Toggle light / dark theme

The headline challenge for building a quantum computer is well known: the quantum states exhibited by such a computer’s computational building blocks—its qubits—must be long-lived and robust against disruption by the environment. But even the most resilient qubits are useless for quantum computing if they can’t be combined in sufficient numbers. Maciej Malinowski at Oxford Ionics, UK, and his colleagues have now tackled this problem through a more efficient architecture for controlling qubits [1]. Applying their “Wiring using Integrated Switching Electronics” (WISE) approach to trapped-ion qubits specifically, they present a design for a quantum computer with 1,000 qubits—far more than the few tens of qubits that make up the largest commercially available trapped-ion device currently available.

Trapped-ion quantum computers share much of their solid-state chip technology with modern classical computers, but they have added complexity. Whereas the bits in a classical computer are written and read using simple signals sent via a small number of electrodes, the qubits in a trapped-ion computer are controlled using subtler, more varied signals, which are delivered by as many as ten separate electrodes per qubit. As the number of qubits in a quantum computer increases, fitting these electrodes and signal generators on the chip—not to mention dissipating the heat that they generate—gets more difficult.

In their WISE approach, Malinowski and his colleagues use fewer signal generators and move them off the chip. Instead of every individual qubit having its own dedicated control structure, the signal from one signal generator is relayed to multiple qubits via a small number of local switches. Malinowski says that a trapped-ion quantum computer employing their control method could be built using existing semiconductor fabrication techniques.

A new thermometer allows thermal mapping of surfaces with microscale resolution and enables studies of heat flow through materials at cryogenic temperatures.

To study tiny systems such as microelectronic components, researchers would like to map cryogenic temperatures of structures at the nanoscale. But current techniques involve some heating that can spoil the measurements. Now a research team has demonstrated a cryogenic thermometer that provides microscale resolution and that has little effect on the temperature of the system being measured [1]. Single molecules embedded in tiny crystals are the sensors, and they have millikelvin sensitivity. The team says that the technique could be useful for a wide range of cryogenic studies of the thermal properties of surfaces having nanoscale structures.

Understanding and controlling heat flow through materials is essential for developing a wide range of technologies. For example, researchers have begun to use two-dimensional materials, such as graphene, cooled to cryogenic temperatures, to conduct heat away from hot spots in microelectronic devices. In these materials and at these low temperatures, heat can travel long distances without dissipation, which makes these materials extremely effective heat conductors. However, the precise mechanisms for this heat transport are still poorly understood. More generally, researchers would also like to better understand other anomalous thermal properties of materials that apply at these temperatures, such as a regime where heat flows as waves.

The more diverse species in your gut, the better it is for your health. Now an international team led by the Hudson Institute of Medical Research has found a way to determine which species are important and how they interact to create a healthy microbiome.

Understanding these relationships opens the door to a new world of medical opportunities for conditions from inflammatory bowel disease to infections, and cancers.

Associate Professor Samuel Forster and his team at Hudson Institute of Medical Research, working with collaborators from the Institute for Systems Biology in the U.S. and local collaborators at Monash University and Monash Health, have spent years studying the gut microbiome and working out which species perform which functions.

Researchers have revealed a radical new use of AI — to predict earthquakes.

A team from Tokyo Metropolitan University have used machine-learning techniques to analyze tiny changes in geomagnetic fields.

These allow the system, to predict natural disaster far earlier than current methods.