Publications

QMware's hybrid quantum computing approach: turning research into practice.

At QMware, we pride ourselves on our research-based hybrid quantum computing approach. Our team of experts is dedicated to staying on the cutting edge of quantum computing research, and we apply our findings to develop our QMware cloud platform. This platform offers a hybrid quantum-classical infrastructure that can be utilized for both business applications and research purposes. We strive to bridge the gap between quantum computing theory and practical applications by providing a reliable and accessible platform for businesses and researchers. In addition, we offer continuous benchmarking services to compare publicly available hardware technologies, ensuring transparency in the market and providing valuable insights to the quantum computing community.

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A uniform quantum computing model based on virtual quantum processors

Quantum Computers, once fully realized, can represent an exponential boost in computing power. However, the computational power of the current quantum computers, referred to as Noisy Internediate Scale Quantum, or NISQ, is severely limited because of environmental and intrinsic noise, as well as the very low connectivity between qubits compared to their total amount. We propose a virtual quantum processor that emulates a generic hybrid quantum machine which can serve as a logical version of quantum computing hardware. This hybrid classical quantum machine powers quantum-logical computations which are substitutable by future native quantum processors.

Author: George Gesek

March 2023

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Benchmarking simulated and physical quantum processing units using quantum and hybrid algorithms

Powerful hardware services and software libraries are vital tools for quickly and affordably designing, testing, and executing quantum algorithms. A robust large-scale study of how the performance of these platforms scales with the number of qubits is key to providing quantum solutions to challenging industry problems. Such an evaluation is difficult owing to the availability and price of physical quantum processing units. This work benchmarks the runtime and accuracy for a representative sample of specialized high-performance simulated and physical quantum processing units. Results show the QMware cloud computing service can reduce the runtime for executing a quantum circuit by up to 78% compared to the next fastest option for algorithms with fewer than 27 qubits. The AWS SV1 simulator offers a runtime advantage for larger circuits, up to the maximum 34 qubits available with SV1. Beyond this limit, QMware provides the ability to execute circuits as large as 40 qubits. Physical quantum devices, such as Rigetti's Aspen-M2, can provide an exponential runtime advantage for circuits with more than 30. However, the high financial cost of physical quantum processing units presents a serious barrier to practical use. Moreover, of the four quantum devices tested, only IonQ's Harmony achieves high fidelity with more than four qubits. This study paves the way to understanding the optimal combination of available software and hardware for executing practical quantum algorithms.

Author: Mohammad Kordzanganeh, Markus Buchberger, Maxim Povolotskii, Wilhelm Fischer, Andrii Kurkin, Wilfrid Somogyi, Asel Sagingalieva, Markus Pflitsch, Alexey Melnikov

November 2022

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