VERITAS: Accurately Estimating the Correct Output on Noisy Intermediate-Scale Quantum Computers
Tirthak Patel, Devesh Tiwari
Abstract
Noisy Intermediate-Scale Quantum (NISQ) machines are being increasingly used to develop quantum algorithms and establish use cases for quantum computing. However, these devices are highly error-prone and produce output, which can be far from the correct output of the quantum algorithm. In this paper, we propose VERITAS, an end-to-end approach toward designing quantum experiments, executing experiments, and correcting outputs produced by quantum circuits post their execution such that the correct output of the quantum algorithm can be accurately estimated.
Topics & Concepts
Computer scienceQuantum computerQuantumScale (ratio)Quantum error correctionQuantum algorithmAlgorithmQuantum circuitComputer engineeringTheoretical computer sciencePhysicsQuantum mechanicsQuantum Computing Algorithms and ArchitectureQuantum Information and CryptographyQuantum-Dot Cellular Automata