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Quantum Imaginary-Time Evolution with Polynomial Resources in Time
Lei Zhang, Jizhe Lai, Xian Wu, Xin Wang
https://arxiv.org/abs/2507.00908 https://…

Quantum Imaginary-Time Evolution with Polynomial Resources in Time
Imaginary-time evolution is fundamental to analyzing quantum many-body systems, yet classical simulation requires exponentially growing resources in both system size and evolution time. While quantum approaches reduce the system-size scaling, existing methods rely on heuristic techniques with measurement precision or success probability that deteriorates as evolution time increases. We present a quantum algorithm that prepares normalized imaginary-time evolved states using an adaptive normaliza…

AstroECP: towards more practical Electron Channeling Contrast Imaging
M. Haroon Qaiser, Lukas Berners, Robin J. Scales, Tianbi Zhang, Martin Heller, Jiri Dluhos, Sandra Korte-Kerzel, T. Ben Britton
https://arxiv.org/abs/2507.00354

AstroECP: towards more practical Electron Channeling Contrast Imaging
Electron channeling contrast imaging (ECCI) is a scanning electron microscopy (SEM) based technique that enables bulk-sample characterization of crystallographic defects (e.g. dislocations, stacking faults, low angle boundaries). Despite its potential, ECCI remains underused for quantitative defect analysis as compared to transmission electron microscope (TEM) based methods. Here, we overcome barriers that limit the use of ECCI including optimizing signal-to-noise contrast, precise determinatio…

Watermarking Without Standards Is Not AI Governance
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
https://arxiv.org/abs/2505.23814 https://

Watermarking Without Standards Is Not AI Governance
Watermarking has emerged as a leading technical proposal for attributing generative AI content and is increasingly cited in global governance frameworks. This paper argues that current implementations risk serving as symbolic compliance rather than delivering effective oversight. We identify a growing gap between regulatory expectations and the technical limitations of existing watermarking schemes. Through analysis of policy proposals and industry practices, we show how incentive structures di…

High resolution up-conversion imaging in the 10 {\mu}m band under incoherent illumination
Zhao-Qi-Zhi Han, Xiao-Hua Wang, Jin-Peng Li, Bo-Wen Liu, Zheng-He Zhou, He Zhang, Yin-Hai Li, Zhi-Yuan Zhou, Bao-Sen Shi
https://arxiv.org/abs/2505.24367

High resolution up-conversion imaging in the 10 μm band under incoherent illumination
Long-wavelength infrared band exhibits significant utility in thermal signature acquisition and molecular spectral analysis, among other applications. The up-conversion detection technique enables effective signal transduction into the detection bandwidth of silicon-based photodetectors, thereby facilitating high-sensitivity photonic measurements. We realized high-resolution up-conversion imaging for incoherent thermal targets in the 10 μm spectral regime for the first time. Furthermore, this …

Flux Trapping Characterization for Superconducting Electronics Using a Cryogenic Widefield NV-Diamond Microscope
Rohan T. Kapur, Pauli Kehayias, Sergey K. Tolpygo, Adam A. Libson, George Haldeman, Collin N. Muniz, Alex Wynn, Nathaniel J. O'Connor, Neel A. Parmar, Ryan Johnson, Andrew C. Maccabe, John Cummings, Justin L. Mallek, Danielle A. Braje, Jennifer M. Schloss

Flux Trapping Characterization for Superconducting Electronics Using a Cryogenic Widefield NV-Diamond Microscope
Magnetic flux trapping is a significant hurdle limiting reliability and scalability of superconducting electronics, yet tools for imaging flux vortices remain slow or insensitive. We present a cryogenic widefield NV-diamond magnetic microscope capable of rapid, micron-scale imaging of flux trapping in superconducting devices. Using this technique, we measure vortex expulsion fields in Nb thin films and patterned strips, revealing a crossover in expulsion behavior between $10$ and $20~μ$m strip…

CANUCS/Technicolor Data Release 1: Imaging, Photometry, Slit Spectroscopy, and Stellar Population Parameters
Ghassan T. E. Sarrouh, Yoshihisa Asada, Nicholas S. Martis, Chris J. Willott, Kartheik G. Iyer, Ga\"el Noirot, Adam Muzzin, Marcin Sawicki, Gabriel Brammer, Guillaume Desprez, Gregor Rihtar\v{s}i\v{c}, Johannes Zabl, Roberto Abraham, Maru\v{s}a Brada\v{c}, Ren\'e Doyon, Jacqueline Antwi-Danso, Samantha Berek, Westley Brown, Vince Estrada-Carpenter, Jeremy Favaro, Giorda…

CANUCS/Technicolor Data Release 1: Imaging, Photometry, Slit Spectroscopy, and Stellar Population Parameters
We present the first data release of the CAnadian NIRISS Unbiased Cluster Survey (CANUCS), a JWST Cycle 1 GTO program targeting 5 lensing clusters and flanking fields in parallel (Abell 370, MACS0416, MACS0417, MACS1149, MACS1423; survey area \tilda100 arcmin$^{2}$), with NIRCam imaging, NIRISS slitless spectroscopy, and NIRSpec prism multi-object spectroscopy. Fields centered on cluster cores include imaging in 8 bands from 0.9-4.4$μ$m, alongside continuous NIRISS coverage from 1.15-2$μ$m, w…

This https://arxiv.org/abs/2504.18903 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Numerical analysis of an H(div)-conforming divergence-free DG method with a second-order explicit Runge-Kutta scheme for incompressible flows
Recently, H(div)-conforming DG type methods coupled with Runge-Kutta (RK) time stepping have been widely employed for simulating high Reynolds number flows, with the convective terms treated explicitly. Although the analysis techniques of RKDG methods were well developed, the extension to incompressible flows is highly nontrivial due to the exactly divergence-free constraint, where the key lies in analyzing the convective terms. We neglect viscosity effects, and conduct an error analysis for an…

Single-shot HDR using conventional image sensor shutter functions and optical randomization
Xiang Dai, Kyrollos Yanny, Kristina Monakhova, Nicholas Antipa
https://arxiv.org/abs/2506.22426

Single-shot HDR using conventional image sensor shutter functions and optical randomization
High-dynamic-range (HDR) imaging is an essential technique for overcoming the dynamic range limits of image sensors. The classic method relies on multiple exposures, which slows capture time, resulting in motion artifacts when imaging dynamic scenes. Single-shot HDR imaging alleviates this issue by encoding HDR data into a single exposure, then computationally recovering it. Many established methods use strong image priors to recover improperly exposed image detail. These approaches struggle wi…

From Pixels to Camera: Scaling Superconducting Nanowire Single-Photon Detectors for Imaging at the Quantum-Limit
Jun Gao, Jin Chang, Bruno Lopez Rodriguez, Iman Esmaeil Zadeh, Val Zwiller, Ali W. Elshaari
https://arxiv.org/abs/2505.24725

From Pixels to Camera: Scaling Superconducting Nanowire Single-Photon Detectors for Imaging at the Quantum-Limit
Superconducting nanowire single-photon detectors (SNSPDs) have emerged as essential devices that push the boundaries of photon detection with unprecedented sensitivity, ultrahigh timing precision, and broad spectral response. Recent advancements in materials engineering, superconducting electronics integration, and cryogenic system design are enabling the evolution of SNSPDs from single-pixel detectors toward scalable arrays and large-format single-photon time tagging cameras. This perspective …

Estimating Head Motion in Structural MRI Using a Deep Neural Network Trained on Synthetic Artifacts
Charles Bricout, Samira Ebrahimi Kahou, Sylvain Bouix
https://arxiv.org/abs/2505.23916

Estimating Head Motion in Structural MRI Using a Deep Neural Network Trained on Synthetic Artifacts
Motion-related artifacts are inevitable in Magnetic Resonance Imaging (MRI) and can bias automated neuroanatomical metrics such as cortical thickness. Manual review cannot objectively quantify motion in anatomical scans, and existing automated approaches often require specialized hardware or rely on unbalanced noisy training data. Here, we train a 3D convolutional neural network to estimate motion severity using only synthetically corrupted volumes. We validate our method with one held-out site…