Quantum Limitations on the Storage and Transmission of Information
Jacob D. Bekenstein, Marcelo Schiffer
Abstract
Information must take up space, must weigh, and its flux must be limited. Quantum limits on communication and information storage leading to these conclusions are here described. Quantum channel capacity theory is reviewed for both steady state and burst communication. An analytic approximation is given for the maximum signal information possible with occupation number signal states as a function of mean signal energy. A theorem guaranteeing that these states are optimal for communication is proved. A heuristic "proof" of the linear bound on communication is given, followed by rigorous proofs for signals with specified mean energy, and for signals with given energy budget. And systems of many parallel quantum channels are shown to obey the linear bound for a natural channel architecture. The time--energy uncertainty principle is reformulated in information language by means of the linear bound. The quantum bound on information storage capacity of quantum mechanical and quantum field devices is reviewed. A simplified version of the analytic proof for the bound is given for the latter case. Solitons as information caches are discussed, as is information storage in one dimensional systems. The influence of signal self--gravitation on communication is considerd. Finally, it is shown that acceleration of a receiver acts to block information transfer.
Create a lesson
Related papers
Using topology to reveal all mutually unbiased bases in dimension six
Mateo Cárdenes Wuttig, Joseph Tindall
Arithmetic Depth, Minimal Gate Alphabets, and Exact Program-State Resources for Single-Qubit Dyadic Programs
Tony Newton, Dan-Adrian German
Probing gravity at megahertz frequencies with levitated rotors
Matteo Fadel, Andrea Vinante
Optimal Holding Times for Entanglement Swapping
Van Sy Mai, Richard J. La, Abdella Battou
Quantum Algorithms for Molecular Response Functions: Resolvent Kernels, Time-Domain Sampling, Query Lower Bounds with Matched Single-Point Calibers, and a Six-Route Comparison
Yunlong Liu, Yujin Tang, Miao Xu et al.
GFlowQEC: Generative Flow Networks that Learn to Sample Quantum LDPC Codes
Nuno Batista, Gabriel Falcao, Penousal Machado