QuEra, a quantum computing startup founded by researchers from Harvard and the Massachusetts Institute of Technology, recently released what may be the most ambitious quantum technology roadmap we’ve seen yet.
The company plans on releasing a quantum computer with 100 logical qubits and 10,000 physical qubits by 2026. It also claims this planned system will demonstrate “practical quantum advantage,” meaning they’d be capable of useful computation feats that classical, binary computers aren’t.
Producing photons one at a time on demand at room temperature is a key requirement for the rollout of a quantum internet—and the practical quantum computers that would undergird that network. The photons can be used as quantum bits (qubits), the quantum equivalent of classical computing’s 0s and 1s. Labs around the world have devised various ways to generate single photons, but they can involve complex engineering techniques such as doped carbon nanotubes or costly cryogenically-cooled conditions. On the other hand, less complicated techniques such as using traditional light sources do not provide the necessary level of control over single-photon emissions required for quantum networks and computers.
Now, researchers from Tokyo University of Science (TUS) and the Okinawa Institute of Science and Technology have collaborated to develop a prototype room temperature single-photon light source using standard materials and methods. The team described the fabrication of the prototype and its results in a recent issue of the journal Physical Review Applied.
“Our single-photon light source … increases the potential to create quantum networks—a quantum internet—that are cost-effective and accessible.” —Kaoru Sanaka, Tokyo University of Science.
The research conducted by Elena Hassinger, an expert in low-temperature physics working at ct.qmat—Complexity and Topology in Quantum Matter (a joint initiative by two universities in Würzburg and Dresden), has always been synonymous with extreme cold.
In 2021, she discovered the unconventional superconductor cerium-rhodium-arsenic CeRh2As2). Superconductors normally have just one phase of resistance-free electron transport, which occurs below a certain critical temperature. However, as reported in the academic journal Science, CeRh2As2 is so far the only quantum material to boast two certain superconducting states.
Lossless current conduction in superconductors has remained a central focus in solid-state physics for decades and has emerged as a significant prospect for the future of power engineering. The discovery of a second superconducting phase in CeRh2As2, which results from an asymmetric crystal structure around the cerium atom (the rest of the crystal structure is completely symmetrical), positions this compound as a prime candidate for use in topological quantum computing.
It is still unclear whether and how quantum computing might prove useful in solving known large-scale classical machine learning problems. Here, the authors show that variants of known quantum algorithms for solving differential equations can provide an advantage in solving some instances of stochastic gradient descent dynamics.
Before delving into the prospects of the Fifth Industrial Revolution, let’s reflect on the legacy of its predecessor. The Fourth Industrial Revolution, characterised by the fusion of digital, physical, and biological systems, has already transformed the way we live and work. It brought us AI, blockchain, the Internet of Things, and more. However, it also raised concerns about automation’s impact on employment and privacy, leaving us with a mixed legacy.
The promise of the Fifth Industrial Revolution.
The Fifth Industrial Revolution represents a quantum leap forward. At its core, it combines AI, advanced biotechnology, nanotechnology, and quantum computing to usher in a new era of possibilities. One of its most compelling promises is the extension of human life. With breakthroughs in genetic engineering, regenerative medicine, and AI-driven healthcare, we are inching closer to not just treating diseases but preventing them altogether. It’s a vision where aging is not an inevitability, but a challenge to overcome.
A new study in Physical Review Letters illuminates the intricacies of energy exchanges within bipartite quantum systems, offering profound insights into quantum coherence, pure dephasing effects, and the potential impact on future quantum technologies.
In quantum systems, the behavior of particles and energy transfer are governed by probability distributions and wave functions, adding layers of complexity to the understanding of energy exchanges.
The exploration of energy exchanges in quantum systems inherently involves tackling the complexities arising from quantum decoherence and the scales at which quantum systems operate, introducing sensitivity.
A study led by the University of Oxford has used the power of machine learning to overcome a key challenge affecting quantum devices. For the first time, the findings reveal a way to close the “reality gap”: the difference between predicted and observed behavior from quantum devices. The results have been published in Physical Review X.
Quantum computing could supercharge a wealth of applications, from climate modeling and financial forecasting to drug discovery and artificial intelligence. But this will require effective ways to scale and combine individual quantum devices (also called qubits). A major barrier against this is inherent variability, where even apparently identical units exhibit different behaviors.
Functional variability is presumed to be caused by nanoscale imperfections in the materials from which quantum devices are made. Since there is no way to measure these directly, this internal disorder cannot be captured in simulations, leading to the gap in predicted and observed outcomes.