2022
,
Seidel, Raphael
,
Bock, Sebastian
,
Tcholtchev, Nikolay Vassilev
,
Hauswirth, Manfred
The recent advances of quantum computation hardware spark realistic hopes to achieve commercially relevant quantum advantage in less than a decade. While the physics side of quantum computing makes significant progress, the support for high-level quantum programming abstractions is still in its infancy compared to modern classical languages and frameworks. In this article we present Qrisp, a framework which aims to bridge several of the existing gaps between the abstract high-level programming paradigms of state-of-the art software engineering and the physical reality of today's quantum hardware. The goal of the framework is to provide a uniform high-level programming interface, abstraction and low-level backend interface for different hardware platforms. We specify a simple and expressive syntax which nevertheless compiles to efficient circuits. Compared to many other high-level language approaches, Qrisps most outstanding feature is that it's programs are compiled to the circuit level and can thus be executed on most of today's physical backends.
2021
,
Seidel, Raphael
,
Becker, Colin Kai-Uwe
,
Tcholtchev, Nikolay
,
Gheorghe-Pop, Ilie-Daniel
,
Hauswirth, Manfred
The steadily growing research interest in quantum computing together with the accompanying technological advances in the realization of quantum hardware fuels the development of meaningful real-world applications, as well as implementations for well-known quantum algorithms. One of the most prominent examples till today is Grover's algorithm, which can be used for efficient search in unstructured databases. Quantum oracles that are frequently masked as black boxes play an important role in Grover's algorithm. Hence, the automatic generation of oracles is of paramount importance. Moreover, the automatic generation of the corresponding circuits for a Grover quantum oracle is deeply linked to the synthesis of reversible quantum logic, which despite numerous advances in the field still remains a challenge till today in terms of synthesizing efficient and scalable circuits for complex boolean functions. In this paper, we present a flexible method for automatically encoding unstructured databases into oracles, which can then be efficiently searched with Grover's algorithm. Furthermore, we develop a tailor-made method for quantum logic synthesis, which vastly improves circuit complexity over other current approaches. Finally, we present another logic synthesis method that considers the requirements of scaling onto real world backends. We compare our method with other approaches through evaluating the oracle generation for random databases and analyzing the resulting circuit complexities using various metrics.