In the context of quantum physics, the term “duality” refers to transformations that link apparently distinct physical theories, often unveiling hidden symmetries. Some recent studies have been aimed at understanding and implementing duality transformations, as this could aid the study of quantum states and symmetry-protected phenomena.
Researchers at the University of Cambridge, Ghent University, Institut des Hautes Études Scientifiques and the University of Sydney recently demonstrated the implementation of dualities in symmetric 1-dimensional (1D) quantum lattice models, outlining a method to turn duality operators into unitary linear-depth quantum circuits.
Their paper, published in Physical Review Letters, is part of a larger research effort aimed at better understanding symmetries and dualities in quantum lattice models.
The quantum black hole with (almost) no equations by Professor Gerard ‘t Hooft.
How to reconcile Einstein’s theory of General Relativity with Quantum Mechanics is a notorious problem. Special relativity, on the other hand, was united completely with quantum mechanics when the Standard Model, including Higgs mechanism, was formulated as a relativistic quantum field theory.
Since Stephen Hawking shed new light on quantum mechanical effects in black holes, it was hoped that black holes may be used to obtain a more complete picture of Nature’s laws in that domain, but he arrived at claims that are difficult to use in this respect. Was he right? What happens with information sent into a black hole?
The discussion is not over; in this lecture it is shown that a mild conical singularity at the black hole horizon may be inevitable, while it doubles the temperature of quantum radiation emitted by a black hole, we illustrate the situation with only few equations.
About the Higgs Lecture.
The Faculty of Natural, Mathematical & Engineering Sciences is delighted to present the Annual Higgs Lecture. The inaugural Annual Higgs Lecture was delivered in December 2012 by its name bearer, Professor Peter Higgs, who returned to King’s after graduating in 1950 with a first-class honours degree in Physics, and who famously predicted the Higgs Boson particle.
In this talk, Klaus Mainzer explores the connections between the Leibniz’ Monadology, the structure and function of the brain, and recent developments in quantum computing. He reflects on the nature of complexity, intelligence, and the possibilities of quantum information technologies.
Machine learning automates the control of a large and highly connected array of semiconductor quantum dots.
Even the most compelling experiment can become boring when repeated dozens of times. Therefore, rather than using artificial intelligence to automate the creative and insightful aspects of science and engineering, automation should focus instead on improving the productivity of researchers. In that vein, Justyna Zwolak of the National Institute of Standards and Technology in Maryland and her colleagues have demonstrated software for automating standard parts of experiments on semiconductor quantum-dot qubits [1]. The feat is a step toward the fully automated calibration of quantum processors. Larger and more challenging spin and quantum computing experiments will likely also benefit from it [2].
Semiconductor technology enables the fabrication of quantum-mechanical devices with unparalleled control [3], performance [4], reproducibility [5], and large-scale integration [6]—exactly what is needed for a highly scalable quantum computer. Classical digital logic represents bits as localized volumes of high or low electric potential, and the semiconductor industry has developed efficient ways to control such potentials—exactly what is needed for the operation of qubits based on quantum dots. Silicon or germanium are nearly ideal semiconductors to host qubits encoded in the spin state of electrons or electron vacancies (holes) confined in an electric potential formed in a quantum dot by transistor-like gate electrodes.
Researchers at Swansea University have discovered a way to use mirrors to dramatically reduce the quantum noise that disturbs tiny particles—a breakthrough that might seem magical but is rooted in quantum physics.
When scientists measure extremely small objects, such as nanoparticles, they face a difficult challenge: simply observing these particles disturbs them. This happens because photons, particles of light, used for measurement “kick” the tiny particles they hit, an effect known as “backaction.”
In a new study published in Physical Review Research, a team from the university’s Physics Department has revealed a remarkable connection, that this relationship works both ways.
Swinburne researchers have discovered unexpected and entirely new quantum behaviors that only occur in one-dimensional systems, such as electrical current. Their new paper, published in Physical Review Letters, explores a fundamental question in quantum physics: what happens when a single “impurity” particle, such as an atom or electron, is introduced into a tightly packed crowd of identical particles.
Nearly every material in the world contains small imperfections or extra particles; understanding how these “outsiders” interact with their environment is key to figuring out how materials conduct electricity, create light, or respond to external forces.
A team at the Center for Quantum Technology Theory at Swinburne studied this in the setting of a one-dimensional optical lattice (a kind of artificial crystal made with laser light) using a well-known theoretical framework called the Fermi-Hubbard model.
Recently, a group of researchers discovered a novel way to achieve spin-valve effects using kagome quantum magnets.
“This approach uses a prototype device made from the kagome magnet TmMn₆Sn₆,” explained Associate Prof. XU Xitong, “This breakthrough eliminates the need for the complex fabrication techniques traditionally required by spin-valve structures.”
The findings were published in Nature Communications. The team was led by Prof. Qu Zhe from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, together with Prof. Chang Tay-Rong from National Cheng Kung University.
A quantum computer can solve optimization problems faster than classical supercomputers, a process known as “quantum advantage” and demonstrated by a USC researcher in a paper recently published in Physical Review Letters.
The study shows how quantum annealing, a specialized form of quantum computing, outperforms the best current classical algorithms when searching for near-optimal solutions to complex problems.
“The way quantum annealing works is by finding low-energy states in quantum systems, which correspond to optimal or near-optimal solutions to the problems being solved,” said Daniel Lidar, corresponding author of the study and professor of electrical and computer engineering, chemistry, and physics and astronomy at the USC Viterbi School of Engineering and the USC Dornsife College of Letters, Arts and Sciences.
*Apply to join Foresight Intelligent Cooperation program:* https://foresight.org/intelligent-cooperation/ A group of scientists, engineers, and entrepreneurs in computer science, ML, cryptocommerce, and related fields who leverage those technologies to improve voluntary cooperation across humans, and ultimately AIs.
*Maarten Boudry | Will Humanity Be Subjugated by Superintelligent AIs?* Abstract: Some people are worried that if we ever create superintelligent AIs, they might turn against us—trying to subjugate humanity, wrest control, and grab resources, much like living creatures shaped by evolution. Dan Hendrycks from the Center for AI Safety has argued that AI systems are already undergoing a form of natural selection, facing ruthless market competition in the current AI race. Will this endow them with the instinctive drives for self-preservation and dominance typical of evolved creatures? In this talk, I push back against this evolutionary doom scenario, using the framework of “Darwinian spaces” by Peter Godfrey-Smith. A better analogy for AI evolution might be the domestication of animals. Just as humans have bred dogs to be friendly and obedient, we might shape AIs in similar ways, selecting for desirable traits like helpfulness and non-aggression. Even in a highly competitive AI race, AIs are unlikely to become selfish or power-hungry. That said, we do agree with the AI doomers on one point: if we allow AIs to “go feral” and be subjected to truly blind evolution—like wild animals competing in nature—that could become very dangerous.
Bio: Dr. Maarten Boudry is a philosopher of science and first holder of the Etienne Vermeersch Chair of Critical Thinking at Ghent University. He published over 50 academic papers and two edited volumes: Science Unlimited? (2018) and Philosophy of Pseudoscience (2013). He wrote six trade books in Dutch on science and philosophy, the latest one being The Betrayal of Enlightenment (Het verraad aan de verlichting, 2025). He’s also a Roots of Progress fellow and a regular contributor to Quillette, The Conversation, The Independent and Human Progress. Substack for English writings: maartenboudry.substack.com.
Bio: Simon Friederich is an associate professor of philosophy of science at the University of Groningen, the Netherlands. He is currently focused on the philosophy of quantum theory, trying to solve the quantum measurement problem along the lines envisioned by Einstein before advanced AI makes his efforts redundant. He has also worked on the philosophy of technology, notably on nuclear energy, sustainability, and advanced AI. His thoughts on these topics have been featured in German and Dutch media. With his wife and five kids he lives in a village in the North of the Netherlands.
RIKEN physicists have devised a theoretical method to probe elusive Majorana fermions in topological superconductors by leveraging their unique electromagnetic responses, paving the way for breakthroughs in quantum material science. A new theoretical approach for exploring exotic particles on the
