New scheme for correcting quantum errors

Environmental factors called decoherences lead to random rotation of qubits. For example, the central qubit is rotated in the middle figure, which represents a quantum error. The task of QEC diagrams is to detect and correct these errors so that the qubits can be returned to their original state. Credit: Sangkha Borah, OIST

Quantum computers hold huge promise in our world of big data. If researchers can harness their potential, these devices can perform complex calculations on a large scale at lightning speed.

Classical computers like 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 0 and 1 at the same time, which is what gives them their power. With the increase in the number of bits stored in a quantum computer, this computer can process information faster than a conventional computer.

But there is a downside. Qubits are fragile. Their states change very quickly, for example in response to environmental factors Like temperature, causing a lot of errors. Researchers have struggled to develop an effective way to correct these errors in real time. Methods for correcting such quantum errors are known as Quantum Error Correction (QEC) Charts.

“For Quantitative StatisticsThese errors are really problematic, says Dr. Sangka Bora, 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 may have usable quantum computers very soon.”

Now, Dr. Bora and 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 method, recently published in Physical Review Research.

MBE-CQEC: A new scheme for quantum error correction

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

The QEC investigation involves performing an array of multiple qubits using a property of quantum mechanics called entanglement. To detect errors that occur in qubits, the QEC scheme must apply a series of measurements known as symmetry measurements. These measurements assess whether two of the nearest neighboring qubits are aligned in the same direction. The results of these measurements are called synapses, and based on them, the error in qubits can be detected and later corrected.

Commonly used QEC schemas are usually slow and result in rapid loss of information stored in qubits due to errors that they fail to detect and correct in real time. In addition, QEC methods use a traditional quantum measurement method called projective quantification to obtain symmetries. This method requires several additional qubits, which makes it very resource intensive.

Instead, Dr. Bora and colleagues used an approach called continuous scaling. Such measurements can be made much more quickly than traditional projective measurements in a highly resource-efficient manner. They developed a QEC scheme called the Quantum Continuous Measurement-Based Estimation scheme Error Correction (MBE-CQEC), which can quickly and efficiently detect and correct errors from noisy partial syndrome measurements. They set up a powerful classical computer to act as an external controller (or estimator) that estimates errors in a quantum system, filters out noise perfectly, and applies feedback to correct them.

Dr. Bora explains that the new QEC scheme is based on a theoretical model that still needs to be validated experimentally on a quantum computer. Also, it has important limitations: as the number of qubit In the system, the real-time simulation of the estimator becomes significantly slower.

“We are working on it, and we hope that others in the field will take over the problem as well,” concluded Dr. Bora.

Adding logical qubits to a Sycamore quantum computer reduces the error rate

more information:
Sangkha Borah et al, Scheme of Measurement-Based Estimation for Continuous Quantitative Error Correction, Physical Review Research (2022). DOI: 10.1103/ PhysRevResearch.4.033207

the quote: MBE-CQEC: New Quantitative Error Correction Scheme (2022, September 15) Retrieved September 15, 2022 from

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