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A cryogenic microscope reveals the atomic-scale processes that disrupt the charge-ordered state in a material as the temperature rises.

Many of the exotic materials being investigated for next-generation technologies exhibit charge order, a state in which the electrons arrange themselves into a periodic pattern, such as stripes of high and low electron density. Researchers have now shown that they can track the evolution of this state as it warms up and melts away by using a cryogenic electron microscope [1]. Their experimental approach offers a new way to explore the interactions between different phases of quantum materials, which could inform the development of future electronic and data storage devices.

In certain materials with strongly interacting electrons, charge order appears—usually below room temperature—as an electron density that varies periodically in a pattern of stripes, a checkerboard, or a more complicated 3D structure. Researchers want to understand this phase because it coexists and interacts with other states and properties of the material, many of which are useful for novel devices and technologies. In high-temperature superconductors, for example, charge order is known to suppress the material’s superconducting behavior. In other materials, strong coupling between charge order and ferromagnetism can trigger colossal magnetoresistance, a property that could be exploited in magnetic storage devices.

To develop scalable and reliable quantum computers, engineers and physicists will need to devise effective strategies to mitigate errors in their quantum systems without adding complex additional components. A promising strategy to reduce errors entails the use of so-called dual-type qubits.

These are qubits that can encode quantum information in a system across two different types of quantum states. These qubits could increase the flexibility of quantum computing architectures, while also reducing undesirable crosstalk between qubits and enhancing a system’s operational fidelity.

Researchers at Tsinghua University and other research institutes in China recently realized an entangling gate between dual-type qubits in an experimental setting.

How can computer models help medical professionals combat antibiotic resistance? This is what a recent study published in PLOS Biology hopes to address as a team of researchers from the University of Virginia (UVA) developed computer models that can be used to target specific genes in bacteria to combat antimicrobial resistant (AMR) bacteria. This study has the potential to help scientists, medical professionals, and the public better understand innovative methods that can be used to combat AMR with bacterial diseases constantly posing a risk to global human health.

For the study, the researchers used computer models to produce an assemblage of genome-scale metabolic network reconstructions (GENREs) diseases to identify key genes in stomach diseases that can be targeted with antibiotics to circumvent AMR in these bacterial diseases. The researchers validated their findings with laboratory experiments involving microbial samples and found that a specific gene was responsible for producing stomach diseases, thus strengthening the argument for using targeted antibiotics to combat AMR.

“Using our computer models we found that the bacteria living in the stomach had unique properties,” said Emma Glass, who is a PhD Candidate in Biomedical Engineering at UVA and lead author of the study. “These properties can be used to guide design of targeted antibiotics, which could hopefully one day slow the emergence of resistant infections.”

It’s expected that the technology will tackle myriad problems that were once deemed impractical or even impossible to solve. Quantum computing promises huge leaps forward for fields spanning drug discovery and materials development to financial forecasting.

But just as exciting as quantum computing’s future are the breakthroughs already being made today in quantum hardware, error correction and algorithms.

NVIDIA is celebrating and exploring this remarkable progress in quantum computing by announcing its first Quantum Day at GTC 2025 on Thursday, March 20. This new focus area brings together leading experts for a comprehensive and balanced perspective on what businesses should expect from quantum computing in the coming decades — mapping the path toward useful quantum applications.

Physicists discover a unique quantum behavior that offers a new way to manipulate electron-spin and magnetization to push forward cutting-edge spintronic technologies, like neuromorphic computing.

Symmetry plays a crucial role in understanding fundamental phenomena such as conservation laws, the classification of phases of matter, and their transitions. Recently, researchers have been exploring ways to manipulate symmetries in quantum many-body systems with time-dependent driving protocols and, in particular, engineering new symmetries that do not naturally occur. This significantly enriches the toolbox for quantum simulation and computation, and has led to many exciting discoveries of nonequilibrium phases such as discrete time crystals. However, controlling multiple symmetries—especially in a simple and experimentally friendly way—has remained a challenge. In this work, we propose a novel method to engineer hierarchical symmetries by time-dependent protocols.

By carefully controlling how symmetry-indicating observables evolve over time, we show how to create a sequence of symmetries that emerge one after another, each with distinct properties. Our method relies on a recursive construction that hierarchically minimizes the effects of symmetry-breaking processes. This leads to a corresponding sequence of prethermal steady states with controllable lifetimes, each exhibiting a lower symmetry than the preceding one. We illustrate this protocol with several examples, demonstrating how different types of order can emerge through hierarchical symmetry breaking.

This toolbox of hierarchical symmetries opens a new path to stabilizing quantum states and controlling unwanted symmetry-breaking effects, which can be particularly useful in quantum computing and quantum simulation. The construction applies to classical and quantum, fermionic and bosonic, interacting and noninteracting systems. The underlying mechanism generalizes state-of-the-art dynamical decoupling techniques and is implementable on present-day quantum simulation platforms.

TSMC is aiming to begin mass production of Apple’s A-series chips for the iPhone as soon as this quarter at its Arizona plant.

Watch Firefly Aerospace’s Blue Ghost lunar lander lift off from NASA’s Kennedy Space Center in Florida on a SpaceX Falcon 9 rocket. SpaceX and Firefly Aerospace are targeting 1:11 a.m. EST (0611 UTC) Wednesday, Jan. 15, 2025, for launch. The lander will carry 10 NASA science investigations to the Moon’s surface.

Following launch, the lander will spend approximately 45 days in transit to the Moon before landing on the lunar surface in early March 2025. The 10 NASA payloads aboard the lander aim to test and demonstrate lunar subsurface drilling technology, regolith sample collection capabilities, global navigation satellite system abilities, radiation tolerant computing, and lunar dust mitigation methods.

Continue reading “Firefly Blue Ghost Mission 1 Launch to the Moon (Official NASA Broadcast)” »

The operation and performance of quantum computers relies on the ability to realize and control entanglement between multiple qubits. Yet entanglement between many qubits is inherently susceptible to noise and imperfections in quantum gates.

In recent years, quantum physicists and engineers worldwide have thus been trying to develop more robust protocols to realize and control entanglement. To be most effective for real-world applications, these approaches should reliably support long-range entanglement, or in other words ensure that qubits remain entangled even when they are separated by large distances.

Researchers at IBM Quantum, University of Cologne and Harvard University set out to demonstrate one of these protocols in an experimental setting.