A recurrent, transformer-based neural network, called AlphaQubit, learns high-accuracy error decoding to suppress the errors that occur in quantum systems, opening the prospect of using neural-network decoders for real quantum hardware.
The V-score benchmarks classical and quantum algorithms in solving the many-body problem. The study highlights quantum computings potential for tackling complex material systems while providing an open-access framework for future research innovations.
Scientists aspire to use quantum computing to explore complex phenomena that have been difficult for current computers to analyze, such as the characteristics of novel and exotic materials. However, despite the excitement surrounding each announcement of “quantum supremacy,” it remains challenging to pinpoint when quantum computers and algorithms will offer a clear, practical advantage over classical systems.
A large collaboration led by Giuseppe Carleo, a physicist at the Swiss Federal Institute for Technology (EPFL) in Lausane and the member of the National Center for Competence in Research NCCR MARVEL, has now introduced a method to compare the performance of different algorithms, both classical and quantum ones, when simulating complex phenomena in condensed matter physics. The new benchmark, called V-score, is described in an article just published in Science.
Researchers have developed a new quantum theory that for the first time defines the precise shape of a photon, showing its interaction with atoms and its environment.
This breakthrough allows for the visualization of photons and could revolutionize nanophotonic technologies, enhancing secure communication, pathogen detection, and molecular control in chemical reactions.
A groundbreaking quantum theory has allowed researchers to define the exact shape of a single photon for the first time.
A breakthrough at Rice University enhances thermophotovoltaic systems with a new thermal emitter design, achieving over 60% efficiency.
This could transform energy conversion, making it a viable alternative to batteries for grid-scale energy storage and sustainable industry practices.
Researchers at Rice University have developed an innovative way to enhance thermophotovoltaic (TPV) systems, which convert heat into electricity using light. Drawing inspiration from quantum physics, engineer Gururaj Naik and his team designed a highly efficient thermal emitter that works within realistic design constraints.
Heeding those sentiments, the Australian Army is strategically investing in technological innovation to find better solutions to the complex logistics challenges they face in managing the efficient and safe deployment of personnel and equipment on the battlefield. For a difficult class of problems in an area called “optimization”, quantum computing is on the roadmap for exploration.
With the help of our quantum infrastructure software, they’ve now been able to test and validate a quantum computing solution on real hardware that promises to outperform their existing methods.
The U.S. faces a critical cybersecurity threat as quantum computers edge closer to disrupting the cryptographic systems that secure vital government and infrastructure data, according to a Government Accountability Office (GAO) report.
U.S. faces significant cybersecurity risks from quantum computing due to leadership gaps and an incomplete national strategy.
Dr. Seung-Woo Lee and his team at the Quantum Technology Research Center at the Korea Institute of Science and Technology (KIST) have developed a world-class quantum error correction technology and designed a fault-tolerant quantum computing architecture based on it.
- Quantum error correction is a key technology in the implementation and practicalization of quantum computing.
- Groundbreaking quantum error correction technology contributes to the development of K-quantum computing deployments.
Solving the problem of error is essential for the practical application of quantum computing technologies that surpass the performance of digital computers. Information input into a qubit, the smallest unit of quantum computation, is quickly lost and error-prone. No matter how much we mitigate errors and improve the accuracy of qubit control, as the system size and computation scale increase, errors accumulate and algorithms become impossible to perform. Quantum error correction is a way to solve this problem. As the race for global supremacy in quantum technology intensifies, most major companies and research groups leading the development of quantum computing are now focusing on developing quantum error correction technology.
Determining the passage of time in our world of ticking clocks and oscillating pendulums is a simple case of counting the seconds between ‘then’ and ‘now’
Down at the quantum scale of buzzing electrons, however, ‘then’ can’t always be anticipated. Worse still, ‘now’ often blurs into a haze of vagueness. A stopwatch simply isn’t going to work for some scenarios.
A potential solution could be found in the very shape of the quantum fog itself, according to a 2022 study by researchers from Uppsala University in Sweden.