tensorial
简明释义
英[tɛnˈsɔr.i.əl]美[tɛnˈsɔr.i.əl]
adj. 张量的
英英释义
Relating to or denoting a tensor, which is a mathematical object that generalizes scalars, vectors, and matrices. | 与张量相关或表示的,张量是一种数学对象,概括了标量、向量和矩阵。 |
单词用法
同义词
张量 | Tensor calculus is essential in the study of general relativity. | 张量微积分在广义相对论的研究中至关重要。 | |
向量的 | 向量量既有大小又有方向。 | ||
矩阵的 | 矩阵运算是线性代数中的基础。 |
反义词
标量 | 标量量只有大小,例如温度。 | ||
向量的 | Vectorial analysis is crucial in understanding forces in physics. | 向量分析在理解物理中的力时至关重要。 |
例句
1.In general, fluxes and forces may have different tensorial characters.
一般说来,力和通量可以具有不同的张量特征标。
2.In general, fluxes and forces may have different tensorial characters.
一般说来,力和通量可以具有不同的张量特征标。
3.When analyzing stress and strain in solid mechanics, we utilize tensorial 张量的 representations.
在固体力学中分析应力和应变时,我们利用tensorial 张量的表述。
4.The concept of tensorial 张量的 transformations is crucial in the study of relativity.
在相对论研究中,tensorial 张量的变换概念至关重要。
5.The equations governing fluid dynamics can be expressed in a tensorial 张量的 form, making them easier to manipulate.
流体动力学的方程可以用tensorial 张量的形式表达,从而更容易操作。
6.In advanced physics, we often deal with tensorial 张量的 quantities to describe the properties of materials.
在高级物理中,我们常常处理tensorial 张量的量来描述材料的性质。
7.In machine learning, tensorial 张量的 data structures are used to represent high-dimensional data.
在机器学习中,tensorial 张量的数据结构用于表示高维数据。
作文
In the realm of mathematics and physics, the concept of tensors plays a crucial role in understanding complex systems. Tensors are mathematical objects that generalize scalars and vectors, allowing for the representation of multi-dimensional data. One of the terms associated with tensors is tensorial, which refers to properties or operations related to tensors. Understanding the tensorial nature of physical quantities is essential for fields such as continuum mechanics, general relativity, and electromagnetism.To illustrate the importance of tensorial concepts, let us consider the field of general relativity. In this theory, gravity is not viewed as a force but rather as the curvature of spacetime caused by mass. The mathematical framework used to describe this curvature involves the Riemann curvature tensor, which is inherently tensorial. This tensor encapsulates information about how spacetime bends and how objects move within that curved space.Another example can be found in fluid dynamics, where the stress tensor is a tensorial representation of the internal forces acting within a fluid. It allows scientists and engineers to analyze how fluids respond to external forces, making it possible to predict flow patterns and behavior under various conditions. The ability to express physical laws in a tensorial form enables a more profound understanding of the interactions within the system, leading to more accurate models and simulations.Moreover, the tensorial framework is not limited to theoretical discussions; it has practical applications in engineering and technology. For instance, in computer vision and machine learning, tensors are used to represent images and data structures. The manipulation of these tensors through tensorial operations allows for the extraction of features and patterns from large datasets, facilitating advancements in artificial intelligence.The significance of tensorial analysis extends into the realm of quantum mechanics as well. In quantum field theory, fields are described using tensorial constructs that encapsulate the behavior of particles and their interactions. This approach provides a unified framework that bridges classical and quantum physics, demonstrating the versatility and power of tensorial mathematics.In conclusion, the term tensorial signifies a fundamental aspect of modern science and mathematics. Its application spans various disciplines, providing a robust language for describing complex phenomena. As we delve deeper into the intricacies of the universe, the tensorial framework will undoubtedly continue to play a pivotal role in our quest for knowledge and understanding. By mastering the concept of tensorial relationships, we equip ourselves with the tools necessary to tackle the challenges posed by both theoretical inquiries and practical applications in our ever-evolving world.
在数学和物理的领域中,张量的概念在理解复杂系统方面发挥着至关重要的作用。张量是广义化标量和向量的数学对象,允许表示多维数据。与张量相关的一个术语是tensorial,它指的是与张量相关的属性或操作。理解物理量的tensorial特性对于连续介质力学、广义相对论和电磁学等领域至关重要。为了说明tensorial概念的重要性,让我们考虑广义相对论这一领域。在该理论中,重力并不是被视为一种力,而是由质量引起的时空弯曲。用于描述这种弯曲的数学框架涉及到黎曼曲率张量,它本身就是tensorial的。这个张量包含了关于时空如何弯曲以及物体如何在那个弯曲的空间中运动的信息。另一个例子可以在流体动力学中找到,其中应力张量是流体内部作用力的tensorial表示。它允许科学家和工程师分析流体如何响应外部力量,使得预测流动模式和在各种条件下的行为成为可能。以tensorial形式表达物理定律的能力使得对系统内相互作用的更深刻理解成为可能,从而导致更准确的模型和模拟。此外,tensorial框架不仅限于理论讨论;它在工程和技术中的实际应用也非常广泛。例如,在计算机视觉和机器学习中,张量用于表示图像和数据结构。通过tensorial操作对这些张量的处理使得从大型数据集中提取特征和模式成为可能,促进了人工智能的进步。tensorial分析的重要性还延伸到量子力学的领域。在量子场论中,场使用tensorial构造来描述粒子及其相互作用的行为。这种方法提供了一个统一的框架,桥接了经典物理和量子物理,展示了tensorial数学的多功能性和力量。总之,术语tensorial意味着现代科学和数学的一个基本方面。它的应用跨越多个学科,为描述复杂现象提供了强大的语言。随着我们深入探索宇宙的复杂性,tensorial框架无疑将继续在我们追求知识和理解的过程中发挥关键作用。通过掌握tensorial关系的概念,我们为应对理论探究和实践应用所带来的挑战装备了必要的工具。