Major quantum computing breakthroughs are making headlines, with the announcement of Google Willow earlier this month and expectations that the technology could become more widely used over the coming years.
Google's quantum chip, Willow, completed a mathematical problem designed to test its problem-solving potential in less than five minutes—something a traditional supercomputer could not complete in 10 septillion years.
Many experts are confident that quantum computing may revolutionize industries by tackling problems that traditional computers cannot solve. USC scientists are available to talk about the technology and where it is headed.
Contact: Will Kwong at willkwon@usc.edu; USC Media Relations at uscnews@usc.edu or (213) 740-2215
Quantum's roadblock: error correction
"One of my areas of focus in quantum computing is `quantum algorithmic speedup,' the milestone where a quantum computer can solve problems with an advantage relative to even the most powerful non-quantum computer, and that advantage grows as the problem gets harder," says Daniel Lidar, holder of the Viterbi Professorship of engineering and professor of electrical and computer engineering, chemistry, and physics and astronomy at USC Viterbi School of Engineering.
“Error correction is essential for quantum computers to function well and become useful. Errors occur when a quantum system interacts with its external environment and loses it delicate quantum characteristics. It's the biggest challenge quantum computing faces."
"Google's new experimental results using their quantum computer chip, Willow, is a significant advance. They have demonstrated that quantum error correction works as theoreticians have predicted: as they made their error-corrected `logical qubit’ larger, the results improved. Previously, in most cases, errors only increased.”
Areas of expertise: quantum algorithms, quantum advantage, experimental quantum machines, error correction and academic labs
Contact: willkwon@usc.edu
Outlooks on quantum computing
“The quantum computers we have today are still hampered by their extreme sensitivity to errors and the unavoidable noise present in any physical system. For the whole field of quantum computing to advance, we need to be able to manage this hindrance," says Federico Spedalieri, research assistant professor of electrical and computer engineering at USC Viterbi School of Engineering, and managing director of the quantum initiative at USC Viterbi's Information Sciences Institute.
"Google's Willow processor has shown that we can indeed engineer the building blocks that would allow us to tame this noise and unleash the revolutionary computational power that quantum computers can bring.”
Area of expertise: quantum annealing
Contact: willkwon@usc.edu
The difference between quantum computing and traditional computing
"In simple terms, the algorithms used in quantum computing are different than traditional computers due to optimizing specialized computational methods that can leverage the unique properties of quantum mechanics to solve complex problems classical computers can't," says Eli Levinson-Falk, assistant professor of physics and astronomy and electrical and computer engineering at USC Dornsife College of Letters, Arts and Sciences.
"Quantum algorithms utilize quantum bits (qubits), which are the fundamental units of information in quantum computing. An everyday computer has bits that can only be 0 or 1, while a qubit can exist in multiple states simultaneously; this unique condition can lead to exponentially more computational power."
"What's so exciting about Google's new experimental machine (Willow) is it was able to scale up to more and more qubits while keeping each individual qubit working well. By solving all sorts of tough engineering challenges they were able to make a large processor that functioned well enough to run an error correction algorithm. The big result is that they had error correction running well enough to really improve the performance of the device as a whole, and they showed that the more qubits they included in the algorithm, the better it ran. As long as they can keep scaling to larger processors without making the individual qubits worse, they should be able to continue to improve performance."
Areas of expertise: intro to quantum computing, qubits, quantum hardware and quantum mechanics
Contact: elevenso@usc.edu
Potential quantum application: computational biology
“As of now, the technology of quantum computing has too many errors to have everyday practical applications in the field of computational biology,” says Rosa Di Felice, professor of physics, astronomy, and quantitative and computational biology at USC Dornsife College of Letters, Arts and Sciences.
“I identify areas where quantum computing can potentially transform computational biology. For example, the quantification of energy properties in the chemical reactions in biomolecules and cells is currently almost impossible. The problem is intrinsically a quantum mechanical problem that would naturally benefit from the use of error-corrected quantum algorithms.
“Errors critically undermine the performance of quantum information storage and processing in relation to computational biology. The new Google experimental machine shows promise that a viable solution may be possible.”
Area of expertise: speculative quantum applications in computational biology
Contact: difelice@usc.edu
Further application: Dark matter
“Dark matter is one of the biggest mysteries in the known universe. To understand the exact nature of it will require further research that may be supported by the development of a more powerful quantum processor, potentially solving quantum receiver design problems in quantum sensing," says Quntao Zhuang, assistant professor of electrical and computer engineering and physics and astronomy at USC Viterbi School of Engineering.
"My research is focused on axion dark matter, which refers to the theoretical concept that a hypothetical particle called an 'axion' could be the primary constituent of dark matter in the universe."
Area of expertise: quantum sensing
Contact: willkwon@usc.edu