1. A method for data clustering, comprising: obtaining a set of source data using a dynamic quantum clustering server system, where the set of source data comprises a data dimensionality; assigning a subset of the set of source data to a representational space using the dynamic quantum clustering server system, where the representational space allows a distance between pieces of data in the set of source data to be measured; constructing a potential function based on the representational space and the set of source data using the dynamic quantum clustering server system; computing a frame of animation for the set of source data over a time interval using the dynamic quantum clustering server system, wherein computing the frame of animation includes: associating data points from the set of source data with states, wherein the states include initial wave functions; computing kinetic and potential energies for each initial wave function; determining updated wave functions using the time-dependent Schrodinger equation based on the kinetic and potential energies of each initial wave function; determining at least one trajectory for the time interval based upon the updated wave functions; and constructing the frame of animation based on the at least one trajectory; evaluating the computed frame of animation for the set of source data over a time period using the dynamic quantum clustering server system, where the evaluation identifies data clusters comprising a subset of the set of source data within the computed frame of animation; generating a representation of the computed frame of animation using the dynamic quantum clustering server system; and transmitting the generated representation to a client device configured to display the generated representation by providing an interactive visual animation of point positions at one or more selected times.