Computation with Qubits

Sergei Kurgalin, Sergei Borzunov

Ahmed Banafa

Quantum computing is the area of study focused on developing computer technology based on the principles of quantum theory. As we progress to smaller and faster circuits, we begin to reach the physical limits of materials and the threshold for classical laws of physics to apply. Classical computers use transistors as the physical building blocks of logic, while quantum computers may use trapped ions, superconducting loops, quantum dots or vacancies in a diamond. Physical qubits are the physical qubits in a quantum computer, whereas logical qubits are groups of physical qubits we use as a single qubit in our computation to fight noise and improve error correction. There are many estimates as to how many qubits the authors will need to perform certain calculations, but some of these estimates talk about logical qubits and others talk about physical qubits. For example, to break RSA cryptography we would need thousands of logical qubits but millions of physical qubits.

Krish Kotru

Neutral-atom qubits offer a promising platform for fault-tolerant quantum computing. We demonstrate a quantum computer—featuring 100s of atomic qubits, a universal gateset, and qubit movement—performing error correction and computation on 24-28 logical qubits.

Swamit Tannu, Moinuddin K. Qureshi

Recently, IBM, Google, and Intel showcased quantum computers ranging from 49 to 72 qubits. While these systems represent a significant milestone in the advancement of quantum computing, existing and near-term quantum computers are not yet large enough to fully support quantum error-correction. Such systems with few tens to few hundreds of qubits are termed as Noisy Intermediate Scale Quantum computers (NISQ), and these systems can provide benefits for a class of quantum algorithms. In this paper, we study the problems of Qubit-Allocation (mapping of program qubits to machine qubits) and Qubit-Movement(routing qubits from one location to another to perform entanglement). We observe that there exists variation in the error rates of different qubits and links, which can have an impact on the decisions for qubit movement and qubit allocation. We analyze characterization data for the IBM-Q20 quantum computer gathered over 52 days to understand and quantify the variation in the error-rates and find that there is indeed significant variability in the error rates of the qubits and the links connecting them. We define reliability metrics for NISQ computers and show that the device variability has the substantial impact on the overall system reliability. To exploit the variability in error rate, we propose Variation-Aware Qubit Movement (VQM) and Variation-Aware Qubit Allocation (VQA), policies that optimize the movement and allocation of qubits to avoid the weaker qubits and links and guide more operations towards the stronger qubits and links. We show that our Variation-Aware policies improve the reliability of the NISQ system up to 2.5x.

Hyunseok Jeong