Mitigating depolarizing noise on quantum computers with noise-estimation
circuits
- URL: http://arxiv.org/abs/2103.08591v1
- Date: Mon, 15 Mar 2021 17:59:06 GMT
- Title: Mitigating depolarizing noise on quantum computers with noise-estimation
circuits
- Authors: Miroslav Urbanek, Benjamin Nachman, Vincent R. Pascuzzi, Andre He,
Christian W. Bauer, Wibe A. de Jong
- Abstract summary: We present a method to mitigate the depolarizing noise by first estimating its rate with a noise-estimation circuit.
We find that our approach in combination with readout-error correction, compiling, randomized, and zero-noise extrapolation produces results close to exact results even for circuits containing hundreds of CNOT gates.
- Score: 1.3375143521862154
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: A significant problem for current quantum computers is noise. While there are
many distinct noise channels, the depolarizing noise model often appropriately
describes average noise for large circuits involving many qubits and gates. We
present a method to mitigate the depolarizing noise by first estimating its
rate with a noise-estimation circuit and then correcting the output of the
target circuit using the estimated rate. The method is experimentally validated
on the simulation of the Heisenberg model. We find that our approach in
combination with readout-error correction, randomized compiling, and zero-noise
extrapolation produces results close to exact results even for circuits
containing hundreds of CNOT gates.
Related papers
- Optimized Noise Suppression for Quantum Circuits [0.40964539027092917]
Crosstalk noise is a severe error source in, e.g., cross-resonance based superconducting quantum processors.
Intrepid programming algorithm extends previous work on optimized qubit routing by swap insertion.
We evaluate the proposed method by characterizing crosstalk noise for two chips with up to 127 qubits.
arXiv Detail & Related papers (2024-01-12T07:34:59Z) - Fault-tolerant quantum architectures based on erasure qubits [49.227671756557946]
We exploit the idea of erasure qubits, relying on an efficient conversion of the dominant noise into erasures at known locations.
We propose and optimize QEC schemes based on erasure qubits and the recently-introduced Floquet codes.
Our results demonstrate that, despite being slightly more complex, QEC schemes based on erasure qubits can significantly outperform standard approaches.
arXiv Detail & Related papers (2023-12-21T17:40:18Z) - Accurate and Honest Approximation of Correlated Qubit Noise [39.58317527488534]
We propose an efficient systematic construction of approximate noise channels, where their accuracy can be enhanced by incorporating noise components with higher qubit-qubit correlation degree.
We find that, for realistic noise strength typical for fixed-frequency superconducting qubits, correlated noise beyond two-qubit correlation can significantly affect the code simulation accuracy.
arXiv Detail & Related papers (2023-11-15T19:00:34Z) - Emergence of noise-induced barren plateaus in arbitrary layered noise
models [44.99833362998488]
In variational quantum algorithms the parameters of a parameterized quantum circuit are optimized in order to minimize a cost function that encodes the solution of the problem.
We discuss how, and in which sense, the phenomenon of noise-induced barren plateaus emerges in parameterized quantum circuits with a layered noise model.
arXiv Detail & Related papers (2023-10-12T15:18:27Z) - Classical simulations of noisy variational quantum circuits [0.0]
Noisely affects quantum computations so that they not only become less accurate but also easier to simulate classically as systems scale up.
We construct a classical simulation algorithm, LOWESA, for estimating expectation values of noisy parameterised quantum circuits.
arXiv Detail & Related papers (2023-06-08T17:52:30Z) - Folding-Free ZNE: A Comprehensive Quantum Zero-Noise Extrapolation
Approach for Mitigating Depolarizing and Decoherence Noise [13.362818196498257]
A range of quantum error mitigation techniques has been proposed to address noise in quantum computers.
ZNE involves increasing the noise levels in a circuit and then using extrapolation to infer the zero noise case from the noisy results.
This paper presents a novel ZNE approach that does not require circuit folding or noise scaling to mitigate depolarizing and/or decoherence noise.
arXiv Detail & Related papers (2023-05-01T01:54:26Z) - Learning Noise via Dynamical Decoupling of Entangled Qubits [49.38020717064383]
Noise in entangled quantum systems is difficult to characterize due to many-body effects involving multiple degrees of freedom.
We develop and apply multi-qubit dynamical decoupling sequences that characterize noise that occurs during two-qubit gates.
arXiv Detail & Related papers (2022-01-26T20:22:38Z) - Numerical Simulations of Noisy Quantum Circuits for Computational
Chemistry [51.827942608832025]
Near-term quantum computers can calculate the ground-state properties of small molecules.
We show how the structure of the computational ansatz as well as the errors induced by device noise affect the calculation.
arXiv Detail & Related papers (2021-12-31T16:33:10Z) - Benchmarking near-term quantum computers via random circuit sampling [3.48887080077816]
We develop an algorithm that can sample-efficiently estimate the total amount of noise induced by a layer of arbitrary non-Clifford gates.
Our algorithm is inspired by Google's quantum supremacy experiment and is based on random circuit sampling.
arXiv Detail & Related papers (2021-05-11T17:49:16Z) - Efficient and robust certification of genuine multipartite entanglement
in noisy quantum error correction circuits [58.720142291102135]
We introduce a conditional witnessing technique to certify genuine multipartite entanglement (GME)
We prove that the detection of entanglement in a linear number of bipartitions by a number of measurements scales linearly, suffices to certify GME.
We apply our method to the noisy readout of stabilizer operators of the distance-three topological color code and its flag-based fault-tolerant version.
arXiv Detail & Related papers (2020-10-06T18:00:07Z) - A deep learning model for noise prediction on near-term quantum devices [137.6408511310322]
We train a convolutional neural network on experimental data from a quantum device to learn a hardware-specific noise model.
A compiler then uses the trained network as a noise predictor and inserts sequences of gates in circuits so as to minimize expected noise.
arXiv Detail & Related papers (2020-05-21T17:47:29Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.