@arXiv_physicsinsdet_bot@mastoxiv.page2026-08-21 07:58:08
UPLOAD-ANYON: Progress Towards an Optimised Twisted Anyon Cavity with High-Sensitivity AM-Noise Detection for an Ultralight Axion Dark Matter Search
Robert Crew, Emma Paterson, Maxim Goryachev, Eugene Ivanov, Pashupati Dhakal, Tugrul Talha Ersoz, Michael Tobar, Jeremy Bourhill
https://arxiv.org/abs/2608.19225 https://arxiv.org/pdf/2608.19225 https://arxiv.org/html/2608.19225
arXiv:2608.19225v1 Announce Type: new
Abstract: We propose a superconducting single-mode microwave haloscope based on helical cavity resonators for the detection of ultralight dark matter axions over the mass range $10^{-18}$ to $10^{-13}\,\mathrm{eV}$. Building on the single-mode helical-cavity concept introduced by Bourhill et al. [Phys. Rev. D 108, 052014 (2023); arXiv:2208.01640], we use an inverse-design framework to develop practical resonator geometries compatible with superconducting niobium fabrication. The optimisation employs a figure of merit derived to minimise the measurement time required to achieve a fixed experimental sensitivity. Relative to the heuristic M\"obius-geometry benchmark, the best subtractively manufacturable bulk-niobium design achieves a figure of merit more than three orders of magnitude larger. An experimentally informed microwave interferometric readout model, incorporating measured electronics noise and active suppression of pump amplitude noise, is used to project the sensitivity of the proposed experiment. For an acquisition time of three months, the haloscope is projected to reach $g_{a\gamma\gamma}<10^{-11}\,\mathrm{GeV}^{-1}$ across more than four orders of magnitude in axion mass. The projected sensitivity extends approximately one order of magnitude below the current exclusion limits set by CAST, providing a practical pathway towards a high-sensitivity direct search for ultralight dark matter axions.
toXiv_bot_toot
@macandi@social.heise.de2026-09-18 11:51:03
@arXiv_physicsmedph_bot@mastoxiv.page2026-07-21 07:55:04
Theoretical derivation of blood velocity from TOF-MRA based artery centerline
Abrar Faiyaz
https://arxiv.org/abs/2607.16498 https://arxiv.org/pdf/2607.16498 https://arxiv.org/html/2607.16498
arXiv:2607.16498v1 Announce Type: new
Abstract: Time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for structural vascular imaging, but extracting functional hemodynamics like blood velocity typically requires supplementary phase-contrast scans. This study proposes a novel, physics-informed computational framework to extract variable fluid velocity directly from standard TOF-MRA signal profiles. We analytically expand the Bloch equations into Bloch-McConnell flow equations, establishing a mathematical relationship between the spatial decay of longitudinal magnetization and fluid velocity. To validate this derivation and overcome the limitations of constant-velocity assumptions, a MATLAB simulation framework was developed to model fluid flow in two variable-geometry flowing tube cases i.e continuous tapering and focal stenosis -under synthetic scanner noise. A global inverse optimization approach utilizing Dual-Tikhonov regularization was deployed to stably invert the ill-posed transit time integral, actively penalizing high-frequency numerical ringing while preserving structural curve stiffness. The computational sim-ulations successfully recovered ground-truth point-wise velocities, accurately tracking gradual hemodynamic accelerations and sharp stenotic jets. This theoretical framework provides a robust mathematical proof-of-concept that quantitative, localized functional hemodynamic metrics can be extracted from standard structural MRA imaging, estab-lishing a foundation for advanced flow quantification without requiring additional scan time.
toXiv_bot_toot
@cdarwin@c.im2026-09-07 02:27:19
@samvarma@fosstodon.org2026-07-17 15:09:51
@arXiv_physicsmedph_bot@mastoxiv.page2026-07-21 07:53:01
Continuous 3-D Latent Diffusion for Medical Generation and Reconstruction
Youness Mellak, Antoine De Paepe, Dimitris Visvikis, Alexandre Bousse
https://arxiv.org/abs/2607.16491 https://arxiv.org/pdf/2607.16491 https://arxiv.org/html/2607.16491
arXiv:2607.16491v1 Announce Type: new
Abstract: High-resolution three-dimensional (3-D) medical diffusion models remain constrained by the cost of processing full volumes, even when denoising is performed in a compact latent space. We introduce a continuous 3-D latent diffusion model (LDM) framework for computed tomography (CT) and magnetic resonance imaging (MRI) generation and measurement-guided reconstruction. Its central component is a compact autoencoder (AE) with a coordinate-conditioned local implicit image function (LIIF) decoder that represents a volume as a continuous function of spatial coordinates. By evaluating the convolutional decoder once on the latent grid and restricting repeated computation to a lightweight implicit head, the proposed design avoids overlapping sub-volume decoding while remaining differentiable for inverse-problem optimization. We evaluate the framework on CT volumes of 512^3 voxels and MRI volumes of 256^3 voxels. On high-resolution CT, the proposed AE is approximately x12-32 faster than the evaluated reference autoencoders, achieves the lowest peak graphics processing unit (GPU) memory use, and retains comparable structural fidelity despite a moderate reduction in voxel-level accuracy. The resulting frozen 3-D latent prior generates coherent full volumes without visible patch seams and can be applied, without task-specific retraining, to sparse-view CT and accelerated MRI reconstruction through hard data consistency. Although direct pixel-domain reconstruction remains more accurate, the results demonstrate that a single volumetric latent prior can support both unconditional generation and measurement-conditioned reconstruction on one GPU. Overall, the framework provides a practical trade-off between continuous volumetric decoding, computational efficiency, and fine-detail preservation. Our code will be made available at https://github.com/mellak/.
toXiv_bot_toot
@macandi@social.heise.de2026-08-10 10:07:03
@arXiv_physicsinsdet_bot@mastoxiv.page2026-08-20 08:54:34
Replaced article(s) found for physics.ins-det. https://arxiv.org/list/physics.ins-det/new
[1/1]:
- Flow-dependent tagging of $^{214}$Pb decays in the LZ dark matter detector
J. Aalbers, et al.
https://arxiv.org/abs/2508.19117 https://mastoxiv.page/@arXiv_physicsinsdet_bot/115099888730207431
- Experimental Characterization of Bulk Micromegas for Development of Active Target Time Projection...
Pralay Kumar Das, Nayana Majumdar, Supratik Mukhopadhyay
https://arxiv.org/abs/2602.21238 https://mastoxiv.page/@arXiv_physicsinsdet_bot/116135916399290266
- An AI-based Detector Simulation and Reconstruction Model for the ALEPH Experiment at LEP
Ya-Feng Lo, Dmitrii Kobylianskii, Benjamin Nachman, Eilam Gross
https://arxiv.org/abs/2604.11834 https://mastoxiv.page/@arXiv_physicsinsdet_bot/116407678561282432
- New Spallation Background Rejection Techniques to Greatly Improve the Solar Neutrino Sensitivity ...
Obada Nairat, John F. Beacom, Shirley Weishi Li
https://arxiv.org/abs/2510.12873 https://mastoxiv.page/@arXiv_hepph_bot/115382755693449240
- Quantization Effects of Artificial Neural Networks for Embedded Edge-Computing Applications
Aksoy, Bekman, Dimitrov, Dorosti, Eguzo, Fleitmann, Hader, Zambanini, van Waasen
https://arxiv.org/abs/2511.05479 https://mastoxiv.page/@arXiv_csNE_bot/115524263599389339
toXiv_bot_toot
@cdarwin@c.im2026-08-16 01:36:34
The Office of the Comptroller of the Currency, a regulatory agency whose leader was chosen by Donald Trump,
granted preliminary approval on Friday to World Liberty Financial’s application for a federal bank charter.
World Liberty Financial is a crypto venture launched in 2024 by the president’s two eldest sons,
Donald Trump Jr. and Eric Trump,
and several partners.
The firm’s website states that WLF is 38% owned by “an entity affiliated with Donald J. Trump and …
@macandi@social.heise.de2026-08-14 15:33:03
Nachgebaute Apple Watch verbindet sich mit iPhones
Nils Rollshausen von der TU Darmstadt hat Apples Computeruhr im Labor in Software nachgebaut. Das zeigt potenzielle Angriffspunkte.
https://www.
