Quantum computers have yet to yield a machine that can kick off the promised revolution in computing, but researchers are making progress and becoming more optimistic about their potential applications. Quantum computers store data in quantum bits, or qubits, and perform computations that are practically impossible using classical computers. Nature has created a brief review of Quantum Computing, including some of the problems and, some might say, hype around the sector.
However, useful computations require many qubits, which do not yet exist. Despite the challenges, researchers are finding ways to make quantum algorithms more efficient and reduce errors in quantum computers. Some companies are even promising useful commercial applications in the near-future, such as in drug development and discovery.
Introduction
Researchers at Universal Quantum, a UK-based start-up, are working with engineering firm Rolls-Royce to build a large-scale, modular quantum computer. Quantum computers have the potential to revolutionize fields such as drug discovery, encryption, and machine learning. Despite the challenges in building quantum hardware, researchers are progressing in reducing errors and improving efficiency. Companies like Algorithmiq and Riverlane are optimistic about the near-future applications of quantum computing in drug development and materials science.
Quantum Computing Progress and Potential
Quantum computers have been developing for decades, but they have yet to deliver on their promise of revolutionizing computing. However, researchers are optimistic about the progress and potential applications of quantum computing. Jeannette Garcia, senior research manager for quantum applications and software at IBM, says that the field is surprising itself with how much has been accomplished.
Quantum computers have the potential to accelerate drug discovery, crack encryption, speed up financial transactions, improve machine learning, develop revolutionary materials, and even address climate change. Computational mathematician Steve Brierley believes that the quantum sweet spot could be more spectacular than anything we can imagine today as long as the field is given the necessary time.
“People do understand that this is a long-term play.”
Steve Brierley, founder and chief executive of quantum-computing firm Riverlane in Cambridge, UK.
Challenges in Quantum Computing
One of the main challenges in quantum computing is building the hardware itself. Quantum computers store data in quantum binary digits called qubits, which can be made using various technologies. Some require cooling to near absolute zero, while others operate at room temperature. Researchers have yet to agree on how the performance of quantum computers should be measured.
Another challenge is achieving practical computations on quantum machines with many qubits, which do not yet exist. Qubits and their interactions must also be robust against errors introduced through various noise sources. These disturbances can cause the information to leak out of the processor, a situation known as decoherence, which can require dedicating a large proportion of qubits to error-correction routines.
Optimism and Breakthroughs in Quantum Computing
Despite the challenges, researchers are optimistic about the future of quantum computing. For example, Michael Beverland at Microsoft Quantum believes that some obstacles facing quantum chemistry calculations can be overcome through hardware breakthroughs. Nicole Holzmann at Riverlane and her colleagues have shown that quantum algorithms can be made radically more efficient, cutting the theoretical runtime of specific calculations from over 1,000 years to just a few days.
IBM’s Jeannette Garcia and her team have also made gains in quantum computing by reducing errors and improving efficiency. They have successfully performed quantum simulations of the sulfonium ion, which could enhance lithography techniques for semiconductor manufacturing and revolutionize drug design.
Near-Term Applications of Quantum Computing
Some companies are optimistic about the near-term commercial applications of quantum computing. Helsinki-based start-up Algorithmiq, for example, expects to demonstrate practical quantum advances in drug development and discovery within five years. Potential near-term applications include financial risk management, materials science, and logistics optimization.
Quantum Machine Learning and Future Possibilities
“I’m not trying to take away from how much work there is to do, but we’re surprising ourselves about how much we’ve done,”
Jeannette Garcia, senior research manager for quantum applications and software at technology giant IBM in San Jose, California.
One of the more speculative long-term applications of quantum computing is quantum machine learning. Quantum versions of machine learning algorithms could require fewer parameters and much less training data due to the vast range of different states available to quantum particles. Researchers at Duke University and IonQ have developed quantum machine-learning algorithms that can distinguish between road signs in laboratory tests with significantly fewer parameters and training iterations than classical neural networks.
While quantum machine learning cannot outperform classical algorithms, there is room for exploration and development. As quantum computing advances, researchers focus on building a quantum-skilled workforce and validating the performance of quantum algorithms and machines against classical computers.
“The short-term hype is a bit high,” says Brierley, who is the founder and chief executive of quantum-computing firm Riverlane in Cambridge, UK. “But the long-term hype is nowhere near enough.”
“All of the other use cases that people talk about are either more marginal, more speculative, or both,”
Scott Aaronson, a computer scientist at the University of Texas at Austin.
“Different options give you different results,” Holzmann says, “and we haven’t thought about many of these options yet.”
“Five years ago, that was a million trillion,” he says. – Steve Brierley, founder and chief executive of quantum-computing firm Riverlane in Cambridge, UK.
“We’re confident about that,” says Sabrina Maniscalco, Algorithmiq’s co-founder and chief executive, and a physicist at the University of Helsinki.
“If anything is going to give something useful in the next five years, it will be chemistry calculations,” says Ronald de Wolf, senior researcher at CWI, a research institute for mathematics and computer science in Amsterdam.
“This would be possible using quantum computers with a relatively small number of qubits,” he says. – Shintaro Sato, head of the Quantum Laboratory at Fujitsu Research in Tokyo.
“That is what will give us confidence when we start pushing past what is classically possible.” – Jeannette Garcia, senior research manager for quantum applications and software at technology giant IBM in San Jose, California.
“There’s not going to be this one point when suddenly we have a rainbow coming out of our lab and all problems can be solved,” he says. – Winfried Hensinger, a physicist at the University of Sussex in Brighton, UK.
Summary
Quantum computers are still in their early stages. Still, recent advances in quantum algorithms and error mitigation techniques make their potential applications in drug discovery, materials science, and machine learning more plausible. While commercial applications may be years away, researchers are optimistic about the progress and potential for quantum computing to revolutionize various industries.
“We are seeing that we can unlock extra performance in the hardware, and make it do things that people didn’t expect.”
Michael Biercuk, a quantum physicist at the University of Sydney in Australia and Chief executive and founder of Sydney-based start-up firm Q-CTRL.
- Quantum computers have not yet reached their full potential, but researchers are progressing and remain optimistic about their future capabilities.
- Jeannette Garcia, senior research manager for quantum applications and software at IBM, says development is proceeding better than expected.
- Physicist Winfried Hensinger at the University of Sussex has published a proof of principle for a large-scale, modular quantum computer. His start-up, Universal Quantum, is working with Rolls-Royce and others to build it.
- Quantum computers could accelerate drug discovery, crack encryption, speed up financial transactions, improve machine learning, develop revolutionary materials, and address climate change.
- Researchers are finding ways to make quantum algorithms more efficient and reduce errors in quantum computers.
- Some companies, like Helsinki-based start-up Algorithmiq, are confident they will demonstrate practical quantum advances in drug development and discovery within five years.
- Long-term quantum computing applications could include quantum versions of machine learning, requiring fewer parameters and less training data than classical algorithms.
Read More
