All submissions of the EM system will be redirected to **Online Manuscript Submission System**. Authors are requested to submit articles directly to **Online Manuscript Submission System** of respective journal.

**Zhang Lee ^{*}**

Department of Applied Mathematics and Theoretical Physics, Xiamen University, Fujian, China

- *Corresponding Author:
- Zhang Lee

Department of Applied Mathematics and Theoretical Physics,

Xiamen University,

Fujian,

China

**E-mail:**[email protected]

**Received:** 04-Apr-2022, Manuscript No. JSMS-22-60600; **Editor assigned:** 06- Apr-2022, Pre QC No. JSMS-22-60600 (PQ); **Reviewed:** 20-Apr-2022, QC No. JSMS-22-60600; **Revised: **22-Apr-2022, Manuscript No.** **JSMS-22-60600 (A); **Published:** 29-Apr-2022, DOI: 10.4172/ J Stats Math Sci.8.4.001.

**Visit for more related articles at** Research & Reviews: Journal of Statistics and Mathematical Sciences

A differential equation is a mathematical equation that connects one or more unknown functions with their derivatives. In applications, functions are used to represent physical quantities, derivatives are used to describe their rates of change, and the differential equation is used to define a connection between them. Differential equations play an important role in many areas, including engineering, physics, economics, and biology, because such relationships are widespread.

Mainly the study of differential equations consists of the study of their solutions (the set of functions that satisfy each equation), and of the qualities of their solutions. Only the most basic differential equations can be solved using explicit formulae; nevertheless, many features of solutions to a differential equation can be known without computing them precisely.

When there isn't a closed-form equation for the answer, it's often possible to approximate it numerically using computers. Many numerical approaches have been developed to determine solutions with a specified degree of precision, whereas the theory of dynamical systems emphasises qualitative analysis of systems defined by differential equations.

The motion of a body is characterized by its position and velocity as the time value fluctuates in classical mechanics. Newton's laws allow these variables to be dynamically written as a differential equation for the unknown location of the body as a function of time (given the position, velocity, acceleration, and other forces acting on the body).

This differential equation (also known as an equation of motion) can be solved explicitly in some instances.

The estimation of the velocity of a ball falling through the air, considering just gravity and air resistance, is an example of modeling a real-world issue using differential equations. The acceleration of the ball towards the earth is equal to gravity's acceleration minus air resistance's deceleration.

The acceleration of the ball towards the earth is equal to gravity's acceleration minus air resistance's deceleration. Air resistance may be described as proportional to the ball's velocity, and gravity is assumed to be constant. This implies that the ball's acceleration, which is a derivative of its velocity, is affected by it (and the velocity depends on time). Solving a differential equation and validating its correctness is required to determine velocity as a function of time.

There are various forms of differential equations. These kinds of differential equations can assist inform the approach to a solution in addition to providing the features of the equation itself. Ordinary or partial equations, linear or non-linear equations, and homogeneous or heterogeneous equations are all common differences. This list is far from complete; differential equations have many more features and subclasses that can be highly useful in certain situations.

**Ordinary differential equations**

An Ordinary Differential Equation (ODE) is a mathematical expression that contains an unknown function of one real or complex variable x, as well as its derivatives and certain known functions of x. The unknown function is usually represented as a variable (commonly abbreviated y) that is dependent on x. As a result, x is frequently referred to as the equation's independent variable. The term "ordinary" is used to distinguish itself from the phrase "partial differential equation," which can refer to many independent variables.

The differential equations that are linear in the unknown function and its derivatives are known as linear differential equations. Their theory is well established, and their solutions may often be expressed in terms of integrals. The majority of ODEs seen in physics are linear. As a result, most special functions may be defined as linear differential equation solutions.

Numerical techniques are widely employed to solve differential equations on a computer since the solutions of a differential equation cannot be stated using a closed-form expression.

**Partial differential equations**

A Partial Differential Equation (PDE) is a differential equation in which the partial derivatives of unknown multivariable functions are unknown (This differs from conventional differential equations, which deal with single-variable functions and their derivatives). PDEs are used to construct problems involving many variables' functions, and they are either solved in closed form or utilized to develop an appropriate computer model.

PDEs may be used to model a wide range of natural phenomena, including sound, heat, electrostatics, electrodynamics, fluid flow, elasticity, and quantum mechanics. In terms of PDEs, these seemingly disparate physical events may be expressed identically. Partial differential equations are used to describe multidimensional systems in the same way that ordinary differential equations are used to model one-dimensional dynamical systems. Partial differential equations for modeling randomization are referred to as stochastic partial differential equations.