In this post, we continue our discussion of the rapidly emerging field of quantum computing patents. Consider US 10275721, which is a "Quantum computing machine learning module". Particularly, we discuss the significance of Zlatko Minev's groundbreaking research into quantum jump prediction and its implications for the enablement requirements under 35 USC 112(a) and the utility requirements under 35 USC 101. Quantum computing works by utilizing really weird properties of electrons that appear to defy conventional Physics. Specifically, conventional Quantum Physics has taught for decades that electrons seem to often be in multiple places at once and spin in particular directions for no predictable reason. Applying the principle of "quantum superposition", i.e., the notion that an electron may be in multiple states at the same time, one may store a lot more data than they can with only conventional digital logic gates.
Under this massive assumption of traditional Quantum Physics regarding superposition, an extremely powerful method of encryption has emerged. To play around with a free Quantum Computer, see D-Wave's website for a trial(https://www.dwavesys.com/) or see this great simulator(http://www.quantumplayground.net/#/home). From these trials or simulators, you can see that the encryption rests on the idea that one cannot predict an electron's state and transition from one state to another. The enablement requirements in U.S. Patent No. 10,275,721 clearly rest on this idea that quantum jumps are unpredictable because a PHOSITA would necessarily interpret the claims to mean that quantum superposition is the driving principle behind the module. Specifically, the drafters write "It is understood that quantum memories are devices that can store quantum data for a long time with high fidelity and efficiency, e.g., light-matter interfaces where light is used for transmission and matter for storing and preserving the quantum features of quantum data such as superposition or quantum coherence. " If Dr. Minev's experiment holds true, then this above statement is false. This essentially means that a PHOSITA would be unable to use quantum superposition to store the relevant machine learning data, as the methods described to do so are in fact false. In our next entry, coming soon, we will discuss this issue in greater detail and also discuss what quantum jump prediction would imply in light of the Alice decision.
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