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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.

Over the past few years, engineers have been trying to devise alternative hardware designs that would allow a single device to both perform computations and store data. These emerging electronics, known as computing-in-memory devices, could have numerous advantages, including faster speeds and enhanced data analysis capabilities.

To store data safely and retain a , these devices should be based on with advantageous properties and that can be scaled down in terms of thickness. Two-dimensional (2D) semiconductors that exhibit a property known as sliding ferroelectricity have been found to be promising candidates for realizing computing-in-memory, yet attaining the necessary switchable electric polarization in these materials can prove difficult.

Researchers at National Taiwan Normal University, Taiwan Semiconductor Research Institute, National Yang Ming Chiao Tung University and National Cheng Kung University recently devised an effective strategy to achieve a switchable electric polarization in molybdenum disulfide (MoS2). Using this method, outlined in a Nature Electronics paper, they ultimately developed new promising ferroelectric transistors for computing-in-memory applications.

Joe McEntee visits the Lawrence Berkeley National Laboratory to learn about QUANT-NET’s plan to create a quantum network tested for distributed quantum computing applications in the US. Joe McEntee visits Lawrence Berkeley National Laboratory (Berkeley Lab) in California to check out progress on the enabling quantum technologies.

Over the past decade or so, physicists and engineers have been trying to identify new materials that could enable the development of electronic devices that are faster, smaller and more robust. This has become increasingly crucial, as existing technologies are made of materials that are gradually approaching their physical limits.

Antiferromagnetic (AFM) spintronics are devices or components for electronics that couple a flowing current of charge to the ordered spin ‘texture’ of specific materials. In physics, the term spin refers to the intrinsic angular momentum observed in electrons and other particles.

The successful development of AFM spintronics could have very important implications, as it could lead to the creation of devices or components that surpass Moore’s law, a principle first introduced by microchip manufacturer Gordon Earle Moore’s law essentially states that the memory, speed and performance of computers may be expected to double every two years due to the increase in the number of transistors that a microchip can contain.

Researchers at the University of Chicago’s Pritzker School of Molecular Engineering (PME), Argonne National Laboratory, and the University of Modena and Reggio Emilia have developed a new computational tool to describe how the atoms within quantum materials behave when they absorb and emit light.

The tool will be released as part of the open-source software package WEST, developed within the Midwest Integrated Center for Computational Materials (MICCoM) by a team led by Prof. Marco Govoni, and it helps scientists better understand and engineer new materials for quantum technologies.

“What we’ve done is broaden the ability of scientists to study these materials for quantum technologies,” said Giulia Galli, Liew Family Professor of Molecular Engineering and senior author of the paper, published in Journal of Chemical Theory and Computation. “We can now study systems and properties that were really not accessible, on a large scale, in the past.”

But what would it actually mean to transfer your mind from “meat space” to cyberspace, and how could it be done? The basic idea rests on several assumptions, says Angela Thornton, a researcher at the Horizon Centre for Doctoral Training at University of Nottingham, who is also partnered with the Carboncopies Foundation, a non-profit that focuses on “whole brain emulation” and the creation of substrate-independent minds. “It assumes that we could replicate our brain [with] a certain level of understanding of how it works,” she says. “Not necessarily knowing all the detail, but enough to be able to emulate it.” Then, she adds, we have to make the assumption that the “mind” (i.e. the abstract part of us that thinks, remembers, imagines and senses) naturally emerges from the structures of the physical brain.

This is a lot to take on, which is partly why current brain emulation research is still stuck at the level of worms and, in more advanced studies, mice. Whether you agree with them or not, though, the arguments to take experiments further – toward larger mammals and, finally, humans – are quite obvious. For one, we could theoretically ‘live’ forever as a disembodied consciousness (or at least until the machines that hosted our virtual minds were destroyed), and continue interacting with our loved ones after they’ve passed as well. It’s possible that this could also go some way to solving the alleged population crisis, while limiting the impact of our physical bodies on the planet’s finite resources.

Of course, there are plenty of important questions that need answers before any of this can actually happen. Below, Thornton helps us unpick some of the main constraints and controversies.