥檚 largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. 夜色直播鈥檚 technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, 夜色直播 leads the quantum computing revolution across continents.聽
- The Sanger Institute illustrates the value of quantum computing to genomics research
- 夜色直播 supports developments in a field that promises to deliver a profound and positive societal impact
Twenty-five years ago, scientists accomplished a task likened to a biological : the sequencing of the entire human genome.
The Human Genome Project revealed a complete human blueprint comprising around 3 billion base pairs, the chemical building blocks of DNA. It led to breakthrough medical treatments, scientific discoveries, and a new understanding of the biological functions of our body.
Thanks to technological advances in the quarter-century since, what took 13 years and cost $2.7 billion then in under 12 minutes for a few hundred dollars. Improved instruments such as next-generation sequencers and a better understanding of the human genome 鈥 including the availability of a 鈥渞eference genome鈥 鈥 have aided progress, alongside enormous advances in algorithms and computing power.
But even today, some genomic challenges remain so complex that they stretch beyond the capabilities of the most powerful classical computers operating in isolation. This has sparked a bold search for new computational paradigms, and in particular, quantum computing.
Quantum Challenge: Accepted
The is pioneering this new frontier. The program funds research to develop quantum algorithms that can overcome current computational bottlenecks. It aims to test the classical boundaries of computational genetics in the next 3-5 years.
One consortium 鈥 led by the University of Oxford and supported by prestigious partners including the Wellcome Sanger Institute, the Universities of Cambridge, Melbourne, and Kyiv Academic University 鈥 is taking a leading role.
鈥淭he overall goal of the team鈥檚 project is to perform a range of genomic processing tasks for the most complex and variable genomes and sequences 鈥 a task that can go beyond the capabilities of current classical computers鈥 鈥 Wellcome Sanger Institute , July 2025
Selecting 夜色直播
Earlier this year, the Sanger Institute selected 夜色直播 as a technology partner in their bid to succeed in the Q4Bio challenge.
Our flagship quantum computer, System H2, has for many years led the field of commercially available systems for qubit fidelity and consistently holds the global record for Quantum Volume, currently benchmarked at 8,388,608 (223).
In this collaboration, the scientific research team can take advantage of 夜色直播鈥檚 full stack approach to technology development, including hardware, software, and deep expertise in quantum algorithm development.
鈥淲e were honored to be selected by the Sanger Institute to partner in tackling some of the most complex challenges in genomics. By bringing the world鈥檚 highest performing quantum computers to this collaboration, we will help the team push the limits of genomics research with quantum algorithms and open new possibilities for health and medical science.鈥 鈥 Rajeeb Hazra, President and CEO of 夜色直播
Quantum for Biology
At the heart of this endeavor, the consortium has announced a bold central mission for the coming year: to encode and process an entire genome using a quantum computer. This achievement would be a potential world-first and provide evidence for quantum computing鈥檚 readiness for tackling real-world use cases.
Their chosen genome, the bacteriophage PhiX174, carries symbolic weight, as its sequencing his second Nobel Prize for Chemistry in 1980. Successfully encoding this genome quantum mechanically would represent a significant milestone for both genomics and quantum computing.
Sooner than many expect, quantum computing may play an essential role in tackling genomic challenges at the very frontier of human health. The Sanger Institute and 夜色直播鈥檚 partnership reminds us that we may soon reach an important step forward in human health research 鈥 one that could change medicine and computational biology as dramatically as the original Human Genome Project did a quarter-century ago.
鈥淨uantum computational biology has long inspired us at 夜色直播, as it has the potential to transform global health and empower people everywhere to lead longer, healthier, and more dignified lives.鈥 鈥 Ilyas Khan, Founder and Chief Product Officer of 夜色直播
Every year, The IEEE International Conference on Quantum Computing and Engineering 鈥 or 鈥 brings together engineers, scientists, researchers, students, and others to learn about advancements in quantum computing.
This year鈥檚 conference from August 31st 鈥 September 5th, is being held in Albuquerque, New Mexico, a burgeoning epicenter for quantum technology innovation and the home to our new location that will support ongoing collaborative efforts to advance the photonics technologies critical to furthering our product development.
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 #507 and join the below sessions to discover how 夜色直播 is forging the path to fault-tolerant quantum computing with our integrated full-stack.
September 2nd
Quantum Software 2.1: Open Problems, New Ideas, and Paths to Scale
1:15 鈥 2:10pm MDT | Mesilla
We recently shared the details of our new software stack for our next-generation systems, including Helios (launching in 2025). 夜色直播鈥檚 Agust铆n Borgna will deliver a lighting talk to introduce Guppy, our new, open-source programming language based on Python, one of the most popular general-use programming languages for classical computing.
September 3rd
PAN08: Progress and Platforms in the Era of Reliable Quantum Computing
1:00 鈥 2:30pm MDT | Apache
We are entering the era of reliable quantum computing. Across the industry, quantum hardware and software innovators are enabling this transformation by creating reliable logical qubits and building integrated technology stacks that span the application layer, middleware and hardware. Attendees will hear about current and near-term developments from Microsoft, 夜色直播 and Atom Computing. They will also gain insights into challenges and potential solutions from across the ecosystem, learn about Microsoft鈥檚 qubit-virtualization system, and get a peek into future developments from 夜色直播 and Microsoft.
BOF03: Exploring Distributed Quantum Simulators on Exa-scale HPC Systems
3:00 鈥 4:30pm MDT | Apache
The core agenda of the session is dedicated to addressing key technical and collaborative challenges in this rapidly evolving field. Discussions will concentrate on innovative algorithm design tailored for HPC environments, the development of sophisticated hybrid frameworks that seamlessly combine classical and quantum computational resources, and the crucial task of establishing robust performance benchmarks on large-scale CPU/GPU HPC infrastructures.
September 4th
PAN11: Real-time Quantum Error Correction: Achievements and Challenges
1:00 鈥 2:30pm MDT | La Cienega
This panel will explore the current state of real-time quantum error correction, identifying key challenges and opportunities as we move toward large-scale, fault-tolerant systems. Real-time decoding is a multi-layered challenge involving algorithms, software, compilation, and computational hardware that must work in tandem to meet the speed, accuracy, and scalability demands of FTQC. We will examine how these challenges manifest for multi-logical qubit operations, and discuss steps needed to extend the decoding infrastructure from intermediate-scale systems to full-scale quantum processors.
September 5th
Keynote by NVIDIA
8:00 鈥 9:30am MDT | Kiva Auditorium
During his keynote talk, NVIDIA鈥檚 Head of Quantum Computing Product, Sam Stanwyck, will detail our partnership to fast-track commercially scalable quantum supercomputers. Discover how 夜色直播 and NVIDIA are pushing the boundaries to deliver on the power of hybrid quantum and classical compute 鈥 from integrating NVIDIA鈥檚 CUDA-Q Platform with access to 夜色直播鈥檚 industry-leading hardware to the recently announced NVIDIA Quantum Research Center (NVAQC).
Featured Research at the IEEE Poster Session:
Visible Photonic Component Development for Trapped-Ion Quantum Computing
September 2nd from 6:30 - 8:00pm MDT | September 3rd from 9:30 - 10:00am MDT |聽September 4th from 11:30 - 12:30pm MDT
鈥Authors: Elliot Lehman, Molly Krogstad, Molly P. Andersen, Sara Cambell, Kirk Cook, Bryan DeBono, Christopher Ertsgaard, Azure Hansen, Duc Nguyen, Adam聽Ollanik, Daniel Ouellette, Michael Plascak, Justin T. Schultz, Johanna Zultak, Nicholas Boynton, Christopher DeRose,Michael Gehl, and Nicholas Karl
Scaling Up Trapped-Ion Quantum Processors with Integrated Photonics
September 2nd from 6:30 - 8:00pm MDT and 2:30 - 3:00pm MDT |聽September 4th from 9:30 - 10:00am MDT
Authors: Molly Andersen, Bryan DeBono, Sara Campbell, Kirk Cook, David Gaudiosi, Christopher Ertsgaard, Azure Hansen, Todd Klein, Molly Krogstad, Elliot Lehman, Gregory MacCabe, Duc Nguyen, Nhung Nguyen, Adam Ollanik, Daniel Ouellette, Brendan Paver, Michael Plascak, Justin Schultz and Johanna Zultak
Research Collaborations with the Local Ecosystem
In a partnership that is part of a long-standing relationship with Los Alamos National Laboratory, we have been working on new methods to make quantum computing operations more efficient, and ultimately, scalable.
Learn more in our Research Paper:
Our teams collaborated with Sandia National Laboratories demonstrating our leadership in benchmarking. In this paper, we implemented a technique devised by researchers at Sandia to measure errors in mid-circuit measurement and reset. Understanding these errors helps us to reduce them while helping our customers understand what to expect while using our hardware.
Learn more in our Research Paper:
From machine learning to quantum physics, tensor networks have been quietly powering the breakthroughs that will reshape our society. Originally developed by the legendary Nobel laureate Roger Penrose, they were first used to tackle esoteric problems in physics that were previously unsolvable.
Today, tensor networks have become indispensable in a huge number of fields, including both classical and quantum computing, where they are used everywhere from quantum error correction (QEC) decoding to quantum machine learning.
In , we teamed up with luminaries from the University of British Columbia, California Institute of Technology, University of Jyv盲skyl盲, KBR Inc, NASA, Google Quantum AI, NVIDIA, JPMorgan Chase, the University of Sherbrooke, and Terra Quantum AG to provide a comprehensive overview of the use of tensor networks in quantum computing.
Standing on the shoulders of giants
Part of what drives our leadership in quantum computing is our commitment to building the best scientific team in the world. This is precisely why we hired Dr. Reza Haghshenas, one of the world鈥檚 leading experts in tensor networks, and a co-author on the paper.
Dr. Haghshenas has been researching tensor networks for over a decade across both academia and industry. Dr. Haghshenas did postdoctoral work under , a leading figure in the use of tensor networks for quantum physics and chemistry.
鈥淲orking with Dr. Garnet Chan at Caltech was a formative experience for me鈥, remarked Dr. Haghshenas. 鈥淲hile there, I contributed to the development of quantum simulation algorithms and advanced classical methods like tensor networks to help interpret and simulate many-body physics.鈥
Since joining 夜色直播, Dr. Haghshenas has led projects that bring tensor network methods into direct collaboration with experimental hardware teams 鈥 exploring quantum magnetism on real quantum devices and helping demonstrate early signs of quantum advantage. He also contributes to , helping the broader research community access these methods.
Dr. Haghshenas鈥 work sits in a broad and vibrant ecosystem exploring novel uses of tensor networks. Collaborations with researchers like Dr. Chan at Caltech, and NVIDIA have brought GPU-accelerated tools to bear on the forefront of applying tensor networks to quantum chemistry, quantum physics, and quantum computing.
A powerful simulation tool
Of particular interest to those of us in quantum computing, the best methods (that we know of) for simulating quantum computers with classical computers rely on tensor networks. Tensor networks provide a nice way of representing the entanglement in a quantum algorithm and how it spreads, which is crucial but generally quite difficult for classical algorithms. In fact, it鈥檚 partly tensor networks鈥 ability to represent entanglement that makes them so powerful for quantum simulation. Importantly, it is our in-house expertise with tensor networks that makes us confident we are indeed moving past classical capabilities.
A theory of evolution
Tensor networks are not only crucial to cutting-edge simulation techniques. 聽At 夜色直播, we're working on understanding and implementing quantum versions of classical tensor network algorithms, from quantum matrix product states to holographic simulation methods. In doing this, we are leveraging decades of classical algorithm development to advance quantum computing.
A topic of growing interest is the role of tensor networks in QEC, particularly in a process known as decoding. QEC works by encoding information into an entangled state of multiple qubits and using syndrome measurements to detect errors. These measurements must then be decoded to identify the specific error and determine the appropriate correction. This decoding step is challenging鈥攊t must be both fast (within the qubit鈥檚 coherence time) and accurate (correctly identifying and fixing errors). Tensor networks are emerging as one of the most for tackling this task.
Looking forward (and backwards, and sideways...)
Tensor networks are more than just a powerful computational tool 鈥 they are a bridge between classical and quantum thinking. As this new paper shows, the community鈥檚 understanding of tensor networks has matured into a robust foundation for advancing quantum computing, touching everything from simulation and machine learning to error correction and circuit design.
At 夜色直播, we see this as an evolutionary step, not just in theory, but in practice. By collaborating with top minds across academia and industry, we're charting a path forward that builds on decades of classical progress while embracing the full potential of quantum mechanics. This transition is not only conceptual but algorithmic, advancing how we formulate and implement methods utilizing efficiently both classical and quantum computing. Tensor networks aren鈥檛 just helping us keep pace with classical computing; they鈥檙e helping us to transcend it.