Gleipnir: Toward Practical Error Analysis for Quantum Programs (Extended Version)
arXiv:2104.06349
Abstract
Practical error analysis is essential for the design, optimization, and evaluation of Noisy Intermediate-Scale Quantum(NISQ) computing. However, bounding errors in quantum programs is a grand challenge, because the effects of quantum errors depend on exponentially large quantum states. In this work, we present Gleipnir, a novel methodology toward practically computing verified error bounds in quantum programs. Gleipnir introduces the -diamond norm, an error metric constrained by a quantum predicate consisting of the approximate state and its distance to the ideal state . This predicate can be computed adaptively using tensor networks based on the Matrix Product States. Gleipnir features a lightweight logic for reasoning about error bounds in noisy quantum programs, based on the -diamond norm metric. Our experimental results show that Gleipnir is able to efficiently generate tight error bounds for real-world quantum programs with 10 to 100 qubits, and can be used to evaluate the error mitigation performance of quantum compiler transformations.
arXiv commenttypos corrected
References in corpus (33)
- Quantum Computing in the NISQ era and beyond
- Quantum secret sharing
- The density-matrix renormalization group
- Surface codes: Towards practical large-scale quantum computation
- Efficient classical simulation of slightly entangled quantum computations
- Matrix Product States, Projected Entangled Pair States, and variational renormalization group methods for quantum spin systems
- A Quantum Approximate Optimization Algorithm
- Quantum Coherence as a Resource
- Quantum Computing with Very Noisy Devices
- Reliable Quantum Computers
- Operational Resource Theory of Coherence
- A class of quantum many-body states that can be efficiently simulated
- Quantum Error Correction for Beginners
- Classical simulation of infinite-size quantum lattice systems in two spatial dimensions
- Roads towards fault-tolerant universal quantum computation
- Noise tailoring for scalable quantum computation via randomized compiling
- The Resource Theory of Stabilizer Computation
- Positive Wigner functions render classical simulation of quantum computation efficient
- Application of a resource theory for magic states to fault-tolerant quantum computing
- Algorithms for entanglement renormalization
- Randomized Benchmarking with Confidence
- ScaffCC: Scalable Compilation and Analysis of Quantum Programs
- A Verified Optimizer for Quantum Circuits
- Quantum MERA Channels
- On quantum non-signalling boxes
- Phase space simulation method for quantum computation with magic states on qubits
- TensorNetwork for Machine Learning
- Errors and pseudo-thresholds for incoherent and coherent noise
- Approximation of real error channels by Clifford channels and Pauli measurements
- From estimation of quantum probabilities to simulation of quantum circuits
- Comparing the Overhead of Topological and Concatenated Quantum Error Correction
- Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers
- CertiQ: A Mostly-automated Verification of a Realistic Quantum Compiler