Coincidence postselection for genuine multipartite nonlocality: Causal diagrams and threshold efficiencies

• URL: http://arxiv.org/abs/2207.13579v2
• Date: Wed, 21 Dec 2022 11:30:38 GMT
• Title: Coincidence postselection for genuine multipartite nonlocality: Causal diagrams and threshold efficiencies
• Authors: Valentin Gebhart and Augusto Smerzi
• Abstract summary: We show how to close the detection loophole for a coincidence detection in demonstrations of nonlocality and GMN. Our results imply that genuine $N$-partite nonlocality can be generated from $N$ independent particle sources even when allowing for non-ideal detectors.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Genuine multipartite nonlocality (GMN), the strongest form of multipartite nonlocality that describes fully collective nonlocal correlations among all experimental parties, can be observed when different distant parties each locally measure a particle from a shared entangled many-particle state. For the demonstration of GMN, the experimentally observed statistics are typically postselected: Events for which some parties do not detect a particle must be discarded. This coincidence postselection generally leads to the detection loophole that invalidates a proper nonlocality demonstration. In this work, we address how to close the detection loophole for a coincidence detection in demonstrations of nonlocality and GMN. We first show that if the number of detected particles is conserved, i.e., using ideal and noiseless experimental devices, one can employ causal diagrams and the no-signalling principle to prove that a coincidence postselection cannot create any detection loophole. Furthermore, for realistic experimental devices with finite detection efficiencies, we show how a general Bell inequality can be sharpened such that its new version is still valid after a postselection of the measurement data. In this case, there are threshold detection efficiencies that, if surpassed in the experiment, lead to the possibility to demonstrate nonlocality and GMN without opening the detection loophole. Our results imply that genuine $N$-partite nonlocality can be generated from $N$ independent particle sources even when allowing for non-ideal detectors.

Related papers

• Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection [63.93728560200819]
  Unsupervised out-of-distribution (U-OOD) detection is to identify data samples with a detector trained solely on unlabeled in-distribution (ID) data. Recent studies have developed various detectors based on DGMs to move beyond likelihood. We apply two techniques for each direction, specifically post-hoc prior and dataset entropy-mutual calibration. Experimental results demonstrate that the Resultant could be a new state-of-the-art U-OOD detector.
  arXiv  Detail & Related papers  (2024-09-05T02:58:13Z)
• To Believe or Not to Believe Your LLM [51.2579827761899]
  We explore uncertainty quantification in large language models (LLMs) We derive an information-theoretic metric that allows to reliably detect when only epistemic uncertainty is large. We conduct a series of experiments which demonstrate the advantage of our formulation.
  arXiv  Detail & Related papers  (2024-06-04T17:58:18Z)
• MSFlow: Multi-Scale Flow-based Framework for Unsupervised Anomaly Detection [124.52227588930543]
  Unsupervised anomaly detection (UAD) attracts a lot of research interest and drives widespread applications. An inconspicuous yet powerful statistics model, the normalizing flows, is appropriate for anomaly detection and localization in an unsupervised fashion. We propose a novel Multi-Scale Flow-based framework dubbed MSFlow composed of asymmetrical parallel flows followed by a fusion flow. Our MSFlow achieves a new state-of-the-art with a detection AUORC score of up to 99.7%, localization AUCROC score of 98.8%, and PRO score of 97.1%.
  arXiv  Detail & Related papers  (2023-08-29T13:38:35Z)
• On detection statistics in double-double-slit experiment [0.0]
  We analyze the statistics of detection data in a general double-double-slit experiment. The main result is the joint distribution of detection data including the arrival time and position of the particles on left and right screens.
  arXiv  Detail & Related papers  (2022-08-02T09:19:29Z)
• Experimental demonstration of genuine tripartite nonlocality under strict locality conditions [16.812051020169257]
  Nonlocality captures one of the counterintuitive features of nature that defies classical intuition. Recent investigations reveal that our physical world's nonlocality is at least tripartite. We experimentally demonstrate such genuine tripartite nonlocality in a network under strict locality constraints.
  arXiv  Detail & Related papers  (2022-03-02T06:08:19Z)
• Provable RL with Exogenous Distractors via Multistep Inverse Dynamics [85.52408288789164]
  Real-world applications of reinforcement learning (RL) require the agent to deal with high-dimensional observations such as those generated from a megapixel camera. Prior work has addressed such problems with representation learning, through which the agent can provably extract endogenous, latent state information from raw observations. However, such approaches can fail in the presence of temporally correlated noise in the observations.
  arXiv  Detail & Related papers  (2021-10-17T15:21:27Z)
• Observation-dependent suppression and enhancement of two-photon coincidences by tailored losses [68.8204255655161]
  Hong-Ou-Mandel (HOM) effect can lead to a perfect suppression of two-particle coincidences between the output ports of a balanced beam splitter. In this work, we demonstrate experimentally that the two-particle coincidence statistics of two bosons can instead be seamlessly tuned to substantial enhancement. Our findings reveal a new approach to harnessing non-Hermitian settings for the manipulation of multi-particle quantum states.
  arXiv  Detail & Related papers  (2021-05-12T06:47:35Z)
• A local hidden-variable model for experimental tests of the GHZ puzzle [0.0]
  This paper describes a physically motivated local hidden-variable model based on amplitude-threshold detection. A curious emergent feature of the model is that detection efficiencies may depend upon which observables are chosen for measurement.
  arXiv  Detail & Related papers  (2021-04-27T20:48:16Z)
• Genuine multipartite nonlocality with causal-diagram postselection [0.0]
  We establish conditions under which GMN is demonstrable even if observations are postselected collectively. Results are derived using the causal structure of the experiment and the no-signalling condition imposed by relativity.
  arXiv  Detail & Related papers  (2021-04-20T15:46:50Z)
• Experimentally friendly approach towards nonlocal correlations in multisetting N -partite Bell scenarios [0.0]
  We study a recently proposed operational measure of nonlocality by Fonseca and Parisio[Phys. A 92, 03(R)] which describes the probability of violation of local realism under randomly sampled observables. We show that even with both a randomly chosen $N$-qubit pure state and randomly chosen measurement bases, a violation of local realism can be detected experimentally almost $100%$ of the time.
  arXiv  Detail & Related papers  (2020-09-24T13:54:44Z)
• Using Randomness to decide among Locality, Realism and Ergodicity [91.3755431537592]
  An experiment is proposed to find out, or at least to get an indication about, which one is false. The results of such experiment would be important not only to the foundations of Quantum Mechanics.
  arXiv  Detail & Related papers  (2020-01-06T19:26:32Z)

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.