Automated Design of Quantum Circuits

Khaled Khalfaoui, Tahar Boudjedaa, Elhillali Kerkouche

Damian Rovara, Robert Wille

As quantum circuits grow beyond small toy examples, preparing them for execution on physical devices becomes increasingly complex. Design automation is therefore essential for scalable quantum computing: Compilation procedures optimize resource requirements and transform circuits to a format compatible with specific hardware; resource estimation evaluates execution cost; verification methods prove circuit correctness. However, these concepts present a steep learning curve for novices, particularly when quantum circuits are introduced through low-level textual representations. To address this, we present a block-based programming framework for quantum design automation, implemented as an extension to the Scratch programming platform. This system allows users to build quantum circuits as a sequence of blocks and embed them in classical control logic to perform evaluations, compare simulation results, and directly apply different design automation techniques. We evaluated the approach in a user study with computer science students, who completed guided exercises using the platform and provided structured feedback in the form of self-reports and short knowledge assessments. Results demonstrate strong understanding and confidence in quantum design automation concepts, suggesting that the block-based approach successfully lowers the entry barrier to quantum design automation. The implemented framework is open-source and available at https://github.com/munich-quantum-toolkit/scratch-quantum.

Fatma Hamzaoui, Roselyne Chotin-Avot, Mohsen Machhout +2 more

Colin P. Williams, Alexander Gray

Abstract. In order to design a quantum circuit that performs a desired quantum computation, it is necessary to find a decomposition of the unitary matrix that represents that computation in terms of a sequence of quantum gate operations. To date, such designs have either been found by hand or by exhaustive enumeration of all possible circuit topologjks. In this paper we propose an automated approach to quantum circuit design using search heuristics based on principles abstracted from evolutionary genetics, i.e. using a genetic programming algorithm adapted specially for this problem. We demonstrate the method on the task of discovering quantum circuit designs for quantum teleportation. We show that to find a given known circuit design (one which was hand-crafted by a human), the method considers roughly an order of magnitude fewer designs than naive enumeration. In addition, the method finds novel circuit designs superior to those previously known. 1

Jincheng Zhang

This paper introduces a novel Differentiable Quantum Circuit Design Language (DQCDL), designed to facilitate automated quantum algorithm design through direct optimization within the circuit's parameter space. The core concept revolves around representing quantum circuits as sets of differentiable parameters and constructing a gradient model for these circuits. Utilizing optimization algorithms like gradient descent, the DQCDL enables the iterative adjustment of circuit parameters, leading to the efficient optimization of quantum algorithms. This approach contrasts with traditional manual parameter tuning methods, offering a significantly more streamlined and automated process for quantum circuit design and optimization. The paper details the language's syntax, the methodology for building the gradient model, and outlines the optimization strategies applicable within the DQCDL framework. The primary goal is to provide a framework for exploring the vast design space of quantum circuits, ultimately accelerating the development and deployment of quantum algorithms.

Rasit Onur Topaloglu