Update to Solar System Gravimetry and Gravitational Engineering

Everyone,

I am including this as an update to this project because the routine laboratory and wide area measurement of the speed of the gravitational potential is critical to all the groups working together. You HAVE to be able to measure the signals at high enough sampling rates to get good correlations and comparisons. For large things like tracking coronal mass ejections and mass flows from the sun, there is now enough information on the precise timing and mass distributions involved to solve for the signals that will arrive at the sensors. The reason LIGO could start was because the signal was clear, they had LOTS of stronger signals they could have used, but at 16,384 samples per second, and only three detectors, there are not a lot of reference sources that can be used.

On this paper, I am not sure. Any mass that reaches relativistic levels where there is additional mass, that can be used for signal generation and detection. But macroscopic masses are hard to get to those speeds. Many of the heavy ion accelerators, especially collisions of highly symmetric isotopes could be use. The laser vacuum experiments that generate particle antiparticle pairs can be used. Anywhere mass is converted to energy or energy to mass will change the gravitational potential. With precise timing, orientation and energy levels the signals involved are often well within reach of SOMEONE’s methods. But with everyone going in their own directions, it is like random chance that get any progress overall. I am hopeful, but I have been at it for 40 years and I am getting a bit tired.

ALL the “kT” noise is actually a mixture of the local wave function, magnetic variations, power system “noise”, and gravitational potential changes impacting rate of clocks or accelerations. Most of that can be modeled and calibrated now. But it takes many global networks to each calibrate their systems, then to intercalibrate. Only talking to one sensor type won’t get the job done. Pretty much every sensor needs to be compared to every other one. I think that there is enough information on the sun to image its interior, AND to use its mass flows to calibrate sensors on earth and in orbit. I have not found any big holes. But just “solar observing” and “stellar modeling” is large, and all the groups are chasing Nobel prizes and fame for discoveries, not consolidating, calibrating and sharing. It is that sharing and comparing that will have the largest impacts for the human species, not a few hundred new Nobel prizes or new job titles or perks.

Richard Collins, The Internet Foundation

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Johan,

I have two hurdles for groups developing gravitational sensors.

First they have to calibrate their instrument over long periods (days and weeks) to the sun moon vector tidal acceleration signal. There are several groups that can do that, but they have not gone further.

Second, they measure time of flight (sampling rates high enough to track laboratory targets) signals from observable masses. To make things easy they can use atmospheric models, earthquake seismic waves, ocean surface waves, ocean current, highway traffic, or even humans. That is not hard, but it takes a level of effort and skills that is a good indication of the abilities of the group.

No one has reached stage II – measuring the speed of gravity (and making sure it is a gravitational, not an electromagnetic near field signal) that travels at the speed of light.

Amrit Ć orli I agree with you that a superfluid quantum vacuum is a good model for the local gravitational potential. The gradient of that potential is the acceleration. There are tens of thousands of groups and individuals hammering away on gravitational engineering problems. Trying to keep the language simple – to fit the common background of the people and groups involved – is needed so the pieces all come together without a lot of chatter and ill feelings and wasted time. The gravitational waves of LIGO type detectors are measuring displacement. It is better to keep that in mind, then differentiate to get the velocity, and again to get acceleration. Those pieces will fit, but groups are somewhat sloppy and don’t carefully separate their signals. That is why I keep harping on groups using arrays of time of flight and angle of arrival sensors so they can determine the source distance and characteristics with mathematical and statistical methods everyone is familiar with.

When groups go riffing on their favorite methods, that only slows things down. Keep it simple, make sure all the steps are easy to follow and testable. Reach out to new groups who are struggling. Get real data. Get ALL the sensors so they are calibrated to the HUGE sun moon tidal signal (anyone says “earth tides” should be able to do that easily). There are close to 40 groups who could do a time of flight gravitational imaging demonstration of the speed of gravity. I found groups under every possible term – quantum experiments, Bose Einstein Experiments, atomic clocks, atom interferometers, atomic microscopy, all kinds of scattering experiments, precise magnetic moment experiments, most latest generation accelerators, Sagnac detectors and many derivatives, nuclear fission statistics, atomic decay statistics, GPS time variations, Mossbauer. And dozens or hundreds of groups for each. LOTS of individuals who have spent decades of hard effort to figure out pieces of the puzzle.

It just has that many parts and ramifications. Changing for electromagnetism to gravitation is not hard, it is just tedious. Much of what we call “electromagnetic” is also gravitational. Much of what we call “gravitational”” also applies to electromagnetism. Almost ALWAYS it is a mix that requires patient and tedious separation. But it is not hard.

Richard Collins, The Internet Foundation

Richard K Collins

About: Richard K Collins

Director, The Internet Foundation Studying formation and optimized collaboration of global communities. Applying the Internet to solve global problems and build sustainable communities. Internet policies, standards and best practices.


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