夜色直播 Sets New Record with Highest Ever Quantum Volume
Simpler, faster and fewer errors: How arbitrary angle gates help increase H1鈥檚 quantum volume
New arbitrary angle gate capabilities enable increase in Quantum Volume (QV) to 8192 as 夜色直播 continues to achieve its previously stated objective of increasing its QV by 10x every year; TKET downloads surpass 500,000
夜色直播 President and COO Tony Uttley announced three major accomplishments during his keynote address at the IEEE Quantum Week event in Colorado last week.听
The three milestones, representing actionable acceleration for the quantum computing eco-system, are: (i) new arbitrary angle gate capabilities on the H-series hardware, (ii) another QV record for the System Model H1 hardware, and (iii) over 500,000 downloads of 夜色直播鈥檚 open-sourced , a world-leading quantum software development kit (SDK).听
The announcements were made during Uttley鈥檚 keynote address titled, 鈥淎 Measured Approach to Quantum Computing.鈥
These advancements are the latest examples of the company鈥檚 continued demonstration of its leadership in the quantum computing community.听
鈥溡股辈 is accelerating quantum computing鈥檚 impact to the world,鈥 Uttley said. 鈥淲e are making significant progress with both our hardware and software, in addition to building a community of developers who are using our TKET SDK.鈥
This latest quantum volume measurement of 8192 is particularly noteworthy and is the second time this year 夜色直播 has published a new QV record on their trapped-ion quantum computing platform, the System Model H1, Powered by Honeywell.听
A key to achieving this latest record is the new capability of directly implementing arbitrary angle two-qubit gates. For many quantum circuits, this new way of doing a two-qubit gate allows for more efficient circuit construction and leads to higher fidelity results.听
Dr. Brian Neyenhuis, Director of Commercial Operations at 夜色直播, said, 鈥淭his new capability allows for several user advantages. In many cases, this includes shorter interactions with the qubits, which lowers the error rate. This allows our customers to run long computations with less noise.鈥
These arbitrary angle gates build on the overall design strength of the trapped-ion architecture of the H1, Neyenhuis said.听
鈥淲ith the quantum-charged coupled device (QCCD) architecture, interactions between qubits are very simple and can be limited to a small number of qubits which means we can precisely control the interaction and don鈥檛 have to worry about additional crosstalk,鈥 he said.听
This new gate design represents a third method for 夜色直播 to improve the efficiency of the H1 generation, said Dr. Jenni Strabley, Senior Director of Offering Management at 夜色直播.
鈥溡股辈モ檚 goal is to accelerate quantum computing. We know we have to make the hardware better and we have to make the algorithms smarter, and we鈥檙e doing that,鈥 she said. 鈥淣ow we can also implement the algorithms more efficiently on our H1 with this new gate design.鈥
A powerful new capability: More information on arbitrary angle gates聽
Currently, researchers can do single qubit gates 鈥 rotations on a single qubit 鈥 or a fully entangling two-qubit gate. It鈥檚 possible to build any quantum operation out of just those building blocks.
With arbitrary angle gates, instead of just having a two-qubit gate that's fully entangling, scientists can use a two-qubit gate that is partially entangling.听
鈥淭here are many algorithms where you want to evolve the quantum state of the system one tiny step at a time. Previously, if you wanted a tiny bit of entanglement for some small time step, you had to entangle it all the way, rotate it a little bit, and then unentangle it almost all the way back,鈥 Neyenhuis said. 鈥淣ow we can just add this tiny little bit of entanglement natively and then go to the next step of the algorithm.鈥
There are other algorithms where this arbitrary angle two-qubit gate is the natural building block, according to Neyenhuis. One example is the quantum Fourier transform. Using arbitrary angle two-qubit gates cuts the number of two-qubit gates (and the overall error) in half, drastically improving the fidelity of the circuit. Researchers can use this new gate design to run harder problems that resulted in catastrophic errors in previous experiments.
鈥淏y going to an arbitrary angle gate, in addition to cutting the number of two-qubit gates in half, the error we get per gate is lower because it scales with the amplitude of that gate,鈥 Neyenhuis said.听
This is a powerful new capability, particularly for noisy intermediate-scale quantum algorithms. Another demonstration from the 夜色直播 team was to use arbitrary angle two-qubit gates to study non-equilibrium phase transitions, the technical details of which are .听
鈥淔or the algorithms that we are going to want to run in this NISQ regime that we're in right now, this is a more efficient way to run your algorithm,鈥 Neyenhuis said. 鈥淭here are lots of different circuits you would want to run where this arbitrary angle gate gives you a fairly significant increase in the fidelity of your overall circuit.听This capability also allows for a speed up in the circuit execution by removing unneeded gates, which ultimately reduces the time of executing a job on our machines.鈥
Researchers working with machine learning algorithms, variational algorithms, and time evolution algorithms would see the most benefit from these new gates. This advancement is particularly relevant for simulating the dynamics of other quantum systems.听
鈥淭his just gave us a big win in fidelity because we can run the sort of interaction you're after natively, rather than constructing it out of some other Lego blocks,鈥 Neyenhuis said.听
A new milestone in quantum volume
Quantum volume tests require running arbitrary circuits. At each slice of the quantum volume circuit, the qubits are randomly paired up and a complex two-qubit operation is performed. This SU(4) gate can be constructed more efficiently using the arbitrary angle two-qubit gate, lowering the error at each step of the algorithm.听
The H1-1鈥檚 quantum volume of 8192 is due in part to the implementation of arbitrary angle gates and the continued reduction in error rates.听夜色直播鈥檚 last quantum volume increase was in April when the System Model H1-2 doubled its performance to become the first commercial quantum computer to pass Quantum Volume 4096.
This new increase is the seventh time in two years that 夜色直播鈥檚 H-Series hardware has set an industry record for measured quantum volume as it continues to achieve its goal of 10X annual improvement.
Quantum volume, a benchmark introduced by IBM in 2019, is a way to measure the performance of a quantum computer using randomized circuits, and is a frequently used metric across the industry.听
Building a quantum ecosystem among developers
夜色直播 has also achieved another milestone: over 500,000 downloads of .
TKET is an advanced software development kit for writing and running programs on gate-based quantum computers. TKET enables developers to optimize their quantum algorithms, reducing the computational resources required, which is important in the NISQ era.听
TKET is open source and accessible through the PyTKET Python package. The SDK also integrates with major quantum software platforms including Qiskit, Cirq and Q#. has been available as an open source language for almost a year.听
This universal availability and TKET鈥檚 portability across many quantum processors are critical for building a community of developers who can write quantum algorithms. The number of downloads includes many companies and academic institutions which account for multiple users.听
夜色直播 CEO Ilyas Khan said, 鈥淲hilst we do not have the exact number of users of TKET, it is clear that we are growing towards a million people around the world who have taken advantage of a critical tool that integrates across multiple platforms and makes those platforms perform better. We continue to be thrilled by the way that TKET helps democratize as well as accelerate innovation in quantum computing.鈥
Arbitrary angle two-qubit gates and other recent 夜色直播 advances are all built into TKET.
鈥淭KET is an evolving platform and continues to take advantage of these new hardware capabilities,鈥 said Dr. Ross Duncan, 夜色直播鈥檚 Head of Quantum Software. 鈥淲e鈥檙e excited to put these new capabilities into the hands of the rapidly increasing number of TKET users around the world.鈥
Additional Data for Quantum Volume 8192
The average single-qubit gate fidelity for this milestone was 99.9959(5)%, the average two-qubit gate fidelity was 99.71(3)% with fully connected qubits, and state preparation and measurement fidelity was 99.72(1)%. The 夜色直播 team ran 220 circuits with 90 shots each, using standard QV optimization techniques to yield an average of 175.2 arbitrary angle two-qubit gates per circuit.
The System Model H1-1 successfully passed the quantum volume 8192 benchmark, outputting heavy outcomes 69.33% of the time, with a 95% confidence interval lower bound of 68.38% which is above the 2/3 threshold.
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.听
Back in 2020, we to increase our Quantum Volume (QV), a measure of computational power, by 10x聽per year.听
Today, we鈥檙e pleased to share that we鈥檝e followed through on our commitment: Our System Model H2 has reached a Quantum Volume of 2虏鲁 = 8,388,608, proving not just that we always do what we say, but that our quantum computers are leading the world forward.听
The QV benchmark was developed by IBM to represent a machine鈥檚 performance, accounting for things like qubit count, coherence times, qubit connectivity, and error rates. :听
鈥渢he higher the Quantum Volume, the higher the potential for exploring solutions to real world problems across industry, government, and research."
Our announcement today is precisely what sets us apart from the competition. No one else has been bold enough to make a similar promise on such a challenging metric 鈥 and no one else has ever completed a five-year goal like this.
We chose QV because we believe it鈥檚 a great metric. For starters, it鈥檚 not gameable, like other metrics in the ecosystem. Also, it brings together all the relevant metrics in the NISQ era for moving towards fault tolerance, such as gate fidelity and connectivity.听
Our path to achieve a QV of over 8 million was led in part by Dr. Charlie Baldwin, who studied under the legendary Ivan H. Deutsch. Dr. Baldwin has made his name as a globally renowned expert in quantum hardware performance over the past decade, and it is because of his leadership that we don鈥檛 just claim to be the best, but that we can prove we are the best.听
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Alongside the world鈥檚 biggest quantum volume, we have the industry鈥檚 . To that point, the table below breaks down the leading commercial specs for each quantum computing architecture.听
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We鈥檝e never shied away from benchmarking our machines, because we know the results will be impressive. It is our provably world-leading performance that has enabled us to demonstrate:
As we look ahead to our next generation system, Helios, 夜色直播鈥檚 Senior Director of Engineering, Dr. Brian Neyenhuis, reflects: 鈥淲e finished our five-year commitment to Quantum Volume ahead of schedule, showing that we can do more than just maintain performance while increasing system size. We can improve performance while scaling.鈥澛
Helios鈥 performance will exceed that of our previous machines, meaning that 夜色直播 will continue to lead in performance while following through on our promises.听
As the undisputed industry leader, we鈥檙e racing against no one other than ourselves to deliver higher performance and to better serve our customers.
At the heart of quantum computing鈥檚 promise lies the ability to solve problems that are fundamentally out of reach for classical computers. One of the most powerful ways to unlock that promise is through a novel approach we call Generative Quantum AI, or GenQAI. A key element of this approach is the (GQE).
GenQAI is based on a simple but powerful idea: combine the unique capabilities of quantum hardware with the flexibility and intelligence of AI. By using quantum systems to generate data, and then using AI to learn from and guide the generation of more data, we can create a powerful feedback loop that enables breakthroughs in diverse fields.
Unlike classical systems, our quantum processing unit (QPU) produces data that is extremely difficult, if not impossible, to generate classically. That gives us a unique edge: we鈥檙e not just feeding an AI more text from the internet; we鈥檙e giving it new and valuable data that can鈥檛 be obtained anywhere else.
The Search for Ground State Energy
One of the most compelling challenges in quantum chemistry and materials science is computing the properties of a molecule鈥檚 ground state. For any given molecule or material, the ground state is its lowest energy configuration. Understanding this state is essential for understanding molecular behavior and designing new drugs or materials.
The problem is that accurately computing this state for anything but the simplest systems is incredibly complicated. You cannot even do it by brute force鈥攖esting every possible state and measuring its energy鈥攂ecause 聽the number of quantum states grows as a double-exponential, making this an ineffective solution. This illustrates the need for an intelligent way to search for the ground state energy and other molecular properties.
That鈥檚 where GQE comes in. GQE is a methodology that uses data from our quantum computers to train a transformer. The transformer then proposes promising trial quantum circuits; ones likely to prepare states with low energy. You can think of it as an AI-guided search engine for ground states. The novelty is in how our transformer is trained from scratch using data generated on our hardware.
Here's how it works:
- We start with a batch of trial quantum circuits, which are run on our QPU.
- Each circuit prepares a quantum state, and we measure the energy of that state with respect to the Hamiltonian for each one.
- Those measurements are then fed back into a transformer model (the same architecture behind models like GPT-2) to improve its outputs.
- The transformer generates a new distribution of circuits, biased toward ones that are more likely to find lower energy states.
- We sample a new batch from the distribution, run them on the QPU, and repeat.
- The system learns over time, narrowing in on the true ground state.
To test our system, we tackled a benchmark problem: finding the ground state energy of the hydrogen molecule (H鈧). This is a problem with a known solution, which allows us to verify that our setup works as intended. As a result, our GQE system successfully found the ground state to within chemical accuracy.
To our knowledge, we鈥檙e the first to solve this problem using a combination of a QPU and a transformer, marking the beginning of a new era in computational chemistry.
The Future of Quantum Chemistry
The idea of using a generative model guided by quantum measurements can be extended to a whole class of problems鈥攆rom to materials discovery, and potentially, even drug design.
By combining the power of quantum computing and AI we can unlock their unified full power. Our quantum processors can generate rich data that was previously unobtainable. Then, an AI can learn from that data. Together, they can tackle problems neither could solve alone.
This is just the beginning. We鈥檙e already looking at applying GQE to more complex molecules鈥攐nes that can鈥檛 currently be solved with existing methods, and we鈥檙e exploring how this methodology could be extended to real-world use cases. This opens many new doors in chemistry, and we are excited to see what comes next.
Last year, we joined forces with RIKEN, Japan's largest comprehensive research institution, to install our hardware at RIKEN鈥檚 campus in Wako, Saitama. This deployment is part of RIKEN鈥檚 project to build a quantum-HPC hybrid platform consisting of high-performance computing systems, such as the supercomputer Fugaku and 夜色直播 Systems. 聽
Today, marks the first of many breakthroughs coming from this international supercomputing partnership. The team from RIKEN and 夜色直播 joined up with researchers from Keio University to show that quantum information can be delocalized (scrambled) using a quantum circuit modeled after periodically driven systems. 聽
"Scrambling" of quantum information happens in many quantum systems, from those found in complex materials to black holes. 聽Understanding information scrambling will help researchers better understand things like thermalization and chaos, both of which have wide reaching implications.
To visualize scrambling, imagine a set of particles (say bits in a memory), where one particle holds specific information that you want to know. As time marches on, the quantum information will spread out across the other bits, making it harder and harder to recover the original information from local (few-bit) measurements.
While many classical techniques exist for studying complex scrambling dynamics, quantum computing has been known as a promising tool for these types of studies, due to its inherently quantum nature and ease with implementing quantum elements like entanglement. The joint team proved that to be true with their latest result, which shows that not only can scrambling states be generated on a quantum computer, but that they behave as expected and are ripe for further study.
Thanks to this new understanding, we now know that the preparation, verification, and application of a scrambling state, a key quantum information state, can be consistently realized using currently available quantum computers. Read the paper , and read more about our partnership with RIKEN here. 聽