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\begin{document}

%\preprint{APS/123-QED}

%\title{Efficient conversion of coherent laser light to photon bunching}
\title{Thermal LIDAR}

\author{Darren Ming Zhi Koh$^{1}$}
\author{Xi Jie Yeo$^{1}$}
\author{Christian Kurtsiefer$^{1,2}$}
\email{christian.kurtsiefer@gmail.com}
\author{Peng Kian Tan$^{1}$}
\email{cqttpk@nus.edu.sg}
\affiliation{$^{1}$Centre for Quantum Technologies, 3 Science Drive 2, Singapore 117543}
\affiliation{$^{2}$Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore, 117551}

\date{\today}% It is always \today, today,
             %  but any date may be explicitly specified

\begin{abstract}
Lorem ipsum dolor sit amet consectetur adipiscing elit. Quisque faucibus ex sapien vitae pellentesque sem placerat. In id cursus mi pretium tellus duis convallis. Tempus leo eu aenean sed diam urna tempor. Pulvinar vivamus fringilla lacus nec metus bibendum egestas. Iaculis massa nisl malesuada lacinia integer nunc posuere. Ut hendrerit semper vel class aptent taciti sociosqu. Ad litora torquent per conubia nostra inceptos himenaeos.
\end{abstract}

% \keywords{Photon Bunching, Quantum Sensing, Stationary Light, Temporal Correlations, Thermal Source}%Use showkeys class option if keyword display desired

\maketitle
\section{Introduction}
Since its invention, light detection and ranging (lidar) has been a workhorse for remote sensing in fields such as geodesy, atmospheric physics and autonomous vehicles. Lidar systems typically make use of pulsed lasers as their light source, but these suffer from range ambiguity due to the fixed pulse timing interval. To overcome this, random modulation continuous wave lidar was introduced in which properties such as amplitude and frequency. These systems practically have unlimited range but to achieve the same resolution as pulsed systems require fast modulation which can be costly.

An alternative would be to use light sources with inherent modulation. For instance, photon pairs from nonlinear processes such as spontaneous four wave mixing or spontaneous parametric down conversion (SPDC). Lidar systems with SPDC photon pairs can achieve similar performance to pulsed lidar systems due to their strong timing correlation. However, these sources are quite dim (~1M pairs/s ?) and as such has only been demonstrated in free space table setups.

In recent years, there has been a growing interest in using thermal light for lidar. Thermal light exhibit the Hanbury Brown Twiss effect, meaning that thermal photons have a tendency to be detected closer together than described by a Poissonian timing statistics. A proof of concept experiment was first carried out using pseudothermal light generated from laser light scattered off a rotating ground glass. Again, this generation process is inefficient resulting in a dim light source and limiting the demonstration to a fiber based measurement.

An even brighter source of thermal light would be a laser diode driven below its lasing threshold, producing thermal light through amplified spontaneous emission. With this, it was shown that range finding in free space at the kilometer distances is possible. However, the power restriction from the driving current meant that it was necessary to use a retroreflector as the target.

In this work, we demonstrate long range lidar of non-cooperative targets using thermal light. show that thermal light can be made bright enough to serve as our light source in a practical lidar system without the need of specialized targets. Buildings up to distances of 600\,m was measured with a depth resolution of at least 20\,cm was achieved.

\section{Experimental setup}
\begin{figure}[h]
\centering
\includegraphics[width=\columnwidth]{lidar_setup.eps}
% \vspace{\BeforeCaptionVSpace}
\caption{\label{fig:lidar_setup}
BS: Beamsplitter, DM: Dichoric mirror, f$_{1}=18.75$\,mm, f$_{2}=25.4$\,mm, f$_{3}=200$\,mm, f$_{4}=10.90$\,mm}
\end{figure}

\begin{figure}[h]
\centering
\includegraphics[width=\columnwidth]{1loop_g2.eps}
% \vspace{\BeforeCaptionVSpace}
\caption{\label{fig:1looop_g2}
Measured g2 function without amplification using PIN photodiodes}
\end{figure}

Our source of thermal light is generated with a fiber based n-emitter setup using with a laser light at 1550\,nm wavelength as input. The peak height and coherence time can be tuned by cascading interferometers and by changing the laser current. More details on the source can be found in. For this demonstration, we kept our setup simple by limiting to just 1 interferometer, and measured a g(2) peak of 1.40 with a coherence time of 10\,ns.

0.1\,\% of the light was sampled as a local reference beam and sent to a reference detector. The remainder is sent into an Erbium-doped fiber amplifier (EDFA), which provided control of optical power independent of laser current. It is interesting to note that the noise arising from spontaneous emission in the EDFA has minimal effect on g2. In figure 2, we plot our g2 measurements at different EDFA pump current values with minimal changes observed in the g2 peak. (Need to verify again and measure.)

The output of the EDFA is then sent to our transmitter telescope where the fiber output is first collimated with an aspheric lens followed by beam expansion with a pair of plano convex lens to reduce beam divergence. A dichoric mirror was included to have a separate optical path in the visible regime to assist in aiming. Aiming was done using a green visible laser and a camera to image the field of view.
The reflected scattered light was collected with an identical telescope and sent to a single photon detector. Both the reference and collection detector used are InGaAs single photon avalanche photodiodes each with 10\,\% detection efficiency and 500\,ps jitter. The result photodetection events are then timestamped with a resolution of X\,ns.

\section{Results}

\begin{figure}[h]
\centering
\includegraphics[width=\columnwidth]{600m_lidar.eps}
% \vspace{\BeforeCaptionVSpace}
\caption{\label{fig:600m_lidar}
g2 measurement off a building surface at 600\,m. Approximately 100\,ns coherence time and 300\,s integration time}
\end{figure}

\begin{figure}[h]
\centering
\includegraphics[width=\columnwidth]{2d_lidar_image.jpg}
% \vspace{\BeforeCaptionVSpace}
\caption{\label{fig:2d_lidar_image}
Image of telescope with optical tube diameter approximately 40\,cm imaged.}
\end{figure}

\begin{figure}[h]
\centering
\includegraphics[width=\columnwidth]{2d_lidar_scan.eps}
% \vspace{\BeforeCaptionVSpace}
\caption{\label{fig:2d_lidar_scan}
2d indices correspond to pixel coordinates. 120\, integration time per pixel. The top, bottom and middle of the optical tube can be clearly distinguished, showing a depth resolution of at least 20\,cm.}
\end{figure}

Would a separate figure with peak height values from the scan be useful...

Measurements to do 
\begin{itemize}
\item g2 before and after amplification at different pump currents, as well as with and without extra filtering
\item Raster scan singtel building
\item Raster scan car?
\item Create target consisting of different depths with 1cm step and measure to see what is the depth resolution?
\end{itemize}

Things to consider
\begin{itemize}
\item Can justin clock sync peak finding probability be used to put a limit on the integration time required?
\end{itemize}

\section{Conclusion and Outlook}
This can be combined with multiple baselines like in ... to yield resolution better than the diffraction limit of the telescopes.

\section{Acknowledgments}
This research is supported by the Quantum Engineering Programme through NRF2021-QEP2-03-P02, the Ministry of Education, and the National Research Foundation, Prime Minister's Office, Singapore.

\vfill
\bibliography{tlidar_bib}


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