Lifeboat Foundation

Imagine that you have a secret decoder ring that you can use to decipher a secret message with important clues about things around you: where they came from, why they are there, and what will become of them in the future. Now imagine that the secret decoder ring is actually a sensor that can be flown in space to unravel secrets about the matter in the solar system. Where did this matter originate, how did it become energized, and how could it impact humans living on Earth and traveling in space?

The Solar Wind Pickup Ion Composition Energy Spectrometer (SPICES) is like a decoder ring for the plasma (gas consisting of electrically charged particles) in the solar system. It has the potential to reveal important information about how the sun behaves and interacts with planets and their atmospheres, and how the solar system is impacted by its own motion through interstellar space.

The universe is mostly made of hydrogen, but the elements that make up life as well as the planets, comets, and many other celestial bodies are heavier than hydrogen. In fact, these heavier elements, although not as abundant, can hold the key to understanding how numerous processes in the universe work. In our solar system, these “heavy elements”—which are called “heavy ions” when they are electrically charged—can help us trace plasma to its origin at planets, comets, the sun and solar atmosphere, and even to interstellar space.

Speech production is a complex neural phenomenon that has left researchers explaining it tongue-tied. Separating out the complex web of neural regions controlling precise muscle movement in the mouth, jaw and tongue with the regions processing the auditory feedback of hearing your own voice is a complex problem, and one that has to be overcome for the next generation of speech-producing protheses.

Now, a team of researchers from New York University have made key discoveries that help untangle that web, and are using it to build vocal reconstruction technology that recreates the voices of patients who have lost their ability to speak.

The team, co-led by Adeen Flinker, Associate Professor of Biomedical Engineering at NYU Tandon and Neurology at NYU Grossman School of Medicine, and Yao Wang, Professor of Biomedical Engineering and Electrical and Computer Engineering at NYU Tandon, as well as a member of NYU WIRELESS, created and used complex neural networks to recreate speech from brain recordings, and then used that recreation to analyze the processes that drive human speech.

Europe is pushing to create a network infrastructure based on quantum physics.

In May 2023, Dr. Benjamin Lanyon at the University of Innsbruck in Austria took an important step toward creating a new kind of internet: he transferred information along an optical fiber 50 kilometers long using the principles of quantum physics.

Information in quantum physics differs from the units of data—binary digits—stored and processed by computers that form the core of the current World Wide Web. The quantum physics realm covers the properties and interactions of molecules, atoms and even smaller particles such as electrons and photons.

Absorption spectroscopy is an analytical chemistry tool that can determine if a particular substance is present in a sample by measuring the intensity of the light absorbed as a function of wavelength. Measuring the absorbance of an atom or molecule can provide important information about electronic structure, quantum state, sample concentration, phase changes or composition changes, among other variables, including interaction with other molecules and possible technological applications.

Molecules with a high probability of simultaneously absorbing two photons of low-energy light have a wide array of applications: in molecular probes for high-resolution microscopy, as a substrate for data storage in dense three-dimensional structures, or as vectors in medicinal treatments, for example.

Studying the phenomenon by means of direct experimentation is difficult, however, and computer simulation usually complements spectroscopic characterization. Simulation also provides a microscopic view that is hard to obtain in experiments. The problem is that simulations involving relatively large molecules require several days of processing by supercomputers or months by conventional computers.

In a recent publication in EPJ Quantum Technology, Le Bin Ho from Tohoku University’s Frontier Institute for Interdisciplinary Sciences has developed a technique called time-dependent stochastic parameter shift in the realm of quantum computing and quantum machine learning. This breakthrough method revolutionizes the estimation of gradients or derivatives of functions, a crucial step in many computational tasks.

Typically, computing derivatives requires dissecting the function and calculating the rate of change over a small interval. But even classical computers cannot keep dividing indefinitely. In contrast, quantum computers can accomplish this task without having to discrete the function. This feature is achievable because quantum computers operate in a realm known as “quantum space,” characterized by periodicity, and no need for endless subdivisions.

One way to illustrate this concept is by comparing the sizes of two elementary schools on a map. To do this, one might print out maps of the schools and then cut them into smaller pieces. After cutting, these pieces can be arranged into a line, with their total length compared (see Figure 1a). However, the pieces may not form a perfect rectangle, leading to inaccuracies. An infinite subdivision would be required to minimize these errors, an impractical solution, even for classical computers.

Whether improperly closing a door or shanking a kick in soccer, our brains tell us when we’ve made a mistake because these sounds differ from what we expect to hear. While it’s long been established that our neurons spot these errors, it has been unclear whether there are brain cells that have only one job—to signal when a sound is unexpected or “off.”

A team of New York University neuroscientists has now identified a class of neurons—what it calls “prediction-error neurons”—that are not responsive to sounds in general, but only respond when sounds violate expectations, thereby sending a message that a mistake has been made.

“Brains are remarkable at detecting what’s happening in the world, but they are even better at telling you whether what happened was expected or not,” explains David Schneider, an assistant professor in NYU’s Center for Neural Science and the senior author of the study, which appears in JNeurosci. “We found that there are specific neurons in the brain that don’t tell you what happened, but instead tell you what went wrong.”

Researchers have developed a method that can reveal the location of errors in quantum computers, making them up to 10 times easier to correct. This will significantly accelerate progress towards large-scale quantum computers capable of tackling the world’s most challenging computational problems, the researchers said.

Led by Princeton University’s Jeff Thompson, the team demonstrated a way to identify when errors occur in quantum computers more easily than ever before. This is a new direction for research into quantum computing hardware, which more often seeks to simply lower the probability of an error occurring in the first place.

A paper detailing the new approach was published in Nature on Oct. 11. Thompson’s collaborators include Shruti Puri at Yale University and Guido Pupillo at Strasbourg University.

Scientists testing a new method of sequencing single cells have unexpectedly changed our understanding of the rules of genetics.

The genome of a protist has revealed a seemingly unique divergence in the DNA

DNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).

Here is how the brain adapts to diverse styles.