Error analysis of optical quantum circuits consisting of multiple quantum gates

Anika Zaman

In this work, we present a Python framework designed to demonstrate various error types within quantum circuits through the utilization of probabilistic data obtained from quantum computers. The framework serves as a valuable tool for monitoring and mitigating errors across all stages of quantum circuits involving multiple qubits and gates. Leveraging the Harrow-Hassidim-Lloyd (HHL) quantum circuit, we conduct an analysis of errors on an IBM quantum computer and subsequently optimize the circuit. The paper introduces an automated methodology for computing single bit-flip errors and propagation errors, and gate errors offering insights into opportunities for mitigating errors in the context of the HHL quantum circuit.

Alex Neville

繁樹 竹内

Adrian Chapman, Steven T. Flammia

Fermionic averaged circuit eigenvalue sampling (FACES) is a protocol to simultaneously learn the averaged error rates of many fermionic linear optical (FLO) gates simultaneously and self-consistently from a suitable collection of FLO circuits. It is highly flexible, allowing for the in situ characterization of FLO-averaged gate-dependent noise under natural assumptions on a family of continuously parameterized one- and two-qubit gates. We rigorously show that our protocol has an efficient sampling complexity, owing in-part to useful properties of the Kravchuk transformations that feature in our analysis. We support our conclusions with numerical results. As FLO circuits become universal with access to certain resource states, we expect our results to inform noise characterization and error mitigation techniques on universal quantum computing architectures which naturally admit a fermionic description.

Till J. Weinhold, Jeremy L. O’Brien, Geoff J. Pryde +1 more

Kimihiro Saito

Optical quantum devices are promoting the development not only of communication but also of quantum computation using optical quantum gates. Here, we will explain how to replace circuits consisting of gates such as NOT, AND, etc. used in classical logic calculations with quantum calculation gates. These classical gates can be expressed as NOT and CNOT of quantum computing gates. We show how to express these quantum gates as optical devices using the behavior of the polarization of discrete photons. Next, we describe the backtracking method of quantum circuits utilizing the reversibility of quantum gates. Since classical gates are not unitary, we use probabilistic methods that rely on measurements. In a typical classical gate, there are multiple inputs corresponding to a certain output, so backtracking requires tracing multiple states. The quantum bit representation, which can represent superposition states, is suitable for this purpose. As an application example, we explain how to backtrack integer multipliers and perform factorization. In configuration using quantum gates, one measurement quantum bit is required for each element, resulting in a large number of state bits. However, by reusing bits that are no longer needed, it was possible to construct a circuit with a number of state bits proportional to the number of bits for the integer multiplicand. We simulated an integer multiplier circuit by combining classical gates, and backtrack the circuit to derive two factors from a composite number represented by quantum bits. We performed simulations on a PC and succeeded in factorizing a 100-bit composite number.