Graphics programming is the most obvious one and it uses it plenty, but really any application that can be modeled as a series of discrete changes will mostly likely be using calculus.
Time series data is the most common form of this, where derivatives are the rate of change from one time step to the next and integrals are summing the changes across a range of time.
But it can even be more abstract than that. For example, there’s a recent-ish paper on applying signal processing techniques (which use calculus themselves, btw) to databases for the purposes of achieving efficient incremental view maintenance: https://arxiv.org/abs/2203.16684
The idea is that a database is a sequence of transactions that apply a set of changes to said database. Integrating gets you the current state of the database by applying all of the changes.
Graphics programming is the most obvious one and it uses it plenty, but really any application that can be modeled as a series of discrete changes will mostly likely be using calculus.
Time series data is the most common form of this, where derivatives are the rate of change from one time step to the next and integrals are summing the changes across a range of time.
But it can even be more abstract than that. For example, there’s a recent-ish paper on applying signal processing techniques (which use calculus themselves, btw) to databases for the purposes of achieving efficient incremental view maintenance: https://arxiv.org/abs/2203.16684
The idea is that a database is a sequence of transactions that apply a set of changes to said database. Integrating gets you the current state of the database by applying all of the changes.