Important

This repository has been subsumed by https://github.com/qqq-wisc/guoq. Please refer to the instructions there on how to use QUESO.

QUESO

This is a tool for synthesizing quantum-circuit optimizers as described in [1]. To reproduce the experimental conditions of the paper, see the Zenodo artifact, which contains a Docker image with everything set up.

Dependencies

• Java 17
• Maven 3

Installation

git clone https://github.com/qqq-wisc/queso.git
cd queso
mvn package -Dmaven.test.skip

The JAR will be in queso/target.

Usage

Supported Gate Sets

If the gate set you are looking for is not in this list, read on to the next section to see how to add a new gate set. Additionally, feel free to open an issue requesting a new gate set. Pull requests adding new gate sets are welcome!

• IBM (old): u1, u2, u3, cx
• IBM (new): rz, sx, x, cx
• Rigetti: rx(pi/2), rx(-pi/2), rx(pi), rz, cz
• Ion trap: rx, ry, rz, rxx
• Nam [2]: h, rz, x, cx

Defining a New Gate Set

1. Derive path sum semantics for the relevant gates
2. Implement path sum semantics in a method in PathSum.java for each gate
3. Add each new gate to applyGate(...) in Synthesizer.java and specify how angles should be enumerated if this is a parameterized gate
4. Add the gate set at the bottom of Synthesizer.java with the desired angles

Synthesizing Rules

To see options available:

java --enable-preview -cp target/QUESO-1.0-jar-with-dependencies.jar Synthesizer

Example commands:

java --enable-preview -cp target/QUESO-1.0-jar-with-dependencies.jar Synthesizer -g nam -q 3 -s 3
java --enable-preview -cp target/QUESO-1.0-jar-with-dependencies.jar Synthesizer -g nam -q 3 -s 6

Optimizing a Circuit

To see options available:

java --enable-preview -cp target/QUESO-1.0-jar-with-dependencies.jar Optimizer

Example command:

java --enable-preview -cp target/QUESO-1.0-jar-with-dependencies.jar Optimizer -c benchmarks/decomposed/decomp0/nam_rz/decomp0_tof_3.qasm -g nam -r rules_q3_s6_nam.txt -sr rules_q3_s3_nam_symb.txt -t 3600 -o optimized_benchmarks -j "nam"

The following rule sizes result in the best performance:

	Not Symbolic	Symbolic
Nam	6	3
IBM (old)	4	3
Rigetti	5	3
Ion trap	3	3

References

[1] Amanda Xu, Abtin Molavi, Lauren Pick, Swamit Tannu, Aws Albarghouthi. Synthesizing quantum-circuit optimizers. Proceedings of the ACM on Programming Languages. Volume 7, PLDI, 2023. https://doi.org/10.1145/3591254

[2] Yunseong Nam, Neil J Ross, Yuan Su, Andrew M Childs, and Dmitri Maslov. 2018. Automated optimization of large quantum circuits with continuous parameters. npj Quantum Information 4, 1 (2018), 1-12.