Search

Building on previous works to construct a homogeneous sample of brown dwarfs in binary systems, we investigate microlensing events detected by the Korea Microlensing Telescope Network (KMTNet) survey during the 2022 and 2023 seasons. Given the difficulty in distinguishing brown-dwarf events from those produced by binary lenses with nearly equal-mass components, we analyze all lensing events detected during the seasons that exhibit anomalies characteristic of binary-lens systems. Using the same criteria consistently applied in previous studies, we identify six additional brown dwarf candidates through the analysis of lensing events KMT-2022-BLG-0412, KMT-2022-BLG-2286, KMT-2023-BLG-0201, KMT-2023-BLG-0601, KMT-2023-BLG-1684, and KMT-2023-BLG-1743. An examination of the mass posteriors shows that the median mass of the lens companions ranges from 0.02 $M_\odot$ to 0.05 $M_\odot$, indicating that these companions fall within the brown-dwarf mass range. The mass of the primary lenses ranges from 0.11 $M_\odot$ to 0.68 $M_\odot$, indicating that they are low-mass stars with substantially lower masses compared to the Sun., Comment: 13 pages, 17 figures, 12 tables

Global optimization of crystal compositions is a significant yet computationally intensive method to identify stable structures within chemical space. The specific physical properties linked to a three-dimensional atomic arrangement make this an essential task in the development of new materials. We present a method that efficiently uses active learning of neural network force fields for structure relaxation, minimizing the required number of steps in the process. This is achieved by neural network force fields equipped with uncertainty estimation, which iteratively guide a pool of randomly generated candidates towards their respective local minima. Using this approach, we are able to effectively identify the most promising candidates for further evaluation using density functional theory (DFT). Our method not only reliably reduces computational costs by up to two orders of magnitude across the benchmark systems Si16 , Na8Cl8 , Ga8As8 and Al4O6 , but also excels in finding the most stable minimum for the unseen, more complex systems Si46 and Al16O24 . Moreover, we demonstrate at the example of Si16 that our method can find multiple relevant local minima while only adding minor computational effort.

Image generative AI has garnered significant attention in recent years. In particular, the diffusion model, a core component of recent generative AI, produces high-quality images with rich diversity. In this study, we propose a novel CT reconstruction method by combining the denoising diffusion probabilistic model with iterative CT reconstruction. In sharp contrast to previous studies, we optimize the fidelity loss of CT reconstruction with respect to the latent variable of the diffusion model, instead of the image and model parameters. To suppress anatomical structure changes produced by the diffusion model, we shallow the diffusion and reverse processes, and fix a set of added noises in the reverse process to make it deterministic during inference. We demonstrate the effectiveness of the proposed method through sparse view CT reconstruction of 1/10 view projection data. Despite the simplicity of the implementation, the proposed method shows the capability of reconstructing high-quality images while preserving the patient's anatomical structure, and outperforms existing methods including iterative reconstruction, iterative reconstruction with total variation, and the diffusion model alone in terms of quantitative indices such as SSIM and PSNR. We also explore further sparse view CT using 1/20 view projection data with the same trained diffusion model. As the number of iterations increases, image quality improvement comparable to that of 1/10 sparse view CT reconstruction is achieved. In principle, the proposed method can be widely applied not only to CT but also to other imaging modalities such as MRI, PET, and SPECT., Comment: 19 pages, 9 figures

We present the first measurement of nuclear recoils from solar $^8$B neutrinos via coherent elastic neutrino-nucleus scattering with the XENONnT dark matter experiment. The central detector of XENONnT is a low-background, two-phase time projection chamber with a 5.9\,t sensitive liquid xenon target. A blind analysis with an exposure of 3.51\,t$\times$y resulted in 37 observed events above 0.5\,keV, with ($26.4^{+1.4}_{-1.3}$) events expected from backgrounds. The background-only hypothesis is rejected with a statistical significance of 2.73\,$\sigma$. The measured $^8$B solar neutrino flux of $(4.7_{-2.3}^{+3.6})\times 10^6\,\mathrm{cm}^{-2}\mathrm{s}^{-1}$ is consistent with results from dedicated solar neutrino experiments. The measured neutrino flux-weighted CE$\nu$NS cross-section on Xe of $(1.1^{+0.8}_{-0.5})\times10^{-39}\,\mathrm{cm}^2$ is consistent with the Standard Model prediction. This is the first direct measurement of nuclear recoils from solar neutrinos with a dark matter detector.

The signature of an unatomic system is revealed by a continuous scale invariance that appears during a progressive dimensional squeezing of a resonantly interacting trimer. The unatomic regime is reached at the dimension $\overline D$, which for three identical atoms is found to be $\overline D=2.292$ - below this value, the trimer wave function at short distances displays a power-law behaviour. The fingerprint of this crossover is a sharp evolution of the contacts that characterizes the trimer momentum distribution tail.

We address the question of the reliability of the Born-Oppenheimer (BO) approximation for a mass-imbalanced resonant three-body system embedded in noninteger dimensions. We address this question within the problem of a system of currently experimental interest, namely $^7$Li$-^{87}$Rb$_2$. We compare the Efimov scale parameter as well as the wave functions obtained using the BO approximation with those obtained using the Bethe-Peierls boundary condition.

Recently, the experimental values of the muon $(g-2)_\mu$ and of the $W$ boson mass $m_{_W}$ have both indicated significant deviations from the SM predictions, motivating the exploration of extensions with extra particles and symmetries. We revisit a lepton portal model with $U(1)'$ gauge symmetry where an extra Higgs doublet, a scalar singlet and one $SU(2)_L$ singlet vector-like fermion are introduced. In this model, $(g-2)_\mu$ can be explained by extra one-loop contributions from the vector-like lepton and the $Z'$ boson, whereas $m_{_W}$ can be increased by a tree-level mixing between the $Z$ and $Z'$. Setting the $Z'$ and lepton couplings at low energies to account for the SM anomalies, we perform a Renormalization Group analysis to investigate on the high-energy behaviour of the model, in particular on the issue of vacuum stability. We find that in the alignment limit for the two Higgs doublets, the Landau pole and the scale where perturbativity is lost are of order $10-100\,{\rm TeV}$, not far from the scales experimentally reached so far, and sensibly lower than the stability scale. We show how the Landau pole can be increased up to $\sim10^9\,{\rm GeV}$ in a misaligned scenario where the experimental anomalies are still accommodated and a positive shift of the Higgs quartic coupling to improve stability can be achieved., Comment: 36 pages, 10 figures, 2 Appendices

Domestic service robots (DSRs) that support people in everyday environments have been widely investigated. However, their ability to predict and describe future risks resulting from their own actions remains insufficient. In this study, we focus on the linguistic explainability of DSRs. Most existing methods do not explicitly model the region of possible collisions; thus, they do not properly generate descriptions of these regions. In this paper, we propose the Nearest Neighbor Future Captioning Model that introduces the Nearest Neighbor Language Model for future captioning of possible collisions, which enhances the model output with a nearest neighbors retrieval mechanism. Furthermore, we introduce the Collision Attention Module that attends regions of possible collisions, which enables our model to generate descriptions that adequately reflect the objects associated with possible collisions. To validate our method, we constructed a new dataset containing samples of collisions that can occur when a DSR places an object in a simulation environment. The experimental results demonstrated that our method outperformed baseline methods, based on the standard metrics. In particular, on CIDEr-D, the baseline method obtained 25.09 points, whereas our method obtained 33.08 points., Comment: Accepted for presentation at Advanced Robotics 24

The transparent formulation of explanation methods is essential for elucidating the predictions of neural networks, which are typically black-box models. Layer-wise Relevance Propagation (LRP) is a well-established method that transparently traces the flow of a model's prediction backward through its architecture by backpropagating relevance scores. However, the conventional LRP does not fully consider the existence of skip connections, and thus its application to the widely used ResNet architecture has not been thoroughly explored. In this study, we extend LRP to ResNet models by introducing Relevance Splitting at points where the output from a skip connection converges with that from a residual block. Our formulation guarantees the conservation property throughout the process, thereby preserving the integrity of the generated explanations. To evaluate the effectiveness of our approach, we conduct experiments on ImageNet and the Caltech-UCSD Birds-200-2011 dataset. Our method achieves superior performance to that of baseline methods on standard evaluation metrics such as the Insertion-Deletion score while maintaining its conservation property. We will release our code for further research at https://5ei74r0.github.io/lrp-for-resnet.page/, Comment: Accepted for presentation at ECCV2024

We examined the affection of the flux-trapped states of Sn60-Pb40 solders on superconducting properties of a Sn wire. The temperature dependence of electrical resistivity at H = 0 Oe after zero-field cooling (ZFC) showed a sharp superconducting transition at T = 3.7 K. In contrast, that after field cooling (FC) resulted in broadening of the transition. The difference between ZFC and FC data evidences critical affection of trapped fluxes at solders on superconducting states. We propose that, in electrical measurements where magnetic fields of several hundred Oe are critical, field experience should be seriously considered when using solders., Comment: 11 pages, 4 figures, supplementary data

Electronic $K$ x rays emitted by muonic Ar atoms in the gas phase were observed using a superconducting transition-edge-sensor microcalorimeter. The high-precision energy spectra provided a clear signature of the presence of muonic atoms accompanied by a few electrons, which have never been observed before. One-, two-, and three-electron bound, i.e., H-like, He-like, and Li-like, muonic Ar atoms were identified from electronic $K$ x rays and hyper-satellite $K$ x rays. These $K$ x rays are emitted after the charge transfer process by the collisions with surrounding Ar atoms. With the aid of theoretical calculations, we confirmed that the peak positions are consistent with the x-ray energies from highly charged Cl ions, and the intensities reflecting deexcitation dynamics were successfully understood by taking into account the interaction between the muon and bound electrons.

Various gravity theories beyond general relativity have been rigorously investigated in the literature such as Horndeski and degenerate higher-order scalar-tensor (DHOST) theories. In general, numerous model parameters are involved in such theories, which should be constrained to test the theories with experiments and observations. We construct the kurtosis consistency relations, calculated based on matter density fluctuations, in which the information of gravity theories is encoded. We derive two independent consistency relations that should hold in the framework of the DHOST theories and argue that such consistency relations would be useful for testing gravity theories., Comment: 19 pages, 3 figures

We introduce the spin-1 $U(1)_X$ gauged field $X$ with $Z_2$ odd dark parity for evading the current strong constraints for the kinetic mixing. Then, $X$ becomes stable and a candidate for the dark matter. The lowest mass dimension of interaction is six, and the type is like Higgs portal. Two types of dim-6 operators are introduced. We consider the freeze-out dark matter scenario. With the limit of null momentum transfer, a parity odd operator is free from the direct detection constraints. Accordingly, the strong constraints on a parity even operator indicate turning on this parity odd operator to realize the dark matter relic density of the universe. With the 1 TeV cut-off scale, our dark matter of around 400 GeV mass can explain the dark matter relic density and is allowed from the LUX-ZEPLIN experiment of the direct detection., Comment: 13 pages, 6 figures

In this study, we theoretically investigated x-ray spectra from the radiative decay of muonic deuterium molecules dd$\mu$ in resonance states, which plays an important role in a new kinetic model of muon catalyzed fusion ($\mu$CF). The resonance states are Feshbach resonances located below the d$\mu$($n=2$) + d threshold energy and radiatively decay into the continuum or bound states. The x-ray spectra having characteristic shapes according to the radial distribution of the two nuclei are obtained using precise three-body wave functions. We carefully examined the convergence of the x-ray spectra and achieved agreements between the length- and velocity-gauge calculations. We revealed a non-adiabatic kinetic energy distribution of the decay fragments, indicating that the radiative decay becomes a heating source of muonic atoms. We also investigated the decay branch that directly results in bound-state muonic molecules. Some resonance states dd$\mu^\ast$ and dt$\mu^\ast$ are found to have high branching ratios to the bound state where intramolecular nuclear fusion occurs. The formation of the muonic molecules in the bound states from metastable muonic atoms can be a fast track in the $\mu$CF cycle which skips a slow path to form the bound state from the ground-state muonic atoms and increases the $\mu$CF cycle rate. Although the spectra from the radiative decays are located in the energy range of $1.5$--$1.997$ keV, which is close to the K$\alpha$ x-ray of 1.997 keV from muonic deuterium atoms, state-of-the-art microcalorimeters can distinguish them., Comment: 17 pages, 15 figures, 4 tables

Recently, huge uniaxial negative thermal expansion (NTE) along a $c$-axis has been observed in transition-metal ($Tr$) zirconides $Tr$Zr$_{2}$ with a tetragonal CuAl$_{2}$-type structure. In a recent study on FeZr$_{2}$ [M. Xu et al., Nat. Commun. 14, 4439 (2023)], the importance of optical phonons to the emergence of the $c$-axis NTE in FeZr$_{2}$ has been proposed. In this study, the physical properties of $Tr$Zr$_{2}$ ($Tr$ = Fe and Co$_{1-x}$Ni$_{x}$) have been studied by specific heat, sound velocity measurements, and theoretical phonon calculations to discuss the importance of optical phonons to the emergence of the $c$-axis NTE in CoZr$_{2}$ and FeZr$_{2}$. From analyses of lattice specific heat, we found that Ni substitution results in a systematic decrease in oscillator strength for the Einstein modes with 8.74 meV (CoZr$_{2}$). From phonon calculations, the low-energy optical phonon branches at the $\Gamma$ point were observed for CoZr$_{2}$ and FeZr$_{2}$ with $c$-axis NTE, but not in NiZr$_{2}$ with positive thermal expansion. The enhancement of phonon density of states near the above-mentioned optical phonon energy in CoZr$_{2}$ and FeZr$_{2}$ is consistent with the specific heat analyses. We propose the importance of the low-energy optical phonons to the emergence of the $c$-axis NTE in TrZr$_{2}$., Comment: 14 pages, 9 figures, and 3 tables

The XENONnT experiment searches for weakly-interacting massive particle (WIMP) dark matter scattering off a xenon nucleus. In particular, XENONnT uses a dual-phase time projection chamber with a 5.9-tonne liquid xenon target, detecting both scintillation and ionization signals to reconstruct the energy, position, and type of recoil. A blind search for nuclear recoil WIMPs with an exposure of 1.1 tonne-years yielded no signal excess over background expectations, from which competitive exclusion limits were derived on WIMP-nucleon elastic scatter cross sections, for WIMP masses ranging from 6 GeV/$c^2$ up to the TeV/$c^2$ scale. This work details the modeling and statistical methods employed in this search. By means of calibration data, we model the detector response, which is then used to derive background and signal models. The construction and validation of these models is discussed, alongside additional purely data-driven backgrounds. We also describe the statistical inference framework, including the definition of the likelihood function and the construction of confidence intervals., Comment: 20 pages, 10 figures

Rare-earth Zintl compound EuIn$_2$As$_2$ has been theoretically recognized as a candidate for realizing an intrinsic antiferromagnetic (AFM) bulk axion insulator and a higher-order topological state, which provides a fertile platform to explore novel topological transport phenomena. However, the axion state has yet to be realized because EuIn$_2$As$_2$ is highly hole-doped. Here, we synthesized a series of high-quality Ca-doped EuIn2As2 (Ca$_x$Eu$_{1-x}$In$_2$As$_2$, x = 0 ~ 0.25) single crystals to tune the Fermi energy above the hole pocket. Our Hall measurements reveal that the isovalent Ca substitution decreases the hole carrier density by shrinking the lattice spacing, which is also confirmed by our first-principles calculations. We further find that both the temperature dependence of the magnetic susceptibility with a local maximum at the N\'eel temperature and the topological Hall effect originating from the finite real-space spin chirality persist in the Ca-doped samples as observed in the pristine EuIn$_2$As$_2$, despite that the nonmagnetic Ca substitution decreases the effective moment and the N\'eel temperature. These results show that the Ca substitution tunes the Fermi energy while keeping the AFM magnetic structure, suggesting that the axion insulating state may be realized by further Ca substitution., Comment: 18 pages, 8 figures

We investigated the nature of the anomalies appearing in four microlensing events KMT-2020-BLG-0757, KMT-2022-BLG-0732, KMT-2022-BLG-1787, and KMT-2022-BLG-1852. The light curves of these events commonly exhibit initial bumps followed by subsequent troughs that extend across a substantial portion of the light curves. We performed thorough modeling of the anomalies to elucidate their characteristics. Despite their prolonged durations, which differ from the usual brief anomalies observed in typical planetary events, our analysis revealed that each anomaly in these events originated from a planetary companion located within the Einstein ring of the primary star. It was found that the initial bump arouse when the source star crossed one of the planetary caustics, while the subsequent trough feature occurred as the source traversed the region of minor image perturbations lying between the pair of planetary caustics. The estimated masses of the host and planet, their mass ratios, and the distance to the discovered planetary systems are $(M_{\rm host}/M_\odot, M_{\rm planet}/M_{\rm J}, q/10^{-3}, \dl/{\rm kpc}) = (0.58^{+0.33}_{-0.30}, 10.71^{+6.17}_{-5.61}, 17.61\pm 2.25,6.67^{+0.93}_{-1.30})$ for KMT-2020-BLG-0757, $(0.53^{+0.31}_{-0.31}, 1.12^{+0.65}_{-0.65}, 2.01 \pm 0.07, 6.66^{+1.19}_{-1.84})$ for KMT-2022-BLG-0732, $(0.42^{+0.32}_{-0.23}, 6.64^{+4.98}_{-3.64}, 15.07\pm 0.86, 7.55^{+0.89}_{-1.30})$ for KMT-2022-BLG-1787, and $(0.32^{+0.34}_{-0.19}, 4.98^{+5.42}_{-2.94}, 8.74\pm 0.49, 6.27^{+0.90}_{-1.15})$ for KMT-2022-BLG-1852. These parameters indicate that all the planets are giants with masses exceeding the mass of Jupiter in our solar system and the hosts are low-mass stars with masses substantially less massive than the Sun., Comment: 10 pages, 12 figures, 7 tables

This paper presents a regularized Newton method (RNM) with generalized regularization terms for unconstrained convex optimization problems. The generalized regularization includes quadratic, cubic, and elastic net regularizations as special cases. Therefore, the proposed method serves as a general framework that includes not only the classical and cubic RNMs but also a novel RNM with elastic net regularization. We show that the proposed RNM has the global $\mathcal{O}(k^{-2})$ and local superlinear convergence, which are the same as those of the cubic RNM.

Realizing smooth traffic flow is important for achieving carbon neutrality. Adaptive traffic signal control, which considers traffic conditions, has thus attracted attention. However, it is difficult to ensure optimal vehicle flow throughout a large city using existing control methods because of their heavy computational load. Here, we propose a control method called AMPIC (Adaptive Model Predictive Ising Controller) that guarantees both scalability and optimality. The proposed method employs model predictive control to solve an optimal control problem at each control interval with explicit consideration of a predictive model of vehicle flow. This optimal control problem is transformed into a combinatorial optimization problem with binary variables that is equivalent to the so-called Ising problem. This transformation allows us to use an Ising solver, which has been widely studied and is expected to have fast and efficient optimization performance. We performed numerical experiments using a microscopic traffic simulator for a realistic city road network. The results show that AMPIC enables faster vehicle cruising speed with less waiting time than that achieved by classical control methods, resulting in lower CO2 emissions. The model predictive approach with a long prediction horizon thus effectively improves control performance. Systematic parametric studies on model cities indicate that the proposed method realizes smoother traffic flows for large city road networks. Among Ising solvers, D-Wave's quantum annealing is shown to find near-optimal solutions at a reasonable computational cost., Comment: 18 pages, 8 figures

Recent observations show that certain rupture phase can propagate backward relative to the earlier one during a single earthquake event. Such back-propagating rupture (BPR) was not well considered by the conventional earthquake source studies and remains a mystery to the seismological community. Here we present a comprehensive analysis of BPR, by combining theoretical considerations, numerical simulations, and observational evidences. First, we argue that BPR in terms of back-propagating stress wave is an intrinsic feature during dynamic ruptures; however, its signature can be easily masked by the destructive interference behind the primary rupture front. Then, we propose an idea that perturbation to an otherwise smooth rupture process may make some phases of BPR observable. We test and verify this idea by numerically simulating rupture propagation under a variety of perturbations, including a sudden change of stress, bulk or interfacial property and fault geometry along rupture propagation path. We further cross-validate the numerical results by available observations from laboratory and natural earthquakes, and confirm that rupture "reflection" at free surface, rupture coalescence and breakage of prominent asperity are very efficient for exciting observable BPR. Based on the simulated and observed results, we classify BPR into two general types: interface wave and high-order re-rupture, depending on the stress recovery and drop before and after the arrival of BPR, respectively. Our work clarifies the nature and excitation of BPR, and can help improve the understanding of earthquake physics, the inference of fault property distribution and evolution, and the assessment of earthquake hazard., Comment: 70 pages, 16 figures, 2 tables

Ising machines are expected to solve combinatorial optimization problems faster than the existing integer programming solvers. These problems, particularly those encountered in practical situations, typically involve inequality constraints. However, owing to the hardware limitations of the current Ising machines, solving combinatorial optimization problems with inequality constraints remains challenging. The Capacitated Vehicle Routing Problem (CVRP) is a typical example of a problem with inequality constraints. The objective function of the CVRP is to minimize the total distance traveled by each vehicle while limiting the total demand of customers served by a single vehicle to the vehicle's capacity. The CVRP is classified as NP-hard and, thus, is commonly solved using heuristic algorithms, such as column generation. Column generation attempts to iteratively generate only the promising routes, as the number of feasible routes increases exponentially. Within this framework, the CVRP is formulated as a set cover problem. The corresponding dual solutions are used to define the pricing subproblem, which is intended to create a new route. By applying Ising machines to this pricing subproblem, the overall computation time can be reduced. This study aims to solve combinatorial optimization problems with inequality constraints using a hybrid algorithm that combines column generation and Ising machines, thereby extending the applications of the latter. We parameterize the difficulty of the inequality constraints and demonstrate that our annealing-assisted column generation can converge to a better lower bound., Comment: 13 pages, 10 figures

Removing rain artifacts in images is recognized as a significant issue. In this field, deep learning-based approaches, such as convolutional neural networks (CNNs) and Transformers, have succeeded. Recently, State Space Models (SSMs) have exhibited superior performance across various tasks in both natural language processing and image processing due to their ability to model long-range dependencies. This study introduces SSM to rain removal and proposes a Deraining Frequency-Enhanced State Space Model (DFSSM). To effectively remove rain streaks, which produce high-intensity frequency components in specific directions, we employ frequency domain processing concurrently with SSM. Additionally, we develop a novel mixed-scale gated-convolutional block, which uses convolutions with multiple kernel sizes to capture various scale degradations effectively and integrates a gating mechanism to manage the flow of information. Finally, experiments on synthetic and real-world rainy image datasets show that our method surpasses state-of-the-art methods.

We present the development of an automated scanning probe microscopy (SPM) measurement system using an advanced large-scale language model (LLM). This SPM system can receive instructions via social networking services (SNS), and the integration of SNS and LLMs enables real-time, language-agnostic control of SPM operations, thereby improving accessibility and efficiency. The integration of LLMs with AI systems with specialized functions brings the realization of self-driving labs closer.

In this study, we critically examine the foundational premise of algorithmic recourse - a process of generating counterfactual action plans (i.e., recourses) assisting individuals to reverse adverse decisions made by AI systems. The assumption underlying algorithmic recourse is that individuals accept and act on recourses that minimize the gap between their current and desired states. This assumption, however, remains empirically unverified. To address this issue, we conducted a user study with 362 participants and assessed whether minimizing the distance function, a metric of the gap between the current and desired states, indeed prompts them to accept and act upon suggested recourses. Our findings reveal a nuanced landscape: participants' acceptance of recourses did not correlate with the recourse distance. Moreover, participants' willingness to act upon recourses peaked at the minimal recourse distance but was otherwise constant. These findings cast doubt on the prevailing assumption of algorithmic recourse research and signal the need to rethink the evaluation functions to pave the way for human-centered recourse generation., Comment: Accepted at IJCAI 2024 (this is the extended version with supplementary materials)

For the first time, we introduce a rapid wavelength-swept, passively mode-locked fiber laser in an all-polarization-maintaining and all-fiber configuration. Achieving an exceptional wavelength sweep rate of up to 19 kHz through external modulation of the LD driver pump current, this laser offers a high sweep rate, simple cavity design, cost-effectiveness, and excellent repeatability., Comment: 7 pages, 5 figures, 25 reference

We investigate the nature of the short-term anomaly that appears in the lensing light curve of KMT-2023-BLG-1866. The anomaly was only partly covered due to its short duration, less than a day, coupled with cloudy weather conditions and restricted nighttime duration. Considering intricacy of interpreting partially covered signals, we thoroughly explore all potential degenerate solutions. Through this process, we identify three planetary scenarios that equally well account for the observed anomaly. These scenarios are characterized by the specific planetary parameters: $(s, q)_{\rm inner} = [0.9740 \pm 0.0083, (2.46 \pm 1.07) \times 10^{-5}]$, $(s, q)_{\rm intermediate} = [0.9779 \pm 0.0017, (1.56 \pm 0.25)\times 10^{-5}]$, and $(s, q)_{\rm outer} = [0.9894 \pm 0.0107, (2.31 \pm 1.29)\times 10^{-5}]$, where $s$ and $q$ denote the projected separation (scaled to the Einstein radius) and mass ratio between the planet and its host, respectively. We identify that the ambiguity between the inner and outer solutions stems from the inner-outer degeneracy, while the similarity between the intermediate solution and the others is due to an accidental degeneracy caused by incomplete anomaly coverage. Through Bayesian analysis utilizing the constraints derived from measured lensing observables and blending flux, our estimation indicates that the lens system comprises a very low-mass planet orbiting an early M-type star situated approximately (6.2 -- 6.5)~kpc from Earth in terms of median posterior values for the different solutions. The median mass of the planet host is in the range of (0.48 -- 0.51)~$M_\odot$, and that of the planet's mass spans a range of (2.6 -- 4.0)~$M_{\rm E}$, varying across different solutions. The detection of KMT-2023-BLG-1866Lb signifies the extension of the lensing surveys to very low-mass planets that have been difficult to be detected from earlier surveys., Comment: 9 pages, 8 figures, 4 tables

We investigated photon-helicity-induced magnetization precession in Co$_{1-x}$Pt$_{x}$ alloy thin films. In addition to field-like torque, attributable to magnetic field generation owing to {\it the inverse Faraday effect}, we observed non-trivial and large damping-like torque which has never been discussed for single ferromagnetic layer. The composition dependence of those two torques is effectively elucidated by a model that considers mutual coupling via spin-orbit interaction between magnetization and the electronic orbital angular momentum generated by photon-helicity. This work significantly enhances our understanding of the physics relevant to the interplay of photon-helicity and magnetization in magnetic metals., Comment: 6 pages, 4 figures

We approach designing a state-space model for deep learning applications through its dual representation, the transfer function, and uncover a highly efficient sequence parallel inference algorithm that is state-free: unlike other proposed algorithms, state-free inference does not incur any significant memory or computational cost with an increase in state size. We achieve this using properties of the proposed frequency domain transfer function parametrization, which enables direct computation of its corresponding convolutional kernel's spectrum via a single Fast Fourier Transform. Our experimental results across multiple sequence lengths and state sizes illustrates, on average, a 35% training speed improvement over S4 layers -- parametrized in time-domain -- on the Long Range Arena benchmark, while delivering state-of-the-art downstream performances over other attention-free approaches. Moreover, we report improved perplexity in language modeling over a long convolutional Hyena baseline, by simply introducing our transfer function parametrization. Our code is available at https://github.com/ruke1ire/RTF., Comment: Resubmission 02/06/2024: Fixed minor typo of recurrent form RTF

Content creation today often takes place via collaborative writing. A longstanding interest of CSCW research lies in understanding and promoting the coordination between co-writers. However, little attention has been paid to individuals who write in their non-native language and to co-writer groups involving them. We present a mixed-method study that fills the above gap. Our participants included 32 co-writer groups, each consisting of one native speaker (NS) of English and one non-native speaker (NNS) with limited proficiency. They performed collaborative writing adopting two different workflows: half of the groups began with NNSs taking the first editing turn and half had NNSs act after NSs. Our data revealed a "late-mover disadvantage" exclusively experienced by NNSs: an NNS's ideational contributions to the joint document were suppressed when their editing turn was placed after an NS's turn, as opposed to ahead of it. Surprisingly, editing help provided by AI-powered tools did not exempt NNSs from being disadvantaged. Instead, it triggered NSs' overestimation of NNSs' English proficiency and agency displayed in the writing, introducing unintended tensions into the collaboration. These findings shed light on the fair assessment and effective promotion of a co-writer's contributions in language diverse settings. In particular, they underscore the necessity of disentangling contributions made to the ideational, expressional, and lexical aspects of the joint writing.

CuAl2-type transition-metal (Tr) zirconides are superconductor family, and the Tr-site element substitution largely modifies its transition temperature (Tc). Here, we synthesized polycrystalline samples of Fe1-xNixZr2 by arc melting. From magnetic susceptibility measurements, bulk superconductivity was observed for 0.4 < x < 0.8, and the highest Tc of 2.8 K was observed for x = 0.6. Specific heat measurements were also performed, bulk superconductivity was observed for 0.4 < x < 0.8, and the highest Tc of 2.6 K was observed for x = 0.6. The obtained superconductivity phase diagram exhibits dome-shaped trend, which is similar to unconventional superconductors, where magnetic fluctuations are essential for superconductivity. In addition, from the c/a lattice constant ratio analysis, we show the possible relationship between the suppression of bulk superconductivity in the Ni-rich compositions and a collapsed tetragonal transition., Comment: 16 pages, 8 figures, SI

Silver bismuth diselenide (AgBiSe2) has much attention as an efficient thermoelectric material due to its low thermal conductivity. However, AgBiSe2 exhibits multiple crystal structural transitions with temperature, and high thermoelectric performance was realized only in high-temperature cubic phase. We previously reported the stabilization of cubic phase in AgBiSe2-2xSxTex with x = 0.6-0.8 at room temperature by high-entropy-alloy (HEA) approach. The cubic HE-type AgBiSe0.8S0.6Te0.6 achieved a high ZT value of 0.8 at 748 K. In this paper, we succeeded in stabilizing the cubic phase in AgBiSe2-2xSxTex with x = 0-0.6 by ice-quenching method, and investigated the HE effect on the thermoelectric properties. Cubic AgBiSe2-2xSxTex exhibited n-type conductivity from 300 K to 10 K. We found that electronic conductivity was largely increased around room temperature with increasing the amount of S and Te, although carrier concentration showed almost the same values. The S and Te substitutions induced the variation of band structure, resulting in the carrier mobility enhancement. Furthermore, thermal conducutivity showed reduction tendency with increasing the amount of S and Te due to enhancement of phonon scattering. Simultaneous electronic conductivity increase and thermal conductivity reduction resulted in the systematic improvement of the ZT values for HE-type cubic AgBiSe2-2xSxTex., Comment: 21 pages, 7 figures

The threshold pump power for modelocking decreased by 18% when the temperature was increased from 25 to 100 degrees C, where a SWCNT/PDMS coated tapered fiber was used as the saturable absorber in a fiber laser. Further, the pump power at which multi-pulse operation began decreased by 24%, and the pump power range over which fundamental modelocking could be maintained decreased by 59% over the same temperature range. This decrease in stability is attributed to the large thermo-optic coefficient of the PDMS polymer, which results in a 40% reduction of the overlap between the evanescent field and SWCNT coating of the taper fiber over a temperature range of 75 degrees C., Comment: 10 pages, 6 figures

Repetition-rate-scanned lasers are practical in accordion frequency comb generation that serves as a variable gearbox connecting optical and radio wave domains. Rapid and wide-range scanned repetition rate can benefit versatile purposes, however scanning robustness remains unsecured that typically requires complicated feedback loops. Recently, multiplexed lasers have been demonstrated with the nature of common-noise rejection among simultaneously emitted combs. Here, we propose a bidirectional polarization-multiplexed fiber laser that delivers synchronized pulses with rapid-scanned and reference-free repetition rates. Benefiting from the all polarization-maintaining fiber configuration, the laser shows good robustness and inter-comb coherence. As rapid as 493.5 kHz/s scanning rate over 329-kHz scanning range of fundamental repetition rate is realized. The 1-hour and 1-day maximal variations of difference frequency are merely 0.52 Hz and 5.46 Hz. The capability to rebuilt steady state after mode hopping is also demonstrated. These results provide a promising solution for developing high-performance accordion-frequency laser sources., Comment: 9 pages

In the recent rapid progress of quantum technology, controlling quantum states has become an important subject of study. Of particular interest is the control of open quantum systems, where the system of interest couples to the environment in an essential way. One formalism to describe open systems is the non-Hermitian quantum mechanics. Photonics systems have been a major platform to study non-Hermitian quantum mechanics due to its flexibility in engineering gain and loss. Ultracold atomic gases have also used to study non-Hermitian quantum mechanics. However, unlike in photonics, gain is not easily controllable in ultracold atomic gases, and exploration of non-Hermitian physics has been limited to control of losses. In this paper, we report engineering of effective gain through evaporative cooling of judiciously chosen initial thermal atoms. We observe resulting formation of Bose-Einstein condensation (BEC) in excited eigenstates of a synthetic lattice. We realize formation of BEC in a topological edge state of the Su-Schrieffer-Heeger lattice in the synthetic hyperfine lattice, which can be regarded as atomic laser oscillations at a topological edge mode, i.e. topological atom laser. Gain-loss engineering in ultracold atoms opens a novel prospect to explore open many-body quantum systems., Comment: 13 pages, 7 figures

We present the analysis of the microlensing event OGLE-2015-BLG-0845, which was affected by both the microlensing parallax and xallarap effects. The former was detected via the simultaneous observations from the ground and Spitzer, and the latter was caused by the orbital motion of the source star in a relatively close binary. The combination of these two effects led to a mass measurement of the lens object, revealing a low-mass ($0.14 \pm 0.05 M_{\odot}$) M-dwarf at the bulge distance ($7.6 \pm 1.0$ kpc). The source binary consists of a late F-type subgiant and a K-type dwarf of $\sim1.2 M_{\odot}$ and $\sim 0.9 M_{\odot}$, respectively, and the orbital period is $70 \pm 10$ days. OGLE-2015-BLG-0845 is the first single-lens event in which the lens mass is measured via the binarity of the source. Given the abundance of binary systems as potential microlensing sources, the xallarap effect may not be a rare phenomenon. Our work thus highlights the application of the xallarap effect in the mass determination of microlenses, and the same method can be used to identify isolated dark lenses., Comment: New version after the review process. Accepted for publication in Monthly Notices of the Royal Astronomical Society

We demonstrate a 783-MHz fundamental repetition rate mode-locked Er-doped all-fiber ring laser with a pulse width of 623 fs. By using carbon nanotubes (CNT) saturable absorber (SA), a relatively low self-starting pump threshold of 108 mW is achieved. The laser has a very compact footprint less than 10 cm * 10 cm, benefiting from the all-active-fiber cavity design. The robust mode-locking is confirmed by the low relative intensity noise (RIN) and a long-term stability test. We propose a new scheme for generating high repetition rate femtosecond optical pulses from a compact and stable all-active-fiber ring oscillator., Comment: 11 pages, 5 figures, 1 table

We present an advanced scanning probe microscopy system enhanced with artificial intelligence (AI-SPM) designed for self-driving atomic-scale measurements. This system expertly identifies and manipulates atomic positions with high precision, autonomously performing tasks such as spectroscopic data acquisition and atomic adjustment. An outstanding feature of AI-SPM is its ability to detect and adapt to surface defects, targeting or avoiding them as necessary. It's also engineered to address typical challenges such as positional drift and tip apex atomic variations due to the thermal effect, ensuring accurate, site-specific surface analyses. Our tests under the demanding conditions of room temperature have demonstrated the robustness of the system, successfully navigating thermal drift and tip fluctuations. During these tests on the Si(111)-(7x7) surface, AI-SPM autonomously identified defect-free regions and performed a large number of current-voltage spectroscopy measurements at different adatom sites, while autonomously compensating for thermal drift and monitoring probe health. These experiments produce extensive data sets that are critical for reliable materials characterization and demonstrate the potential of AI-SPM to significantly improve data acquisition. The integration of AI into SPM technologies represents a step toward more effective, precise and reliable atomic-level surface analysis, revolutionizing materials characterization methods.

We report the H, C, and N isotopic compositions of microscale (0.2 to 2$\mu$m) organic matter in samples of asteroid Ryugu and the Orgueil CI carbonaceous chondrite. Three regolith particles of asteroid Ryugu, returned by the Hayabusa2 spacecraft, and several fragments of Orgueil were analyzed by NanoSIMS isotopic imaging. The isotopic distributions of the Ryugu samples from two different collection spots are closely similar to each other and to the Orgueil samples, strengthening the proposed Ryugu-CI chondrite connection. Most individual sub-$\mu$m organic grains have isotopic compositions within error of bulk values, but 2-8% of them are outliers exhibiting large isotopic enrichments or depletions in D, $^{15}$N, and/or $^{13}$C. The H, C and N isotopic compositions of the outliers are not correlated with each other: while some C-rich grains are both D- and $^{15}$N-enriched, many are enriched or depleted in one or the other system. This most likely points to a diversity in isotopic fractionation pathways and thus diversity in the local formation environments for the individual outlier grains. The observation of a relatively small population of isotopic outlier grains can be explained either by escape from nebular and/or parent body homogenization of carbonaceous precursor material or addition of later isotopic outlier grains. The strong chemical similarity of isotopically typical and isotopically outlying grains, as reflected by synchrotron x-ray absorption spectra, suggests a genetic connection and thus favors the former, homogenization scenario. However, the fact that even the least altered meteorites show the same pattern of a small population of outliers on top of a larger population of homogenized grains indicates that some or most of the homogenization occurred prior to accretion of the macromolecular organic grains into asteroidal parent bodies., Comment: Accepted for publication in Earth and Planetary Science Letters. 8 figures (plus 3 supplementary figs), two tables

We report the magnetic properties of a cobalt oxalate metal-organic-framework featuring the hyperoctagon lattice. Our thermodynamic measurements reveal the $J_{\rm{eff}}$ = 1/2 state of the high-spin Co$^{2+}$ (3$\textit{d}^{7}$) ion and the two successive magnetic transitions at zero field with two-stage entropy release. $^{13}$C-NMR measurements reveal the absence of an internal magnetic field in the intermediate temperature phase. Multiple field-induced phases are observed before full saturation at around 40 T. We argue the unique cobalt oxalate network gives rise to the Kitaev interaction and/or a bond frustration effect, providing an unconventional platform for frustrated magnetism on the hyperoctagon lattice., Comment: 6 pages, 4 figures

We are aimed at giving a differential geometric, and accordingly physical, explanation of the 576-periodicity of TMF. In this paper, we settle the problem of giving the lower bound 576. We formulate the problem as follows: we assume a spectrum $\mathrm{SQFT}$ with some conditions, suggest from physical considerations about the classifying spectrum for two-dimensional $\mathcal{N}=(0,1)$-supersymmetric quantum field theories, and show that the periodicity of $\mathrm{SQFT}$ is no less than 576. The main tool for the proof is the analogue of the Anderson duality pairing introduced by the second-named author and Tachikawa. We do not rely on the Segal-Stolz-Teichner conjecture, so in particular we do not use any comparison map with TMF., Comment: 30 pages

Teaching unbiased decision-making is crucial for addressing biased decision-making in daily life. Although both raising awareness of personal biases and providing guidance on unbiased decision-making are essential, the latter topics remains under-researched. In this study, we developed and evaluated an AI system aimed at educating individuals on making unbiased decisions using fairness-aware machine learning. In a between-subjects experimental design, 99 participants who were prone to bias performed personal assessment tasks. They were divided into two groups: a) those who received AI guidance for fair decision-making before the task and b) those who received no such guidance but were informed of their biases. The results suggest that although several participants doubted the fairness of the AI system, fair machine guidance prompted them to reassess their views regarding fairness, reflect on their biases, and modify their decision-making criteria. Our findings provide insights into the design of AI systems for guiding fair decision-making in humans., Comment: 18 pages, 8 figures, proceeding of ACM CHI 2024

We undertake a project to reexamine microlensing data gathered from high-cadence surveys. The aim of the project is to reinvestigate lensing events with light curves exhibiting intricate anomaly features associated with caustics, yet lacking prior proposed models to explain these features. Through detailed reanalyses considering higher-order effects, we identify that accounting for orbital motions of lenses is vital in accurately explaining the anomaly features observed in the light curves of the lensing events OGLE-2018-BLG-0971, MOA-2023-BLG-065, and OGLE-2023-BLG-0136. We estimate the masses and distances to the lenses by conducting Bayesian analyses using the lensing parameters of the newly found lensing solutions. From these analyses, we identify that the lenses of the events OGLE-2018-BLG-0971 and MOA-2023-BLG-065 are binaries composed of M dwarfs, while the lens of OGLE-2023-BLG-0136 is likely to be a binary composed of an early K-dwarf primary and a late M-dwarf companion. For all lensing events, the probability of the lens residing in the bulge is considerably higher than that of it being located in the disk., Comment: 11 pages, 13 figures, 6 tables

Sparse Bayesian learning has promoted many effective frameworks for brain activity decoding, especially for the reconstruction of muscle activity. However, existing sparse Bayesian learning mainly employs Gaussian distribution as error assumption in the reconstruction task, which is not necessarily the truth in the real-world application. On the other hand, brain recording is known to be highly noisy and contains many non-Gaussian noises, which could lead to significant performance degradation for sparse Bayesian learning method. The goal of this paper is to propose a new robust implementation for sparse Bayesian learning, so that robustness and sparseness can be realized simultaneously. Motivated by the great robustness of maximum correntropy criterion (MCC), we proposed an integration of MCC into the sparse Bayesian learning regime. To be specific, we derived the explicit error assumption inherent in the MCC and then leveraged it for the likelihood function. Meanwhile, we used the automatic relevance determination (ARD) technique for the sparse prior distribution. To fully evaluate the proposed method, a synthetic dataset and a real-world muscle activity reconstruction task with two different brain modalities were employed. Experimental results showed that our proposed sparse Bayesian correntropy learning framework improves significantly the robustness in a noisy regression task. The proposed method can realize higher correlation coefficient and lower root mean squared error in the real-world muscle activity reconstruction tasks. Sparse Bayesian correntropy learning provides a powerful tool for neural decoding which can promote the development of brain-computer interfaces.

As thermoelectric generators can convert waste heat into electricity, they play an important role in energy harvesting. The metal chalcogenide AgBiSe2 is one of the high-performance thermoelectric materials with low lattice thermal conductivity (klat), but it exhibits temperature-dependent crystal structural transitions from hexagonal to rhombohedral, and finally a cubic phase as the temperature rises. The high figure-of-merit ZT is obtained only for the high-temperature cubic phase. In this study, we utilized the high-entropy-alloy (HEA) concept for AgBiSe2 to stabilize the cubic phase throughout the entire temperature range with enhanced thermoelectric performance. We synthesized high-entropy-type AgBiSe2-2xSxTex bulk polycrystals and realized the stabilization of the cubic phase from room temperature to 800 K for x > 0.6. The ultra-low klat at of 0.30 Wm^-1K^-1 and the high peak ZT 0.9 at around 750 K were realized for cubic AgBiSe2-2xSxTex without carrier tuning. In addition, the average ZT value of x = 0.6 and 0.7 for the temperature range of 360-750 K increased to 0.38 and 0.40, respectively, which are comparable to the highest previously reported values., Comment: 44 pages, 8 figures

In this paper, we propose a new efficient method for a sparse Gaussian graphical model with hidden clustering structures by extending a dual spectral projected gradient (DSPG) method proposed by Nakagaki et al.~(2020). We establish the global convergence of the proposed method to an optimal solution, and we show that the projection onto the feasible region can be solved with a low computational complexity by the use of the pool-adjacent-violators algorithm. Numerical experiments on synthesis data and real data demonstrate the efficiency of the proposed method. The proposed method takes 0.91 seconds to achieve a similar solution to the direct application of the DSPG method which takes 4361 seconds., Comment: 21 pages, 3 figures