Researchers Propose New Quantum Error Correction Technique

September 15, 2022

Sept. 15, 2022 — Quantum computers hold enormous promise in our big data world. If researchers can harness their potential, these devices could perform massively complex computations at lightning speed.

This schematic shows how the MBE-CQEC scheme works for three qubits. Qubits in a quantum computer (left) are continuously measured by an estimator (right), which is run by a classical computer. The estimator detects errors by making syndrome measurements, then corrects them with appropriate feedback. Credit: Sangkha Borah, OIST.

Classical computers such as our laptops store information in bits, which exist in one of two physical states: 0 or 1. But qubits, the equivalent form of data storage for quantum computers, work differently because their nature is probabilistic rather than deterministic. They can exist as both 0 and 1 simultaneously, which is what gives them their power. As the number of qubits stored in a quantum computer increases, that computer can process information exponentially faster than a classical computer.

But there is a downside. Qubits are fragile. Their states change very quickly, for example in response to environmental factors such as temperature, introducing a lot of errors. Researchers have struggled to develop an efficient way to correct these errors in real-time. The methods to correct such quantum errors are known as quantum error correction (QEC) schemes.

“For quantum computing, these errors are really an issue,” says Dr. Sangkha Borah, a postdoctoral researcher in the Quantum Machines Unit led by Professor Jason Twamley at the Okinawa Institute of Science and Technology (OIST). “If we can figure out how to accurately perform QEC, we might have usable quantum computers very soon.”

Now, Dr. Borah and his colleagues at OIST, and their collaborators at Trinity College in Dublin, Ireland, and the University of Queensland in Brisbane, Australia, have proposed a new error correction technique, which has recently been published in Physical Review Research.

Achieving QEC involves making a collection of multiple qubits using a quantum mechanical property called entanglement. To detect errors happening in the qubits, a QEC scheme must apply a series of measurements known as syndrome measurements. These measurements assess whether two nearest neighbour qubits are aligned in the same direction or not. The results of these measurements are called syndromes, and based them, the error in the qubits can be detected and subsequently corrected.

Commonly used QEC schemes are usually slow, and they also result in a rapid loss of information stored in the qubits due to errors they fail to catch and correct in real time. Additionally, such QEC methods employ a conventional quantum measurement approach called projective measurement to get the syndromes. This approach requires several additional qubits, making it resource-intensive.

Environmental factors – called decoherences – lead to random rotations of the qubits. For example, the central qubit is rotated in the middle figure, representing a quantum error. The task of QEC schemes is to detect and correct such errors so the qubits can be returned to their original states. Credit: Sangkha Borah, OIST.

Instead, Dr. Borah and his colleagues used an approach called continuous measurement. Such measurements can be carried out much more rapidly than conventional projective measurements in a highly resource-efficient way. They developed a QEC scheme called measurement-based estimator scheme for continuous quantum error correction (MBE-CQEC), which could quickly and efficiently detect and correct errors from partial, noisy syndrome measurements. They set up a powerful classical computer to act as an outside controller (or estimator) that estimates errors in the quantum system, filters out the noise perfectly, and applies feedback to correct them.

The new QEC scheme is based on a theoretical model that still needs to be validated experimentally on a quantum computer, Dr. Borah explains. Also, it has an important limitation: As the number of qubits in the system increases, real-time simulation of the estimator becomes exponentially slower.

“We are working on it, and we hope others in the field will also take up the problem,” Dr. Borah concluded.


Source: Alla Katsnelson, Okinawa Institute of Science and Technology

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!

Intel’s Silicon Brain System a Blueprint for Future AI Computing Architectures

April 24, 2024

Intel is releasing a whole arsenal of AI chips and systems hoping something will stick in the market. Its latest entry is a neuromorphic system called Hala Point. The system includes Intel's research chip called Loihi 2, Read more…

Anders Dam Jensen on HPC Sovereignty, Sustainability, and JU Progress

April 23, 2024

The recent 2024 EuroHPC Summit meeting took place in Antwerp, with attendance substantially up since 2023 to 750 participants. HPCwire asked Intersect360 Research senior analyst Steve Conway, who closely tracks HPC, AI, Read more…

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, and this day of contemplation is meant to provide all of us Read more…

Intel Announces Hala Point – World’s Largest Neuromorphic System for Sustainable AI

April 22, 2024

As we find ourselves on the brink of a technological revolution, the need for efficient and sustainable computing solutions has never been more critical.  A computer system that can mimic the way humans process and s Read more…

Empowering High-Performance Computing for Artificial Intelligence

April 19, 2024

Artificial intelligence (AI) presents some of the most challenging demands in information technology, especially concerning computing power and data movement. As a result of these challenges, high-performance computing Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

Intel’s Silicon Brain System a Blueprint for Future AI Computing Architectures

April 24, 2024

Intel is releasing a whole arsenal of AI chips and systems hoping something will stick in the market. Its latest entry is a neuromorphic system called Hala Poin Read more…

Anders Dam Jensen on HPC Sovereignty, Sustainability, and JU Progress

April 23, 2024

The recent 2024 EuroHPC Summit meeting took place in Antwerp, with attendance substantially up since 2023 to 750 participants. HPCwire asked Intersect360 Resear Read more…

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips 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…

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…

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…

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…

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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

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…

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…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

Intel’s Xeon General Manager Talks about Server Chips 

January 2, 2024

Intel is talking data-center growth and is done digging graves for its dead enterprise products, including GPUs, storage, and networking products, which fell to Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire