Two Forms of the Generalized Uncertainty Principle

Various quantum gravitational theories predict the existence of the minimum length scale, which leads to the modification to the general uncertainty principle (GUP) of the standard uncertainty principle. In this paper, we studied two forms of GUP and calculated the influence of them on the energy of harmonic oscillator and hydrogen atoms more precisely than in previous work. Furthermore, it shows how GUP modifies the Lorentz force method and the time-energy uncertainty principle. Introduction The development of quantum gravity theory is one of the major challenges in theoretical physics.

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Various quantum gravitational theories predict the existence of the minimum length scale, which leads to the modification to the general uncertainty principle (GUP) of the standard uncertainty principle. In this paper, we studied two forms of GUP and calculated the influence of them on the energy of harmonic oscillator and hydrogen atoms more precisely than in previous work. Furthermore, it shows how GUP modifies the Lorentz force method and the time-energy uncertainty principle. Whether drugs designed with computers can target fatal diseases. Medicine is a drug or substance that affects how the body works. Salt dissolves in water to promote corrosion, and enzyme (protein) acts as a biocatalyst as well, promoting the chemical reaction in the body. Diseased cells need to be treated with drugs to avoid development

At the beginning of the 20th century, light proved to have confusing waves and particle quality. This non-intuitive concept of quantum physics, the duality of waves and particles, also appears as the principle of uncertainty. A more general concept is the recently discovered "holographic duality". Obviously, nature also links two different objects - holograms and their higher dimensional projection - in the same strangely same way. There is essentially a holographic duality, which may also lead to the operation of a deep learning network. . The greater the generalization of the network, the more entangled the neurons, the more difficult the network will become to interpret. The principle of uncertainty applicable to deep learning can be expressed as follows.