Quantum correlations from local amplitudes and the resolution of the Einstein-Podolsky-Rosen nonlocality puzzle
C. S. Unnikrishnan
Abstract
The Einstein-Podolsky-Rosen nonlocality puzzle has been recognized as one of the most important unresolved issues in the foundational aspects of quantum mechanics. We show that the problem is resolved if the quantum correlations are calculated directly from local quantities which preserve the phase information in the quantum system. We assume strict locality for the probability amplitudes instead of local realism for the outcomes, and calculate an amplitude correlation function.Then the experimentally observed correlation of outcomes is calculated from the square of the amplitude correlation function. Locality of amplitudes implies that the measurement on one particle does not collapse the companion particle to a definite state. Apart from resolving the EPR puzzle, this approach shows that the physical interpretation of apparently `nonlocal' effects like quantum teleportation and entanglement swapping are different from what is usually assumed. Bell type measurements do not change distant states. Yet the correlations are correctly reproduced, when measured, if complex probability amplitudes are treated as the basic local quantities. As examples we discuss the quantum correlations of two-particle maximally entangled states and the three-particle GHZ entangled state.
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