Noise: an unexpected ally for quantum computing

Quantum computers are distinguished by the use of quantum bits (qubits) instead of bits. This allows them to store and process much more information at a much faster rate, by taking advantage of quantum properties such as superposition and entanglement. However, there is an important limitation for the full development of these computers: noise (understood as general environmental disturbances).

Noise causes errors to propagate when complex algorithms are executed, thus undermining the promising potential of quantum computing to revolutionize many fields of science and technology.

Teams around the world have been working intensively for years to overcome this barrier, concentrating their efforts mainly on techniques for error correction or mitigation, and on the design of simpler algorithms that adapt to the limitations.

Now, researchers from the Autonomous University of Madrid (UAM) in Spain have given a twist to the question. In a recent study they have found an alternative solution: using noise to improve the results of quantum algorithms.

A new algorithm performs machine learning (a form of artificial intelligence) predictions using quantum systems with random parameters to extract useful information from the studied system. In this way, it can solve a wide variety of problems, such as quantum chemical calculations or time series predictions, as well as help in the discovery of new drugs.

“The idea behind Quantum Reservoir Computing is to use the Hilbert space, where quantum states live, to extract essential properties from the studied data. Thus, using quantum properties such as superposition and entanglement, we can obtain useful information from the data and provide it to a machine learning model, which makes the final prediction”, Laia Domingo and her colleagues detail.

The authors of the new study propose using noise to improve the results of quantum algorithms. In the image, artist’s recreation of two quantum bits. (Illustration: Jorge Munnshe for NCYT from Amazings)

A new perspective on quantum computing

The study concludes that some types of noise, such as the so-called “amplitude damping noise”, improve the quality of Quantum Reservoir Computing results. Therefore, not only is it unnecessary to correct for this type of noise, but it could be beneficial for quantum calculations.

However, other sources of errors, such as “depolarizing noise”, can degrade the results in all cases, so it is essential to prioritize their correction in quantum computers.

The study also provides a theoretical demonstration that helps explain this phenomenon. Through the mathematical formalism of density matrices and quantum channels, the authors of the study illustrate how amplitude damping noise makes it possible to more effectively explore the space of quantum operators. This makes it easier to extract more complex and valuable properties from the data, which are then used to predict the target variable.

In short, the finding made by Laia Domingo’s team offers a new perspective on the physical mechanisms inherent in quantum devices. In addition, it provides solid practical guidelines for a successful implementation of quantum information processing in today’s technology.

The study is titled “Taking advantage of noise in quantum reservoir computing”. And it has been published in the academic journal Scientific Reports, from the Nature group. (Source: UAM)