## Research Applications

Qiskit allows for easy research and development for specific industry use cases that have the highest potential for quantum advantage.

See docsThe Qiskit Optimization package covers the whole range from high-level modeling of optimization problems, with automatic conversion of problems to different required representations, to a suite of easy-to-use quantum optimization algorithms that are ready to run on classical simulators, as well as on real quantum systems.

Solve the Max Cut ProblemThe Qiskit Finance package contains components to load uncertainty models, e.g., for pricing securities/derivatives or analyzing the risk involved. It also contains data providers to source real or random data to finance experiments and together with the Qiskit Optimization package allows easy modeling of optimization problems as arising e.g. in portfolio management.

Perform Option Pricing with qGansThe Qiskit Machine Learning package simply contains sample datasets at present. Qiskit has some classification algorithms such as QSVM (Quantum Support Vector Machine) and VQC (Variational Quantum Classifier), where this data can be used for experiments, and there is also QGAN (Quantum Generative Adversarial Network) algorithm.

Classify data with a VQCThe Qiskit Chemistry package supports problems including ground state energy computations, excited states and dipole moments of molecule, both open and closed-shell.

Find the Energy Ground State of a Molecule