Evidence map›Paper›PMID 37050472›Full record

ReviewSensors (Basel, Switzerland)2023

Modeling for Single-Photon Avalanche Diodes: State-of-the-Art and Research Challenges.

Xuanyu Qian, Wei Jiang, Ahmed Elsharabasy, M Jamal Deen

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Surface Plasmon Enhanced Photoluminescence of Carbon Dots Formed In Situ on Silver Gratings.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xuanyu QianDepartment of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada.
Wei JiangDepartment of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada.ORCID 0000-0002-3949-3581
Ahmed ElsharabasyDepartment of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada.
M Jamal DeenDepartment of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada.ORCID 0000-0002-6390-0933

Funding

NSERC N/A
6 · The paper itself

Abstract

With the growing importance of single-photon-counting (SPC) techniques, researchers are now designing high-performance systems based on single-photon avalanche diodes (SPADs). SPADs with high performances and low cost allow the popularity of SPC-based systems for medical and industrial applications. However, few efforts were put into the design optimization of SPADs due to limited calibrated models of the SPAD itself and its related circuits. This paper provides a perspective on improving SPAD-based system design by reviewing the development of SPAD models. First, important SPAD principles such as photon detection probability (PDP), dark count rate (DCR), afterpulsing probability (AP), and timing jitter (TJ) are discussed. Then a comprehensive discussion of various SPAD models focusing on each of the parameters is provided. Finally, important research challenges regarding the development of more advanced SPAD models are summarized, followed by the outlook for the future development of SPAD models and emerging SPAD modeling methods.

Indexed as

afterpulsing probability (AP)complementary metal-oxide-semiconductor (CMOS) photodiodesdark count rate (DCR)imaging systemphoton detection probability (PDP)silicon photomultiplier (SiPM)single-photon avalanche diodes (SPADs)timing jitter

Identifiers

PMID37050472
PMCPMC10099089

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.