Scalable noisy quantum circuits for biased-noise qubits
- URL: http://arxiv.org/abs/2305.02045v4
- Date: Mon, 8 Jan 2024 16:11:25 GMT
- Title: Scalable noisy quantum circuits for biased-noise qubits
- Authors: Marco Fellous-Asiani, Moein Naseri, Chandan Datta, Alexander
Streltsov, Micha{\l} Oszmaniec
- Abstract summary: We consider biased-noise qubits affected only by bit-flip errors, which is motivated by existing systems of stabilized cat qubits.
For realistic noise models, phase-flip will not be negligible, but in the Pauli-Twirling approximation, we show that our benchmark could check the correctness of circuits containing up to $106$ gates.
- Score: 41.78224056793453
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: In this work, we consider biased-noise qubits affected only by bit-flip
errors, which is motivated by existing systems of stabilized cat qubits. This
property allows us to design a class of noisy Hadamard-tests involving
entangling and certain non-Clifford gates, which can be conducted reliably with
only a polynomial overhead in algorithm repetitions. On the flip side we also
found classical algorithms able to efficiently simulate both the noisy and
noiseless versions of our specific variants of Hadamard test. We propose to use
these algorithms as a simple benchmark of the biasness of the noise at the
scale of large circuits. The bias being checked on a full computational task,
it makes our benchmark sensitive to crosstalk or time-correlated errors, which
are usually invisible from individual gate tomography. For realistic noise
models, phase-flip will not be negligible, but in the Pauli-Twirling
approximation, we show that our benchmark could check the correctness of
circuits containing up to $10^6$ gates, several orders of magnitudes larger
than circuits not exploiting a noise-bias. Our benchmark is applicable for an
arbitrary noise-bias, beyond Pauli models.
Related papers
- Practical implementation of a single-qubit rotation algorithm [0.0]
The Toffoli is an important universal quantum gate, and will alongside the Clifford gates be available in future Fault-Tolerant Quantum Computing hardware.
We evaluate the performance of a recently proposed single-qubit rotation algorithm using the Clifford+Toffoli gate set.
arXiv Detail & Related papers (2024-10-24T13:53:21Z) - 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) - Can shallow quantum circuits scramble local noise into global white
noise? [0.0]
Shallow quantum circuits are believed to be the most promising candidates for achieving early practical quantum advantage.
We investigate what degree practical shallow quantum circuits scramble local noise into global white noise.
We find in all cases that the commutator norm is sufficiently small guaranteeing a very good performance of purification-based error mitigation.
arXiv Detail & Related papers (2023-02-02T05:10:14Z) - Quantum error correction with dissipatively stabilized squeezed cat
qubits [68.8204255655161]
We propose and analyze the error correction performance of a dissipatively stabilized squeezed cat qubit.
We find that for moderate squeezing the bit-flip error rate gets significantly reduced in comparison with the ordinary cat qubit while leaving the phase flip rate unchanged.
arXiv Detail & Related papers (2022-10-24T16:02:20Z) - Quantum Goemans-Williamson Algorithm with the Hadamard Test and
Approximate Amplitude Constraints [62.72309460291971]
We introduce a variational quantum algorithm for Goemans-Williamson algorithm that uses only $n+1$ qubits.
Efficient optimization is achieved by encoding the objective matrix as a properly parameterized unitary conditioned on an auxilary qubit.
We demonstrate the effectiveness of our protocol by devising an efficient quantum implementation of the Goemans-Williamson algorithm for various NP-hard problems.
arXiv Detail & Related papers (2022-06-30T03:15:23Z) - 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) - Mitigating depolarizing noise on quantum computers with noise-estimation
circuits [1.3375143521862154]
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.
arXiv Detail & Related papers (2021-03-15T17:59:06Z) - Learning based signal detection for MIMO systems with unknown noise
statistics [84.02122699723536]
This paper aims to devise a generalized maximum likelihood (ML) estimator to robustly detect signals with unknown noise statistics.
In practice, there is little or even no statistical knowledge on the system noise, which in many cases is non-Gaussian, impulsive and not analyzable.
Our framework is driven by an unsupervised learning approach, where only the noise samples are required.
arXiv Detail & Related papers (2021-01-21T04:48:15Z) - 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.