Search

We investigate the previous microlensing data collected by the KMTNet survey in search of anomalous events for which no precise interpretations of the anomalies have been suggested. From this investigation, we find that the anomaly in the lensing light curve of the event KMT-2021-BLG-1547 is approximately described by a binary-lens (2L1S) model with a lens possessing a giant planet, but the model leaves unexplained residuals. We investigate the origin of the residuals by testing more sophisticated models that include either an extra lens component (3L1S model) or an extra source star (2L2S model) to the 2L1S configuration of the lens system. From these analyses, we find that the residuals from the 2L1S model originate from the existence of a faint companion to the source. The 2L2S solution substantially reduces the residuals and improves the model fit by $\Delta\chi^2=67.1$ with respect to the 2L1S solution. The 3L1S solution also improves the fit, but its fit is worse than that of the 2L2S solution by $\Delta\chi^2=24.7$. According to the 2L2S solution, the lens of the event is a planetary system with planet and host masses $(M_{\rm p}/M_{\rm J}, M_{\rm h}/M_\odot)=\left( 1.47^{+0.64}_{-0.77}, 0.72^{+0.32}_{-0.38}\right)$ lying at a distance $\D_{\rm L} =5.07^{+0.98}_{-1.50}$~kpc, and the source is a binary composed of a subgiant primary of a late G or an early K spectral type and a main-sequence companion of a K spectral type. The event demonstrates the need of sophisticated modeling for unexplained anomalies for the construction of a complete microlensing planet sample., Comment: 9 pages, 4 tables, 7 figures

Kilonovae are a rare class of astrophysical transients powered by the radioactive decay of nuclei heavier than iron, synthesized in the merger of two compact objects. Over the first few days, the kilonova evolution is dominated by a large number of radioactive isotopes contributing to the heating rate. On timescales of weeks to months, its behavior is predicted to differ depending on the ejecta composition and merger remnant. However, late-time observations of known kilonovae are either missing or limited. Here we report observations of a luminous red transient with a quasi-thermal spectrum, following an unusual gamma-ray burst of long duration. We classify this thermal emission as a kilonova and track its evolution up to two months after the burst. At these late times, the recession of the photospheric radius and the rapidly-decaying bolometric luminosity ($L_{\rm bol}\propto t^{-2.7\pm 0.4}$) support the recombination of lanthanide-rich ejecta as they cool., Comment: 47 pages, 14 figures, 9 tables; submitted; a minor typo fixed

We present an analysis of microlensing event OGLE-2019-BLG-0825. This event was identified as a planetary candidate by preliminary modeling. We find that significant residuals from the best-fit static binary-lens model exist and a xallarap effect can fit the residuals very well and significantly improves $\chi^2$ values. On the other hand, by including the xallarap effect in our models, we find that binary-lens parameters like mass-ratio, $q$, and separation, $s$, cannot be constrained well. However, we also find that the parameters for the source system like the orbital period and semi major axis are consistent between all the models we analyzed. We therefore constrain the properties of the source system better than the properties of the lens system. The source system comprises a G-type main-sequence star orbited by a brown dwarf with a period of $P\sim5$ days. This analysis is the first to demonstrate that the xallarap effect does affect binary-lens parameters in planetary events. It would not be common for the presence or absence of the xallarap effect to affect lens parameters in events with long orbital periods of the source system or events with transits to caustics, but in other cases, such as this event, the xallarap effect can affect binary-lens parameters., Comment: 19 pages, 7 figures, 6 tables. Accepted by AJ

We complete the analysis of planetary candidates found by the KMT AnomalyFinder for the 2017 prime fields that cover $\sim 13\,{\rm deg}^2$. We report 3 unambiguous planets: OGLE-2017-BLG-0640, OGLE-2017-BLG-1275, and OGLE-2017-BLG-1237. The first two of these were not previously identified, while the last was not previously published due to technical complications induced by a nearby variable. We further report that a fourth anomalous event, the previously recognized OGLE-2017-BLG-1777, is very likely to be planetary, although its light curve requires unusually complex modeling because the lens and source both have orbiting companions. One of the 3 unambiguous planets, OGLE-2017-BLG-1275 is the first AnomalyFinder discovery that has a {\it Spitzer} microlens parallax measurement, $\pi_E \sim 0.045\pm0.015$, implying that this planetary system almost certainly lies in the Galactic bulge. In the order listed, the four planetary events have planet-host mass ratios $q$, and normalized projected separations $s$, of $(\log q,s)$ = $(-2.31,0.61)$, $(-2.06,0.63/1.09)$, $(-2.10,1.04)$, and $(-2.86,0.72)$. Combined with previously published events, the 2017 AnomalyFinder prime fields contain 11 unambiguous planets with well-measured $q$ and one very likely candidate, of which 3 are AnomalyFinder discoveries. In addition to these 12, there are three other unambiguous planets with large uncertainties in $q$., Comment: 67 pages, 13 figures, 16 tables

As a part of the project aiming to build a homogeneous sample of binary-lens (2L1S) events containing brown-dwarf (BD) companions, we investigate the 2021 season microlensing data collected by the Korea Microlensing Telescope Network (KMTNet) survey. For this purpose, we first identify 2L1S events by conducting systematic analyses of anomalous lensing events. We then select candidate BD-companion events by applying the criterion that the mass ratio between the lens components is less than $q_{\rm th}\sim 0.1$. From this procedure, we find four binary-lens events including KMT-2021-BLG-0588, KMT-2021-BLG-1110, KMT-2021-BLG-1643, and KMT-2021-BLG-1770, for which the estimated mass ratios are $q\sim 0.10$, 0.07, 0.08, and 0.15, respectively. The event KMT-2021-BLG-1770 is selected as a candidate despite the fact that the mass ratio is slightly greater than $q_{\rm th}$ because the lens mass expected from the measured short time scale of the event, $t_{\rm E}\sim 7.6$~days, is small. From the Bayesian analyses, we estimate that the primary and companion masses are $(M_1/M_\odot, M_2/M_\odot)= (0.54^{+0.31}_{-0.24}, 0.053^{+0.031}_{-0.023})$ for KMT-2021-BLG-0588L, $(0.74^{+0.27}_{-0.35}, 0.055^{+0.020}_{-0.026})$ for KMT-2021-BLG-1110L, $(0.73^{+0.24}_{-0.17}, 0.061^{+0.020}_{-0.014})$ for KMT-2021-BLG-1643L, and $(0.13^{+0.18}_{-0.07}, 0.020^{+0.028}_{-0.011})$ for KMT-2021-BLG-1770L. It is estimated that the probabilities of the lens companions being in the BD mass range are 82\%, 85\%, 91\%, and 59\% for the individual events. For confirming the BD nature of the lens companions found in this and previous works by directly imaging the lenses from future high-resolution adaptive-optics (AO) followup observations, we provide the lens-source separations expected in 2030, which is an approximate year of the first AO light on 30~m class telescopes., Comment: 11 pages, 10 tables, 8 figures

We investigate the microlensing data collected in the 2022 season from the high-cadence microlensing surveys in order to find weak signals produced by planetary companions to lenses. From these searches, we find that two lensing events KMT-2022-BLG-0475 and KMT-2022-BLG-1480 exhibit weak short-term anomalies. From the detailed modeling of the lensing light curves, we identify that the anomalies are produced by planetary companions with a mass ratio to the primary of $q\sim 1.8\times 10^{-4}$ for KMT-2022-BLG-0475L and a ratio $q\sim 4.3\times 10^{-4}$ for KMT-2022-BLG-1480L. It is estimated that the host and planet masses and the projected planet-host separation are $(M_{\rm h}/M_\odot, M_{\rm p}/M_{\rm U}, a_\perp/{\rm au}) = (0.43^{+0.35}_{-0.23}, 1.73^{+1.42}_{-0.92}, 2.03^{+0.25}_{-0.38})$ for KMT-2022-BLG-0475L, and $(0.18^{+0.16}_{-0.09}, 1.82^{+1.60}_{-0.92}, 1.22^{+0.15}_{-0.14})$ for KMT-2022-BLG-1480L, where $M_{\rm U}$ denotes the mass of Uranus. Both planetary systems share common characteristics that the primaries of the lenses are early-mid M dwarfs lying in the Galactic bulge and the companions are ice giants lying beyond the snow lines of the planetary systems., Comment: 10 pages, 10 figures

We consider a contextual bandit problem with $S $ contexts and $A $ actions. In each round $t=1,2,\dots$ the learner observes a random context and chooses an action based on its past experience. The learner then observes a random reward whose mean is a function of the context and the action for the round. Under the assumption that the contexts can be lumped into $r\le \min\{S ,A \}$ groups such that the mean reward for the various actions is the same for any two contexts that are in the same group, we give an algorithm that outputs an $\epsilon$-optimal policy after using at most $\widetilde O(r (S +A )/\epsilon^2)$ samples with high probability and provide a matching $\widetilde\Omega(r (S +A )/\epsilon^2)$ lower bound. In the regret minimization setting, we give an algorithm whose cumulative regret up to time $T$ is bounded by $\widetilde O(\sqrt{r^3(S +A )T})$. To the best of our knowledge, we are the first to show the near-optimal sample complexity in the PAC setting and $\widetilde O(\sqrt{{poly}(r)(S+K)T})$ minimax regret in the online setting for this problem. We also show our algorithms can be applied to more general low-rank bandits and get improved regret bounds in some scenarios.

We measure the Einstein radius of the single-lens microlensing event KMT-2022-BLG-2397 to be theta_E=24.8 +- 3.6 uas, placing it at the upper shore of the Einstein Desert, 9 < theta_E / uas < 25, between free-floating planets (FFPs) and bulge brown dwarfs (BDs). In contrast to the six BD (25 < theta_E < 50) events presented by Gould+22, which all had giant-star source stars, KMT-2022-BLG-2397 has a dwarf-star source, with angular radius theta_* ~ 0.9 uas. This prompts us to study the relative utility of dwarf and giant sources for characterizing FFPs and BDs from finite-source point-lens (FSPL) microlensing events. We find `dwarfs' (including main-sequence stars and subgiants) are likely to yield twice as many theta_E measurements for BDs and a comparable (but more difficult to quantify) improvement for FFPs. We show that neither current nor planned experiments will yield complete mass measurements of isolated bulge BDs, nor will any other planned experiment yield as many theta_E measurements for these objects as KMT. Thus, the currently anticipated 10-year KMT survey will remain the best way to study bulge BDs for several decades to come., Comment: 45 pages, 9 Figures, submitted to AAS Journals

Regret Matching+ (RM+) and its variants are important algorithms for solving large-scale games. However, a theoretical understanding of their success in practice is still a mystery. Moreover, recent advances on fast convergence in games are limited to no-regret algorithms such as online mirror descent, which satisfy stability. In this paper, we first give counterexamples showing that RM+ and its predictive version can be unstable, which might cause other players to suffer large regret. We then provide two fixes: restarting and chopping off the positive orthant that RM+ works in. We show that these fixes are sufficient to get $O(T^{1/4})$ individual regret and $O(1)$ social regret in normal-form games via RM+ with predictions. We also apply our stabilizing techniques to clairvoyant updates in the uncoupled learning setting for RM+ and prove desirable results akin to recent works for Clairvoyant online mirror descent. Our experiments show the advantages of our algorithms over vanilla RM+-based algorithms in matrix and extensive-form games.

Recently, there have been reports of various types of degeneracies in the interpretation of planetary signals induced by planetary caustics. In this work, we check whether such degeneracies persist in the case of well-covered signals by analyzing the lensing event KMT-2021-BLG-1150, for which the light curve exhibits a densely and continuously covered short-term anomaly. In order to identify degenerate solutions, we thoroughly investigate the parameter space by conducting dense grid searches for the lensing parameters. We then check the severity of the degeneracy among the identified solutions. We identify a pair of planetary solutions resulting from the well-known inner-outer degeneracy, and find that interpreting the anomaly is not subject to any degeneracy other than the inner-outer degeneracy. The measured parameters of the planet separation (normalized to the Einstein radius) and mass ratio between the lens components are $(s, q)_{\rm in}\sim (1.297, 1.10\times 10^{-3})$ for the inner solution and $(s, q)_{\rm out}\sim (1.242, 1.15\times 10^{-3})$ for the outer solution. According to a Bayesian estimation, the lens is a planetary system consisting of a planet with a mass $M_{\rm p}=0.88^{+0.38}_{-0.36}~M_{\rm J}$ and its host with a mass $M_{\rm h}=0.73^{+0.32}_{-0.30}~M_\odot$ lying toward the Galactic center at a distance $D_{\rm L} =3.8^{+1.3}_{-1.2}$~kpc. By conducting analyses using mock data sets prepared to mimic those obtained with data gaps and under various observational cadences, it is found that gaps in data can result in various degenerate solutions, while the observational cadence does not pose a serious degeneracy problem as long as the anomaly feature can be delineated., Comment: 9 pages, 8 figures

We inspect the microlensing data of the KMTNet survey collected during the 2018--2020 seasons in order to find lensing events produced by binaries with brown-dwarf companions. In order to pick out binary-lens events with candidate BD lens companions, we conduct systematic analyses of all anomalous lensing events observed during the seasons. By applying the selection criterion with mass ratio between the lens components of $0.03\lesssim q\lesssim 0.1$, we identify four binary-lens events with candidate BD companions, including KMT-2018-BLG-0321, KMT-2018-BLG-0885, KMT-2019-BLG-0297, and KMT-2019-BLG-0335. For the individual events, we present the interpretations of the lens systems and measure the observables that can constrain the physical lens parameters. The masses of the lens companions estimated from the Bayesian analyses based on the measured observables indicate that the probabilities for the lens companions to be in the brown-dwarf mass regime are high: 59\%, 68\%, 66\%, and 66\% for the four events respectively., Comment: 10 pages, 8 figures

We inspect 4 microlensing events KMT-2021-BLG-1968, KMT-2021-BLG-2010, KMT-2022-BLG-0371, and KMT-2022-BLG-1013, for which the light curves exhibit partially covered short-term central anomalies. We conduct detailed analyses of the events with the aim of revealing the nature of the anomalies. We test various models that can give rise to the anomalies of the individual events including the binary-lens (2L1S) and binary-source (1L2S) interpretations. Under the 2L1S interpretation, we thoroughly inspect the parameter space to check the existence of degenerate solutions, and if they exist, we test the feasibility of resolving the degeneracy. We find that the anomalies in KMT-2021-BLG-2010 and KMT-2022-BLG-1013 are uniquely defined by planetary-lens interpretations with the planet-to-host mass ratios of $q\sim 2.8\times 10^{-3}$ and $\sim 1.6\times 10^{-3}$, respectively. For KMT-2022-BLG-0371, a planetary solution with a mass ratio $q\sim 4\times 10^{-4}$ is strongly favored over the other three degenerate 2L1S solutions with different mass ratios based on the $\chi^2$ and relative proper motion arguments, and a 1L2S solution is clearly ruled out. For KMT-2021-BLG-1968, on the other hand, we find that the anomaly can be explained either by a planetary or a binary-source interpretation, making it difficult to firmly identify the nature of the anomaly. From the Bayesian analyses of the identified planetary events, we estimate that the masses of the planet and host are $(M_{\rm p}/M_{\rm J}, M_{\rm h}/M_\odot) = (1.07^{+1.15}_{-0.68}, 0.37^{+0.40}_{-0.23})$, $(0.26^{+0.13}_{-0.11}, 0.63^{+0.32}_{-0.28})$, and $(0.31^{+0.46}_{-0.16}, 0.18^{+0.28}_{-0.10})$ for KMT-2021-BLG-2010L, KMT-2022-BLG-0371L, and KMT-2022-BLG-1013L, respectively., Comment: 12 pages, 17 figures

We investigate the data collected by the high-cadence microlensing surveys during the 2022 season in search for planetary signals appearing in the light curves of microlensing events. From this search, we find that the lensing event MOA-2022-BLG-249 exhibits a brief positive anomaly that lasted for about 1 day with a maximum deviation of $\sim 0.2$~mag from a single-source single-lens model. We analyze the light curve under the two interpretations of the anomaly: one originated by a low-mass companion to the lens (planetary model) and the other originated by a faint companion to the source (binary-source model). It is found that the anomaly is better explained by the planetary model than the binary-source model. We identify two solutions rooted in the inner--outer degeneracy, for both of which the estimated planet-to-host mass ratio, $q\sim 8\times 10^{-5}$, is very small. With the constraints provided by the microlens parallax and the lower limit on the Einstein radius, as well as the blend-flux constraint, we find that the lens is a planetary system, in which a super-Earth planet, with a mass $(4.83\pm 1.44)~M_\oplus$, orbits a low-mass host star, with a mass $(0.18\pm 0.05)~M_\odot$, lying in the Galactic disk at a distance $(2.00\pm 0.42)$~kpc. The planet detection demonstrates the elevated microlensing sensitivity of the current high-cadence lensing surveys to low-mass planets., Comment: 10 pages, 9 figures

As a part of the ``Systematic KMTNet Planetary Anomaly Search" series, we report five new planets (namely, OGLE-2016-BLG-1635Lb, MOA-2016-BLG-532Lb, KMT-2016-BLG-0625Lb, OGLE-2016-BLG-1850Lb, and KMT-2016-BLG-1751Lb) and one planet candidate (KMT-2016-BLG-1855), which were found by searching $2016$ KMTNet prime fields. These $buried$ planets show a wide range of masses from Earth--class to Super--Jupiter--class, and are located in both the disk and the bulge. The ultimate goal of this series is to build a complete planet sample. Because our work provides a complementary sample to other planet detection methods, which have different detection sensitivities, our complete sample will help us to obtain a better understanding of planet demographics in our Galaxy., Comment: 38 pages, 17 figures, 12 Tables, submitted to the AAS journal

This letter proposes a novel Cloud Radio Access Network (C-RAN) traffic analysis and management model that estimates probable RAN traffic congestion and mitigate its effect by adopting a suitable handling mechanism. A computation approach is introduced to classify heterogeneous RAN traffic into distinct traffic states based on bandwidth consumption and execution time of various job requests. Further, a cloud-based traffic management is employed to schedule and allocate resources among user job requests according to the associated traffic states to minimize latency and maximize bandwidth utilization. The experimental evaluation and comparison of the proposed model with state-of-the-art methods reveal that it is effective in minimizing the worse effect of traffic congestion and improves bandwidth utilization and reduces job execution latency up to 17.07% and 18%, respectively.

We complete the publication of all microlensing planets (and ``possible planets'') identified by the uniform approach of the KMT AnomalyFinder system in the 21 KMT subprime fields during the 2019 observing season, namely KMT-2019-BLG-0298, KMT-2019-BLG-1216, KMT-2019-BLG-2783, OGLE-2019-BLG-0249, and OGLE-2019-BLG-0679 (planets), as well as OGLE-2019-BLG-0344, and KMT-2019-BLG-0304 (possible planets). The five planets have mean log mass-ratio measurements of $(-2.6,-3.6,-2.5,-2.2,-2.3)$, median mass estimates of $(1.81,0.094,1.16,7.12,3.34)\, M_{\rm Jup}$, and median distance estimates of $(6.7,2.7,5.9,6.4,5.6)\, {\rm kpc}$, respectively. The main scientific interest of these planets is that they complete the AnomalyFinder sample for 2019, which has a total of 25 planets that are likely to enter the statistical sample. We find statistical consistency with the previously published 33 planets from the 2018 AnomalyFinder analysis according to an ensemble of five tests. Of the 58 planets from 2018-2019, 23 were newly discovered by AnomalyFinder. Within statistical precision, half of all the planets have caustic crossings while half do not (as predicted by Zhu et al. 2014), an equal number of detected planets result from major-image and minor-image light-curve perturbations, and an equal number come from KMT prime fields versus subprime fields., Comment: 17 tables, 20 figures, submitted to AAS journals

For tabular data sets, we explore data and model distillation, as well as data denoising. These techniques improve both gradient-boosting models and a specialized DNN architecture. While gradient boosting is known to outperform DNNs on tabular data, we close the gap for datasets with 100K+ rows and give DNNs an advantage on small data sets. We extend these results with input-data distillation and optimized ensembling to help DNN performance match or exceed that of gradient boosting. As a theoretical justification of our practical method, we prove its equivalence to classical cross-entropy knowledge distillation. We also qualitatively explain the superiority of DNN ensembles over XGBoost on small data sets. For an industry end-to-end real-time ML platform with 4M production inferences per second, we develop a model-training workflow based on data sampling that distills ensembles of models into a single gradient-boosting model favored for high-performance real-time inference, without performance loss. Empirical evaluation shows that the proposed combination of methods consistently improves model accuracy over prior best models across several production applications deployed worldwide., Comment: 11 pages, 1 figure, 17 tables

We report the analysis of microlensing event OGLE-2017-BLG-1038, observed by the Optical Gravitational Lensing Experiment, Korean Microlensing Telescope Network, and Spitzer telescopes. The event is caused by a giant source star in the Galactic Bulge passing over a large resonant binary lens caustic. The availability of space-based data allows the full set of physical parameters to be calculated. However, there exists an eightfold degeneracy in the parallax measurement. The four best solutions correspond to very-low-mass binaries near ($M_1 = 170^{+40}_{-50} M_J$ and $M_2 = 110^{+20}_{-30} M_J$), or well below ($M_1 = 22.5^{+0.7}_{-0.4} M_J$ and $M_2 = 13.3^{+0.4}_{-0.3} M_J$) the boundary between stars and brown dwarfs. A conventional analysis, with scaled uncertainties for Spitzer data, implies a very-low-mass brown dwarf binary lens at a distance of 2 kpc. Compensating for systematic Spitzer errors using a Gaussian process model suggests that a higher mass M-dwarf binary at 6 kpc is equally likely. A Bayesian comparison based on a galactic model favors the larger-mass solutions. We demonstrate how this degeneracy can be resolved within the next ten years through infrared adaptive-optics imaging with a 40 m class telescope., Comment: 20 pages, 11 figures, 4 tables

We systematically inspect the microlensing data acquired by the KMTNet survey during the previous seasons in order to find anomalous lensing events for which the anomalies in the lensing light curves cannot be explained by the usual binary-lens or binary-source interpretations. From the inspection, we find that interpreting the three lensing events OGLE-2018-BLG-0584, KMT-2018-BLG-2119, and KMT-2021-BLG-1122 requires four-body (lens+source) models, in which either both the lens and source are binaries (2L2S event) or the lens is a triple system (3L1S event). Following the analyses of the 2L2S events presented in \citet{Han2023}, here we present the 3L1S analysis of the KMT-2021-BLG-1122. It is found that the lens of the event KMT-2021-BLG-1122 is composed of three masses, in which the projected separations (normalized to the angular Einstein radius) and mass ratios between the lens companions and the primary are $(s_2, q_2)\sim (1.4, 0.53)$ and $(s_3, q_3) \sim (1.6, 0.24)$. By conducting a Bayesian analysis, we estimate that the masses of the individual lens components are $(M_1, M_2, M_3)\sim (0.47\,M_\odot, 0.24\,M_\odot, 0.11\,M_\odot)$. The companions are separated in projection from the primary by $(a_{\perp,2}, a_{\perp,3})\sim (3.5, 4.0)$~AU. The lens of KMT-2018-BLG-2119 is the first triple stellar system detected via microlensing., Comment: 8 pages, 7 figures, 2 tables

Gradient-based meta-learning methods have primarily been applied to classical machine learning tasks such as image classification. Recently, PDE-solving deep learning methods, such as neural operators, are starting to make an important impact on learning and predicting the response of a complex physical system directly from observational data. Since the data acquisition in this context is commonly challenging and costly, the call of utilization and transfer of existing knowledge to new and unseen physical systems is even more acute. Herein, we propose a novel meta-learning approach for neural operators, which can be seen as transferring the knowledge of solution operators between governing (unknown) PDEs with varying parameter fields. Our approach is a provably universal solution operator for multiple PDE solving tasks, with a key theoretical observation that underlying parameter fields can be captured in the first layer of neural operator models, in contrast to typical final-layer transfer in existing meta-learning methods. As applications, we demonstrate the efficacy of our proposed approach on PDE-based datasets and a real-world material modeling problem, illustrating that our method can handle complex and nonlinear physical response learning tasks while greatly improving the sampling efficiency in unseen tasks.

We present the observations and analysis of a high-magnification microlensing planetary event, KMT-2022-BLG-0440, for which the weak and short-lived planetary signal was covered by both the KMTNet survey and follow-up observations. The binary-lens models with a central caustic provide the best fits, with a planet/host mass ratio, $q = 0.75$--$1.00 \times 10^{-4}$ at $1\sigma$. The binary-lens models with a resonant caustic and a brown-dwarf mass ratio are both excluded by $\Delta\chi^2 > 70$. The binary-source model can fit the anomaly well but is rejected by the ``color argument'' on the second source. From Bayesian analyses, it is estimated that the host star is likely a K or M dwarf located in the Galactic disk, the planet probably has a Neptune-mass, and the projected planet-host separation is $1.9^{+0.6}_{-0.7}$ or $4.6^{+1.4}_{-1.7}$ au, subject to the close/wide degeneracy. This is the third $q < 10^{-4}$ planet from a high-magnification planetary signal ($A \gtrsim 65$). Together with another such planet, KMT-2021-BLG-0171Lb, the ongoing follow-up program for the KMTNet high-magnification events has demonstrated its ability in detecting high-magnification planetary signals for $q < 10^{-4}$ planets, which are challenging for the current microlensing surveys., Comment: MNRAS accepted

We conduct a systematic investigation of the microlensing data collected during the previous observation seasons for the purpose of reanalyzing anomalous lensing events with no suggested plausible models. We find that two anomalous lensing events OGLE-2018-BLG-0584 and KMT-2018-BLG-2119 cannot be explained with the usual models based on either a binary-lens single-source (2L1S) or a single-lens binary-source (1L2S) interpretation. We test the feasibility of explaining the light curves with more sophisticated models by adding an extra lens (3L1S model) or a source (2L2S model) component to the 2L1S lens-system configuration. We find that a 2L2S interpretation well explains the light curves of both events, for each of which there are a pair of solutions resulting from the close and wide degeneracy. For the event OGLE-2018-BLG-0584, the source is a binary composed of two K-type stars, and the lens is a binary composed of two M dwarfs. For KMT-2018-BLG-2119, the source is a binary composed of two dwarfs of G and K spectral types, and the lens is a binary composed of a low-mass M dwarf and a brown dwarf., Comment: 9 pages, 9 figures

Events deviating from normal traffic patterns in driving, anomalies, such as aggressive driving or bumpy roads, may harm delivery efficiency for transportation and logistics (T&L) business. Thus, detecting anomalies in driving is critical for the T&L industry. So far numerous researches have used vehicle sensor data to identify anomalies. Most previous works captured anomalies by using deep learning or machine learning algorithms, which require prior training processes and huge computational costs. This study proposes a method namely Anomaly Detection in Driving by Cluster Analysis Twice (ADDCAT) which clusters the processed sensor data in different physical properties. An event is said to be an anomaly if it never fits with the major cluster, which is considered as the pattern of normality in driving. This method provides a way to detect anomalies in driving with no prior training processes and huge computational costs needed. This paper validated the performance of the method on an open dataset.

Cloud computing has become inevitable for every digital service which has exponentially increased its usage. However, a tremendous surge in cloud resource demand stave off service availability resulting into outages, performance degradation, load imbalance, and excessive power-consumption. The existing approaches mainly attempt to address the problem by using multi-cloud and running multiple replicas of a virtual machine (VM) which accounts for high operational-cost. This paper proposes a Fault Tolerant Elastic Resource Management (FT-ERM) framework that addresses aforementioned problem from a different perspective by inducing high-availability in servers and VMs. Specifically, (1) an online failure predictor is developed to anticipate failure-prone VMs based on predicted resource contention; (2) the operational status of server is monitored with the help of power analyser, resource estimator and thermal analyser to identify any failure due to overloading and overheating of servers proactively; and (3) failure-prone VMs are assigned to proposed fault-tolerance unit composed of decision matrix and safe box to trigger VM migration and handle any outage beforehand while maintaining desired level of availability for cloud users. The proposed framework is evaluated and compared against state-of-the-arts by executing experiments using two real-world datasets. FT-ERM improved the availability of the services up to 34.47% and scales down VM-migration and power-consumption up to 88.6% and 62.4%, respectively over without FT-ERM approach., Comment: IEEE Transactions of Network and Service Management, 2022

This article reviews the two major recent developments that significantly improved cosmological measurements of fundamental constants derived from high resolution quasar spectroscopy. The first one is the deployment of astronomical Laser Frequency Combs on high resolution spectrographs and the second one is the development of spectral analysis tools based on Artificial Intelligence methods. The former all but eliminated the previously dominant source of instrumental uncertainty whereas the latter established optimal methods for measuring the fine structure constant ($\alpha$) in quasar absorption systems. The methods can be used on data collected by the new ESPRESSO spectrograph and the future ANDES spectrograph on the Extremely Large Telescope to produce unbiased $\Delta\alpha/\alpha$ measurements with unprecedented precision., Comment: 10 pages, part of the HACK100 conference proceedings

Searches for variations of fundamental constants require accurate measurement errors. There are several potential sources of errors and quantifying each one accurately is essential. This paper addresses one source of uncertainty relating to measuring the fine structure constant on white dwarf surfaces. Detailed modelling of photospheric absorption lines requires knowing the underlying spectral continuum level. Here we describe the development of a fully automated, objective, and reproducible continuum estimation method, based on fitting cubic splines to carefully selected data regions. Example fits to the Hubble Space Telescope spectrum of the white dwarf G191-B2B are given. We carry out measurements of the fine structure constant using two continuum models. The results show that continuum placement variations result in small systematic shifts in the centroids of narrow photospheric absorption lines which impact significantly on fine structure constant measurements. This effect must therefore be included in the overall error budget of future measurements. Our results also suggest that continuum placement variations should be investigated in other contexts, including fine structure constant measurements in stars other than white dwarfs, quasar absorption line measurements of the fine structure constant, and quasar measurements of cosmological redshift drift., Comment: 10 pages, 4 figures. 4 additional files provided as supplementary material. Submitted to MNRAS 1 Dec 2022

The high resolution spectrograph ESPRESSO on the VLT allows measurements of fundamental constants at unprecedented precision and hence enables tests for spacetime variations predicted by some theories. In a series of recent papers, we developed optimal analysis procedures that both exposes and eliminates the subjectivity and bias in previous quasar absorption system measurements. In this paper we analyse the ESPRESSO spectrum of the absorption system at z_{abs}=1.15 towards the quasar HE0515-4414. Our goal here is not to provide a new unbiased measurement of fine structure constant, alpha, in this system (that will be done separately). Rather, it is to carefully examine the impact of blinding procedures applied in the recent analysis of the same data by Murphy (2022) and prior to that, in several other analyses. To do this we use supercomputer Monte Carlo AI calculations to generate a large number of independently constructed models of the absorption complex. Each model is obtained using AI-VPFIT, with alpha fixed until a "final" model is obtained, at which point alpha is then released as a free parameter for one final optimisation. The results show that the "measured" value of alpha is systematically biased towards the initially-fixed value i.e. this process produces meaningless measurements. The implication is straightforward: to avoid bias, all future measurements must include alpha as a free parameter from the beginning of the modelling process., Comment: 17 pages, 7 figures, and 5 tables. Submitted to MNRAS 1 Dec 2022