In complex systems with many degrees of freedom such as spin glass and biomolecular systems, conventional simulations in canonical ensemble suffer from the quasi-ergodicity problem. A simulation in generalized ensemble performs a random walk in potential energy space and overcomes this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review the generalized-ensemble algorithms. Three well-known methods, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present five new generalized-ensemble algorithms which are extensions of the above methods.

Spatial prediction refers to the estimation of unobserved values from spatially distributed observations. Although recent advances have improved the capacity to model diverse observation types, adoption in practice remains limited in industries that demand interpretability. To mitigate this gap, surrogate models that explain black-box predictors provide a promising path toward interpretable decision making. In this study, we propose a graph partitioning problem to construct spatial segments that minimize the sum of within-segment variances of individual predictions. The assignment of data points to segments can be formulated as a mixed-integer quadratic programming problem. While this formulation potentially enables the identification of exact segments, its computational complexity becomes prohibitive as the number of data points increases. Motivated by this challenge, we develop an approximation scheme that leverages the structural properties of graph partitioning. Experimental results demonstrate the computational efficiency of this approximation in identifying spatial segments.

We investigate the stellar shape and size-mass relationship of X-ray selected Active Galactic Nuclei (AGN) host galaxies using the high-angular resolution and deep sensitivity in the near-infrared of the COSMOS-Web JWST survey field. We present the rest-frame 1-$\mu m$ size, stellar mass, Sersic index, axis-ratio, Gini-$M_{20}$ parameters of 690 moderate luminosity AGNs between redshift 0-3 and with stellar mass $\log M_s\sim 10.75$. We find that AGN host galaxies have an effective radius of 1-5 kpc, which is between star-forming (SFG) and quiescent galaxies (QGs) of the same stellar mass. AGN hosts have similar size-mass trends as SFG and QGs, being smaller at higher redshift for the same stellar mass. The slope of the size-mass relationship of AGN host galaxies is steeper than that of star-forming galaxies. Their rest-frame 1$\mu m$ stellar morphology indicates a significant spheroidal component. We observed a low merger fraction (6%) in our sample as well as substructures similar to disks, bars, and spiral arms in the residual images, which are in tension with evolutionary pathways that require major mergers. However, it may also be due to the different timescales between mergers and AGN activity.

SBS~0335-052E is a young star-forming dwarf galaxy with a total stellar mass of $M_{*} \lesssim 10^{8}~M_{\odot}$ and an extremely low metallicity ($Z \sim 1/40~Z_{\odot}$), which has long been considered to be devoid of an active galactic nucleus (AGN). Here we report the detection of temporal flux variability of SBS~0335-052E in near-infrared (NIR) 3-4\ ${\rm \mu}$m bands on timescales of several years, showing dimming and brightening of up to 50\% over 14~years, based on archival data from the Wide-field Infrared Survey Explorer. Our spectral energy distribution (SED) fitting of archival ultraviolet (UV)-NIR photometry, including AGN SED models, indicates that the variable NIR emission arises from an edge-on AGN dust torus. The UV-optical emission from the accretion disk is obscured and does not reach us, leading to the dominance of the host galaxy's young stellar population in the UV-optical wavelengths. This analysis favors the presence of a Compton-thick, heavily obscured AGN in SBS~0335-052E, consistent with its observed X-ray weakness. From the SED fitting, we estimate an AGN bolometric luminosity of $L_{\rm bol} = 1.2\times10^{43}\ {\rm erg\ s^{-1}}$, which implies a black hole mass of $M_{\rm BH} \simeq 10^{5}\ M_\odot$ if the AGN is accreting at the Eddington limit. If confirmed, SBS~0335-052E would be the least massive galaxy known to host an AGN, likely harboring an intermediate-mass black hole.

The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data has been collected in the COSMOS field. This paper describes the collection, processing, and analysis of this new imaging data to produce a new reference photometric redshift catalog. Source detection and multi-wavelength photometry is performed for 1.7 million sources across the $2\,\mathrm{deg}^{2}$ of the COSMOS field, $\sim$966,000 of which are measured with all available broad-band data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, The Farmer, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes. Finally, a comparison is made between the performance of the photometric methodologies and of the redshift codes to demonstrate an exceptional degree of self-consistency in the resulting photometric redshifts. The i<21 sources have sub-percent photometric redshift accuracy and even the faintest sources at $25

We update the constraints on the fraction of the Universe that may have gone into primordial black holes (PBHs) over the mass range $10^{-5}\text{--}10^{50}$ g. Those smaller than $\sim 10^{15}$ g would have evaporated by now due to Hawking radiation, so their abundance at formation is constrained by the effects of evaporated particles on big bang nucleosynthesis, the cosmic microwave background (CMB), the Galactic and extragalactic $\gamma$-ray and cosmic ray backgrounds and the possible generation of stable Planck mass relics. PBHs larger than $\sim 10^{15}$ g are subject to a variety of constraints associated with gravitational lensing, dynamical effects, influence on large-scale structure, accretion and gravitational waves. We discuss the constraints on both the initial collapse fraction and the current fraction of the CDM in PBHs at each mass scale but stress that many of the constraints are associated with observational or theoretical uncertainties. We also consider indirect constraints associated with the amplitude of the primordial density fluctuations, such as second-order tensor perturbations and $\mu$-distortions arising from the effect of acoustic reheating on the CMB, if PBHs are created from the high-$\sigma$ peaks of nearly Gaussian fluctuations. Finally we discuss how the constraints are modified if the PBHs have an extended mass function, this being relevant if PBHs provide some combination of the dark matter, the LIGO/Virgo coalescences and the seeds for cosmic structure. Even if PBHs make a small contribution to the dark matter, they could play an important cosmological role and provide a unique probe of the early Universe.

The issue of shortcut learning is widely known in NLP and has been an important research focus in recent years. Unintended correlations in the data enable models to easily solve tasks that were meant to exhibit advanced language understanding and reasoning capabilities. In this survey paper, we focus on the field of machine reading comprehension (MRC), an important task for showcasing high-level language understanding that also suffers from a range of shortcuts. We summarize the available techniques for measuring and mitigating shortcuts and conclude with suggestions for further progress in shortcut research. Importantly, we highlight two concerns for shortcut mitigation in MRC: (1) the lack of public challenge sets, a necessary component for effective and reusable evaluation, and (2) the lack of certain mitigation techniques that are prominent in other areas.

We present the final results of our search for new Milky Way (MW) satellites using the data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP) survey over $\sim 1,140$ deg$^2$. In addition to three candidates that we already reported, we have identified two new MW satellite candidates in the constellation of Sextans at a heliocentric distance of $D_{\odot} \simeq 126$kpc, and Virgo at $D_{\odot} \simeq 151$kpc, named Sextans II and Virgo III, respectively. Their luminosities (Sext II:$M_V\simeq-3.9$mag; Vir III:$M_V\simeq-2.7$mag) and half-light radii (Sext II:$r_h\simeq154$ pc; Vir III:$r_h\simeq 44$ pc) place them in the region of size-luminosity space of ultra-faint dwarf galaxies (UFDs). Including four previously known satellites, there are a total of nine satellites in the HSC-SSP footprint. This discovery rate of UFDs is much higher than that predicted from the recent models for the expected population of MW satellites in the framework of cold dark matter models, thereby suggesting that we encounter a too many satellites problem. Possible solutions to settle this tension are also discussed.

Nonnegative matrix factorization (NMF) is a popular method in machine learning and signal processing to decompose a given nonnegative matrix into two nonnegative matrices. In this paper, we propose new algorithms, called majorization-minimization Bregman proximal gradient algorithm (MMBPG) and MMBPG with extrapolation (MMBPGe) to solve NMF. These iterative algorithms minimize the objective function and its potential function monotonically. Assuming the Kurdyka--Łojasiewicz property, we establish that a sequence generated by MMBPG(e) globally converges to a stationary point. We apply MMBPG and MMBPGe to the Kullback--Leibler (KL) divergence-based NMF. While most existing KL-based NMF methods update two blocks or each variable alternately, our algorithms update all variables simultaneously. MMBPG and MMBPGe for KL-based NMF are equipped with a separable Bregman distance that satisfies the smooth adaptable property and that makes its subproblem solvable in closed form. Using this fact, we guarantee that a sequence generated by MMBPG(e) globally converges to a Karush--Kuhn--Tucker (KKT) point of KL-based NMF. In numerical experiments, we compare proposed algorithms with existing algorithms on synthetic data and real-world data.

Emerging high redshift cosmological probes, in particular quasars (QSOs), show a preference for larger matter densities, $\Omega_{m} \approx 1$, within the flat $\Lambda$CDM framework. Here, using the Risaliti-Lusso relation for standardizable QSOs, we demonstrate that the QSOs recover the \textit{same} Planck-$\Lambda$CDM Universe as Type Ia supernovae (SN), $\Omega_m \approx 0.3$ at lower redshifts 0 < z \lesssim 0.7, before transitioning to an Einstein-de Sitter Universe ($\Omega_m =1$) at higher redshifts $z \gtrsim 1$. We illustrate the same trend, namely increasing $\Omega_{m}$ and decreasing $H_0$ with redshift, in SN but poor statistics prevent a definitive statement. We explain physically why the trend is expected in the flat $\Lambda$CDM cosmology, illustrate the intrinsic bias and non-Gaussian tails with mock Pantheon data, and identify a similar trend in BAO below $z=1$. Our results highlight an intrinsic bias in the flat $\Lambda$CDM Universe, whereby $\Omega_m$ increases, $H_0$ decreases and $S_8$ increases with effective redshift, thus providing a new perspective on $\Lambda$CDM tensions; even in a Planck-$\Lambda$CDM Universe the current tensions might have been expected.

We present a study of $B\to X(3872)K$ with X(3872) decaying to $D^{*0}\bar D^0$using a sample of 657 million$B\bar B$ pairs recorded at the $\Upsilon(4S)$ resonance with the Belle detector at the KEKB asymmetric-energy $e^+e^-$ collider. Both $D^{*0}\to D^0\gamma$ and $D^{*0}\to D^0\pi^0$ decay modes are used. We find a peak of $50.1^{+14.8}_{-11.1}$ events with a mass of $(3872.9^{+0.6 +0.4}_{-0.4 -0.5}){\rm MeV}/c^2$, a width of $(3.9^{+2.8 +0.2}_{-1.4 -1.1}){\rm MeV}/c^2$and a product branching fraction${\cal B}(B\to X(3872)K)\times{\cal B}(X(3872)\to D^{*0}\bar D^0)=(0.80\pm0.20\pm0.10)\times10^{-4}$, where the first errors are statistical and the second ones are systematic. The significance of the signal is $6.4\sigma$. The difference between the fitted mass and the $D^{*0}\bar D^0$ threshold is calculated to be $(1.1^{+0.6 +0.1}_{-0.4 -0.3}){\rm MeV}/c^2$. We also obtain an upper limit on the product of branching fractions ${\cal B}(B\to Y(3940)K)\times{\cal B}(Y(3940)\to D^{*0}\bar D^0)$of$0.67\times10^{-4}$ at 90% CL.

We further discuss a rotating dual giant Wilson loop (D3-brane) solution constructed in Lorentzian AdS by Drukker et al. The solution is shown to be composed of a dual giant Wilson loop and a dual giant graviton by minutely examining its shape. This observation suggests that the corresponding gauge-theory operator should be a k-th symmetric Wilson loop with the insertions of dual giant graviton operators. To support the correspondence, the classical action of the solution should be computed and compared with the gauge-theory result. For this purpose we first perform a Wick rotation to the Lorentzian solution by following the tunneling prescription and obtain Euclidean solutions corresponding to a circular or a straight-line Wilson loop. In Euclidean signature boundary terms can be properly considered in the standard manner and the classical action for the Euclidean solutions can be evaluated. The result indeed reproduces the expectation value of the k-th symmetric Wilson loop as well as the power-law behavior of the correlation function of dual giant graviton operators.

Stable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface within a broad space of atomic configurations. Generally, this requires repeated first-principles energy calculations, which is often impractical for large crystalline systems. Here, we present significant progress toward solving the crystal structure prediction problem: we performed noniterative, single-shot screening using a large library of virtually created crystal structures with a machine-learning energy predictor. This shotgun method (ShotgunCSP) has two key technical components: transfer learning for accurate energy prediction of pre-relaxed crystalline states, and two generative models based on element substitution and symmetry-restricted structure generation to produce promising and diverse crystal structures. First-principles calculations were performed only to generate the training samples and to refine a few selected pre-relaxed crystal structures. The ShotunCSP method is computationally less intensive than conventional methods and exhibits exceptional prediction accuracy, reaching 93.3% in benchmark tests with 90 different crystal structures.

The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed: the main science targets, Sgr A* and M87 along with various calibrators. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-Königl (BK) jet model. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Then, we studied the dependences of the VLBI core flux density, size, and brightness temperature on the frequency measured in the AGN host frame. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Our results indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations.

We construct Green-Schwarz (GS) light-cone closed superstring theory from type IIB matrix model. A GS light-cone string action is derived from two dimensional N=8 U(n) noncommutative Yang-Mills (NCYM) by identifying noncommutative scale with string scale. Supersymmetry transformation for the light-cone gauge action is also derived from supersymmetry transformation for IIB matrix model. By identifying the physical states and interaction vertices, string theory is perturbatively reproduced.

Quantifying the correlation between the complex structures of amorphous materials and their physical properties has been a long-standing problem in materials science. In amorphous Si, a representative covalent amorphous solid, the presence of a medium-range order (MRO) has been intensively discussed. However, the specific atomic arrangement corresponding to the MRO and its relationship with physical properties, such as thermal conductivity, remain elusive. Here, we solve this problem by combining topological data analysis, machine learning, and molecular dynamics simulations. By using persistent homology, we constructed a topological descriptor that can predict the thermal conductivity. Moreover, from the inverse analysis of the descriptor, we determined the typical ring features that correlated with both the thermal conductivity and MRO. The results provide an avenue for controlling the material characteristics through the topology of nanostructures.

Several correlations among Gamma-Ray Bursts (GRBs) quantities, both in the prompt and afterglow emissions, have been established during the last decades, thus enabling the standardization of GRBs as cosmological probes. Since GRBs are observed up to redshift $z \sim 9$, they represent a valuable tool to fill in the gap of information on the Universe evolution between the farthest type Ia supernovae and the Cosmic Microwave Background Radiation and to shed new light on the current challenging cosmological tensions. Without claiming for completeness, here we describe the state of the art of GRB correlations, their theoretical interpretations, and their cosmological applications both as standalone probes and in combination with other probes. In this framework, we pinpoint the importance of correcting the correlations for selection biases and redshift evolution to derive intrinsic relations, the assets of combining probes at different scales, and the need for the employment of the appropriate cosmological likelihood to precisely constrain cosmological parameters. Furthermore, we emphasize the benefits of the cosmographic approach to avoid any cosmological assumptions and the valuable applications of machine learning techniques to reconstruct GRB light curves and predict unknown GRB redshifts. Finally, we stress the relevance of all these factors, along with future observations, to definitely boost the power of GRBs in cosmology.