Quantum Computing Environments

Frank Tabakin A, Bruno Julia Diaz

Darrell Teegarden, Allison Casey, F. Gino Serpa +4 more

Quantum Computing (QC) has evolved from a few custom quantum computers, which were only accessible to their creators, to an array of commercial quantum computers that can be accessed on the cloud by anyone. Accessing these cloud quantum computers requires a complex chain of tools that facilitate connecting, programming, simulating algorithms, estimating resources, submitting quantum computing jobs, retrieving results, and more. Some steps in the chain are hardware dependent and subject to change as both hardware and software tools, such as available gate sets and optimizing compilers, evolve. Understanding the trade-offs inherent in this process is essential for evaluating the power and utility of quantum computers. ARLIS has been systematically investigating these environments to understand these complexities. The work presented here is a detailed summary of three months of using such quantum programming environments. We show metadata obtained from these environments, including the connection metrics to the different services, the execution of algorithms, the testing of the effects of varying the number of qubits, comparisons to simulations, execution times, and cost. Our objective is to provide concrete data and insights for those who are exploring the potential of quantum computing. It is not our objective to present any new algorithms or optimize performance on any particular machine or cloud platform; rather, this work is focused on providing a consistent view of a single algorithm executed using out-of-the-box settings and tools across machines, cloud platforms, and time. We present insights only available from these carefully curated data.

E. K. Subramanian, C. S. Sanoj

Current quantum computer simulation strategies are inefficient in simulation and their realizations are also failed to minimize those impacts of the exponential complexity for simulated quantum computations. We proposed a Quantum computer simulator model in this paper which is a coordinated Development Environment – QuIDE (Quantum Integrated Development Environment) to support the improvement of algorithm for future quantum computers. The development environment provides the circuit diagram of graphical building and flexibility of source code. Analyze the complexity of algorithms shows the performance results of the simulator and used for simulation as well as result of its deployment during simulation.

Hansika Weerasena, Prabhat Mishra

Ginés Carrascal, Guillermo Botella, Alberto Antonio Del Barrio

Quantum Computing allows for substantial speed-ups e.g. for integer factorization or database search, compared to conventional computation. However, since real quantum computers are an emerging technology, a significant amount of research in this domain still relies on simulations of quantum computations on conventional machines. This paper proposes a containerized environment to simulate quantum circuits, making this environment quick and easy to share within research teams. Also test the environment implementing an arithmetic circuit (Vedral’s adder) and compares the performance of two of the current more used environments: IBM QISKit and Google Cirq.

Osama Babakhel, Mujahid Tabassum, Tripti Sharma