Quantinuum Sets New Record with Highest Ever Quantum Volume

Simpler, faster and fewer errors: How arbitrary angle gates help increase H1’s quantum volume

September 27, 2022
New arbitrary angle gate capabilities enable increase in Quantum Volume (QV) to 8192 as Quantinuum continues to achieve its previously stated objective of increasing its QV by 10x every year; TKET downloads surpass 500,000
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Quantinuum President and COO Tony Uttley announced three major accomplishments during his keynote address at the IEEE Quantum Week event in Colorado last week. 

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 Quantinuum’s open-sourced TKET, a world-leading quantum software development kit (SDK). 

The announcements were made during Uttley’s keynote address titled, “A Measured Approach to Quantum Computing.”

These advancements are the latest examples of the company’s continued demonstration of its leadership in the quantum computing community. 

“Quantinuum is accelerating quantum computing’s impact to the world,” Uttley said. “We are making significant progress with both our hardware and software, in addition to building a community of developers who are using our TKET SDK.”

This latest quantum volume measurement of 8192 is particularly noteworthy and is the second time this year Quantinuum has published a new QV record on their trapped-ion quantum computing platform, the System Model H1, Powered by Honeywell. 

The plot above shows the growth of measured quantum volume by Quantinuum. For each test, the heavy output probability ‘h’ is listed and the system is identified by the marker type. The dashed grey line shows our target scaling of increasing QV × 10 yearly.

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. 

Dr. Brian Neyenhuis, Director of Commercial Operations at Quantinuum, said, “This 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.”

These arbitrary angle gates build on the overall design strength of the trapped-ion architecture of the H1, Neyenhuis said. 

“With 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’t have to worry about additional crosstalk,” he said. 

This new gate design represents a third method for Quantinuum to improve the efficiency of the H1 generation, said Dr. Jenni Strabley, Senior Director of Offering Management at Quantinuum.

“Quantinuum’s 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’re doing that,” she said. “Now we can also implement the algorithms more efficiently on our H1 with this new gate design.”

A powerful new capability: More information on arbitrary angle gates 

Currently, researchers can do single qubit gates – rotations on a single qubit – or a fully entangling two-qubit gate. It’s 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. 

“There 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,” Neyenhuis said. “Now we can just add this tiny little bit of entanglement natively and then go to the next step of the algorithm.”

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.

“By 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,” Neyenhuis said. 

This is a powerful new capability, particularly for noisy intermediate-scale quantum algorithms. Another demonstration from the Quantinuum team was to use arbitrary angle two-qubit gates to study non-equilibrium phase transitions, the technical details of which are available on the arXiv here

“For 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,” Neyenhuis said. “There 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. 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.”

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. 

“This 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,” Neyenhuis said. 

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. 

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The plot above shows the individual heavy output probability for each circuit in the Quantum Volume 8192 test. The blue line is the cumulative average heavy output probability and the green regions are the cumulative two-sigma confidence interval calculated by the new method.

The H1-1’s quantum volume of 8192 is due in part to the implementation of arbitrary angle gates and the continued reduction in error rates. Quantinuum’s 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 Quantinuum’s 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. 

Building a quantum ecosystem among developers

Quantinuum has also achieved another milestone: over 500,000 downloads of TKET.

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. 

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#. TKET has been available as an open source language for almost a year. 

This universal availability and TKET’s 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. 

Quantinuum CEO Ilyas Khan said, “Whilst 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.”

Arbitrary angle two-qubit gates and other recent Quantinuum advances are all built into TKET.

“TKET is an evolving platform and continues to take advantage of these new hardware capabilities,” said Dr. Ross Duncan, Quantinuum’s Head of Quantum Software. “We’re excited to put these new capabilities into the hands of the rapidly increasing number of TKET users around the world.”

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 Quantinuum 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 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. 

Blog
March 20, 2025
Initiating Impact Today: Combining the World’s Most Powerful in Quantum and Classical Compute
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Quantinuum and NVIDIA, world leaders in their respective sectors, are combining forces to fast-track commercially scalable quantum supercomputers, further bolstering the announcement Quantinuum made earlier this year about the exciting new potential in Generative Quantum AI. 

Make no mistake about it, the global quantum race is on. With over $2 billion raised by companies in 2024 alone, and over 150 new startups in the past five years, quantum computing is no longer restricted to ‘the lab’.  

The United Nations proclaimed 2025 as the International Year of Quantum Science and Technology (IYQ), and as we march toward the end of the first quarter, the old maxim that quantum computing is still a decade (or two, or three) away is no longer relevant in today’s world. Governments, commercial enterprises and scientific organizations all stand to benefit from quantum computers, led by those built by Quantinuum.

That is because, amid the flurry of headlines and social media chatter filled with aspirational statements of future ambitions shared by those in the heat of this race, we at Quantinuum continue to lead by example. We demonstrate what that future looks like today, rather than relying solely on slide deck presentations.

Our quantum computers are the most powerful systems in the world. Our H2 system, the only quantum computer that cannot be classically simulated, is years ahead of any other system being developed today. In the coming months, we’ll introduce our customers to Helios, a trillion times more powerful than H2, further extending our lead beyond where the competition is still only planning to be. 

At Quantinuum, we have been convinced for years that the impact of quantum computers on the real world will happen earlier than anticipated. However, we have known that impact will be when powerful quantum computers and powerful classical systems work together. 

This sort of hybrid ‘supercomputer’ has been referenced a few times in the past few months, and there is, rightly, a sense of excitement about what such an accelerated quantum supercomputer could achieve.

The Power of Hybrid Quantum and Classical Compute

In a revolutionary move on March 18th, 2025, at the GTC AI conference, NVIDIA announced the opening of a world-class accelerated quantum research center with Quantinuum selected as a key founding collaborator to work on projects with NVIDIA at the center. 

With details shared in an accompanying press statement and blog post, the NVIDIA Accelerated Quantum Research Center (NVAQC) being built in Boston, Massachusetts, will integrate quantum computers with AI supercomputers to ultimately explore how to build accelerated quantum supercomputers capable of solving some of the world’s most challenging problems. The center will begin operations later this year.

As shared in Quantinuum’s accompanying statement, the center will draw on the NVIDIA CUDA-Q platform, alongside a NVIDIA GB200 NVL72 system containing 576 NVIDIA Blackwell GPUs dedicated to quantum research. 

The Role of CUDA-Q in Quantum-Classical Integration  

Integrating quantum and classical hardware relies on a platform that can allow researchers and developers to quickly shift context between these two disparate computing paradigms within a single application. NVIDIA CUDA-Q platform will be the entry-point for researchers to exploit the NVAQC quantum-classical integration. 

In 2022, Quantinuum became the first company to bring CUDA-Q to its quantum systems, establishing a pioneering collaboration that continues to today. Users of CUDA-Q are currently offered access to Quantinuum’s System H1 QPU and emulator for 90 days.

Quantinuum’s future systems will continue to support the CUDA-Q platform. Furthermore, Quantinuum and NVIDIA are committed to evolving and improving tools for quantum classical integration to take advantage of the latest hardware features, for example, on our upcoming Helios generation. 

The Gen-Q-AI Moment

A few weeks ago, we disclosed high level details about an AI system that we refer to as Generative Quantum AI, or GenQAI. We highlighted a timeline between now and the end of this year when the first commercial systems that can accelerate both existing AI and quantum computers.

At a high level, an AI system such as GenQAI will be enhanced by access to information that has not previously been accessible. Information that is generated from a quantum computer that cannot be simulated. This information and its effect can be likened to a powerful microscope that brings accuracy and detail to already powerful LLM’s, bridging the gap from today’s impressive accomplishments towards truly impactful outcomes in areas such as biology and healthcare, material discovery and optimization.

Through the integration of the most powerful in quantum and classical systems, and by enabling tighter integration of AI with quantum computing, the NVAQC will be an enabler for the realization of the accelerated quantum supercomputer needed for GenQAI products and their rapid deployment and exploitation.

Innovating our Roadmap

The NVAQC will foster the tools and innovations needed for fully fault-tolerant quantum computing and will be enabler to the roadmap Quantinuum released last year.

With each new generation of our quantum computing hardware and accompanying stack, we continue to scale compute capabilities through more powerful hardware and advanced features, accelerating the timeline for practical applications. To achieve these advances, we integrate the best CPU and GPU technologies alongside our quantum innovations. Our long-standing collaboration with NVIDIA drives these advancements forward and will be further enriched by the NVAQC. 

Here are a couple of examples: 

In quantum error correction, error syndromes detected by measuring "ancilla" qubits are sent to a "decoder." The decoder analyzes this information to determine if any corrections are needed. These complex algorithms must be processed quickly and with low latency, requiring advanced CPU and GPU power to calculate and apply corrections keeping logical qubits error-free. Quantinuum has been collaborating with NVIDIA on the development of customized GPU-based decoders which can be coupled with our upcoming Helios system. 

In our application space, we recently announced the integration of InQuanto v4.0, the latest version of Quantinuum’s cutting edge computational chemistry platform, with NVIDIA cuQuantum SDK to enable previously inaccessible tensor-network-based methods for large-scale and high-precision quantum chemistry simulations.

Our work with NVIDIA underscores the partnership between quantum computers and classical processors to maximize the speed toward scaled quantum computers. These systems offer error-corrected qubits for operations that accelerate scientific discovery across a wide range of fields, including drug discovery and delivery, financial market applications, and essential condensed matter physics, such as high-temperature superconductivity.

We look forward to sharing details with our partners and bringing meaningful scientific discovery to generate economic growth and sustainable development for all of humankind.

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March 18, 2025
Setting the Benchmark: Independent Study Ranks Quantinuum #1 in Performance

By Dr. Chris Langer

In the rapidly advancing world of quantum computing, to be a leader means not just keeping pace with innovation but driving it forward. It means setting new standards that shape the future of quantum computing performance. A recent independent study comparing 19 quantum processing units (QPUs) on the market today has validated what we’ve long known to be true: Quantinuum’s systems are the undisputed leaders in performance.

The Benchmarking Study

A comprehensive study conducted by a joint team from the Jülich Supercomputing Centre, AIDAS, RWTH Aachen University, and Purdue University compared QPUs from leading companies like IBM, Rigetti, and IonQ, evaluating how well each executed the Quantum Approximate Optimization Algorithm (QAOA), a widely used algorithm that provides a system level measure of performance. After thorough examination, the study concluded that:

“...the performance of quantinuum H1-1 and H2-1 is superior to that of the other QPUs.”

Quantinuum emerged as the clear leader, particularly in full connectivity, the most critical category for solving real-world optimization problems. Full connectivity is a huge comparative advantage, offering more computational power and more flexibility in both error correction and algorithmic design. Our dominance in full connectivity—unattainable for platforms with natively limited connectivity—underscores why we are the partner of choice in quantum computing.

Leading Across the Board

We take benchmarking seriously at Quantinuum. We lead in nearly every industry benchmark, from best-in-class gate fidelities to a 4000x lead in quantum volume, delivering top performance to our customers.

Our Quantum Charged-coupled Device (QCCD) architecture has been the foundation of our success, delivering consistent performance gains year-over-year. Unlike other architectures, QCCD offers all-to-all connectivity, world-record fidelities, and advanced features like real-time decoding. Altogether, it’s clear we have superior performance metrics across the board.

While many claim to be the best, we have the data to prove it. This table breaks down industry benchmarks, using the leading commercial spec for each quantum computing architecture.

TABLE 1. Leading commercial spec for each listed architecture or demonstrated capabilities on commercial hardware. Download Benchmarking Results

These metrics are the key to our success. They demonstrate why Quantinuum is the only company delivering meaningful results to customers at a scale beyond classical simulation limits.

Our progress builds upon a series of Quantinuum’s technology breakthroughs, including the creation of the most reliable and highest-quality logical qubits, as well as solving the key scalability challenge associated with ion-trap quantum computers — culminating in a commercial system with greater than 99.9% two-qubit gate fidelity.

From our groundbreaking progress with System Model H2 to advances in quantum teleportation and solving the wiring problem, we’re taking major steps to tackle the challenges our whole industry faces, like execution speed and circuit depth. Advancements in parallel gate execution, faster ion transport, and high-rate quantum error correction (QEC) are just a few ways we’re maintaining our lead far ahead of the competition.

This commitment to excellence ensures that we not only meet but exceed expectations, setting the bar for reliability, innovation, and transformative quantum solutions. 

Onward and Upward

To bring it back to the opening message: to be a leader means not just keeping pace with innovation but driving it forward. It means setting new standards that shape the future of quantum computing performance.

We are just months away from launching Quantinuum’s next generation system, Helios, which will be one trillion times more powerful than H2. By 2027, Quantinuum will launch the industry’s first 100-logical-qubit system, featuring best-in-class error rates, and we are on track to deliver fault-tolerant computation on hundreds of logical qubits by the end of the decade. 

The evidence speaks for itself: Quantinuum is setting the standard in quantum computing. Our unrivaled specs, proven performance, and commitment to innovation make us the partner of choice for those serious about unlocking value with quantum computing. Quantinuum is committed to doing the hard work required to continue setting the standard and delivering on our promises. This is Quantinuum. This is leadership.

Dr. Chris Langer is a Fellow, a key inventor and architect for the Quantinuum hardware, and serves as an advisor to the CEO.

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Citations from Benchmarking Table
1 Quantinuum. System Model H2. Quantinuum, https://www.quantinuum.com/products-solutions/quantinuum-systems/system-model-h2
2 IBM. Quantum Services & Resources. IBM Quantum, https://quantum.ibm.com/services/resources
3 Quantinuum. System Model H1. Quantinuum, https://www.quantinuum.com/products-solutions/quantinuum-systems/system-model-h1
4 Google Quantum AI. Willow Spec Sheet. Google, https://quantumai.google/static/site-assets/downloads/willow-spec-sheet.pdf
5 Sales Rodriguez, P., et al. "Experimental demonstration of logical magic state distillation." arXiv, 19 Dec 2024, https://arxiv.org/pdf/2412.15165
6 Quantinuum. H1 Product Data Sheet. Quantinuum, https://docs.quantinuum.com/systems/data_sheets/Quantinuum%20H1%20Product%20Data%20Sheet.pdf
7 Google Quantum AI. Willow Spec Sheet. Google, https://quantumai.google/static/site-assets/downloads/willow-spec-sheet.pdf
8 Sales Rodriguez, P., et al. "Experimental demonstration of logical magic state distillation." arXiv, 19 Dec 2024, https://arxiv.org/pdf/2412.15165
9 Quantinuum. H2 Product Data Sheet. Quantinuum, https://docs.quantinuum.com/systems/data_sQuantinuum. H2 Product Data Sheet. Quantinuum,heets/Quantinuum%20H2%20Product%20Data%20Sheet.pdf
10 Google Quantum AI. Willow Spec Sheet. Google, https://quantumai.google/static/site-assets/downloads/willow-spec-sheet.pdf
11 Sales Rodriguez, P., et al. "Experimental demonstration of logical magic state distillation." arXiv, 19 Dec 2024, https://arxiv.org/pdf/2412.15165
12 Moses, S. A., et al. "A Race-Track Trapped-Ion Quantum Processor." Physical Review X, vol. 13, no. 4, 2023, https://journals.aps.org/prx/pdf/10.1103/PhysRevX.13.041052
13 Google Quantum AI and Collaborators. "Quantum Error Correction Below the Surface Code Threshold." Nature, vol. 638, 2024, https://www.nature.com/articles/s41586-024-08449-y
14 Bluvstein, Dolev, et al. "Logical Quantum Processor Based on Reconfigurable Atom Arrays." Nature, vol. 626, 2023, https://www.nature.com/articles/s41586-023-06927-3
15 DeCross, Matthew, et al. "The Computational Power of Random Quantum Circuits in Arbitrary Geometries." arXiv, Published on 21 June 2024, hhttps://arxiv.org/pdf/2406.02501
16 Montanez-Barrera, J. A., et al. "Evaluating the Performance of Quantum Process Units at Large Width and Depth." arXiv, 10 Feb. 2025, https://arxiv.org/pdf/2502.06471
17 Evered, Simon J., et al. "High-Fidelity Parallel Entangling Gates on a Neutral-Atom Quantum Computer." Nature, vol. 622, 2023, https://www.nature.com/articles/s41586-023-06481-y
18 Ryan-Anderson, C., et al. "Realization of Real-Time Fault-Tolerant Quantum Error Correction." Physical Review X, vol. 11, no. 4, 2021, https://journals.aps.org/prx/abstract/10.1103/PhysRevX.11.041058
19 Carrera Vazquez, Almudena, et al. "Scaling Quantum Computing with Dynamic Circuits." arXiv, 27 Feb. 2024, https://arxiv.org/html/2402.17833v1
20 Moses, S.A.,, et al. "A Race Track Trapped-Ion Quantum Processor." arXiv, 16 May 2023, https://arxiv.org/pdf/2305.03828
21 Garcia Almeida, D., Ferris, K., Knanazawa, N., Johnson, B., Davis, R. "New fractional gates reduce circuit depth for utility-scale workloads." IBM Quantum Blog, IBM, 18 Nov. 2020, https://www.ibm.com/quantum/blog/fractional-gates
22 Ryan-Anderson, C., et al. "Realization of Real-Time Fault-Tolerant Quantum Error Correction." arXiv, 15 July 2021, https://arxiv.org/pdf/2107.07505
23 Google Quantum AI and Collaborators. “Quantum error correction below the surface code threshold.” arXiv, 24 Aug. 2024, https://arxiv.org/pdf/2408.13687v1
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Blog
March 16, 2025
APS Global Physics Summit 2025

The 2025 Joint March Meeting and April Meeting — referred to as the APS Global Physics Summit — is the largest physics research conference in the world, uniting 14,000 scientific community members across all disciplines of physics.  

The Quantinuum team is looking forward to participating in this year’s conference to showcase our latest advancements in quantum technology. Find us throughout the week at the below sessions and visit us at Booth 1001.

Join these sessions to discover how Quantinuum is advancing quantum computing

T11: Quantum Error Correction
Speaker: Natalie Brown
Date: Sunday, March 16th
Time: 8:00 – 8:12am
Location: Anaheim Convention Center, 261B (Level 2)

The computational power of random quantum circuits in arbitrary geometries
Session MAR-F34: Near-Term Quantum Resource Reduction and Random Circuits

Speaker: Matthew DeCross
Date: Tuesday, March 18th
Time: 8:00 – 8:12am
Location: Anaheim Convention Center, 256A (Level 2)

Topological Order from Measurements and Feed-Forward on a Trapped Ion Quantum Computer
Session MAR-F14: Realizing Topological States on Quantum Hardware

Speaker: Henrik Dreyer
Date: Tuesday, March 18th
Time: 9:12 – 9:48am
Location: Anaheim Convention Center, 158 (Level 1)

Trotter error time scaling separation via commutant decomposition
Session MAR-F34: Near-Term Quantum Resource Reduction and Random Circuits
Speaker: Yi-Hsiang Chen (Quantinuum)
Date: Tuesday, March 18th
Time: 10:00 – 10:12am
Location: Anaheim Convention Center, 256A (Level 2)

Squared overlap calculations with linear combination of unitaries
Session MAR-J35: Circuit Optimization and Compilation

Speaker: Michelle Wynne Sze
Date: Tuesday, March 18th
Time: 4:36 – 4:48pm
Location: Anaheim Convention Center, 256B (Level 2)

High-precision quantum phase estimation on a trapped-ion quantum computer
Session MAR-L16: Quantum Simulation for Quantum Chemistry

Speaker: Andrew Tranter
Date: Wednesday, March 19th
Time: 9:48 – 10:00am
Location: Anaheim Convention Center, 160 (Level 1)

Robustness of near-thermal dynamics on digital quantum computers
Session MAR-L16: Quantum Simulation for Quantum Chemistry

Speaker: Eli Chertkov
Date: Wednesday, March 19th
Time: 10:12 – 10:24am
Location: Anaheim Convention Center, 160 (Level 1)

Floquet prethermalization on a digital quantum computer
Session MAR-Q09: Quantum Simulation of Condensed Matter Physics

Speaker: Reza Haghshenas
Date: Thursday, March 20th
Time: 10:00 – 10:12am
Location: Anaheim Convention Center, 204C (Level 2)

Teleportation of a Logical Qubit on a Trapped-ion Quantum Computer
Session MAR-S11: Advances in QEC Experiments

Speaker: Ciaran Ryan-Anderson
Date: Thursday, March 20th
Time: 11:30 – 12:06pm
Location: Anaheim Convention Center, 155 (Level 1)

*All times in Pacific Standard Time

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