Miracle-dz/UniFAR-FTUs huggingface dataset:
Battery‐Operated Mid‐Infrared Diode Laser Frequency Combs

Mid‐wave infrared (MIR, 3–5 µm) optical frequency combs (OFC) are of critical importance for spectroscopy of fundamental molecular transitions in space and terrestrial applications. Although in this band OFCs can be obtained via supercontinuum or difference frequency generation using optical pumping schemes, unprecedented source miniaturization, and monolithic design are unique to electrically‐pumped semiconductor laser structures. To date, high‐brightness OFC generation in this region has been demonstrated in quantum‐ and interband cascade lasers (QCL/ICL), yet with sub‐optimal spectral properties. Here, an MIR quantum well diode laser (QWDL) OFC is shown, whose excellent spectral uniformity, narrow optical linewidths, and milliwatt optical power are obtained at a fraction of a watt of power consumption. The continuously tunable source offers ≈1 THz of optical span centered at 3.04 µm, and a repetition rate of 10 GHz. As a proof‐of‐principle, a directly‐battery‐operated MIR dual‐comb source is shown with almost 0.5 THz of optical coverage accessible in the electrical domain in microseconds. These results indicate the high suitability of QWDL OFCs for future chip‐based real‐time sensing systems in the mid‐infrared.
Synchronized Front Propagation and Delayed Flame Quenching in Strain G-equation and Time-Periodic Cellular Flows

G-equations are level-set type Hamilton-Jacobi partial differential equations modeling propagation of flame front along a flow velocity and a laminar velocity. In consideration of flame stretching, strain rate may be added into the laminar speed. We perform finite difference computation of G-equations with the discretized strain term being monotone with respect to one-sided spatial derivatives. Let the flow velocity be the time-periodic cellular flow (modeling Rayleigh-B\'enard advection), we compute the turbulent flame speeds as the asymptotic propagation speeds from a planar initial flame front. In strain G-equation model, front propagation is enhanced by the cellular flow, and flame quenching occurs if the flow intensity is large enough. In contrast to the results in steady cellular flow, front propagation in time periodic cellular flow may be locked into certain spatial-temporal periodicity pattern, and turbulent flame speed becomes a piecewise constant function of flow intensity. Also the disturbed flame front does not cease propagating until much larger flow intensity.
Control of Aerodynamic Flows. Delivery Order 0051: Transition Prediction Method Review Summary for the Rapid Assessment Tool for Transition Prediction (RATTraP)

Abstract : The purpose of this report is to review available methods for predicting the transition of boundary layers. The emphasis will be on methods for transition mechanisms which are relevant to the flight conditions and geometric configurations of high altitude, long endurance aircraft, although the methods themselves may be much more general than this specific case. Each method will be evaluated according to certain criteria which are appropriate to the development of a computationally efficient, accurate and robust transition prediction module which is fully integrated into a general purpose CFD code. For each particular transition mechanism, a method will be selected which best satisfies all of the criteria.
Spectral analysis for compressible quantum fluids

Turbulent ﬂuid dynamics typically involves excitations on many diﬀerent length scales. Classical incompressible ﬂuids can be cleanly represented in Fourier space enabling spectral analysis of energy cascades and other turbulence phenomena. In quantum ﬂuids, additional phase information and singular behavior near vortex cores thwarts the direct extension of standard spectral techniques. We develop a formal and numerical spectral analysis for U (1) symmetry-breaking quantum ﬂuids suitable for analyzing turbulent ﬂows, with speciﬁc application to the Gross-Pitaevskii ﬂuid. Our analysis builds naturally on the canonical approach to spectral analysis of velocity ﬁelds in compressible quantum ﬂuids, and establishes a clear correspondence between energy spectral densities, power spectral densities, and autocorrelation functions, applicable to energy residing in velocity, quantum pressure, interaction, and potential energy of the ﬂuid. Our formulation includes all quantum phase information and also enables arbitrary resolution spectral analysis, a valuable feature for numerical analysis. A central vortex in a trapped planar Bose-Einstein condensate provides an analytically tractable example with spectral features of interest in both the infrared and ultraviolet regimes. Sampled distributions modeling the dipole gas, plasma, and clustered regimes exhibit velocity correlation length increasing with vortex energy, consistent with known qualitative behavior across the vortex clustering transition. The spectral analysis of compressible quantum ﬂuids presented here oﬀers a rigorous tool for analysing quantum features of superﬂuid turbulence in atomic or polariton condensates.
Exploitation of X-ray technology for the detection of contraband-aviation security applications

A number of methods are available for detecting contraband items in luggage. Perhaps the most powerful of these is the use of X ray, for the reason that humans rely heavily on their sense of vision and X ray technology gives us a convenient and unobtrusive way of visually revealing the contents of an item under inspection. The paper examines the use of this technology in the aviation security industry, from the simple systems that were used to detect weapons through to the advanced systems, which are operational today, for the automatic detection of explosive substances. The increase in air traffic has meant corresponding increased demand being made on security screening, Although the overriding performance consideration for the legislator is the detection capability, this, in reality, has to be balanced with other operational considerations. This compromise situation has shaped the way systems have been developed. The paper covers the application of X ray technology to security screening per se and the different modes of application which have produced a number of successful screening devices. In addition the programme of work carried out by PSDB, with DoT funding, is discussed, including some aspects of testing automatic explosive detection systems in conjunction with UK airports.
Learning Over All Stabilizing Nonlinear Controllers for a Partially-Observed Linear System

This letter proposes a nonlinear policy architecture for control of partially-observed linear dynamical systems providing built-in closed-loop stability guarantees. The policy is based on a nonlinear version of the Youla parameterization, and augments a known stabilizing linear controller with a nonlinear operator from a recently developed class of dynamic neural network models called the recurrent equilibrium network (REN). We prove that RENs are universal approximators of contracting and Lipschitz nonlinear systems, and subsequently show that the proposed Youla-REN architecture is a universal approximator of stabilizing nonlinear controllers. The REN architecture simplifies learning since unconstrained optimization can be applied, and we consider both a model-based case where exact gradients are available and reinforcement learning using random search with zeroth-order oracles. In simulation examples our method converges faster to better controllers and is more scalable than existing methods, while guaranteeing stability during learning transients.
No Intrinsic Decoherence of Inflationary Cosmological Perturbations

After a brief summary of the four main veins in the treatment of decoherence and quantum to classical transition in cosmology since the 1980s, we focus on one of these veins in the study of quantum decoherence of cosmological perturbations in inflationary universe, the case when it does not rely on any environment. This is what ‘intrinsic’ in the title refers to—a closed quantum system, consisting of a quantum field which drives inflation. The question is whether its quantum perturbations, which interact with the density contrast giving rise to structures in the universe, decohere with an inflationary expansion of the universe. A dominant view which had propagated for a quarter of a century asserts yes, based on the belief that the large squeezing of a quantum state after a duration of inflation renders the system effectively classical. This paper debunks this view by identifying the technical fault-lines in its derivations and revealing the pitfalls in its arguments which drew earlier authors to this wrong conclusion. We use a few simple quantum mechanical models to expound where the fallacy originated: The highly squeezed ellipse quadrature in phase space cannot be simplified to a line, and the Wigner function cannot be replaced by a delta function. These measures amount to taking only the leading order in the relevant parameters in seeking the semiclassical limit and ignoring the subdominant contributions where quantum features reside. Doing so violates the bounds of the Wigner function, and its wave functions possess negative eigenvalues. Moreover, the Robertson-Schrödinger uncertainty relation for a pure state is violated. For inflationary cosmological perturbations, in addition to these features, entanglement exists between the created pairs. This uniquely quantum feature cannot be easily argued away. Indeed, it could be our best hope to retroduce the quantum nature of cosmological perturbations and the trace of an inflation field. All this points to the invariant fact that a closed quantum system, even when highly squeezed, evolves unitarily without loss of coherence; quantum cosmological perturbations do not decohere by themselves.
Spanning Trees of a Claw-Free Graph Whose Reducible Stems Have Few Leaves

Let T be a tree. The reducible stem of T is the smallest subtree that contains all branch vertices of T. In this paper, we first use a new technique of Gould and Shull [5] to state a new short proof for a result of Kano et al. [10] on the spanning tree with a bounded number of leaves in a claw-free graph. After that, we use a similar idea to prove a sharp sufficient condition for a claw-free graph having a spanning tree whose reducible stem has few leaves.
Time-frequency Quantum Key Distribution over a Free-Space Optical Link

We present an implementation of the time-frequency (TF) quantum key distribution (QKD) protocol realized mainly with standard telecommunication components at 1550 nm. TF-QKD is implemented with modulations in time and frequency, namely pulse position modulation (PPM) and frequency shift keying (FSK). The time-frequency uncertainty relation ensures the security of the protocol. We further demonstrate free-space optical QKD transmission over a 388-m distance. Since the QKD setup is single-mode fiber (SMF) -based, precise coupling in and out of the SMFs is crucial. Thus, we implemented an optical tracking system. The QKD signal is wavelength-multiplexed with a strong beacon for optical tracking. Strong spectral filtering is necessary to separate beacon and QKD signal. Together with spatial filtering caused by the SMF most background light is filtered, enabling daylight QKD transmission.
Coupling function from bath density of states

Modelling of an open quantum system requires knowledge of parameters that specify how it couples to its environment. However, beyond relaxation rates, realistic parameters for specific environments and materials are rarely known. Here we present a method of inferring the coupling between a generic system and its bosonic (e.g., phononic) environment from the experimentally measurable density of states (DOS). With it we confirm that the DOS of the well-known Debye model for three-dimensional solids is physically equivalent to choosing an Ohmic bath. We further match a real phonon DOS to a series of Lorentzian coupling functions, allowing us to determine coupling parameters for gold, yttrium iron garnet (YIG) and iron as examples. The results illustrate how to obtain material-specific dynamical properties, such as memory kernels. The proposed method opens the door to more accurate modelling of relaxation dynamics, for example for phonon-dominated spin damping in magnetic materials.
An Introduction to Motility-Induced Phase Separation

Active particles may undergo phase separation when interactions oppose self-propulsion, in the absence of any cohesive forces. The corresponding Motility-Induced Phase Separation (MIPS) is arguably the simplest non-trivial collective feature that distinguishes active from passive particles. It is observed in a large variety of systems which we review in this chapter. We describe in depth the case of motile particles interacting via quorum-sensing interactions, whose theoretical framework is by now well-established. We close the chapter by discussing the features observed in systems undergoing MIPS that still challenge our understanding.
A Robust Completed Local Binary Pattern (RCLBP) for Surface Defect Detection

In this paper, we present a Robust Completed Local Binary Pattern (RCLBP) framework for a surface defect detection task. Our approach uses a combination of Non-Local (NL) means filter with wavelet thresholding and Completed Local Binary Pattern (CLBP) to extract robust features which are fed into classifiers for surface defects detection. This paper combines three components: A denoising technique based on Non-Local (NL) means filter with wavelet thresholding is established to denoise the noisy image while preserving the textures and edges. Second, discriminative features are extracted using the CLBP technique. Finally, the discriminative features are fed into the classifiers to build the detection model and evaluate the performance of the proposed framework. The performance of the defect detection models are evaluated using a real-world steel surface defect database from Northeastern University (NEU). Experimental results demonstrate that the proposed approach RCLBP is noise robust and can be applied for surface defect detection under varying conditions of intraclass and inter-class changes and with illumination changes.
Quantum computing Floquet band structures

Quantum systems can be dynamically controlled using time-periodic exter-nal ﬁelds, leading to the concept of Floquet engineering, with promising technological applications. Computing Floquet band structures is harder than only computing ground state properties or single time-dependent trajectories, and scales exponentially with the Hilbert space dimension. Especially for strongly correlated systems in the low frequency limit, classical approaches based on truncation break down. Here, we present two quantum algorithms to determine eﬀective Floquet modes and band structures. We combine the deﬁning properties of Floquet modes in time and frequency domains with the expressiveness of parameterized quantum circuits to overcome the limitations of classical approaches. We benchmark our algorithms and provide an analysis of the key properties relevant for near-term quantum hardware.
Alpha-robust investment-reinsurance strategy for a mean-variance insurer under a defaultable market

In this paper, we consider the robust optimal reinsurance investment problem of the insurer under the $\alpha$-maxmin mean-variance criterion in the defaultable market. The financial market consists of risk-free bonds, a stock and a defaultable bond. The insurer's surplus process is described by a L\'{e}vy insurance model. From the perspective of game theory, the extended Hamilton-Jacobi-Bellman equations are established for the post-default and pre-default conditions respectively. In both cases, the closed-form expressions and corresponding value functions of the robust optimal investment reinsurance strategies are derived. Finally, numerical examples and sensitivity analysis are used to illustrate the influence of parameters on the optimal strategies.
ESAFE: Enterprise Security and Forensics at Scale

Securing enterprise networks presents challenges in terms of both their size and distributed structure. Data required to detect and characterize malicious activities may be diffused and may be located across network and endpoint devices. Further, cyber-relevant data routinely exceeds total available storage, bandwidth, and analysis capability, often by several orders of magnitude. Real-time detection of threats within or across very large enterprise networks is not simply an issue of scale, but also a challenge due to the variable nature of malicious activities and their presentations. The system seeks to develop a hierarchy of cyber reasoning layers to detect malicious behavior, characterize novel attack vectors and present an analyst with a contextualized human-readable output from a series of machine learning models. We developed machine learning algorithms for scalable throughput and improved recall for our Multi-Resolution Joint Optimization for Enterprise Security and Forensics (ESAFE) solution. This Paper will provide an overview of ESAFE's Machine Learning Modules, Attack Ontologies, and Automated Smart Alert generation which provide multi-layer reasoning over cross-correlated sensors for analyst consumption.
Generation of multiple entangled fields via mechanical oscillator displacement

We present a convenient and efficient scheme to generate arbitrarily multipartite continuous-variable entanglement via mechanical oscillator displacement induced by two strong input pump fields in the conventional single-cavity optomechanical system. It is shown that multipartite entanglement among the outputs of the two pump fields and any number of relatively weak probe fields can be realized and optimized when the two pump fields with suitable amplitude ratio and relative initial phase are, respectively, tuned to the red and blue mechanical sidebands of a single cavity mode and each probe field is red-detuned by the mechanical frequency with respect to a different neighboring cavity mode. This method can, in principle, be extended to flexibly and conveniently generate arbitrarily multiple nondegenerate bright entangled fields by using only coherent laser fields, and may find promising applications in realistic quantum communication and networks.
Pareto Domain Adaptation

Domain adaptation (DA) attempts to transfer the knowledge from a labeled source domain to an unlabeled target domain that follows different distribution from the source. To achieve this, DA methods include a source classification objective to extract the source knowledge and a domain alignment objective to diminish the domain shift, ensuring knowledge transfer. Typically, former DA methods adopt some weight hyper-parameters to linearly combine the training objectives to form an overall objective. However, the gradient directions of these objectives may conflict with each other due to domain shift. Under such circumstances, the linear optimization scheme might decrease the overall objective value at the expense of damaging one of the training objectives, leading to restricted solutions. In this paper, we rethink the optimization scheme for DA from a gradient-based perspective. We propose a Pareto Domain Adaptation (ParetoDA) approach to control the overall optimization direction, aiming to cooperatively optimize all training objectives. Specifically, to reach a desirable solution on the target domain, we design a surrogate loss mimicking target classification. To improve target-prediction accuracy to support the mimicking, we propose a target-prediction refining mechanism which exploits domain labels via Bayes' theorem. On the other hand, since prior knowledge of weighting schemes for objectives is often unavailable to guide optimization to approach the optimal solution on the target domain, we propose a dynamic preference mechanism to dynamically guide our cooperative optimization by the gradient of the surrogate loss on a held-out unlabeled target dataset. Extensive experiments on image classification and semantic segmentation benchmarks demonstrate the effectiveness of ParetoDA
CoMPS: Continual Meta Policy Search

We develop a new continual meta-learning method to address challenges in sequential multi-task learning. In this setting, the agent's goal is to achieve high reward over any sequence of tasks quickly. Prior meta-reinforcement learning algorithms have demonstrated promising results in accelerating the acquisition of new tasks. However, they require access to all tasks during training. Beyond simply transferring past experience to new tasks, our goal is to devise continual reinforcement learning algorithms that learn to learn, using their experience on previous tasks to learn new tasks more quickly. We introduce a new method, continual meta-policy search (CoMPS), that removes this limitation by meta-training in an incremental fashion, over each task in a sequence, without revisiting prior tasks. CoMPS continuously repeats two subroutines: learning a new task using RL and using the experience from RL to perform completely offline meta-learning to prepare for subsequent task learning. We find that CoMPS outperforms prior continual learning and off-policy meta-reinforcement methods on several sequences of challenging continuous control tasks.
Broadband right-angle transition from substrate-integrated waveguide to rectangular waveguide

A broadband right-angle transition from a substrate-integrated waveguide (SIW) to a rectangular waveguide (RWG) is proposed. A coupling aperture etched on the broad wall of the SIW and two stepped ridges embedded in the RWG flange are designed for good matching between both waveguides. A Ka-band prototype is designed and fabricated. Good agreement between the measured and simulated results is obtained. The measured results show an insertion loss <;0.55 dB and a return loss below -15 dB from 31.3 to 38.35 GHz. This broadband transition may be used in microwave and millimetre-wave circuits and systems.
FUNDING ECOTOURISM CERTIFICATION PROGRAMS

By becoming more familiarized with the importance of sustaining the ecosystem, one may find the necessity of introducing the ecotourism to the world’s industry. Despite numerous attempts to draw unique definition, one may say that it deals with the fact that urges responsibility while traveling to natural areas and conserves the environment, as well as improves the well-being of local inhabitants. The paper gives a snapshot on the ecotourism essentials and presents the importance of applying ecotourism certification programs. Moreover, the paper poses the general and specific objectives stated in the specific ecotourism accreditation programs. The basic financial obstacles, with which tourism enterprises are faced, are noted in addition. In this line, the types and mechanisms for funding, as well as the major financial “players” are elaborated. Finally, the paper concludes that tourism businesses, which have identified the necessity of certifying ecotourism programs, needs unconditionally to follow the ecotourism principles.