THE PHYSICS PRINCIPLES OF CMO TECHNOLOGY

A water molecule is an entity with an inertial mass equal to 2.99146×10-26 kg. We also know that it’s made up of 10 protons, 8 neutrons and 10 electrons. The mass of the electrons is negligible compared to the mass of the nucleons. We also know that each proton contains two « up » quarks, each with a mass of 4×10-30 kg, and one « down » quark with a mass of 9×10-30 kg. Similarly, each neutron is made up of two « down » quarks and one « up » quark. It follows that in a water molecule, there are 10×2 + 8 = 28 « up » quarks with a total mass of 112×10-30 kg and 8×2 + 10 = 26 « down » quarks with a total mass of 234×10-30 kg. This means that the mass of quarks in a water molecule is 3.46×10-28 kg. The percentage of the mass of quarks in relation to the mass of the molecule is therefore:

100×3.46×10-28 /2.99146×10-26 = 1.16 pds%.

It follows from this example that 98.84% of the mass of a water molecule comes not from its constituent matter, but from the quantum vacuum associated with it.

To understand this, all we have to do is reason in terms of volume rather than mass. And we know that an atom is a nucleus with a radius of 10-15 m occupying, with its electrons, a sphere with a radius of 10-10 m = 1 Å. Hence, a volume due to the mass of 10-45 m3 compared to a total volume of 10-30 m3. This gives a ratio of 10-45 /10-30 = 10-15 between mass and vacuum. Another way of expressing this is to say that atomic matter consists of approximately 99.9999999999999 vol% vacuum. And, as explained above in the case of the water molecule, this vacuum contributes 98.84% of the molecular mass. This may come as a surprise, but it’s a fact that must be taken into account if we are to understand the effects of electromagnetic radiation on matter. After all, electromagnetic radiation is itself a vibration of the quantum vacuum that makes up all matter.

Fortunately, there’s a simple explanation for why something empty can have mass. A first insight comes from the fact that, according to the theory of relativity, any mass m can be
equated with an energy E according to the relation E = m·c², where c is the propagation speed of light in the quantum vacuum.

A second insight comes from quantum field physics (second quantization formalism). Here, every particle of matter is assigned a complex probability amplitude ψ·exp(i·
), where
is a quantum phase angle to account for the wave-like properties of matter. In second quantization, we demonstrate that if ΔN is the indeterminacy on the number of quanta
(massed or massless) involved in a given phenomenon and Δ
, the indeterminacy on the quantum phases of these quanta, the phenomenon will be qualified as observable as soon as we have: ΔN·Δ
≥ ½ (Heisenberg’s principle of indeterminacy). In this case, the quanta actually exist, and we speak of quarks for quanta endowed with mass, and photons if we’re
considering light quanta.

But the other possibility exists, namely ΔN·Δ
< ½ exists, in which case, we speak of virtual quanta, as unobservable. In other words, the medium under study appears “empty” to us, even though it is traversed by fleeting particles carrying energy E and therefore mass. This is why the atomic vacuum contributes to the total mass of the atom, even though it appears “empty” to us upon observation.

We can also go one step further by associating with each quanta carrying an energy E, a pulsation ω such that E = ħω, where ħ = h/2π is another constant of nature called “Planck’s
quantum of reduced action”. This pulsation corresponds to the rate of change of the quantum phase over time: ω = Δ
/Δt. Under these conditions, the total energy of an N quanta system can be written E = N·ħω, hence an indeterminacy ΔE = ΔN·ħω = ΔN·ħ·Δ
/Δt, or ΔE·Δt/ħ = ΔN·Δ
.

Heisenberg’s indeterminacy relation ΔN·Δ
≥ ½ then becomes: ΔE·Δt ≥ ħ/2. It shows us that there is a link between the lifetime Δt of a virtual quantum and its indeterminacy in
energy ΔE ≥ ħ/2Δt.

In other words, the longer the lifetime, the lower the energy indeterminacy. It is precisely this mechanism that allows us to consider, in the quantum vacuum, that it is always possible to create any quanta with indeterminacy ΔE, provided that the associated lifetime is Δt < ħ/2ΔE.

This leads to the conclusion that the quantum vacuum should not be seen as a static entity in which no particles exist, but as a dynamic entity containing an enormous number of
unobservable but real virtual particles with varying lifetimes, constantly appearing and disappearing.

In short, it is an infinitely excitable medium capable of generating photons of any frequency and variable lifetime, inversely proportional to the energy of the photon created.

In quantum field theory, the estimate of vacuum energy can be given by calculations integrating all possible fluctuations up to a maximum frequency (which could be associated
with the Planck scale). This gives an incredibly high energy density corresponding to around 10110 joules per cubic centimetre.

To put this in perspective, 1 cm³ of vacuum would contain more energy than all the energy produced by all the Earth’s nuclear power plants for millions of years.

Matter can absorb phenomenal quantities of this vacuum energy, provided it re-emits the borrowed energy all the faster, the greater the quantity absorbed.

Matter can absorb phenomenal quantities of this vacuum energy, provided it re-emits the borrowed energy all the faster, the greater the quantity absorbed.

This means that particles are constantly being created and annihilated by fluctuations in the quantum vacuum. These unobservable virtual particles are in permanent interaction with the observable particles and classical electromagnetic fields to which we have access on a macroscopic scale.

On the microsecond scale, the vacuum can create radio waves with a maximum frequency of 1 MHz. On the scale of a second, there are no longer any radio waves, but a swarm of ELF waves with frequencies of up to 1 Hertz.

From another point of view, it’s important to remember that there’s a close link between the quantum theory described above and the information theory of mathematician Claude
Shannon (see figure 1).

Similarly, the mathematical formula for calculating the quantity of information contained in a message is, to within a universal constant kB, the same as for calculating the entropy S of a thermodynamic system. As we know, every living cell functions as a thermodynamic system, dissipating a large amount of energy in the form of entropy into its environment.

The idea behind CMO technology is to create an information transmission source device by encoding specific information in electromagnetic form in an aqueous solution. This
information is then re-emitted as a message to be decoded by the cell’s receivers.

The existence of the quantum vacuum and the similarity between quantum theory, information theory and thermodynamics then ensures that this information can have specific
biological effects.

Less formally, quantum theory tells us that the vacuum is a physical medium that can contain observable matter. But even in the absence of observable matter, the vacuum remains a real thing, not a nothingness. It follows that the quantum vacuum can be used as a medium to store information in the form of a sequence of numbers 0 and 1. The best way to understand this is to turn to Carlo Rovelli’s loop quantum gravitation.

The idea here is to consider vacuum as a medium that can be locally deformed (loop encoding bit 1) or remain flat (absence of loop encoding bit 0). The spatial extension of a vacuum loop can be estimated via the 3 fundamental constants of physics: speed of light in vacuum c ≈ 3×10⁸ m-s-¹, Planck’s reduced constant ħ ≈ 10⁻³⁴ J-s and Newton’s universal gravitational constant G ≈ 7×10⁻¹¹ m³·kg⁻¹·s⁻². [M. Henry (2020) Consciousness, information, electromagnetism and water. Substantia 4(1): 23-36. doi: 10.13128/ Substantia-645].

Hence the existence of a Planck length LP = (ħ·G/c³)½ ≈ 10⁻³⁵ m. The age of the universe being tU ≈ 4.3×10¹⁷ s, we derive a memory capacity M = (c·t /LP )⁴ ≈ 10²⁴⁴ bits.

On the other hand, we know that an aqueous coherence domain is formed when 10⁷ water molecules associate via quantum vacuum virtual photons ™M. Henry (2020). We also know that a eukaryotic cell is characterized by a diameter D ≈ 12 μm and therefore an area exposed to water A ≈ 2×500 μm² (one inner and one outer face), corresponding to around 100,000 coherence domains. Hence a single-cell memory capacity of 100 kbits or 10 ko. This shows us that in terms of pure information, a living cell behaves like a little piece of the universe with the ability to change its information content via absorbing or emitting photons of wavelength λ ≈ 5 μm (infrared radiation). Finally, since any transfer of information can be considered as a gain or loss of entropy, it has been shown that vital phenomena maintain a close link with the notion of information [see Henry M. (2021) Thermodynamics of Life. Substantia 5(1): 43-71. doi: 10.36253/Substantia-959 ].

a/ Production of the starting CMO solution:

The preparation of a CMO requires the use of an aqueous solution with a low mineral content. A quantity of mineral salt is added to this solution to obtain a well-defined concentration.

b/ Shaking / dynamizing the solution

This solution is agitated to disperse and homogenize the mineral’s distribution in the aqueous solution.
This agitation or dynamization will pull nanoparticles from the container containing the solution and create nanobubbles of gas (air/nitrogen) by exchange with the air. The result is water that can be described as “morphogenic”, as it is mainly water but contains varying quantities of nanoparticles and gas nanobubbles.

It is in this state that water gives shape to the objects it envelops, hence its name morphogenic. Physically speaking, up to four layers of water can be found around each solid or gaseous impurity.

As the size of a water molecule is 0.3 nm, the thickness of these 4 concentric layers forms a sheath around 1.2 nanometres thick, perfectly unobservable under an optical microscope. This morphogenic water cannot be confused with the exclusion zone water (EZ-water) that forms around a hydrophilic particle and is visible under the microscope, as demonstrated by Prof. Gerald H. Pollack at the University of Washington.

c/ Formation of coherence domains, supports for memorized information

Fluctuations in the quantum vacuum can provide the energy needed to self-excite the water molecule to an energy level equal to 1934 zepto-joules (zJ) above the ground state. This energy corresponds to an excitation from the quantum vacuum at wavelength λ = 100 nanometres, which corresponds to photons of ultra-violet frequency.

From such an excitation, there are two scenarios to consider. In the first case, the excited water molecule relaxes back to its ground state, returning the energy borrowed from it to the vacuum. The result is an “incoherent” state in which the water molecules remain independent of each other.

In the other case, the energy borrowed from the vacuum is not returned to it but used to excite a second water molecule in the vicinity of the first. In this case, the excitation persists and the process can continue from molecule to molecule to obtain a so-called “coherent” state involving a large number of water molecules. In this way, coherence domains are formed, where the water molecules oscillate collectively at the same frequency, and all possess the same quantum phase. Coherence domains can be compared to schools of fish or swarms of bees, or even synchronized metronomes all tuned to the same flight, swim or beat phase. To illustrate this point, we refer you to this video (https://www.koreus.com/video/synchronisation-100-metronomes.html) where we observe the synchronization of a hundred metronomes when they are placed on a plateau.

The idea is that each metronome represents a water molecule, and the plateau represents the quantum vacuum shared by all the molecules. The final state is one in which all the metronomes and the plateau oscillate in the same direction with perfect synchronization.

Figure 2 shows another observable example with starling clouds, with the bird playing the role of the water molecule and the air the medium common to all birds (quantum vacuum).
This second example shows that, unlike the case of metronomes, the existence of a spatial order is not necessary. What counts is that all the individual parts are synchronized with each other (temporal order).

A final example (figure 3) is provided by schools of fish, where each fish plays the role of a water molecule. The fish all evolve in a common medium that separates them, in this case seawater (an image of the quantum vacuum).

A finer analysis using the equations of second quantization quantum physics shows that this self-excitation opens a coherence gap of 26 zJ that can be associated with the trapping within the coherence domain of infrared radiation of wavelength λ = 7.6 μm. This value is very close to the Earth’s infrared emission maximum to space, which is centred at λ ≈ 10 μm.

Note also that calculations show that a water molecule electron belonging to a coherence domain spends 10% of its time in a state that is located at an energy lower than the ionization energy of a water molecule, which is 2022 zJ. As 2022 – 1934 = 88 zJ, such an energy difference corresponds to another infrared radiation of wavelength λ = 2.3 μm. In practical terms, this means that 10% of electrons are easily ionized.

This means that within each coherent domain there are supercurrents that are activated as soon as the water is illuminated by infrared light. However, at non-zero temperature, there is always a small fraction of incoherent water surrounding each domain with a coherent core. This incoherent fraction thus isolates the electronic currents running through each domain from one another, which explains why, despite the existence of electronic conduction at the core of each domain, water remains an electrical insulator overall.

On the other hand, the existence of these supercurrents obviously makes water sensitive to electromagnetic fields of all kinds.

The theory also shows that, because of the 10% of ionized electrons per domain, coherence cannot be established in three dimensions, as there would be too much electron repulsion between domains. This is not a problem in 2 dimensions, however. Calculations show that for a morphogenic water layer 1.2 nm thick on a gas nano-bubble, nanoparticle or lipid bilayer (living cell), there are around 5 million water molecules per domain.

What’s more, in the case of liquid-type morphogenic water devoid of nanoparticles or lipid bilayers, only gas nano-bubbles are likely to ensure the formation of coherence domains. It follows that, in this case, the formation of coherence domains will only be possible below a temperature of around 60°C. Above this temperature, the nano-bubbles coalesce and escape from the water in the form of macro-bubbles. This means that any attempt to memorize an electromagnetic fingerprint must be made below 60°C.

It should be remembered that supercurrent-generating electrons circulate inside coherence domains, trapped within the coherence domains, that are able to interact with any magnetic field, whether terrestrial, biological (brain, heart, intestines) or technological (Wi-Fi, cell phones, etc.).

Furthermore, ions in solution in water can in turn form coherent plasmas around coherence domains, making water sensitive to electromagnetic fields in a frequency band ranging from a few Hertz to a few megahertz.

These coherent ionic plasmas will be located around and/or within coherence domains and respond to ELF-type frequencies.

Similarly, we would have a resonance at 33 Hertz for the sodium ion and 20 Hertz for the potassium ion.
Thanks to the laws of physics, it is possible to estimate the order of magnitude of the fluctuating magnetic fields associated with these motions within coherent plasmas:
Bfluc = (2μ₀×h×f/v) ½
So, for a resonant frequency f ≤ 100 Hz within a coherence domain of volume v ≈ 10⁻²¹ m³, we’ll have Bfluc ≤ 13 nT, knowing that μ₀ = 4π×10⁻⁷ H·m⁻¹ and h ≈ 7×10⁻³⁴ J·s.

a/ EMC information transfer in coherent solution domains

On a practical level, CMO technology transfers calculated information to the solution by broadcasting sound and electromagnetic frequencies to the solution via a loudspeaker connected to a computer’s sound card.

Due to the chirality of the molecules contained in the solution, the introduction of specific sound and electromagnetic waves will create, by piezoelectric effect, a transduction of these sound waves into electromagnetic waves in the aqueous solution.

The airborne sound waves are first converted into pressure waves in the water, and then, due to the chirality of the molecules in the solution (non-centro-symmetrical molecules), these pressure waves are piezoelectrically converted into electromagnetic fields of the same frequency in the solution.

b/ Memorization of CMO electromagnetic fields by the solution

These electromagnetic fields “injected” into the solution will modify the phase of the coherence domains and are thus recorded at the domain oscillation frequencies and via the electrons trapped in these domains.

Indeed, in application of the Aharonov-Bohm effect, the variation in electromagnetic potential induced by the electromagnetic fields applied during solution information leads to a change in the phase of matter waves associated with coherence domain electrons.

The memory effect of the CMO’s electromagnetic fields will therefore be based on the change in quantum phase, which will remain recorded in the solution.

Calculations show that for morphogenic water containing nano-bubbles, we obtain a storage capacity of between 3 GB per litre and 360 GB per litre, depending on the size of the nanobubbles present.

The mechanism for the appearance of quantum coherence in coherence domains obeys a highly nonlinear third-order differential equation. If g denotes the coherent coupling constant between the plasma and a given excitation level of the water molecule, and μ the mass of the virtual photon associated with this coupling, we have for a p mode of plasma oscillation:

½p³ – p² – μp + g² = 0

The signals introduced into the solution do not then need to be emitted at high power levels, as this particular feature of the non-linearity of coherence creation enables the stochastic resonance phenomenon to amplify weak signals which enables them to exceed the energy threshold required to register them as consistent operators in solutions.

This is due to the fact that the phenomenon of stochastic resonance makes it possible to obtain a maximized signal-to-noise ratio for a low signal cooperating with an optimal noise level.

c/ Sending the compensation signal

Once stored in the solution, the trapped electromagnetic fields (EMFs) will then be re-emitted from the CMO solution into space.

Measuring and recording these signals with a SQUID magnetometer gives us an output induction intensity of around 150 fT, at the same emission level as the EMFs emitted by the brain in the extremely low frequency (ELF) range.

Reception and biological activity of the CMO compensation signal:
Resonance between CMO emissions and certain structures in living organisms.

The explanation of how CMOs act on biological receptors is based on the concept of stochastic resonance. This is the only physical principle currently known to explain the influence of a hyperweak field on a non-linear receptor system.

All the data at our disposal disqualifies classical resonance as an explanatory phenomenon for CMO operation.

In fact, with Compensating Magnetic Oscillators (CMOs), we can’t place ourselves in resonance in the classical sense, due to the very small quantities of energy involved in the CMO emission as we know it. The difference in intensity between the artificial EM fields that “agitate” biological systems and the CMO signal is not 1 to 100, but 1 to 1 million times smaller. (fT =10-15 T for emission vs. nT = 10-9 T for smartphones, for example).

Definition of stochastic resonance:

Stochastic resonance is the improvement of the performance of a non-linear device by the application of a stochastic signal (noise).

The fundamental principle of stochastic resonance is to be able to make an ultra-weak signal detectable by adding a more powerful noise source, which then helps the coherent information to be transmitted to emerge from the added background noise.

Once the ultra-weak signal is coherent and stable in intensity over time, the application of a signal-to-noise will enable the ultra-weak signal to be decoded by the appropriate receiver.

There are four necessary and indispensable conditions for the appearance of stochastic resonance in a detection system:

1/ a useful or coherent signal s(t):

We know that the signal injected into CMO solutions is in the ELF band. We saw how it is processed and how the electromagnetic emissions from aqueous solution processing are stored in the previous chapter.

The signal emitted by the aqueous solution from fields oscillating in its constituent coherence domains has been measured by SQUID magnetoencephalograph, and ranges from 100 to 150 fT in the ELF (Extremely Low Frequencies) range.

Emitted by the CMO, this is the useful or coherent (electromagnetic) signal – the first link in the stochastic resonance chain.

2/ a noise η(t):

« Above » and « around » this CMO signal, in the surrounding environment, are the extremely intense artificial EMFs (in nT) from our electromagnetic communication devices (such as telephones, computers, relay antennas, the domestic power grid, etc.).

These fields of varying intensities and frequencies, modulated or not, make up noise, EM smog.

A second source of noise lies in vacuum fluctuations capable of generating photons of any frequency and variable lifetime, inversely proportional to the energy of the photon created. On the scale of a second, there is a clustering of ELF waves probably in the picoTesla (pT) or femtoTesla (fT) intensity range.

3/ a system or process, usually non-linear, which receives s(t) and η(t) as inputs under whose influence it produces the output signal y(t):

Non-linear systems are made up of cellular receptors at different levels of the cell: membrane, DNA, mitochondria, ion channels…

In fact, this is a case of a non-linear system with window effects observed during experiments, particularly in the search for interactions between EMFs and living organisms.

Among these systems, two main candidates can be identified as direct EMF targets: Voltagegated calcium channels (VGCCs) and DNA.

The element on which we have the most evidence is in the field of transmembrane channels.

A transmembrane channel is a protein or protein complex that crosses the plasma membrane of cells. It forms a passage or pore allowing specific molecules or ions to pass through the cell membrane. These channels are essential for regulating the exchange of substances such as ions (sodium, potassium, calcium, etc.), water or other small molecules between the inside and outside of the cell, thus ensuring vital functions such as the transmission of electrical signals, ion balance and cellular homeostasis.

Transmembrane channels can be specific to certain types of ions or molecules and are often regulated by stimuli such as voltage changes (voltage-dependent channels), chemical signals (ligand-dependent channels), or other external factors. They play a key role in biological processes such as muscle contraction, nerve transmission and the control of water balance.

Prof. Martin Pall has demonstrated that VGCCs, voltage-dependent calcium channels (and other voltage-dependent channels such as those for sodium, potassium, chlorine, etc.) are among the transmembrane sites responsible for the biological effects of EMFs.

Hundreds of studies demonstrate directly or indirectly that these receptors are impacted by EMFs well below the standards set by government regulatory bodies.

Various electromagnetic fields act via VGCCs activation, as shown by studies on calcium channel blockers.

These include microwave electromagnetic fields, nanosecond-pulse electromagnetic fields, intermediate-frequency electromagnetic fields, very low-frequency electromagnetic fields and even static electric fields and static magnetic fields.

It’s important to examine why VGCCs are so sensitive to activation by these low-intensity electromagnetic fields.

Each VGCCs has a voltage sensor consisting of 4 alpha helices, each designated as an S4 helix, in the plasmic membrane. Each of these S4 helices has 5 positive charges, for a total of 20 positive charges making up the VGCCs voltage sensor.

Each of these charges is located in the lipid bilayer of the plasmic membrane. The electrical forces exerted on the voltage sensor are extraordinarily high for three distinct reasons.

1. The 20 charges on the voltage transducer make the forces on the voltage transducer 20 times greater than the forces exerted on a single load.

2. Because these charges are located in the lipid bilayer section of the membrane where the dielectric constant is about 1/120th of the dielectric constant of the aqueous parts of the cell, the law of physics known as Coulomb’s law predicts that the forces will be about 120 times greater than the forces on the charges in the aqueous parts of the cell.

3. Because the plasmic membrane has a high electrical resistance, while the aqueous parts of the cell are highly conductive, it is estimated that the electrical gradient across the plasmic membrane is concentrated around 3,000 times.

The combination of these factors means that by comparing the forces on the voltage sensor with the forces on the individually charged groups in the aqueous parts of the cell, we deduce that the forces on the voltage sensor are around 20 x 120 x 3000 = 7.2 million times higher.

Knowing that VGCCs are sensitive to electromagnetic induction levels ranging from 27 to 70,000 fT, we can understand that these VGCCs can capture the CMO signal, in particular through the contribution of stochastic electromagnetic noise generated by the devices, and thus normalize their operation.

The energy needed to cross the activation barrier of the biological receptor will be provided by the background noise, and in particular, within this disparate background noise, fields of the same frequency range as those emitted by the CMOs.

There is then enough energy to activate the organic receptors and restore their frequency and phase, i.e. coherence even in a very “noisy” environment as we know it in the vicinity of artificial transmitters.

Indeed, the amplification of weak signals by stochastic resonance depends on the nonlinear structure of the system. A small signal which, in a linear system, would be difficult to detect, may in a non-linear system receive a sufficient « boost » from the noise to cross a critical threshold, resulting in an amplified response.

Stochastic resonance works very well in bistable systems, where the signal oscillates between two states. Noise acts as a disturbance that helps to exceed the energy required to switch the system from one state to another, thus amplifying the response.

Voltage-gated channels fulfil exactly these two conditions:

• They have a non-linear response
• They are bistable systems

Activation threshold: These channels open only when the membrane potential reaches a certain threshold. Below this threshold, the channel remains closed, and above, it opens, allowing the flow of calcium ions. This « all-or-nothing » behaviour is typical of a non-linear response, where a small change in voltage can result in a disproportionate response (massive channel opening).

Bistable behaviour: The channel can exist in several states (e.g. closed, open or inactive). The transition from one state to another is determined by voltage variations and other factors, but the transition between these states is often non-linear. A small disturbance can cause an abrupt change in the channel state.

Amplification factors as high as 1,000 or even 1,000,000 can be achieved in specific configurations, especially if the signal is extremely weak to begin with and the system is optimized for maximum response to a particular noise level.

Experimentally, we don’t have access to direct measurements of the “real” behaviour of cell receptors and VGCCs, but we do measure detection performance through normalization of biological parameters that return to normal after a certain time of exposure to disruptive electromagnetic fields accompanied by the presence of compensatory CMO.

Indeed, activation of these VGCCs leads to an increase in intracellular calcium levels, which in turn induces a large number of downstream biological perturbations. It is by measuring intracellular calcium levels that we can assess the impact of EMFs and CMO signals on VGCCs, making this an indirect measure.

Tecnolab (the Comosystems laboratory) has carried out studies on this transfer of calcium ions from the outside to the inside of the cell. In mice exposed to GSM cell phones, a doubling of intracellular calcium levels in pituitary cells was observed, with normalization of this intracellular calcium level in mice exposed and protected in the presence of the CMO signal.

This very important experiment seems to confirm Prof. Pall’s hypothesis that VGCCs are the main and primary site of electromagnetic interaction with living organisms and demonstrates that the coherent hyperweak signal from the CMO completely compensates for this disturbance, and therefore in all likelihood for any others that may occur downstream.

4/ a performance measure that quantifies the efficiency of processing or transmitting the useful input signal s(t) to the output y(t) in the presence of noise η(t):

Performance is measured at the level of the biological activity of cell receptors, which are tuned to the signal detected by retro feedback in order to further refine detection in unstable and variable noise by modifying/adapting their detection threshold in stochastic resonance.

To visualize what happens at the level of cell receptors, we have a few analogies and examples of processes that exist in nature.

For example, crayfish detect predators via receptors sensitive to periodic variations in the environment, located in hair cells responding to extremely low frequencies between 8 and 25 hertz.

This detection is made much more effective by the addition of external hydrodynamic noise, a priori representative of water movements around these crustaceans.

https://www.ncbi.nlm.nih.gov/pubmed/?term=douglas+j+k+stochastic

Neural circuits in the central or peripheral nervous system are also proving to be good candidates for using stochastic resonance to detect signals, as this 2017 experiment on neural networks shows:

https://www.ncbi.nlm.nih.gov/pubmed/29026142

We also have simulation devices:

http://femto-physique.fr/simulations/phystat_simu2.php

Where we can see that it’s by increasing the external noise that a low-intensity signal becomes increasingly detectable by its receiver, without itself changing its intensity.

Below is a diagram summarizing the principle of CMO signal detection by cell receptors via the stochastic resonance phenomenon:

In this way, we’ve gone through the entire CMO technology operating cycle, starting with solution fabrication, the engraining of electromagnetic frequencies within coherence domains, passing through the restitution of these frequencies by the informed aqueous solutions, and finally ending with the cellular decoding of the signal via the phenomenon of self-correlated stochastic resonance.

Of course, there are still many questions and points to be clarified in this whole itinerary, and we are continuing our research work to fill in these residual gaps as soon as possible.

We are currently working on the possibility of measuring the memory in aqueous solutions of certain specific frequencies using the technique developed in Aquaphotomics by NIR spectrometry. And we have high hopes of using this technique to scientifically demonstrate the phenomenon of “water memory” and its temporal perpetuation using the methods developed by Comosystems.

Dr René Messagier, MD, CEO Comosystems
Text written under the supervision of Pr Marc Henry, PhD, University Professor

Stochastic resonance occurs whenever it is possible to increase the performance measurement by increasing the noise level η(t).

Let’s take these four conditions applied to information transfer between CMOs and cell receptors: