arXiv subjects

Gaganpreet Singh

Publications and source records attributed to Gaganpreet Singh.

8 recordsLinked to original sources

arXiv2026

Design of ALPHA Phase I: A Plasma Haloscope for 10--20 GHz Post-Inflation Axions

The axion is a well-motivated hypothetical particle capable of resolving both the strong CP problem and the dark matter mystery, with recent post-inflationary cosmological simulations favoring masses above 40 μeV. Plasma haloscopes serve as a promising experimental approach to reach theoretically preferred sensitivities in this mass range. ALPHA, hosted at Yale Wright Laboratory, is an international collaboration developing plasma haloscopes to search for QCD dark matter axions. In this letter we present the detailed design and sensitivity projection for the first phase of the ALPHA experiment, which will search the mass range from 10 GHz to 20 GHz (~40 μeV to 80 μeV). This search will make use of wire-array plasma resonators to decouple the physical size from the resonant frequency, a limitation typically faced by traditional microwave cavities, allowing broadband sensitivity approaching KSVZ coupling strengths.

hep-ex↗

arXiv2025

Optimizing broadband microwave absorbers for applications in the 70-200 GHz range

We present results of an extensive suite of numerical simulations that probe square-tiled microwave absorber performance as a function of material properties, frequency, geometry, and unit cell size. The work, which probes both specular reflection and total absorption, highlights the critical importance of the absorber scale size relative to the incidence wavelength while suggesting that material properties have a comparatively weaker impact on overall performance. We show that some absorber designs can achieve 99.5-99.9% frequency-averaged absorption across the 70 to 200 GHz range for normal incidence and that low specular reflectance does not necessarily guarantee optimal absorption performance. Our results indicate that exponential, Klopfenstein, and linear impedance tapers provide comparable performance as long as a unit cell size of 1 to 4 mm is chosen. Simulation results are validated against measurements of specular reflectance.

astro-ph.IM↗

arXiv2025

Spiral Tuning of Wire-metamaterial Cavity for Plasma Haloscope

Axions are hypothetical particles that provide a compelling solution to two major mysteries in modern physics: the strong CP problem and the nature of dark matter. The plasma haloscope has been proposed as a promising approach for probing the higher-mass regime for dark matter axions by employing a periodic arrangement of conducting wires. In this work, we introduce a novel tuning mechanism for such wire-based structures by arranging the wires into a spiral configuration. This design enables continuous frequency tuning of 25% with a single central rotation while maintaining the form factor. It also achieves scanning speeds several times faster than traditional tuning approaches, primarily due to the circular perimeter geometry, making it well suited for solenoidal magnet bores. To validate the concept, we fabricated a prototype cavity with six spiral arms and experimentally demonstrated its feasibility, obtaining frequency tuning in close agreement with numerical simulations.

hep-ex↗

arXiv2025

Tunable Epsilon Near Zero Metamaterial with Rotating Obround-Shaped Meta-Atoms

A new design of a microwave-range ENZ metamaterial consisting of rods with an obround cross-section is proposed. The plasma frequency of the metamaterial can be tuned by rotating the constituent meta-atoms. Tunability of the plasma frequency by 26% is demonstrated both experimentally and numerically. The observed tuning range is dramatically higher than in the one observed in natural materials at optical range.

physics.optics↗

arXiv2024

Reflectance measurements of mm-wave absorbers using frequency-domain continuous wave THz spectroscopy

Due to high dynamic range and ease of use, continuous wave terahertz spectroscopy is an increasingly popular method for optical characterization of components used in cosmic microwave background (CMB) experiments. In this work, we describe an optical testbed that enables simultaneous measurements of transmission and reflection properties of various radiation absorbing dielectric materials, essential components in the reduction of undesired optical loading. To demonstrate the performance of the testbed, we have measured the reflection response of five absorbers commonly used for such applications: TKRAM, carbon- and iron-loaded Stycast, HR10, AN72, and an in-house 3D printed absorber across a frequency range of 100 to 500 GHz, for both S- and P-polarization, with incident angles varying from 15 to 45 degrees. We present results on both the specular and scattered reflection response of these absorbers.

astro-ph.IM↗

arXiv2023

Searching For Dark Matter with Plasma Haloscopes

We summarise the recent progress of the Axion Longitudinal Plasma HAloscope (ALPHA) Consortium, a new experimental collaboration to build a plasma haloscope to search for axions and dark photons. The plasma haloscope is a novel method for the detection of the resonant conversion of light dark matter to photons. ALPHA will be sensitive to QCD axions over almost a decade of parameter space, potentially discovering dark matter and resolving the Strong CP problem. Unlike traditional cavity haloscopes, which are generally limited in volume by the Compton wavelength of the dark matter, plasma haloscopes use a wire metamaterial to create a tuneable artificial plasma frequency, decoupling the wavelength of light from the Compton wavelength and allowing for much stronger signals. We develop the theoretical foundations of plasma haloscopes and discuss recent experimental progress. Finally, we outline a baseline design for ALPHA and show that a full-scale experiment could discover QCD axions over almost a decade of parameter space.

hep-ph↗

arXiv2023

Maximising Weather Forecasting Accuracy through the Utilisation of Graph Neural Networks and Dynamic GNNs

Weather forecasting is an essential task to tackle global climate change. Weather forecasting requires the analysis of multivariate data generated by heterogeneous meteorological sensors. These sensors comprise of ground-based sensors, radiosonde, and sensors mounted on satellites, etc., To analyze the data generated by these sensors we use Graph Neural Networks (GNNs) based weather forecasting model. GNNs are graph learning-based models which show strong empirical performance in many machine learning approaches. In this research, we investigate the performance of weather forecasting using GNNs and traditional Machine learning-based models.

cs.LG↗

arXiv2023

3D Object Detection in LiDAR Point Clouds using Graph Neural Networks

LiDAR (Light Detection and Ranging) is an advanced active remote sensing technique working on the principle of time of travel (ToT) for capturing highly accurate 3D information of the surroundings. LiDAR has gained wide attention in research and development with the LiDAR industry expected to reach 2.8 billion $ by 2025. Although the LiDAR dataset is of rich density and high spatial resolution, it is challenging to process LiDAR data due to its inherent 3D geometry and massive volume. But such a high-resolution dataset possesses immense potential in many applications and has great potential in 3D object detection and recognition. In this research we propose Graph Neural Network (GNN) based framework to learn and identify the objects in the 3D LiDAR point clouds. GNNs are class of deep learning which learns the patterns and objects based on the principle of graph learning which have shown success in various 3D computer vision tasks.

cs.CV↗