“They shine thanks to nuclear fusion in their cores, but once the star has burned through progressively heavier atoms—right up to the point where further fusion no longer yields energy—the core collapses. At that point, the star collapses because gravity is no longer counterbalanced; the rapid contraction raises the internal pressure dramatically and triggers the explosion.”
The first hours and days after the blast preserve direct clues to the progenitor system—information that helps distinguish competing explosion models, estimate critical parameters, and study the local environment. “The sooner we see them, the better,” Galbany notes.
Historically, obtaining such early data was difficult because most supernovae were discovered days or weeks after the explosion. Modern wide-field, high-cadence surveys—covering large swaths of sky and revisiting them frequently—are changing that picture and allowing discoveries within mere hours or days.
There are high hopes for quantum computers: they are supposed to perform specific calculations much faster than current supercomputers and, therefore, solve scientific and practical problems that are insurmountable for ordinary computers. The centerpiece of a quantum computer is the quantum bit, qubit for short, which can be realized in different ways—for instance, using the energy levels of atoms or the spins of electrons.
When making such qubits, however, researchers face a dilemma. On the one hand, a qubit needs to be isolated from its environment as much as possible. Otherwise, its quantum superpositions decay in a short time and the quantum calculations are disturbed. On the other hand, one would like to drive qubits as fast as possible in analogy with the clocking of classical bits, which requires a strong interaction with the environment.
Normally, these two conditions cannot be fulfilled at the same time, as a higher driving speed automatically entails a faster decay of the superpositions and, therefore, a shorter coherence time.
Topological quantum systems are physical systems exhibiting properties that depend on the overall connectivity of their underlying lattice, as opposed to local interactions and their microscopic structure. Predicting the evolution of these systems over time and their long-range quantum correlations is often challenging, as their behavior is not defined by magnetization or other parameters linked to local interactions.
Topological spin textures, spatially organized patterns linked to the intrinsic angular momentum of particles, have proved to be highly advantageous for the development of spintronics and quantum technologies. One of the most studied among these textures are skyrmionic textures, which are two-dimensional and stable patterns of spin orientation. Recently, the study of skyrmionic textures has gained significant attention in the field of optics and photonics, revealing novel physical properties and promising potential applications.
From self-driving cars to facial recognition, modern life is growing more dependent on machine learning, a type of artificial intelligence (AI) that learns from datasets without explicit programming.
Despite its omnipresence in society, we’re just beginning to understand the mechanisms driving the technology. In a recent study, Zhengkang (Kevin) Zhang, assistant professor in the University of Utah’s Department of Physics & Astronomy, demonstrated how physicists can play an important role in unraveling its mysteries.
“People used to say machine learning is a black box—you input a lot of data and at some point, it reasons and speaks and makes decisions like humans do. It feels like magic because we don’t really know how it works,” said Zhang. “Now that we’re using AI across many critical sectors of society, we have to understand what our machine learning models are really doing—why something works or why something doesn’t work.”
High-purity multi-photon states are essential for photonic quantum computing. Among existing platforms, semiconductor quantum dots offer a promising route to scalable and deterministic multi-photon state generation. However, to fully realize their potential we require a suitable optical excitation method. Current approaches of multi-photon generation rely on active polarization-switching elements (e.g., electro-optic modulators, EOMs) to spatio-temporally demultiplex single photons. Yet, the achievable multi-photon rate is fundamentally limited by the switching speed of the EOM. Here, we introduce a fully passive demultiplexing technique that leverages a stimulated two-photon excitation process to achieve switching rates that are only limited by the quantum dot lifetime. We demonstrate this method by generating two-photon states from a single quantum dot without requiring any active switching elements. Our approach significantly reduces the cost of demultiplexing while shifting it to the excitation stage, enabling loss-free demultiplexing and effectively doubling the achievable multi-photon generation rate when combined with existing active demultiplexing techniques.
I Introduction.
Photonic quantum computing offers a unique advantage over other quantum platforms due to the long coherence time of photons, enabling robust quantum communication, quantum information processing, and quantum simulations. A critical requirement for these applications is the reliable generation of high-purity multi-photon states, i.e., nn indistinguishable photons in nn spatial modes – which serve as fundamental building blocks for quantum algorithms, error correction, quantum simulations, and advanced photonic networks. Multi-photon states are also essential for probing quantum optical phenomena such as multi-photon interference. The most widely used sources to produce multi-photon quantum states are the ones relying on parametric down-conversion or four wave mixing in nonlinear crystals. However, the scalability here is limited, due to the probabilistic nature of photon emission and the required resource overhead for computing and boson sampling applications.
The reliable engineering of quantum states, particularly those involving several particles, is central to the development of various quantum technologies, including quantum computers, sensors and communication systems. These collective quantum states include so-called Dicke and Greenberger-Horne-Zeilinger (GHZ) states, multipartite entangled states that can be leveraged to collect precise measurements, to correct errors made by quantum computers and to enable communication between remote devices leveraging quantum mechanical effects.