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Annals of the New York Academy of Sciences

Geometry of Quantum Statesa

Samuel L. Braunstein, Carlton M. Caves

Published Apr 1, 1995• 7 citations
Publisher
DOI
10.1111/j.1749-6632.1995.tb39020.x

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•Aug 31, 2026•0 citations
\n \nWe have investigated the electric field ionization of highly excited (ns)\nand (nd) Rydberg states of the barium ion by microwave fields. For states\nwith a principal quantum number nleq40n\\leq 40nleq40 the observed microwave ionization\nthreshold fields show the Z3/3n5Z^3/3n^5Z3/3n5 dependence expected on the basis of\npreviously observed ionization of neutral Rydberg states with Z=1. We show\nthat for states in this n regime microwave ionization is a state selective\ndetection technique. Threshold fields for states with n> 40, however,\ndepart from the expected behaviour, the thresholds become broader and shift\nto higher fields. For a total of 58 states we present the field strengths\nwhere 90% , 50% and 10% ionization occur.\n\n\n
We examine how a superfluid state is approached in a system of localizedbosons (tightly bound electron pairs) in contact with a reservoir of itinerantfermions (electrons). Assuming spontaneous decay and recombination betweenthese two species, the initially localized states of the bosons change overinto free-particle--like propagating statesas the temperature is lowered and the superfluid transition at Tc{T}_{c}Tc​ is approached. Concomitantly a pseudogap opens up in the fermionic density of states which deepens with decreasing temperature.
This paper presents a novel quantum geometry optimization algorithm based on adaptive topology, designed to enhance the precision of quantum geometry modeling. Traditional methods often necessitate manual parameter tuning, limiting the algorithm's potential. Our approach dynamically adjusts geometry based on input data, offering a significant reduction in computational complexity and potentially unlocking more accurate representations of complex quantum systems. The core mechanism leverages quantum geometry optimization to iteratively refine the geometry, leading to improved modeling fidelity. We discuss the algorithm's design, implementation details, and preliminary results, demonstrating its potential for advancing quantum geometry research.