Quantum Simulation of the Thermal Dark Counts of the SPAD Detector for Space Applications

Single-Photon Avalanche Diodes (SPADs) are widely employed in spacebased photon detection systems for applications such as deep-space communication, LIDAR, and radiation monitoring. However, their performance is fundamentally limited by thermal dark counts, which are spurious detection events arising from temperature-induced carrier excitations. In this work, we present a quantum-mechanical modelling framework in which the SPAD is represented as a quantized two-level system | g > , | e > corresponding to the ground and excited (avalanche-triggering) states. Thermal effects are incorporated through open quantum system dynamics using the Lindblad master equation, enabling a physically consistent description of temperature-driven carrier generation and relaxation processes. To enable scalable and hardware-relevant analysis, we implement the model within a gate-based quantum simulation framework, where quantum state transitions emulate thermally induced carrier excitation events. The time evolution of the excitation probability is computed to extract the theoretical dark count rate under varying thermal conditions relevant to space environments. This approach establishes a quantum simulation platform for predicting SPAD noise behaviour in temperature-variable environments, providing a foundation for optimizing detector design and improving photon-counting reliability in space applications.

Authors

Institutions

Publication Details

Journal
EPJ Web of Conferences
Published
2026-01-01
DOI
https://doi.org/10.1051/epjconf/202636001026
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantum Simulation of the Thermal Dark Counts of the SPAD Detector for Space Applications

Kavita Lalwani, Durgesh Tinker
EPJ Web of Conferences
Advanced Optical Sensing Technologies
article

Quantum Simulation of the Thermal Dark Counts of the SPAD Detector for Space Applications

Kavita Lalwani, Durgesh Tinker
article en

Abstract

Single-Photon Avalanche Diodes (SPADs) are widely employed in spacebased photon detection systems for applications such as deep-space communication, LIDAR, and radiation monitoring. However, their performance is fundamentally limited by thermal dark counts, which are spurious detection events arising from temperature-induced carrier excitations. In this work, we present a quantum-mechanical modelling framework in which the SPAD is represented as a quantized two-level system | g > , | e > corresponding to the ground and excited (avalanche-triggering) states. Thermal effects are incorporated through open quantum system dynamics using the Lindblad master equation, enabling a physically consistent description of temperature-driven carrier generation and relaxation processes. To enable scalable and hardware-relevant analysis, we implement the model within a gate-based quantum simulation framework, where quantum state transitions emulate thermally induced carrier excitation events. The time evolution of the excitation probability is computed to extract the theoretical dark count rate under varying thermal conditions relevant to space environments. This approach establishes a quantum simulation platform for predicting SPAD noise behaviour in temperature-variable environments, providing a foundation for optimizing detector design and improving photon-counting reliability in space applications.

EPJ Web of ConferencesVol. 360
Malaviya National Institute of Technology Jaipur (IN)
Openalex Percentile: Top 13%
Advanced Optical Sensing Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.