Related papers: Characterizing and optimizing qubit coherence based on SQUID geometry

Characterizing and optimizing qubit coherence based on SQUID geometry

URL: http://arxiv.org/abs/2002.09372v1
Date: Fri, 21 Feb 2020 15:59:52 GMT
Title: Characterizing and optimizing qubit coherence based on SQUID geometry
Authors: Jochen Braum\"uller, Leon Ding, Antti Veps\"al\"ainen, Youngkyu Sung, Morten Kjaergaard, Tim Menke, Roni Winik, David Kim, Bethany M. Niedzielski, Alexander Melville, Jonilyn L. Yoder, Cyrus F. Hirjibehedin, Terry P. Orlando, Simon Gustavsson, William D. Oliver
Abstract summary: The dominant source of decoherence in frequency-tunable superconducting qubits is 1/$f$ flux noise. We systematically study flux noise amplitudes in more than 50 flux qubits with varied SQUID geometry parameters. Our results and detailed model provide a guide for minimizing the flux noise susceptibility in future circuits.
Score: 41.85858790455642
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: The dominant source of decoherence in contemporary frequency-tunable superconducting qubits is 1/$f$ flux noise. To understand its origin and find ways to minimize its impact, we systematically study flux noise amplitudes in more than 50 flux qubits with varied SQUID geometry parameters and compare our results to a microscopic model of magnetic spin defects located at the interfaces surrounding the SQUID loops. Our data are in agreement with an extension of the previously proposed model, based on numerical simulations of the current distribution in the investigated SQUIDs. Our results and detailed model provide a guide for minimizing the flux noise susceptibility in future circuits.

Related papers

Straightness of Rectified Flow: A Theoretical Insight into Wasserstein Convergence [54.580605276017096]
Rectified Flow (RF) aims to learn straight flow trajectories from noise to data using a sequence of convex optimization problems. RF theoretically straightens the trajectory through successive rectifications, reducing the number of evaluations function (NFEs) while sampling. We provide the first theoretical analysis of the Wasserstein distance between the sampling distribution of RF and the target distribution.
arXiv Detail & Related papers (2024-10-19T02:36:11Z)
Mixed Noise and Posterior Estimation with Conditional DeepGEM [1.1650821883155187]
We develop a novel algorithm for jointly estimating the posterior and the noise parameters in inverse problems. We show that our model is able to incorporate information from many measurements, unlike previous approaches.
arXiv Detail & Related papers (2024-02-05T12:42:21Z)
Modelling non-Markovian noise in driven superconducting qubits [2.7648976108201815]
Non-Markovian noise can be a significant source of errors in superconducting qubits. We develop gate sequences that allow us to characterise and model the effects of non-Markovian noise on both idle and driven qubits.
arXiv Detail & Related papers (2023-06-22T16:30:29Z)
Tensor network reduced order models for wall-bounded flows [0.0]
We introduce a widely applicable tensor network-based framework for developing reduced order models. We consider the incompressible Navier-Stokes equations and the lid-driven cavity in two spatial dimensions.
arXiv Detail & Related papers (2023-03-06T10:33:00Z)
Optimal Algorithms for the Inhomogeneous Spiked Wigner Model [89.1371983413931]
We derive an approximate message-passing algorithm (AMP) for the inhomogeneous problem. We identify in particular the existence of a statistical-to-computational gap where known algorithms require a signal-to-noise ratio bigger than the information-theoretic threshold to perform better than random.
arXiv Detail & Related papers (2023-02-13T19:57:17Z)
Diffusion Posterior Sampling for General Noisy Inverse Problems [50.873313752797124]
We extend diffusion solvers to handle noisy (non)linear inverse problems via approximation of the posterior sampling. Our method demonstrates that diffusion models can incorporate various measurement noise statistics.
arXiv Detail & Related papers (2022-09-29T11:12:27Z)
Quantum precision limits of displacement noise free interferometers [12.14598582153305]
Current laser-interferometric gravitational wave detectors suffer from a fundamental limit to their precision due to displacement noise of optical elements. Several schemes for Displacement-Noise Free Interferometers (DFI) have been proposed to mitigate their effects. We derive quantum precision limits for general DFI schemes, including optimal measurement basis and optimal squeezing schemes.
arXiv Detail & Related papers (2022-09-07T08:51:31Z)
Physics-informed compressed sensing for PC-MRI: an inverse Navier-Stokes problem [78.20667552233989]
We formulate a physics-informed compressed sensing (PICS) method for the reconstruction of velocity fields from noisy and sparse magnetic resonance signals. We find that the method is capable of reconstructing and segmenting the velocity fields from sparsely-sampled signals.
arXiv Detail & Related papers (2022-07-04T14:51:59Z)
Reconstructing the Universe with Variational self-Boosted Sampling [7.922637707393503]
Traditional algorithms such as Hamiltonian Monte Carlo (HMC) are computationally inefficient due to generating correlated samples. Here we develop a hybrid scheme called variational self-boosted sampling (VBS) to mitigate the drawbacks of both algorithms. VBS generates better quality of samples than simple VI approaches and reduces the correlation length in the sampling phase by a factor of 10-50 over using only HMC.
arXiv Detail & Related papers (2022-06-28T21:30:32Z)
High-Order Qubit Dephasing at Sweet Spots by Non-Gaussian Fluctuators: Symmetry Breaking and Floquet Protection [55.41644538483948]
We study the qubit dephasing caused by the non-Gaussian fluctuators. We predict a symmetry-breaking effect that is unique to the non-Gaussian noise.
arXiv Detail & Related papers (2022-06-06T18:02:38Z)

This list is automatically generated from the titles and abstracts of the papers in this site.