Search

The intensity noise of a laser source represents one of the key factors limiting the ultimate sensitivity in laser-based systems for sensing and telecommunication. For advanced applications based on interferometry, the availability of a shot-noise-limited local oscillator is even more important for the effective feasibility of high-precision measurements. This is particularly crucial in quantum optics applications based on homodyne detection schemes to measure non-classical light states, such as squeezed states. This work deeply investigates and analyzes the intensity noise features of the most widely used mid-infrared semiconductor heterostructured lasers: quantum cascade and interband cascade lasers. For this purpose, a comprehensive comparison of three different continuous-wave lasers operating at room temperature around 4.5 {\mu}m wavelength is presented. First, a thorough electro-optical characterization is given, highlighting the differences and the shared common characteristics of the tested devices. Then, a detailed intensity noise analysis is reported, identifying their different noise operations with a particular reference to shot-noise-limited operations. Finally, some perspectives towards advanced applications are discussed., Comment: 17 pages, 5 figures

Angle-of-Arrival estimation technology, with its potential advantages, emerges as an intriguing choice for indoor localization. Notably, it holds the promise of reducing installation costs. In contrast to ToF/TDoA based systems, AoA-based approaches require a reduced number of nodes for effective localization. This characteristic establishes a trade-off between installation costs and the complexity of hardware and software. Moreover, the appeal of acoustic localization is further heightened by its capacity to provide cost-effective hardware solutions while maintaining a high degree of accuracy. Consequently, acoustic AoA estimation technology stands out as a feasible and compelling option in the field of indoor localization. Sparse arrays additionally have the ability to estimate the DoA of more sources than available sensors by placing sensors in a specific geometry. In this contribution, we introduce a measurement platform designed to evaluate various sparse array geometries experimentally. The acoustic microphone array comprises 64 microphones arranged in an 8x8 grid, following an Uniform Rectangular Array (URA) configuration, with a grid spacing of 8.255 mm. This configuration achieves a spatial Nyquist frequency of approximately 20.8 kHz in the acoustic domain at room temperature. Notably, the array exhibits a mean spherical error of 1.26{\deg} when excluding higher elevation angles. The platform allows for masking sensors to simulate sparse array configurations. We assess four array geometries through simulations and experimental data, identifying the Open-Box and Nested array geometries as robust candidates. Additionally, we demonstrate the array's capability to concurrently estimate the directions of three emitting sources using experimental data, employing waveforms consisting of orthogonal codes., Comment: Submitted for review to the IEEE Journal of Indoor and Seamless Positioning and Navigation (J-ISPIN) in April 24

Many precision applications in the mid-infrared spectral range have strong constraints based on quantum effects that are expressed in particular noise characteristics. They limit, e.g., sensitivity and resolution of mid-infrared imaging and spectroscopic systems as well as the bit-error rate in optical free-space communication. Interband cascade lasers (ICLs) are a class of mid-infrared laser exploiting interband transitions in type-II band alignment geometry. They are currently gaining significant importance for mid-infrared applications from <3 {\mu}m to >6 {\mu}m wavelength, enabled by novel types of high-performance ICLs such as ring-cavity devices. Their noise-behavior is an important feature that still needs to be thoroughly analyzed, including its potential reduction with respect to the shot noise limit. In this work, we provide a comprehensive characterization of {\lambda} = 3.8 {\mu}m-emitting, continuous-wave ring-ICLs operating at room temperature. It is based on an in-depth study of their main physical intensity noise features, such as their bias-dependent intensity noise power spectral density (INPSD) and relative intensity noise (RIN). We obtain shot-noise-limited statistics for Fourier frequencies above 100 kHz. This is an important result for precision applications, e.g. interferometry or advanced spectroscopy, which benefit from exploiting the advantage of using such a shot-noise limited source, enhancing the setup sensitivity. Moreover, it is an important feature for novel quantum optics schemes including testing specific light states below the shot noise level, such as squeezed states.

In this paper, we propose to exploit the side-tuning framework for multimodal document classification. Side-tuning is a methodology for network adaptation recently introduced to solve some of the problems related to previous approaches. Thanks to this technique it is actually possible to overcome model rigidity and catastrophic forgetting of transfer learning by fine-tuning. The proposed solution uses off-the-shelf deep learning architectures leveraging the side-tuning framework to combine a base model with a tandem of two side networks. We show that side-tuning can be successfully employed also when different data sources are considered, e.g. text and images in document classification. The experimental results show that this approach pushes further the limit for document classification accuracy with respect to the state of the art., Comment: 2020 25th International Conference on Pattern Recognition (ICPR)

The recent development of Quantum Cascade Lasers (QCLs) represents one of the biggest opportunities for the deployment of a new class of Free Space Optical (FSO) communication systems working in the mid-infrared (Mid-IR) wavelength range. As compared to more common FSO systems exploiting the telecom range, the larger wavelength employed in Mid-IR systems delivers exceptional benefits in case of adverse atmospheric conditions, as the reduced scattering rate strongly suppresses detrimental effects on the FSO link length given by the presence of rain, dust, fog and haze. In this work, we use a novel FSO testbed operating at \SI{4.7}{\micro m}, to provide a detailed experimental analysis of noise regimes that could occur in realistic FSO Mid-IR systems based on QCLs. Our analysis reveals the existence of two distinct noise regions, corresponding to different realistic channel attenuation conditions, which are precisely controlled in our setup. To relate our results with real outdoor configurations, we combine experimental data with predictions of an atmospheric channel loss model, finding that error-free communication could be attained for effective distances up to 8~km in low visibility conditions of 1 km. Our analysis of noise regimes may have a key relevance for the development of novel, long-range FSO communication systems based on Mid-IR QCL sources

A novel study on harmonic frequency combs emitted by Quantum Cascade Lasers (QCLs) is here presented, demonstrating the presence of intensity correlations between twin modes characterising the emission spectra. These originate from a Four-Wave Mixing (FWM) process driven by the active medium's third-order non-linearity. The study of such correlations is essential for the engineering of a new generation of semiconductor devices with the potential of becoming integrated emitters of light with quantum properties, such as squeezing and entanglement. Starting from experimental results, the limits of state-of-the-art technology are discussed as well as the possible methodologies that could lead to the detection of non-classical phenomena, or alternatively improve the design of QCLs, in the compelling perspective of generating quantum correlations in mid-infrared light., Comment: 14 pages, 6 figures

This work marks an important progress towards practical quantum optical technologies in the continuous variable regime, as it shows the feasibility of experiments where non-Gaussian state generation entirely relies on plug-&-play components from guided-wave optics technologies. This strategy is demonstrated experimentally with the heralded preparation of low amplitude Schr\"odinger cat states based on single-photon subtraction from a squeezed vacuum. All stages of the experiment are based on off-the-shelf fiber components. This leads to a stable, compact, and easily re-configurable realization, fully compatible with existing fibre networks and, more in general, with future out-of-the-laboratory applications.

Meta-solver approaches exploits a number of individual solvers to potentially build a better solver. To assess the performance of meta-solvers, one can simply adopt the metrics typically used for individual solvers (e.g., runtime or solution quality), or employ more specific evaluation metrics (e.g., by measuring how close the meta-solver gets to its virtual best performance). In this paper, based on some recently published works, we provide an overview of different performance metrics for evaluating (meta-)solvers, by underlying their strengths and weaknesses.

Quantum cascade laser frequency combs are nowadays well-appreciated sources for infrared spectroscopy. Here their applicability for free-space optical communication is demonstrated. The spontaneously-generated intermodal beat note of the frequency comb is used as carrier for transferring the analog signal via frequency modulation. Exploiting the atmospheric transparency window at 4 $\mu$m, an optical communication with a signal-to-noise ratio up to 65 dB is realized, with a modulation bandwidth of 300 kHz. The system tolerates a maximum optical attenuation exceeding 35 dB. The possibility of parallel transmission of an independent digital signal via amplitude modulation at 5 MS/s is also demonstrated., Comment: 17 pages, 13 figures

This paper proposes two efficient and easy-to-use error mitigation solutions to the problem of three-dimensional (3-D) angle-of-arrival (AOA) source localization in the mixed line-of-sight (LOS) and non-line-of-sight (NLOS) indoor environments. A weighted linear least squares estimator is derived first for the LOS AOA components in terms of the direction vectors of arrival, albeit in a sub-optimal manner. Next, data selection exploiting the sum of squared residuals is carried out to discard the error-prone NLOS connections. In so doing, the first approach is constituted and more accurate closed-form location estimates can be obtained. The second method applies a simulated annealing stochastic framework to realize the robust $\ell_1$-minimization criterion, which therefore falls into the methodology of statistical robustification. Computer simulations and ultrasonic onsite experiments are conducted to evaluate the performance of the two proposed methods, demonstrating their outstanding positioning results in the respective scenarios., Comment: This paper has been accepted for oral presentation at 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 29 Nov. -- 2 Dec. 2021, Lloret de Mar, Spain

We present the characterization of a novel balanced homodyne detector operating in the mid-infrared. The challenging task of revealing non-classicality in mid-infrared light, e.~g. in quantum cascade lasers emission, requires a high-performance detection system. Through the intensity noise power spectral density analysis of the differential signal coming from the incident radiation, we show that our setup is shot-noise limited. We discuss the experimental results with a view to possible applications to quantum technologies, such as free-space quantum communication., Comment: 15 pages, 6 figures

Programming language detection is a common need in the analysis of large source code bases. It is supported by a number of existing tools that rely on several features, and most notably file extensions, to determine file types. We consider the problem of accurately detecting the type of files commonly found in software code bases, based solely on textual file content. Doing so is helpful to classify source code that lack file extensions (e.g., code snippets posted on the Web or executable scripts), to avoid misclassifying source code that has been recorded with wrong or uncommon file extensions, and also shed some light on the intrinsic recognizability of source code files. We propose a simple model that (a) use a language-agnostic word tokenizer for textual files, (b) group tokens in 1-/2-grams, (c) build feature vectors based on N-gram frequencies, and (d) use a simple fully connected neural network as classifier. As training set we use textual files extracted from GitHub repositories with at least 1000 stars, using existing file extensions as ground truth. Despite its simplicity the proposed model reaches 85% in our experiments for a relatively high number of recognized classes (more than 130 file types).