Darwin2049/ChatGPT4/PhaseShift
Hosting: Quantum Computing. Because of the inherent novelty of what a quantum computing environment might make possible the following discussion limits itself to what is currently known.
Published reports from giants such as IBM, Intel and Google lay out explicit timelines and project goals. In each case the expected goal of qubit availability is provided.
What has already been made very clear is that even with the very limited quantum computing capabilities currently available, these systems prove themselves to be orders of magnitude faster in solving difficult problems than even the most powerful classical supercomputer ensembles.
If we take a short step into the near term future then we might be obliged to attempt to assimilate and rationalize developments happening on a daily basis. Any or even all of which can have transformative implications.
As quantum computing becomes more prevalent the field of deep learning will take another leap forward which will put those who possess it at an incalculable advantage. Should it become possible to train using large to extremely large data sets in minutes or even possibly in seconds then the reality of quantum computing of deep learning systems will take a revolutionary step forward. Combinations of knowledge could be incorporated almost instantly. This would change the entire complexion of how difficult to intractable problems become soluble.
The central problem in these most recent developments arises because of the well recognized human inability to process changes that happen in a nonlinear fashion. If change is introduced in a relatively linear fashion at a slow to moderate pace then most people adapt to and accommodate the change. However if change happens geometrically like what we see in the areas of deep learning then it is much more difficult to adapt to change.
- CG.X-Quantum will completely eclipse current incarnations of CG4: Quantum computing devices are already demonstrating their ability to solve problems in seconds or minutes that classical von Neuman computing machines require decades, centuries or even millennia to solve.
- Phase Shift. Classical physics describes how states of matter possess different properties depending upon their energy state or environment. Thus on the surface of the earth we can experience the gas of the atmosphere. In environments that are somewhat above the freezing point of water we are unaware of the fact that we inhale and exhale atmospheric gas. It is odorless, colorless and tasteless.
- State: Gas. Were we to collect sufficient quantities of atmospheric gas into a sealable container it would be possible to cool the gasses comprising earth's atmosphere into liquids. The idea of wetness, shape conformability and other properties of a liquid would suddenly become evident. Yet it would be difficult to adduce wetness if we never had experience with a liquids.
- State: Liquid. If one never had contact with the liquid state of H2O then properties as buoyancy, wetness, conformability (i.e. to the shape of a container, evaporation, discoloration and similar properties might be very difficult to imagine. It would be difficult if not even impossible to envision something that was otherwise undetectable because it was odorless, colorless and tasteless could somehow cause one's death by drowning. Yet were one to be plunged into a large enough body of water but not possess swimming skills one could very well die by drowning.
- State: Solid. The process can be repeated. If we were to use water as a basis then we might discover another state of matter that water can exhibit. This is the state of ice. Many of us use this material (ice) to condition our beverages. That a heretofore wet liquid could become solid might also defy our ability to imagine it taking on solid form. These all consist of the same substance, i.e. H2O. Yet properties found in one state, or phase bear little or no resemblance to those in the subsequent state. We should expect to see an evolution comparable happening in fast forward motion that is very comparable to "gas to liquid, liquid to solid". When DeepMind or CG4 are re-hosted in a quantum computing environment equally unimaginable capabilities will become the norm.
- State: Gas. Were we to collect sufficient quantities of atmospheric gas into a sealable container it would be possible to cool the gasses comprising earth's atmosphere into liquids. The idea of wetness, shape conformability and other properties of a liquid would suddenly become evident. Yet it would be difficult to adduce wetness if we never had experience with a liquids.
The analyst can find a number of useful references addressing the topics of quantum bits, entanglement and superposition
In some cases they will prove to be fairly technical.
Going forward existing computationally intensive tasks will migrate into the quantum computing world. When this happens there will be dramatic collapses in the amoun of time to turn around formulation and analysis of complex to extremely complex problems to analyzing the available results.
Existing problems that involve multiple dimensions and numerous independent variables for their solution will become child's play for these new devices. Current reports indicate that minimizing noise and enhancing stability of the entanglement condition require continued refinement and improvement. As these advances continue the power of quantum computing will eventually approach then surpass even the most powerful classical computing systems.
- Molecular Structure.
- Process Modeling.
- User Interaction.
- Encryption.
References
- Basic Elements.
- Hadamard Gates.
- Bloch Sphere.
- <0 : 1> Bounded Solutions.
- Quantum Logic: AND OR NOR NAND XOR.
- Vector Space.
- P/NP Complete Problems.
- Entanglement.
- Coherence and Error Correcting.
- Superposition.
- Quantum Problem Space.
- Algorithms. (or, more than you ever wanted to know);
- Shor's Algorithm.
- Deutsch.
- AI.
- Uses
- Encryption.
- Drug Design.
- Process Optimization.
- Artificial Intelligence.
- Some sources.
- Basics
- IBM Quantum System Two - Osprey - 432 Q-Bit Device.
- "Sand box:" Quantum Computing practice environments.
- Basics.
- Some Overview.
- Hadamard Gates.
- Bloch Sphere.
- Watch
- Bloch Sphere Coordinate Mapping
- Simplified
{Zero:One} Bounded Solutions. Vector Space. P/NP Complete Problems.
Quantum Logic: AND OR NOR NAND XOR. Error Correcting. Quantum Problem Space.
Shor’s Algorithm. Is a powerful tool for factoring extremely large prime numbers. Quantum computers can collapse the time and effort required to factor large prime numbers. With the ability to factor large prime numbers it becomes possible to crack RSA encryption.
- Explained Simply.
- Using simple mathematics.
- Shor’s Algorithm – illustrated.
- Step by step.
- Grover’s Algorithm. This is an algorithm developed in 1996 by Lov Grover. It leverages quantum conputing to collapse the amount of time needed to perform a search of N unordered elements. Note that a crucial factor is that in performing the search for a specific element that meets a set of desired criteria, any evaluation of an element in the set yields no information about which other element in the set of N elements might help determine the desired one.
- Somewhat abstruse video of how Grover’s Algorithm reduces search cost from N to N1/2.
- Deutsch’s Algorithm.
- Uses
Encryption. Drug Design. Process Optimization AI.