Lifeboat Foundation

Major technical improvements to a quantum computer based on trapped ions could bring a large-scale version closer to reality.

Scientists are exploring various platforms for future large-scale quantum computation. Among the leading contenders, those in which the quantum bits (qubits) are trapped ions stand out for their low-error operation. However, scaling up such platforms to the millions of qubits needed for utility-scale quantum computing is a daunting task. Now Steven Moses at Quantinuum in Colorado and colleagues describe an impressive new trapped-ion quantum computer, the Quantinuum System Model H2, in which they have been able to increase the number of qubits (from 20 to 32) without increasing the error rate [1]. The researchers have put this system through its paces with full component-level testing, a suite of industry-standard benchmark tests, and a set of diverse applications.

In a typical trapped-ion quantum computer, a linear chain of ions is confined by an electric potential using direct-current (dc) and radio-frequency (rf) fields. Whereas the ion-trap apparatus can be at any temperature, the ions themselves need to be laser cooled to near their ground state. Their motion can then be quantized, and the resulting motional modes can be used to entangle any pair of ions in the chain—a requirement for performing quantum operations. However, controlling individual ions in a long chain comes with its own technical difficulties, and it is unlikely that a million qubits—as needed to build a universal, fault-tolerant quantum computer [2]—could be trapped in a single potential.

The National Institute for Materials Science (NIMS) has succeeded in directly observing the “anisotropic magneto-Thomson effect,” a phenomenon in which the heat absorption/release proportional to an applied temperature difference and charge current (i.e., Thomson effect) changes anisotropically depending on the magnetization direction in magnetic materials.

This research is expected to lead to further development of basic physics and materials science related to the fusion area of thermoelectrics and spintronics, as well as to the development of new functionalities to control thermal energy with magnetism. The study is published in the journal Physical Review Letters.

The Thomson effect has long been known as one of the fundamental thermoelectric effects in metals and semiconductors, along with the Seebeck and Peltier effects, which are driving principles of thermoelectric conversion technologies.

Attempts to turn string theory into a workable theory of nature have led to the potential conclusion that our universe is a hologram—that what we perceive as three spatial dimensions is actually composed of only two. The greatest realization of this hologram-led program is a proposal that goes by the awkward and clunky name of the AdS/CFT correspondence, first proposed by string theorist Juan Maldacena in the late 1990s.

The AdS/CFT correspondence is not a solution to the problems posed by string theory per se, but a statement motivated by advances in the theory when one takes the holographic principle seriously. It is also not a revolution by itself, but it does tell us that we are not entirely misguided when we make the bold claim that we live in a hologram, and begin to dream about what that revelation might entail.

We need to, briefly I assure you, unpack these acronyms to see how powerful this connection is, and what it might teach us about the wider universe. The “AdS” stands for anti-de Sitter, which is a particular kind of solution to Einstein’s general theory of relativity. The name comes from Dutch physicist Willem de Sitter, who constructed a mock universe that was empty of all matter and energy with the exception of a strong outwards curvature.

Computer-generated holography (CGH) represents a cutting-edge technology that employs computer algorithms to dynamically reconstruct virtual objects. This technology has found extensive applications across diverse fields such as three-dimensional display, optical information storage and processing, entertainment, and encryption.

Despite the broad application spectrum of CGH, contemporary techniques predominantly rely on projection devices like spatial light modulators (SLMs) and digital micromirror devices (DMDs). These devices inherently face limitations in display capabilities, often resulting in narrow field-of-view and multilevel diffraction in projected images.

In recent developments, metasurfaces composed of an array of subwavelength nanostructures have demonstrated exceptional capabilities in modulating electromagnetic waves. By introducing abrupt changes to fundamental wave properties like amplitude and phase through nanostructuring at subwavelength scales, metasurfaces enable modulation effects that are challenging to achieve with traditional devices.

As object identification and three-dimensional (3D) reconstruction techniques become essential in various reverse engineering, artificial intelligence, medical diagnosis, and industrial production fields, there is an increasing focus on seeking vastly efficient, faster speed, and more integrated methods that can simplify processing.

In the current field of object identification and 3D reconstruction, extracting sample contour information is primarily accomplished by various computer algorithms. Traditional computer processors suffer from multiple constraints, such as high-power consumption, low-speed operation, and complex algorithms. In this regard, there has recently been growing attention in searching for alternative optical methods to perform those techniques.

The development of optical computing theory and image processing has provided a more complete theoretical basis for object identification and 3D reconstruction techniques. Optical methods have received more attention as an alternative paradigm than traditional mechanisms in recent years due to their enormous advantages of ultra-fast operation speed, high integration, and low latency.

String theory found its origins in an attempt to understand the nascent experiments revealing the strong nuclear force. Eventually another theory, one based on particles called quarks and force carriers called gluons, would supplant it, but in the deep mathematical bones of the young string theory physicists would find curious structures, half-glimpsed ghosts, that would point to something more. Something deeper.

String theory claims that what we call particles —the point-like entities that wander freely, interact, and bind together to make up the bulk of material existence—are nothing but. Instead, there is but a single kind of fundamental object: the string. These strings, each one existing at the smallest possible limit of existence itself, vibrate. And the way those strings vibrate dictates how they manifest themselves in the larger universe. Like notes on a strummed guitar, a string vibrating with one mode will appear to us as an electron, while another vibrating at a different frequency will appear as a photon, and so on.

String theory is an audacious attempt at a theory of everything. A single mathematical framework that explains the particles that make us who and what we are along with the forces that act as the fundamental messengers among those particles. They are all, every quark in the cosmos and every photon in the field, bits of vibrating strings.

New research enhances hybrid supercapacitors by creating more efficient electrodes, marking a significant step forward in energy storage technology.

Like batteries, supercapacitors are a type of energy-storage device. However, while batteries store energy electrochemically, supercapacitors store energy electrostatically—through the buildup of charge on their electrode surfaces.

Hybrid supercapacitors (HSCs) combine the advantages of both systems by incorporating battery-type and capacitor-type electrodes. Despite synthesis techniques that allow the active components in HSC electrodes to grow directly on conductive substrates without added binders (“self-supporting” electrodes), the fraction of active material in these electrodes has remained too low for commercial requirements.

The researchers found 139 genes that are common across the primate groups but highly divergent in their expression in human brains.

An international team led by researchers at the University of Toronto has uncovered over 100 genes that are common to primate brains but have undergone evolutionary divergence only in humans – and which could be a source of our unique cognitive ability.

The researchers, led by Associate Professor Jesse Gillis from the Donnelly Centre for Cellular and Biomolecular Research and the Department of Physiology at U of T’s Temerty Faculty of Medicine, found the genes are expressed differently in the brains of humans compared to four of our relatives – chimpanzees, gorillas, macaques, and marmosets.

Feng Guo, an associate professor of intelligent systems engineering at the Indiana University Luddy School of Informatics, Computing and Engineering, is addressing the technical limitations of artificial intelligence computing hardware by developing a new hybrid computing system—which has been dubbed “Brainoware”—that combines electronic hardware with human brain organoids.

Advanced AI techniques, such as machine learning and deep learning, which are powered by specialized silicon computer chips, expend enormous amounts of energy. As such, engineers have designed neuromorphic computing systems, modeled after the structure and function of a human brain, to improve the performance and efficiency of these technologies. However, these systems are still limited in their ability to fully mimic brain function, as most are built on digital electronic principles.

In response, Guo and a team of IU researchers, including graduate student Hongwei Cai, have developed a hybrid neuromorphic computing system that mounts a brain organoid onto a multielectrode assay to receive and send information. The brain organoids are brain-like 3D cell cultures derived from stem cells and characterized by different brain cell types, including neurons and glia, and brain-like structures such as ventricular zones.