RUI: Nonlinear and Neural Dynamics in Josephson Networks

* 技术摘要 * 该个人研究者奖支持超导约瑟夫森结网络中非线性动力学的实验和计算研究。 约瑟夫森结是非线性系统的例子，可以用可调参数制造，以简单的方式测量，并且容易扩展到大的网络尺寸。 此外，在长时间内测量的大约瑟夫森结电路包含基本上不可能在计算机上计算的动态，但可以通过电气测量观察到。 这个项目将采取多方面的方法来研究约瑟夫森结网络的集体涌现行为。 首先，它将遵循以前的工作领域的孤立子样模式称为通量和本地化模式称为离散呼吸。 接下来，将对无序振子系统的同步进行研究。 最后，约瑟夫森结电路的设计，以准确地模拟生物神经元的时间依赖性电压将被制造和测试。 这有一个长期目标，即研究一个大型耦合神经网络的涌现行为。 * 非技术性摘要 * 当今物理学的一个重要方面是努力理解自然的基本定律如何导致复杂的行为。 例如，考虑一个气体分子系统。 简单的力和动量定律支配着它们的碰撞。 由于只有几个分子，这个系统简单而乏味。 然而，有了大量的分子，系统可以将自己组织成复杂的东西，比如龙卷风。 这种新的行为不是因为基本定律的变化，而是因为系统的组分（在这种情况下是气体分子）数量的变化。 在这项研究中，一个简单的电路元件被称为约瑟夫森结进行了研究。 约瑟夫森结是由超导金属制成的，在非常低的温度下工作。 过去的实验研究了单个约瑟夫森结的行为，发现它能够产生有趣的电学行为。 然而，由大量约瑟夫森结组成的电路尚未得到充分研究。 就像气体分子的情况一样，当组分的数量增加时，会产生新的集体行为。 本项目将研究其中的几种新行为。 其中之一，像龙卷风一样，是一个电流漩涡。 另一种是集体电压振荡，一种像两个钟摆一起摆动一样的来回运动。 最后一个行为是电压尖峰，类似于生物神经元的开关放电。 对于最后一种行为，一个长期的目标是建立能够模拟人类大脑中集体行为的电路，其中大量的神经元连接在一起。 该项目将本科生作为主要研究人员，为他们在科学领域的技术职业做好准备。

****Technical abstract**** This individual investigator award supports an experimental and computational study of nonlinear dynamics in networks of superconducting Josephson junctions. Josephson junctions are examples of nonlinear systems which can be fabricated with adjustable parameters, measured in a straightforward fashion, and easily scaled to large network sizes. In addition, a large Josephson junction circuit measured over a long time contains dynamics which would essentially be impossible to calculate on a computer, but which can be observed with electrical measurements. This project will take a multi-faceted approach to studying the collective, emergent behavior of Josephson junction networks. First, it will follow previous work in the field on soliton-like modes called fluxons and localized modes called discrete breathers. Next, studies will be performed on the synchronization of a system of disordered oscillators. Finally, a circuit of Josephson junctions designed to accurately model the time-dependent voltage of a biological neuron will be fabricated and tested. This has a longer-term goal of studying the emergent behavior of a large, coupled neural network. ****Non-technical abstract**** An important aspect of physics today is the effort to understand how the fundamental laws of nature result in complex behavior. For example, consider a system of gas molecules. Simple laws of force and momentum govern their collisions. With only a few molecules, the system is simple and uninteresting. With a large number of molecules, however, the system can organize itself into something complex, like a tornado. This new behavior comes about not because of a change in the fundamental laws, but rather a change in the number of constituents, in this case gas molecules, of the system. In this research, a simple electrical circuit element known as a Josephson junction is studied. Josephson junctions are made from superconducting metals and work at very low temperatures. Past experiments have looked at the behavior of a single Josephson junction and found it capable of interesting electrical behavior. However, circuits composed of large numbers of Josephson junctions have yet to be fully studied. Just like the case of gas molecules, new collective behaviors result when the number of constituents is increased. This project will look at several of these new behaviors. One of these, like a tornado, is a swirl of electrical current. Another is a collective voltage oscillation, a back and forth motion like pendulums swinging together. A final behavior is voltage spiking, similar to the on-off firing of a biological neuron. With this last behavior, a longer term goal is to build circuits which would emulate collective behaviors in the human brain, where large numbers of neurons are connected together. This project incorporates undergraduate students as the primary researchers, preparing them for technical careers in the sciences.