Coordinating large-scale, heterogeneous building aggregations for demand response (DR) is impeded by a dual challenge: the computational intractability of centralized Model Predictive Control (MPC) and the inadequacy of conventional feature selection methods, which fail to address the error-compounding nature of multi-step forecasting required by MPC. This paper proposes a comprehensive, data-driven framework that first employs a systematic, MPC-aware feature selection methodology to ensure robust multi-step prediction, then models the complex building dynamics using a novel Input-Convex Encoder-Only Transformer (IC-EoT) to guarantee a convex optimization problem, and finally solves the resulting constraint-coupled problem (CCP) in a fully distributed manner using the Tracking Alternating Direction Method of Multipliers (ADMM) algorithm. The framework is validated in a high-fidelity co-simulation environment, controlling a heterogeneous aggregation of consumer and prosumer buildings based on the EnergyPlus under a dynamic time-of-use (TOU) tariff. Results demonstrate that the proposed distributed approach achieves near-identical economic optimality and superior thermal comfort compared to a theoretical centralized controller, while exhibiting exceptional computational scalability that overcomes the real-time infeasibility of the centralized approach for large aggregations.

We consider the closure of three classical combination properties, namely, stable infiniteness, gentleness and shininess (or, equivalently for decidable theories, strong politeness), under intersection and combinability. We compute every possible intersection, and then compute the maximal set of theories that can be combined with each resulting intersection. We iterate this process until no new sets are identified. How many properties will we end up with?

We present a detailed characterisation of radio frequency interference (RFI) in the 2.4 GHz band around Murriyang, CSIRO's Parkes radio telescope. The dominant sources of interference are Wi-Fi and Bluetooth transmissions. We quantify how the intensity and directionality of this RFI vary with time of day and document its evolution over several years. Although most observers currently discard data within this band, our analysis shows that the interference is confined in both timeand frequency and can be effectively mitigated. Using 10 seconds of 16-bit voltage data recorded during observations of the Vela Pulsar (PSR J0835-4510), we demonstrate that the majority of the channelised data remain unaffected by RFI. We compare three RFI detection and mitigation algorithms and evaluate their relative performance. All methods perform effectively, and any could be implemented in real time to enable productive use of this observing band. A real time implementation would allow the scientific use of this 128 MHz observing band to increase, from almost 70% of the band being completely unusable all of the time, to over 90% of becoming accessible for science. Given its simplicity and efficiency, a basic power-threshold approach offers a relatively straightforward solution.

The reversible stress limit (\mathit{R}_{rev}) of second-generation high-temperature superconducting (2G-HTS) tapes is a critical performance indicator, typically characterized through uniaxial tensile testing. In practice, the accuracy of the measured Rrev value is often compromised by stress concentration induced by the voltage tap solder joint. The present study investigates the underlying interference mechanism using integrated experimental and numerical methods. Mechanistic analysis reveals that under uniaxial tensile loading, the local geometric inhomogeneity introduced by the solder joint induces an external, bending-like stress in the vicinity of the solder joint, transitioning from additional tensile stress in the zone adjacent to the joint to additional compressive stress in the zone remote from it. When the solder joint is attached to the front surface of the tape (the side closer to the superconducting layer), the superconducting layer experiences localized additional tensile stress, triggering premature damage and early \mathit{I}_{c} degradation. Consequently, an optimized back-surface soldering approach is proposed, which positions the superconducting layer in a localized compressive zone. Experimental validation demonstrates that the proposed approach effectively mitigates testing errors for various tape configurations. Notably, for the tape with a copper layer thickness of 5 μm, the measured \mathit{R}_{rev} increased from 546 MPa to 734 MPa, corresponding to a 42% increase, and moved closer to the actual value. The findings provide essential insights for the precision characterization of the electromechanical performances (EMPs) of 2G-HTS tapes.

The classical Liouville theorem states that every bounded harmonic function on Euclidean space is constant. On complete Rie mannian manifolds, analogous conclusions hold under geometric as sumptions such as nonnegative Ricci curvature. The quadratic Wasserstein space $\mathcal{P}_2(M)$ is often regarded (following Otto) as an infinite-dimensional Riemannian manifold; however, it has no canonical infinite-dimensional Riemannian volume and therefore no canonica Laplace--Beltrami operator. In this paper we introduce a canonical finite-dimensional trace notion of harmonicity: a continuous function $u:\mathcal{P}_2(M)\to\mathbb{R}$ is called empirically harmonic if, for every $N\geq 1$, its pullback to the $N$-particle empirical stratum, \begin{equation*} (x_1,\ldots,x_N)\longmapsto u\left(\frac1N\sum_{i=1}^Nδ_{x_i}\right), \end{equation*} is weakly harmonic on $M^N$. We prove that if $M$ has the finite-product Liouville property, then every bounded empirically harmonic function on $\mathcal{P}_2(M)$ is constant. In particular, this applies to $M=\mathbb{R}^d$ and, more generally, to every complete connected Riemannian manifold with nonnegative Ricci curvature. We also show sharpness: if $M$ admits a nonconstant bounded harmonic function, then $\mathcal{P}_2(M)$ admits a nonconstant bounded empirically harmonic function.

We consider collisions of multiple random walks on the trace of a simple random walk on the four-dimensional integer lattice. For two independent walks (in continuous time), we apply a result of Noda to derive a scaling limit for the collision time process. For three independent walks (in discrete time), we demonstrate infinitely many triple collisions occur.

Motivated by the recent work of Harper--Kohli--Song--Tahar, we formulate a positivity, hole-free, and log-concavity conjecture for the Links--Gould polynomial of alternating links and verify it for all 51.3 million alternating knots with at most 19 crossings. All but 544 of those knots satisfy a stronger type-B log-concavity condition characterized by the slopes of edges in the subdivision of the monomial support induced by the log coefficients.

Superconductivity in infinite-layer nickelates has drawn wide interest as a cuprate analogue, yet how the electronic structure evolves with hole doping remains unsettled. Here we map the doping- and temperature-dependent unoccupied states of the La-based infinite-layer nickelate La1-xCaxNiO2 using O K-edge and Ni L-edge x-ray absorption spectroscopy. Superconductivity occurs for 0.18<=x<=0.27. Near x~0.20-0.23, low-energy spectral weight redistributes: Ni3d-dominated states decrease while O2p-hybridized states increase, indicating an orbital-selective crossover in Ni-O covalency. This crossover coincides with a sign reversal of the Hall coefficient and precedes the reduction of the superconducting critical temperature at higher doping. By directly linking transport anomalies and the superconducting dome to a measurable Ni-O orbital reorganization, our results provide a key step toward a unified, orbital-resolved phase diagram for infinite-layer nickelates and a practical route to engineer superconductivity via hybridization control.

Scaling ferroelectrics to nanometer thicknesses remains a central challenge for low-power, nonvolatile electronics, as leakage currents increasingly dominate with reduced dimensions. Alkali-based, lead-free ferroelectrics offer an environmentally sustainable alternative to lead-based systems, yet their scaling is severely limited by leakage arising from volatile alkali constituents. Here, we show that this intrinsic limitation can be transformed into an advantageous degree of freedom through defect engineering. By precisely modulating alkali deficiency during thin-film synthesis, we engineer clustered defect complexes that function as deep trap states, strongly suppressing leakage and enabling robust ferroelectric operation in ultrathin films down to the sub-10 nm regime at voltages below 100 mV. Our results establish defect-enabled scaling as a viable pathway for advancing environmentally benign ferroelectrics toward ultra-low-power, non-volatile electronic technologies.

We introduce BijectiveRemesh, a robust algorithm for maintaining a continuous, bijective mapping across complex remeshing sequences on both 2D triangle surfaces and 3D tetrahedral meshes. Unlike traditional data transfer methods that rely on interpolation or projection, our approach constructs a mathematically rigorous composite map from the input mesh to the output mesh by chaining local bijective atlases defined for each primitive remeshing operation. Our framework represents the overall mapping as a composition of local bijective atlases, one per remeshing operation. Building upon successive self-parameterization, we introduce a Shared Scaffold structure for 2D triangle meshes that enforces global bijectivity through local orientation preservation. We extend this approach to handle edge splits, edge swaps, and vertex smoothing beyond the original edge collapses. For 3D tetrahedral meshes, we generalize the local atlas construction using Steinitz's Theorem and Maxwell-Cremona lifting to ensure valid embeddings. This enables exact tracking of geometric entities, including points, curves, and surfaces, across remeshing, with applications from texture transfer to volumetric simulations.

This paper studies integral forms for affine vertex superalgebras and their modules. We first obtain integral forms for the universal enveloping superalgebra $U(\hat{\g})$ of an affine Lie superalgebra $\hat{\g}$. For $\g$ a basic classical Lie superalgebra, we give another construction of integral forms for $U(\hat{\g})$ using Chevalley basis, generalizing Kostant-Garland integral form theory. Then we apply the theory to construct integral forms for vertex (operator) superalgebras based on affine Lie superalgebras and their modules, we also investigate when an integral form contains the conformal vector, and integral forms in contragredient modules for vertex operator superalgebras.

In this work, we define the interaction graph for a continuous-time Markov chain to analyze its dynamic structure. Under certain assumptions, we demonstrate that verifying Kolmogorov's reversibility criterion reduces to checking it for a cycle basis of the incidence matrix kernel associated with the interaction graph. This result provides an efficient tool for verifying reversibility in Markov continuous chains.

In tensor dynamics for liquid crystals derived from molecular models, a common problem is closure approximation. For rod-like molecules, the Bingham closure has proved to outperform other methods because it inherits the gradient flow structure of the molecular model, but is difficult to achieve efficient computations maintaining the gradient flow structure. We propose a closure approximation by the quasi-entropy that has been successfully applied to the free energy, based on which we construct the tensor gradient flow. The quasi-entropy closure has the same symmetry properties as the Bingham closure. The resulting tensor gradient flow is able to constrain the eigenvalues of the tensor within the physical range, guaranteeing the positive definiteness of the dissipation operator given by the higher-order tensors. The quasi-entropy closure is easy to implement since it can be reduced to minimizing an elementary function of three variables. As a result, we construct a numerical scheme preserving the eigenvalue constraints and energy dissipation, with the closure approximation decoupled from solving the scheme. Numerical simulations are carried out for the interface between the isotropic and the uniaxial nematic phase, as well as the defect evolutions, where the higher-order tensors indeed make a difference.

Weak CN absorption near ~8000 A has recently been detected in evolved red supergiants (RSGs) of 5-10 $M_\odot$ across three Local Group galaxies. These weak-CN RSGs sit in a narrow molecular regime: cool enough for CN to be visible in a non-carbon, C/O<1 atmosphere, but warm enough that TiO is not saturated and changes in $T_{\rm eff}$ and in the surface C+N reservoir move CN and TiO in distinct directions. We test this picture with pseudo-continuum equivalent widths (EWs) measured from LMC, M33, and M31 weak-CN and carbon-star coadds, compared at matched resolution to a self-consistent grid of synthetic RSG atmospheres spanning $T_{\rm eff}$, $[α/{\rm Fe}]$, and surface C and N offsets relative to each host's scaled-solar baseline. Ordinary cool-RSG models reproduce the weak-CN coadds across all three hosts, with per-feature residuals at the level of the adopted EW systematic floors. The robust observable is the combined surface abundance $Δ$[C/H]+$Δ$[N/H] rather than each offset individually, because CN forms from the product of available C and N number densities. Mapping $Δ$[C/H]+$Δ$[N/H] to initial rotation through PARSEC v2.0 has modest leverage -- the variable shifts by ~0.07 dex from $ω_i$=0 to $ω_i$=0.6 -- and within this resolution slow-rotation first dredge-up is consistent with LMC and M33, and with M31 once a single-feature CaT 8542 A calibration anchor is allowed. The straightforward resolution of the discovery puzzle is therefore that weak CN is not an exotic carbon-star intermediate but the expected molecular-equilibrium signature of ordinary cool RSGs.

While quantum position verification aims to certify a prover's location using quantum information, existing security definitions only guarantee that part of the successful adversarial party is in the claimed location. This leaves open the possibility that a distributed team of adversaries can jointly simulate a prover in a way that defeats the intended meaning of ``being at a location'' in position-based cryptography. We introduce stronger notions of position verification that we call quantum localization, which requires that there is a specified, unclonable state at the verified spacetime point -- and that this state can be found nowhere else. We show that quantum localization leads naturally to a meaningful notion of trajectory verification, in which quantum information is verifiably tracked through space and time. We construct quantum localization and trajectory verification protocols using quantum anchor states, which generalize coset states from unclonable cryptography. The security of our schemes is proven in the classical oracle (i.e. ideal obfuscation) model, which can be heuristically instantiated in the plain model using post-quantum indistinguishability obfuscation. We also introduce and instantiate the concept of functionality localization, which guarantees that the adversary has the ability to compute a secret function at the verified spacetime point, and this function cannot be computed anywhere else. This raises the intriguing possibility of localizing computational capabilities in space and time. More broadly, we believe our notions of quantum localization and our feasibility results provide stronger foundations for position-based cryptography.

While quartz (SiO2) ampule sealing is commonly used in laboratories to prevent sample oxidation during synthesis, its application is limited for reactions involving highly reactive elements such as alkali, alkaline-earth, and rare-earth metals. These elements can react with SiO2 at elevated temperatures, causing compositional loss, tube failure, and experimental inconsistencies. Here, we introduce an inexpensive boron nitride (BN) cap sealing technique. This approach is readily adaptable to centrifugal separation and flux transport growth and yields superior sample quality. We demonstrate its efficacy by growing KFe2As2 and CsCr6Sb6 single crystals, the former exhibiting record-high quality, with a residual resistivity ratio (RRR) exceeding 2500, and the latter achieving significantly larger crystal dimensions than other methods. This accessible and economical method promises to accelerate the discovery of novel materials that contain reactive elements.

A $\mathbf{GL}$-variety is a (typically) infinite dimensional variety $X$ equipped with an action of the infinite general linear group. In recent work of the first two authors with Draisma, a candidate definition for the singular locus of $X$ was put forth. The approach there made use of auxiliary finite dimensional varieties associated to $X$. In this paper, we give a number of characterizations of the singular locus that are intrinsic to $X$. This work shows that the candidate definition is clearly correct, and helps clarify the geometric meaning of singular points.

This work presents a Lie symmetry classification of a generalized nonlinear heat equation with a reaction source term in radial geometry. The model involves three arbitrary constitutive functions that represent thermal capacity, thermal conductivity, and nonlinear heat generation or absorption. Using the classical Lie invariance criterion, the determining equations for point symmetries are derived and simplified through suitable transformations involving the ratios of the constitutive functions. The classification identifies several admissible subclasses for which the principal symmetry algebra is extended, including power-law and logarithmic branches associated with special values of the radial parameter. For these cases, the admitted Lie algebras, commutator structures, and optimal systems of one-dimensional subalgebras are obtained. The corresponding similarity reductions are constructed, reducing the governing partial differential equation to nonlinear ordinary differential equations. Some exact group-invariant solutions are also derived for special parameter choices. The results show that the inclusion of the nonlinear source term significantly enriches the symmetry structure compared with the source-free radial heat equation.

Machine learning holds fundamental computational significance due to the increasing demand for efficient solutions to complex tasks in data analysis, pattern recognition, and optimization, which are essential for addressing the multifaceted challenges of modern society. As the volume of data proliferates at an unprecedented rate, the need for more powerful machine learning strategies becomes increasingly evident. Quantum neural networks (QNNs) represent an emerging and transformative research field that seeks to harness the unique principles of quantum mechanics to enhance the capabilities of machine learning algorithms. This survey examines various QNN approaches, including fully connected QNNs, quantum convolutional neural networks, equivariant QNNs, quantum Hopfield networks, quantum Boltzmann machines, quantum reservoir computing, and composite networks for quantum reinforcement learning, quantum generative learning, and quantum transfer learning. We summarize the relevant investigations on their performance, including learning accuracy, training time, and resource requirements, etc. Each QNN type has unique strengths and weaknesses, offering diverse solutions for different applications.

Persistent alternation of high and low water in coastal and oceanic regions has attracted human attention for millennia. This movement of water is generally explained through the double water bulge model. Although this model has been widely adopted in the scientific literature on tides since the 18th century, the physical existence of water bulges on the Earth's surface has yet to be verified. Herein, we establish a lunar angle phase-dependent statistical analysis of tide patterns at 362,370 oceanic locations spotted by Jason-3 satellite of AVISO in 2021 to address this issue. We show that during lunar angle phases of 0 degree-45 degree and 135 degree-180 degree, which spatially correspond to the water bulging regions expected in the double water bulge model, the number of low tides consistently exceeds that of high tides. Conversely, during lunar angle phase of 45 degree-135 degree, which spatially correspond to the water-depressing region expected in the model, high tides predominantly outnumber low tides. These findings evidently contradict the physical existence of two water bulges in the world's oceans, suggesting that the scientific community should pay additional attention to alternative explanations for tides, such as gravitational forcing mechanism and oceanic basin oscillation-generated driving mechanism.

Topic models are often used as dimension-reduction tools before regression, with estimated document-level topic shares treated as observed covariates. This plug-in workflow creates two inferential difficulties: valid inference requires a regular first-stage-to-second-stage expansion that propagates topic-estimation uncertainty, and, at fixed document length, a document's topic mixture cannot be consistently recovered from its own words even when the population topic matrix is known. Corrected spectral moment methods for latent Dirichlet allocation (LDA) offer a starting point: when the total Dirichlet concentration is known, low-order word moments can be corrected to yield operators diagonal in the latent topic basis. We extend this to downstream regression. Under a finite LDA model with response residuals orthogonal to the low-order token moments used for identification, response-weighted word moments admit the same correction, and the resulting supervised operator identifies the regression coefficient $β$ directly, without estimating document-level topic shares. The main obstacle is that the correction depends on the unknown total concentration $α_0$. We show that, for $k\ge3$ topics and under a generic finite-probe condition, $α_0$ is identified by commutativity: at the true value a family of corrected word-moment operators commute, whereas away from it they generically do not. This yields a feasible estimator and lets uncertainty in $\hatα_0$ propagate into inference for $β$. The estimator is asymptotically linear as the number of documents grows with fixed document length, with sandwich standard errors from document-level moment contributions. Simulations show near-nominal coverage where plug-in topic-share regressions can undercover, and an application to top economics journals illustrates contrast inference for latent topic effects.

The two-dimensional metallic quantum critical problem is a long-standing puzzle that is widely believed to hold the key to resolving ubiquitous non-Fermi liquid behavior in strongly correlated electronic systems. In this study, we present a non-perturbative renormalization group (RG) analysis of the metallic Ising-nematic quantum critical point in two dimensions, formulated directly around an intrinsically nonlocal infrared (IR) boson propagator. Rather than treating the anomalous dynamical critical exponent $a$ as a fixed phenomenological parameter, we regard it as an intrinsic component of the fixed-point data to be determined from the internal consistency of the low-energy patch field theory under highly anisotropic scaling dimensions ($[k_0]=a+1$, $[k_x]=2$, $[k_y]=1$). While the leading two-loop diagrammatics vanish identically due to kinematic pole configurations, our three-loop evaluation reveals a profound structural asymmetry between the sectors: the fermion self-energy and Yukawa vertex receive non-vanishing logarithmic corrections, whereas the corresponding bosonic counter-term remains strictly zero. Consequently, we find that no self-consistent, intersecting fixed-point solution for the exponent $a$ exists within the three-loop truncation, failing to reproduce the physical value of $a \approx 1.85$ observed in quantum Monte Carlo simulations. We conjecture that the cross-linked topology of the four-loop boson self-energy diagrams is exactly marginal and yields the minimal, mandatory bosonic counter-term required to restore multi-sector self-consistency. Our framework establishes a rigid multi-loop matching scheme necessary to uniquely pin down the critical exponent, and uncovers a stable phase space for field anomalous dimensions.

A detailed understanding of the capabilities and fidelity of low-energy reconstruction is crucial for taking advantage of MeV-scale neutrino physics opportunities in liquid argon time projection chambers (LArTPCs). This study presents a measurement of the resolution of reconstructed energy in the MicroBooNE LArTPC at $\approx 1.5$ MeV. The characterization is performed using monoenergetic signals generated by $2.614$ MeV $γ$-rays from $^{208}$Tl decays undergoing pair production in the detector. The resolution is found to be ($7.52 \pm 0.78 \text{(stat)} \pm 0.92 \text{(syst)}$)%. This value is consistent with the MicroBooNE simulation prediction of ($9.70 \pm 0.65 \text{(stat)}$)% at the $1.6 σ$ level. This study represents the first ever measurement of LArTPC energy resolution at the MeV scale and provides a pathway for monoenergetic energy calibrations in future experiments using LArTPC detectors.

All embodied agents are fundamentally patterns in physiological or other excitable media, blurring the distinction between objects and processes. Emergent patterns with complex behaviors, such as Gliders in the Game of Life and virtual patterns in Lenia, are powerful model systems in which to understand the properties and origins of behavioral traits in novel agents. To evaluate the behavior of patterns in Lenia, we introduce regions into their environment from which no sensory information is available - in effect, making creatures blind to parts of their surroundings. Complementing the conventional concept of infotaxis, we find that creatures tend to avoid these regions, a behavior we term agnosiophobia. To explain this behavior, we map each test creature's sensitivity to targeted occlusions and interpret the results in the language of dynamical systems. We observe Lenia creatures taking advantage of their freedom to change heading in order to achieve what appears to be a more fundamental goal: the preservation of their morphology. This work illustrates the beginning of an important roadmap to understand how emergent agents' behavioral propensities interact with the informational, not only tangible, topography of their world.

We consider the directed polymer model on $\mathbb{Z}^d$, in an i.i.d.\ random environment $ω=(ω_{n,x})_{n\geq 0,x\in\mathbb Z^d}$, focusing on the critical dimension $d=2$. Our main contribution is to give a sharp lower bound on the free energy in the high-temperature regime. Our proof uses a percolation argument inspired by Lacoin (2010), for which we introduce a key property of bounded ``$\log$-energy'': this property quantifies the regularity of the polymer measures at diffusive scales and we show that it propagates along open paths. Writing $\mathfrak{f}(β)$ for the quenched free energy, and setting $λ(β):=\log \mathbb E[e^{βω_{1,0}}]$ and $σ(β)^2:=e^{λ(2β)-2λ(β)}-1$, our lower bound combined with Theorem 2.8 of Berger, Caravenna, and Turchi (2025) gives $$ -\mathfrak{f}(β) \asymp \exp{\Big(- \fracπ{σ^2(β)}\Big)},\quad \text{ as $β\downarrow 0$.} $$

We have derived the nonlinear Schrodinger equation generalizing the Gross-Pitaevskii (GP) equa tion for dilute Bose gas. The derivation is based on the Hartree-Fock time-dependent mean-field theory with an arbitrary intermolecular interaction potential. It is shown that obtained nonlinear Schrodinger equation with appropriate redefinition of coefficients can be used for description of dense Bose fluid at low temperatures. We also present the Schrodinger type equation describing the superfluid component of helium in two fluid hydrodynamics. This approach leads to quantum correction for superfluid component of velocity in two fluid hydrodynamics. We also have derived the nonlinear Schrodinger equation for superfluid He4 film at low temperatures. It is shown that this Schrodinger type equation for superfluid He4 film leads to phonon-roton dispersion relation for elementary excitation at low temperatures.

Single-pixel cameras have recently emerged as promising alternatives to multi-pixel sensors due to reduced costs and superior durability, which are particularly attractive for mid-infrared (MIR) imaging pertinent to applications including industry inspection and biomedical diagnosis. To date, MIR single-pixel photon-sparse imaging has yet been realized, which urgently calls for high-sensitivity optical detectors and high-fidelity spatial modulators. Here, we demonstrate a MIR single-photon computational imaging with a single-element silicon detector. The underlying methodology relies on nonlinear structured detection, where the encoded time-varying pump patterns are optically imprinted onto the MIR object image through sum-frequency generation. Simultaneously, the MIR radiation is spectrally translated into the visible region, thus permitting infrared single-photon upconversion detection. Then, the use of advanced algorithms of compress sensing and deep learning allows us to reconstruct MIR images under sub-Nyquist sampling and photon-starving illumination. The presented paradigm of single-pixel upconversion imaging is featured with single-pixel simplicity, single-photon sensitivity, and room-temperature operation, which would establish a new path for sensitive imaging at longer infrared wavelengths or terahertz frequencies, where high-sensitivity photon counters and high-fidelity spatial modulators are typically hard to access.

Active mid-infrared (MIR) imagers capable of retrieving three-dimensional (3D) structure and reflectivity information are highly attractive in a wide range of biomedical and industrial applications. However, the infrared 3D imaging at low-light levels is still challenging due to the deficiency of sensitive and fast MIR sensors. Here we propose and implement a MIR time-of-flight imaging system that operates at single-photon sensitivity and femtosecond timing resolution. Specifically, back-scattered infrared photons from a scene are optically gated by delay-controlled ultrashort pump pulses through nonlinear frequency upconversion. The upconverted images with time stamps are then recorded by a silicon camera to facilitate the 3D reconstruction with high lateral and depth resolutions. Moreover, an effective numerical denoiser based on spatiotemporal correlation allows us to reveal the object profile and reflectivity under photon-starving conditions with a detected flux below 0.05 photons/pixel/second. The presented MIR 3D imager features with high detection sensitivity, precise timing resolution, and wide-field operation, which may open new possibilities in life and material sciences.

Sensitive and fast mid-infrared (MIR) spectroscopy is highly attractive in a variety of applications including astronomical observation, pharmaceutical synthesis, and environmental monitoring. However, the performance of conventional MIR spectrometers has long been hindered by the limited sensitivity of narrow-bandgap detectors and/or the deficient brightness of broadband light sources. Here, we devise and implement an ultra-sensitive and broadband MIR upconversion spectrometer, which integrates a supercontinuum source covering 1.5-4.2 $μ$m based on a silicon nitride nanophotonic waveguide. High-efficiency and low-noise nonlinear frequency upconversion is realized based on coincidence pulsed pumping with spectro-temporal optimization, which enables to leverage silicon detectors for facilitating MIR single-photon spectroscopy at 0.2 photons/nm/pulse. Furthermore, the upconversion-based array spectrometer is manifested with high-speed spectral acquisition rates beyond 200 kHz, which is about ten-fold faster than the state-of-the-art scan rates for FTIR-based spectrometers at a comparable spectral resolution. The achieved features of broadband spectral coverage, single-photon sensitivity, and sub-MHz refreshing rate might open up new possibilities in infrared transient spectral measurements in combustion analysis, high-throughput sorting and reaction tracking, among others.

The System-Theoretic Process Analysis (STPA) is a well-established hazard analysis technique that has been applied to a wide range of safety-critical systems. Despite its popularity, there is relatively little automation support for STPA, and most of its steps are carried out manually by a human analyst, which can be time consuming and error prone. This paper investigates the potential use of model-based engineering and formal methods to assist human analysts in efficiently and accurately carrying out STPA. The proposed tool, called FASR (Formalizing and Automating STPA with Robustness), enables automated, complete identification of unsafe control actions (UCAs), leveraging recent advances in robustness analysis to identify UCAs as undesirable deviations in the controller's actions. The use of the tool is demonstrated on a case study involving a Braking System Control Unit (BSCU) in an avionics system. As a preliminary exploration of the potential benefits and limitations of the tool, the paper reports on a user study involving nine participants with varying backgrounds in STPA, model-based engineering, and formal methods; the study found that most participants considered the tool a useful aid in identifying UCAs, while suggesting improvements that would make a tool such as FASR usable and applicable to a wider range of systems and analysts.