17 research outputs found
Black hole entropy divergence and the uncertainty principle
Black hole entropy has been shown by 't Hooft to diverge at the horizon. The
region near the horizon is in a thermal state, so entropy is linear to energy
which consequently also diverges. We find a similar divergence for the energy
of the reduced density matrix of relativistic and non-relativistic field
theories, extending previous results in quantum mechanics. This divergence is
due to an infinitely sharp division between the observable and unobservable
regions of space, and it stems from the position/momentum uncertainty relation
in the same way that the momentum fluctuations of a precisely localized quantum
particle diverge. We show that when the boundary between the observable and
unobservable regions is smoothed the divergence is tamed. We argue that the
divergence of black hole entropy can also be interpreted as a consequence of
position/momentum uncertainty, and that 't Hooft's brick wall tames the
divergence in the same way, by smoothing the boundary.Comment: Added clarifications and explanation
Entanglement and the Speed of Evolution in Mixed States
Entanglement speeds up evolution of a pure bipartite spin state, in line with
the time energy uncertainty. However if the state is mixed this is not
necessarily the case. We provide a counter example and point to other factors
affecting evolution in mixed states, including classical correlations and
entropy
A Colloquium on Art/Science/Spirituality Reconnections within Emerging Planetary Cultures
Communication Systems Performance at mm and THz as a Function of a Rain Rate Probability Density Function Model
6G is already being planned and will employ much higher frequencies, leading to a revolutionary era in communication between people as well as things. It is well known that weather, especially rain, can cause increased attenuation of signal transmission for higher frequencies. The standard methods for evaluating the effect of rain on symbol error rate are based on long-term averaging. These methods are inaccurate, which results in an inefficient system design. This is critical regarding bandwidth scarcity and energy consumption and requires a more significant margin of effort to cope with the imprecision. Recently, we have developed a new and more precise method for calculating communication system performance in case of rain, using the probability density function of rain rate. For high rain rate (above 10 mm/h), for a typical set of parameters, our method shows the symbol error rate in this range to be higher by orders of magnitude than that found by ITU standard methods. Our model also indicates that sensing and measuring the rain rate probability is important in order to provide the required bit error rate to the users. This will enable the design of more efficient systems, enabling design of an adaptive system that will adjust itself to rain conditions in such a way that performance will be improved. To the best knowledge of the authors, this novel analysis is unique. It can constitute a more efficient performance metric for the new era of 6G communication and prevent disruption due to incorrect system design