Acknowledging the inter-disciplinary aspect of quantum computing, there is a need to make quantum programming more accessible for its fast-growing community. With the advent of quantum computers with hundreds of qubits designing circuits manually is infeasible. Most current languages are low-level or involve a steep learning curve or lack control. Thus we propose a quantum programming language (QPL) that allows for high-level abstractions with intuitive syntax while still allowing users to directly construct circuits.
Acknowledging the inter-disciplinary aspect of quantum computing, there is a need to make quantum programming more accessible for its fast-growing community. With the advent of quantum computers with hundreds of qubits designing circuits manually is infeasible. Most current languages are low-level or involve a steep learning curve or lack control. Thus we propose a quantum programming language (QPL) that allows for high-level abstractions with intuitive syntax while still allowing users to directly construct circuits.
Quantum computing leverages the principles of quantum mechanics to perform computations far beyond the capabilities of classical systems, particularly in fields such as cryptography and optimization. However, current quantum programming languages often require low-level implementation, posing significant barriers for many developers due to their steep learning curve and limited abstraction. In response, we introduce Qutes, a high-level quantum programming language designed to simplify quantum algorithm development while maintaining the flexibility required for advanced applications. By abstracting complex quantum operations and allowing intuitive expressions through high-level constructs, Qutes enables users to write efficient quantum programs without extensive knowledge of quantum mechanics or circuit design. Built upon Qiskit, Qutes translates its syntax directly into executable quantum code, facilitating seamless integration with quantum hardware. This paper provides an overview of the language's architecture, core functionalities, and its ability to unify classical and quantum operations within a single framework. Additionally, we demonstrate Qutes' application in key quantum algorithms, showcasing its potential to make quantum programming more accessible and practical for a wider range of developers and researchers.
Abstract Quantum computing offers transformative capabilities by exploiting quantum mechanical principles to solve problems that are intractable for classical systems, particularly in areas like cryptography, optimization, and data analysis. However, most current quantum programming languages operate at a low level, requiring in-depth expertise in quantum mechanics and circuit theory, which presents a barrier to wider adoption. In this work, we introduce Qutes, a high-level quantum programming language that simplifies the development of quantum algorithms while preserving the flexibility needed for advanced applications. Qutes abstracts low-level quantum operations through intuitive syntax and high-level constructs, enabling developers to express complex algorithms without detailed circuit knowledge. Built atop Qiskit, Qutes transpiles seamlessly into executable code, ensuring compatibility with real quantum hardware. We present the architecture, language design, and hybrid classical-quantum integration of Qutes, and demonstrate its use through implementations of canonical quantum algorithms. Our results highlight Qutes’ potential to democratize quantum programming by lowering the entry threshold and accelerating prototyping for researchers and developers alike.
Quantum computing hardware is advancing at a rapid pace, yet the lack of high-level programming abstractions remains a serious bottleneck in the development of new applications. Widely used frameworks still rely on gate-level circuit descriptions, causing the algorithm's functional intent to become lost in low-level implementation details, and hindering flexibility and reuse. While various high-level quantum programming languages have emerged in recent years - offering a significant step toward higher abstraction - many still lack support for classicallike expression syntax, and native constructs for useful quantum algorithmic idioms. This paper presents Qmod, a high-level quantum programming language designed to capture algorithmic intent in natural terms while delegating implementation decisions to automation. Qmod introduces quantum numeric variables and expressions, including digital fixed-point arithmetic tuned for compact representations and optimal resource usage. Beyond digital encoding, Qmod also supports nondigital expression modes phase and amplitude encoding - frequently exploited by quantum algorithms to achieve computational advantages. We describe the language's constructs, demonstrate practical usage examples, and outline future work on evaluating Qmod across a broader set of use cases.
Quantum computing hardware is advancing at a rapid pace, yet the lack of high-level programming abstractions remains a serious bottleneck in the development of new applications. Widely used frameworks still rely on gate-level circuit descriptions, causing the algorithm's functional intent to become lost in low-level implementation details, and hindering flexibility and reuse. While various high-level quantum programming languages have emerged in recent years - offering a significant step toward higher abstraction - many still lack support for classical-like expression syntax, and native constructs for useful quantum algorithmic idioms. This paper presents Qmod, a high-level quantum programming language designed to capture algorithmic intent in natural terms while delegating implementation decisions to automation. Qmod introduces quantum numeric variables and expressions, including digital fixed-point arithmetic tuned for compact representations and optimal resource usage. Beyond digital encoding, Qmod also supports non-digital expression modes - phase and amplitude encoding - frequently exploited by quantum algorithms to achieve computational advantages. We describe the language's constructs, demonstrate practical usage examples, and outline future work on evaluating Qmod across a broader set of use cases.
Since the invention of Quantum Computing (QC) in the 1980s, substantial claims about QC’s ability to solve computational problems of unparalleled complexity have emerged. However, forty years later, no significant real-world QC applications exist. Indeed, the availability of small-scale noisy quantum computers is to blame. Still, simultaneously, the programming of quantum computers is too close to quantum hardware, requiring software engineers with specialized backgrounds to build QC applications and limiting the maximum exploitation of QC’s potential. Thus, there is a need for an abstract yet intuitive quantum-oriented paradigm (QOP) for building QC applications, similar to the object-oriented paradigm established in the 1960s for classical computers that laid the foundations of modern programming and modeling languages for classical computers. Unfortunately, such a QC paradigm doesn’t exist. Thus, we foresee the need to build a novel QOP based on which future quantum programming and modeling languages shall be developed. Such QOP shall enable users with diverse backgrounds (e.g., computer scientists, software engineers, and physicists) to build QC applications cost-effectively, intuitively, and independently of low-level quantum mechanics characteristics (e.g., superposition and entanglement). This paper discusses the emerging work of QOP and presents research directions that the software engineering and programming communities can follow to build a successful QOP.
Quantum Computers are quickly becoming capable of solving certain tasks substantially faster than classical computers and the promise of quantum-driven advancements in research and economy continues to accelerate the development of quantum technology. However, most software development for quantum computers relies on the tedious manual implementation of quantum circuits on a very low level of abstraction, with tools such as the prominent IBM Qiskit SDK. In 2020, Silq, a quantum language to enable more intuitive and robust quantum development, was presented. While it substantially simplifies the write- and readability of quantum programs, Silq Code can only be run through its simulator on classical hardware. In comparison, Qiskit and its close integration with IBM’s Quantum Experience even enable users to run and evaluate quantum programs on physical quantum hardware. This paper proposes an automatic source-to-source translator for basic Silq Code and the extension of Qiskit by core concepts of Silq’s abstraction layers, such as Quantum Indexing and Quantum Control Flow.