arXiv subjects

Xie

Publications and source records attributed to Xie.

At least 19 recordsLinked to original sources

arXiv2026

CCAT: The Prime-Cam Instrument for the Fred Young Submillimeter Telescope -- Overview and Status

Prime-Cam is a first-generation science instrument for the CCAT Observatory's six-meter aperture Fred Young Submillimeter Telescope (FYST), under construction at an elevation of 5600 m on Cerro Chajnantor in Chile's Atacama Desert. Prime-Cam will deliver over ten times greater mapping speed at submillimeter wavelengths than current facilities for unprecedented broadband and spectroscopic measurements in windows between 1.4 -- 0.3 mm (220 -- 850 GHz). When fully populated, Prime-Cam will field over 100,000 kinetic inductance detectors across seven independently optimized instrument modules. With Prime-Cam, the CCAT Collaboration will address a suite of science goals, from Big Bang cosmology, to galaxy evolution and star formation over cosmic time. Prime-Cam is scheduled for integration in FYST in late 2026, followed by a year of early science observations with the 280 and 350 GHz instrument modules. We discuss the design and in-lab testing of the 1.8-m diameter Prime-Cam receiver and 280 GHz instrument module, and give an update on deployment status and early science plans.

astro-ph.IM↗

arXiv2026

CCAT: a two-octave 1.024 GHz KID readout featuring an overlap-channel polyphase synthesis filter bank on RFSoC

Next-generation submillimeter instruments require gigahertz-scale readout bandwidths to support the growing detector counts of large microwave kinetic inductance detector (KID) arrays. Designed to meet the readout bandwidth and tone-capacity requirements of the CCAT Prime-Cam 850 GHz and 410 GHz instrument modules, we developed our second-generation (Gen2) KID readout system on a Xilinx ZCU111 radio frequency system-on-chip (RFSoC), based on a parallelized overlap-channel polyphase synthesis filter bank and a companion wideband receiving channelizer. This two-octave architecture reads out four independent RF networks, each with 1.024 GHz instantaneous bandwidth and up to 2048 detectors. The polyphase synthesis doubles the baseline channel count and bandwidth, and enables on-the-fly control of individual tone frequency, amplitude and phase, facilitating optimized KID biasing and providing a gateway to tone tracking. These capabilities may also be useful more broadly across Prime-Cam and in similar frequency-division multiplexed (FDM) readout systems. We present the design in DSP simulation, and measurements in RF loopback as well as with two KID test chips, one spanning the full two-octave band. Loopback measurements demonstrate comparable noise performance between the first-generation (Gen1) baseline and Gen2; preliminary on/off-resonance measurements indicate detector-noise-limited operation for the majority of channels; and the digital channel crosstalk is measured and discussed. We report FPGA resource and power utilization and assess scalability toward future large-format KID instruments.

astro-ph.IM↗

arXiv2026

CCAT: Characterization of the first science-grade MKID array for the Prime-Cam 850 GHz module

The Fred Young Submillimeter Telescope (FYST) is a 6-meter crossed-Dragone telescope developed by the CCAT collaboration. Sited at 5600 m on Cerro Chajnantor in the Atacama Plateau of Chile, FYST aims to provide superior atmospheric transmission and a wide field of view for submillimeter observations. Prime-Cam is a first-generation instrument for FYST designed to house up to seven separate instrument modules. Among these, the 850 GHz module represents the highest-frequency band and is optimized for ultra-sensitive broadband polarimetry and imaging. This module is designed to deploy ~38,000 polarization-sensitive lumped-element titanium-nitride (TiN) microwave kinetic inductance detectors (MKIDs) across three arrays. Thus the 850 GHz module will have the most submillimeter MKIDs in a single instrument module to date. These detectors have adopted a novel two-octave design to maximize the multiplexing achieved using a RFSoC readout system. We review the design parameters and fabrication process for the first 850 GHz science-grade array. The preliminary measurements of the array show a fabrication yield of 99%, highlighting the successful application of the design and fabrication process. We further present the cryogenic characterization of the first full MKID array developed for the Prime-Cam 850 GHz module. Multiple tests were performed on the devices including resonator frequency mapping, quality factor measurements, optical load sweeps and noise performance. From these measurements, we discuss the measured optical efficiency, sensitivity, and uniformity across the array and the expected on-sky performance of the module. The 850 GHz module will be deployed for observing in 2027.

astro-ph.IM↗

arXiv2026

CCAT: Design and Characterization of the 350 GHz Instrument Module

The CCAT Collaboration's Prime-Cam instrument will soon be deployed to the Fred Young Submillimeter Telescope (FYST) in Chile's Atacama Desert. Featuring prominently in Prime-Cam's calibration and early science observations will be the 350 GHz instrument module, a broadband camera that will field more than 10,000 microwave kinetic inductance detectors (KIDs) across three detector arrays. Forecasts show this module will be capable of making the most sensitive to-date measurements of polarized dust emission over a large fraction of the sky at this frequency, enabling new galactic polarization science and improved understanding of cosmological foregrounds. In this work we discuss the design of the 350 GHz instrument module, covering aspects of the optics, readout, and detector arrays. We then report on the results of in-lab testing of the fully-integrated module, achieving stable cryogenic performance with a 100 mK focal plane, high detector yield, and a passband comparable to designed specifications. Upon completion of these tests, this module was shipped to the telescope site in Chile for integration in Prime-Cam.

astro-ph.IM↗

arXiv2026

CCAT: The 410 GHz camera module for FYST - design and testing of the MKID focal plane

Prime-Cam, the primary first-light instrument for the Fred Young Submillimeter Telescope (FYST) developed by the Cerro Chajnantor Atacama Telescope (CCAT) Collaboration, will accommodate seven modules. Here we describe the off-central 410 GHz imager/polarimeter. The 410 GHz instrument is a camera module for CCAT funded by the Canadian Foundation for Innovation, being developed as a collaboration between Dalhousie University, University of British Columbia (UBC), National Research Council (NRC) - Herzberg, and Duke University. With atmospheric loading in the 410 GHz window being significantly higher than at 350 GHz (but substantially lower than 850 GHz), we assess four MKID test devices with varying inductor volume for performance at 410 GHz. We propose a design for an array of ~6,700 horn-coupled TiN MKIDs optimized for use at 410 GHz, with a planned ~20,000 MKIDs over three arrays, exploring mapping speed versus detector number. We test the four MKID devices optically and assess optimal Qi/Qc and responsivity for the 410 GHz atmospheric window atop Cerro Chajnantor. The detectors will be designed in frequency to be efficiently readout with a second generation, two octave readout (based on the Xilinx RFSoC board), with over 4000 detectors per board.

astro-ph.IM↗

arXiv2026

Robust Cross-Domain Generalization Using Unlabeled Target Data with Source-Domain Supervision

It is often desirable to generalize medical imaging AI models trained with dense annotations to data acquired from different ultrasound scanners or clinical sites; however, retraining these models with new annotations is often difficult and costly. We examine this challenge in pediatric wrist fracture assessment using point-of-care ultrasound (POCUS), where fractures are common and can be effectively triaged via ultrasound. AI has shown radiologist-level performance for fracture detection, often aided by high-quality bony structure segmentation. However, due to significant domain shifts, models perform poorly on data from other centers or probes, and obtaining segmentation labels across devices is impractical due to manual annotation effort and data privacy concerns. To address this, we propose a target-informed self-supervised pretraining and model-ensemble strategy. Specifically, our approach combines masked image modeling (MIM) and contrastive learning to learn target-domain structural representations without labels, and introduces a confidence-aware infusion head to adaptively integrate predictions. The source dataset, collected with a Philips Lumify probe, contained dense labels, while the target dataset, acquired with a TeleMED portable probe, was unlabeled. The datasets were kept strictly separate throughout the entire process. Our method used labeled source data for supervised training and leveraged target-domain pretraining to improve generalization. On 318 images from 62 pediatric POCUS videos, this approach significantly improved cross-device performance, achieving over 6% Dice improvement on the target domain versus the baseline. These results demonstrate a label-efficient and privacy-preserving approach for cross-device-robust ultrasound AI, offering a framework that can be extended to multi-center studies or federated learning setups.

cs.CV↗

arXiv2025

CCAT: Optical Responsivity, Noise, and Readout Optimization of KIDs for Prime-Cam

The Prime-Cam instrument on the Fred Young Submillimeter Telescope (FYST) at the CCAT Observatory will conduct sensitive millimeter to submillimeter surveys for a range of astrophysical and cosmological sciences. Prime-Cam will use kinetic inductance detectors (KIDs) sensitive to multiple frequency bands spanning 280-850 GHz. With over 100,000 sensors under development, these KID arrays will soon form the largest submillimeter focal plane ever built. With fixed microwave tones probing amplitude and phase modulations in the KIDs due to incoming radiation, challenges arise in determining the optimal readout settings, especially under varying atmospheric loading. Realizing the science goals of FYST requires operating the detectors at optimal performance and determining accurate responsivities, which depend on readout tone placement and power. To address these challenges, we present laboratory measurements of sample pixels from the 280 GHz TiN and Al arrays using a blackbody cold load to simulate observing conditions. These measurements probe detector responsivity and noise across varying optical loading, tone power, and tone placement, providing the foundation to guide in situ calibration and operation of the >100,000 KIDs. We characterize detector sensitivity via the Noise Equivalent Power (NEP) as a function of readout tone power and placement, and measure the impact of detuning due to varying optical power on the NEP. Our test setup and methodology will inform the commissioning of Prime-Cam, in situ detector calibration procedures, the cadence of probe tone resetting, and potential design refinements for future arrays, supporting FYST's planned first light in 2026.

astro-ph.IM↗

arXiv2025

CCAT: Design, Implementation, and Testing of a System to Read Out over 10,000 280 GHz KIDs using RFSoC Electronics

Over the past decade, kinetic inductance detectors (KIDs) have emerged as a viable superconducting technology for astrophysics at millimeter and submillimeter wavelengths. KIDs spanning 210 - 850 GHz across seven instrument modules will be deployed in the Prime-Cam instrument of CCAT Observatory's Fred Young Submillimeter Telescope at an elevation of 5600 m on Cerro Chajnantor in Chile's Atacama Desert. The natural frequency-division multiplexed readout of KIDs allows hundreds of detectors to be coupled to a single radio frequency (RF) transmission line, but requires sophisticated warm readout electronics. The FPGA-based Xilinx ZCU111 radio frequency system on chip (RFSoC) offers a promising and flexible solution to the challenge of warm readout. CCAT uses custom packaged RFSoCs to read out KIDs in the Prime-Cam instrument. Each RFSoC can simultaneously read out four RF channels with up to 1,000 detectors spanning a 512 MHz bandwidth per channel using the current firmware. We use five RFSoCs to read out the >10,000 KIDs in the broadband 280 GHz instrument module. Here, we describe and demonstrate the readout hardware, software and pipeline for the RFSoC system. We present a detector position map of the 280 GHz module focal plane and preliminary averaged spectral responses of a small subset of detectors from the TiN and first Al arrays. These measurements demonstrate our ability to simultaneously readout thousands of detectors, validate the end-to-end performance of the readout and optical systems, and represent a critical step toward reading out the ~100,000 KIDs in Prime-Cam in its future full capacity configuration.

astro-ph.IM↗

arXiv2025

CCAT: Magnetic Sensitivity Measurements of Kinetic Inductance Detectors

The CCAT Observatory is a ground-based submillimeter to millimeter experiment located on Cerro Chajnantor in the Atacama Desert, at an altitude of 5,600 meters. CCAT features the 6-meter Fred Young Submillimeter Telescope (FYST), which will cover frequency bands from 210 GHz to 850 GHz using its first-generation science instrument, Prime-Cam. The detectors used in Prime-Cam are feedhorn-coupled, lumped-element superconducting microwave kinetic inductance detectors (KIDs). The telescope will perform wide-area surveys at speeds on the order of degrees per second. During telescope operation, the KIDs are exposed to changes in the magnetic field caused by the telescope's movement through Earth's magnetic field and internal sources within the telescope. We present and compare measurements of the magnetic sensitivity of three different CCAT KID designs at 100 mK. The measurements are conducted in a dilution refrigerator (DR) with a set of room temperature Helmholtz coils positioned around the DR. We discuss the implications of these results for CCAT field operations.

astro-ph.IM↗

arXiv2025

CCAT: Mod-Cam Cryogenic Performance and its Impact on 280 GHz KID Array Noise

The CCAT Observatory's Fred Young Submillimeter Telescope (FYST) is designed to observe submillimeter astronomical signals with high precision, using receivers fielding state-of-the-art kinetic inductance detector (KID) arrays. Mod-Cam, a first-light instrument for FYST, serves as a testbed for instrument module characterization, including detailed evaluation of thermal behavior under operating conditions prior to deploying modules in the larger Prime-Cam instrument. Prime-Cam is a first generation multi-band, wide-field camera for FYST, designed to field up to seven instrument modules and provide unprecedented sensitivity across a broad frequency range. We present results from two key laboratory characterizations: an "optically open" cooldown to validate the overall thermal performance of the cryostat, and a "cold load" cooldown to measure the effect of focal plane temperature stability on detector noise. During the optically open test, we achieved stable base temperatures of 1.5 K on the 1 K stage and 85 mK at the detector stage. In the cold load configuration, we measured a detector focal plane RMS temperature stability of 3.2e-5 K. From this stability measurement, we demonstrate that the equivalent power from focal plane thermal fluctuations is only 0.0040% of a 5pW incident photon power for aluminum detectors and 0.0023% for titanium-nitride detectors, a negligible level for CCAT science goals. This highlights the success of the cryogenic system design and thermal management.

astro-ph.IM↗

arXiv2025

CCAT: Mod-Cam Readout Overview and Flexible Stripline Performance

The CCAT Observatory's primary science instrument, Prime-Cam, is nearing readiness for deployment to the Fred Young Submillimeter Telescope (FYST) in the Atacama Desert in northern Chile. When fully deployed, Prime-Cam will field approximately 100,000 kinetic inductance detectors (KIDs) across seven instrument modules making both broadband and polarimetric measurements. Meanwhile, in-lab characterization of the first CCAT instrument module, a 280 GHz broadband camera fielding over 10,000 KIDs, is currently underway in the testbed instrument Mod-Cam. Both Mod-Cam and Prime-Cam will employ 46 cm long low-thermal-conductivity flexible circuits ("stripline") between 4 K and 300 K to connect large-format arrays of multiplexed KIDs in each instrument module to readout electronics. The 280 GHz camera currently installed in Mod-Cam uses six of these striplines to read out its over 10,000 detectors. We have examined the thermal and electrical performance of the stripline installed in Mod-Cam. We begin by characterizing the OFHC copper in the stripline traces, allowing for the estimation of thermal loading through these flexible circuits in their configurations in both Mod-Cam and Prime-Cam. We then directly measure the thermal conductivity of the stripline, finding it is best described by $kA = 22\pm6~T^{0.84\pm0.09}~\mathrm{\mu~W~m~K^{-1}}$ for temperature ranges of 6 K < T < 20 K and $kA~=~0.6\pm0.3~T^{-0.4\pm0.1}~\mathrm{mW~m~K^{-1}}$ for ranges from 20 K < T < 80 K. Following our thermal characterizations, we report on the transmission and crosstalk properties of the Mod-Cam readout chain, isolating elevated crosstalk to SMP-SMA transition printed circuit boards (PCBs) that interface with the stripline. This finding validates the stripline circuit as a viable high-density cabling option for large-format array readout.

astro-ph.IM↗

arXiv2025

An Information-Theoretic Framework for Feature Construction in Out-of-Distribution Detection

We present a theory for the construction of out-of-distribution (OOD) detection features for neural networks. We introduce random features for OOD through a novel information-theoretic loss functional consisting of two terms, the first based on the KL divergence separates resulting in-distribution (ID) and OOD feature distributions and the second term is the Information Bottleneck, which favors compressed features that retain the OOD information. We formulate a variational procedure to optimize the loss and obtain OOD features. Based on assumptions on OOD distributions, one can recover properties of existing OOD features, i.e., shaping functions. Furthermore, we show that our theory can predict a new shaping function that out-performs existing ones on OOD benchmarks, including both semantic and a wide range of covariate shifts. Our theory provides a general framework for constructing a variety of new features with clear explainability.

cs.LG↗

arXiv2025

CCAT: Multi-Rate DSP for Sub-mm Astronomy: Polyphase Synthesis Filter Bank on FPGA for Enhanced MKID Readout

The next-generation mm/sub-mm/far-IR astronomy will in part be enabled by advanced digital signal processing (DSP) techniques. The Prime-Cam instrument of the Fred Young Submillimeter Telescope (FYST), featuring the largest array of submillimeter detectors to date, utilizes a novel overlap-channel polyphase synthesis filter bank (OC-PSB) for the AC biasing of detectors, implemented on a cutting-edge Xilinx Radio Frequency System on Chip (RFSoC). This design departs from traditional waveform look-up-table(LUT) in memory, allowing real-time, dynamic signal generation, enhancing usable bandwidth and dynamic range, and enabling microwave kinetic inductance detector (MKID) tracking for future readout systems. Results show that the OC-PSB upholds critical performance metrics such as signal-to-noise ratio (SNR) while offering additional benefits such as scalability. This paper will discuss DSP design, RFSoC implementation, and laboratory performance, demonstrating OC-PSB's potential in submillimeter-wave astronomy MKID readout systems.

astro-ph.IM↗

arXiv2024

Maximizing User Connectivity in AI-Enabled Multi-UAV Networks: A Distributed Strategy Generalized to Arbitrary User Distributions

Deep reinforcement learning (DRL) has been extensively applied to Multi-Unmanned Aerial Vehicle (UAV) network (MUN) to effectively enable real-time adaptation to complex, time-varying environments. Nevertheless, most of the existing works assume a stationary user distribution (UD) or a dynamic one with predicted patterns. Such considerations may make the UD-specific strategies insufficient when a MUN is deployed in unknown environments. To this end, this paper investigates distributed user connectivity maximization problem in a MUN with generalization to arbitrary UDs. Specifically, the problem is first formulated into a time-coupled combinatorial nonlinear non-convex optimization with arbitrary underlying UDs. To make the optimization tractable, a multi-agent CNN-enhanced deep Q learning (MA-CDQL) algorithm is proposed. The algorithm integrates a ResNet-based CNN to the policy network to analyze the input UD in real time and obtain optimal decisions based on the extracted high-level UD features. To improve the learning efficiency and avoid local optimums, a heatmap algorithm is developed to transform the raw UD to a continuous density map. The map will be part of the true input to the policy network. Simulations are conducted to demonstrate the efficacy of UD heatmaps and the proposed algorithm in maximizing user connectivity as compared to K-means methods.

eess.SY↗

arXiv2024

Learning with Dynamics: Autonomous Regulation of UAV Based Communication Networks with Dynamic UAV Crew

Unmanned Aerial Vehicle (UAV) based communication networks (UCNs) are a key component in future mobile networking. To handle the dynamic environments in UCNs, reinforcement learning (RL) has been a promising solution attributed to its strong capability of adaptive decision-making free of the environment models. However, most existing RL-based research focus on control strategy design assuming a fixed set of UAVs. Few works have investigated how UCNs should be adaptively regulated when the serving UAVs change dynamically. This article discusses RL-based strategy design for adaptive UCN regulation given a dynamic UAV set, addressing both reactive strategies in general UCNs and proactive strategies in solar-powered UCNs. An overview of the UCN and the RL framework is first provided. Potential research directions with key challenges and possible solutions are then elaborated. Some of our recent works are presented as case studies to inspire innovative ways to handle dynamic UAV crew with different RL algorithms.

eess.SY↗

arXiv2024

When Learning Meets Dynamics: Distributed User Connectivity Maximization in UAV-Based Communication Networks

Distributed management over Unmanned Aerial Vehicle (UAV) based communication networks (UCNs) has attracted increasing research attention. In this work, we study a distributed user connectivity maximization problem in a UCN. The work features a horizontal study over different levels of information exchange during the distributed iteration and a consideration of dynamics in UAV set and user distribution, which are not well addressed in the existing works. Specifically, the studied problem is first formulated into a time-coupled mixed-integer non-convex optimization problem. A heuristic two-stage UAV-user association policy is proposed to faster determine the user connectivity. To tackle the NP-hard problem in scalable manner, the distributed user connectivity maximization algorithm 1 (DUCM-1) is proposed under the multi-agent deep Q learning (MA-DQL) framework. DUCM-1 emphasizes on designing different information exchange levels and evaluating how they impact the learning convergence with stationary and dynamic user distribution. To comply with the UAV dynamics, DUCM-2 algorithm is developed which is devoted to autonomously handling arbitrary quit's and join-in's of UAVs in a considered time horizon. Extensive simulations are conducted i) to conclude that exchanging state information with a deliberated task-specific reward function design yields the best convergence performance, and ii) to show the efficacy and robustness of DUCM-2 against the dynamics.

cs.NI↗

arXiv2022

Real-Time Dynamic Map with Crowdsourcing Vehicles in Edge Computing

Autonomous driving perceives surroundings with line-of-sight sensors that are compromised under environmental uncertainties. To achieve real time global information in high definition map, we investigate to share perception information among connected and automated vehicles. However, it is challenging to achieve real time perception sharing under varying network dynamics in automotive edge computing. In this paper, we propose a novel real time dynamic map, named LiveMap to detect, match, and track objects on the road. We design the data plane of LiveMap to efficiently process individual vehicle data with multiple sequential computation components, including detection, projection, extraction, matching and combination. We design the control plane of LiveMap to achieve adaptive vehicular offloading with two new algorithms (central and distributed) to balance the latency and coverage performance based on deep reinforcement learning techniques. We conduct extensive evaluation through both realistic experiments on a small-scale physical testbed and network simulations on an edge network simulator. The results suggest that LiveMap significantly outperforms existing solutions in terms of latency, coverage, and accuracy.

cs.DC↗

arXiv2021

U-Statistics for Left Truncated and Right Censored Data

The analysis left truncated and right censored data is very common in survival and reliability analysis. In lifetime studies patients often subject to left truncation in addition to right censoring. For example, in bone marrow transplant studies based on International Bone Marrow Transplant Registry (IBMTR), the patients who die while waiting for the transplants will not be reported to the IBMTR. In this paper, we develop novel U-statistics under left truncation and right censoring. We prove the $\sqrt{n}$-consistency of the proposed U-statistics. We derive the asymptotic distribution of the U-statistics using counting process technique. As an application of the U-statistics, we develop a simple non-parametric test for testing the independence between time to failure and cause of failure in competing risks when the observations are subject to left truncation and right censoring. The finite sample performance of the proposed test is evaluated through Monte Carlo simulation study. Finally we illustrate our test procedure using lifetime data of transformers.

stat.ME↗