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Gravitational-wave scientists propose new method to refine the Hubble Constant—the expansion and age of the universeA team of international scientists, led by the Galician Institute of High Energy Physics (IGFAE) and the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav), has proposed a simple and novel method to bring the accuracy of the Hubble constant measurements down to 2% using a single obse…

Gravitational wave scientists from The University of Western Australia have led the development of a new laser mode sensor with unprecedented precision that will be used to probe the interiors of neutron stars and test fundamental limits of general relativity.

Recently, scientists made groundbreaking detections that allowed them that gravity does not act instantaneously as Newton thought, instead it propagates at the speed of light.

Neil Cornish, a physicist at Montana State University said, “The speed of gravity, like the speed of light, is one of the fundamental constants in the Universe. Until the advent of gravitational wave astronomy, we had no way to directly measure the speed of gravity.”

In the course of recent months, physicists have gained exceptionally fast ground in bouncing the speed of gravity utilizing gravitational wave perceptions. Earlier, the first LIGO detections of gravitational waves constrained the speed of gravity suggests 50% of the speed of light.

(2022). Journal of Experimental & Theoretical Artificial Intelligence. Ahead of Print.

AI has for decades attempted to code commonsense concepts, e.g., in knowledge bases, but struggled to generalise the coded concepts to all the situations a human would naturally generalise them to, and struggled to understand the natural and obvious consequences of what it has been told. This led to brittle systems that did not cope well with situations beyond what their designers envisaged. John McCarthy (1968) said ‘a program has common sense if it automatically deduces for itself a sufficiently wide class of immediate consequences of anything it is told and what it already knows’; that is a problem that has still not been solved. Dreifus (1998) estimated that ‘Common sense is knowing maybe 30 or 50 million things about the world and having them represented so that when something happens, you can make analogies with others’. Minsky presciently noted that common sense would require the capability to make analogical matches between knowledge and events in the world, and furthermore that a special representation of knowledge would be required to facilitate those analogies. We can see the importance of analogies for common sense in the way that basic concepts are borrowed, e.g., the tail of an animal, or the tail of a capital ‘Q’, or the tail-end of a temporally extended event (see also examples of ‘contain’, ‘on’, in Sec. 5.3.1). More than this, for known facts, such as ‘a string can pull but not push an object’, an AI system needs to automatically deduce (by analogy) that a cloth, sheet, or ribbon, can behave analogously to the string. For the fact ‘a stone can break a window’, the system must deduce that any similarly heavy and hard object is likely to break any similarly fragile material. Using the language of Sec. 5.2.1, each of these known facts needs to be treated as a schema,¹⁴ and then applied by analogy to new cases.

Projection is a mechanism that can find analogies (see Sec. 5.3.1) and hence could bridge the gap between models of commonsense concepts (i.e., not the entangled knowledge in word embeddings learnt from language corpora) and text or visual or sensorimotor input. To facilitate this, concepts should be represented by hierarchical compositional models, with higher levels describing relations among elements in the lower-level components (for reasons discussed in Sec. 6.1). There needs to be an explicit symbolic handle on these subcomponents; i.e., they cannot be entangled in a complex network. For visual object recognition, a concept can simply be a set of spatial relations among component features, but higher concepts require a complex model involving multiple types of relations, partial physics theories, and causality. Secs. 5.2 and 5.3 give a hint of what these concepts may look like, but a full example requires a further paper.

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What do you do when a tried-and-true method for determining the sun’s chemical composition appears to be at odds with an innovative, precise technique for mapping the sun’s inner structure? That was the situation facing astronomers studying the sun—until new calculations that have now been published by Ekaterina Magg, Maria Bergemann and colleagues, and that resolve the apparent contradiction.

The decade-long solar abundance crisis is the conflict between the internal structure of the sun as determined from solar oscillations (helioseismology) and the structure derived from the fundamental theory of stellar evolution, which in turn relies on measurements of the present-day sun’s chemical composition. The new calculations of the physics of the sun’s atmosphere yield updated results for abundances of different chemical elements, which resolve the conflict. Notably, the sun contains more oxygen, silicon and neon than previously thought. The methods employed also promise considerably more accurate estimates of the chemical compositions of stars in general.

A water wave incident on a grooved wall is shown to be analogous to electromagnetic waves called surface plasmon polaritons.

The ability of metamaterials to steer light has enabled amazing inventions from superresolution microscopes to “invisiblity” cloaks. But the physics underlying these structures also applies to other waves, such as acoustic, seismic, and water waves. Huanyang Chen and his colleagues at Xiamen University in China have demonstrated a structure that can change the propagation of surface water waves, making a localized wave that is analogous to an electromagnetic excitation called a surface plasmon polariton [1].

Surface plasmon polaritons occur at the interface between a dielectric and a negative-permittivity material such as a metal. Generating an equivalent excitation in surface water waves requires a similar sort of interface, such as that between water and a vertical barrier. In this case, the water’s parameter that is analogous to a metal’s permittivity is its depth. Of course, it’s impossible for water to have negative depth, but using metamaterials, Chen and his colleagues engineered the boundary conditions of the waves to achieve the same effect.

Do the laws of physics place a hard limit on how far technology can develop, or could an advanced civilization re-write those laws?

Technology could make indoor areas as safe as outdoors, say physicists.

Today is the opening of The CAPT.(DR.) IDAHOSA WELLS OKUNBO STEM AND INNOVATION CENTER in the rural area of Iyara, warri, delta state, Nigeria.aa.

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