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We present the discovery of a binary system containing a white dwarf candidate using data from the LAMOST. Our analysis of the radial velocity data allowed us to determine an orbital period of approximately 0.953 days and a mass function of 0.129 $M_\odot$. Through spectral energy distribution (SED) fitting, we obtained the stellar parameters of the visible star. By combining these results with the mass function, we established a relationship between the mass of the invisible star and the system's inclination angle, along with the Roche lobe radius. We find that the mass of the invisible star is below the Chandrasekhar limit when the inclination angle exceeds $35^\circ$. Given that systems with large variations in radial velocity typically have high inclination angles, we classify the invisible star as a white dwarf candidate. The Roche lobe radius exceeds the physical radius of the visible star, indicating that no mass transfer occurs, which results in a weak ellipsoidal modulation effect. Additionally, we obtained light curves from the TESS, ASAS-SN, and CRTS surveys. The light curves also exhibit a periodicity of approximately 0.95 days, with ellipsoidal modulation only in the 2019 TESS observations. Coupled with the strong $\rm H_{\alpha}$ emission line observed in the LAMOST MRS spectrum, we infer that the surface of the visible star contains significant hot spots. This obscures the system's inherently weak ellipsoidal modulation, resulting in a manifestation of rotational variables. Furthermore, an analysis of the dynamical characteristics of this system indicates that it has a high inclination angle ($>60$ degrees) and its orbital properties are consistent with those of typical thin disk stars, supporting the hypothesis that the invisible object is a white dwarf., Comment: 13pages, 10figures. Accepted by the Journal of High Energy Astrophysics

High-dimensional entangled states offer higher information capacity and stronger resilience to noise compared with two-dimensional systems. However, the large number of modes and sensitivity to random rotations complicate experimental entanglement certification. Here, we experimentally certify three-dimensional entanglement in a five-dimensional two-photon state using 800 Haar-random measurements implemented via a 10-plane programmable light converter. We further demonstrate the robustness of this approach against random rotations, certifying high-dimensional entanglement despite arbitrary phase randomization of the optical modes. This method, which requires no common reference frame between parties, opens the door for high-dimensional entanglement distribution through long-range random links.

Graph contrastive learning has been successfully applied in text classification due to its remarkable ability for self-supervised node representation learning. However, explicit graph augmentations may lead to a loss of semantics in the contrastive views. Secondly, existing methods tend to overlook edge features and the varying significance of node features during multi-graph learning. Moreover, the contrastive loss suffer from false negatives. To address these limitations, we propose a novel method of contrastive multi-graph learning with neighbor hierarchical sifting for semi-supervised text classification, namely ConNHS. Specifically, we exploit core features to form a multi-relational text graph, enhancing semantic connections among texts. By separating text graphs, we provide diverse views for contrastive learning. Our approach ensures optimal preservation of the graph information, minimizing data loss and distortion. Then, we separately execute relation-aware propagation and cross-graph attention propagation, which effectively leverages the varying correlations between nodes and edge features while harmonising the information fusion across graphs. Subsequently, we present the neighbor hierarchical sifting loss (NHS) to refine the negative selection. For one thing, following the homophily assumption, NHS masks first-order neighbors of the anchor and positives from being negatives. For another, NHS excludes the high-order neighbors analogous to the anchor based on their similarities. Consequently, it effectively reduces the occurrence of false negatives, preventing the expansion of the distance between similar samples in the embedding space. Our experiments on ThuCNews, SogouNews, 20 Newsgroups, and Ohsumed datasets achieved 95.86\%, 97.52\%, 87.43\%, and 70.65\%, which demonstrates competitive results in semi-supervised text classification., Comment: 16 pages, 6 figures

Modeling and estimation of the vocal tract and glottal source parameters of vowels from raw speech can be typically done by using the Auto-Regressive with eXogenous input (ARX) model and Liljencrants-Fant (LF) model with an iteration-based estimation approach. However, the all-pole autoregressive model in the modeling of vocal tract filters cannot provide the locations of anti-formants (zeros), which increases the estimation errors in certain classes of speech sounds, such as nasal, fricative, and stop consonants. In this paper, we propose the Auto-Regressive Moving Average eXogenous with LF (ARMAX-LF) model to extend the ARX-LF model to a wider variety of speech sounds, including vowels and nasalized consonants. The LF model represents the glottal source derivative as a parametrized time-domain model, and the ARMAX model represents the vocal tract as a pole-zero filter with an additional exogenous LF excitation as input. To estimate multiple parameters with fewer errors, we first utilize the powerful nonlinear fitting ability of deep neural networks (DNNs) to build a mapping from extracted glottal source derivatives or speech waveforms to corresponding LF parameters. Then, glottal source and vocal tract parameters can be estimated with fewer estimation errors and without any iterations as in the analysis-by-synthesis strategy. Experimental results with synthesized speech using the linear source-filter model, synthesized speech using the physical model, and real speech signals showed that the proposed ARMAX-LF model with a DNN-based estimation method can estimate the parameters of both vowels and nasalized sounds with fewer errors and estimation time.

The ability to manipulate the spatial structure of light is fundamental for a range of applications, from classical communication to quantum information processing. Multi-plane light conversion (MPLC) addresses the limitations of single-plane modulation by enabling full control over multiple spatial modes of light through a series of phase masks separated by free-space propagation. In this tutorial, we present a step-by-step guide for building and aligning a 10-plane programmable light converter using a single spatial light modulator (SLM) and standard optical components. Our method allows precise alignment, achieving single-pixel accuracy with a relatively simple setup. We hope that this guide will help other researchers to quickly adopt and adapt MPLC technology for their own experiments.

Ghost imaging enables the imaging of an object using intensity correlations between a single-pixel detector placed behind the object and a camera that records light that did not interact with the object. The object and the camera are often placed at conjugate planes to ensure correlated illumination patterns. Here, we show how the combined effect of optical reciprocity and the memory effect in a random medium gives rise to correlations between two beams that traverse the random medium in opposite directions. Using these correlations, we demonstrate a ghost imaging scheme in which the object and camera are placed at opposite ends of the random medium and illuminated by counter-propagating beams that can potentially be emitted by two different sources.

Entangled photons provide transformative new paths in the fields of communication, sensing, and computing. However, when entangled photons propagate through a complex medium such as a biological tissue or a turbulent atmosphere, their correlations are scrambled. Using wavefront shaping to compensate for the scattering and retrieve the two-photon correlations is challenging due to the low signal-to-noise ratio of the two-photon signal. While previous works partly addressed this challenge by using feedback from a strong classical laser beam that co-propagates with the entangled photons, such methods frequently depend on assumptions about the complex medium, limiting the applicability of quantum wavefront shaping. In this work, we propose and demonstrate a new feedback mechanism that is inspired by Klyshko's advanced wave picture, in which the classical laser beam counter-propagates with one of the entangled photons and co-propagates with the other. The new Klyshko feedback allows compensation of scattering in thick samples and even in situations where each photon propagates through a different scattering medium. Since the advanced wave picture applies whenever optical reciprocity is valid, such Klyshko optimization can be utilized across a wide range of configurations, offering a robust and alignment-free setup. We therefore believe this protocol will open the door for real-world applications of quantum wavefront shaping.

High-dimensional quantum key distribution (QKD) offers higher information capacity and stronger resilience to noise compared to its binary counterpart. However, these advantages are often hindered by the difficulty of realizing the required high-dimensional measurements and transformations. Here, we implement a large-scale multi-plane light converter (MPLC) and program it as a high-dimensional mode sorter of spatial modes for QKD. Using the MPLC, we demonstrate five-dimensional QKD with six mutually unbiased bases and 25-dimensional QKD with two mutually unbiased bases in the same experimental setup. Furthermore, we propose a construction of pairs of mutually unbiased bases that are robust to experimental errors, with measurement complexity scaling only with the square root of the encoded dimension. This approach paves the way for QKD implementations in higher dimensions.

Multimode optical fibers support the dense, low-loss transmission of many spatial modes, making them attractive for technologies such as communications and imaging. However, information propagating through multimode fibers is scrambled, due to modal dispersion and mode mixing. This is usually rectified using wavefront shaping techniques with devices such as spatial light modulators. Recently, we demonstrated an all-fiber system for controlling light propagation inside multimode fibers using mechanical perturbations, called the fiber piano. In this tutorial we explain the design considerations and experimental methods needed to build a fiber piano, and review applications where fiber pianos have been used.

The capacity of information delivered by single photons is boosted by encoding high-dimensional quantum dits in their transverse shape. Transporting such high-dimensional quantum dits in optical networks may be accomplished using multimode optical fibers, which support the low-loss transmission of multiple spatial modes over existing infrastructure. However, when photons propagate through a multimode fiber their transverse shape gets scrambled because of mode mixing and modal interference. This is usually corrected using free-space spatial light modulators, inhibiting a robust all-fiber operation. In this work, we demonstrate an all-fiber approach for controlling the shape of single photons and the spatial correlations between entangled photon pairs, using carefully controlled mechanical perturbations of the fiber. We optimize these perturbations to localize the spatial distribution of a single photon or the spatial correlations of photon pairs in a single spot, enhancing the signal in the optimized spot by over an order of magnitude. Using the same approach we show a similar enhancement for coupling light from a multimode fiber into a single-mode fiber.

When making strategic decisions, we are often confronted with overwhelming information to process. The situation can be further complicated when some pieces of evidence are contradicted each other or paradoxical. The challenge then becomes how to determine which information is useful and which ones should be eliminated. This process is known as meta-decision. Likewise, when it comes to using Artificial Intelligence (AI) systems for strategic decision-making, placing trust in the AI itself becomes a meta-decision, given that many AI systems are viewed as opaque "black boxes" that process large amounts of data. Trusting an opaque system involves deciding on the level of Trustworthy AI (TAI). We propose a new approach to address this issue by introducing a novel taxonomy or framework of TAI, which encompasses three crucial domains: articulate, authentic, and basic for different levels of trust. To underpin these domains, we create ten dimensions to measure trust: explainability/transparency, fairness/diversity, generalizability, privacy, data governance, safety/robustness, accountability, reproducibility, reliability, and sustainability. We aim to use this taxonomy to conduct a comprehensive survey and explore different TAI approaches from a strategic decision-making perspective.

Correlations between entangled photons are a key ingredient for testing fundamental aspects of quantum mechanics and an invaluable resource for quantum technologies. However, scattering from a dynamic medium typically scrambles and averages out such correlations. Here we show that multiply-scattered entangled photons reflected from a dynamic complex medium remain partially correlated. We observe in experiments and in full-wave simulations enhanced correlations, within an angular range determined by the transport mean free path, which prevail disorder averaging. Theoretical analysis reveals that this enhancement arises from the interference between scattering trajectories, in which the photons leave the sample and are then virtually reinjected back into it. These paths are the quantum counterpart of the paths that lead to the coherent backscattering of classical light. This work points to opportunities for entanglement transport despite dynamic multiple scattering in complex systems.

Scattering by atmospheric turbulence is one of the main challenges in creating long free-space optical links, and specifically links of entangled photons. Classical compensation methods are hard to apply to entangled photons, due to inherently low signal to noise ratios and the fragility of entanglement. We have recently shown that we can use the bright laser beam that pumps spontaneous parametric down conversion to control the spatial correlations between entangled photons for compensating their scattering. In this work, we apply the pump-shaping technique to compensate for scrambling of correlations between entangled photons that scatter by emulated atmospheric turbulence. We use a spatial light modulator and Kolmogorov's turbulence model to emulate atmospheric turbulence in the lab, and enhance the entangled photons' signal by a factor of fifteen using pump optimization. We show this for both static and dynamic emulated atmosphere, and demonstrate also the compensation of the scattering of a higher-order mode. Our results can open the door towards realizing free-space quantum links with entangled photons, used in applications such as quantum key distribution.

High-dimensional entanglement offers a variety of advantages for both fundamental and applied applications in quantum information science. A central building block for such applications is a programmable processor of entangled states, which is crucial for the certification, manipulation and distribution of high-dimensional entanglement. The leading technology for processing photons is integrated multiport interferometers. However, such devices are incompatible with structured light, and their scaling is challenging. Here, we unlock these limitations by demonstrating a reconfigurable processor of entangled photons in high-dimensions that is based on multi-plane light conversion (MPLC), a technology that was recently developed for multiplexing hundreds of spatial modes for classical communication. We use our programmable MPLC platform to certify three-dimensional entanglement in two mutually unbiased bases, perform 400 arbitrary random transformations on entangled photons, and convert the mode basis of entangled photons for entanglement distribution.

Free-space quantum key distribution is gaining increasing interest as a leading platform for long range quantum communication. However, the sensitivity of quantum correlations to scattering induced by turbulent atmospheric links limits the performance of such systems. Recently, methods for compensating the scattering of entangled photons have been demonstrated, allowing for real-time optimization of their quantum correlations. In this Letter, we demonstrate the use of wavefront shaping for compensating the scattering of non-collinear and non-degenerate entangled photons. These results demonstrate the applicability of wavefront shaping schemes for protocols utilizing the large bandwidth and emission angle of the entangled photons.

The observation of the Hanbury Brown and Twiss (HBT) effect with thermal light marked the birth of quantum optics. All the thermal sources considered to date did not feature quantum signatures of light, as they consisted of independent emitters that emit uncorrelated photons. Here, we propose and demonstrate an incoherent light source based on phase-randomized spatially entangled photons, which we coin thermal biphotons. We show that in contrast to thermal light, the width of the HBT peak for thermal biphotons is determined by their correlations, leading to violation of the Siegert relation and breakdown of the speckle-fluctuations interpretation. We further provide an alternative interpretation of the results by drawing a connection between the HBT effect and coherent backscattering of light. Finally, we discuss the role of spatial entanglement in the observed results, deriving a relation between the Schmidt number and the degree of violation of the Siegert relation under the double-Gaussian approximation of spontaneous parametric down conversion (SPDC). Our work reflects new insights on the coherence properties of thermal light in the presence of entanglement, paving the way for entanglement certification using disorder averaged measurements.

Over the past decade, Airy beams have been the subject of extensive research, leading to new physical insights and various applications. In this letter, we extend the concept of Airy beams to the quantum domain. We generate entangled photons in a superposition of two-photon Airy states via spontaneous parametric down conversion, pumped by a classical Airy beam. We show that the entangled Airy photons preserve the intriguing properties of classical Airy beams, such as free acceleration and reduced diffraction, while exhibiting non-classical anti-correlations.

Quantum technologies hold great promise for revolutionizing photonic applications such as cryptography. Yet their implementation in real-world scenarios is held back, mostly due to sensitivity of quantum light to scattering. Recent developments in optimizing the shape of single photons introduce new ways to control quantum light. Nevertheless, shaping single photons in real-time remains a challenge due to the weak associated signals, which are too noisy for optimization processes. Here, we overcome this challenge and control scattering of entangled photons by shaping the classical laser beam that stimulates their creation. We discover that since the classical beam and the entangled photons follow the same path, the strong classical signal can be used for optimizing the weak quantum signal. We show that this approach can increase the length of free-space turbulent quantum links by up to two orders of magnitude, opening the door for employing wavefront shaping for quantum communications.

We study experimentally and theoretically the interactions among ultrashort optical pulses in the soliton rain multiple-pulse dynamics of a fiber laser. The laser is mode-locked by a graphene saturable absorber fabricated using the mechanical transfer technique. Dissipative optical solitons aggregate into pulse bunches that exhibit complex behavior, which includes acceleration and bi-directional motion in the moving reference frame. The drift speed and direction depend on the bunch size and relative location in the cavity, punctuated by abrupt changes under bunch collisions. We model the main effects using the recently proposed noise-mediated pulse interaction mechanism, and obtain a good agreement with experiments. This highlights the major role of long-range Casimir-like interactions over dynamical pattern formations within ultrafast lasers.

Mentoring at-risk students has become one of the fastest growing and frequently used strategies across the nation to help young people. This document examines the structure and implementation of mentoring programs. Chapter 1 discusses mentoring as an appropriate and effective strategy. The mentoring relationship is examined, natural versus planned mentoring is discussed, and program types and examples are provided. Chapter 2 considers needs assessment issues. Analysis of data, program costs, liability, and support are discussed. Chapter 3 looks at program management; goal setting, clarifying objectives, evaluating a program, goals and rationales, setting timelines, and a timetable for a mentoring program are addressed. Chapter 4 discusses the identification, selection, and recruitment of proteges, training, and orienting. Chapter 5 deals with finding and selecting mentors and publicizing the program. Also discussed are matching mentors and proteges, mentor orientation and training, and the first meeting. Chapter 6 contains information about managing the program; mentor contact, protege contact, and supervising the match are discussed. Also included is information about group activities, recognizing mentors and proteges, expanding and refining the program, and terminating mentors and proteges. Sample forms which can be used by program planners are included and discussed in the appendices. (LLL)