## What is BQSKit

**The Berkeley Quantum Synthesis Toolkit (BQSKit) is a superoptimizing quantum compiler and research vehicle that combines ideas from several projects at LBNL into an easily accessible and quickly extensible software suite.**

- QSearch: Optimal depth synthesis up to four qubits
- LEAP: Best quality of solution synthesis up to six qubits
- QFAST: Scales good solution quality synthesis up to eight qubits
- QGO: Optimizing compiler combining partitioning and synthesis
- QFactor: Fastest quantum circuit optimizer using tensor networks

All of our software is free and open-source. We have several tools available for synthesis and optimization. Explore our GitHub Page. We are constantly working on improving our software, join our mailing list to be the first to hear about software updates.

### Global Circuit Optimization

Global circuit optimization is the process of taking a quantum program, given as a quantum circuit, and reducing (optimizing) the depth of it. The depth of a quantum circuit is directly related to the program’s runtime and the probability of error in the final result. BQSKit combines circuit partitioning and synthesis to optimize circuits far beyond what traditional optimizing compilers can do.

### Circuit Synthesis

Quantum synthesis is the process of converting a mathematical description of a quantum program, given as a unitary matrix, to an executable quantum circuit that implements it. This is used as a subroutine in global circuit optimization, as well as, in research for algorithm or gate set discovery.

### Circuit Parameter Optimization

Circuit parameter optimization is a subroutine that tunes the parameters in a circuit to better fit a target unitary. This is used extensively in quantum synthesis. The BQSKit IR has been designed for efficient parameter optimization to better support research.

# Showcase

### Constant Depth TFIM Circuits

Quantum circuit synthesis enables algorithm discovery. There is no better example of this than the work carried out by Lindsay Bassman and Roel Van Beeumen. Ethan Smtih discovered our synthesis tools produced similar circuits for all time-steps of TFIM circuits, which enabled Lindsay and Roel to explore constant depth circuits from first-principles.

### Real Time Compilation of QITE Algorithm

The BQSKit team is collaborating with researchers from the AQT project. We are assisting them with real-time optimization of the circuits produced from their hybrid algorithm. Where Qiskit’s synthesis falls short, we are able to reduce depth greatly.

This work was supported by the DOE Office of Advanced Scientific Computing Research (ASCR) through the Accelerated Research for Quantum Computing Program