Abstract
The majority of the combinatorial optimization problems are solved by searching a solution space that grows as an exponential function of the problem size. Such class of problems scales inefficiently on the Boolean von Neumann architecture. On the other hand, alternative computing techniques like coupled-oscillator networks are efficient in solving combinatorial optimization problems. In this article, we demonstrate the effectiveness of antiferroelectric tunnel junctions (AFTJs) in coupled-oscillator networks for solving combinatorial optimization problems such as graph coloring. AFTJs are tunnel junctions that show a high ON-/OFF-current ratio. The high ON-/OFF-current ratio of AFTJs allows a higher sense margin at low bias current. Consequently, AFTJ oscillators are more energy-efficient compared to VO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -, HfTaOx-, and TaOx-based oscillators. This article explains the origin of the large ON-/OFF-current ratio of AFTJs. A physics-based model is proposed to predict the AFTJ current. The proposed AFTJ model is compared to experimental results to show the ability of the model to predict AFTJ behavior. The proposed AFTJ model is implemented in Verilog-A and used in circuit simulations of the AFTJ-based coupled-oscillator network.
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