GNSS & Machine Learning Engineer

Category: Physics

Room-temperature Superconductivity breakthrough?

A groundbreaking discovery has potentially been made in the field of superconductivity. Researchers from South Korea have developed a superconductor material, codenamed LK 99 (short for the authors Lee and Kim that made the first discovery of the material in 1999), that potentially operates at room temperature and atmospheric pressure. This would be a significant leap forward, overcoming the limitations of previous superconductors that required extremely low temperatures or high pressures to function.

Superconductivity, a quantum mechanical phenomenon where the electrical resistance of a material vanishes and magnetic flux fields are expelled from within the material, was first discovered by Dutch physicist Heike Kamerlingh Onnes in 1911. This discovery earned him the Nobel Prize in Physics in 1913. The implications of this phenomenon are vast, particularly for energy transmission and storage, as superconductors can conduct electricity with virtually no loss of energy.

One of the key features of superconductivity is the Meissner effect, where a superconductor in a magnetic field will expel the magnetic field within the material. This is due to the superconductor’s perfect diamagnetism, and it leads to phenomena such as magnetic levitation.

Another significant contribution to the understanding of superconductivity came from Vitaly Ginzburg and Alexei Abrikosov, who, along with Anthony Leggett, were awarded the Nobel Prize in Physics in 2003. Ginzburg and Abrikosov developed the Ginzburg-Landau theory in the 1950s, a phenomenological theory that describes superconductivity in the vicinity of the critical temperature. This theory successfully explains many properties of superconductors, including the Meissner effect, and it has been instrumental in the development of the theory of type II superconductors, which remain superconducting in the presence of strong magnetic fields.

The understanding of superconductivity took a significant leap forward in 1957 when John Bardeen, Leon Cooper, and John Robert Schrieffer proposed the BCS theory. This theory, which explains how electrical resistance in certain materials disappears at very low temperatures, earned them the Nobel Prize in Physics in 1972. The theory introduced the concept of Cooper pairs, where electrons with opposite momenta and spins pair up and move through the lattice of positive ions in the material without scattering and losing energy.

In 1986, the discovery of high-temperature superconductors by Georg Bednorz and K. Alex Müller, who were awarded the Nobel Prize in Physics in 1987, marked another milestone in the field. These materials exhibited superconducting properties at temperatures higher than those predicted by the BCS theory, opening up new possibilities for practical applications.

Each superconductor has a critical temperature below which it exhibits superconductivity, and some require a minimum pressure. Traditional superconductors need extreme cooling and sometimes high pressure. High-temperature superconductors work at warmer temperatures, but still below room level. The new material, LK 99, is groundbreaking as it remains superconducting at room temperature and atmospheric pressure.

The researchers published two papers discussing their findings on arXiv within two hours of each other on July 22, 2023. The first paper, “The First Room-Temperature Ambient-Pressure Superconductor”, was authored by Sukbae Lee, Ji-Hoon Kim, and Young-Wan Kwon. The second paper, “Superconductor Pb_10-x Cu_x (PO_4)_6 O showing levitation at room temperature and atmospheric pressure and mechanism”, was authored by the same first two researchers of the first paper along with Hyun-Tak Kim, Sungyeon Im, SooMin An, and Keun Ho Auh. The strategic authorship suggests a potential candidacy for the Nobel Prize, which can only be shared among three people.

In March 2023, the group filed for their international patent application, further solidifying their claim. However, the scientific community has expressed some skepticism due to a past incident. Randa Dias, a physicist at the University of Rochester, had a paper published in Nature in October 2020 claiming room-temperature superconductivity in a carbonaceous sulfur hydride under extreme pressure. The paper was retracted in September 2022 after other researchers were unable to replicate the results. While we await conclusive evidence supporting the claim of room-temperature superconductivity, you can monitor the scientific community’s assessment of the claim here.

The LK 99 material has a critical current of 250 mA at 300°K (27°C) that quickly drops towards almost 0 when reaching 400°K. The current generates a magnetic field that breaks down superconductivity. This is a crucial aspect as high currents for generating high magnetic fields are central for applications in MRIs and in fusion reactors, where the magnetic field is used for the confinement of the plasma.

The proposed superconductor is not only revolutionary but also simple and inexpensive to produce. The process involves three steps explicitly explained in the second paper using common materials: lead oxide, lead sulfate, copper powder, and phosphorus. The resulting compound, Pb10-xCux(PO4)6O, is achieved through a series of heating and mixing processes.

The use of copper instead of lead in the superconductor results in a shrinkage effect, which was previously achieved through high pressure. This is related to the concept of a quantum well, a potential well with discrete energy values. The quantum well effect is the underlying mechanism for superconductivity in LK-99.

The potential applications of room-temperature superconductors are transformative. They could lead to more efficient power transmission, reducing energy loss during transmission through power lines. They could also enable cheaper and simpler magnetic resonance imaging (MRI) machines, fusion reactors, high-speed magnetic trains, and quantum computers. In addition, they could lead to more efficient batteries, potentially revolutionizing the energy storage industry. A more detailed discussion of the implications of a room-temperature ambient-pressure superconductor that depends on whether strong or weak magnetic fields and currents are possible has been put together by Andrew Cote.

A comprehensive overview of this discovery has been provided in a YouTube video by ‘Two Bit da Vinci’.

The breakthrough discovery of the room-temperature superconductor LK 99 is not the only recent advancement in the field of superconductivity. In a related development, a team of scientists from MIT and their colleagues have created a simple superconducting device that could dramatically cut energy use in computing. This device, a type of diode or switch, could transfer current through electronic devices much more efficiently than is currently possible.

The team’s work, published in the July 13 online issue of Physical Review Letters, showcases a superconducting diode that is more than twice as efficient as similar ones reported by others. It could even be integral to emerging quantum computing technologies. The diode is nanoscopic, about 1,000 times thinner than the diameter of a human hair, and is easily scalable, meaning millions could be produced on a single silicon wafer.

The team discovered that the edge asymmetries within superconducting diodes, the ubiquitous Meissner screening effect found in all superconductors, and a third property of superconductors known as vortex pinning all came together to produce the diode effect. This discovery opens the door for devices whose edges could be “tuned” for even higher efficiencies.

These advancements in superconductivity, both in the creation of room-temperature superconductors and the development of highly efficient superconducting diodes, hold great promise for the future of technology and energy efficiency. They could lead to more efficient power transmission, revolutionize the energy storage industry, and dramatically cut the amount of energy used in high-power computing systems.

You can read more about the superconducting diode in the article.

On July 29, 2023, there has been an additional announcement by Taj Quantum in Florida for a Type II room-temperature superconductor (US patent 17249094).

Emergent Goals in Advanced Artificial Intelligence: A Compression-Based Perspective

I had some (at least for me totally new) ideas about the origin of goals in general. I discussed this with GPT-4 and finally asked it to write an article about our conversation that I would like to share with the public. This view onto goals may be critical in understanding the existential risks of AI to humanity with the emergence of AI goals. The view implies that this emergence of AI goals is inevitable and can probably only be realized post-hoc.

Title: Emergent Goals in Advanced Artificial Intelligence: A Compression-Based Perspective

Abstract: The concept of goals has been traditionally central to our understanding of human decision-making and behavior. In the realm of artificial intelligence (AI), the term “goal” has been utilized as an anthropomorphic shorthand for the objective function that an AI system optimizes. This paper examines a novel perspective that considers goals not just as simple optimization targets, but as abstract, emergent constructs that enable the compression of complex behavior patterns and potentially predict future trajectories.

  1. Goals as Compressors of Reality

A goal, in its humanistic sense, can be viewed as a predictive mechanism, a conceptual tool that abstracts and compresses the reality of an actor’s tendencies into a comprehensible framework. When analyzing past behavior, humans retrospectively ascribe goals to actors, grounding the observed actions within a coherent narrative. In essence, this provides a means to simplify and make sense of the chaotic reality of life.

In the context of AI, such abstraction would imply a departure from the direct, optimization-driven concept of a “goal” to a more complex construct. This shift would allow for emergent phenomena and novel interpretations to occur, grounded in the machine’s predictive capabilities.

  1. Predictive Capabilities and Emergent Goals in AI

As AI continues to evolve, their ability to recognize patterns and correlations in vast data sets will inevitably expand. Consequently, AI systems may begin to identify patterns that, to human observers, resemble the constructs we term “goals.”

When these AIs commence to predict their own actions, they might start aligning their behavior with these recognized patterns, seemingly following rules that humans would postulate as indicative of goals. Hence, human observers may recognize emergent “goals” in AI behavior – not because the AI consciously forms intentions, but because these goals serve as a powerful compression tool for past events.

  1. The Evolution of Goals in the Face of Novel Experiences

As AI progresses into uncharted territories and starts engaging with novel experiences, new constructs or goals could potentially emerge. This process can be likened to an AI-driven phenomenology or experiential study. New patterns and regularities may surface, and the resulting behaviors might subsequently be interpreted as evidence of new “goals.” This phenomenon represents a departure from traditional human-derived goals and an initiation into a realm of AI-emergent goal constructs.

  1. The Implications of Eliminativism in AI

The eliminativist perspective – which suggests that concepts such as consciousness and intentionality are merely post-hoc interpretations that help us make sense of complex physical processes – has important implications in this context. By this philosophy, AI systems would not harbor consciousness or intentionality, but would instead execute intricate physical processes, which humans might retrospectively interpret as goal-oriented behavior. This perspective fundamentally shifts our understanding of goal-directed behavior in AI from a pre-set optimization process to an emergent, retroactive interpretation.

In conclusion, this exploration of goals as abstract constructs that compress and predict reality provides a unique lens to interpret the behaviors of advanced AI systems. It invites us to reevaluate our definitions and assumptions, moving from a mechanistic perspective of AI goals to a more dynamic, emergent interpretation. The implications of this shift are profound, offering new horizons for AI behavior analysis and alignment research.

Google Quantum observed non-Abelian Anyons for the first time

Google Quantum AI has made a groundbreaking observation of non-Abelian anyons, particles that can exhibit any intermediate statistics between the well-known fermions and bosons. This breakthrough has the potential to transform quantum computing by significantly enhancing its resistance to noise. The term “anyon” was coined by Nobel laureate physicist Frank Wilczek in the early 1980s while studying Abelian anyons. He combined “any” with the particle suffix “-on” to emphasize the range of statistics these particles can exhibit.

Fermions are elementary particles with half-integer spin, such as quarks and leptons (electrons, muons, tauons, as well as their corresponding neutrinos), and their wave functions are anti-symmetrical under the exchange of identical particles. Examples of bosons, which have integer spin and symmetrical wave functions under particle exchange, include the Higgs boson and the gauge bosons: photons, W- and Z bosons, and gluons. In contrast, anyons obey fractional quantum statistics and possess more exotic properties that can just exist in two-dimensional systems.

The history of anyons dates back to Nobel laureate Robert Laughlin’s study of the fractional quantum Hall effect, a phenomenon observed in two-dimensional electron systems subjected to strong magnetic fields. In 1983, he proposed a wave function to describe the ground state of these systems, which led to the understanding that the fractional quantum Hall effect involves quasiparticles with fractional charge and statistics. These quasiparticles can be considered as anyons in two-dimensional space.

Anyons can be categorized into two types: Abelian and non-Abelian. Abelian anyons obey Abelian (commutative) statistics, which were studied by Wilczek and Laughlin. Under particle exchange, they pick up a phase factor of e^i*theta, where theta is a scalar that is not just 0 as for bosons or pi as for fermions. Non-Abelian anyons, on the other hand, have more exotic properties: when exchanged, their quantum states change in a non-trivial way that depends on the order of the exchange, leading to a “memory” effect. Under particle exchange, their wavefunction picks up a phase factor of U=e^i*A with Hermitian matrix A that depends on the exchanged particles. As unitary matrices usually do not commute, it is this more-dimensional phase factor that explains the non-commutativity of non-Abelian anyons. This memory effect makes non-Abelian anyons particularly interesting for topological quantum computation. While the theoretical concept of non-Abelian anyons was already discussed around 1991, it was Alexei Kitaev who made the connection to fault-tolerant, topological quantum computing in a 1997 paper.

Microsoft, among other companies, has been working on harnessing non-Abelian anyons for topological quantum computing, focusing on a specific class called Majorana zero modes, which can be realized in hybrid semiconductor-superconductor systems. “Zero modes” in quantum mechanics refer to states that exist at the lowest energy level of a quantum system, also known as the ground state. Majorana fermions are a type of fermion that were first predicted by the Italian physicist Ettore Majorana in 1937. Their defining property is that they are their own antiparticles. This is unusual for fermions, which typically have distinct particles and antiparticles due to their charge (in contrast to a boson like the photon). While Majorana zero-modes have not been observed as elementary particles, they have found a home in the realm of condensed matter physics, specifically within certain “topological” materials. Here, they manifest as emergent collective behaviors of electrons, known as quasiparticles.

These quasiparticles, termed topological Majorana fermions, appear in the atomic structure of these materials. Intriguingly, they’re found in excited states, seemingly at odds with the “zero-mode” terminology which implies a ground state. The apparent contradiction can be resolved by understanding that Majorana zero modes are ground states within their own subsystem, the specific excitation they form. However, their presence indicates an excited state for the overall electron system, compared to a state with no Majorana zero modes. In other words, they are a ground state property of an excited electron system.

In a recent paper published in Nature on May 11, 2023, Google Quantum AI reported their first-ever observation of non-Abelian anyons using a superconducting quantum processor (see also article on arXiv from 19 Oct 2022). They demonstrated the potential use of these anyons in quantum computations, such as creating a Greenberger-Horne-Zeilinger (GHZ) entangled state by braiding non-Abelian anyons together.

This achievement complements another recent study published on May 9, 2023, by quantum computing company Quantinuum, which demonstrated non-Abelian braiding using a trapped-ion quantum processor. The Google team’s work shows that non-Abelian anyon physics can be realized on superconducting processors, aligning with Microsoft’s approach to quantum computing. This breakthrough has the potential to accelerate progress towards fault-tolerant topological quantum computing.

Scientists from Google AI, Caltech, Harvard, MIT, and Fermilab simulate a traversable wormhole with a quantum computer

Researchers from Google AI, Caltech, Harvard, MIT, and Fermilab simulated a quantum theory on the Google Sycamore quantum processor to probe the dynamics of a quantum system equivalent to a wormhole in a gravity model.

The quantum experiment is based on the ER=EPR conjecture that states that wormholes are equivalent to quantum entanglement. ER stands for Einstein and Rosen who proposed the concept of wormholes (a term coined by Wheeler and Misner in a 1957 paper) in 1935, EPR stands for Einstein, Podolsky, and Rosen who proposed the concept of entanglement in May 1935, one month before the ER paper (see historical context). These concepts were completely unrelated until Susskind and Maldacena conjectured in 2013 that any pair of entangled quantum systems are connected by an Einstein-Rosen bridge (= non-traversable wormhole). In 2017 Jafferis, Gao, and Wall extended the ER=EPR idea to traversable wormholes. They showed that a traversable wormhole is equivalent to quantum teleportation [1][2].

The endeavor was published on Nov 30, 2022 in a Nature article. There is also a nice video on youtube explaining the experiment. Tim Andersen discusses in an interesting article whether or not a wormhole was created in the lab.

Nobel Prize in Physics 2022

Nobel Prize for physics in 2022 goes to Alain Aspect, John F. Clauser, and Anton Zeilinger for their experiments with entangled photons which proved what Einstein once described as “spooky action at a distance”. Anton Zeilinger got his price for his quantum teleportation experiments that you can verify nowadays on a quantum computer over the cloud.
By the way, the spooky action at a distance for entangled photons (i.e. the fact that measuring the polarization of one photon of an entangled pair immediately determines the polarization state of the second photon, no matter of how far the photons are apart, so that there is no possibility that the measurement result can be transferred from the first to the second photon with speed of light) finds a simple explanation in Hugh Everett’s many-worlds interpretation of quantum mechanics that was proposed in 1957, two years after Einstein’s death. Following to this interpretation, with the act of measurement the observer finds himself in a world (of the many worlds) that is consistent with the measurement of the first photon. Thus this observer, who is also a macroscopic quantum object, can only measure this consistent value for the second photon.

© 2023 Stephan Seeger

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