scholarly journals Error mitigation on a near-term quantum photonic device

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 452
Author(s):  
Daiqin Su ◽  
Robert Israel ◽  
Kunal Sharma ◽  
Haoyu Qi ◽  
Ish Dhand ◽  
...  
Keyword(s):  
Measurement Data ◽  
Photonic Devices ◽  
Error Correction Codes ◽  
Post Processing ◽  
Sampling Device ◽  
Error Mitigation ◽  
Hardware Resource ◽  
Near Term ◽  
Moderate Cost ◽  
Photon Loss

Photon loss is destructive to the performance of quantum photonic devices and therefore suppressing the effects of photon loss is paramount to photonic quantum technologies. We present two schemes to mitigate the effects of photon loss for a Gaussian Boson Sampling device, in particular, to improve the estimation of the sampling probabilities. Instead of using error correction codes which are expensive in terms of their hardware resource overhead, our schemes require only a small amount of hardware modifications or even no modification. Our loss-suppression techniques rely either on collecting additional measurement data or on classical post-processing once the measurement data is obtained. We show that with a moderate cost of classical post processing, the effects of photon loss can be significantly suppressed for a certain amount of loss. The proposed schemes are thus a key enabler for applications of near-term photonic quantum devices.

scholarly journals Mitigation of readout noise in near-term quantum devices by classical post-processing based on detector tomography

Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 257 ◽  
Author(s):  
Filip B. Maciejewski ◽  
Zoltán Zimborás ◽  
Michał Oszmaniec
Keyword(s):  
Quantum Algorithms ◽  
Probability Distributions ◽  
Post Processing ◽  
Measurement Device ◽  
Quantum Devices ◽  
Quantum Process ◽  
Error Mitigation ◽  
Process Tomography ◽  
State Tomography ◽  
Near Term

We propose a simple scheme to reduce readout errors in experiments on quantum systems with finite number of measurement outcomes. Our method relies on performing classical post-processing which is preceded by Quantum Detector Tomography, i.e., the reconstruction of a Positive-Operator Valued Measure (POVM) describing the given quantum measurement device. If the measurement device is affected only by an invertible classical noise, it is possible to correct the outcome statistics of future experiments performed on the same device. To support the practical applicability of this scheme for near-term quantum devices, we characterize measurements implemented in IBM's and Rigetti's quantum processors. We find that for these devices, based on superconducting transmon qubits, classical noise is indeed the dominant source of readout errors. Moreover, we analyze the influence of the presence of coherent errors and finite statistics on the performance of our error-mitigation procedure. Applying our scheme on the IBM's 5-qubit device, we observe a significant improvement of the results of a number of single- and two-qubit tasks including Quantum State Tomography (QST), Quantum Process Tomography (QPT), the implementation of non-projective measurements, and certain quantum algorithms (Grover's search and the Bernstein-Vazirani algorithm). Finally, we present results showing improvement for the implementation of certain probability distributions in the case of five qubits.

scholarly journals Development of Urban Driving Cycle with GPS Data Post Processing

2016 ◽  
Vol 28 (4) ◽  
pp. 353-364 ◽  
Author(s):  
Peter Lipar ◽  
Irena Strnad ◽  
Martin Česnik ◽  
Tomaž Maher
Keyword(s):  
Data Collection ◽  
Urban Area ◽  
Measurement Data ◽  
Driving Cycle ◽  
Gps Data ◽  
Post Processing ◽  
The Difference ◽  
Large Random Sample ◽  
Representative Area ◽  
Development Methods

This paper presents GIS-based methodology for urban area driving cycle construction. The approach reaches beyond the frames of usual driving cycle development methods and takes into account another perspective of data collection. Rather than planning data collection, the approach is based on available in-vehicle measurement data post processing using Geographic Information Systems to manipulate the excessive database and extract only the representative and geographically limited individual trip data. With such data post processing the data was carefully adjusted to include only the data that describe representative driving in Ljubljana urban area. The selected method for the driving cycle development is based on searching for the best microtrips combination while minimizing the difference between two vectors; one based on generated cycle and the other on the database. Accounting for a large random sample of actual trip data, our approach enables more representative area-specific driving cycle development than the previously used techniques.

scholarly journals Error mitigation with Clifford quantum-circuit data

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 592
Author(s):  
Piotr Czarnik ◽  
Andrew Arrasmith ◽  
Patrick J. Coles ◽  
Lukasz Cincio
Keyword(s):  
State Energy ◽  
Quantum Computer ◽  
Quantum Circuit ◽  
Training Data ◽  
Quantum Circuits ◽  
Accurate Estimation ◽  
Error Mitigation ◽  
Order Of Magnitude ◽  
Quantum Observables ◽  
Near Term

Achieving near-term quantum advantage will require accurate estimation of quantum observables despite significant hardware noise. For this purpose, we propose a novel, scalable error-mitigation method that applies to gate-based quantum computers. The method generates training data {Xinoisy,Xiexact} via quantum circuits composed largely of Clifford gates, which can be efficiently simulated classically, where Xinoisy and Xiexact are noisy and noiseless observables respectively. Fitting a linear ansatz to this data then allows for the prediction of noise-free observables for arbitrary circuits. We analyze the performance of our method versus the number of qubits, circuit depth, and number of non-Clifford gates. We obtain an order-of-magnitude error reduction for a ground-state energy problem on 16 qubits in an IBMQ quantum computer and on a 64-qubit noisy simulator.

scholarly journals Amplitude estimation without phase estimation

2020 ◽  
Vol 19 (2) ◽  
Author(s):  
Yohichi Suzuki ◽  
Shumpei Uno ◽  
Rudy Raymond ◽  
Tomoki Tanaka ◽  
Tamiya Onodera ◽  
...  
Keyword(s):  
Measurement Data ◽  
Likelihood Estimation ◽  
Estimation Algorithm ◽  
Quantum Circuits ◽  
Phase Estimation ◽  
Amplitude Estimation ◽  
Quantum Amplitude ◽  
Phase Estimation Algorithm ◽  
Near Term ◽  
Quantum Speedup

AbstractThis paper focuses on the quantum amplitude estimation algorithm, which is a core subroutine in quantum computation for various applications. The conventional approach for amplitude estimation is to use the phase estimation algorithm, which consists of many controlled amplification operations followed by a quantum Fourier transform. However, the whole procedure is hard to implement with current and near-term quantum computers. In this paper, we propose a quantum amplitude estimation algorithm without the use of expensive controlled operations; the key idea is to utilize the maximum likelihood estimation based on the combined measurement data produced from quantum circuits with different numbers of amplitude amplification operations. Numerical simulations we conducted demonstrate that our algorithm asymptotically achieves nearly the optimal quantum speedup with a reasonable circuit length.

scholarly journals Algorithmic Error Mitigation Scheme for Current Quantum Processors

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 492
Author(s):  
Philippe Suchsland ◽  
Francesco Tacchino ◽  
Mark H. Fischer ◽  
Titus Neupert ◽  
Panagiotis Kl. Barkoutsos ◽  
...  
Keyword(s):  
Quantum Chemistry ◽  
Ground State ◽  
State Of The Art ◽  
Quantum Algorithms ◽  
Quantum Circuit ◽  
Lanczos Method ◽  
Error Mitigation ◽  
Near Term ◽  
The Impact ◽  
Different Sources

We present a hardware agnostic error mitigation algorithm for near term quantum processors inspired by the classical Lanczos method. This technique can reduce the impact of different sources of noise at the sole cost of an increase in the number of measurements to be performed on the target quantum circuit, without additional experimental overhead. We demonstrate through numerical simulations and experiments on IBM Quantum hardware that the proposed scheme significantly increases the accuracy of cost functions evaluations within the framework of variational quantum algorithms, thus leading to improved ground-state calculations for quantum chemistry and physics problems beyond state-of-the-art results.

scholarly journals INTERPRETATION OF STALL PRECURSOR SIGNATURES

2021 ◽  
pp. 1-15
Author(s):  
Christoph Brandstetter ◽  
Xavier Ottavy ◽  
Benoit Paoletti ◽  
Sina C Stapelfeldt
Keyword(s):  
Cross Correlation ◽  
Sensor Placement ◽  
Experimental Studies ◽  
Measurement Data ◽  
Post Processing ◽  
Correlation Methods ◽  
Stall Precursor ◽  
Processing Techniques ◽  
Highly Loaded ◽  
Spectral Averaging

Abstract A specific phenomenon that has been observed in many experimental studies on turbomachinery compressors and fans is discussed under the term ‘rotating instabilities’. It is associated to a local aerodynamic phenomenon, typically occurring in the tip region at highly loaded near stall conditions and often linked to blade vibrations. Even though the effect has been discussed over more than two decades, a very ambiguous interpretation still prevails. A particular problem is that certain signatures in measurement data are often considered to characterize the phenomenon despite possible misinterpretations. The present paper illustrates that a specific image of a pulsating disturbance that has been established in the 1990s needs to be reconsidered. At the example of a recent investigation on a composite fan the difficulties concerning sensor placement and post-processing techniques is discussed with a focus on spectral averaging, isolation of non-synchronous phenomena and multi-sensor cross-correlation methods.

scholarly journals Variational Quantum Computation of Excited States

Quantum ◽  
2019 ◽  
Vol 3 ◽  
pp. 156 ◽  
Author(s):  
Oscar Higgott ◽  
Daochen Wang ◽  
Stephen Brierley
Keyword(s):  
Excited State ◽  
Excited States ◽  
Quantum Algorithms ◽  
Reaction Rates ◽  
Mitigation Strategies ◽  
Quantum Computers ◽  
Error Mitigation ◽  
Near Term ◽  
Ground State Energies ◽  
High Depth

The calculation of excited state energies of electronic structure Hamiltonians has many important applications, such as the calculation of optical spectra and reaction rates. While low-depth quantum algorithms, such as the variational quantum eigenvalue solver (VQE), have been used to determine ground state energies, methods for calculating excited states currently involve the implementation of high-depth controlled-unitaries or a large number of additional samples. Here we show how overlap estimation can be used to deflate eigenstates once they are found, enabling the calculation of excited state energies and their degeneracies. We propose an implementation that requires the same number of qubits as VQE and at most twice the circuit depth. Our method is robust to control errors, is compatible with error-mitigation strategies and can be implemented on near-term quantum computers.

scholarly journals Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Zhenyu Cai
Keyword(s):  
Estimation Accuracy ◽  
Quantum Computers ◽  
Practical Application ◽  
Combined Method ◽  
Error Mitigation ◽  
Sampling Cost ◽  
Mitigation Techniques ◽  
Near Term ◽  
Quantum Error ◽  
Error Count

AbstractNoise in quantum hardware remains the biggest roadblock for the implementation of quantum computers. To fight the noise in the practical application of near-term quantum computers, instead of relying on quantum error correction which requires large qubit overhead, we turn to quantum error mitigation, in which we make use of extra measurements. Error extrapolation is an error mitigation technique that has been successfully implemented experimentally. Numerical simulation and heuristic arguments have indicated that exponential curves are effective for extrapolation in the large circuit limit with an expected circuit error count around unity. In this Article, we extend this to multi-exponential error extrapolation and provide more rigorous proof for its effectiveness under Pauli noise. This is further validated via our numerical simulations, showing orders of magnitude improvements in the estimation accuracy over single-exponential extrapolation. Moreover, we develop methods to combine error extrapolation with two other error mitigation techniques: quasi-probability and symmetry verification, through exploiting features of these individual techniques. As shown in our simulation, our combined method can achieve low estimation bias with a sampling cost multiple times smaller than quasi-probability while without needing to be able to adjust the hardware error rate as required in canonical error extrapolation.

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