arXiv subjects

Shanshan Gao

Publications and source records attributed to Shanshan Gao.

7 recordsLinked to original sources

arXiv2026

Long-term stability-degradation analysis of DUNE SiPMs in Liquid Nitrogen

We developed a cryogenic photon readout system to monitor arrays of DUNE SiPMs operating at various over-voltages in liquid nitrogen (LN2) for over three months. Photoelectron signals were read out simultaneously via weak capacitive coupling to the micro-FEMB, a 32-channel charge sensitive readout board designed for 77 K to 300 K operation in liquid argon time projection chambers (LAr-TPCs). A waveform snippet acquisition scheme was implemented to capture waveform signals whenever they exceeded a predetermined trigger level; consequently, empty waveforms were discarded. Selected SiPM parameters were monitored to detect any deviations beyond statistical fluctuations. While some parameters exhibited ~1σ variations over the 3-month test period, there was no evidence of drift being enhanced when operating at 4 V or 5 V compared to a 3 V over-voltage. However, a discernible PDE drop was observed across all channels, which warrants further investigation. In addition, we demonstrated that our system can simultaneously read out single photons from a selected group of SiPMs at room temperature.

physics.ins-det↗

arXiv2026

Can Agent Benchmarks Support Their Scores? Evidence-Supported Bounds for Interactive-Agent Evaluation

Interactive agent benchmarks map an agent run to a binary outcome through outcome checks. When these checks rely on surface level signals or fail to capture the agent's actual action path, they cannot reliably determine whether the run succeeded. For example, a benchmark task may ask whether Alice's shipping address was changed, while the outcome check only verifies that the agent clicked "Save." This does not guarantee that the intended state change occurred, since the agent may have modified the wrong record. Treating such a run as successful therefore makes the reported score misleading. Benchmark quality thus depends not only on task design, but also on the reliability of outcome detection. We address this problem by introducing an outcome evidence reporting layer for existing benchmarks, without modifying their tasks, agents, or evaluators. The layer performs three functions. First, before scoring, it specifies which stored artifacts are required to verify the claimed outcome for each case. Second, it applies a locked checklist to each completed run and assigns one of three evidence labels: Evidence Pass, Evidence Fail, or Unknown. Third, it reports evidence supported score bounds that quantify uncertainty arising from Unknown cases. Rather than silently counting, discarding, or hiding uncertain cases inside a single aggregate success rate, the framework keeps them explicitly visible. We evaluate the outcome evidence layer on five public benchmarks: ANDROIDWORLD, AGENTDOJO, APPWORLD, tau3 bench retail, and MINIWOB. The resulting reports separate several empirically distinct failure modes.

cs.AI↗

arXiv2024

UbiHR: Resource-efficient Long-range Heart Rate Sensing on Ubiquitous Devices

Ubiquitous on-device heart rate sensing is vital for high-stress individuals and chronic patients. Non-contact sensing, compared to contact-based tools, allows for natural user monitoring, potentially enabling more accurate and holistic data collection. However, in open and uncontrolled mobile environments, user movement and lighting introduce. Existing methods, such as curve-based or short-range deep learning recognition based on adjacent frames, strike the optimal balance between real-time performance and accuracy, especially under limited device resources. In this paper, we present UbiHR, a ubiquitous device-based heart rate sensing system. Key to UbiHR is a real-time long-range spatio-temporal model enabling noise-independent heart rate recognition and display on commodity mobile devices, along with a set of mechanisms for prompt and energy-efficient sampling and preprocessing. Diverse experiments and user studies involving four devices, four tasks, and 80 participants demonstrate UbiHR's superior performance, enhancing accuracy by up to 74.2\% and reducing latency by 51.2\%.

eess.SP↗

arXiv2019

Low Noise Cold Electronics System for SBND LAr TPC

The Short Baseline Near Detector (SBND) is one of three liquid argon (LAr) neutrino detectors sitting in the Booster Neutrino Beam (BNB) at Fermilab as part of the Short Baseline Neutrino (SBN) program. The detector is in a cryostat holding 260-ton of LAr and consists of four 2.5 m (L) $\times$ 4 m (W) Anode Plane Assembles (APAs) and two Cathode Plane Assemblies (CPAs), which leads to 11,264 Time Projection Chamber (TPC) readout channels and two separate 2 m long drift regions. As an enabling technology, Cold Electronics (CE) developed for cryogenic temperature operation makes possible an optimum balance among various design and performance requirements for such large sized detectors. Brookhaven National Laboratory (BNL) has been leading the R&D and implementation of the entire front-end CE system for LAr TPC readout in collaboration with other SBND institutes. The front-end readout electronics system includes the cold front-end electronics placed close to the wire electrodes, which detects and digitizes the charge signal in LAr, as well as the warm interface electronics placed on the signal feed-through flange outside of the cryostat, which further organizes and transmits the digitized signal to the DAQ system. An extensive study of electronics suitable for 77 K - 300 K, including the custom designed front-end ASIC and commercial components, e.g. ADC and FPGA, has been made to meet requirements such as low noise, low power consumption, high reliability and long lifetime. Furthermore, an integral design concept of APA, CE, feed-through, warm interface electronics with local diagnostics, grounding and isolation rules has been practiced with vertical slice test stands to make projection of the CE performance in the SBND detector.

physics.ins-det↗

arXiv2016

The calibration and electron energy reconstruction of the BGO ECAL of the DAMPE detector

The DArk Matter Particle Explorer (DAMPE) is a space experiment designed to search for dark matter indirectly by measuring the spectra of photons, electrons, and positrons up to 10 TeV. The BGO electromagnetic calorimeter (ECAL) is its main sub-detector for energy measurement. In this paper, the instrumentation and development of the BGO ECAL is briefly described. The calibration on the ground, including the pedestal, minimum ionizing particle (MIP) peak, dynode ratio, and attenuation length with the cosmic rays and beam particles is discussed in detail. Also, the energy reconstruction results of the electrons from the beam test are presented.

physics.ins-det↗

arXiv2014

Design of the Readout Electronics for the Qualification Model of DAMPE BGO Calorimeter

The DAMPE (DArk Matter Particle Explorer) is a scientific satellite being developed in China, aimed at cosmic ray study, gamma ray astronomy, and searching for the clue of dark matter particles, with a planned mission period of more than 3 years and an orbit altitude of about 500 km. The BGO Calorimeter, which consists of 308 BGO (Bismuth Germanate Oxid) crystal bars, 616 PMTs (photomultiplier tubes) and 1848 dynode signals, has approximately 32 radiation lengths. It is a crucial sub-detector of the DAMPE payload, with the functions of precisely measuring the energy of cosmic particles from 5 GeV to 10TeV, distinguishing positrons/electrons and gamma rays from hadron background, and providing trigger information for the whole DAMPE payload. The dynamic range for a single BGO crystal is about 2?105 and there are 1848 detector signals in total. To build such an instrument in space, the major design challenges for the readout electronics come from the large dynamic range, the high integrity inside the very compact structure, the strict power supply budget and the long term reliability to survive the hush environment during launch and in orbit. Currently the DAMPE mission is in the end of QM (Qualification Model) stage. This paper presents a detailed description of the readout electronics for the BGO calorimeter.

astro-ph.IM↗

arXiv2014

Study on FPGA SEU Mitigation for Readout Electronics of DAMPE BGO Calorimeter

The BGO calorimeter, which provides a wide measurement range of the primary cosmic ray spectrum, is a key sub-detector of Dark Matter Particle Explorer (DAMPE). The readout electronics of calorimeter consists of 16 pieces of Actel ProASIC Plus FLASH-based FPGA, of which the design-level flip-flops and embedded block RAMs are single event upset (SEU) sensitive in the harsh space environment. Therefore to comply with radiation hardness assurance (RHA), SEU mitigation methods, including partial triple modular redundancy (TMR), CRC checksum, and multi-domain reset are analyzed and tested by the heavy-ion beam test. Composed of multi-level redundancy, a FPGA design with the characteristics of SEU tolerance and low resource consumption is implemented for the readout electronics.

physics.ins-det↗