9+4+1+1+3*4=27 and a 9th Gluon for 26 Not

It still comes to mind that the “Tits Group gluon” might be a real thing, as although there seem to be eight, the ninth one is in the symmetry of self attraction, perhaps causing a shift in the physical inertia from a predicted instead of filled in constant of nature.

There would appear to be only two types of self dual coloured gluons needed in the strong nuclear force. As though the cube roots of unity were entering into the complex analysis that is within the equations of the universe.

9+4+1+1+3*4=27

The 3*4 is the fermionic 12 while the relativistic observational deviation from the abstract conceptual observation frame versus the actual moving observation particle provides for the cyclotomic 9+4+1+1 = 15 one of which is not existential within itself but just kind of a sub factor of one of the other essentials. Also it does point out a 3*5 that may also be somewhere.

Given the Tits Gluon, the number of bosons would be 14, which removing 8 for gluons, leaves 6, and removing 4 for the electrowek boson set would leave 2, and removing the Higgs, would leave 1 boson left to discover for that amount of complexity in the bosonic cyclotomic groups.

The fantastic implications of the 26 group of particles and the undelying fundementals which lead to strong complex rooted pairs, and leptonic pair set separation. Well, that’s another future.

Roll on the Plankon as good a name as any. The extension of any GUT beyond it would either be some higher bosonic cyclotomy or a higher order effect of fermions leading to deviation from Heisenburg uncertainty.

Up Charm Top
Down Strange Bottom
Electron Muon Tau
E Neutrino M Neutrino T Neutrino
H Photon W+
? Z0 W
Gluon Gluon Gluon
Gluon Tits Gluon Gluon
Gluon Gluon Gluon

Dimensions of Manifolds

The Lorentz manifold is 7 dimensional with 3 space like 1 time like and 3 velocity like, while the other connected manifold is 2 space like 1 time like, 2 velocity like and a dimensionless “unitless” dimension. So the 6 dimensional “charge” manifold has properties of perhaps 2 toroids and 2 closed path lines in a topological product.

Metres to the 4th power per second. Rate of change of a 4D spacial object perhaps. The Lorentz manifold having a similar metres to the 6th power per second squared measure of dimensional product. Or area per kilogram and area per kilogram squared respectively. This links well with the idea of an invariant gravitational constant for a dimensionless “force” measure, and a mass “charge” in the non Lorentz manifold of root kilogram.

Root seconds per metre? Would this  be the Uncertain Geometry secondary “quantum mass per length field” and the “relativistic invariant Newtonian mass per length field”. To put it another way the constant G maps the kg squared per unit area into a force, but the dimensionless quantity (not in units of force) becomes a projector through the dimensionless to force map.

GF*GD = G and only GF is responsible for mapping to units of force with relativistic corrections. GD maps to a dimensionless quantity and hence would be invariant. In the non Lorentz manifold the GMM/r^2 eqivalent would have in units of root kilogram ((root seconds) per metre), and GD would have different units too. Another option is for M to be quantized and of the form GM/r^2 as both the “charge” masses could be the same quantized quantity.

The reason the second way is more inconsistent with the the use of the product of field energies as the linear projection of force would give an M^2 over an r^2, and it would remove some logical mappings or symmetries. In terms of moment of inertia thinking, GMM/Mr^2 springs to mind, but has little form beyond an extra idea to test out the maths with.

W Baryogenisis Asymmetrical Charge

The split of W plus and minus into separate particle slots takes the idea that the charge mass asymmetry between electrons and protons can come from a tiny mass half life asymmetry. Charge cancellation of antiparticle WW pairs may still hold but momentum cancellation does not have to be exact, leading to a net dielectric momentum. Who knows an experiment to test this? A slight induced photon to Z imbalance on the charge gradient, with a neutrino emission. The cause of the W plus to minus mass ratio being a consequence of the sporadic group orders and some twist in very taught space versus some not as taught space or dimensionless expression of a symmetrically broken balance of exacts.

The observation of a dimensionless “unitless*” dimension being invariant to spacetime and mass density dilation. My brain is doing a little parallel axis theorem on the side, and saying 3D conservation of energy as an emerging construction with torsion being a dialative observable in taught spacetime.

Recent experiment of inertia of spin in neutrons provides a wave induction mechanism. Amplified remote observation of non EM radio maybe possible. Lenz’s law of counter EM cancellation may not apply. It is interesting. Mass aperture flux density per bit might be ok depending on S/N ratio. That reminds me of nV/root Hz. So root seconds is per root Hz, and nV or scaled Volts is Joules per mol charge, Z integer scale */ Joules, or just Joules or in Uncertain Geometry house units Hz. So Hz per root Hz, or just root Hz (per mol).

So root seconds per metre is per root Hz metre. As the “kilogram equivalent but for a kind of hypercharge” in the non Lorentz manifold perhaps. The equivalent of GD (HD) projecting the invariant to an actual force. By moving the dialative into GF and HF use can be made of invariant analysis. Mols per root Hz metre is also a possible QH in FHI = HDQHQH/R^2 the manifold disconnect being of a radius calculated norm in nature. A “charge” in per noise energy metre?

Beyond the Particles to the 18n of Space with a Tits Connection

Why I lad, it’s sure been a beginning. The 26 sporadic groups and the Tits group as a connection to the 18n infinite families of simple groups. What is the impedance of free space (Google), and does water become an increase or decrease on that number of ohms. Inside the nature of the speed of light at a refractory boundary, what shape is the bend of a deflection and what ohm expectations on the impedance to the progress of light?

Boltzmann Statistics in the Conduction of Noise Energy as Dark Energy

Just like ohm metres is a resistivity of the medium, it’s inverse being a conductivity in the medium, a united quantity relating to “noise energy or intensity” with a metres extra maybe an area over length transform of a bulk property of a thing. The idea a “charge” can be a bulk noise conductivity makes for an interesting question or two. Is entanglement conducted? Can qubits be shielded? Can noise be removed from a volume of space?

If noise pushes on spacetime is it dark energy? Is the Tits gluon connection an axion with extras conducting into the spacetime field at a particular cycle size of the double cover of the from 18n singular group which shall be known as the flux origin. 2F4(2)′, maybe the biggest communication opportunity this side of the supermassive black hole Sagittarius A*. 

The Outer Manifold Multiverse Time Advantage Hypothesis

Assuming conductivity, and locations of the dimensionally reduced holographic manifold, plus time relativistic dilation, what is the speed of light to entanglement conduction ratio possibilities?

As noise from entanglement comes from everywhere, then any noise directionality control implies focus and control of noisy amounts from differential noise shaped sources. Information is therefore not in the bit state, but in the error spectrums of the bits.

The inner (or Lorentz) manifold is inside the horizon, and maybe the holographic principal is in error in that both manifolds project onto each other, and what is inside a growing black remains inside, and when growth happens does the outer manifold completely get pushed further out?

A note on dimensionfull invariants such as velocities is that although they are invariant they become susceptible to environmental density manipulation where as dimensionless invariants are truly invariant in that there is no metre or second that will ever alter the scalar value. For example Planck’s constant is dimensionless in Uncertain Geometry house units.

So even though the decode may take a while due to the distance of the environmental entanglement and its influence on statistics, (is it a radius or radius square effect), the isolation of transmission via a vacuum could in principal be detected. Is there a relationship between distance, time of decode for relevance of data causality?

If the spectrum of the “noise” is detectable then it must have properties different from other environmental noise, such as being the answer to a non binary question and hopefully degenerative pressure eventually forces the projection of the counter solutions in the noise, allowing detection by statistical absence.

Of course you could see it as a way of the sender just knowing what had not been received, from basic entanglement ideas, and you might be right. As the speed of temperature conduction is limited by the speed of light and non “cool packed” atomic orbital occupancy as in the bulk controlled by photon exchange and not degenerative limits imposed by Pauli exclusion. A quantum qubit system not under vacuum of cooling does not produce the right answer, but does it statistically very slightly produce it more often? Is the calculation drive of the gating applying a calculative pressure to the system of qubits, such that other qubits under a different calculation pressure can either unite or compete for the honour of the results?

Quantum noise plus thermal noise equals noise? 1/f? Shott noise for example is due to carrier conduction in PN junction semiconductors, in some instances. It could be considered a kind of particle observation by the current in the junction which gets (or can be) amplified. I’m not sure if it is independent of temperature in a limited (non plasma like) range, but it is not thermal noise.

The Lambda Outer Manifold Energy in a More General Relativity

The (inner of the horizon) manifold described by GR has a cosmological constant option associated with it. This could be filled by the “gravitation of quantum noise conduction” symmetrical outer manifold isomorphic field with a multiplicative force (dark energy?) Such that the total when viewed in an invariant force measure picture is not complicated by the horizon singularities of the infinities from division by zero. Most notably the Lorentz contraction of the outer manifold as it passed through the horizon on expansion or contraction of the radius.

The radius itself not being invariant can not be cast to other observers to make sense, only calculated invariants (and I’d go as far to say dimensionless invariants) have the required properties to be shared (or just agreed) between observers without questions of relativistic reshaping. Communication does not have to happen to agree on this knowledge of the entangled dimensionless measure.

CMB Focus History

With the CMB assume a temperature bends due to density and distance from a pixel as a back step in time then becomes a new picture with its own fluctuations in density and hence bend to sum an action on a pixel for a earlier accumulation over pixels drifting to a bent velocity. Motion in the direction of heat moved further back in time. Anything good show up? Does the moment weight of other things beside an inverse square bend look a little different?

So as the transparency emission happened over a time interval, the mass should allow a kind of focus back until the opacity happens. Then that is not so much as a problem as it appears or not, as it is a fractional absorbtion ratio, and the transparency balance passed or crosses through zero on an extrapolation of the expectation of continuation.

Then there maybe further crossings back as the down conversion of the red shift converts ulta gamma into the microwave band and lower. The fact the the IF stage of the CMB reciever has a frequency response curve and that a redshift function maybe defined by a function in variables might make for an interesting application of an end point integral as the swapping of a series in dx (Simpson’s rule) becomes a series in differentials of the function but with an exponetial kind of weighting better applicable to series acceleration.

Looking back via a kind of differential calculus induction of function, right back, and back. The size of the observation appature will greatly assist, as would effective interpolation in the size of the image with some knowledge of general relativity and 3D distance of the source of the CMB.

To the Manifold and Beyond

Always fun to end with a few jokes so the one about messing with your experiment from here in multiple ways, and taking one way home and not telling you if I switched it off seems a good one. There are likely more, but today has much thought in it, and there is quite a lot I can’t do. I can only suggest CERN keep the W+ and W- events in different buckets on the “half spin anti-matter opposite charge symmetry, full spin boson anti-matter same charge symmetry as could just be any” and “I wonder if the aliens in the outer universe drew a god on the outside of the black hole just for giggles.”

 

Time Series Prediction

Given any time series of historical data, the prediction of the future values in the sequence is a computational task which can increase in complexity depending on the dimensionality of the data. For simple scalar data a predictive model based on differentials and expected continuation is perhaps the easiest. The order to which the series can be analysed depends quite a lot on numerical precision.

The computational complexity can be limited by using the local past to limit the size of the finite difference triangle, with the highest order assumption of zero or Monti Carlo spread Gaussian. Other predictions based on convolution and correlation could also be considered.

When using a local difference triangle, the outgoing sample to make way for the new sample in the sliding window can be used to make a simple calculation about the error introduced by “forgetting” the information. This could be used in theory to control the window size, or Monti Carlo variance. It is a measure related to the Markov model of a memory process with the integration of high differentials multiple times giving more predictive deviation from that which will happen.

This is obvious when seen in this light. The time sequence has within it an origin from differential equations, although of extream complexity. This is why spectral convolution correlation works well. Expensive compute but it works well. Other methods have a lower compute requirement and this is why I’m focusing on other methods this past few days.

A modified Gaussian density approach might be promising. Assuming an amplitude categorization about a mean, so that the signal (of the time series in a DSP sense) density can approximate “expected” statistics when mapped from the Gaussian onto the historical amplitude density given that the motion (differentials) have various rates of motion themselves in order for them to express a density.

The most probable direction until over probable changes the likely direction or rates again. Ideas form from noticing things. Integration for example has the naive accumulation of residual error in how floating point numbers are stored, and higher multiple integrals magnify this effect greatly. It would be better to construct an integral from the local data stream of a time series, and work out the required constant by an addition of a known integral of a fixed point.

Sacrifice of integral precision for the non accumulation of residual power error is a desirable trade off in many time series problems. The inspiration for the integral estimator came from this understanding. The next step in DSP from my creative prospective is a Gaussian Compander to normalize high passed (or regression subtracted normalized) data to match a variance and mean stabilized Gaussian amplitude.

Integration as a continued sum of Gaussians would via the central limit theorem go toward a narrower variance, but the offset error and same sign square error (in double integrals, smaller but no average cancellation) lead to things like energy amplification in numerical simulation of energy conservational systems.

Today’s signal processing piece was sparseLaplace for finding quickly for some sigma and time the integral going toward infinity. I wonder how the series of the integrals goes as a summation of increasing sections of the same time step, and how this can be accelerated as a series approximation to the Laplace integral.

The main issue is that it is calculated from the localized data, good and bad. The accuracy depends on the estimates of differentials and so the number of localized terms. It is a more dimensional “filter” as it has an extra set of variables for centre and length of the window of samples as well as sigma. A few steps of time should be all that is required to get a series summation estimate. Even the error in the time step approximation to the integral has a pattern, and maybe used to make the estimate more accurate.

Ideas in AI

It’s been a few weeks and I’ve been writing a document on AI and AGI which is currently internal and selective distributed. There is definitely a lot to try out including new network arrangements or layer types, and a fundamental insight of the Category Space Theorem and how it relates to training sets for categorization or classification AIs.

Basically, the category space is normally created to have only one network loss function option to minimise on backpropagation. It can be engineered so this is not true, and training data does not compete so much in a zero-sum game between categories. There is also some information context for an optimal order in categorization when using non-exact storage structures.

Book Published in Electronic Format. Advanced Content not Beginner Level. Second Edition may Need a Glossary.

The book is now live at £3 on Amazon in Kindle format.

It’s a small book, with some bad typesetting, but getting information out is more important for a first edition. Feedback and sales are the best way for me to decide if and what to put in a second edition. It may be low on mathematical equations but does need an in-depth understanding of neural networks, and some computer science.

Kindle Fire (Pt. III)

A general complaint about Android devices is that when you’re low on power, and it always wants to switch on and waste it rather than wait until you press the on button. It’s part of the global always on spy network, designed for idiots with money and not for intelligent or off-grid people. Alexa likely wants to know your inside leg measurement. As I said this is general to all Android devices, so I suppose expecting more from Amazon was just too much.

I suppose it would be too much to edit things like the above equation on the device, but I will try to see if there is such an equation editing tool. Plenty of good calculators, but few typographical tools. I sometimes would like to do this. It’s not as though I need the mathematical assistance, more typographical layout, for including in documents.

It seems there is nothing which will do this offline. Maybe an app opportunity? Likely a long development. It depends on other tools such as MathML being hack-able into something else. Of course n=k in the above equation. A bit of maths in the “analytic closure of integration” to make it a deterministic process for a CAS (Computer Algebra System). It replaces integration (hard for computers to pattern match, and based on a large and incomplete knowledge base) with simultaneous equations and factorization.

There seem to be some downloaded episodes of some series happened this morning. Three free episodes (Number 1) of some random TV shows. I assume this is to get people into watching exciting stuff. I feel a bandwidth suck in the making. Ah, so it’s called “On Deck“, and although kind of interesting, it would be nice to make it only use certain WiFi networks. While on 4G hotspot proxy, it will make my bank account sad.