Port-based teleportation under pure-dephasing decoherence
- URL: http://arxiv.org/abs/2602.16513v1
- Date: Wed, 18 Feb 2026 15:01:27 GMT
- Title: Port-based teleportation under pure-dephasing decoherence
- Authors: Rajendra S. Bhati, Michał Studziński, Jarosław K. Korbicz,
- Abstract summary: We study port based teleportation in the presence of noise affecting both the resource state and the measurement process.<n>We find that noise-adapted measurements perform worse than noiseless ones.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We study deterministic port based teleportation in the presence of noise affecting both the entangled resource state and the measurement process. We focus on a physically motivated model in which each Bell pair constituting the resource interacts with an identical local environment, corresponding to independently distributed entangled links. Two noisy scenarios are analyzed: one with decoherence acting solely on the resource state and ideal measurements, and another with noisy, noise adapted measurements optimised for the given noise model. In the first case, we derive an analytical lower bound and later a closed-form expression for the entanglement fidelity of the teleportation channel and analyze its asymptotic behaviour. In the second, we combine semi analytical and numerical methods. Surprisingly, we find that noise-adapted measurements perform worse than the noiseless ones. To connect the abstract noise description with microscopic physics, we embed the protocol in a spin boson model and investigate the influence of bath memory and temperature on the teleportation fidelity, highlighting qualitative differences between different environments.
Related papers
- Diffusion-Based Unsupervised Audio-Visual Speech Separation in Noisy Environments with Noise Prior [24.815262863931334]
We propose a generative unsupervised technique that models both clean speech and structured noise components.<n>Our approach leverages an audio-visual score model that incorporates visual cues to serve as a strong generative speech prior.<n> Experimental results demonstrate promising performance, highlighting the effectiveness of our direct noise modelling approach.
arXiv Detail & Related papers (2025-09-17T19:25:35Z) - InJecteD: Analyzing Trajectories and Drift Dynamics in Denoising Diffusion Probabilistic Models for 2D Point Cloud Generation [48.55037712252843]
InJecteD is a framework for interpreting Denoising Diffusion Probabilistic Models (DDPMs)<n>We apply this framework to three datasets from the Datasaurus Dozen bullseye, dino, and circle.<n>Our approach quantifies trajectory properties, including displacement, velocity, clustering, and drift field dynamics.
arXiv Detail & Related papers (2025-09-09T14:53:19Z) - Entanglement sharing across a damping-dephasing channel [2.249916681499244]
Entment distillation is a fundamental information processing task.<n>Noise experienced by quantum communication and computing platforms occurs not only in the form of Pauli noise but also non-Pauli noise.<n>We propose a distillation scheme that completely isolates away the damping noise.
arXiv Detail & Related papers (2024-05-10T03:51:40Z) - Stochastic action for the entanglement of a noisy monitored two-qubit
system [55.2480439325792]
We study the effect of local unitary noise on the entanglement evolution of a two-qubit system subject to local monitoring and inter-qubit coupling.
We construct a Hamiltonian by incorporating the noise into the Chantasri-Dressel-Jordan path integral and use it to identify the optimal entanglement dynamics.
Numerical investigation of long-time steady-state entanglement reveals a non-monotonic relationship between concurrence and noise strength.
arXiv Detail & Related papers (2024-03-13T11:14:10Z) - Coherent interaction-free detection of noise [0.0]
We propose interaction-free measurements as a noise-detection technique.
We explore two conceptually different schemes: the coherent and the projective realizations.
We study the signature of noise correlations in the detector's signal.
arXiv Detail & Related papers (2023-12-28T18:24:13Z) - Negative Pre-aware for Noisy Cross-modal Matching [46.5591267410225]
Cross-modal noise-robust learning is a challenging task since noisy correspondence is hard to recognize and rectify.
We present a novel Negative Pre-aware Cross-modal matching solution for large visual-language model fine-tuning on noisy downstream tasks.
arXiv Detail & Related papers (2023-12-10T05:52:36Z) - Probing flux and charge noise with macroscopic resonant tunneling [45.36850110238202]
We measure rates of incoherent tunneling from the lowest energy state in the initial well to the ground.
We develop a theoretical model that allows us to extract information about flux and charge noise within one experimental setup.
arXiv Detail & Related papers (2022-10-04T16:15:34Z) - A Study on Robustness to Perturbations for Representations of
Environmental Sound [16.361059909912758]
We evaluate two embeddings -- YAMNet, and OpenL$3$ on monophonic (UrbanSound8K) and polyphonic (SONYC UST) datasets.
We imitate channel effects by injecting perturbations to the audio signal and measure the shift in the new embeddings with three distance measures.
arXiv Detail & Related papers (2022-03-20T01:04:38Z) - Joint Direction and Proximity Classification of Overlapping Sound Events
from Binaural Audio [7.050270263489538]
We aim to investigate several ways of performing joint proximity and direction estimation from recordings.
Considering the limitations of audio, we propose two methods of splitting the sphere into angular areas in order to obtain a set of directional classes.
We propose various ways of combining the proximity and direction estimation problems into a joint task providing temporal information about the onsets and offsets of appearing sources.
arXiv Detail & Related papers (2021-07-26T08:48:46Z) - Adaptive Multi-View ICA: Estimation of noise levels for optimal
inference [65.94843987207445]
Adaptive multiView ICA (AVICA) is a noisy ICA model where each view is a linear mixture of shared independent sources with additive noise on the sources.
On synthetic data, AVICA yields better sources estimates than other group ICA methods thanks to its explicit MMSE estimator.
On real magnetoencephalograpy (MEG) data, we provide evidence that the decomposition is less sensitive to sampling noise and that the noise variance estimates are biologically plausible.
arXiv Detail & Related papers (2021-02-22T13:10:12Z) - Leveraging Global Parameters for Flow-based Neural Posterior Estimation [90.21090932619695]
Inferring the parameters of a model based on experimental observations is central to the scientific method.
A particularly challenging setting is when the model is strongly indeterminate, i.e., when distinct sets of parameters yield identical observations.
We present a method for cracking such indeterminacy by exploiting additional information conveyed by an auxiliary set of observations sharing global parameters.
arXiv Detail & Related papers (2021-02-12T12:23:13Z) - Quantum limits of superresolution in a noisy environment [2.3339135709418817]
We analyze the ultimate quantum limit of resolving two identical sources in a noisy environment.
Noisy cases contrast with a noiseless case where it has been shown to be nonzero for a small distance.
We show that false excitation on an arbitrary measurement, such as dark counts, also makes the classical Fisher information of the measurement approach to zero.
arXiv Detail & Related papers (2020-08-26T02:09:55Z) - Hamiltonian Dynamics for Real-World Shape Interpolation [66.47407593823208]
We revisit the classical problem of 3D shape and propose a novel, physically plausible approach based on Hamiltonian dynamics.
Our method yields exactly volume preserving intermediate shapes, avoids self-intersections and is scalable to high resolution scans.
arXiv Detail & Related papers (2020-04-10T18:38:52Z)
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.