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100 kilometers of quantum-encrypted transfer



100 kilometers of quantum-encrypted transfer

Researchers at DTU have successfully distributed a quantum-secure key using a method called Continuous Variable Quantum Key Distribution (CV QKD). The researchers have managed to make the method work over a record 100 km distance — the longest distance ever achieved using the CV QKD method. The advantage of the method is that it can be applied to the existing Internet infrastructure.

Quantum computers threaten existing algorithm-based encryptions, which currently secure data transfers against eavesdropping and surveillance. They are not yet powerful enough to break them, but it’s a matter of time. If a quantum computer succeeds in figuring out the most secure algorithms, it leaves an open door to all data connected via the internet. This has accelerated the development of a new encryption method based on the principles of quantum physics.

But to succeed, researchers must overcome one of the challenges of quantum mechanics — ensuring consistency over longer distances. Continuous Variable Quantum Key Distribution has so far worked best over short distances.

“We have achieved a wide range of improvements, especially regarding the loss of photons along the way. In this experiment, published in Science Advances, we securely distributed a quantum-encrypted key 100 kilometres via fibre optic cable. This is a record distance with this method,” says Tobias Gehring, an associate professor at DTU, who, together with a group of researchers at DTU, aims to be able to distribute quantum-encrypted information around the world via the internet.

Secret keys from quantum states of light

“When data needs to be sent from A to B, it must be protected. Encryption combines data with a secure key distributed between sender and receiver so both can access the data. A third party must not be able to figure out the key while it is being transmitted; otherwise, the encryption will be compromised. Key exchange is, therefore, essential in encrypting data.

Quantum Key Distribution (QKD) is an advanced technology that researchers are working on for crucial exchanges. The technology ensures the exchange of cryptographic keys by using light from quantum mechanical particles called photons.

When a sender sends information encoded in photons, the quantum mechanical properties of the photons are exploited to create a unique key for the sender and receiver. Attempts by others to measure or observe photons in a quantum state will instantly change their state. Therefore, it is physically only possible to measure light by disturbing the signal.

“It is impossible to make a copy of a quantum state, as when making a copy of an A4 sheet — if you try, it will be an inferior copy. That’s what ensures that it is not possible to copy the key. This can protect critical infrastructure such as health records and the financial sector from being hacked,” explains Tobias Gehring.

Works via existing infrastructure

The Continuous Variable Quantum Key Distribution (CV QKD) technology can be integrated into the existing internet infrastructure.

“The advantage of using this technology is that we can build a system that resembles what optical communication already relies on.”

The backbone of the internet is optical communication. It works by sending data via infrared light running through optical fibres. They function as light guides laid in cables, ensuring we can send data worldwide. Data can be sent faster and over longer distances via fibre optic cables, and light signals are less susceptible to interference, which is called noise in technical terms.

“It is a standard technology that has been used for a long time. So, you don’t need to invent anything new to be able to use it to distribute quantum keys, and it can make implementation significantly cheaper. And we can operate at room temperature,” explains Tobias Gehring, adding:

“But CV QKD technology works best over shorter distances. Our task is to increase the distance. And the 100 kilometres is a big step in the right direction.”

Noise, Errors, and Assistance from Machine Learning

The researchers succeeded in increasing the distance by addressing three factors that limit their system in exchanging the quantum-encrypted keys over longer distances:

Machine learning provided earlier measurements of the disturbances affecting the system. Noise, as these disturbances are called, can arise, for example, from electromagnetic radiation, which can distort or destroy the quantum states being transmitted. The earlier detection of the noise made it possible to reduce its corresponding effect more effectively.

Furthermore, the researchers have become better at correcting errors that can occur along the way, which can be caused by noise, interference, or imperfections in the hardware.

“In our upcoming work, we will use the technology to establish a secure communication network between Danish ministries to secure their communication. We will also attempt to generate secret keys between, for example, Copenhagen and Odense to enable companies with branches in both cities to establish quantum-safe communication,” Tobias Gehring says.


We don’t exactly know what happens — yet.

Quantum Key Distribution was developed as a concept in 1984 by Bennett and Brassard, while the Canadian physicist and computer pioneer Artur Ekert and his colleagues carried out the first practical implementation of QKD in 1992. Their contribution has been crucial for developing modern QKD protocols, a set of rules, procedures, or conventions that determine how a device should perform a task.

Quantum Key Distribution (QKD) is based on a fundamental uncertainty in copying photons in a quantum state. Photons are the quantum mechanical particles that light consists of.

Photons in a quantum state carry a fundamental uncertainty, meaning it is not possible with certainty to know whether the photon is one or several photons collected in the given state, also called coherent photons. This prevents a hacker from measuring the number of photons, making it impossible to make an exact copy of a state.

They also carry a fundamental randomness because photons are in multiple states simultaneously, also called superposition. The superposition of photons collapses into a random state when the measurement occurs. This makes it impossible to measure precisely which phase they are in while in superposition.

Together, it becomes nearly impossible for a hacker to copy a key without introducing errors, and the system will know if a hacker is trying to break in and can shut down immediately. In other words, it becomes impossible for a hacker to first steal the key and then to avoid the door locking as he tries to put the key in the lock.

Continuous Variable Quantum Key Distribution (CV QKD) focuses on measuring the smooth properties of quantum states in photons. It can be compared to conveying information in a stream of all the nuances of colours instead of conveying information step by step in each colour.


The Innovation Fund Denmark, the Danish National Research Foundation, the European Union’s Horizon Europe research and innovation program, the Carlsberg Foundation, and the Czech Science Foundation support the project.

The research group comprises Adnan A.E. Hajomer, Nitin Jain, Hou-Man Chin, Ivan Derkach, Ulrik L. Andersen, and Tobias Gehring.

The Danish Quantum Communication Infrastructure (QCI.DK) targets the first deployment of Danish quantum communication technologies in a versatile network supporting real-life Quantum Key Distribution applications.

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This alloy is kinky




This alloy is kinky

Researchers have uncovered a remarkable metal alloy that won’t crack at extreme temperatures due to kinking, or bending, of crystals in the alloy at the atomic level.  A metal alloy composed of niobium, tantalum, titanium, and hafnium has shocked materials scientists with its impressive strength and toughness at both extremely hot and cold temperatures, a combination of properties that seemed so far to be nearly impossible to achieve. In this context, strength is defined as how much force a material can withstand before it is permanently deformed from its original shape, and toughness is its resistance to fracturing (cracking). The alloy’s resilience to bending and fracture across an enormous range of conditions could open the door for a novel class of materials for next-generation engines that can operate at higher efficiencies.

The team, led by Robert Ritchie at Lawrence Berkeley National Laboratory (Berkeley Lab) and UC Berkeley, in collaboration with the groups led by professors Diran Apelian at UC Irvine and Enrique Lavernia at Texas A&M University, discovered the alloy’s surprising properties and then figured out how they arise from interactions in the atomic structure. Their work is described in a study that was published April 11, 2024 in Science.

“The efficiency of converting heat to electricity or thrust is determined by the temperature at which fuel is burned — the hotter, the better. However, the operating temperature is limited by the structural materials which must withstand it,” said first author David Cook, a Ph.D. student in Ritchie’s lab. “We have exhausted the ability to further optimize the materials we currently use at high temperatures, and there’s a big need for novel metallic materials. That’s what this alloy shows promise in.”

The alloy in this study is from a new class of metals known as refractory high or medium entropy alloys (RHEAs/RMEAs). Most of the metals we see in commercial or industrial applications are alloys made of one main metal mixed with small quantities of other elements, but RHEAs and RMEAs are made by mixing near-equal quantities of metallic elements with very high melting temperatures, which gives them unique properties that scientists are still unraveling. Ritchie’s group has been investigating these alloys for several years because of their potential for high-temperature applications.

“Our team has done previous work on RHEAs and RMEAs and we have found that these materials are very strong, but generally possess extremely low fracture toughness, which is why we were shocked when this alloy displayed exceptionally high toughness,” said co-corresponding author Punit Kumar, a postdoctoral researcher in the group.

According to Cook, most RMEAs have a fracture toughness less than 10 MPa√m, which makes them some of the most brittle metals on record. The best cryogenic steels, specially engineered to resist fracture, are about 20 times tougher than these materials. Yet the niobium, tantalum, titanium, and hafnium (Nb45Ta25Ti15Hf15) RMEA alloy was able to beat even the cryogenic steel, clocking in at over 25 times tougher than typical RMEAs at room temperature.

But engines don’t operate at room temperature. The scientists evaluated strength and toughness at five temperatures total: -196°C (the temperature of liquid nitrogen), 25°C (room temperature), 800°C, 950°C, and 1200°C. The last temperature is about 1/5 the surface temperature of the sun.

The team found that the alloy had the highest strength in the cold and became slightly weaker as the temperature rose, but still boasted impressive figures throughout the wide range. The fracture toughness, which is calculated from how much force it takes to propagate an existing crack in a material, was high at all temperatures.

Unraveling the atomic arrangements

Almost all metallic alloys are crystalline, meaning that the atoms inside the material are arranged in repeating units. However, no crystal is perfect, they all contain defects. The most prominent defect that moves is called the dislocation, which is an unfinished plane of atoms in the crystal. When force is applied to a metal it causes many dislocations to move to accommodate the shape change. For example, when you bend a paper clip which is made of aluminum, the movement of dislocations inside the paper clip accommodates the shape change. However, the movement of dislocations becomes more difficult at lower temperatures and as a result many materials become brittle at low temperatures because dislocations cannot move. This is why the steel hull of the Titanic fractured when it hit an iceberg. Elements with high melting temperatures and their alloys take this to the extreme, with many remaining brittle up to even 800°C. However, this RMEA bucks the trend, withstanding snapping even at temperatures as low as liquid nitrogen (-196°C).

To understand what was happening inside the remarkable metal, co-investigator Andrew Minor and his team analyzed the stressed samples, alongside unbent and uncracked control samples, using four-dimensional scanning transmission electron microscopy (4D-STEM) and scanning transmission electron microscopy (STEM) at the National Center for Electron Microscopy, part of Berkeley Lab’s Molecular Foundry.

The electron microscopy data revealed that the alloy’s unusual toughness comes from an unexpected side effect of a rare defect called a kink band. Kink bands form in a crystal when an applied force causes strips of the crystal to collapse on themselves and abruptly bend. The direction in which the crystal bends in these strips increases the force that dislocations feel, causing them to move more easily. On the bulk level, this phenomenon causes the material to soften (meaning that less force has to be applied to the material as it is deformed). The team knew from past research that kink bands formed easily in RMEAs, but assumed that the softening effect would make the material less tough by making it easier for a crack to spread through the lattice. But in reality, this is not the case.

“We show, for the first time, that in the presence of a sharp crack between atoms, kink bands actually resist the propagation of a crack by distributing damage away from it, preventing fracture and leading to extraordinarily high fracture toughness,” said Cook.

The Nb45Ta25Ti15Hf15 alloy will need to undergo a lot more fundamental research and engineering testing before anything like a jet plane turbine or SpaceX rocket nozzle is made from it, said Ritchie, because mechanical engineers rightfully require a deep understanding of how their materials perform before they use them in the real world. However, this study indicates that the metal has potential to build the engines of the future.

This research was conducted by David H. Cook, Punit Kumar, Madelyn I. Payne, Calvin H. Belcher, Pedro Borges, Wenqing Wang, Flynn Walsh, Zehao Li, Arun Devaraj, Mingwei Zhang, Mark Asta, Andrew M. Minor, Enrique J. Lavernia, Diran Apelian, and Robert O. Ritchie, scientists at Berkeley Lab, UC Berkeley, Pacific Northwest National Laboratory, and UC Irvine, with funding from the Department of Energy (DOE) Office of Science. Experimental and computational analysis was conducted at the Molecular Foundry and the National Energy Research Scientific Computing Center — both are DOE Office of Science user facilities.

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Giant galactic explosion exposes galaxy pollution in action




Giant galactic explosion exposes galaxy pollution in action

A team of international researchers studied galaxy NGC 4383, in the nearby Virgo cluster, revealing a gas outflow so large that it would take 20,000 years for light to travel from one side to the other.

The discovery was published today in the journal Monthly Notices of the Royal Astronomical Society.

Lead author Dr Adam Watts, from The University of Western Australia node at the International Centre for Radio Astronomy Research (ICRAR), said the outflow was the result of powerful stellar explosions in the central regions of the galaxy that could eject enormous amounts of hydrogen and heavier elements.

The mass of gas ejected is equivalent to more than 50 million Suns.

“Very little is known about the physics of outflows and their properties because outflows are very hard to detect,” Dr Watts said.

“The ejected gas is quite rich in heavy elements giving us a unique view of the complex process of mixing between hydrogen and metals in the outflowing gas.

“In this particular case, we detected oxygen, nitrogen, sulphur and many other chemical elements.”

Gas outflows are crucial to regulate how fast and for how long galaxies can keep forming stars. The gas ejected by these explosions pollutes the space between stars within a galaxy, and even between galaxies, and can float in the intergalactic medium forever.

The high-resolution map was produced with data from the MAUVE survey, co-led by ICRAR researchers Professors Barbara Catinella and Luca Cortese, who were also co-authors of the study.

The survey used the MUSE Integral Field Spectrograph on the European Southern Observatory’s Very Large Telescope, located in northern Chile.

“We designed MAUVE to investigate how physical processes such as gas outflows help stop star formation in galaxies,” Professor Catinella said.

“NGC 4383 was our first target, as we suspected something very interesting was happening, but the data exceeded all our expectations.

“We hope that in the future, MAUVE observations reveal the importance of gas outflows in the local Universe with exquisite detail.”

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AI and physics combine to reveal the 3D structure of a flare erupting around a black hole




AI and physics combine to reveal the 3D structure of a flare erupting around a black hole

Scientists believe the environment immediately surrounding a black hole is tumultuous, featuring hot magnetized gas that spirals in a disk at tremendous speeds and temperatures. Astronomical observations show that within such a disk, mysterious flares occur up to several times a day, temporarily brightening and then fading away. Now a team led by Caltech scientists has used telescope data and an artificial intelligence (AI) computer-vision technique to recover the first three-dimensional video showing what such flares could look like around Sagittarius A* (Sgr A*, pronounced sadge-ay-star), the supermassive black hole at the heart of our own Milky Way galaxy.

The 3D flare structure features two bright, compact features located about 75 million kilometers (or half the distance between Earth and the Sun) from the center of the black hole. It is based on data collected by the Atacama Large Millimeter Array (ALMA) in Chile over a period of 100 minutes directly after an eruption seen in X-ray data on April 11, 2017.

“This is the first three-dimensional reconstruction of gas rotating close to a black hole,” says Katie Bouman, assistant professor of computing and mathematical sciences, electrical engineering and astronomy at Caltech, whose group led the effort described in a new paper in Nature Astronomy.

Aviad Levis, a postdoctoral scholar in Bouman’s group and lead author on the new paper, emphasizes that while the video is not a simulation, it is also not a direct recording of events as they took place. “It is a reconstruction based on our models of black hole physics. There is still a lot of uncertainty associated with it because it relies on these models being accurate,” he says.

Using AI informed by physics to figure out possible 3D structures

To reconstruct the 3D image, the team had to develop new computational imaging tools that could, for example, account for the bending of light due to the curvature of space-time around objects of enormous gravity, such as a black hole.

The multidisciplinary team first considered if it would be possible to create a 3D video of flares around a black hole in June 2021. The Event Horizon Telescope (EHT) Collaboration, of which Bouman and Levis are members, had already published the first image of the supermassive black hole at the core of a distant galaxy, called M87, and was working to do the same with EHT data from Sgr A*. Pratul Srinivasan of Google Research, a co-author on the new paper, was at the time visiting the team at Caltech. He had helped develop a technique known as neural radiance fields (NeRF) that was then just starting to be used by researchers; it has since had a huge impact on computer graphics. NeRF uses deep learning to create a 3D representation of a scene based on 2D images. It provides a way to observe scenes from different angles, even when only limited views of the scene are available.

The team wondered if, by building on these recent developments in neural network representations, they could reconstruct the 3D environment around a black hole. Their big challenge: From Earth, as anywhere, we only get a single viewpoint of the black hole.

The team thought that they might be able to overcome this problem because gas behaves in a somewhat predictable way as it moves around the black hole. Consider the analogy of trying to capture a 3D image of a child wearing an inner tube around their waist. To capture such an image with the traditional NeRF method, you would need photos taken from multiple angles while the child remained stationary. But in theory, you could ask the child to rotate while the photographer remained stationary taking pictures. The timed snapshots, combined with information about the child’s rotation speed, could be used to reconstruct the 3D scene equally well. Similarly, by leveraging knowledge of how gas moves at different distances from a black hole, the researchers aimed to solve the 3D flare reconstruction problem with measurements taken from Earth over time.

With this insight in hand, the team built a version of NeRF that takes into account how gas moves around black holes. But it also needed to consider how light bends around massive objects such as black holes. Under the guidance of co-author Andrew Chael of Princeton University, the team developed a computer model to simulate this bending, also known as gravitational lensing.

With these considerations in place, the new version of NeRF was able to recover the structure of orbiting bright features around the event horizon of a black hole. Indeed, the initial proof-of-concept showed promising results on synthetic data.

A flare around Sgr A* to study

But the team needed some real data. That’s where ALMA came in. The EHT’s now famous image of Sgr A* was based on data collected on April 6-7, 2017, which were relatively calm days in the environment surrounding the black hole. But astronomers detected an explosive and sudden brightening in the surroundings just a few days later, on April 11. When team member Maciek Wielgus of the Max Planck Institute for Radio Astronomy in Germany went back to the ALMA data from that day, he noticed a signal with a period matching the time it would take for a bright spot within the disk to complete an orbit around Sgr A*. The team set out to recover the 3D structure of that brightening around Sgr A*.

ALMA is one of the most powerful radio telescopes in the world. However, because of the vast distance to the galactic center (more than 26,000 light-years), even ALMA does not have the resolution to see Sgr A*’s immediate surroundings. What ALMA measures are light curves, which are essentially videos of a single flickering pixel, which are created by collecting all of the radio-wavelength light detected by the telescope for each moment of observation.

Recovering a 3D volume from a single-pixel video might seem impossible. However, by leveraging an additional piece of information about the physics that are expected for the disk around black holes, the team was able to get around the lack of spatial information in the ALMA data.

Strongly polarized light from the flares provided clues

ALMA doesn’t just capture a single light curve. In fact, it provides several such “videos” for each observation because the telescope records data relating to different polarization states of light. Like wavelength and intensity, polarization is a fundamental property of light and represents which direction the electric component of a light wave is oriented with respect to the wave’s general direction of travel. “What we get from ALMA is two polarized single-pixel videos,” says Bouman, who is also a Rosenberg Scholar and a Heritage Medical Research Institute Investigator. “That polarized light is actually really, really informative.”

Recent theoretical studies suggest that hot spots forming within the gas are strongly polarized, meaning the light waves coming from these hot spots have a distinct preferred orientation direction. This is in contrast to the rest of the gas, which has a more random or scrambled orientation. By gathering the different polarization measurements, the ALMA data gave the scientists information that could help localize where the emission was coming from in 3D space.

Introducing Orbital Polarimetric Tomography

To figure out a likely 3D structure that explained the observations, the team developed an updated version of its method that not only incorporated the physics of light bending and dynamics around a black hole but also the polarized emission expected in hot spots orbiting a black hole. In this technique, each potential flare structure is represented as a continuous volume using a neural network. This allows the researchers to computationally progress the initial 3D structure of a hotspot over time as it orbits the black hole to create a whole light curve. They could then solve for the best initial 3D structure that, when progressed in time according to black hole physics, matched the ALMA observations.

The result is a video showing the clockwise movement of two compact bright regions that trace a path around the black hole. “This is very exciting,” says Bouman. “It didn’t have to come out this way. There could have been arbitrary brightness scattered throughout the volume. The fact that this looks a lot like the flares that computer simulations of black holes predict is very exciting.”

Levis says that the work was uniquely interdisciplinary: “You have a partnership between computer scientists and astrophysicists, which is uniquely synergetic. Together, we developed something that is cutting edge in both fields — both the development of numerical codes that model how light propagates around black holes and the computational imaging work that we did.”

The scientists note that this is just the beginning for this exciting technology. “This is a really interesting application of how AI and physics can come together to reveal something that is otherwise unseen,” says Levis. “We hope that astronomers could use it on other rich time-series data to shed light on complex dynamics of other such events and to draw new conclusions.”

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