IonQ and U of Maryland Researchers Demonstrate Fault-Tolerant Quantum Error Correction

October 11, 2021

COLLEGE PARK, Md., Oct. 11, 2021 — Researchers from The University of Maryland and IonQ, Inc. (“IonQ”), a leader in trapped-ion quantum computing, on Monday published results in the journal Nature that show a significant breakthrough in error correction technology for quantum computers. In collaboration with scientists from Duke University and the Georgia Institute of Technology, this work demonstrates for the first time how quantum computers can overcome quantum computing errors, a key technical obstacle to large-scale use cases like financial market prediction or drug discovery.

Quantum computers suffer from errors when qubits encounter environmental interference. Quantum error correction works by combining multiple qubits together to form a “logical qubit” that more securely stores quantum information. But storing information by itself is not enough; quantum algorithms also need to access and manipulate the information. To interact with information in a logical qubit without creating more errors, the logical qubit needs to be “fault-tolerant.”

The study, completed at the University of Maryland, peer-reviewed, and published in the journal Nature, demonstrates how trapped ion systems like IonQ’s can soon deploy fault-tolerant logical qubits to overcome the problem of error correction at scale. By successfully creating the first “fault-tolerant logical qubit” — a qubit that is resilient to a failure in any one component — the team has laid the foundation for quantum computers that are both reliable and large enough for practical uses such as risk modeling or shipping route optimization. The team demonstrated that this could be achieved with minimal overhead, requiring only nine physical qubits to encode one logical qubit. This will allow IonQ to apply error correction only when needed, in the amount needed, while minimizing qubit cost.

“This is about significantly reducing the overhead in computational power that is typically required for error correction in quantum computers,” said Peter Chapman, President and CEO of IonQ. “If a computer spends all its time and power correcting errors, that’s not a useful computer. What this paper shows is how the trapped ion approach used in IonQ systems can leapfrog others to fault tolerance by taking small, unreliable parts and turning them into a very reliable device. Competitors are likely to need orders of magnitude more qubits to achieve similar error correction results.”

Behind today’s study are recently graduated UMD PhD students and current IonQ quantum engineers, Laird Egan and Daiwei Zhu, IonQ cofounder Chris Monroe as well as IonQ technical advisor and Duke Professor Ken Brown. Coauthors of the paper include: UMD and Joint Quantum Institute (JQI) research scientist Marko Cetina; postdoctoral researcher Crystal Noel; graduate students Andrew Risinger and Debopriyo Biswas; Duke University graduate student Dripto M. Debroy and postdoctoral researcher Michael Newman; and Georgia Institute of Technology graduate student Muyuan Li.

The news follows on the heels of other significant technological developments from IonQ. The company recently demonstrated the industry’s first Reconfigurable Multicore Quantum Architecture (RMQA) technology, which can dynamically configure 4 chains of 16 ions into quantum computing cores. The company also recently debuted patent-pending evaporated glass traps: technology that lays the foundation for continual improvements to IonQ’s hardware and supports a significant increase in the number of ions that can be trapped in IonQ’s quantum computers. Furthermore, it recently became the first quantum computer company whose systems are available for use via all major cloud providers. Last week, IonQ also became the first publicly-traded, pure-play quantum computing company.

About IonQ

IonQ, Inc. is a leader in quantum computing, with a proven track record of innovation and deployment. IonQ’s next-generation quantum computer is the world’s most powerful trapped-ion quantum computer, and IonQ has defined what it believes is the best path forward to scale. IonQ is the only company with its quantum systems available through the cloud on Amazon Braket, Microsoft Azure, and Google Cloud, as well as through direct API access. IonQ was founded in 2015 by Christopher Monroe and Jungsang Kim based on 25 years of pioneering research. To learn more, visit www.ionq.com.

About the University of Maryland

The University of Maryland, College Park is the state’s flagship university and one of the nation’s preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 40,000 students,10,000 faculty and staff, and 297 academic programs. As one of the nation’s top producers of Fulbright scholars, its faculty includes two Nobel laureates, three Pulitzer Prize winners and 58 members of the national academies. The institution has a $2.2 billion operating budget and secures more than $1 billion annually in research funding together with the University of Maryland, Baltimore. For more information about the University of Maryland, College Park, visit www.umd.edu.


Source: IonQ, Inc.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

Nvidia Appoints Andy Grant as EMEA Director of Supercomputing, Higher Education, and AI

March 22, 2024

Nvidia recently appointed Andy Grant as Director, Supercomputing, Higher Education, and AI for Europe, the Middle East, and Africa (EMEA). With over 25 years of high-performance computing (HPC) experience, Grant brings a Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire