Qrisp – Key features

1. Typed quantum variables 

Qrisp algorithms are constituted of variables and functions instead of qubits and circuits, which helps you to structure your code and avoid technical debt.

2. Modularity 


Automated qubit allocation allows separate modules to recycle qubit resources for each other without intertwining the code. This feature facilitates interoperability of code written by respective domain experts.

3. Compatibility 


Compilation results are circuit objects, implying they can be run on a variety of hardware providers such as IBM Quantum, IQM, Quantinuum, eleQtron etc. Further circuit processing is possible using circuit optimizers like PyZX.

4. Automatic uncomputation 

QuantumVariables can be uncomputed automatically once they are not needed anymore. The uncomputation module is tightly integrated with an advanced qubit resource management system.

5. Arithmetic 


A smoothly integrated system of floating-point arithmetic streamlines the development of non-trivial applications.

6. Simulator 

Qrisp ships with a high-performance simulator, that utilizes sparse matrices to store and process quantum states. This allows for the simulation of (some) quantum circuits involving 100+ qubits.