Researchers at ETH have managed to trap ions using static electric and magnetic fields and to perform quantum operations on them. In the future, such traps could be used to realize quantum computers with far more quantum bits than have been possible up to now.
Electronic states that resemble molecules and are promising for use in future quantum computers have been created in superconducting circuits by physicists at RIKEN.
JILA breakthrough in integrating artificial atoms with photonic circuits advances quantum computing efficiency and scalability.
In quantum information science, many particles can act as “bits,” from individual atoms to photons. At JILA, researchers utilize these bits as “qubits,” storing and processing quantum 1s or 0s through a unique system.
While many JILA Fellows focus on qubits found in nature, such as atoms and ions, JILA Associate Fellow and University of Colorado Boulder Assistant Professor of Physics Shuo Sun is taking a different approach by using “artificial atoms,” or semiconducting nanocrystals with unique electronic properties. By exploiting the atomic dynamics inside fabricated diamond crystals, physicists like Sun can produce a new type of qubit, known as a “solid-state qubit,” or an artificial atom.
The work, facilitated by the Chicago Quantum Exchange (CQE) and led by a team that includes UD, Argonne, JPMorgan Chase and University of Chicago scientists, lays groundwork for future applications—and highlights the need for cross-sector collaboration.
The third category, stochastic modeling, is used across the sciences to predict the spread of disease, the evolution of a chemical reaction, or weather patterns. The mathematical technique models complex processes by making random changes to a variable and observing how the process responds to the changes.
The method is used in finance, for instance, to describe the evolution of stock prices and interest rates. With the power of quantum computing behind it, stochastic modeling can provide faster and more accurate predictions about the market.
Physicists used to think they had a good idea of the size of the proton. Values derived from measurements of hydrogen’s emission spectrum and from electron-scattering experiments agreed with a proton radius of around 0.88 femtometers (fm). Then, in 2010, confidence was shaken by a spectral measurement that indicated a proton radius of approximately 0.84 fm [1]. In the years since, this “proton radius puzzle” has become even more of a head-scratcher, with some experiments supporting the original estimate and others finding an even greater discrepancy. Simon Scheidegger and Frédéric Merkt at the Swiss Federal Institute of Technology (ETH), Zurich, have now made precise new measurements of the transition energies between one of hydrogen’s metastable low-energy states and several of its highly excited states [2] (Fig. 1). These measurements allow the researchers to derive some of the atom’s properties, such as its ionization energy, with greater confidence, which should help clear up some of the confusion.
The 2010 study that “shrank the proton” (as the title of the editorial summary in Nature jokingly stated) concerned the 2 S –2 P1/2 Lamb shift [1]. According to Dirac’s predictions, the 2 S and 2 P1/2 levels of atomic hydrogen should be degenerate. The Lamb shift refers to the lifting of this degeneracy by quantum electrodynamic (QED) effects, the largest contribution being the electron “self-energy” due to interactions with virtual photons. Once this and other QED effects are accounted for, a tiny shift of the bound-state energy levels remains, which can be attributed to the proton’s finite size. By measuring this residual energy shift, one can determine the proton radius directly. The authors of the 2010 study did so using hydrogen atoms in which the electron was replaced by its heavier cousin, the muon, since the finite-size effect is stronger in this system.
Ever since that surprise result, researchers have tried to pin down the proton radius both directly, via the finite-size effect, and indirectly, via the Rydberg constant. The Rydberg constant relates an atom’s energy levels to other physical constants and is one of the key inputs used in calculations of the proton radius. Determining its value requires painstaking measurements of the transition energies between hydrogen’s various states. Several groups have made monumental efforts in this regard, but the values they derive for the proton radius have been all over the place. A 2018 measurement of the 1 S –3 S transition by a group in France gave a value of about 0.88 fm [3], a 2019 measurement of the classic Lamb shift (this time in regular hydrogen) by a group in Canada came up with a value of about 0.833 fm [4], and a 2017 measurement of the 2 S –4 P transition by a group in Germany suggested a similarly low value of about 0.834 fm [5]. In 2020, the group in Germany arrived at a slightly higher value of 0.848 fm [6]. In 2022, finally, from measurements of the 2 S –8 D transition, a group at Colorado State University proposed a “compromise value” of about 0.86 fm [7].
Superconductivity makes physics seem like magic. At cold temperatures, superconducting materials allow electricity to flow indefinitely while expelling outside magnetic fields, causing them to levitate above magnets. MRIs, maglev trains, and high-energy particle accelerators use superconductivity, which also plays a crucial role in quantum computing, quantum sensors, and quantum measurement science. Someday, superconducting electric grids might deliver power with unprecedented efficiency.
Challenges with Superconductors
Yet scientists lack full control over conventional superconductors. These solid materials often comprise multiple kinds of atoms in complicated structures that are difficult to manipulate in the lab. It’s even harder to study what happens when there’s a sudden change, such as a spike in temperature or pressure, that throws the superconductor out of equilibrium.
From the article:
“Somewhere between one and ten million qubits are needed for a fault-tolerant quantum computer, whereas IBM has only just realized a 1,200-qubit computer,” says Aoki.
While this approach isn’t limited to any specific platform for quantum computers, it does lend itself to trapped ions and neutral atoms since they don’t need to be cooled to cryogenic temperatures, which makes them much easier to connect.
Continue reading “A fresh approach to quantum computers based on atoms and photons” »
Quantum researchers uncover important implications for quantum technology.
In a recent publication in Nature Physics, the LSU Quantum Photonics Group offers fresh insights into the fundamental traits of surface plasmons, challenging the existing understanding. Based on experimental and theoretical investigations conducted in Associate Professor Omar Magaña-Loaiza’s laboratory, these novel findings mark a significant advancement in quantum plasmonics, possibly the most noteworthy in the past decade.
Rethinking Plasmonic Behavior
Organic computers are based on living, biological “wetware”. This video reports on organic computing research in areas including DNA storage and massively parallel DNA processing, as well as the potential development of biochips and entire biocomputers. If you are interested in this topic you may enjoy my book “Digital Genesis: The Future of Computing, Robots and AI”. You can download a free pdf sampler, here: http://www.explainingcomputers.com/ge… purchase “Digital Genesis” on Amazon.com here: http://amzn.to/2yVKStK Or purchase “Digital Genesis” on Amazon.co.uk here: http://www.amazon.co.uk/dp/1976098068… Links to specific research cited in the video are as follows: Professor William Ditto’s “Leech-ulator”: http://www.zdnet.com/article/us-scien… Development of transcriptor at Stanford: https://med.stanford.edu/news/all-new… Harvard Medical School DNA storage: https://hms.harvard.edu/news/writing–… Yaniv Erlich and Dina Zielinski DNA storage: http://pages.jh.edu/pfleming/bioinfor… Manchester University DNA parallel processing: http://rsif.royalsocietypublishing.or… All biocomputer and other CG animations included in this video were produced by and are copyright © Christopher Barnatt 2017. If you enjoy this video, you may like my previous report on quantum computing: • Quantum Computing 2017 Update More videos on computing-related topics can be found at:
/ explainingcomputers You may also like my ExplainingTheFuture channel at:
/ explainingthefuture.
