Tagged: black holes
This topic contains 1 reply, has 2 voices, and was last updated by Ashish April 12, 2019 at 5:12 am.
- April 11, 2019 at 9:14 pm #7002csbeguParticipant
As you know, there is a lot discussion all over the world about finding the first ever photographic evidence of a black hole, which until now was only a theoretical construct. Now, in your writings you do have some indirect references to black holes and a possible alternative explanation for that phenomenon by invoking the presence or absence or information. These are some quotes from Mystic Universe where you use the term:
“If gravity were indeed the correct way to explain the entire universe (which would mean that the observational anomalies that give rise to the need for dark energy and dark matter would not exist), then this wave would arise through the rotation of heavy objects in space. This rotation requires another heavy object, and the detection is therefore supposed to be caused by a pair of black holes, which is another kind of ‘darkness’ since light cannot escape a black hole.“
“Generally, however, information transfers are so small that it is very difficult to measure these changes using macroscopic instruments. If, therefore, the information transfer is substantial, then the changes can be detected macroscopically. This information transfer need not be caused by a black hole binary; it can also be created by massive amounts of detailed information transfer between two objects, which will cause one object to shrink in size, and the other one to expand, or, by a symbol that represents abstract information. An abstract symbol transfer can quickly and dramatically change the size of objects, while the detailed symbol transfer will require a large number of symbols. They key point is that the physical size of the symbol itself doesn’t entail the resulting size of the object. “
“The uniqueness of Rāhu and Ketu is that unlike the other planets which absorb and emit, these two only absorb light. They are thus ‘accepting’ information but not ‘giving back’ information, and due to that reason we can never see them, because all sight is caused when an object emits light[i]”
[i] ENDNOTE: “In effect, they are similar to what modern cosmology terms a ‘black hole’ which only absorbs light but never emits it, although the modern notion of a black hole involves extreme densities of matter. Some key issues arise in the understanding black holes, such as the disappearance of information. For instance, how can a black hole endlessly absorb light and matter? Where does all this information disappear after being absorbed? Can a black hole actually gobble up an entire universe?”
My first question is, strictly from a modern science viewpoint, is this discovery truly consequential or is it more of a PR exercise? Does it settle any debates or anything?
My second question is, from the point of view of the semantic theory, how does the ‘black hole phenomenon’ fit into the theory, if at all?
- This topic was modified 1 week, 1 day ago by csbegu.
- April 12, 2019 at 5:12 am #7006AshishParticipant
By definition, a black-hole cannot be observed. However, because it is said to attract light, and then absorb it, it is possible to observe a donught-like halo of light in which the black hole is the dark center of the donught. In the normal course of things, you observe stars which are bright in the center and dark around the center. Donught shaped light forms are the anomalies.
To take a picture of this halo you need a telescope as big as the earth. Since that is practically impossible, the next best option is to distribute smaller telescopes all over the earth. Again, practically speaking, you cannot cover the entire earth with telescopes. So, inherently, the data collection produces a very grainy image even when dozens of telescopes are used.
This gives rise to the need for algorithms that can predict the correct form from this grainy picture. Just like you might try to decipher the face of a person from a grainy pixelated picture, similarly, computer scientists have been using algorithms to make the prediction.
Now, we can raise some methodological issues regarding whether the observation over time through many telescopes is valid. E.g. even if there was a rotating object (with a much smaller orbit around a center than what you expect due to gravitational force), and you observed it through tiny snapshots over time and then combined it, you could get a donught.
Similarly, the image recognition algorithm operates on pixelated data, which means there is a lot of information missing. The algorithm then tries to fill in that picture on the basis of training it has received to supply the missing pixels. Most of the focus of the research would be on whether this algorithm is good enough, and one answer to that question is that if the algorithm recognizes other kinds of pixelated images correctly then we can assume that it correctly predicts the donught as well. How good that assumption is, would be a highly technical matter.
So, there are many assumptions involved in this process: (1) that the donught is actually produced by sucking out uniform light from its center rather than a donught natively, (2) that this donught effect is not something we are constructing due to snapshots of an object going around in a much smaller orbit in contradiction to the gravitational theory, and (3) that our algorithms are good to fill-in the massive amounts of missing data to create a picture.
This is as far as classical physical effects are concerned. If we add quantum effects to this, it is possible that there is indeed a round light object although the center of that object doesn’t interact with the telescopes on earth, so we think that it is indeed a black hole. Personally, I’m more inclined toward this type of explanation, because I believe that nature (even macroscopic objects) have to be described using quantum rather than classical physics. But it contradicts a fundamental assumption in physics, namely, that light spreads uniformly everywhere.
The data underdetermines the theory, so to interpret data we have to supply many assumptions. In this case we are adding the assumptions of classical uniformity, gravitational theory, that a picture taken over time is not many pictures superposed, and that our predictive algorithms are indeed correct. If all these are granted, then yes it validates ‘black holes’. But it is not the only possible explanation of the data as we take out one assumption after another.
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