# Cross-verification of independent quantum devices

@article{Greganti2019CrossverificationOI, title={Cross-verification of independent quantum devices}, author={C. Greganti and Tommaso F. Demarie and Martin Ringbauer and J A Jones and Valeria Saggio and I. Alonso Calafell and Lee A. Rozema and Alexander Erhard and Michael Meth and Lukas Postler and Roman Stricker and Philipp Schindler and R Blatt and Thomas Monz and Philip Walther and Joseph Fitzsimons}, journal={2021 Conference on Lasers and Electro-Optics Europe \& European Quantum Electronics Conference (CLEO/Europe-EQEC)}, year={2019}, pages={1-1} }

Today’s intermediate-scale quantum devices are on the brink of outperforming their classical counterparts. Yet these devices remain noisy, and with no trusted classical computers to check their results, we are left with a dire need to verify that they indeed perform as intended. The standard approach to this problem is to benchmark the performance of the individual building blocks using techniques such as quantum process tomography or randomized benchmarking and then extrapolate to the full…

## 9 Citations

### Cross-platform comparison of arbitrary quantum states

- Computer ScienceNature Communications
- 2022

A cross-platform QC comparison using randomized and correlated measurements that results in a wealth of information on the QC systems that allow for scaling to larger systems as compared to full quantum state tomography.

### Distributed Quantum inner product estimation

- Computer ScienceSTOC
- 2022

The sample complexity of the cross-platform verification task, which involves two players Alice and Bob who have k copies of unknown states ρ,σ, is settled, showing that the success achieved by shadow tomography, for sample-efficiently learning the properties of a single system, cannot be generalized to the distributed setting.

### Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack

- Computer ScienceQuantum
- 2021

3 "application-motivated" circuit classes for benchmarking are proposed, showing that noise-aware compilation strategies may be beneficial, and that device connectivity and noise levels play a crucial role in the performance of the system according to the authors' benchmarks.

### A compiler for universal photonic quantum computers

- Physics, Computer Science2022 IEEE/ACM Third International Workshop on Quantum Computing Software (QCS)
- 2022

A pipeline to convert a QASM circuit into a graph representation named measurement-graph (m-graph), that can be directly translated to hardware instructions on an optical one-way quantum computer, and optimize the graph using ZX-Calculus before evaluating the execution on an experimental discrete variable photonic platform.

### Practical verification protocols for analog quantum simulators

- Physics, Computer Sciencenpj Quantum Information
- 2020

A set of experimentally-motivated verification protocols for analog quantum simulators are introduced, discussing their sensitivity to a variety of error sources and their scalability to larger system sizes.

### Quantum information processing with mixed-species ion crystals

- Physics
- 2020

Trapped ions are among the leading platforms for the realization of scalable quantum information processing (QIP). A hybrid system composed of different species of ions extends the control…

### Towards experimental classical verification of quantum computation

- Physics
- 2022

Roman Stricker,1 Jose Carrasco,2 Martin Ringbauer,1 Lukas Postler,1 Michael Meth,1 Claire Edmunds,1 Philipp Schindler,1 Rainer Blatt,1, 3 Peter Zoller,2, 3 Barbara Kraus,2 and Thomas Monz1, 4…

### Near-deterministic hybrid generation of arbitrary photonic graph states using a single quantum emitter and linear optics

- Physics, Computer Science
- 2022

Heralded entanglement between solid-state qubits separated by three metres shows good contact between the qubits.

### Intelligent certification for quantum simulators via machine learning

- Computer Sciencenpj Quantum Information
- 2022

This work proposes Ab initio end-to-end machine learning certification protocol briefly named MLCP, which paves the way for large-scale intelligent certification of quantum simulators and can be extended onto an artificial intelligence center to offer easily accessible services for local quantumSimulation in the noisy intermediate-size quantum (NISQ) era.

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