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Category: physics

Hologram processing method boosts 3D image depth of focus fivefold

Researchers from the University of Tartu Institute of Physics have developed a novel method for enhancing the quality of three-dimensional images by increasing the depth of focus in holograms fivefold after recording, using computational imaging techniques. The technology enables improved performance of 3D holographic microscopy under challenging imaging conditions and facilitates the study of complex biological structures.

The research results were published in the Journal of Physics: Photonics in the article “Axial resolution post-processing engineering in Fresnel incoherent correlation holography.”

One of the main limitations of conventional microscopes and 3D imaging systems is that, once an image or hologram has been recorded, its imaging properties cannot be altered. To overcome this limitation, Shivasubramanian Gopinath, a Junior Research Fellow at the University of Tartu Institute of Physics, and his colleagues have developed a new method that enables to capture a set of holograms with different focal distances at the time of acquisition, instead of a single image. These can then be computationally combined to produce a synthetic hologram that offers a much greater depth of focus than conventional approaches, and allows for post-processing of the recorded image.

X-ray platform images plasma instability for fusion energy and astrophysics

Harnessing the power of the sun holds the promise of providing future societies with energy abundance. To make this a reality, fusion researchers need to address many technological challenges. For example, fusion reactions occur within a superheated state of matter, called plasma, which can form unstable structures that reduce the efficiency of those reactions.

Characterizing different instabilities could help researchers prevent or make use of them. One particular instability, known as current filamentation, is also relevant to understanding astrophysical phenomena.

Now, for the first time, a team led by researchers at the U.S. Department of Energy’s SLAC National Accelerator Laboratory imaged how the current filamentation instability evolves in real time in high-density plasma.

Why the Past Still Exists | Leonard Susskind

We usually think of the past as something that no longer exists. It happened — and then it disappeared. But modern physics challenges this intuition in a profound way.

In this video, we explore why the past may still exist — not as memory, but as structure.

Drawing on ideas associated with Leonard Susskind, this documentary examines how relativity and modern spacetime physics reshape our understanding of time. In Einstein’s framework, there is no universal “now.” What is past for one observer may be present or future for another, depending on motion and frame of reference.

This destroys the idea that the past vanishes.

In the spacetime view, the universe is a four-dimensional structure. Events are not erased — they are located. The past is not something that disappeared. It is something that exists in a different region of spacetime.

From this perspective, time does not flow in the way we imagine. The sense of disappearance comes from human experience, not from fundamental physics.

Continue reading “Why the Past Still Exists | Leonard Susskind” | >

Gravitational lensing technique unveils supermassive black hole pairs

Supermassive black hole binaries form naturally when galaxies merge, but scientists have only confidently observed a very few of these systems that are widely separated. Black hole binaries that closely orbit each other have not yet been measured. In a paper published today in Physical Review Letters, the researchers suggest hunting down the hidden systems by searching for repeating flashes of light from individual stars lying behind the black holes as they are temporarily magnified by gravitational lensing as the binary orbits.

Supermassive black holes reside at the centers of most galaxies. When two galaxies collide and merge, their central black holes eventually form a bound pair, known as a supermassive black hole binary. These systems play a crucial role in galaxy evolution and are among the most powerful sources of gravitational waves in the universe. While future space-based gravitational-wave observatories like LISA will be able to probe such binaries directly, researchers are now showing that they may already be detectable using existing and upcoming electromagnetic surveys.

New perspectives on how physical instabilities drive embryonic development

Multicellularity is one of the most profound phenomena in biology, and relies on the ability of a single cell to reorganize itself into a complex organism. It underpins the diversity in the animal kingdom, from insects to frogs, to humans. But how do cells establish and maintain their individuality with such precision? A team led by Jan Brugués at the Cluster of Excellence Physics of Life (PoL) at TUD Dresden University of Technology has uncovered fundamental mechanisms that shed light on this question.

The findings, published in Nature, reveal how cells establish physical boundaries through an inherently unstable process, and how different species have evolved distinct strategies to circumvent this process.

During early development, embryos divide rapidly and with remarkable precision, while reorganizing into many individual units. This requires the cell material (known as cytoplasm) to be partitioned into compartments in a highly orchestrated manner.

The Singularity: Everyone’s Certain. Everyone’s Guessing

The Technological Singularity is the most overconfident idea in modern futurism: a prediction about the point where prediction breaks. It’s pitched like a destination, argued like a religion, funded like an arms race, and narrated like a movie trailer — yet the closer the conversation gets to specifics, the more it reveals something awkward and human. Almost nobody is actually arguing about “the Singularity.” They’re arguing about which future deserves fear, which future deserves faith, and who gets to steer the curve when it stops looking like a curve and starts looking like a cliff.

The Singularity begins as a definitional hack: a word borrowed from physics to describe a future boundary condition — an “event horizon” where ordinary forecasting fails. I. J. Good — British mathematician and early AI theorist — framed the mechanism as an “intelligence explosion,” where smarter systems build smarter systems and the loop feeds on itself. Vernor Vinge — computer scientist and science-fiction author — popularized the metaphor that, after superhuman intelligence, the world becomes as unreadable to humans as the post-ice age would have been to a trilobite.

In my podcast interviews, the key move is that “Singularity” isn’t one claim — it’s a bundle. Gennady Stolyarov II — transhumanist writer and philosopher — rejects the cartoon version: “It’s not going to be this sharp delineation between humans and AI that leads to this intelligence explosion.” In his framing, it’s less “humans versus machines” than a long, messy braid of tools, augmentation, and institutions catching up to their own inventions.

Scientific Notation Explained | Large & Small Numbers + Practice Questions

Scientific notation is a system developed to represent extremely large and extremely small numbers in a way that is easy to read, write, and understand. In chemistry and physics, many values such as the mass of an electron are too large or too small to be written conveniently in standard notation.

In this video, you will learn:

What scientific notation is and why it is used.
How to write numbers in the form a × 10ⁿ, where a is between 1 and 10
How to convert large numbers into scientific notation.
How to convert small numbers into scientific notation.

The LARS rule:
Left → Add to the exponent.
Right → Subtract from the exponent.

We also discuss how the direction of decimal movement affects the exponent and why the same rules apply to both very large and very small numbers.

📌 At the end of the video, you’ll find practice multiple-choice questions (MCQs) to test your understanding, including a real-life chemistry example involving the mass of an electron.

Continue reading “Scientific Notation Explained | Large & Small Numbers + Practice Questions” | >

A possible first-ever Einstein probe observation of a black hole tearing apart a white dwarf

On July 2, 2025, the China-led Einstein Probe (EP) space telescope detected an exceptionally bright X-ray source whose brightness varied rapidly during a routine sky survey. Its unusual signal immediately set it apart from ordinary cosmic sources, triggering rapid follow-up observations by telescopes worldwide.

Study of the event was coordinated by the EP Science Center of the National Astronomical Observatories, Chinese Academy of Sciences (NAOC), with participation from multiple research institutions in China and abroad. Astrophysicists from the Department of Physics at The University of Hong Kong (HKU), who are integral members of the EP scientific team, worked together with the broader collaboration to interpret the event, proposing that it may mark the moment when an intermediate-mass black hole tears apart and consumes a white dwarf star.

If confirmed, this would be the first observational evidence of such an extreme black hole “feeding” process. The findings have been published as a cover article in Science Bulletin.

The origin of magic numbers: Why some atomic nuclei are unusually stable

For the first time, physicists have developed a model that explains the origins of unusually stable magic nuclei based directly on the interactions between their protons and neutrons. Published in Physical Review Letters, the research could help scientists better understand the exotic properties of heavy atomic nuclei and the fundamental forces that hold them together.

While every chemical element is defined by a fixed number of protons in its atomic nucleus, the number of neutrons it contains is far less constrained. For almost every known element, there are at least two different nuclear configurations, or isotopes, which vary only in their number of neutrons.

However, if the number of protons and neutrons becomes too unbalanced in either direction, the nucleus becomes unstable. Since heavier elements tend to have fewer stable isotopes, these radioactive nuclei grow increasingly rare as this imbalance increases. Yet for certain specific numbers of protons and neutrons (collectively known as “nucleons”), some isotopes are found to be exceptionally stable, for reasons that physicists have struggled to fully explain.

AI method accelerates liquid simulations by learning fundamental physical relationships

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the chemical potential—an indispensable quantity for describing liquids in thermodynamic equilibrium. The researchers present their findings in a new study published in Physical Review Letters.

Many common AI methods are based on the principle of supervised machine learning: a model—for instance, a neural network—is specifically trained to predict a particular target quantity directly. One example that illustrates this approach is image recognition, where the AI system is shown numerous images in which it is known whether or not a cat is depicted. On this basis, the system learns to identify cats in new, previously unseen images.

“However, such a direct approach is difficult in the case of the chemical potential, because determining it usually requires computationally expensive algorithms,” says Prof. Dr. Matthias Schmidt, Chair of Theoretical Physics II at the University of Bayreuth. He and his research associate Dr. Florian Sammüller address this challenge with their newly developed AI method. It is based on a neural network that incorporates the theoretical structure of liquids—and more generally, of soft matter—allowing it to predict their properties with great accuracy.

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