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We introduce a classical algorithm for sampling the output of shallow, noisy random circuits on two-dimensional qubit arrays. The algorithm builds on the recently-proposed "space-evolving block decimation" (SEBD) and extends it to the case…
Spin noise spectroscopy (SNS) is the perfect tool to investigate electron spin dynamics in semiconductors at thermal equilibrium. We simulate SNS measurements and show that ultrafast digitizers with low bit depth enable sensitive, high…
Quantum hardware is advancing rapidly across various platforms, yet implementing large-scale quantum error correction (QEC) remains challenging. As hardware continues to improve, there is a growing need to identify potential applications on…
LiteBIRD, the Lite (Light) satellite for the study of $B$-mode polarization and Inflation from cosmic background Radiation Detection, is a space mission focused on primordial cosmology and fundamental physics. In this paper, we present the…
Source-Free Domain Adaptation (SFDA) aims to train a target model without source data, and the key is to generate pseudo-labels using a pre-trained source model. However, we observe that the source model often produces highly uncertain…
Deep neural networks have proven to be highly effective when large amounts of data with clean labels are available. However, their performance degrades when training data contains noisy labels, leading to poor generalization on the test…
We construct the first comprehensive radioactive background model for a dark matter search with charge-coupled devices (CCDs). We leverage the well-characterized depth and energy resolution of the DAMIC at SNOLAB detector and a detailed…
RGB-D salient object detection (SOD) recently has attracted increasing research interest by benefiting conventional RGB SOD with extra depth information. However, existing RGB-D SOD models often fail to perform well in terms of both…
We present a new particle tracking software algorithm designed to accurately track the motion of low-contrast particles against a background with large variations in light levels. The method is based on a polynomial fit of the intensity…
We have developed a much sensitve technique to conduct magnetometry under ultrahigh pressures up to 6.3~GPa, which can detect a weak volume susceptibilities as small as $\sim 10^{-4}$. An opposed-anvil-type high-pressure cell is designed by…
Indoor localisation techniques suffer from attenuated Global Navigation Satellite System (GNSS) signals and from the accumulation of unbounded drift by integration of proprioceptive sensors. Magnetic field-based Simultaneous Localisation…
Quantization has emerged as a mainstream approach for deploying Large Language Models (LLMs) on resource-constrained devices, yet compressing precision below 4-bit typically causes severe performance degradation or prohibitive retraining…
The ability to achieve submillimter isotropic resolution diffusion MR imaging (dMRI) is critically important to study fine-scale brain structures, particularly in the cortex. One of the major challenges in performing submillimeter dMRI is…
Synchrosqueezed transforms are non-linear processes for a sharpened time-frequency representation of wave-like components. They are efficient tools for identifying and analyzing wave-like components from their superposition. This paper is…
We developed a scanning DC SQUID microscope with novel readout electronics capable of wideband sensing RF magnetic fields from 50 to 200 MHz and simultaneously providing closed-loop response at kHz frequencies. To overcome the 20 MHz…
SIPGI is a spectroscopic pipeline for the data reduction of optical/near-infrared data acquired by slit-based spectrographs. SIPGI is a complete spectroscopic data reduction environment retaining the high level of flexibility and accuracy…
SuperCDMS SNOLAB will be a next-generation experiment aimed at directly detecting low-mass (< 10 GeV/c$^2$) particles that may constitute dark matter by using cryogenic detectors of two types (HV and iZIP) and two target materials…
Several high-performance lab instruments suitable for manual assembly have been developed using low-pin-count 32-bit microcontrollers that communicate with an Android tablet via a USB interface. A single Android tablet app accommodates…
We introduce an algorithm to marginalize the likelihood for a gravitational wave signal from a quasi-circular binary merger over its extrinsic parameters, accounting for the effects of higher harmonics and spin-induced precession. The…
Recently, post-training quantization (PTQ) has driven much attention to produce efficient neural networks without long-time retraining. Despite its low cost, current PTQ works tend to fail under the extremely low-bit setting. In this study,…