The Fabric of Reality

Back in 1997, David Deutsch, a brilliant British physicist, wrote a book that changed my view of reality by explaining the following concepts in clear prose and illustrative diagrams.

Quantum physics and its many-universes interpretation
The theory of evolution (Darwin/Dawkins)
The theory of computation (quantum computation)
The theory of knowledge (Karl Popper), explanation and understanding

The first pages describing light and how it interacts with other universes shows how the quantum world works, the section covering computing and how it relates to the other three topics opens the door to realizing that the multiverse is real and that quantum computing is nature's way of operating, something one would never realize prior to reading a book such as this. Prior to 2007, the notion of practical quantum computing becoming real was considered to be a thought experiment, something weird and wonderful and beyond the capabilities of tech but that is changing at rates that even amazes Deutch, who is considered to be the father of the QC.

Some of the events making the QC possible.
1. Stopping Light
2. Quantum Wells
3. Adiabatic Quantum Computing
4. Controllable Qubits
5. Seth Lloyd

Time to entering the Age Beyond Computation: Five/Ten years. Impact of same: Unknown.

The art of observation ...

Rev II on the duality of existence or why do we see a consistent view of reality even though Quantum Mechanics, as seen through the lens of precise experiments, shows, without question, the Alice in Wonderland characteristics of Quantum Mechanics to be anything but deterministic. Well, because everything is entangled and decohered, observation, which collapses the wave function, driven by existence 24/7, allows us to experience reality in consistent fashion.

To whit ...

Quantum decoherence is the loss of quantum coherence, the process in which a system's behaviour changes from that which can be explained by quantum mechanics to that which can be explained by classical mechanics. In quantum mechanics, particles such as electrons are described by a wave function, a mathematical representation of the quantum state of a system; a probabilistic interpretation of the wave function is used to explain various quantum effects. As long as there exists a definite phase relation between different states, the system is said to be coherent. A definite phase relationship is necessary to perform quantum computing on quantum information encoded in quantum states. Coherence is preserved under the laws of quantum physics.

If a quantum system were perfectly isolated, it would maintain coherence indefinitely, but it would be impossible to manipulate or investigate it. If it is not perfectly isolated, for example during a measurement, coherence is shared with the environment and appears to be lost with time; a process called quantum decoherence or environmental decoherence. As a result of this process, quantum behavior is apparently lost, just as energy appears to be lost by friction in classical mechanics.

In classical scattering of a target body by environmental photons, the motion of the target body will not be changed by the scattered photons on the average. In quantum scattering, the interaction between the scattered photons and the superposed target body will cause them to be entangled, thereby delocalizing the phase coherence from the target body to the whole system, rendering the interference pattern unobservable.

When the entanglement of a particle is experimentally created, the wonders of QM become evident.

Spontaneous parametric down-conversion process can split photons into type II photon pairs with mutually perpendicular polarization.

Quantum entanglement is the phenomenon that occurs when a group of particles are generated, interact, or share spatial proximity in a way such that the quantum state of each particle of the group cannot be described independently of the state of the others, including when the particles are separated by a large distance. The topic of quantum entanglement is at the heart of the disparity between classical and quantum physics: entanglement is a primary feature of quantum mechanics not present in classical mechanics.[1]

Everything is entangled

When two particles interact, their quantum states generally become entangled. Further interaction with other particles spreads the entanglement far and wide. Subsequent local manipulations of separated particles cannot, in the absence of quantum communication, undo the entanglement.

This is why precise experiments show how coherence occurs when depicting some of the wonderful mysteries of Quantum Mechanics while decoherence hides the mysteries of same under the guise of classical. :)

From Analog to Digital/Rev II

Trapping a beam of light in which the wavelength has been increased, which amplifies diffraction and interference effects. The simulation was suggested to me by viewer André Pscherer. It is based on a question on stackexchange, asking whether it is possible to trap a laser beam between reflectors: Nils Berglund

Mathematically correct, extraordinarily beautiful, this works shows light is analog. When hitting the reflectors, the photons become digital for a moment, (the photoelectric effect) going back to analog after leaving the reflector, thus showing Einstein was right as was Planck and Young in proving light is both a particle and a wave depending on the circumstance said photon finds itself at any given time. When looking at this in context of the Full System Audit, this is a prime example of 137, the specific address specified in the universal routing table for light quantifying the strength of the electromagnetic interaction between elementary charged particles.

De Broglie in 1929

When looking at how light behaves both as wave and particle, the same phenomenon applies to particles as seen by the experiment depicted below. As per deBroglie, the matter wave rules.

An illustration of particles behaving like a wave. Physicists have coaxed thousands of sodium nanoparticles into acting like waves in a new superposition experiment. (Image credit: Getty Images)

In the experiment, the team produced a beam of sodium nanoparticles and aimed it at a narrow slit. Their results, published Jan. 21 in the journal Nature, show that the sodium nanoparticles spread out to produce an interference pattern, exhibiting the strange quantum behavior known as wave-particle duality. These sodium nanoparticles have now collectively set the record for the most macroscopic objects to be observed in a quantum superposition.

When combined with entanglement, the Full System Audit begins to make sense as nature's lazy. The Principle of Least Action applies and Entanglement, the digital snapshot of analog quantum, happening at 232 Attosecond speed and decohering immediately thereafter, creates a consistent view of reality for all to see. Read below to see why this concept rings true.

At the deepest level of quantum physics, particles may not be as independent as they appear. New theoretical work shows that nonlocal behavior can emerge simply because identical particles are fundamentally indistinguishable. Credit: Stock

At the most fundamental level of physics, nature does not behave locally. Particles separated by vast distances can act not as independent objects, but as components of a single quantum system. Researchers in Poland have now demonstrated that this kind of nonlocal behavior, which stems from the simple fact that particles of the same type are indistinguishable, can be observed experimentally for nearly all possible states of identical particles.

As for the Universal Modeler ... Voxels are suitable for working with qubits as quantum computers, the analog hardware construct, is finally beginning to take off.

Schematic of how a metasurface shapes a single beam of light into multiple tightly focused beams in a single step. These beams form a series of optical tweezers to trap individual atoms into arrays with arbitrary geometry. Credit: Will and Yu labs, Columbia University

Neutral atom arrays have emerged as one of the leading approaches for building quantum hardware. In a key demonstration led by graduate students Aaron Holman and Yuan Xu from the Will and Yu research groups, the team successfully trapped 1,000 strontium atoms. Their results also show that the same technique can be extended to systems containing well over 100,000 atoms.

Atoms are well suited to serve as qubits because they naturally support the quantum behaviors required for computation, including superposition and entanglement. Just as importantly, every atom of a given type is identical. This removes the need to individually tune and synchronize qubits, a growing challenge for fabricated systems as their size increases.

Voxels can handle qubits without restriction.

The Grid (A): The discrete, binary alphabet of space.

The Solid State (B): A volumetric reality where the model and the object are one.

As per Full System Audit - Voxels, used in MRIs, is a way to model 3D structures (hearts, brains, etc, etc,) in ways impossible to do by any other means. For MRIs, it involves imaging slices of the organ in question and connecting the slices using lofting, The lofting connecting to the slices are voxels. Voxel generated lattices can encompass or model any arbitrary external geometry known to science. (including qubits) 3D printing also applies. 

Primary source for The Universal Modeler - Voxel Invention Kit: Reconfigurable Building Blocks for Interactive Electronic Structures (ACM Digital Library.

QC2, the optical Microtubule Quantum Computer

Penrose and Hammeroff were right. Microtubules is the start point for quantum processing in life,
a process that's been around since the beginning of time. 

In 2010, biologists made a shocking discovery. Living in the mud of the North Sea were microorganisms whose genes looked a lot like ours. Genetic analysis revealed that humans, oak trees, blue whales — any living things whose cells have nuclei and mitochondria — are related to these microbes, which were named the Asgard archaea after the home of the Norse gods. Two billion years ago, it was an ancestor of an Asgard that diverged from its kin and eventually became us.

In our cells, cytoskeletal proteins called tubulins snap onto each other to form soaring tubular arches and rails, capable of spanning entire cells, growing at one end while they fall apart at the other. These tubes, known as microtubules, form and bloom and decay in a dance that controls many aspects of eukaryotic life. They handle our chromosomes and help cells divide. They carry machines and act as tracks for motors. They push and pull cellular membranes, turning them into useful shapes.

This is quantum computing at room temperature, something life has been doing for four billion years.

 Fast forward to 2026, optical computing and artificial microtubule QCs are in play and
Voxels can model them.

To whit. 

The rapid advancements in quantum technology have revealed the revolutionary potential of quantum lithography in nanomanufacturing. This study explores the theoretical advantages of next-generation quantum lithography in fabricating photonic quantum neural microtubule chips and identifies key innovations through technical predictions. The paper provides a comprehensive analysis of the core components of lithography machines, the feasibility of chip structural design, and the potential application scenarios. The results demonstrate that photonic quantum neural microtubule chips o!er significant improvements in computational e”- ciency, energy consumption, and parallel processing capabilities, paving the way for groundbreaking hardware support in quantum computing and artificial intelligence.

source,11 two-photon source,12 and multiphoton source,13 respectively. Left: Quantum light manipulation: interference,14 state modulation,15 and logic gates.16 Right: Quantum light detection: sensing,17 state characterization,18 and imaging.19 Li et al., eLight 3, 19 (2023). Copyright 2023 Author(s), licensed under a Creative Commons Attribution (CC BY) license. Zhang et al., Sci. Adv. 8, eabq4240 (2022). Copyright 2022 Author(s), licensed under a Creative Commons Attribution NonCommercial License 4.0 

To be continued.

Beyond computation ...

 

A new system developed by researchers at the University of Rochester allows them to conduct quantum simulations in a synthetic space that mimics the physical world by controlling the frequency, or color, of quantum entangled photons as time elapses.
Credit: University of Rochester illustration / Michael Osadciw

Everybody talks about quantum computing from the code-breaking and factoring side of things due to the fact the compute power of said systems goes beyond computation because qubits can be 0s AND 1s at the same time, thus exponentially increasing the ability to solve difficult problems beyond the kin of serial processing via bits - 0s OR 1s, the way every non-QC system in the world crunches data. With this said, the real power of QC may be its ability to recreate reality in finite space, a concept discussed in detail by Seth Lloyd in his seminal book titled Programming the Universe.

Recreating reality was just a conjecture, until now.

Scientists have made an important step toward developing computers advanced enough to simulate complex natural phenomena at the quantum level. While these types of simulations are too cumbersome or outright impossible for classical computers to handle, photonics-based quantum computing systems could provide a solution.

A team of researchers from the University of Rochester’s Hajim School of Engineering & Applied Sciences developed a new chip-scale optical quantum simulation system that could help make such a system feasible. The team, led by Qiang Lin, a professor of electrical and computer engineering and optics, published their findings on June 22 in the journal Nature Photonics.

Lin’s team ran the simulations in a synthetic space that mimics the physical world by controlling the frequency, or color, of quantum entangled photons as time elapses. This approach differs from the traditional photonics-based computing methods in which the paths of photons are controlled, and also drastically reduces the physical footprint and resource requirements.

“For the first time, we have been able to produce a quantum-correlated synthetic crystal,” says Lin. “Our approach significantly extends the dimensions of the synthetic space, enabling us to perform simulations of several quantum-scale phenomena such as random walks of quantum entangled photons.”

The researchers say that this system can serve as a basis
for more intricate simulations in the future.

Channeling the monolith ...

QC/Ethics/Costs ...

Everything has a cost. There ain't no such thing as a free lunch thanks to the two laws of thermodynamics, a fact BRT has bandied about for quite some time. The above clip discusses this fact regarding AI and Quantum Computing, as both are open ended and fraught with possibilities of the negative kind.

Metallurgy, steam power and the integrated circuit are just a few of the many technologies that have had a profound effect on humanity. Will quantum computing soon join this list? Some people think so and they are warning that we should begin thinking about the ethical implications of a technology that could solve problems well beyond the reach of even the most powerful quantum computers. In the above video from Quantum Daily, six leading lights in the nascent quantum computing industry discuss the issue.

TANSTAAFL, on the other hand, indicates an acknowledgement that in reality a person or a society cannot get "something for nothing". Even if something appears to be free, there is always a cost to the person or to society as a whole, although that may be a hidden cost or an externality. For example, as Heinlein has one of his characters point out, a bar offering a free lunch will likely charge more for its drinks.[8]

Same as it ever was - Talking Heads.

Music of the Spheres

The real power of quantum computing is NOT the ability to crack security codes or to search huge databases at blinding speeds, the real power of quantum computing lies in simulating reality.

"The physicists of the University of Innsbruck and the Institute for Quantum Optics and Quantum Information (IQOQI) in Innsbruck have come considerably closer to their goal to investigate complex phenomena in a model system: They have realized a digital, and therefore, universal quantum simulator in their laboratory, which can, in principle, simulate any physical system efficiently."

Back in 2008, Seth Lloyd, in his eloquent book Programming The Universe, stated the underlying reason why the scientists at Innsbruck were able to do something which, in time, could change the future of man in ways impossible to comprehend.

"Quantum computers process the information stored on individual atoms, electrons, and photons. A quantum computer is a democracy of information: every atom, electron, and photon participates equally in registering and processing information. And this fundamental democracy of information is not confined to quantum computers. All physical systems are at bottom quantum-mechanical, and all physical systems register and process information."

In indirect fashion, The Music of the Spheres seems apropos as man begins to tease information out of reality using photons and atoms just as the ancients used the motion of celestial bodies to tease out harmonic and relational aspects of nature using music as the mechanism to make it happen.

QC's other uses ...

In Valeria Saggio’s Vienna lab, she directed a laser of single photons into a special quantum circuit to show how the vagaries of quantum physics can improve machine learning.

What's curious about quantum systems is the sole focus by the press on said tech being the end-all for breaking encryption instead of discussing why QC would also be perfect for AI-driven neural nets and ray tracing due to the inherent parallelism of qubits being in superposition to enable quantum computers to escape the limitations of serial processing forever.

For Valeria Saggio to boot up the computer in her former Vienna lab, she needed a special crystal, only as big as her fingernail. Saggio would place it gently into a small copper box, a tiny electric oven, which would heat the crystal to 77 degrees Fahrenheit. Then she would switch on a laser to bombard the crystal with a beam of photons.

This crystal, at this precise temperature, would split some of those photons into two photons. One of these would go straight to a light detector, its journey finished; the other would travel into a tiny silicon chip — a quantum computing processor. Miniature instruments on the chip could drive the photon down different paths, but ultimately there were only two outcomes: the right way, and the many wrong ways. Based on the result, her processor could choose another path and try again.

The sequence feels more Rube Goldberg than Windows, but the goal was to have a quantum computer teach itself a task: Find the right way out. For Saggio, a quantum physicist who moved to the Massachusetts Institute of Technology a few weeks ago, the project was akin to sticking a robot in a maze. The computer must learn the right path without any prior knowledge of where to turn along the way. It’s not too hard a chore — a normal classical computer could brute-force its way through dead ends and lucky guesses. But Saggio wondered, “Can quantum mechanics help?” She and her collaborators showed last year that it can.

Crucially, the chip is not just moving through faster cycles of trial-and-error, said Lucas Lamata, a quantum machine learning expert at the University of Seville. “The novelty in this paper is that they show a speedup in learning. [It’s] an important breakthrough.” Quantum mechanics makes the system learn in fewer steps. In that sense, it shows in an experiment what Temme’s theoretical speedup promised: Quantum physics can outwit — not just outrun — classical computing. 

It's all about kernels.

Samuel Velasco/Quanta Magazine

The story of MAGI Mathematical Applications Group Incorporated begins with the “simple” question, “What paths would radiation take when a 20 megaton nuke goes off? Hypothetical target? NYC." 

MAGI was tasked to answer the question by inventing ray tracing to track the radiation paths of the nuke’s blast to the environment but also to apply the same technique to imaging as a nuke is a single energy source like a light bulb and blast and light rays propagate exactly the same but with the difference being light rays nondestructively intersect with objects and react according to the kind of characteristics the objects in question may possess like color, texture, transparency and reflectivity, using the laws of physics to generate an accurate 3D rendering of the scene in question. Computationally intense, ray tracing, and it's even more complex sibling, radiosity, are the most accurate ways to render high-resolution 3D scenes known to science. Note, in reality, rays propagate from light sources to illuminate the scene in question. 

Which means QC would be perfect for this kind of intense image creation without question.

Illustration of the ray-tracing algorithm for one pixel (up to the first bounce)

The ray-tracing algorithm builds an image by extending rays into a scene and bouncing them off surfaces and towards sources of light to approximate the color value of pixels.

It's only the beginning. :)

Diamonds are Forever

BRT has talked about quantum computers on several occasions as said devices are not only incomprehensively fast due to the superpostion of qubits but, more importantly, have the potential of creating reality in finite space, but before getting to that computing nirvana requires flawless quantum teleportation of information via entangled quibits, something not considered doable until now.

To date, scientists have struggled to use entanglement as a means of communication—it's been achieved but the error rate has been so great that it would be unfeasible as a real-world application. In this new effort, the researchers claim to have solved the error rate problem—they've brought it down to zero percent. They did it, they report, by trapping electrons in diamonds at very low temperatures and shooting them with lasers, resulting in the creation of qubits. The diamonds, the team reports, serve as really tiny prisons, holding the electrons in place. Held as they were, the researchers were able to cause a spin state to exist and then to read it at both locations, which meant that information had been conveyed.

Seen below is a short video showing how information can be processed via quantum teleportation.

The Matrix - phase 1.

Realizing robust quantum information transfer between long-lived qubit registers is a key challenge for quantum information science and technology. Here, we demonstrate unconditional teleportation of arbitrary quantum states between diamond spin qubits separated by 3 m. We prepare the teleporter through photon-mediated heralded entanglement between two distant electron spins and subsequently encode the source qubit in a single nuclear spin. By realizing a fully deterministic Bell-state measurement combined with real-time feed-forward quantum teleportation is achieved upon each attempt with an average state fidelity exceeding the classical limit. These results establish diamond spin qubits as a prime candidate for the realization of quantum networks for quantum communication and network-based quantum computing.

Of something eternal

Of something eternal - RM/Freepik/NanoBanana

Glass, amorphous, eternal, made from sand, perfect ... for optical computing, 

The Thermodynamic Breakthrough

Recent research into Generative Thermodynamic Computing employing noise to drive AI neural nets proves that structured data —by "jiggling" atoms— can be generated using orders of magnitude less energy than current generative AI models, a process akin to the principle of least action nature adheres to in seekking the most efficient route possible, switching between potential and kinetic energy requirements as needs warrant. 

A path to the Moon must account for the motion of the Moon during the voyage.

The problem

Current systems count by 0s and 1s when moving electrons around in silicon, generating heat and requiring significant power in order to compute whereas optical computing, using glass as the substrate and combining it with analog thermodynamic computation, power requirements drops to almost nothing while photons travel at the speed of light. To make the process go even faster, quantum computing using the Penrose -Hammeroff conjecture becomes possible as QCs are analog as they measure, not count. The key is to make noise your friend, not your enemy, something todays systems fight endlessly to quench while requiring enormous amount of power to do so. Think AI data centers for example.

A conversation with Gemini

Recent 2025-2026 research confirms that microtubules can support decoherence-resistant entangled states at ambient temperatures, effectively acting as biological QED cavities. Similarly, glass nanoparticles have been "frozen" into pure quantum ground states at room temperature using optical controls, proving that glass is the ideal substrate for stable qubits. 

This analog approach of thermodynamic science validates the work of Roger Penrose and Stuart Hameroff. Their Orch-OR theory identifies the microtubule as the biological "Loom" of consciousness—a room-temperature quantum processor that has been around for four billion years.

In our cells, cytoskeletal proteins called tubulins snap onto each other to form soaring tubular arches and rails, capable of spanning entire cells, growing at one end while they fall apart at the other. These tubes, known as microtubules, form and bloom and decay in a dance that controls many aspects of eukaryotic life. They handle our chromosomes and help cells divide. They carry machines and act as tracks for motors. They push and pull cellular membranes, turning them into useful shapes.

NbRe & Majorana Stabilizers: The niobium-rhenium (NbRe) alloy, as an intrinsic triplet superconductor, is the "holy grail" for creating Majorana particles. These particles act as their own antiparticles and are "Majorana-Sighted"—they encode information in a way that is inherently protected from local noise, providing the 1% Truth required for error correction.

Oscillating conductance This measurement on the middle quantum dot shows how the bulk gap in the system can be created and removed. This control is important for the manipulation and protection of Majorana modes.
(Courtesy: Image by QuTech)

The Glass Sanctuary: By embedding NbRe/Majorana stabilizers within a glass substrate, we create a topological sanctuary where quantum information can reside without de-rendering into the "Analog Blur" of environmental decoherence. By leveraging  Orch-OR in glass, room temperature QC becomes possible.

Modeling the system

The Grid (A): The discrete, binary alphabet of space.

The Solid State (B): A volumetric reality where the model and the object are one.

To map the waveguides in glass using The Universal Modeler as the entity of mathematical precision and structural persistence becomes possible through the use of CSG operators of Union, Difference, and Intersection as the scaffolding to generate increasingly smaller voxels as this eliminates the "Discretization Gap." while creating the correct Voxel-CSG coordinates needed to properly etch the microtubule structures directly into the glass. substrate.

Challenge to the titans

To the "boffins" at IBM, Intel, and Google: You have the toolkits, but you are still using silicon and electrons to compute. The science of RT QC in glass is now open for all to see.

Q Day

Illustration: Nicholas Law

Ah, viable quantum computing, the long sought after holy grail, is worth pursuing no matter the cost as said tech not only goes beyond computation in terms of crunching numbers but also has the ability to model reality due to the superposition of qubits connected by entanglement, the prime driver to an existence in which we all share. With this being said, there's always a cost to everything, in this instance, privacy as QCs are uniquely qualified to deal with the issue of primes as prime numbers are the building blocks of cryptography, the mathematical construct on which privacy depends.

The general definition of a qubit as the quantum state of a two-level quantum system.

To whit ...

Suppose you ask a classical computer to solve a simple math problem: Break the number 15 into its smallest prime factors. The computer would try all the options one by one and give you a near-instantaneous answer: 3 and 5. If you then ask the computer to factor a number with 1,000 digits, it would tackle the problem in exactly the same way—but the calculation would take millennia. This is the key to a lot of modern cryptography.

Take RSA encryption, developed in the late 1970s and still used for securing email, websites, and much more. In RSA, you (or your encrypted messaging app of choice) create a private key, which consists of two or more large prime numbers. Those numbers, multiplied together, form part of your public key. When someone wants to send you a message, they use your public key to encrypt it. You’re the only person who knows the original prime numbers, so you’re the only person who can decrypt it. Until, that is, someone else builds a quantum computer that can use its spooky powers of parallel computation to derive the private key from the public one—not in millennia but in minutes. Then the whole system collapses.

The algorithm to do this already exists. In 1994, decades before anyone had built a real quantum computer, an AT&T Bell Labs researcher named Peter Shor designed the killer Q-Day app. Shor’s algorithm takes advantage of the fact that quantum computers run not on bits but on qubits. Rather than being locked in a state of 0 or 1, they can exist as both simultaneously—in superposition. When you run an operation on a handful of qubits in a given quantum state, you’re actually running that same operation on those same qubits in all their potential quantum states. With qubits, you’re not confined to trial and error. A quantum computer can explore all potential solutions simultaneously. You’re calculating probability distributions, waves of quantum feedback that pile onto each other and peak at the correct answer. With Shor’s algorithm, carefully designed to amplify certain mathematical patterns, that’s exactly what happens: Large numbers go in one end, factors come out the other.

There are now hundreds of companies trying to build quantum computers using wildly different methods, all geared toward keeping qubits isolated from the environment and under control: superconducting circuits, trapped ions, molecular magnets, carbon nanospheres. While progress on hardware inches forward, computer scientists are refining quantum algorithms, trying to reduce the number of qubits required to run them. Each step brings Q-Day closer.

That bomb going off will only be the beginning. When Q-Day becomes public knowledge, either via grim governmental address or cheery big-tech press release, the world will enter the post-quantum age. It will be an era defined by mistrust and panic—the end of digital security as we know it. “And then the scramble begins,” says Demchak.

Illustration: Nicholas Law 

Criticality ...

 Photo by Bastien Nvs on Unsplash

The 1st law of thermodynamics rules as it's all about energy as said entity can neither be created or destroyed, only transformed. i.e.The flow of heat is a form of energy transfer. Heating is the natural process of moving energy to or from a system other than by work or the transfer of matter. With this being said, excess heat generated from thermodynamic processes to include erasing bits, is a killer for computers as well as being bad for the environment, a problem needing a solution now.

In case you had not noticed, computers are hot—literally. A laptop can pump out thigh-baking heat, while data centers consume an estimated 200 terawatt-hours each year—comparable to the energy consumption of some medium-sized countries. The carbon footprint of information and communication technologies as a whole is close to that of fuel use in the aviation industry. And as computer circuitry gets ever smaller and more densely packed, it becomes more prone to melting from the energy it dissipates as heat.

 Entropy also rules.

In 1961 physicist Rolf Landauer of IBM’s Thomas J. Watson Research Center in Yorktown Heights, N.Y., showed that conventional computing incurs an unavoidable cost in energy dissipation—basically, in the generation of heat and entropy. That is because a conventional computer has to sometimes erase bits of information in its memory circuits in order to make space for more. Each time a single bit (with the value 1 or 0) is reset, a certain minimum amount of energy is dissipated—which Ray and Crutchfield have christened “the Landauer.” Its value depends on ambient temperature: in your living room, one Landauer would be around 10–21 joule. (For comparison, a lit candle emits on the order of 10 joules of energy per second.)

Is there a way out as the faster machines get, the hotter they get.

Possibly ...

Harnessing a particle’s velocity for computing is not an entirely new idea. Momentum computing is closely analogous to a reversible-computing concept called ballistic computing that was proposed in the 1980s: in it, information is encoded in objects or particles that move freely through the circuits under their own inertia, carrying with them some signal that is used repeatedly to enact many logical operations. If the particle interacts elastically with others, it will not lose any energy in the process. In such a device, once the ballistic bits have been “launched,” they alone power the computation without any other energy input. The computation is reversible as long as the bits continue bouncing along their trajectories. Information is only erased, and energy is only dissipated, when their states are read out.

Whereas, in ballistic computing, a particle’s velocity simply transports it through the device, allowing the particle to ferry information from input to output, Crutchfield says, in momentum computing, a particle’s velocity and position collectively allow it to embody a unique and unambiguous sequence of states during a computation. This latter circumstance is the key to reversibility and thus low dissipation, he adds, because it can reveal exactly where each particle has been.

It's all about reading out particle states using quantum computing in real time, to lessen the heat equation. Unfortunately, QC's a tech far from being practical in the year of our lord 2022 in addition to the impact Heisenberg's Uncertainty Principle may have on any given computation.

To be continued.

The 3rd Law: A system's entropy approaches a constant value as its temperature approaches absolute zero.

a) Single possible configuration for a system at absolute zero, i.e., only one microstate is accessible. b) At temperatures greater than absolute zero, multiple microstates are accessible due to atomic vibration (exaggerated in the figure)

Another match made in heaven ...

The ability to process quantum data directly with a quantum device (right) allows one to resolve aspects of our universe exponentially faster than going through a classical intermediate (left). This may allow us to discover novel physical phenomena that would have been practically invisible without such technology. Credit: Google Quantum AI Hook

Yours truly has long said QCs would be perfect for ray tracing as said imaging technique lends itself to any system capable of parallel processing at high level, something QC systems do at speeds far surpassing any digital system due to the fact QCs process data using 0 & 1 at the sane time rather then 0 or 1. Now, researchers are using QC's to leverage AI driven machine learning in ways promising to develop systems of unimagined power as the tech continues to advance 24/7.

A team of researchers affiliated with multiple institutions in the U.S., including Google Quantum AI, and a colleague in Australia, has developed a theory suggesting that quantum computers should be exponentially faster on some learning tasks than classical machines. In their paper published in the journal Science, the group describes their theory and results when tested on Google's Sycamore quantum computer. Vedran Dunjko with Leiden University City has published a Perspective piece in the same journal issue outlining the idea behind combining quantum computing with machine learning to provide a new level of computer-based learning systems.

To find out if the idea might be possible, and more importantly, if the results would be better than those achieved on classical computers, the researchers posed the problem in a novel way—they devised a machine learning task that would learn via experiments repeated many times over. They then developed theories describing how a quantum system could be used to conduct such experiments and to learn from them. They found that they were able to prove that a quantum computer could do it, and that it could do it much better than a classical system. In fact, they found a reduction in the required number of experiments needed to learn a concept to be four orders of magnitude lower than for classical systems. The researchers then built such a system and tested it on Google's Sycamore quantum computer and confirmed their theory.

The work suggests that if a usable, real-word quantum computer is ever developed, it might be capable of leaning new things on a nearly unimaginable scale.

IBM Q System One (2019), the first circuit-based commercial quantum computer.