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Researchers at Australia’s CSIRO have achieved a world-first demonstration of quantum machine learning in semiconductor fabrication. The quantum-enhanced model outperformed conventional AI methods and could reshape how microchips are designed. The team focused on modeling a crucial—but hard to predict—property called “Ohmic contact” resistance, which measures how easily current flows where metal meets a semiconductor.

They analysed 159 experimental samples from advanced gallium nitride (GaN) transistors (known for high power/high-frequency performance). By combining a quantum processing layer with a final classical regression step, the model extracted subtle patterns that traditional approaches had missed.

Tackling a difficult design problem

According to the study, the CSIRO researchers first encoded many fabrication variables (like gas mixtures and annealing times) per device and used principal component analysis (PCA) to shrink 37 parameters down to the five most important ones. Professor Muhammad Usman – who led the study – explains they did this because “the quantum computers that we currently have very limited capabilities”.

Classical machine learning, by contrast, can struggle when data are scarce or relationships are nonlinear. By focusing on these key variables, the team made the problem manageable for today’s quantum hardware.

A quantum kernel approach

To model the data, the team built a custom Quantum Kernel-Aligned Regressor (QKAR) architecture. Each sample’s five key parameters were mapped into a five-qubit quantum state (using a Pauli-Z feature map), enabling a quantum kernel layer to capture complex correlations.

The output of this quantum layer was then fed into a standard learning algorithm that identified which manufacturing parameters mattered most. As Usman says, this combined quantum–classical model pinpoints which fabrication steps to tune for optimal device performance.

In tests, the QKAR model beat seven top classical algorithms on the same task. It required only five qubits, making it feasible on today’s quantum machines. CSIRO’s Dr. Zeheng Wang notes that the quantum method found patterns classical models might miss in high-dimensional, small-data problems.

To validate the approach, the team fabricated new GaN devices using the model’s guidance; these chips showed improved performance. This confirmed that the quantum-assisted design generalized beyond its training data.

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How NASA Saved a Dying Camera Near Jupiter with Just Heat

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How NASA Saved a Dying Camera Near Jupiter with Just Heat

NASA’s Juno spacecraft, in orbit around Jupiter, had a huge problem when its JunoCam imager started to fail after sitting through the planet’s harsh radiation belts for so many orbits. Designed to only last through the initial few orbits, JunoCam astonishingly endured 34 orbits. Yet by the 47th orbit, the effects of radiation damage became visible, and by the 56th orbit, images were almost illegible. With few alternatives and time slipping away before a close flyby of Jupiter’s volcanic moon Io, engineers made a daring but creative gamble. Employing an annealing process, they sought to resuscitate the imager by warming it up—an experiment that proved successful.

Long-distance fix

According to NASA, JunoCam’s camera resides outside the spacecraft’s radiation-shielded interior and is extremely vulnerable. After several orbits, it started developing damage thought to be caused by a failing voltage regulator. From a distance of hundreds of millions of miles, the mission team implemented a last-ditch repair: annealing. The technique, which subjects materials to heat in order to heal microscopic defects, is poorly understood but has been succeeding in the lab. By heating the camera to 77°F, scientists wished to reorient its silicon-based parts.

At first, efforts were for naught, but only days before the December 2023 flyby of Io, the camera unexpectedly recovered—restoring close-to-original image quality just in time to photograph previously unseen volcanic landscapes.

Radiation Lessons for the Future

Though the camera showed renewed degradation during Juno’s 74th orbit, the successful restoration has led to broader applications. The team has since applied similar annealing strategies to other Juno instruments, helping them withstand harsh conditions longer. Juno’s findings are now informing spacecraft design across the board. “We’re learning how to build radiation-tolerant systems that benefit both defense and commercial satellites,” said Juno’s principal investigator Scott Bolton. These findings would inform future missions, such as those visiting outer planets or working in high-radiation environments near Earth, in the Van Allen belts. Juno’s mission continues to pay dividends with unexpected innovations—a lesson in how a small amount of heat can do wonders.

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NASA’s X-59 Moves Closer to First Flight with Advanced Taxi Tests and Augmented Vision

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NASA’s X-59 Moves Closer to First Flight with Advanced Taxi Tests and Augmented Vision

X-59 of NASA has been designed from the ground to fly at a faster speed of sound without making thunderous sonic booms, which are usually associated with supersonic flight. This 99-foot aircraft, which features a logically elongated design, jettisons the front windscreen and is now heading towards the runway. Pilots can see what is at the front through an augmented reality (AR) enabled closed-circuit camera system, which is termed by NASA as the External Vision System (XVS). NASA took control of an experimental aircraft and performed taxi tests on it during this month.

X-59’s Futuristic Design: Eliminating Sonic Booms with External Vision System

According to As per NASA, the test pilot Nils Larson, during the test, drove the X-59 at the runway by keeping a low speed. This is done to ensure the working of the steering and braking systems of the jet. Lockheed Martina and NASA would perform the taxi tests at high speed, in which the X-59 will move faster to make it to the speed at which it will go for takeoff.

Taxi tests are held at the U.S. Air Force’s Plant 42 facility in Palmdale, California. The contractors and the Air Force utilise the plant for manufacturing and testing the aircraft. Lockheed Martin has developed this aircraft, whose Skunk Works is found in Plant 42.

Taxi Tests at Plant 42: NASA and Lockheed Martin Prepare X-59 for First Flight

Some advanced aircraft of the U.S. military were developed to a certain extent at Plant 42, together with the B-2 Spirit, the F-22 Raptor, and the uncrewed RQ-170 Sentinel spy drone.

SOFIA airborne observatory aircraft, which is a flying telescope called Plant 42, home recently retired. The space shuttle of the agency is the world’s first reusable spacecraft; these were assembled and tested at the facility.

Such taxi tests have started over the last months. NASA worked in collaboration with the Japan Aerospace Exploration Agency for testing a scale model of the X-59 in the supersonic wind tunnel to measure the noise created under the aircraft.

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Unusual Plasma Waves Above Jupiter’s North Pole Can Possibly Be Explained

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Unusual Plasma Waves Above Jupiter’s North Pole Can Possibly Be Explained

In recent observations, NASA’s Juno spacecraft has significantly detected the presence of a variety of plasma waves. The emergence of these waves on Jupiter’s powerful magnetic field is projected to be surprising, as their existence was never marked in the planetary magnetospheres. However, scientists might have come out with an explanation. Furthermore, the current studies have been questioned by scientists surfacing the activity at the North Pole. The article below will exemplify the findings and shed light on the plasmas. 

Uncovering Mystery at Jupiter’s North Pole 

According to a paper published in the Physical Review Letters, the scientists have uncovered the explanation behind the presence of these strange waves. They mainly suspect that the formation of these waves lies behind their evolution as a plasma, which later transforms into something different. 

Inside Jupiter’s Plasmas and Their Variants 

Plasmas are best referred to as the waves that pass through the amalgamation of the charged particles in the planet’s magnetosphere.These plasma waves come across in two forms: One, Langmuir waves, which are high-pitched lights crafted with electrons, while the other, Alfven waves, are slower, formed by ions (heavy particles). 

About Juno’s Findings

As unveiled by the Juno, the findings turned out to be questionable after the scientists noted that in Jupiter’s far northern region, the plasma waves were relatively slower. The magnetic field is about 40 times stronger than the Earth’s, but scientists were shocked to witness the results as the waves were slower. To analyse this further, a team from the University of Minnesota, led by Robert Lysak, identified the possibility of Alfven waves transforming into Langmuir waves. Post studying the data extracted from the Juno, the researchers then began to compare the relationship between the plasma wave frequency and number. 

According to Lysak’s research team, near Jupiter’s north pole, there might be a potential pathway of Alfven waves, which are massive in numbers, transforming into Langmuir waves. Scientists are also predicting that the reason behind evolution might be strong electrons that are shooting upwards at a very high energy. This discovery was made in the year 2016. Considering the current findings, the researchers indicate that Jupiter’s magnetosphere may comprise a new type of plasma wave mode that occurs during high magnetic field strength. 

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