Researchers at Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed (AQT) demonstrated that an experimental method known as randomized compiling (RC) can dramatically reduce error rates in quantum algorithms and lead to more accurate and stable quantum computations. No longer just a theoretical concept for quantum computing, the multidisciplinary team’s breakthrough experimental results are published in Physical Review X.

The experiments at AQT were performed on a four-qubit superconducting quantum processor. The researchers demonstrated that RC can suppress one of the most severe types of errors in quantum computers: coherent errors.

Akel Hashim, AQT researcher, involved in the experimental breakthrough and a graduate student at the University of California, Berkeley explained: “We can perform quantum computations in this era of noisy intermediate-scale quantum (NISQ) computing, but these are very noisy, prone to errors from many different sources, and don’t last very long due to the decoherence—that is, information loss—of our qubits.”

By Stina Andersson and Ellinor Wanzambi

Researchers have been working on quantum algorithms since physicists first proposed using principles of quantum physics to simulate nature decades. One important component in many quantum algorithms is quantum walks, which are the quantum equivalent of the classical Markov chain, i.e., a random walk without memory. Quantum walks are used in algorithms in areas such as searching, node ranking in networks, and element distinctness.

Consider the graph in Figure 1 and imagine that we randomly want to move between nodes A, B, C, and D in the graph. We can only move between nodes that are connected by an edge, and each edge has an associated probability that decides how likely we are to move to the connected node. This is a random walk. In this article, we are working only with Markov chains, also called the memory-less random walks, meaning that the probabilities are independent of the previous steps. For example, the probabilities of arriving at node A are the same no matter if we got there from node B or node D.

Recent theoretical breakthroughs have settled two long-standing questions about the viability of simulating quantum systems on future quantum computers, overcoming challenges from complexity analyses to enable more advanced algorithms. Featured in two publications, the work by a quantum team at Los Alamos National Laboratory shows that physical properties of quantum systems allow for faster simulation techniques.

“Algorithms based on this work will be needed for the first full-scale demonstration of quantum simulations on quantum computers,” said Rolando Somma, a quantum theorist at Los Alamos and coauthor on the two papers.