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We posit that inconsistent interpretations of experimental data have led to inaccurate claims on metalens focusing efficiencies. By performing a meta-analysis,we show that extraordinary claims of high focusing efficiency at high numerical apertures are, unfortunately, not yet backed by rigorous simulation or experimental results. In this document, we have included the original comment and supplement, as well as the revised versions that correct the errors found in the original.

To lower the barrier to diffractive optical neural networks (DONNs) design, exploration, and deployment, we propose LightRidge, the first end-to-end optical ML compilation framework, which consists of (1) precise and differentiable optical physics kernels that enable complete explorations of DONNs architectures, (2) optical physics computation kernel acceleration that significantly reduces the runtime cost in training, emulation, and deployment of DONNs, and (3) versatile and flexible optical system modeling and user-friendly domain-specific-language (DSL). As a result, LightRidge framework enables efficient end-to-end design and deployment of DONNs, and significantly reduces the efforts for programming, hardware-software codesign, and chip integration. Our results are experimentally conducted with physical optical systems, where we demonstrate: (1) the optical physics kernels precisely correlated to low-level physics and systems, (2) significant speedups in runtime with physics-aware emulation workloads compared to the state-of-the-art commercial system, (3) effective architectural design space exploration verified by the hardware prototype and on-chip integration case study, and (4) novel DONN design principles including successful demonstrations of advanced image classification and image segmentation task using DONNs architecture and topology., Comment: 16 pages, 13 figures, Architectural Support for Programming Languages and Operating Systems (ASPLOS'24)

The phenomenon of resonant tunneling transport through polar double-barrier heterostructures is systematically investigated using a combined experimental and theoretical approach. On the experimental side, GaN/AlN RTDs are grown by MBE. In-situ electron diffraction is employed to monitor the number of monolayers incorporated into each tunneling barrier. Using this precise epitaxial control at the monolayer level, we demonstrate exponential modulation of the resonant tunneling current as a function of barrier thickness. Both the peak voltage and characteristic threshold bias exhibit a dependence on barrier thickness as a result of the intense electric fields present in the polar heterostructures. To get further insight into the asymmetric tunneling injection, we present an analytical theory for tunneling transport across polar heterostructures. A general expression for the resonant tunneling current with contributions from coherent and sequential tunneling processes is introduced. After applying this theory to the case of GaN/AlN RTDs, their experimental current-voltage characteristics are reproduced over both bias polarities, with tunneling currents spanning several orders of magnitude. This agreement allows us to elucidate the role played by the internal polarization fields on the magnitude of the tunneling current and broadening of the resonant line shape. Under reverse bias, we identify new tunneling features originating from highly attenuated resonant tunneling phenomena, which are completely captured by our model. Our analytical model, provides a simple expression which reveals the connection between the polar RTD design parameters and its current-voltage characteristics. This new theory paves the way for the design of polar resonant tunneling devices exhibiting efficient resonant current injection and enhanced tunneling dynamics, as required in various practical applications., Comment: 13 pages, 3 figures

We demonstrate a new substrate cleaning and buffer growth scheme in $\beta$-Ga$_2$O$_3$ epitaxial thin films using metalorganic vapor phase epitaxy (MOVPE). For the channel structure, a low-temperature (LT, 600 $^\circ$C) undoped Ga$_2$O$_3$ buffer is grown followed by transition layers to a high-temperature (HT, 810 $^\circ$C) Si-doped Ga$_2$O$_3$ channel layers without growth interruption. The (010) Ga$_2$O$_3$ Fe-doped substrate cleaning uses solvent cleaning followed by an additional HF (49% in water) treatment for 30 mins before the epilayer growth. This step is shown to compensate the parasitic Si channel at the epilayer-substrate interface that originates from the substrate polishing process or contamination from the ambient. SIMS analysis shows the Si peak atomic density at the substrate interface is several times lower than the Fe atomic density in the substrate - indicating full compensation. The elimination of the parasitic electron channel at the epi-substrate interface was also verified by electrical (capacitance-voltage profiling) measurements. In the LT-grown buffer layers, it is seen that the Fe forward decay tail from the substrate is very sharp with a decay rate of $\sim$ 9 nm$/$dec. These channels show record high electron mobility in the range of 196 - 85 cm$^2$/Vs in unintentionally doped and Si-doped films in the doping range of 2$\times$10$^{16}$ to 1$\times$10$^{20}$ cm$^{-3}$. Si delta-doped channels were also grown utilizing this substrate cleaning and the hybrid LT-buffers. Record high electron Hall mobility of 110 cm$^2$/Vs was measured for sheet charge density of 9.2$\times$10$^{12}$ cm$^{-2}$. This substrate cleaning combined with the LT-buffer scheme shows the potential of designing Si-doped $\beta$-Ga$_2$O$_3$ channels with exceptional transport properties for high performance gallium oxide-based electron devices., Comment: 20 pages, 10 figures

Diffractive optical neural networks have shown promising advantages over electronic circuits for accelerating modern machine learning (ML) algorithms. However, it is challenging to achieve fully programmable all-optical implementation and rapid hardware deployment. Furthermore, understanding the threat of adversarial ML in such system becomes crucial for real-world applications, which remains unexplored. Here, we demonstrate a large-scale, cost-effective, complex-valued, and reconfigurable diffractive all-optical neural networks system in the visible range based on cascaded transmissive twisted nematic liquid crystal spatial light modulators. With the assist of categorical reparameterization, we create a physics-aware training framework for the fast and accurate deployment of computer-trained models onto optical hardware. Furthermore, we theoretically analyze and experimentally demonstrate physics-aware adversarial attacks onto the system, which are generated from a complex-valued gradient-based algorithm. The detailed adversarial robustness comparison with conventional multiple layer perceptrons and convolutional neural networks features a distinct statistical adversarial property in diffractive optical neural networks. Our full stack of software and hardware provides new opportunities of employing diffractive optics in a variety of ML tasks and enabling the research on optical adversarial ML., Comment: 34 pages, 4 figures

We designed, fabricated and characterized a flat multi-level diffractive lens (MDL) comprised of only silicon with diameter = 15.2mm, focal length of 19mm, and operating over the longwave infrared (LWIR) spectrum of 8um to 14um. We experimentally demonstrated field of view of 46deg, depth of focus >7mm and wavelength-averaged Strehl ratio of 0.46. All these metrics were comparable to those of a conventional refractive lens. The active device thickness is only 8um and its weight (including the silicon substrate) is less than 0.2g.

Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing efforts on optical neural networks and optical computing based DNNs hardware, which bring significant advantages for deep learning systems in terms of their power efficiency, parallelism and computational speed. Among them, free-space diffractive deep neural networks (D$^2$NNs) based on the light diffraction, feature millions of neurons in each layer interconnected with neurons in neighboring layers. However, due to the challenge of implementing reconfigurability, deploying different DNNs algorithms requires re-building and duplicating the physical diffractive systems, which significantly degrades the hardware efficiency in practical application scenarios. Thus, this work proposes a novel hardware-software co-design method that enables robust and noise-resilient Multi-task Learning in D$^2$NNs. Our experimental results demonstrate significant improvements in versatility and hardware efficiency, and also demonstrate the robustness of proposed multi-task D$^2$NN architecture under wide noise ranges of all system components. In addition, we propose a domain-specific regularization algorithm for training the proposed multi-task architecture, which can be used to flexibly adjust the desired performance for each task., Comment: 23 pages including references and Supplementary Information. To appear in Nature Scientific Reports

The dynamics and performance of a two-coil resonant coupled wireless power transfer system are investigated. At high coupling, the frequency-splitting phenomenon occurs, in which the power transferred to the load attains its maximum at two frequencies away from the resonance frequency. However, this behavior is not a universal property; there exist certain regions of resonator intrinsic parameters in which it is not present for any coupling strength. Therefore, in order to suppress such a phenomenon, there is no need to constrain the coupling of the transmitter and receiver below a certain level as widely reported in the literature. For low-power applications, optimizing the received power is essential. We derive a rigorous asymptotic upper bound for the power that can be delivered to an arbitrary load from a generic source. Our results quantitatively reveal the direct impacts of the unloaded $Q-$factors of the two resonators and the coupling between them on the actual output power. We discuss that, in contrast to the often employed operating power gain, the transducer power gain constitutes a more suitable metric to optimize system efficiency. Once the transferred power reaches its physical bound, the two gains collapse to a unique global optimal solution., Comment: 14 pages

In this work, we demonstrate three ultra-compact integrated-photonics devices, which are designed via a machine-learning algorithm coupled with finite-difference time-domain (FDTD) modeling. Through digitizing the design domain into "binary pixels" these digital metamaterials are readily manufacturable as well. By showing a variety of devices (beamsplitters and waveguide bends), we showcase the generality of our approach. With an area footprint smaller than ${\lambda_0}^2$, our designs are amongst the smallest reported to-date. Our method combines machine learning with digital metamaterials to enable ultra-compact, manufacturable devices, which could power a new "Photonics Moore's Law."

This letter reports proof-of-principle demonstration of 3D printable, low-cost, and compact THz spectral splitters based on diffractive optical elements (DOEs) designed to disperse the incident collimated broadband THz radiation (0.5 THz - 0.7 THz) at a pre-specified distance. Via inverse design, we show that it is possible to design such a diffractive optic, which can split the broadband incident spectrum in any desired fashion, as is evidenced from both FDTD simulations and measured intensity profiles using a 500-750 GHz VNA. Due to its straightforward construction without the usage of any movable parts, our approach, in principle, can have various applications such as in portable, low-cost spectroscopy as well as in wireless THz communication systems as a THz demultiplexer., Comment: This work has been submitted to the IEEE for possible publication

The quasi-static anisotropic permittivity parameters of electrically insulating gallium oxide (beta-Ga2O3) were determined by terahertz spectroscopy. Polarization-resolved frequency domain spectroscopy in the spectral range from 200 GHz to 1 THz was carried out on bulk crystals along different orientations. Principal directions for permittivity were determined along crystallographic axes c, and b, and reciprocal lattice direction a*. No significant frequency dispersion in the real part of dielectric permittivity was observed in the measured spectral range. Our results are in excellent agreement with recent radio-frequency capacitance measurements as well as with extrapolations from recent infrared measurements of phonon mode and high frequency contributions, and close the knowledge gap for these parameters in the terahertz spectral range. Our results are important for applications of beta-Ga2O3 in high-frequency electronic devices, Comment: Main Manuscript is 6 pages long with 3 figures and 1 table. The submission also contains a Supplementary Info section

Multilevel diffractive lenses (MDLs) have emerged as an alternative to both conventional diffractive optical elements (DOEs) and metalenses for applications ranging from imaging to holographic and immersive displays. Recent work has shown that by harnessing structural parametric optimization of DOEs, one can design MDLs to enable multiple functionalities like achromaticity, depth of focus, wide-angle imaging, etc. with great ease in fabrication. Therefore, it becomes critical to understand how fabrication errors still do affect the performance of MDLs and numerically evaluate the trade-off between efficiency and initial parameter selection, right at the onset of designing an MDL, i.e., even before putting it into fabrication. Here, we perform a statistical simulation-based study on MDLs (primarily operating in the THz regime) to analyze the impact of various fabrication imperfections (single and multiple) on the final structure as a function of the number of ring height levels. Furthermore, we also evaluate the performance of these same MDLs with the change in the refractive index of the constitutive material. We use focusing efficiency as the evaluation criterion in our numerical analysis; since it is the most fundamental property that can be used to compare and assess the performance of lenses (and MDLs) in general designed for any application with any specific functionality., Comment: Initial manuscript version of the published article. Some comments were removed in the final published version at the discretion of the reviewers and not of the authors. However the authors would still like to include the discussion for the benefit of the optics community

Compound eyes found in insects provide intriguing sources of biological inspiration for miniaturized imaging systems. Inspired by such insect eye structures, we demonstrate an ultrathin arrayed camera enabled by a flat multilevel diffractive microlens array for super-resolution visible imaging. We experimentally demonstrated that the microlens array can achieve large fill factor (hexagonal close packing with pitch=120um), thickness of 2.6um, and diffraction-limited (strehl ratio = 0.88) achromatic performance in the visible band (450nm to 650nm). We also demonstrate super-resolution imaging with resolution improvement of 1.4 times by computationally merging 1600 images in the array.

We demonstrate an inverse designed achromatic, flat, polarization-insensitive diffractive optic element, i.e., multilevel diffractive lens (MDL), operating across a broadband range of UV light (250 nm - 400 nm) via numerical simulations. The simulated average on-axis focusing efficiency of the MDL is optimized to be as high as ~86%. We also investigate the off-axis focusing characteristics at different incident angles of the incoming UV radiation such that the MDL has a full field of view of 30 degrees. The simulated average off-axis focusing efficiency is ~67%, which is the highest reported till date for any chromatic or achromatic UV metalens or diffractive lens to the best of our knowledge. The designed MDL is composed of silicon nitride. The work reported herein will be useful for the miniaturization and integration of lightweight and compact UV optical systems., Comment: accepted for publication in OSA Continuum

It is generally thought that correcting chromatic aberrations in imaging requires multiple surfaces. Here, we show that by allowing the phase in the image plane of a flat lens to be a free parameter, it is possible to correct chromatic aberrations over a large continuous bandwidth with a single diffractive surface. We experimentally demonstrate imaging using a single flat lens of diameter > 3mm, focal length = 5mm (NA = 0.3, f/1.59) that is achromatic from 0.45um to 1um. This combination of size, NA and operating bandwidth has not been demonstrated in a flat lens before. We experimentally characterized the point-spread functions, off-axis aberrations and the broadband imaging performance. In contrast to conventional lens design, we utilize inverse design, where phase in the focal plane is treated as a free parameter. This approach attains a phase-only (lossless) pupil function, which can be implemented as a multi-level diffractive flat lens that achieves achromatic focusing and imaging., Comment: arXiv admin note: text overlap with arXiv:1907.06251

To date, various optimization algorithms have been employed to design and improve the performance of nanophotonic structures. Here, we propose to utilize a machine-learning algorithm viz. binary-Additive Reinforcement Learning Algorithm (b-ARLA) coupled with finite-difference time-domain (FDTD) simulations to design ultra-compact and efficient on-chip integrated nanophotonic 50:50 beam splitters (T-junctions). Here we present the design of two T-junction splitters each with a footprint of only 1.2 $\mu$m x 1.2 $\mu$m. To the best of our knowledge, these designs are amongst the smallest ever reported till date across either simulations or experiments. The simulated net power transmission efficiency for the first T-junction design is ~ 82% and the second design is ~ 80% $at 4\lambda = 1.55 \mu$m. We envision that the design methodology, as reported herein, would be useful in general for designing any efficient integrated-photonic device for optical communications systems.

Flat lenses enable thinner, lighter, and simpler imaging systems. However, large-area and high-NA flat lenses have been elusive due to computational and fabrication challenges. Here, we applied inverse design to create a multi-level diffractive lens (MDL) with thickness <1.35{\mu}m, diameter of 4.13mm, NA=0.9 at wavelength of 850nm. Since the MDL is created in polymer, it can be cost-effectively replicated via imprint lithography.

It is generally assumed that correcting chromatic aberrations in imaging requires optical elements. Here, we show that by allowing the phase in the image plane to be a free parameter, it is possible to correct chromatic variation of focal length over an extremely large bandwidth, from the visible (Vis) to the longwave infrared (LWIR) wavelengths using a single diffractive surface, i.e., a flat lens. Specifically, we designed, fabricated and characterized a flat, multi-level diffractive lens (MDL) with thickness {\pounds} 10{\mu}m, diameter ~1mm, and focal length = 18mm, which was constant over the operating bandwidth of l=0.45{\mu}m (blue) to 15{\mu}m (LWIR). We experimentally characterized the point-spread functions, aberrations and imaging performance of cameras comprised of this MDL and appropriate image sensors. We further show using simulations that such extreme achromatic MDLs can be achieved even at high numerical apertures (NA=0.81). By drastically increasing the operating bandwidth and eliminating several refractive lenses, our approach enables thinner, lighter and simpler imaging systems., Comment: arXiv admin note: substantial text overlap with arXiv:1907.06251

A lens performs an approximately one-to-one mapping from the object to the image planes. This mapping in the image plane is maintained within a depth of field (or referred to as depth of focus, if the object is at infinity). This necessitates refocusing of the lens when the images are separated by distances larger than the depth of field. Such refocusing mechanisms can increase the cost, complexity and weight of imaging systems. Here, we show that by judicious design of a multi-level diffractive lens (MDL) it is possible to drastically enhance the depth of focus, by over 4 orders of magnitude. Using such a lens, we are able to maintain focus for objects that are separated by as large as ~6m in our experiments. Specifically, when illuminated by collimated light at lambda=0.85mm, the MDL produced a beam that remained in focus from 5mm to ~1500mm from the MDL. The measured full-width at half-maximum of the focused beam varied from 6.6um (5mm away from MDL) to 524um (1500mm away from MDL). Since the sidelobes were well suppressed and the main-lobe was close to the diffraction-limit, imaging with a horizontal X vertical field of view of 20deg x 15deg over the entire focal range was demonstrated. This demonstration opens up a new direction for lens design, where by treating the phase in the focal plane as a free parameter, extreme depth-of-focus imaging becomes possible., Comment: arXiv admin note: text overlap with arXiv:1907.06251

We designed and fabricated a flat multi-level diffractive lens (MDL) that is achromatic in the SWIR band (875nm to 1675nm). The MDL had a focal length of 25mm, aperture diameter of 8.93mm and thickness of only 2.6um. By pairing the MDL with a SWIR image sensor, we also characterized its imaging performance in terms of the point-spread functions, modulation-transfer functions, and still and video imaging.

It is generally thought that correcting chromatic aberrations in imaging requires multiple surfaces. Here, we show that by allowing the phase in the image plane of a flat lens to be a free parameter, it is possible to correct chromatic aberrations over an almost unlimited bandwidth with a single diffractive surface. Specifically, we designed, fabricated and characterized a flat multi-level diffractive lens (MDL) that images at the wavelengths from 450nm to 850nm. We experimentally characterized the focusing efficiency, modulation-transfer function, wavefront aberrations, vignetting, distortion and signal-to-noise ratio performance of a camera comprised of this MDL and a conventional image sensor. Further, we designed two MDLs with operating wavelengths from 500nm to 15{\mu}m, and from 2{\mu}m to 150{\mu}m, respectively. With no apparent limitation in the operating bandwidth, such flat lenses could replace multiple refractive surfaces that are traditionally required for chromatic corrections, leading to thinner, lighter and simpler imaging systems with bandwidth limited primarily by the quantum efficiency of the sensor.

We experimentally demonstrate imaging in the longwave-infrared (LWIR) spectral band (8um to 12um) using a single polymer flat lens based upon multi-level diffractive optics. The device thickness is only 10{\mu}m, and chromatic aberrations are corrected over the entire LWIR band with one surface. Due to the drastic reduction in device thickness, we are able to utilize polymers with absorption in the LWIR, allowing for inexpensive manufacturing via imprint lithography. The weight of our lens is less than 100 times those of comparable refractive lenses. We fabricated and characterized two different flat lenses. Even with about 25% absorption losses, experiments show that our flat polymer lenses obtain good imaging with field of view of ~35degrees and angular resolution less than 0.013 degrees. The flat lenses were characterized with two different commercial LWIR image sensors. Finally, we show that by using lossless, higher-refractive-index materials like silicon, focusing efficiencies in excess of 70% can be achieved over the entire LWIR band. Our results firmly establish the potential for lightweight, ultra-thin, broadband lenses for high-quality imaging in the LWIR band.

Recently, there has been an explosion of interest in metalenses for imaging. The interest is primarily based on their sub-wavelength thicknesses. Diffractive lenses have been used as thin lenses since the late 19th century. Here, we show that multi-level diffractive lenses (MDLs), when designed properly can exceed the performance of metalenses. Furthermore, MDLs can be designed and fabricated with larger constituent features, making them accessible to low-cost, large area volume manufacturing, which is generally challenging for metalenses. The support substrate will dominate overall thickness for all flat optics. Therefore the advantage of a slight decrease in thickness (from ~2{\lambda} to ~{\lambda}/2) afforded by metalenses may not be useful. We further elaborate on the differences between these approaches and clarify that metalenses have unique advantages when manipulating the polarization states of light., Comment: 4 figures, 2 tables

Three-dimensional (3D) semimetals have been predicted and demonstrated to have a wide variety of interesting properties associated with its linear energy dispersion. In analogy to two-dimensional (2D) Dirac semimetals, such as graphene, Cd3As2, a 3D semimetal, has shown ultra-high mobility, large Fermi velocity, and has been hypothesized to support plasmons at terahertz frequencies. In this work, we demonstrate synthesis of high-quality large-area Cd3As2 thin-films through thermal evaporation as well as the experimental realization of plasmonic structures consisting of periodic arrays of Cd3As2 stripes. These arrays exhibit sharp resonances at terahertz frequencies with associated quality-factors (Q) as high as ~ 3.7. Such spectrally-narrow resonances can be understood on the basis of a large kinetic-inductance, resulting from a long momentum scattering time, which in our films can approach ~1 ps at room-temperature. Moreover, we demonstrate an ultrafast tunable response through excitation of photo-induced carriers in optical pump / terahertz probe experiments. Our results evidence that the intrinsic 3D nature of Cd3As2 provides for a very robust platform for terahertz plasmonic applications. Overall, our observations pave a way for the development of myriad terahertz (opto) electronic devices based on Cd3As2 and other 3D Dirac semimetals, benefiting from strong coupling of terahertz radiation, ultrafast transient response, magneto-plasmon properties, etc. Moreover, the long momentum scattering time, thus large kinetic inductance in Cd3As2, also holds enormous potential for the re-design of passive elements such as inductors and hence can have a profound impact in the field of RF integrated circuits., Comment: 32 pages, 8 figures

We describe studies on the nanoscale transport dynamics of carriers in strained AlN/GaN/AlN quantum wells: an electron-hole bilayer charge system with large difference in transport properties between the two charge layers. From electronic band diagram analysis, the presence of spatially separated two-dimensional electron and hole charge layers is predicted at opposite interfaces. Since these charge layers exhibit distinct spectral signatures at terahertz frequencies, a combination of terahertz and far-infrared spectroscopy enables us to extract (a) individual contributions to the total conductivity, as well as (b) effective scattering rates for charge-carriers in each layer. Furthermore, by comparing direct-current and terahertz extracted conductivity levels, we are able to determine the extent to which structural defects affect charge transport. Our results evidence that (i) a non-unity Hall-factor and (ii) the considerable contribution of holes to the overall conductivity, lead to a lower apparent mobility in Hall-effect measurements. Overall, our work demonstrates that terahertz spectroscopy is a suitable technique for the study of bilayer charge systems with large differences in transport properties between layers, such as quantum wells in III-Nitride semiconductors., Comment: Applied Physics Letters

We propose and discuss terahertz electro-absorption modulators based on graphene plasmonic structures. The active device consists of a self-gated pair of graphene layers, which are patterned to structures supporting THz plasmonic resonances. These structures allow for efficient control of the effective THz optical conductivity, thus absorption, even at frequencies much higher than the Drude roll-off in graphene where most previously proposed graphene-based devices become inefficient. Our analysis shows that reflectance-based device configurations, engineered so that the electric field is enhanced in the active graphene pair, could achieve very high modulation-depth, even ~100%, at any frequency up to tens of THz.

Switchable metamaterials offer unique solutions for efficiently manipulating electromagnetic waves, particularly for terahertz waves, which has been difficult since naturally occurring materials rarely respond to terahertz frequencies controllably. However, few terahertz modulators demonstrated to date exhibit simultaneously low attenuation and high modulation depth. In this letter we propose a new class of electrically-tunable terahertz metamaterial modulators employing metallic frequency-selective-surfaces (FSS) in conjunction with capacitively-tunable layers of electrons, promising near 100% modulation depth and < 15% attenuation. The fundamental departure in our design from the prior art is tuning enabled by self-gated electron layers that is independent from the metallic FSS. Our proposal is applicable to all possible electrically tunable elements including graphene, Si, MoS2, oxides etc, thus opening up myriad opportunities for realizing high performance switchable metamaterials over an ultra-wide terahertz frequency range.

The modulation depth of 2-D electron gas (2DEG) based THz modulators using AlGaAs/GaAs heterostructures with metal gates is inherently limited to < 30%. The metal gate not only attenuates the THz signal (> 90%) but also severely degrades the modulation depth. The metal losses can be significantly reduced with an alternative material with tunable conductivity. Graphene presents a unique solution to this problem due to its symmetric band structure and extraordinarily high mobility of holes that is comparable to electron mobility in conventional semiconductors. The hole conductivity in graphene can be electrostatically tuned in the graphene-2DEG parallel capacitor configuration, thus more efficiently tuning the THz transmission. In this work, we show that it is possible to achieve a modulation depth of > 90% while simultaneously minimizing signal attenuation to < 5% by tuning the Fermi level at the Dirac point in graphene., Comment: 15 pages, 3 figures, 1 table