scholarly journals Invisible axion search methods

2021 ◽  
Vol 93 (1) ◽  
Author(s):  
Pierre Sikivie
2003 ◽  
Author(s):  
Mark A. Abramson ◽  
Olga A. Brezhneva ◽  
Jr Dennis ◽  
J. E.

2021 ◽  
Vol 2021 (3) ◽  
Author(s):  
Matthew J. Dolan ◽  
Torben Ferber ◽  
Christopher Hearty ◽  
Felix Kahlhoefer ◽  
Kai Schmidt-Hoberg

A mistake has been found in the numerical code used to reproduce the bounds from proton beam dump experiments from ref. [1] in figures 2 and 7 of ref. [2]. Correcting this mistake leads to slightly stronger bounds as shown below. We note that this correction does not include recent improvements in the analysis of proton beam dump experiments [3]. Additional recent bounds on GeV-scale ALPs can be found in refs. [4–8].


Author(s):  
Hafiz Munsub Ali ◽  
Jiangchuan Liu ◽  
Waleed Ejaz

Abstract In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless networks. We considered a single-hop wireless network consists of base stations (BSs), relay stations (RSs), and user equipment (UEs). Wireless network planning (WNP) should decide the placement of BSs and RSs to the candidate sites and decide the possible connections among them and their further connections to UEs. The objective of the planning is to minimize the hardware and operational cost while planning capacity of a 5G and beyond wireless networks. The formulated WNP is an integer programming problem. Finding an optimal solution by using exhaustive search is not practical due to the demand for high computing resources. As a practical approach, a new population-based meta-heuristic algorithm is proposed to find a high-quality solution. The proposed discrete fireworks algorithm (DFWA) uses an ensemble of local search methods: insert, swap, and interchange. The performance of the proposed DFWA is compared against the low-complexity biogeography-based optimization (LC-BBO), the discrete artificial bee colony (DABC), and the genetic algorithm (GA). Simulation results and statistical tests demonstrate that the proposed algorithm can comparatively find good-quality solutions with moderate computing resources.


2021 ◽  
Vol 125 (2) ◽  
pp. 1578-1591
Author(s):  
Logan Lang ◽  
Adam Payne ◽  
Irais Valencia-Jaime ◽  
Matthieu J. Verstraete ◽  
Alejandro Bautista-Hernández ◽  
...  

2017 ◽  
Vol 78 (3) ◽  
pp. 911-928 ◽  
Author(s):  
Saman Babaie–Kafaki ◽  
Saeed Rezaee

2007 ◽  
Vol 38 (8) ◽  
pp. 1-10
Author(s):  
Tadashi Yamaura ◽  
Hirohisa Tasaki ◽  
Shinya Takahashi
Keyword(s):  

Author(s):  
Shogo Takeuchi ◽  
Tomoyuki Kaneko ◽  
Kazunori Yamaguchi

1999 ◽  
Vol 20 (3/4) ◽  
pp. 189-237 ◽  
Author(s):  
Peter Urwin ◽  
J.R. Shackleton
Keyword(s):  

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