Mordred

Good answer Itoero +1

This will mess you up most likely but it is possible to divide an infinite quantity an infinite number of times and each portion will still be infinite. The theoretical multiverse could be the same, so could our own universe.

Gravity waves arise from anistropies of spacetime. The BB from 10^-43 sec forward is considered homogeneous and isotropic so you wouldn't have GW production from the rapid expansion due to BB

That last bit on the QM agreement/disagreement lies in the three views of QM. Is that Bell used objective local theory. However not all polarization angles agree with Bells. Rather support QM, this can be found by studying CHSH inequalities.

lol ya don't need to understand it all, QM terminology arises from statistical calculus and so does much of its mathematical methodology. For example sections on Stochastic probability, Gaussian, correlation function, locality, probabilities probability density function etc. The rudiments of the math and arguments is in the last link

This paper is an F(R) gravity treatment, https://arxiv.org/abs/1606.07000 that explains the concern I had with the [latex]g_{\mu\nu}[/latex] the first two pages of the above link explains the two treatments. In a nutshell the first paragraph "The questions about the concepts of dark matter and dark energy motivated the development of new gravity theories. Most of them are direct modifications of genneral relativity (GR), such as f(R) theories where, in conntrast to GR, the Einstein-Hilbert Lagrangian density is replaced by a nonlinear function f(R). The nonlinearities lead to different sets of field equations according to the different variational approaches for the action" under F(R) the methodology looks correct. though I'm very rusty on F(R) To understand the methodology a starting point is statistical calculus. https://www.google.ca/url?sa=t&source=web&rct=j&url=http://www.columbia.edu/~mh2078/stochastic_calculus.pdf&ved=0ahUKEwi5l8Dzqs7VAhWN8oMKHceVCnUQFggiMAE&usg=AFQjCNEaY477wJHuzgVAfC6YtvhU8uH8sA Last link will also help in all quantum topics...and engineering etc etc

Thanks for bringing the above to our attention. I know I will study the above lol as RL allows.

As you have already mentioned the extreme difficulty measuring gravity at the quantum scale, about the best we can do is set the upper and lower constraints based upon numerous studies and methodologies based upon indirect and multi particle studies that we can measure. Much like what happened with the Higgs field. Prior to being discovered. The studies pointed to where to look by numerous constraints being gradually tightened. The data to set those bounds would comprise of years of research and various model comparisons to fine tune the bounds. One solid example of applicable datasets is the GW wave data being collected. You get a ton of details that are applicable to quantizing gravity. Amplitude, strength and spin statistics (quadupole data). A solid range of samples will provide incredibly useful data to tighten our constraints.

will study this paper before I reply, but am reading them (the links above are identical). Edit: This is going to take me a bit, gonna have to study it in more details on their new polarization treatments. Mathematically its well detailed but I need to work through them. I don't see anything unsound about what they are doing but still studying it. In particular I am seriously questioning the modifications to the metric tensor. Regarding the time dependencies.

For string theory itself I feel twistor theories has a strong potential. https://www.google.ca/url?sa=t&source=web&rct=j&url=http://conservancy.umn.edu/bitstream/handle/11299/130081/spradlin.pdf%3Fsequence%3D1&ved=0ahUKEwji3Z7g8M3VAhUT24MKHSqDCSAQFggoMAI&usg=AFQjCNGgWPZJMvC0M8LxeTX2RTtu_bCesA Twistor theory link above. You can replicate spinfoam via twistor, just an fyi

LQG is a good solid modelling system, Myself I prefer QFT under quantum geometrodynamics. Here is an intro from arxiv. https://www.google.ca/url?sa=t&source=web&rct=j&url=https://arxiv.org/pdf/1108.3269&ved=0ahUKEwjdtJmq7s3VAhXl1IMKHQZUB20QFghBMAk&usg=AFQjCNG0UYMuDcmyD_f900Ksskv7b1ei8Q Either method String, QFT or LQG stand an equal chance in my opinion. They are all equally capable of describing any dynamic from the quantum scale to individual interactions to spacetime fields There are full treatments of SO(10) both MSM a(minimal standard model) and MSSM ( minimal supersymmetric model) in either methodology of the above. Under particle interactions or under field treatments.

I hope the above helps better understand the above, it isn't a case of a mistake but rather which is the better suited treatment. Bell used frequentism which is primarily the Quassian wavefunction rather than Bayer learning etc. Another oft missed term is Stochastic. A good book on Stochastic probability theory is "An introduction to Schotastic modelling" by Howard M Taylor. However you require Calculus. Lol just a side note statistical mechanics is probably one of my weaker subjects so hopefully I didn't make any mistakes in the above lol I hated statistics for years till I finally realized I needed to understand it to properly understand QM/QFT. Little side note if you want to really want to understand terms such as determinslism, local, real and how they are defined study the two books I recommended. They have specific statistical definitions

Anyways I hope this helps better understand papers such as this one Entropic Dynamics and the Quantum Measurement Problem https://arxiv.org/abs/1108.2550v1

Here this is an example from one of my advanced QM course notes. I honestly can't recall the source book/article but I had it written down when I was studying the three views of QM. let us assume a classical problem (no quantum uncertainty) Suppose we are trying to measure the position of a particle and assign a prior probability function. [latex]p(x)=\frac{1}{\sqrt{2\pi^2_0}}e^{-(x-x_o)^2/2\sigma^2_0}[/latex] our measuring device is not perfect due to noise etc it can only be measured with a resolution[latex] \Delta [/latex] thus if my detector measures position y I assign the likelhood that the postion was x by the Gaussian [latex]p(y|x)=\frac{1}{\sqrt{2\pi\Delta^2}}e^{-(y-x)^2/2\Delta^2}[/latex] you then use Bayes theorem to show that given the new data you must now update your probability assignment of the position to a new Gaussian [latex]p(x|y)=\frac{1}{\sqrt{2\pi\acute{\sigma}^2}}e^{-(x-\acute{x})^2/2\acute{\sigma}^2}[/latex] where [latex]\acute{x}=x_o+k_1(y-x_o), \acute{\sigma}^2=k_2\sigma^2_o, k_1=\frac{o^2_0}{\sigma^2_0+\Delta^2}, k_2=\frac{\Delta^2}{\sigma^2_o+\Delta^2}[/latex] Now unfortunately I cannot post the drawing so take two axis with P(x) on the vertical, x the horizontal axis. Then draw a sinusoidal hump. Bisect this hump down the center and label it x_0, [latex]\sigma_o[/latex] is the error margin to the left and right of x_0. we now measure the position and find value y in my detector the true x may still be different. Given the uncertainty of my detector [latex]\Delta(x)[/latex] with a Quassian distribution let the likelyhood distribution be [latex] P(y|x)=\frac{1}{\sqrt{2\pi\Delta^2}}e^-{\frac{(y-x)^2}{2\Delta^2}}[/latex] thus according to Bayes rule the updated probability is [latex]N^{-1}=\int dxP(y|x)P(x)[/latex] in essence we have narrowed the Gaussian distribution Google Bayes Learning for more details. However in essence we have shifted x_0 to a new location. here is the details on maximum entropy setups http://www-mtl.mit.edu/Courses/6.050/2003/notes/chapter10.pdf now look again at equations 7 and 8 of the first link I gave https://arxiv.org/pdf/physics/0411057.pdf notice it is using Bayesian notation with the use of sigmas in reference to Jaynes treatment ? It is a natural conequence of methodolgy used in statistical math to arrive at two different correlation functions if your using two different qaussian distributions ie Bells vs Jaynes (Bayes learning with maximum entropy) edit a side note Jaynes book is an excellent study aid in learning the above lol. "Probability theory the logic of science" its 758 pages of excellent details I use his Boolean algebra section on a regular basis for the basic identities idempotence, commutivity, associative, distributivity and duality...thats just chapter 1 lol

This is the primary difference is the statistical approach and the corresponding axioms. Either method in my opinion isn't conclusive enough to state which is better for this application so I won't try to sway any opinions but merely supply the details behind the two arguments. Bayesian or Gaussian just to inform here is Gaussian statistics. https://www.google.ca/url?sa=t&source=web&rct=j&url=https://www.physics.ohio-state.edu/~gan/teaching/spring04/Chapter3.pdf&ved=0ahUKEwiq8YXzx8vVAhVU8mMKHeZQCnAQFggwMAM&usg=AFQjCNEsYEG7wHPPW1-ye5PYERh32W7xpw Here is how it relates to Gaussian PDF's probability density functions https://www.google.ca/url?sa=t&source=web&rct=j&url=http://isif.org/fusion/proceedings/fusion2010/pdfs/th1.1.1-0070-final.pdf&ved=0ahUKEwiKg9C9yMvVAhUQ82MKHdu6AuoQFggdMAA&usg=AFQjCNE3D2U5MgKUsFlojPxDGqetCx0Hdw A little hint Bayen statistics uses a conditional probability function [latex]P(A|B)=\frac{P(A|B)P(B)}{P(A)}[/latex] I won't bore everyone detailing the differences but literally how the two handle probability and uncertainty is different statistical methods literally. One must understand both methods to get to the root of the debate.

Ah but is the debate not simply a bottom up vs top down methodology. Jaynes methodolgy being based on maximum Entropy and Bayesian Methods. Shannon entropy follows similar methods. Despite all the pop media hype I have seen papers such as this arxiv https://www.google.ca/url?sa=t&source=web&rct=j&url=https://arxiv.org/pdf/physics/0411057&ved=0ahUKEwjG1tOVuMvVAhVG8WMKHZPkBikQFggfMAA&usg=AFQjCNFbih6KyWVu_ncJUDJUync0rKiNOA Shows that the criticisms Jayne had on Bell as being a difference in methodology in how to treat the probabilities This particular review paper concludes that the two methodologies are not incompatible but the paper studies the two methodologies not the hidden variable aspects. Here is a decent paper on Bayesian statistics. https://www.google.ca/url?sa=t&source=web&rct=j&url=http://www.uv.es/bernardo/BayesStat.pdf&ved=0ahUKEwj33d-qwMvVAhVP0WMKHR5YBlEQFggfMAE&usg=AFQjCNEA0GDuUZ1Y_gybTUqFkg4sT_-8yQI It is an ongoing debate but in all honesty I see far too much hype without detailing the differences in statistical methods

Yes there have been attempts such as Universe from nothing, cyclic and bounce models. However they are I guess you could say proposed extensions to the BB model currently LCDM. LCDM itself stops prior to hitting the singularity problem.

Might help to realise the BB isnt a creation event. The model stops working at 10^-43 seconds.

Good video thanks for sharing

Nice quote will have to remember that one

Though I may not have read the same material Studiot mentioned. I have never come across any materials that William Berkson has written a waste. I'm going to flip the question for you. We have no problem accepting signal delays in electromagnetic field interactions google propogation delay. So why does everyone not accept the same phenomena with other field interactions such as spacetime? Now I don't want a ton of posts answering the above. Instead I want those that have difficulty accepting the equivalence to look at themself and ask yourself "What is the difference" ? Is there any difference ? Remember mass is resistance to inertia change when you ask that question and also remember solid/corpuscular is an illusion of our interpretation of field interactions. Everything we percieve or measure or interact with is subjective to signal delays regardless of what types of field interactions are involved. Aka time dilation "Observer effects" Why does few people not understand why an object gains inertia mass yet understands that it is harder to stop a speeding bullet, when fundamentally they are the same? As an object gains momentum its kinetic energy and ability to perform work increases. Ever try to stop a bullet? fundamentally inertia mass is the same pheneomena. Its much harder to stop a speeding bullet than one rolling on a table. Yet we cannot accept the same phenomena with spacetime why? (other than most people don't know the correct meaning of mass as defined by physics lol) A hint on another key difference in Newtonian physics compared to relativity. In Newtonian physics the object does not gain inertia mass.... You want to accept time dilation you have to accept signal propogation delays as a fundametal property in field interactions and inertial mass as defined by mass is resistance to inertia change and not the amount an object weighs. Length contraction being simply the measuring stick of the signals propogation delay from a to b keeping c invariant via ((ct),x,y,z)

Fair enough, on the financial end. It is a huge infrastructure requirement that is difficult to grasp. However the materials that we mine on Earth for our everyday needs are available in the asteriods. Helium 3 being in far greater abundance. edit lol a discussion on financial feasibility would be a lengthy discussion in and of itself.

Indeed acceptance of death often comes down to acceptance of ones own accomplishments. Though not in the manner most will assume. Accomplishment as per acceptance that one has had a good and meaningful life. The acceptance that you have had influence on those dear to you, acceptance that you have done everything to teach your children self sufficiency. Acceptance that you have accomplished the important goals in your life. The acceptance that you have done the best you can for others.

Excellent example to post, my condolences but at the same time my heartfelt respect for your father.

As difficult as it is to control the Religous forum, it does provide an outlet for those with religous agendas instead of contaminating the mainstream sections. Sides even if the OP doesn't post there the Mod staff can move the thread there.