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Lucy, an early human ancestor, could run upright but much slower than modern humans. New simulations show that muscle and tendon evolution, not just skeletal changes, were key to improving human running speed.

The University of Liverpool has led an international team of scientists in a new investigation into the running abilities of Australopithecus afarensis, the early human ancestor best known through the famous fossil “Lucy.”

Professor Karl Bates, an expert in Musculoskeletal Biology, brought together specialists from institutions in the UK and the Netherlands. Using advanced computer simulations and a digital reconstruction of Lucy’s skeleton, the team explored how this ancient species.

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 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.