|
所在平台: Coursera |
课程主页: https://www.coursera.org/learn/emergent-phenomena
课程评论：没有评论
课程名称：科学与日常生活中的涌现现象 课程概述：在20世纪初量子力学出现之前，大多数科学家认为只要理解构成部分的行为，就应该能够预测宇宙中任何物体的行为。例如，如果能够为系统中每个原子的运动编写方程，就可以借助足够大的计算设备求解这些方程，并对系统的未来做出准确预测。然而，有一些系统挑战了这一观点。例如，生命细胞主要由碳、氢和氧等元素构成，尽管我们可以单独研究这些成分，但无法想象将它们以特定方式结合在一起会导致如此复杂而神奇的生物体。因此，我们可以认为生命是由某种方式精确组织的构成部分的涌现属性。 本课程通过材料科学、数学、生物学、物理学和神经科学的实例，探索涌现的概念，展示普通成分组合在一起时，如何产生意想不到和惊人的行为。 完成此课程后，您将能够： 1. 解释涌现与还原主义科学方法之间的假设差异。 2. 解释为什么许多人认为还原主义方法不足以描述和预测复杂系统。 3. 描述用于研究现象的尺度如何影响分析和理解。 4. 解释为什么寻找解释涌现现象的普遍原理，使其成为科学研究的活跃领域。 5. 讨论涌现现象的例子，并解释它们为何被归类为涌现现象。 课程大纲： - 欢迎 - 开始我们的旅程：介绍涌现的概念以及本课程的流程。 - 泡沫的奥秘：探讨复杂流体作为第一个涌现现象。 - 混沌动力学：研究似乎随机的事件是否真正随机，探索确定性过程如何产生随机性外观。 - 图案形成与系统生物学：解释自然界中图案（如虎和豹的斑点）如何形成。 - 量子相干性、多体状态与量子计算：从还原主义与涌现的角度研究量子事件。 - 意识：探讨意识如何从复杂的原子和分子集合中涌现，分析大脑不同区域如何协调互动以产生意识。
Name:Welcome - Let's Get Started
Description:In this module we'll introduce the concept of emergence and provide an orientation to how this course will proceed.
Name:The Mystery of Foam
Description:Can a substance be both a solid and a liquid? In this module we’ll take a close look at our first emergent phenomena, complex fluids.
Name:Chaotic Dynamics
Description:Are seemingly random events truly random? In this module, we'll examine ways that deterministic processes can produce the appearance of randomness.
Name:Pattern Formation and Systems Biology
Description:Have you ever wondered why tigers have spots and leopards have spots? This module helps to explain how these and other patterns form in nature.
Name:Quantum Coherence, Many-Body States, and Quantum Computing
Description:How can we study quantum events from both a reductionist and emergent perspective? This module takes a look at the atomic and quantum level of some everyday phenomena.
Name:Consciousness
Description:One of the most awe inspiring emergent phenomena is how consciousness emerges from complex collections of atoms and molecules. In this module, we’ll take a look at how the various regions of our brain coordinate and interact to produce consciousness.
Before the advent of quantum mechanics in the early 20th century, most scientists believed that it should be possible to predict the behavior of any object in the universe simply by understanding the behavior of its constituent parts. For instance, if one could write down the equations of motion for every atom in a system, it should be possible to solve those equations (with the aid of a sufficiently large computing device) and make accurate predictions about that system’s future. However, there are some systems that defy this notion. Consider a living cell, which consists mostly of carbon, hydrogen, and oxygen along with other trace elements. We can study these components individually without ever imagining how combining them in just the right way can lead to something as complex and wonderful as a living organism! Thus, we can consider life to be an emergent property of what is essentially an accumulation of constituent parts that are somehow organized in a very precise way. This course lets you explore the concept of emergence using examples from materials science, mathematics, biology, physics, and neuroscience to illustrate how ordinary components when brought together can collectively yield unexpected, surprising behaviors. Note: The fractal image (Sierpinkski Triangle) depicted on the course home page was generated by a software application called XaoS 3.4, which is distributed by the Free Software Foundation under a GNU General Public License. Upon completing this course, you will be able to: 1. Explain the difference in assumptions between an emergent versus reductive approach to science. 2. Explain why the reductivist approach is understood by many to be inadequate as a means of describing and predicting complex systems. 3. Describe how the length scale used to examine a phenomenon can contribute to how you analyze and understand it. 4. Explain why the search for general principles that explain emergent phenomena make them an active locus of scientific investigation. 5. Discuss examples of emergent phenomena and explain why they are classified as emergent.
