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Researchers at Columbia Engineering report today that they have developed the first nanomaterial that demonstrates “photon avalanching,” a process that is unrivaled in its combination of extreme nonlinear optical behavior and efficiency. The realization of photon avalanching in nanoparticle form opens up a host of sought-after applications, from real-time super-resolution optical microscopy, precise temperature and environmental sensing, and infrared light detection, to optical analog-to-digital conversion and quantum sensing.

“Nobody has seen avalanching behavior like this in nanomaterials before,” said James Schuck, associate professor of mechanical engineering, who led the study published today by Nature. “We studied these new nanoparticles at the single-nanoparticle level, allowing us to prove that avalanching behavior can occur in nanomaterials. This exquisite sensitivity could be incredibly transformative. For instance, imagine if we could sense changes in our chemical surroundings, like variations in or the actual presence of molecular species. We might even be able to detect coronavirus and other diseases.”

Avalanching processes—where a cascade of events is triggered by series of small perturbations—are found in a wide range of phenomena beyond snow slides, including the popping of champagne bubbles, nuclear explosions, lasing, neuronal networking, and even financial crises. Avalanching is an extreme example of a nonlinear process, in which a change in input or excitation leads to a disproportionate—often disproportionately large—change in output signal. Large volumes of material are usually required for the efficient generation of nonlinear optical signals, and this had also been the case for photon avalanching, until now.

Over the past decade or so, deep neural networks have achieved very promising results on a variety of tasks, including image recognition tasks. Despite their advantages, these networks are very complex and sophisticated, which makes interpreting what they learned and determining the processes behind their predictions difficult or sometimes impossible. This lack of interpretability makes deep neural networks somewhat untrustworthy and unreliable.

Researchers from the Prediction Analysis Lab at Duke University, led by Professor Cynthia Rudin, have recently devised a technique that could improve the interpretability of deep neural networks. This approach, called concept whitening (CW), was first introduced in a paper published in Nature Machine Intelligence.

Continue reading “Concept whitening: A strategy to improve the interpretability of image recognition models” »

On 14 November 2014, a bright flash flagged the All Sky Automated Survey for Supernovae, or ASAS-SN — a global network of 20 telescopes managed at Ohio State University in the U.S. The flash originated in galaxy ESO 253–3, located 570 million light-years away.

The sudden burst of energy was examined by astronomers and categorized as a likely supernova and assigned the event designation ASASSN-14ko. Six years later, Anna Payne, a NASA Graduate Fellow at the University of Hawai’i at Mānoa, discovered it was something much different.

Continue reading “From supernova to something much more intriguing at the core of galaxy 253-3” »

“This is perhaps the hardest part of all DNA storage approaches. If you can get the cells to directly talk to a computer, and interface its DNA-based memory system with a silicon-based memory system, then there are lots of possibilities in the future.”

The work builds on a CRISPR-based cellular recorder Wang had previously designed for E. coli bacteria, which detects the presence of certain DNA sequences inside the cell and records this signal into the organism’s genome.

The system includes a DNA-based “sensing module” that produces elevated levels of a “trigger sequence” in response to specific biological signals. These sequences are incorporated into the recorder’s “DNA ticker tape” to document the signal.

For many automakers, hydrogen fuel cell power isn’t the future of the automobile. But after seeing the SCG 009, we might want to give hydrogen a chance.

Meet the “Yangtze River Three Gorges 1”, an electric cruise ship, announced in December, that is poised to become the world’s largest of its kind (among EVs).

According to the brief info, it will be launched in July and enter service in November of 2021, on popular tourist routes: the Two Dams and One Gorge, the Yichang Yangtze River Night Cruise, and the Three Gorges Shiplift.

Continue reading “China Builds The World’s Largest Electric Cruise Ship” »

Scientists think they may have spied the universe’s “gravitational wave background” after more than a decade of searching.

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Working with theorists in the University of Chicago’s Pritzker School of Molecular Engineering, researchers in the U.S. Department of Energy’s (DOE) Argonne National Laboratory have achieved a scientific control that is a first of its kind. They demonstrated a novel approach that allows real-time control of the interactions between microwave photons and magnons, potentially leading to advances in electronic devices and quantum signal processing.

Microwave photons are elementary particles forming the electromagnetic waves that we use for wireless communications. On the other hand, magnons are the elementary particles forming what scientists call “spin waves”—wave-like disturbances in an ordered array of microscopic aligned spins that can occur in certain magnetic materials.

Microwave photon-magnon interaction has emerged in recent years as a promising platform for both classical and quantum information processing. Yet, this interaction had proved impossible to manipulate in real time, until now.