Lifeboat Foundation

Generative AI is getting plenty of attention for its ability to create text and images. But those media represent only a fraction of the data that proliferate in our society today. Data are generated every time a patient goes through a medical system, a storm impacts a flight, or a person interacts with a software application.

Using generative AI to create realistic synthetic data around those scenarios can help organizations more effectively treat patients, reroute planes, or improve software platforms—especially in scenarios where real-world data are limited or sensitive.

For the last three years, the MIT spinout DataCebo has offered a generative software system called the Synthetic Data Vault to help organizations create synthetic data to do things like test software applications and train machine learning models.

Scientists have revealed why some white dwarfs mysteriously stop cooling—changing ideas on just how old stars really are and what happens to them when they die.

White dwarf stars are universally believed to be ‘dead stars’ that continuously cool down over time. However, in 2019, data from the European Space Agency’s (ESA’s) Gaia satellite discovered a population of white dwarf stars that have stopped cooling for more than eight billion years. This suggested that some white dwarfs can generate significant extra energy, at odds with the classical ‘dead star’ picture, and astronomers initially were not sure how this could happen.

Today, new research published in Nature, led by Dr. Antoine Bédard from the University of Warwick and Dr. Simon Blouin from the University of Victoria (Canada), unveils the mechanism behind this baffling observation.

The demonstration of a device that can triple the number of photons in a microwave signal is a key step toward making a single-microwave-photon detector.

The ability to detect a single microwave photon’s worth of energy remains beyond the capability of any tool in the photonics toolbox. Detectors for one photon’s worth of energy at other photon wavelengths mostly identify the energy via the electrical signals that the photons induce after they hit the detector and are converted into electrons. However, the energies of microwave photons are too low for this process to work effectively. Fortunately, superconducting circuits provide a platform for turning one microwave photon into many, making such photons easier to detect. In a joint effort, researchers at Grenoble Alpes University in France and at the University of Sherbrooke in Canada have now demonstrated a device that can multiply the photons in a weak microwave signal [1]. The demonstration provides a key first step in creating a single-microwave-photon detector.

While detectors for optical photons have existed for decades, scientists only started developing detectors for microwave photons in the past 15 years. The wish list for an effective microwave-photon detector is daunting: it should respond to traveling photons, and not only those localized in space [2– 5]; it should have sufficient sensitivity to register a signal from a single photon [6]; it should be able to count how many photons are in a signal [7]; it should not register so-called dark counts, hits recorded when the microwave source is off; and finally, its lag time between detections should be as short as possible. One proposed way to achieve these goals is to build a microwave-photon detector using the photon-number multiplier that Romain Albert and colleagues have now demonstrated [1, 8].

Last year was awash with claims that researchers had found new high-temperature superconductors. While some of those claims were quickly quashed, others are still being explored, such as the report that single crystals of the nickelate La₃Ni₂O₇ can superconduct at up to 78 K when under a pressure of 18 gigapascals (GPa) [1]. Now experiments performed by Jinguang Cheng of the Chinese Academy of Science and colleagues strengthen the claim that this compound is indeed a superconductor [2]. If confirmed, these results would make La₃Ni₂O₇ one of the few transition-metal compounds outside of cuprates to superconduct at temperatures above the boiling point of liquid nitrogen.

The initial report of superconductivity in La₃Ni₂O₇ came from measurements of single crystals. Those experiments showed a sudden drop in electrical resistance at around 80 K in samples held at pressures above 14 GPa. However, the report lacked measurements of two key hallmarks of a material entering the superconducting state—its resistance falling to zero and the expulsion of external magnetic fields.

For their experiments, Cheng and his colleagues studied polycrystalline samples of La₃Ni₂O₇ subjected to pressures of up to 18 GPa. The researchers chose polycrystalline samples over single-crystal ones, as they are significantly easier to prepare. Their resistance measurements indicated the zero-resistance state needed to confirm the presence of superconductivity. But the researchers’ attempts to detect the magnetic hallmark of superconductivity failed. Cheng says that recent unpublished results from their lab show that doping La₃Ni₂O₇ with the lanthanide praseodymium increases the superconducting temperature to 82.5 K. In those experiments, he says, the team observed both superconducting hallmarks.

Throughout many branches of physics, a connection can be drawn between geometry and dynamics. In general relativity, for example, the motion of stars and planets is governed by the geometry of spacetime. In condensed matter, the motion of electrons in solids is influenced by the so-called quantum geometry, which describes how the electronic wave function evolves in momentum space. The quantum geometry can explain a wide range of observed phenomena, such as topological phases and quantum Hall effects, but it can also lead researchers to new electromagnetic responses. Guided by quantum-geometry predictions, Lujunyu Wang from Peking University and colleagues present experimental evidence of a new Hall effect, the magneto-nonlinear Hall effect, which is proportional to both an in-plane electric field and an in-plane magnetic field [1] (Fig. 1). The effect, which was isolated in a magnet with triangular symmetry, offers a new way to probe in the quantum geometry of materials.

Quantum geometry is a representation of the phase of the Bloch wave functions, which describe electronic behavior in a periodic potential. In the case of a two-level system, this phase can be represented by a unit vector in the momentum space of the electrons. In certain materials, this vector rotates as the momentum changes, an effect that can be characterized by two fundamental geometrical properties: the “quantum metric” and the “Berry curvature.” These two aspects of quantum geometry can describe many phenomena including surface currents in topological insulator and anomalous Hall effects in which the transverse Hall current occurs in the absence of an external magnetic field.

Recently, researchers have uncovered a connection between quantum geometry and nonlinear electromagnetic effects [2– 10]. Here, the nonlinearity is a higher-order response to the input electromagnetic fields. Nonlinear electrical transport is the foundation of applications such as rectification and wave mixing. Classically, the most well-known nonlinear device is a p-n junction. In quantum materials, nonlinear transport suggests novel device applications but also provides a powerful probe of the quantum geometry of the conduction electrons.

Researchers have developed a quantum gas microscope that can pinpoint the horizontal and vertical positions of atoms arranged in a lattice.

Researchers led by Northwestern University and Washington University School of Medicine in St. Louis have developed a new, first-of-its-kind sticker that enables clinicians to monitor the health of patients’ organs and deep tissues with a simple ultrasound device.

When attached to an organ, the soft, tiny sticker changes in shape in response to the body’s changing pH levels, which can serve as an early warning sign for post-surgery complications such as anastomotic leaks. Clinicians then can view these shape changes in real time through ultrasound imaging.

Currently, no existing methods can reliably and non-invasively detect anastomotic leaks—a life-threatening condition that occurs when gastrointestinal fluids escape the digestive system. By revealing the leakage of these fluids with high sensitivity and high specificity, the non-invasive sticker can enable earlier interventions than previously possible. Then, when the patient has fully recovered, the biocompatible, bioresorbable sticker simply dissolves away—bypassing the need for surgical extraction.

Physicists successfully measure gravity in the quantum world, detecting weak gravitational pull on a tiny particle with a new technique that uses levitating magnets, putting scientists closer to solving mysteries of the universe.

Scientists are a step closer to unraveling the mysterious forces of the universe after working out how to measure gravity on a microscopic level.

Experts have never fully understood how the force discovered by Isaac Newton works in the tiny quantum world.

A novel architecture for optical neural networks utilizes wavefront shaping to precisely manipulate the travel of ultrashort pulses through multimode fibers, enabling nonlinear optical computation.

Present-day artificial intelligence systems rely on billions of adjustable parameters to accomplish complex objectives. Yet, the vast quantity of these parameters incurs significant expenses. The training and implementation of such extensive models demand considerable memory and processing power, available only in enormous data center facilities, consuming energy on par with the electrical demands of medium-sized cities. In response, researchers are currently reevaluating both the computing infrastructure and the machine learning algorithms to ensure the sustainable advancement of artificial intelligence continues at its current rate.

Optical implementation of neural network architectures is a promising avenue because of the low-power implementation of the connections between the units. New research reported in Advanced Photonics combines light propagation inside multimode fibers with a small number of digitally programmable parameters and achieves the same performance on image classification tasks with fully digital systems with more than 100 times more programmable parameters.