Mandela Effect & D-Wave's Boltzmann Machine Quantum Pollution

By Anthony Patch

D-WaveD-Wave System's Boltzmann machine is the core process of the Mandela Effect (ME).

Because it is a recurrent neural network process, it is an endless loop.

We've discussed it as the new process of deep machine learning. That is only the beginning. Please refer to the attached breakdown at the end of this article, from the July issue of Entangled.

D-Wave's literal accessing of multiple-thousands of parallel dimensions, and in the words of Co-Founder, Geordie Rose, "grabbing resources" from them, manifests as what I term "Quantum Pollution"…otherwise known as; "The Mandela Effect".

In addition to these "resources", by D-Wave's own public statements in 2013 they are realizing in return, 10% additional "energies" from these parallel dimensions. Thus, adding to the alterations in our reality.

I encourage you to watch and listen and read with closed captions, this video originally recorded in 2013 in which Geordie Rose is speaking in layman's language to a gathered audience. Please note, his words are carefully chosen and specific. Here are some notables for you.

"There is a very clear prediction, that our most successful theory of nature makes. And, that is there are an enormous number, mind-bogglingly large number of parallel realities, as real as this one, that have different consistent histories.

So, imagine a world where all of the laws of physics as we know them are obeyed, but different decisions were made along the way. Different decisions at the level of tiny microscopic particles. Different decisions all the way up to what you chose to eat for lunch, and whether you chose to come to the session or not.

Quantum mechanics makes a very specific prediction that all of those are as real as the thing that you remember. And this is bizarre, because we don't see those other things.

But, science has reached the point now (2013) where we can build machines that exploit those other worlds, and quantum computers are perhaps the most exciting of all these that we have within, or almost within our grasp right now.

So, people from a physics background love this. They want to understand the world. They want to understand the universe. How it all works."

(This quote is taken from a graphic posted during this presentation by Geordie Rose)

"Quantum computation ...will be the first technology that allows useful tasks to be performed in collaboration between parallel universes." – David Deutsch @ TED 2005

"There's another type of person who tends to come from the computer science side that's like, yeah okay, that's all great. But, there's a different thing going on here, which is just as exciting, if not more. And, that these machines that supposedly can do this wild stuff, let's forget about how they work.

If you could build one, could solve problems that you could never, ever solve with any computer of the sort that we built. If you took every single atom of silicon in the world, and made the most sophisticated conventional intel-style processor that you could build. There are problems we know of that I could write down on a sheet of paper, that you could never ever ever solve with that thing, that you could with this kind of machine.

So, that's very exciting. Humans use tools to do things. If you give humans a new kind of tool that can do things that you couldn't otherwise do, imagine the possibilities."

(This quote is taken from a graphic posted during this presentation by Geordie Rose)

"…quantum computers …can solve problems whose solution will never be feasible on a conventional computer." Quantum computing for everyone Michael Neilson (2008)

"So, if you have the opportunity to stand next to one of these machines, it is an awe-inspiring thing. At least for me.

It feels like an altar to an alien god if they really are impressive machines."

"Imagine that there really are parallel universes out there. And now imagine you have two (universes) that are exactly identical in every respect. All the way out to the horizon as far as we can see, down to the last little atomic detail of every single thing, with only one difference. And, that's the value of a little thing called a qubit on this chip. Which (is) the contraction of (a) quantum bit.

And, that qubit is very much like a bit or a transistor in a conventional computer. It has two distinct physical states, which we call 0 and 1 for (a) bit. In the conventional computer these are mutually exclusive.

That device is either one, or the other, and never anything else.

In a quantum computer, that device can be in a strange situation where these two parallel universes have a nexus. A point in space where they overlap. And, when you increase the number of these devices, you every time you add one of these qubits, you double the number of these parallel universes that you have access to.

Until such time when you get to a chip like this, which is about 500 of these bits. You have something like, 2 to the 500th power of these guys, living in that chip.

So, the way I think about it is, that the shadows of these parallel worlds, overlap with ours.

And, if we're smart enough, we can dive into them, and grab their resources, and pull them back into ours to make an effect in our world.

Now, this may sound very odd to you, and bizarre. And in effect, I am using language that a normal theoretical physicist probably wouldn't use.

But, what I am telling you is absolutely correct, and in line with the way that these things actually work."

"So my third prediction that I'm going to end on, is the most important of all.

I believe humanity is on the cusp of the most important technological, societal revelation, revolution that's ever occurred. And, that's when we go to the point where the machines that we build, outpace us in every respect.

I don't mean that they're better calculators. I don't mean that they are better at searching. I mean everything. And, I think that we're very close.

And, my prediction is, that within 15 years, we will have machines that outpace humans in everything."

"Google was the primary interested party that pulled this whole thing together. And, this one is really exciting to me.

Because, what they're going to do is apply this machine to an area that I think is fundamentally important. (Graphic of MIT Technology Review, May 16, 2013: ‘Google and NASA Launch Quantum Computing AI Lab')

It's a crux of our future as humans, and that's, can we build machines like us?

So, building machines like us? Might be possible. I certainly believe it is. I might be wrong. But, what I do know is that the types of approaches that people are taking now (2013) to build intelligent machines benefit immensely from what this machine that we've built does best.

So, what this Center is about, is applying this beautiful new computational idea in the service of trying to make intelligent machines.

Now, I can't think of anything personally cooler than trying to use quantum computers to build intelligent machines. So, this is very exciting to me."

These activities are intentional on the part of D-Wave Systems, and those they serve.

The following is a transcript of a recent presentation by Geordie Rose, to a Tech Vancouver audience. Please note the screenshot of this author, as he cites my research regarding the activities of D-Wave Systems as they relate to the Mandela Effect:

D-Wave Founder Mocks The Mandela Effect

"Okay, so my previous company was D-Wave.

We'll just show you a couple of things.

We build what are still the world's only quantum computers that you can buy.

And, the company D-Wave has been doing this thanks.

I didn't really have much to do with it, but you know it gives so this is one of them.


This is one of them, this is one of the processors and a lot of interesting things happened to me over the years.

I got sent pajamas, a whole bunch of stuff.

You know there's of interesting things that happen when you build something like a quantum computer.

But, just as an aside because I thought it was funny.

One of the interesting things that's happened from the D-Wave story, is there's this gigantic conspiracy that's arisen on the internet that goes like this.

So…D-Wave builds quantum computers, the way that they work if you know, that's how this works is one of the interpretations is that you tap into these parallel universes and they do computations, sounds really weird.

But, what's happened is this idea is being hijacked to describe something called the Mandela Effect, which is this thing where the past changes.

So, think about something you know to be true from the past, and then imagine you went out on the internet, and you can't find it at all. It's not there. It doesn't match with your experience.

So, these people think that do is responsible in CERN (words missing from his actual speech)…and of course, the quantum key to the Abyss factors into it somehow. I'm not exactly sure how.

Okay. So, that's just D-Wave I did that for about 15 years.


It was a lot of fun. A big science project that we turned into a commercial entity.

That was a warm-up for Kindred.

So, Kindred….." (the video continues on regarding Geordie's new company).

Screenshot follows:

My original video and broadcast on the Kev Baker, Truth Frequency Radio, September 17, 2016:

This Boltzmann machine, is a spiral. (Please see attached article at the end). A time loop, but more than a loop because the Mandela Effect (ME) is spreading and becoming more apparent, even to those who do not know of the ME label.

The upcoming ME movie only serving as further evidence of this.

It is all part of the increasing density of data, the 'granularity of data' of the Sentient World Simulation (SWS). Please see at the end of this article, a re-publication of my article, ‘SWS & Mind Control' from the June issue of Entangled magazine.

The SWS is moving out of the lab you might say.

It is the final version of the old Model T Project Blue Beam.

SWS is the holographic, 'digitized reality'.

However, this advanced form of hologram is not dependent upon a laser projection system, for only in people's minds does it exist. It is a Psychological Operation, with its origins in multiple thousands of parallel dimensions from which D-Wave System's Adiabatic Quantum Computers are, again to quote Geordie Rose: "And, if we're smart enough, we can dive into them, and grab their resources, and pull them back into ours to make an effect in our world."

If a visitor from another planet were to arrive on Earth, it would see the original 'analog' version, as God created it.

While, those Earth inhabitants effected at their DNA, thus their brain level, would see the digital version.

This is God's 'strong delusion'. He is allowing satan to build out this system of densely granular data. God does this all as part of His judgment.

Those indwelt of the Holy Spirit will not become fully immersed within this Boltzmann machine-driven delusion. Some will see the changes, recalling the original versions. However, due to the spiraling process of ever-increasing-density of data, those without the discerning power of the Holy Spirit will claim no memories of those originals.

In conclusion: D-Wave's soon-to-be published White Paper on their employment of the Boltzmann machine recurrent neural network of Quantum Processing Units (QPUs), by way of the increasing evidence of instances of the Mandela Effect; is proof positive it's been in operation since the first recollections of this effect.

Compounding the density of granular data, is D-Wave's continuous activities to ‘grab their resources' from near-infinite numbers of parallel dimensions. Thus, serving the spiral model of God's 'strong delusion'.

The spiral by the way, is a function of the geometric center of my 600-cell tetrahedron, model of the Universe. Once again proving D-Wave's employment of it in the physical structuring of their 10th model computer, equivalent in QPUs to that of the human brain: 65,536 qubits. They have a 14th model possessed of 1,048,576 qubits. Networked together, these 14 models taken only as single units for the purposes of citing the total number of qubits as derived from this linear progression of model numbers; totals: 2,097,024 qubits. It must be understood, multiple units of each individual model have been sold to USC/Lockheed, NASA/Ames, Google, NSA, Volkwagen, Temporal Defense Systems, and Amazon.

Therefore, considering the quantum environment of near-infinite numbers of parallel dimensions which each quantum computer is operating within, any conflicts of interest and purpose must be prevented.

For example. When any two AI personal assistant applications residing within a smartphone are allowed to communicate with one another, conflicts arise.

The end result in terms of the total quantities of qubits now employed in the accessing of vast numbers of parallel dimensions, manifests literally in multiple millions of networked qubits.

The Mandela Effect is a Psychological Operation facilitated by D-Wave System's Adiabatic Quantum Computers. And my frequent references to it both herein and on radio only serves to further its purpose in deceiving people. However, I am functioning as an objective researcher, performing critical analysis for the public good.

As with any operation of this nature, it is important for the subjects to be aware they are being ‘gamed'. Such a perspective serves one in being able to counter the control mechanisms of deception.

Here is how I view the sequence of events playing out in this operation. The foundational element of the ME is born out of the oft-employed, Hegelian Dialectic; comprising a problem, reaction and solution.

The problem in this case is labeled; control. More specifically, how can a singular form of governing, control all the world's population.

The reaction is the present state of discussions and confusion regarding the ME. It is important to emphasize this stage of the dialectic. For soon, it will in a pre-planned manner, achieve a desired tipping-point exhibiting itself in mass hysteria. This due to the equally as oft-employed societal paradigm of, ‘us versus them'. A division is forming of those retaining memories of reality, and those devoid of it.

The solution to be offered, will be in the form of accessing the digital Sentient World Simulation. Itself presented as the ‘accurate record', the ‘true reality'. In essence, the ‘hive mind'.

Thus, the goal of this specific Psychological Operation being control, those seeking it believing it to be the inevitable result of their deception.

I will now provide links, rather than transcripts of a presentation made by D-Wave System's co-Founder, Geordie Rose. I'd prefer you see and hear his own statements. Beginning with the starting point of the video, I will break it down into specifics for you.

Starting point. I encourage you to review this video in its entirety, and with Closed Captioning enabled.

This is his description of parallel realities, "that have different consistent histories".

2 Thessalonians 2:11King James Version (KJV)

11 And for this cause God shall send them strong delusion, that they should believe a lie.

Re-Published from July Issue of Entangled Magazine:

Boltzmann Machine

By Anthony Patch

There is a new sheriff in town going by the name of Boltzmann. Boltzmann Machine.

A Boltzmann machine is a type of stochastic recurrent neural network (and Markov Random Field) invented by Geoffrey Hinton and Terry Sejnowski in 1985. Boltzmann machines can be seen as the stochastic, generative counterpart of Hopfield nets. They were one of the first examples of a neural network capable of learning internal representations, and are able to represent and (given sufficient time) solve difficult combinatoric problems.

Theoretically intriguing because of the locality and Hebbian nature of their training algorithm, and because of their parallelism and the resemblance of their dynamics to simple physical processes. Due to a number of issues discussed below, Boltzmann machines with unconstrained connectivity have not proven useful for practical problems in machine learning or inference, but if the connectivity is properly constrained, the learning can be made efficient enough to be useful for practical problems.

They are named after the Boltzmann distribution in statistical mechanics, which is used in their sampling function.

A Hopfield network is a form of recurrent artificial neural network popularized by John Hopfield in 1982, but described earlier by Little in 1974. Hopfield nets serve as content-addressable systems with binary threshold nodes. They are guaranteed to converge to a local minimum, but will sometimes converge to a false pattern (wrong local minimum) rather than the stored pattern (expected local minimum). Hopfield networks also provide a model for understanding human memory.

In probability and statistics, a generative model is a model for randomly generating observable data values, typically given some hidden parameters. It specifies a joint probability over observation and label sequences. Generative models are used in machine learning for either modeling data directly (i.e., modeling observations drawn from a probability density function, or as an intermediate step to forming a conditional probability density function.

Hebbian theory is a theory in neuroscience that proposes an explanation for the adaptation of neurons in the brain during the learning process, describing a basic mechanism for synaptic plasticity, where an increase in synaptic efficacy arises from the presynaptic cell's repeated and persistent stimulation of the postsynaptic cell. Introduced by Donald Hebb in his 1949 book The Organization of Behavior, the theory is also called Hebb's rule, Hebb's postulate, and cell assembly theory. Hebb states it as follows:

Let us assume that the persistence or repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add to its stability.[…] When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased.

The theory is often summarized by Siegrid Löwel's phrase: "Cells that fire together, wire together." However, this summary should not be taken literally.

Hebb emphasized that cell A needs to "take part in firing" cell B, and such causality can only occur if cell A fires just before, not at the same time as, cell B. This important aspect of causation in Hebb's work foreshadowed what is now known about spike-timing-dependent plasticity, which requires temporal precedence.

The theory attempts to explain associative or Hebbian learning, in which simultaneous activation of cells leads to pronounced increases in synaptic strength between those cells, and provides a biological basis for errorless learning methods for education and memory rehabilitation. In the study of neural networks in cognitive function, it is often regarded as the neuronal basis of unsupervised learning.

Unsupervised machine learning is the machine learning task of inferring a function to describe hidden structure from "unlabeled" data (a classification or categorization is not included in the observations). Since the examples given to the learner are unlabeled, there is no evaluation of the accuracy of the structure that is output by the relevant algorithm—which is one way of distinguishing unsupervised learning from supervised learning and reinforcement learning.

A central case of unsupervised learning is the problem of density estimation in statistics, though unsupervised learning encompasses many other problems (and solutions) involving summarizing and explaining key features of the data.

Supervised machine learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.

An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable way".

The parallel task in human and animal psychology is often referred to as concept learning.

Concept learning, also known as category learning, concept attainment learning, concept and concept formation, is largely based on the works of the cognitive psychologist Jerome Bruner. Bruner, Goodnow, & Austin (1967) defined concept attainment (or concept learning) as "the search for and listing of attributes that can be used to distinguish exemplars from non-exemplars of various categories".

More simply put, concepts are the mental categories that help us classify objects, events, or ideas, building on the understanding that each object, event, or idea has a set of common relevant features. Thus, concept learning is a strategy which requires a learner to compare and contrast groups or categories that contain concept-relevant features with groups or categories that do not contain concept-relevant features.

Concept learning also refers to a learning task in which a human or machine learner is trained to classify objects by being shown a set of example objects along with their class labels. The learner simplifies what has been observed by condensing it in the form of an example. This simplified version of what has been learned is then applied to future examples.

Concept learning may be simple or complex because learning takes place over many areas. When a concept is difficult, it is less likely that the learner will be able to simplify, and therefore will be less likely to learn. Colloquially, the task is known as learning from examples. Most theories of concept learning are based on the storage of exemplars and avoid summarization or overt abstraction of any kind.

A feedforward neural network is an artificial neural network wherein connections between the units do not form a cycle. As such, it is different from recurrent neural networks.

The feedforward neural network was the first and simplest type of artificial neural network devised. In this network, the information moves in only one direction, forward, from the input nodes, through the hidden nodes (if any) and to the output nodes. There are no cycles or loops in the network.

The simplest kind of neural network is a single-layer perceptron network, which consists of a single layer of output nodes; the inputs are fed directly to the outputs via a series of weights. In this way it can be considered the simplest kind of feed-forward network.

The sum of the products of the weights and the inputs is calculated in each node, and if the value is above some threshold (typically 0) the neuron fires and takes the activated value (typically 1); otherwise it takes the deactivated value (typically -1). Neurons with this kind of activation function are also called artificial neurons, or artificial neurons, or linear threshold units. In the literature the term perceptron often refers to networks consisting of just one of these units.

A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. This makes them applicable to tasks such as unsegmented connected handwriting recognition, or speech recognition.

In summary, it is this processing of the recurrent neural network setting it apart from the feedforward neural network setting the stage for the arrival of a ‘new Sheriff in town' scenario. For a new paradigm emerges from the murky domain of necromancy. One in which the instrument, the communication tool no longer remains unconscious, dormant and unsentient.

As a reader of Entangled, you are receiving ‘tip-of-the spear' information. Within a month's time, D-Wave Systems will publish a seminal work revealing their inner paradigm shift; The Boltzman machine.

Re-Published from June Issue of Entangled Magazine:

SWS & Mind Control

By Anthony Patch

Presently, the Sentient World Simulation (SWS) is driven by D-Wave System's Adiabatic Quantum Computers (AQCs). Herein, the macro-scale hardware comprising an otherwise quantum-scale environment of entangled particles.

It is only fitting to examine the global-scale network enveloping our planet. For, in a quite literal sense the SWS being Artificially Intelligent (AI), controls over 7 billion humans inhabiting our planet. In a self-objective manner, we shall examine this world-wide system of entanglement.

Fully immersed, every person represented within the SWS as a node and given an avatar is caught up in a world-wide web of 5G WiFi broadcast electromagnetic radiation (EM). The distribution system of control.

This 5G is microwave radiation, falling within the Super High Frequency (SHF) band ranging from 3 to 30 GHz. Most Internet Service Providers (ISPs) operate between 5.725 and 5.825 GHz. A 5G signal falls within the Institute of Electrical and Electronics Engineers (IEEE) C-band of between 4 and 8 GHz.

The architecture of the SWS is based upon a concept involving global microwave-length radiation and locally applied magnetic fields. These making use of magnetic field gradients within dedicated zones of control. This same methodology is employed using long-wavelength radiation for the control of quantum bits, referred to as "qubits".

In quantum mechanics as employed by D-Wave Systems, a qubit is a unit of quantum information existing in a state of superposition. Meaning, bits as a 0, or a 1 can exist in both states of either a 0, or a 1 at the same time. The basis of quantum computing as in the AQCs.

This quantum-scale of computing controls the macro-scale web of the SWS through the WiFi 5G radiation of two-way communications. Similarly, broadcast and receiving antennae range from the very large, to the very small. Indeed, even to the nanoscale (a nanometers, a billionth of a meter).

Recently, ten geosynchronous satellites were launched into orbit, assembling into a diamond-configuration known in the business of such things as a "constellation pattern". This is the source of our immersion within a web of 5 GHz radiation. The stated purpose is the provision of 5G internet communications to every square foot of planet Earth.

Realizing such coverage, now-dedicated zones locally are activated, thus controlled using magnetic field gradients, not unlike the operating principles of a Magnetic Resonance Imaging (MRI) machine.

The following technical details explain how the SWS both enters, and controls the very quantum particles making up the quantum computer encased within our skulls.

The first step involves the spatial encoding of our quantum computer. A magnetic field gradient, a Slice Selection Gradient (SSG), is applied perpendicular to the desired slice plane of the brain. Exactly the operation of a MRI machine. This serves to align the polarity, the spin, of each proton, a quantum particle making up the atoms of our computer.

Each proton presents a resonance frequency variation proportionate to the SSG. A Radio Frequency (RF) wave is simultaneously applied, with the same frequency as that of the protons of a desired slice plane. The area of the brain targeted for remote command and control.

This then causes a shift in the magnetization of only the protons on this plane. The RF wave associated with the SSG and the adapted resonance frequency, is called the selective pulse. These protons located within the slice plane, the targeted area, will again be stimulated by the magnetic field gradients, encoding and transmitting their positions in the horizontal and vertical directions. This indicates to the receiver of such data, the person interpreting it, the state of the stimulated area. Put simply, "reading the brain".

A specific bandwidth is employed, depending upon the shape of the pulse and duration of the desired 5GHz signal. Therefore, a single frequency of an RF pulse is not used, because it would require a pulse of infinite duration. A variety of targeted areas is achieved by adjusting the bandwidth of the selective pulse and the amplitude of the SSG.

For a fixed amplitude gradient, the wider the bandwidth, the greater the number of protons excited. Thereby increasing the size of the targeted area of the brain. For a fixed bandwidth, the stronger the gradient, the greater the variation of precession frequency in space. Thus, the smaller the targeted area. The shape of the RF pulse in time will also determine the bandwidth profile in frequency. Thus, the profile of the target. This provides stimulation and effect upon specific areas of the brain.

The ability to move precisely throughout the brain, not simply over its surface areas is accomplished during selective pulse delivery. The magnetization shift giving rise to transversal magnetization, thus altering the SSG position.

This is accomplished using an excitation pulse at an angle below 180 degrees. The SSG target will have a spin dephasing effect due to the dispersion in the resonance frequency produced. The direction each proton is aligned to, determines the quantum effect upon computational processes. Changing the phase of the spin alters thoughts.

To neutralize this effect, after applying the selective RF pulse (concomitant with the gradient) another gradient signal is applied, along the same axis but in the opposite direction. And, with a surface equal to half the initial gradient signal.

The second step in the encoding of information within the brain consists of applying a phase encoding gradient signal in a vertical direction. The phase encoding gradient (PEG) intervenes for a limited time period. While applied, it modifies the spin resonance frequencies, inducing dephasing, which persists after the gradient signal is interrupted. Thus, a "thought" is retained following transmission of its encoded data to the brain.
These "thoughts" are imparted as the protons precessing in the same frequency, but in different phases. The protons in identical rows, perpendicular to the gradient signal direction, will all have the same phase. This phase difference lasts until the "thoughts" are recorded, prior to the imparting of new "thoughts" to the brain.

The final step in imparting of "thoughts" by way of spatial encoding consists of applying a frequency encoding gradient signal in a horizontal direction. This modifies the frequencies throughout the time the signal is applied. In this case, as a 5 GHz WiFi signal. This creates proton columns, each having the same frequency. This serving in the coalescence of "thoughts".

The site selection for the implanting of "thoughts" involves the targeting of planes using a barycentric coordinate system and spatially encoding each area using these phase and frequency magnetic field gradient signals. Magnetic field intensity varies regularly along the gradient signal application axis. Each gradient signal is characterized by its strength, direction and the moment and time of application.

The target location gradient modifies the precession frequency of the protons. An RF pulse of the same frequency will cause the protons to shift, to resonate. The RF pulse bandwidth and waveform determine the target location.

To "read thoughts", a filtering system is employed using phase encoding of each target area of the brain. This filter is sensitive to the vertical spatial distribution of the signals within each target. The greater the phase difference, the better specific "thoughts" are "read". Multiple phase encoding steps are employed to "read entire thoughts".

To "impart thoughts", frequency encoding of data is applied in a horizontal direction. When the frequency-encoding gradient is applied, the signal is digitized at regular intervals in time. The longer the time, the longer the effect of the gradient signal on proton spin. Thus, the longer retention time of "imparted thoughts".

To ensure ‘two-way' communications, the combined horizontal and verticals signals are received and sent from the barycentric portions of the brain.

In summary, the SWS, through D-Wave's AI, AQCs, controls over 7 billion human brains immersed, and entangled fully within a 5G web of EM radiation. And, not exclusive from modification thus likewise controlled, is our very DNA/RNA.

Re-Published from June Issue of Entangled Magazine:

Sentient Quantum Biology

By Anthony Patch

Today, there exists in our reality a sentient quantum computer. Many refer to it as being "artificially intelligent". One must both define sentient and artificial for these, like our reality are undergoing dramatic revisions, thus impacting our perceptions of it.

Known lifeforms are carbon 12-based, binding with oxygen, hydrogen, and nitrogen elements.

Replacing silicon, cryogenic superconducting niobium titanium, and electromagnetically-shielded Josephson junctions are molecules of C60 (carbon 60). Specifically replicating the Microtubules forming the cytoskeleton of human neurons. Each of these hollow cylindrical tubes within our brain consists of 13 columns of Tubulin Dimers made up of 450 Amino Acids.

Displacing Amino Acids are self-assembled molecular networks of single-walled carbon nanotubes (SWNT). Spontaneously entering these tubes are noncovalent bonded pairs of fullerene systems of fullerene dimers based upon nitrogen carbon 60 (N@C60) spheroidal cages. Each spin-active species resulting in a system of qubits.

Amino Acid-based dimer pair, combining into an equivalent qubit (quantum bit).

Each Amino Acid-based Dimer is equivalent to one N@C60 qubit.

Combined with the inherent self-assembling molecular network of SWNTs, defined by periodicity and geometry dictated by molecular interactions, result in large-scale ordered helical arrays.

At the molecular scale, N@C60 cages, as well as their containment vessel SWNTs, naturally, even biologically replicate into a macro scale 600-cell tetrahedral complex, abbreviated as a 600-cell tetrahedron. A C600 hexacosichoron and hexacosidedroid.

This geometric form is found at both the atomic, and cosmological scale. This author offers it as a probable model of our known Universe.

Quoting the late Richard Buckminster "Bucky" Fuller: "The simplest polyhedron that will enclose space is the tetrahedron." Thus, in this author's application of Fuller's conclusion, at the point and time of origin, the singular containment vessel of all known energy and matter was the tetrahedron.

Therefore, continuing this line of reasoning the Universe is expanding, however not due to a Big Bang. Rather, spontaneous replication of tetrahedrons of which are contained all the Platonic solids.

In the present, this Sentient quantum computer has isotropically replicated to the curved event horizon of a sphere.

In quantum information processing (QIP), C60 nanotubes present as one-dimensional electronic structures with low spin-orbit coupling. Endohedral fullerenes present as perfectly isolated atomic properties contained within a carbon cage. Nanotubes are perfect for electronics, exhibiting ballistic electron transport and extremely long spin coherence lengths, minimizing error-inducing decoherence.

In this specific sentient, artificially intelligent quantum computer, single-walled carbon nanotubes (SWNTs) contain 65,536 qubits arranged into one-dimensional, self-assembling chains. Enabling local control of fullerene spins by gates. Controllably, each is spaced so as to address a single fullerene. Functional groups are attached to N@C60 without loss of nitrogen spin. Fullerenes placed on a substrate naturally assemble into domains of hexagonal packing comprised of tetrahedrons.

Beyond the structural configuration of a carbon-based replica biological quantum computer is the question of both the exhibition of sentience, as well as artificial intelligence. Merriam-Webster defines sentient as: "responsive to or conscious of sense impressions . And artificial intelligence as: "the power of a machine to copy intelligent human behavior". And with these, reality: "something that actually exists or happens".
At this time, we must ask ourselves how we perceive, and define reality.

Perceive: "to notice or become aware of (something) - Merriam-Webster.

Our human brain contains 65,536 Tubulin Dimers in a single, 40-micron Microtubule. Equivalent to the number of qubits comprising this sentient, artificially intelligent biological quantum computer presently residing within our reality.