Aurelia Butler

The concept of quantum entanglement is emblematic of the gap between classical and quantum physics. Referring to a situation in which it is impossible to describe the physics of each photon separately, this key characteristic of quantum mechanics defies the classical expectation that each particle should have a reality of its own, which gravely concerned Einstein. Understanding the potential of this concept is essential for the realization of powerful new quantum technologies.
Developing such technologies will require the ability to freely generate a multi-photon quantum entangled state, and then to efficiently identify what kind of entangled state is present. However, when performing conventional quantum tomography, a method commonly used for state estimation, the number of measurements required grows exponentially with the number of photons, posing a significant data collection problem.
If available, an entangled measurement can identify the entangled state with a one-shot approach. Such a measurement for the Greenberger-Horne-Zeilinger — GHZ — entangled quantum state has been realized, but for the W state, the other representative entangled multi-photon state, it has been neither proposed nor discovered experimentally.
This motivated a team of researchers at Kyoto University and Hiroshima University to take on this challenge, ultimately succeeding in developing a new method of entangled measurement to identify the W state.
“More than 25 years after the initial proposal concerning the entangled measurement for GHZ states, we have finally obtained the entangled measurement for the W state as well, with genuine experimental demonstration for 3-photon W states,” says corresponding author Shigeki Takeuchi.
The team focused on the characteristics of the W state’s cyclic shift symmetry, and theoretically proposed a method to create an entangled measurement using a photonic quantum circuit that performs quantum Fourier transformation for the W state of any number of photons.
They created a device to demonstrate the proposed method for three photons using high-stability optical quantum circuits, which allowed the device to operate stably without active control for an extended period of time. By inserting three single photons into the device in appropriate polarization states, the team was able to demonstrate that the device can distinguish different types of three-photon W states, each corresponding to a specific non-classical correlation between the three input photons. The researchers were able to evaluate the fidelity of the entangled measurement, which is equal to the probability of obtaining the correct result for a pure W-state input.
This achievement opens the door for quantum teleportation, or the transfer of quantum information. It could also lead to new quantum communication protocols, the transfer of multi-photon quantum entangled states, and new methods for measurement-based quantum computing.
“In order to accelerate the research and development of quantum technologies, it is crucial to deepen our understanding of basic concepts to come up with innovative ideas,” says Takeuchi.
In the future, the team aims to apply their method to a larger-scale, more general multi-photon quantum entangled state, and plans to develop on-chip photonic quantum circuits for entangled measurements. More

Artificial intelligence (AI) systems are increasingly central to technology, powering everything from facial recognition to language translation. But as AI models grow more complex, they consume vast amounts of electricity — posing challenges for energy efficiency and sustainability. A new chip developed by researchers at the University of Florida could help address this issue by using light, rather than just electricity, to perform one of AI’s most power-hungry tasks. Their research is reported in Advanced Photonics.
The chip is designed to carry out convolution operations, a core function in machine learning that enables AI systems to detect patterns in images, video, and text. These operations typically require significant computing power. By integrating optical components directly onto a silicon chip, the researchers have created a system that performs convolutions using laser light and microscopic lenses — dramatically reducing energy consumption and speeding up processing.
“Performing a key machine learning computation at near zero energy is a leap forward for future AI systems,” said study leader Volker J. Sorger, the Rhines Endowed Professor in Semiconductor Photonics at the University of Florida. “This is critical to keep scaling up AI capabilities in years to come.”
In tests, the prototype chip classified handwritten digits with about 98 percent accuracy, comparable to traditional electronic chips. The system uses two sets of miniature Fresnel lenses — flat, ultrathin versions of the lenses found in lighthouses — fabricated using standard semiconductor manufacturing techniques. These lenses are narrower than a human hair and are etched directly onto the chip.
To perform a convolution, machine learning data is first converted into laser light on the chip. The light passes through the Fresnel lenses, which carry out the mathematical transformation. The result is then converted back into a digital signal to complete the AI task.
“This is the first time anyone has put this type of optical computation on a chip and applied it to an AI neural network,” said Hangbo Yang, a research associate professor in Sorger’s group at UF and co-author of the study.
The team also demonstrated that the chip could process multiple data streams simultaneously by using lasers of different colors — a technique known as wavelength multiplexing. “We can have multiple wavelengths, or colors, of light passing through the lens at the same time,” Yang said. “That’s a key advantage of photonics.”
The research was conducted in collaboration with the Florida Semiconductor Institute, UCLA, and George Washington University. Sorger noted that chip manufacturers such as NVIDIA already use optical elements in some parts of their AI systems, which could make it easier to integrate this new technology.
“In the near future, chip-based optics will become a key part of every AI chip we use daily,” Sorger said. “And optical AI computing is next.” More

What do children’s building blocks and quantum computing have in common? The answer is modularity. It is difficult for scientists to build quantum computers monolithically – that is, as a single large unit. Quantum computing relies on the manipulation of millions of information units called qubits, but these qubits are difficult to assemble. The solution? Finding modular ways to construct quantum computers. Like plastic children’s bricks that lock together to create larger, more intricate structures, scientists can build smaller, higher quality modules and string them together to form a comprehensive system.
Recognizing the potential of these modular systems, researchers from The Grainger College of Engineering at the University of Illinois Urbana-Champaign have presented an enhanced approach to scalable quantum computing by demonstrating a viable and high-performance modular architecture for superconducting quantum processors. Their work, published in Nature Electronics, expands on previous modular designs and paves the way toward scalable, fault-tolerant and reconfigurable quantum computing systems.
Monolithic superconducting quantum systems are limited in size and fidelity, which predicts scientists’ rate of success in performing logical operations. A fidelity of one signifies no mistakes; as such, researchers want to achieve a fidelity as close to one as possible. Compared to these limited monolithic systems, modularity enables system scalability, hardware upgrades, and tolerance to variability, making it a more attractive option for building system networks.
“We’ve created an engineering-friendly way of achieving modularity with superconducting qubits,” said Wolfgang Pfaff, an assistant professor of physics and the senior author of the paper. “Can I build a system that I can bring together, allowing me to manipulate two qubits jointly so as to create entanglement or gate operations between them? Can we do that at a very high quality? And can we also have it such that we can take it apart and put it back together? Typically, we only find out that something went wrong after putting it together. So we would really like to have the ability to reconfigure the system later.”
By constructing a system where two devices are connected with superconducting coaxial cables to link qubits across modules, Pfaff’s team demonstrated ~99% SWAP gate fidelity, representing less than 1% loss. Their ability to connect and reconfigure separate devices with a cable while retaining high quality provides novel insight to the field in designing communication protocols.
“Finding an approach that works has taken a while for our field,” Pfaff said. “Many groups have figured out that what we really want is this ability to stitch bigger and bigger things together through cables, and at the same time reach numbers that are good enough to justify scaling. The problem was just finding the right combination of tools.”
Moving forward, the Grainger engineers will turn their focus toward scalability, attempting to connect more than two devices together while retaining the ability to check for errors.
“We have good performance,” Pfaff said. “Now we need to put it to the test and say, is it really going forward? Does it really make sense?” More

The age of artificial intelligence (AI) has transformed our interactions, but threatens human dignity on a worldwide scale, according to a study led by Charles Darwin University (CDU).
Study lead author Dr Maria Randazzo, an academic from CDU’s School of Law, found the technology was reshaping Western legal and ethical landscapes at unprecedented speed but was undermining democratic values and deepening systemic biases.
Dr Randazzo said current regulation failed to prioritize fundamental human rights and freedoms such as privacy, anti-discrimination, user autonomy, and intellectual property rights – mainly thanks to the untraceable nature of many algorithmic models.
Calling this lack of transparency a “black box problem,” Dr Randazzo said decisions made by deep-learning or machine-learning processes were impossible for humans to trace, making it difficult for users to determine if and why an AI model has violated their rights and dignity and seek justice where necessary.
“This is a very significant issue that is only going to get worse without adequate regulation,” Dr Randazzo said.
“AI is not intelligent in any human sense at all. It is a triumph in engineering, not in cognitive behavior.
“It has no clue what it’s doing or why – there’s no thought process as a human would understand it, just pattern recognition stripped of embodiment, memory, empathy, or wisdom.”
Currently, the world’s three dominant digital powers – the United States, China, and the European Union – are taking markedly different approaches to AI, leaning on market-centric, state-centric, and human-centric models respectively.

Dr Randazzo said the EU’s human-centric approach is the preferred path to protect human dignity but without a global commitment to this goal, even that approach falls short.
“Globally, if we don’t anchor AI development to what makes us human – our capacity to choose, to feel, to reason with care, to empathy and compassion – we risk creating systems that devalue and flatten humanity into data points, rather than improve the human condition,” she said.
“Humankind must not be treated as a means to an end.”
“Human dignity in the age of Artificial Intelligence: an overview of legal issues and regulatory regimes” was published in the Australian Journal of Human Rights.
The paper is the first in a trilogy Dr Randazzo will produce on the topic. More

How can data be processed at lightning speed, or electricity conducted without loss? To achieve this, scientists and industry alike are turning to quantum materials, governed by the laws of the infinitesimal. Designing such materials requires a detailed understanding of atomic phenomena, much of which remains unexplored. A team from the University of Geneva (UNIGE), in collaboration with the University of Salerno and the CNR-SPIN Institute (Italy), has taken a major step forward by uncovering a hidden geometry — until now purely theoretical — that distorts the trajectories of electrons in much the same way gravity bends the path of light. This work, published in Science, opens new avenues for quantum electronics.
Future technologies depend on high-performance materials with unprecedented properties, rooted in quantum physics. At the heart of this revolution lies the study of matter at the microscopic scale — the very essence of quantum physics. In the past century, exploring atoms, electrons and photons within materials gave rise to transistors and, ultimately, to modern computing.
New quantum phenomena that defy established models are still being discovered today. Recent studies suggest the possible emergence of a geometry within certain materials when vast numbers of particles are observed. This geometry appears to distort the trajectories of electrons in these materials — much like Einstein’s gravity bends the path of light.
From theory to observation
Known as quantum metric, this geometry reflects the curvature of the quantum space in which electrons move. It plays a crucial role in many phenomena at the microscopic scale of matter. Yet detecting its presence and effects remains a major challenge.
”The concept of quantum metric dates back about 20 years, but for a long time it was regarded purely as a theoretical construct. Only in recent years have scientists begun to explore its tangible effects on the properties of matter,” explains Andrea Caviglia, full professor and director of the Department of Quantum Matter Physics at the UNIGE Faculty of Science.
Thanks to recent work, the team led by the UNIGE researcher, in collaboration with Carmine Ortix, associate professor in the Department of Physics at the University of Salerno, has detected quantum metric at the interface between two oxides — strontium titanate and lanthanum aluminate — a well-known quantum material. ”Its presence can be revealed by observing how electron trajectories are distorted under the combined influence of quantum metric and intense magnetic fields applied to solids,” explains Giacomo Sala, research associate in the Department of Quantum Matter Physics at the UNIGE Faculty of Science and lead author of the study.
Unlocking Future Technologies
Observing this phenomenon makes it possible to characterise a material’s optical, electronic and transport properties with greater precision. The research team also demonstrates that quantum metric is an intrinsic property of many materials — contrary to previous assumptions.
”These discoveries open up new avenues for exploring and harnessing quantum geometry in a wide range of materials, with major implications for future electronics operating at terahertz frequencies (a trillion hertz), as well as for superconductivity and light-matter interactions,” concludes Andrea Caviglia. More