Department Publications

This research presents a comprehensive experimental and simulation-based investigation aimed at enhancing the link distance and performance of indoor Visible Light Communication (VLC) systems. A basic VLC setup was incrementally improved by optimizing key system parameters, including LED transmit power, transimpedance amplifier (TIA) feedback resistor, lens configuration, photodiode selection, and wall color. Each enhancement was experimentally validated, and corresponding simulations were conducted to analyze system behavior and verify measurement results. The study also examines the applicability of well-established VLC channel models, such as the Masao Nakagawa model and second-reflection models, in real-world scenarios. The findings confirm that incorporating optical and environmental optimizations can significantly extend link distance, up to 3 m with high accuracy, while aligning …

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse solvers, the throughput of QPM is currently limited by the pixel-rate of the image sensors. Complementarily, to improve throughput further, here we propose to acquire images in a compressed form so that more information can be transferred beyond the existing hardware bottleneck of the image sensor. To this end, we present a numerical simulation of a learnable optical compression-decompression framework that learns content-specific features. The proposed differentiable quantitative phase microscopy (∂-QPM) first uses learnable optical processors as image compressors. The intensity representations produced by these optical processors are then captured by the …

With applications in quantitative metabolomics and label-free digital pathology, Quantitative Phase Microscopy (QPM) measures refractive index maps of thin transparent specimens like live cells or tissue sections. In QPM, refractive index maps are usually reconstructed from interference measurements of the object’s light field with respect to a reference field. To this end, many previous works focused on designing stable full-field interferometers from the bottom up. In this work, we present an alternative strategy to design a QPM system top-down, starting from the desired measurement outcomes, with no explicit knowledge about interferometry. We call our inverse design strategy Differentiable Microcopy. To this end, our Differentiable Microcopy approach designed a range of Fourier-filter-based QPM systems that do not require computational post-reconstruction. Our designs are superior to existing similar designs in …

Recently, various optical neural architectures have been designed to perform imaging and all-optical image processing. These designs consist of several optical masks with optimized transmission coefficients for the task. Designing sparse optical masks for them is important as it can promote different aspects of the design such as ease of fabrication and power efficiency of the design. To this end, inspired by the sparse filter designs, we propose training optical neural architectures with a regularization promoting sparsity in the masks. As preliminary results, we demonstrate a D2NN design for QPI achieving a sparsity of 33% with a performance degradation of only 12%.

Computational optical imaging (COI) systems leverage optical coding elements (CEs) in their setups to encode a high-dimensional scene in a single or in multiple snapshots and decode it by using computational algorithms. The performance of COI systems highly depends on the design of its main components: the CE pattern and the computational method used to perform a given task. Conventional approaches rely on random patterns or analytical designs to set distribution of the CE. However, the available data and algorithm capabilities of deep neural networks (DNNs) have opened a new horizon in CE data-driven designs that jointly consider the optical and computational decoders. Specifically, by modeling the COI measurements through a fully differentiable image-formation model that considers the physics-based propagation of light and its interaction with the CEs, the parameters that define the CE and the …

Since its introduction, diffractive deep neural networks (D2NN) have been an emerging technology with many useful applications, such as 3D object recognition, saliency segmentation, and quantitative phase microscopy. However, fabricating D2NNs operating in the visible range has not been performed due to the complexities of fabricating nano-scale elements. Recent advancements such as Implosion Fabrication have made it possible to fabricate such networks using a discrete number of phase weights. We propose a quantization-aware training approach for D2NNs through modeling the quantization process in a differentiable manner using a sigmoid-based quantization function, facilitating the fabrication process. We also propose an efficient training schedule to guide the optimization process to converge to a better minima despite the limited number of quantization levels. Our method is simulated and …

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. However, the speed of current QPM systems is limited by electronic hardware. To improve throughput further, here we propose differentiable optical-electronic quantitative phase microscopy (∂μ) that acquires images in a compressed form such that more information can be transferred beyond the electronic hardware bottleneck. The proposed microscopy uses optical feature extractors as image compressors. The resultant intensity distribution is then decompressed into QPM images by a reconstruction network. By optimizing optical-electronic parameters in an end-to-end manner, our method can improve the QPI throughput from Hours to Seconds (more than an order of magnitude).

Ever since the first microscope by Zacharias Janssen in the late 16th century, scientists have been inventing new types of microscopes for various tasks. Inventing a novel architecture demands years, if not decades, worth of scientific experience and creativity. In this work, we introduce Differentiable Microscopy (∂ µ), a deep learning-based design paradigm, to aid scientists design new interpretable microscope architectures. Differentiable microscopy first models a common physics-based optical system however with trainable optical elements at key locations on the optical path. Using pre-acquired data, we then train the model end-to-end for a task of interest. The learnt design proposal can then be simplified by interpreting the learnt optical elements. As a first demonstration, based on the optical 4-f system, we present an all-optical quantitative phase microscope (QPM) design that requires no computational post-reconstruction. A follow-up literature survey suggested that the learnt architecture is similar to the generalized phase concept developed two decades ago. We then incorporate the generalized phase contrast concept to simplify the learning procedure. Furthermore, we also demonstrate that similar results can be achieved by an uninterpretable learning based method, namely diffractive deep neural networks (D2NN). We outperform the existing benchmark for all-optical phase-to-intensity conversion on multiple datasets, and ours is the first demonstration of its kind on D2NNs. The proposed differentiable microscopy framework supplements the creative process of designing new optical systems and would perhaps lead to unconventional …

Designing new optical systems from the ground up for microscopy imaging tasks such as phase retrieval, requires substantial scientific expertise and creativity. To augment the traditional design process, we propose differentiable microscopy ( ), which introduces a top-down design approach. Using all optical phase retrieval as an illustrative example, we demonstrate the effectiveness of data-driven microscopy design through . Furthermore, we conduct comprehensive comparisons with existing all-optical phase retrieval methods, showcasing the consistent superiority of our learned designs across multiple datasets, including biological samples. To substantiate our ideas, we experimentally validate the functionality of one of the learned designs, providing a proof of concept. The proposed differentiable microscopy framework supplements the creative process of designing new phase microscopy systems and may be extended to other similar applications in optical design.

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse solvers, the throughput of QPM is currently limited by the speed of electronic hardware. Complementarily, to improve throughput further, here we propose to acquire images in a compressed form such that more information can be transferred beyond the existing electronic hardware bottleneck. To this end, we present a learnable optical compression-decompression framework that learns content-specific features. The proposed differentiable quantitative phase microscopy ( ) first uses learnable optical feature extractors as image compressors. The intensity representation produced by these networks is then captured by the imaging sensor. Finally, a reconstruction network running on electronic hardware decompresses the QPM images. In numerical experiments, the proposed system achieves compression of 64 while maintaining the SSIM of and PSNR of dB on cells. The results demonstrated by our experiments open up a new pathway for achieving end-to-end optimized (i.e., optics and electronic) compact QPM systems that may provide unprecedented throughput improvements.

Self-localization based on passive RFID-based has many potential applications. One of the main challenges it faces is the suppression of the reflected signals from unwanted objects (i.e., clutter). Typically, the clutter echoes are much stronger than the backscattered signals of the passive tag landmarks used in such scenarios. Therefore, successful tag detection can be very challenging. We consider two types of tags, namely low-Q and high-Q tags. The high-Q tag features a sparse frequency response, whereas the low-Q tag presents a broad frequency response. Further, the clutter usually showcases a short-lived response. In this work, we propose an iterative algorithm based on a low-rank plus sparse recovery approach (RPCA) to mitigate clutter and retrieve the landmark response. In addition to that, we compare the proposed approach with the well-known time-gating technique. It turns out that RPCA outperforms significantly time-gating for low-Q tags, achieving clutter suppression and tag identification when clutter encroaches on the time-gating window span, whereas it also increases the backscattered power at resonance by approximately 12 dB at 80 cm for high-Q tags. Altogether, RPCA seems a promising approach to improve the identification of passive indoor self-localization tag landmarks.

This paper discusses advances related to the integration of future mobile electronic THz systems. Without claiming to provide a comprehensive review of this surging research area, the authors gathered research on selected topics that are expected to be of relevance for the future exploration of components for practical mobile THz imaging and sensing applications. First, a brief technology review of integrated mobile THz components is given. Advances in III-V technology, silicon technology, and resonant-tunneling diodes (RTD) are discussed. Based on an RTD source and a SiGe-HBT direct detector, low-cost and compact computed tomography is presented for volumetric continuous-wave imaging at around 300 GHz. Moreover, aspects of system integration of mobile THz MIMO radars are discussed. Thereby, a novel phase-locked loop concept utilizing a high-stability yttrium-iron-garnet-tuned oscillator to …

We address the problem of identification of spherical objects, which are inside a layered structure by wireless sensing. Here, the backscatter response is used to identify the objects. It is a task, which is improved as the resolution gets higher. Therefore, to have a better resolution we consider the THz band. However, in the THz surface scattering expands the backscatter response of the layered structure in time. Thus, the backscatter response of the objects and the layered structure superimpose each other. This becomes even more severe due to the limited bandwidth at the receiver. In consequence, the exploitation of sophisticated signal separation methods for improved object identification is required. Therefore, we propose morphological component analysis (MCA), semi-blind MCA (MCA-SB) and singular value decomposition (SVD) methods. The MCA and MCA-SB rely on the sparse representation of signals …

Visible Light Communication (VLC) is emerging as a next generation data transmission method for short-range communication applications. In this paper we implement and characterize two prototype stereo audio streaming methods utilizing VLC. A software architecture is developed to process and stream data. The software architecture is bridged with a hardware section, which facilitates free-space VLC channel, over a Universal Serial Bus (USB) to serial interface. A particularly attractive feature of our system is that it uses commonly available, low-cost components which enables its implementation in everyday applications.

Tunable laser system requires high resolution and accuracy in position of the wave selective optical element, which can be attained through the use of stepper motor. This paper focuses on the stepper motor controller, with the feedback to improve the accuracy and the microstepping technique to improve the resolution. Sine cosine and trapezoidal current controlling techniques for the micro stepping are used in two different types of situations. The proposed controller uses the linear interpolation and sine cosine current controlling technique to double the rotation accuracy than the resolution of the encoder and detect the obstacle by using the encoder and the static characteristic of the stepper motor. Also, the variable step interval technique is proposed to overcome the speed variation in the trapezoidal current controlling technique. The simulation and the experimental results show that, proposed controller can …

Using a two-step, two-color laser spectroscopy technique, we have completed a measurement of the hyperfine structure within the excited state in . A frequency stabilized GaN diode laser at 410 nm is locked to the ground-state transition and a second 1291 nm diode laser is scanned over the transition to produce hyperfine spectra for the manifold. We find the hyperfine splittings of consecutive sublevels to be as follows: , , and . The magnetic dipole, electric quadrupole, and magnetic octupole hyperfine coupling constants derived from these three splittings are, respectively, , , and . The measured value of the dipole constant, , agrees to within 2% with a recent theoretical prediction.

The hyperfine splittings of the 6P 3/2 state of indium (I= 9/2) have been measured for the first time using a two-step, two-color excitation scheme. These results provide a precise experimental test of new ab initio wavefunction calculations of three-valence-electron atomic systems such as indium and thallium. We first excite ground-state atoms in a heated quartz indium cell to the intermediate 6S 1/2 state using a blue (GaN) diode laser at 410 nm. By measuring the differential atomic vapor cell absorption of double-passed, second-order-diffracted beams from an acousto-optic modulator, we are able to stabilize the blue laser frequency to the sub-MHz level [M. Gunawardena et al., Rev. Sci. Instrum. 79. 103110 (2008)]. A second laser beam at 1291 nm overlaps the first in the vapor cell, exciting Doppler-narrowed hyperfine transitions to the 6P 3/2 excited state. By modulating the blue laser beam and using lock-in …

We are pursuing a series of precise atomic structure measurements in Group III elements--currently thallium and indium--designed to test recent ab initio theory calculations in these three-valence-electron systems [Phys. Rev. A 74, 022504 (2006); Phys. Rev. A 76, 022501 (2007)]. For thallium, independent atomic theory calculations are essential for atomic tests of discrete symmetry violation. In an experiment just completed, we used two-step, two-color laser excitation to measure the hyperfine constants of the 6P 3/2 excited state of indium (I= 9/2) for the first time. Currently we are pursuing a similar two-step excitation experiment in thallium to measure the isotope shift and hyperfine splitting in the 7P 1/2 excited state using a heated quartz vapor cell. In both experiments, the blue laser for the first excitation step is locked to its transition using a new scheme which makes use of an acousto-optic modulator. The thallium …

We present a simple method for diode laser frequency stabilization that makes use of a Doppler-broadened vapor cell absorption signals of two frequency-shifted laser beams. Using second-order-diffracted, double-passed beams from an acousto-optic modulator, we achieve a frequency separation roughly equal to the Doppler half width. The differential transmission signals of the two beams provide an error signal with a very large linear feature, allowing frequency stabilization over a range of greater than 1 GHz by means of standard proportional-integral-derivative servo feedback to the piezoelectric control of the grating in our external cavity diode laser. We have applied this technique to two different diode laser systems, one used to lock to the 410 nm E1 transition in indium and another for locking to the M1/E2 transition in thallium at 1283 nm. In both cases the technique reduces frequency fluctuation to roughly 1 …

We are pursuing a series of precise atomic structure measurements in atomic thallium and indium designed to test new ab initio theory calculations in these three-valence-electron systems [Phys. Rev. A 74, 022504 (2006); Phys. Rev. A 76, 022501 (2007)]. For thallium, independent atomic theory calculations are essential for atomic tests of symmetry violation. In one experiment, using two-color laser excitation, the hyperfine constants of the 6P 3/2 excited state of indium (I= 9/2) have been measured for the first time. We excite ground-state atoms to the 6S 1/2 state using a stabilized 410 nm diode laser system. A second laser beam at 1291 nm overlaps the blue beam in a heated indium vapor cell, driving Doppler-narrowed hyperfine transitions to the 6P 3/2 excited state. By modulating the blue laser beam and using lock-in detection, we obtain background-free, low-noise IR spectra. Current statistical precision is at …

We have developed a two-color, two-pathway coherent control technique to detect and measure weak optical transitions in atoms by coherently beating the transition amplitude for the weak transition with that of a much stronger transition. We demonstrate the technique in atomic cesium, exciting the transition via a strong two-photon transition and a weak controllable Stark-induced transition. We discuss the enhancement in the signal-to-noise ratio for this measurement technique over that of direct detection of the weak transition rate, and project future refinements that may further improve its sensitivity and application to the measurement of other weak atomic interactions.

We report a precise determination of the static polarizability of the state of atomic cesium, carried out jointly through experimental measurements of the dc Stark shift of the transition using Doppler-free two-photon absorption and theoretical computations based on a relativistic all-order method. We enhance the precision of the measurement by imposing phase-modulation sidebands on the laser beam and by using a pair of vapor cells, one of which serves as a reference, and measuring the absorption spectrum in each cell with a single scan of the laser frequency. The measured value for the polarizability of the state is , in very good agreement with our theoretical value of . In addition, the small difference in the Stark shift measurement for the two hyperfine states that we examine yields a variation in the polarizability due to the magnetic dipole contact interaction of …

We describe a technique based upon the principles of two-pathway coherent control that allows one to amplify the magnitude of a weak atomic or molecular transition. In our initial demonstrations, we amplify a weak Stark-induced transition (the transition in atomic cesium) by coherently beating it with a stronger two-photon transition. We describe the measurements in detail, provide a quantitative discussion of the effects of beam overlap and alignment on the depth of modulation, and discuss the enhancement in the signal-to-noise ratio for this measurement technique over that of direct detection of the weak transition rate.

We demonstrate a powerful technique for detecting weak atomic or molecular transitions that is based on homodyning two atomic transition amplitudes. The scheme is tested on a weak Stark-induced transition in cesium by exciting its ground 6s^ 2S 1/2 state to the 8s^ 2S 1/2 excited state by a 411 nm laser field. The strong local oscillator signal is a two-photon transition excited by an 822 nm laser field that connects the same ground and exited states. The Stark-induced transition can be regulated by controlling a DC field across a Cs cell. The simultaneous excitation of the two pathways results in a quantum interference that can be controlled by phase modulating either of the driving laser fields. The change in the relative phase between the laser fields results in a change in the relative phase between the transition amplitudes of the two paths. Thus, phase modulating one of the beams gives rise to an amplitude …