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I found this on NewsBreak: New models of Big Bang show that visible universe and invisible dark matter co-evolved.

Physicists have long theorized that our universe may not be limited to what we can see. By observing gravitational forces on other galaxies, they’ve hypothesized the existence of “dark matter,” which would be invisible to conventional forms of observation.

Our Universe requires dark matter in order to make sense of things, astrophysically. Could massive photons do the trick?

But not in the Einstein/Newtonian Lambda-cold-dark-matter model

This post is based on the research paper by Mazurenko, Banik, Kroupa & Haslbauer (2023, MNRAS). Sergij Mazurenko is an undergraduate physics student at the University of Bonn, and Indranil Banik was an Alexander-von-Humboldt Fellow with us until recently and is currently at the University of St. Andrews. Moritz Haslbauer is a finishing PhD student at the University of Bonn who has been contributing to The Dark Matter Crisis (DMC). The press release from the University of Bonn on this matter can be read here (and from Charles University in Prague here) and a description can also be found in The Conversation.

Dark matter may in fact be made up of light-barrier breaking particles called tachyons, the researchers posit.

The telescope’s studies could help end a long-standing disagreement over the rate of cosmic expansion. But scientists say more measurements are needed.

By Davide Castelvecchi & Nature magazine.

For most stars, neutron stars and black holes are their final resting places. When a supergiant star runs out of fuel, it expands and then rapidly collapses on itself. This act creates a neutron star—an object denser than our sun crammed into a space 13 to 18 miles wide. In such a heavily condensed stellar environment, most electrons combine with protons to make neutrons, resulting in a dense ball of matter consisting mainly of neutrons. Researchers try to understand the forces that control this process by creating dense matter in the laboratory through colliding neutron-rich nuclei and taking detailed measurements.

Thanks to the dizzying growth of cosmic observations and measurement tools and some new advancements (primarily the “discovery” of what we call dark matter and dark energy) all against the backdrop of General Relativity, the early 2000s were a time when nothing seemed capable of challenging the advancement of our knowledge about the cosmos, its origins, and its future evolution.

Dark energy’s grip on the cosmos could be more fickle than scientists once believed.

A quantum squeezing method can enhance interactions between quantum systems, even in the absence of precise knowledge of the system parameters.

Squeezed states are an important class of nonclassical states, where quantum fluctuations can be reduced in one property of a system, such as position. However, at the same time, according to the Heisenberg uncertainty principle, quantum fluctuations increase in the conjugate property, in this case momentum. The ability to suppress noise in at least one variable is valuable in a wide range of areas in quantum technologies. Now Shaun Burd at the National Institute of Standards and Technology, Colorado, and colleagues have experimentally demonstrated a squeezing-based enhancement method that requires no preknowledge of the system’s parameters [1]. The researchers use a trapped-ion system (Fig. 1) and show that they can amplify the motion of the ion using a combination of squeezing procedures. This experimental research can stimulate other novel applications of squeezing, for example, in dark matter searches.

For decades, quantum squeezing has played a central role in high-precision quantum measurements, such as gravitational-wave detection [2, 3] and nondemolition qubit readout [4– 6]. The methods typically involve applying a field or inserting an optical element that reduces the fluctuations in one observable. The measurements of this squeezed observable can beat the standard quantum limit and thus enable a significant improvement in the detection sensitivity or the readout signal-to-noise ratio.