Entanglement-enhanced optomechanical sensor array for dark matter searches

• URL: http://arxiv.org/abs/2210.07291v2
• Date: Wed, 7 Dec 2022 05:19:28 GMT
• Title: Entanglement-enhanced optomechanical sensor array for dark matter searches
• Authors: Anthony J. Brady, Xin Chen, Kewen Xiao, Yi Xia, Jack Manley, Mitul Dey Chowdhury, Zhen Liu, Roni Harnik, Dalziel J. Wilson, Zheshen Zhang and Quntao Zhuang
• Abstract summary: Mechanical sensors are one of the leading candidates for dark matter searches in the low frequency region. We propose entanglement-enhanced optomechanical sensing systems to assist the search for DM with mechanical sensing devices.
• Score: 3.690597210878011
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The nature of dark matter is one of the most important open questions in modern physics. The search for dark matter is challenging since, besides gravitational interaction, it feebly interacts with ordinary matter. Mechanical sensors are one of the leading candidates for dark matter searches in the low frequency region. Here, we propose entanglement-enhanced optomechanical sensing systems to assist the search for DM with mechanical sensing devices. To assess the performance of our setup, we adopt the integrated sensitivity, which is particularly suitable for broadband sensing as it precisely quantifies the bandwidth-sensitivity tradeoff of the system. We then show that, by coherently operating the optomechanical sensor array and utilizing continuous-variable multi-partite entanglement between the optical fields, the array of sensors has a scaling advantage over independent sensors (i.e., $\sqrt{M}\rightarrow M$, where $M$ is the number of sensors) as well as a performance boost due to entanglement. Such an advantage is robust to imhomogeneities of the mechanical sensors and is achievable with off-the-shelf experimental components.

Related papers

• Mechanical Sensors for Ultraheavy Dark Matter Searches via Long-range Forces [0.0]
  We explore the pathway towards searching for dark matter candidates with masses around the Planck-scale using mechanical sensors. These dark matter particles are expected to leave tracks as their signature in mechanical sensor arrays. We show that we can effectively search for such tracks using statistical approaches to track-finding.
  arXiv  Detail & Related papers  (2025-03-14T17:59:03Z)
• Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving Scenes [56.52618054240197]
  We propose a novel, condition-aware multimodal fusion approach for robust semantic perception of driving scenes. Our method, CAFuser, uses an RGB camera input to classify environmental conditions and generate a Condition Token that guides the fusion of multiple sensor modalities. We set the new state of the art with CAFuser on the MUSES dataset with 59.7 PQ for multimodal panoptic segmentation and 78.2 mIoU for semantic segmentation, ranking first on the public benchmarks.
  arXiv  Detail & Related papers  (2024-10-14T17:56:20Z)
• Parametrically enhancing sensor sensitivity at an exceptional point [0.0]
  We propose a scheme to enhance the sensitivity of Non-Hermitian optomechanical mass-sensors. The sensitivity of both sensing schemes is greatly improved, yielding to a better performance of the sensor.
  arXiv  Detail & Related papers  (2023-12-08T14:25:18Z)
• Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor [58.305341034419136]
  We present the first dense SLAM system with a monocular camera and a light-weight ToF sensor. We propose a multi-modal implicit scene representation that supports rendering both the signals from the RGB camera and light-weight ToF sensor. Experiments demonstrate that our system well exploits the signals of light-weight ToF sensors and achieves competitive results.
  arXiv  Detail & Related papers  (2023-08-28T07:56:13Z)
• Fundamental sensitivity limit of lossy cavity-enhanced interferometers with external and internal squeezing [0.0]
  Gravitational-wave detectors have been very successful in implementing cavities and quantum squeezed light for enhancing sensitivity to signals from black hole or neutron star mergers. Here, we derive the fundamental sensitivity limit of cavity and squeezed-light enhanced interferometers with optical loss. We demonstrate the application of internal squeezing to various scenarios and confirm that it indeed allows to reach the best sensitivity in cavity and squeezed-light enhanced linear force sensors.
  arXiv  Detail & Related papers  (2023-07-18T10:27:39Z)
• UltraGlove: Hand Pose Estimation with Mems-Ultrasonic Sensors [14.257535961674021]
  We propose a novel and low-cost hand-tracking glove that utilizes several MEMS-ultrasonic sensors attached to the fingers. Our experimental results demonstrate that this approach is both accurate, size-agnostic, and robust to external interference.
  arXiv  Detail & Related papers  (2023-06-22T03:41:47Z)
• Tactile-Filter: Interactive Tactile Perception for Part Mating [54.46221808805662]
  Humans rely on touch and tactile sensing for a lot of dexterous manipulation tasks. vision-based tactile sensors are being widely used for various robotic perception and control tasks. We present a method for interactive perception using vision-based tactile sensors for a part mating task.
  arXiv  Detail & Related papers  (2023-03-10T16:27:37Z)
• Entanglement-Enhanced Optomechanical Sensing [2.152481479747191]
  Optomechanical systems have been exploited in ultrasensitive measurements of force, acceleration, and magnetic fields. We show that joint force measurements taken with entangled probes on multiple optomechanical sensors can improve the bandwidth in the thermal-noise-dominant regime. The demonstrated entanglement-enhanced optomechanical sensing could enable new capabilities for inertial navigation, acoustic imaging, and searches for new physics.
  arXiv  Detail & Related papers  (2022-10-28T14:51:16Z)
• DC Quantum Magnetometry Below the Ramsey Limit [68.8204255655161]
  We demonstrate quantum sensing of dc magnetic fields that exceeds the sensitivity of conventional $Tast$-limited dc magnetometry by more than an order of magnitude. We used nitrogen-vacancy centers in a diamond rotating at periods comparable to the spin coherence time, and characterize the dependence of magnetic sensitivity on measurement time and rotation speed.
  arXiv  Detail & Related papers  (2022-03-27T07:32:53Z)
• Fiberized diamond-based vector magnetometers [0.0]
  We present two fiberized vector magnetic-field sensors based on nitrogen-vacancy centers in diamond. The sensors feature sub-nT/$sqrttextrmHz$ magnetic sensitivity.
  arXiv  Detail & Related papers  (2021-02-23T19:26:57Z)
• Learning Camera Miscalibration Detection [83.38916296044394]
  This paper focuses on a data-driven approach to learn the detection of miscalibration in vision sensors, specifically RGB cameras. Our contributions include a proposed miscalibration metric for RGB cameras and a novel semi-synthetic dataset generation pipeline based on this metric. By training a deep convolutional neural network, we demonstrate the effectiveness of our pipeline to identify whether a recalibration of the camera's intrinsic parameters is required or not.
  arXiv  Detail & Related papers  (2020-05-24T10:32:49Z)
• OmniTact: A Multi-Directional High Resolution Touch Sensor [109.28703530853542]
  Existing tactile sensors are either flat, have small sensitive fields or only provide low-resolution signals. We introduce OmniTact, a multi-directional high-resolution tactile sensor. We evaluate the capabilities of OmniTact on a challenging robotic control task.
  arXiv  Detail & Related papers  (2020-03-16T01:31:29Z)

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.