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This paper proposes a new conceptual framework called Collective Predictive Coding as a Model of Science (CPC-MS) to formalize and understand scientific activities. Building on the idea of collective predictive coding originally developed to explain symbol emergence, CPC-MS models science as a decentralized Bayesian inference process carried out by a community of agents. The framework describes how individual scientists' partial observations and internal representations are integrated through communication and peer review to produce shared external scientific knowledge. Key aspects of scientific practice like experimentation, hypothesis formation, theory development, and paradigm shifts are mapped onto components of the probabilistic graphical model. This paper discusses how CPC-MS provides insights into issues like social objectivity in science, scientific progress, and the potential impacts of AI on research. The generative view of science offers a unified way to analyze scientific activities and could inform efforts to automate aspects of the scientific process. Overall, CPC-MS aims to provide an intuitive yet formal model of science as a collective cognitive activity.

Polycyclic aromatic hydrocarbon (PAH) dust emission has been proposed as an effective extinction-independent star formation rate (SFR) indicator in the mid-infrared (MIR), but this may depend on conditions in the interstellar medium. The coverage of the AKARI/Infrared Camera (IRC) allows us to study the effects of metallicity, starburst intensity, and active galactic nuclei on PAH emission in galaxies with $f_{\nu}(L18W)\lesssim 19$ AB mag. Observations include follow-up, rest-frame optical spectra of 443 galaxies within the AKARI North Ecliptic Pole survey that have IRC detections from 7-24 $\mu$m. We use optical emission line diagnostics to infer SFR based on H$\alpha$ and [O II]$\lambda\lambda 3726,3729$ emission line luminosities. The PAH 6.2 $\mu$m and PAH 7.7 $\mu$m luminosities ($L(PAH\ 6.2\ \mu m)$ and $L(PAH\ 7.7\ \mu m)$, respectively) derived using multi-wavelength model fits are consistent with those derived from slitless spectroscopy within 0.2 dex. $L(PAH\ 6.2\ \mu m)$ and $L(PAH\ 7.7\ \mu m)$ correlate linearly with the 24 $\mu$m-dust corrected H$\alpha$ luminosity only for normal, star-forming ``main-sequence" galaxies. Assuming multi-linear correlations, we quantify the additional dependencies on metallicity and starburst intensity, which we use to correct our PAH SFR calibrations at $0

The collective reorganization of electrons into a charge density wave (CDW) inside a crystal has long served as a textbook example of an ordered phase in condensed matter physics. Two-dimensional square lattices with $p$ electrons are well-suited to the realization of CDW, due to the anisotropy of the $p$ orbitals and the resulting one dimensionality of the electronic structure. In spite of a long history of study of CDW in square-lattice systems, few reports have recognized the existence and significance of a hidden orbital degree of freedom. The degeneracy of $p_x$ and $p_y$ electrons inherent to a square lattice may give rise to nontrivial orbital patterns in real space that endow the CDW with additional broken symmetries or unusual order parameters. Using scanning tunneling microscopy, we visualize signatures of $p$-orbital texture in the CDW state of the topological semimetal candidate CeSbTe, which contains Sb square lattices with 5$p$ electrons. We image atomic-sized, anisotropic lobes of charge density with periodically modulating anisotropy, that ultimately can be mapped onto a microscopic pattern of $p_x$ and $p_y$ bond density waves. Our results show that even delocalized $p$ orbitals can reorganize into unexpected and emergent electronic states of matter., Comment: 19 pages, 6 figures

Transparent in-line optical power monitoring in Si programmable photonic integrated circuits (PICs) is indispensable for calibrating integrated optical devices such as optical switches and resonators. A Si waveguide (WG) photodetector (PD) based on defect-mediated photodetection is a promising candidate for a transparent in-line optical power monitor owing to its simplicity and ease of integration with a fully complementary metal-oxide-semiconductor (CMOS)-compatible process. Here, we propose a simple optical power monitoring scheme for a 2$\times$2 Mach$\unicode{x2013}$Zehnder interferometer (MZI) optical switch based on InGaAsP/Si hybrid MOS optical phase shifters. In the proposed scheme, a low-doped p-type Si WG PD with a response time of microseconds is utilized as a transparent in-line optical power monitor and the ground terminal of the MOS optical phase shifter is shared with that of the Si WG PD to enable the simple monitoring of the output optical power of the MZI. Based on this scheme, we experimentally demonstrate that the output optical power of a 2$\times$2 MZI can be simply monitored by applying a bias voltage to the Si slabs formed at the output WGs of the MZI without excess optical insertion loss.

Recently, representation learning with contrastive learning algorithms has been successfully applied to challenging unlabeled datasets. However, these methods are unable to distinguish important features from unimportant ones under simply unsupervised settings, and definitions of importance vary according to the type of downstream task or analysis goal, such as the identification of objects or backgrounds. In this paper, we focus on unsupervised image clustering as the downstream task and propose a representation learning method that enhances features critical to the clustering task. We extend a clustering-friendly contrastive learning method and incorporate a contrastive analysis approach, which utilizes a reference dataset to separate important features from unimportant ones, into the design of loss functions. Conducting an experimental evaluation of image clustering for three datasets with characteristic backgrounds, we show that for all datasets, our method achieves higher clustering scores compared with conventional contrastive analysis and deep clustering methods., Comment: 12 pages, 6 figures, 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2024)

We study the electronic structure of Ta2NiSe5 in its low-temperature semiconducting phase, using resonant inelastic x-ray scattering (RIXS) at the Ta L3 edge. We also investigate the electronic properties of Ta2NiSe5 within the density-functional theory using the generalized gradient approximation in the framework of the fully relativistic spin-polarized Dirac linear muffin-tin orbital band-structure method. While ARPES, dc transport, and optical measurements indicate that Ta2NiSe5 is a small band-gap semiconductor, DFT gives a metallic nonmagnetic solution in Ta2NiSe5 . To obtain the semiconducting ground state in Ta2 NiSe5 we use a self-interaction correction (SIC) procedure by introducing an orbital-dependent potential Vl into the Hamiltonian. We investigate theoretically the x-ray absorption spectroscopy (XAS) and RIXS spectra at the Ni and Ta L3 edges and analyze the spectra in terms of interband transitions. We investigate the RIXS spectra as a function of momentum transfer vector Q and incident photon energy. Because Ta2 NiSe5 possesses only fully occupied (Ni 3d and Se 4p) and completely empty (Ta 5d) shells with the formal valencies Ta5+ (5d0), Ni0 (3d10 ), and Se2- (4p6 ), both the Ni and Ta L3 RIXS spectra belong to a charge transfer type with ligand-to-metal excitations., Comment: 11 pages, 15 figures

A prototypical charge-transfer type Mott insulator NiS2 pyrite exhibits a metal-insulator transition with bandwidth control. Recent discoveries on surface-specific electronic states on other 3d transition-metal disulfide pyrites motivate us to further investigate the surface of NiS2, where metallic surface conduction is discussed. Here, the spectroscopic-imaging scanning-tunneling-microscopy observations revealed that the surface is not metallic, contrary to the expectation. Instead, the Mott gap is closed near step edges, suggesting possible electrical conduction from one-dimensional channels. The edge anomaly was observed irrespective of its magnetic order and is limited to the insulator phases., Comment: 5 pages, 5 figures

The facility adaptive optics of the Subaru Telescope AO188 recently received some long-awaited upgrades: a new 3224-actuator deformable mirror (DM) from ALPAO (hence the name change to AO3000 or AO3k), an upgraded GPU-based real-time computer, a visible nonlinear curvature wavefront sensor and a near-infrared wavefront sensor (NIR WFS), closing the loop at up to 2~kHz. The wavefront sensors were added in 2023, while the DM will be installed at the beginning of 2024. With these new features, AO3k will provide extreme-AO level of correction to all the instruments on the IR Nasmyth platform: The NIR-MIR camera and spectrograph IRCS, the high-resolution Doppler spectrograph IRD, and the high-contrast instrument SCExAO. AO3k will also support laser tomography (LTAO), delivering high Strehl ratio imaging with large sky coverage. The high Strehl will especially benefit SCExAO for high-contrast imaging, both in infrared and visible. The second stage extreme AO will no longer have to chase large residual atmospheric turbulence, and will focus on truly high-contrast techniques to create and stabilize dark holes, as well as coherent differential imaging techniques. We will finally be able to leverage the several high performance coronagraphs tested in SCExAO, even in the visible. AO3k will answer crucial questions as a precursor for future adaptive optics systems for ELTs, especially as a technology demonstrator for the HCI Planetary Systems Imager on the Thirty Meter Telescope. A lot of questions are still unanswered on the on-sky behavior of high actuator counts DMs, NIR wavefront sensing, the effect of rolling shutters or persistence. We present here the first on-sky results of AO3k, before the system gets fully offered to the observers in the second half of 2024. These results give us some insight on the great scientific results we hope to achieve in the future., Comment: 15 pages, 11 figures, proceedings of the SPIE Astronomical Telescopes and Instrumentation 2024 (Yokohama, Japan)

We present a catalog of optical and infrared identifications (ID) of X-ray sources in the AKARI North Ecliptic Pole (NEP) Deep field detected with Chandra covering $\sim 0.34\,{\rm deg^{2}}$ with 0.5-2 keV flux limits ranging $\sim 2 \mathrm{-} 20\times 10^{-16}\,{\rm erg\,s^{-1}\,cm^{-2}}$. The optical/near-infrared counterparts of the X-ray sources are taken from our Hyper Suprime Cam (HSC)/Subaru and Wide-Field InfraRed Camera (WIRCam)/Canada-France-Hawaii Telescope (CFHT) data because these have much more accurate source positions due to their spatial resolution than that of {Chandra} and longer wavelength infrared data. We concentrate our identifications in the HSC $g$ band and WIRCam $K_{\rm s}$ band-based catalogs. To select the best counterpart, we utilize a novel extension of the likelihood-ratio (LR) analysis, where we use the X-ray flux as well as $g - K_{\rm s}$ colors to calculate the likelihood ratio. Spectroscopic and photometric redshifts of the counterparts are summarized. Also, simple X-ray spectroscopy is made on the sources with sufficient source counts. We present the resulting catalog in an electronic form. The main ID catalog contains 403 X-ray sources and includes X-ray fluxes, luminosities, $g$ and $K_{\rm s}$ band magnitudes, redshifts, and their sources, optical spectroscopic properties, as well as intrinsic absorption column densities and power-law indices from simple X-ray spectroscopy. The identified X-ray sources include 27 Milky-Way objects, 57 type I AGNs, 131 other AGNs, and 15 galaxies. The catalog serves as a basis for further investigations of the properties of the X-ray and near-infrared sources in this field. (Abridged), Comment: 16 pages, 9 figures, Three electronic (fits) tables are included in src. Accepted to Astronomy and Astrophysics

Recent progress in neural rendering has brought forth pioneering methods, such as NeRF and Gaussian Splatting, which revolutionize view rendering across various domains like AR/VR, gaming, and content creation. While these methods excel at interpolating {\em within the training data}, the challenge of generalizing to new scenes and objects from very sparse views persists. Specifically, modeling 3D humans from sparse views presents formidable hurdles due to the inherent complexity of human geometry, resulting in inaccurate reconstructions of geometry and textures. To tackle this challenge, this paper leverages recent advancements in Gaussian Splatting and introduces a new method to learn generalizable human Gaussians that allows photorealistic and accurate view-rendering of a new human subject from a limited set of sparse views in a feed-forward manner. A pivotal innovation of our approach involves reformulating the learning of 3D Gaussian parameters into a regression process defined on the 2D UV space of a human template, which allows leveraging the strong geometry prior and the advantages of 2D convolutions. In addition, a multi-scaffold is proposed to effectively represent the offset details. Our method outperforms recent methods on both within-dataset generalization as well as cross-dataset generalization settings.

High entropy materials are often entropy stabilized, meaning that the configurational entropy from multiple elements sharing a single lattice site stabilizes the structure. In this work, we study how high-pressure synthesis conditions can stabilize or destabilize a high entropy oxide (HEO). We study the high-pressure and high-temperature phase equilibria of two well-known families of HEOs: the rock-salt structured compound (Mg,Co,Ni,Cu,Zn)O including some cation substitutions and the spinel structured (Cr,Mn,Fe,Co,Ni)$_3$O$_4$. Syntheses were performed at various temperatures, pressures, and oxygen activity levels resulting in dramatically different synthesis outcomes. In particular, in the rock salt HEO we observe the competing tenorite and wurtzite phases and the possible formation of a layered rock salt phase, while the spinel HEO is highly susceptible to decomposition into a mixture of rock-salt and corundum phases. At the highest tested pressures, 15 GPa, we discover the transformation of the spinel HEO into a metastable modified ludwigite-type structure with nominal formula (Cr,Mn,Fe,Co,Ni)$_4$O$_5$. The relationship between the synthesis conditions and the final reaction product is not straightforward. Nonetheless, we conclude that high-pressure conditions provide an important opportunity to synthesize high entropy phases that cannot be formed any other way., Comment: This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing

This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs). LLM-jp aims to develop open-source and strong Japanese LLMs, and as of this writing, more than 1,500 participants from academia and industry are working together for this purpose. This paper presents the background of the establishment of LLM-jp, summaries of its activities, and technical reports on the LLMs developed by LLM-jp. For the latest activities, visit https://llm-jp.nii.ac.jp/en/.

Work extraction is one of the most central processes in quantum thermodynamics. However, the prior analysis of optimal extractable work has been restricted to a limited operational scenario where complete information about the initial state is given. Here, we introduce a general framework of black box work extraction, which addresses the inaccessibility of information on the initial state. We show that the optimal extractable work in the black box setting is completely characterized by the performance of a composite hypothesis testing task, a fundamental problem in information theory.We employ this general relation to reduce the asymptotic black box work extraction to the quantum Stein's lemma in composite hypothesis testing, allowing us to provide their exact characterization in terms of the Helmholtz free energy. We also show a new quantum Stein's lemma motivated in this physical setting, where a composite hypothesis contains a certain correlation. Our work exhibits the importance of information about the initial state and gives a new interpretation of the quantities in the composite quantum hypothesis testing, encouraging the interplay between the physical settings and the information theory., Comment: 5+21 pages, 2 figures, improved version

We report an estimation of the injected mass composition of ultra-high energy cosmic rays (UHECRs) at energies higher than 10 EeV. The composition is inferred from an energy-dependent sky distribution of UHECR events observed by the Telescope Array surface detector by comparing it to the Large Scale Structure of the local Universe. In the case of negligible extra-galactic magnetic fields the results are consistent with a relatively heavy injected composition at E ~ 10 EeV that becomes lighter up to E ~ 100 EeV, while the composition at E > 100 EeV is very heavy. The latter is true even in the presence of highest experimentally allowed extra-galactic magnetic fields, while the composition at lower energies can be light if a strong EGMF is present. The effect of the uncertainty in the galactic magnetic field on these results is subdominant., Comment: 8 pages, 3 figures, accepted for publication in PRL

We use a new method to estimate the injected mass composition of ultrahigh cosmic rays (UHECRs) at energies higher than 10 EeV. The method is based on comparison of the energy-dependent distribution of cosmic ray arrival directions as measured by the Telescope Array experiment (TA) with that calculated in a given putative model of UHECR under the assumption that sources trace the large-scale structure (LSS) of the Universe. As we report in the companion letter, the TA data show large deflections with respect to the LSS which can be explained, assuming small extra-galactic magnetic fields (EGMF), by an intermediate composition changing to a heavy one (iron) in the highest energy bin. Here we show that these results are robust to uncertainties in UHECR injection spectra, the energy scale of the experiment and galactic magnetic fields (GMF). The assumption of weak EGMF, however, strongly affects this interpretation at all but the highest energies E > 100 EeV, where the remarkable isotropy of the data implies a heavy injected composition even in the case of strong EGMF. This result also holds if UHECR sources are as rare as $2 \times 10^{-5}$ Mpc$^{-3}$, that is the conservative lower limit for the source number density., Comment: 18 pages, 11 figures, accepted for publication in PRD

In the previous papers [Tak8,Tak6], we construct the affine varieties $\Sigma_{\mathbb{A}}^{13}$ and $\Pi_{\mathbb{A}}^{14}$ whose partial projectivizations have $\mathbb{P}^{2}\times\mathbb{P}^{2}$-fibrations. In this paper, we produce prime $\mathbb{Q}$-Fano 3-folds of anticanonical codimension 4 belonging to 23 (resp. 8) classes of Graded Ring Database [GRDB] as weighted complete intersections of weighted projectivizations of $\Sigma_{\mathbb{A}}^{13}$ (resp. $\Pi_{\mathbb{A}}^{14}$ or the cone over it). Together with the results of [CD] and [Tak5], prime $\mathbb{Q}$-Fano 3-folds of anticanonical codimension 4 are constructed for 141 classes among the 143 classes in [GRDB]., Comment: The contents of this paper consist of those of the part of [Tak2] and [Tak3] where we construct examples of $\mathbb{Q}$-Fano threefolds. arXiv admin note: substantial text overlap with arXiv:2103.11086, arXiv:2111.14328

The Atacama Large Millimeter/submillimeter Array remains the largest mm radio interferometer observatory world-wide. It is now conducting its 11th observing cycle. In our previous paper presented at this conference series in 2020, we outlined a number of possible improvements to the ALMA end-to-end observing and data processing procedures which could further optimize the uv coverage and thus the image quality while at the same time improving the observing efficiency. Here we report an update of our results refining our proposed adjustments to the scheduling and quality assurance processes. In particular we present new results on ways to assess the uv coverage of a given observation efficiently, methods to define and measure the maximum recoverable angular scale, and on the robustness of the deconvolution in the final interferometric imaging process w.r.t. defects in the uv coverage. Finally we present the outline of a design for integrating uv coverage assessment into the control and processing loop of observation scheduling. The results are applicable to all radio interferometers with more than approx. 10 antennas., Comment: 12 pages, 8 figures, to be published in the proceedings of SPIE Astronomical Telescopes and Instrumentation, 2024, Yokohama, paper no. 13098-27

We report on an observation of the difference between northern and southern skies of the ultrahigh energy cosmic ray energy spectrum with a significance of ${\sim}8\sigma$. We use measurements from the two largest experiments$\unicode{x2014}$the Telescope Array observing the northern hemisphere and the Pierre Auger Observatory viewing the southern hemisphere. Since the comparison of two measurements from different observatories introduces the issue of possible systematic differences between detectors and analyses, we validate the methodology of the comparison by examining the region of the sky where the apertures of the two observatories overlap. Although the spectra differ in this region, we find that there is only a $1.8\sigma$ difference between the spectrum measurements when anisotropic regions are removed and a fiducial cut in the aperture is applied., Comment: 8 pages, 6 figures

Although the similarity between non-stabilizer states -- also known as magic states -- in discrete-variable systems and non-Gaussian states in continuous-variable systems has widely been recognized, the precise connections between these two notions have still been unclear. We establish a fundamental link between these two quantum resources via the Gottesman-Kitaev-Preskill (GKP) encoding. We show that the negativity of the continuous-variable Wigner function for an encoded GKP state coincides with a magic measure we introduce, which matches the negativity of the discrete Wigner function for odd dimensions. We also provide a continuous-variable representation of the stabilizer R\'enyi entropy -- a recent proposal for a magic measure for multi-qubit states. With this in hand, we give a classical simulation algorithm with runtime scaling with the resource contents, quantified by our magic measures. We also employ our results to prove that implementing a multi-qubit logical non-Clifford operation in the GKP code subspace requires a non-Gaussian operation even at the limit of perfect encoding, despite the fact that the ideal GKP states already come with a large amount of non-Gaussianity.

This paper proposes a new algorithm for learning accurate tree-based models while ensuring the existence of recourse actions. Algorithmic Recourse (AR) aims to provide a recourse action for altering the undesired prediction result given by a model. Typical AR methods provide a reasonable action by solving an optimization task of minimizing the required effort among executable actions. In practice, however, such actions do not always exist for models optimized only for predictive performance. To alleviate this issue, we formulate the task of learning an accurate classification tree under the constraint of ensuring the existence of reasonable actions for as many instances as possible. Then, we propose an efficient top-down greedy algorithm by leveraging the adversarial training techniques. We also show that our proposed algorithm can be applied to the random forest, which is known as a popular framework for learning tree ensembles. Experimental results demonstrated that our method successfully provided reasonable actions to more instances than the baselines without significantly degrading accuracy and computational efficiency., Comment: 27 pages, 10 figures, to appear in the 41st International Conference on Machine Learning (ICML 2024)

Context. Ch-type asteroids are distinctive among other dark asteroids in that they exhibit deep negative polarization branches (NPBs). Nevertheless, the physical and compositional properties that cause their polarimetric distinctiveness are less investigated. Aims. We aim to investigate the polarimetric uniqueness of Ch-type asteroids by making databases of various observational quantities (i.e., spectroscopic and photometric properties as well as polarimetric ones) of dark asteroids.Methods. We conducted an intensive polarimetric survey of 52 dark asteroids (including 31 Ch-type asteroids) in the R$_\mathrm{C}$-band to increase the size of polarimetric samples. The observed data are compiled with previous polarimetric, spectroscopic, and photometric archival data to find their correlations. Results. We find remarkable correlations between these observed quantities, particularly the depth of NPBs and their spectroscopic features associated with the hydrated minerals. The amplitude of the opposition effect in photometric properties also shows correlations with polarimetric and spectral properties. However, these observed quantities do not show noticeable correlations with the geometric albedo, thermal inertia, and diameter of asteroids. Conclusions. Based on the observational evidence, we arrive at our conclusion that the submicrometer-sized structures (fibrous or flaky puff pastry-like structures in phyllosilicates) in the regolith particles could contribute to the distinctive NPBs of hydrated asteroids., Comment: 25 pages, 10 figures (Accepted for the publication of Astronomy and Astrophysics on May 30, 2024)

The two stable surfaces of GdRu2Si2 are studied using spin-polarized scanning tunneling microscopy (SP-STM). Depending on the applied magnetic field different magnetic phases have been found and the presented measurements are in agreement with the respective previously proposed multi-Q spin textures. In particular the multi-Q nature of the zero magnetic field state, for which previous experiments could not rule out the coexistence of single-Q states, can be confirmed by our spin-resolved measurements on the Si-terminated surface. The surfaces of GdRu2Si2 exhibit strong magnetism-induced modulations of the spin-averaged density of states. We find that while the magnetic contribution to the tunnel signal can be clearly identified for the Si-terminated surface this proves to be much more difficult for the Gd-terminated surface. However, the magnetic field dependent spatial modulations on the Gd-terminated surface demonstrate that additional magnetic phase transitions occur for the surface layer compared to those identified for bulk GdRu2Si2 and possible spin textures are presented., Comment: 7 pages, 5 figures

The Super-Kamiokande and T2K collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of $19.7(16.3) \times 10^{20}$ protons on target in (anti)neutrino mode, the analysis finds a 1.9$\sigma$ exclusion of CP-conservation (defined as $J_{CP}=0$) and a preference for the normal mass ordering., Comment: 10 pages, 3 figures

Triple decomposition is a useful analytical method for extracting the mean value, organized coherent motion, and stochastic part from a fluctuating quantity. Although the pressure-sensitive paint (PSP) method is widely used to measure the pressure distribution on a surface, the PSP data measuring near atmospheric pressure contain significant noise. Here, we perform triple decomposition of noisy PSP data. To construct phase-averaged data representing an organized coherent motion, we propose a relatively simple method based on a multi-dimensional scaling plot of the cosine similarity between each PSP datum. Then, the stochastic part is extracted by selecting phase-averaged data with an appropriate phase angle based on the similarity between the measurement and phase-averaged data. As a data-driven approach, we also reconstruct the pressure distribution based on the triple decomposition and the pressure data at sparse optimal sensor positions determined from the proper orthogonal decomposition modes of the stochastic part. The optimal sensor positions are determined as a combinatorial optimization problem and are estimated using Fujitsu computing as a service digital annealer. Based on the results obtained, the root mean square error between the pressure measured by a pressure transducer and the reconstructed pressure obtained by the proposed method is small, even when the number of modes and sensor points is small. The application of PSP measurement is expected to expand further, and the framework for calculating triple decomposition and sparse representation based on the decomposition will be useful for flow analysis., Comment: 18 pages

Hybrid logic is a modal logic with additional operators specifying nominals and is highly expressive. For example, there is no formula corresponding to the irreflexivity of Kripke frames in basic modal logic, but there is in hybrid logic. Irreflexivity is significant in that irreflexive and symmetric Kripke frames can be regarded as undirected graphs reviewed from a graph theoretic point of view. Thus, the study of the hybrid logic with axioms corresponding to irreflexivity and symmetry can help to elucidate the logical properties of undirected graphs. In this paper, we formulate the tableau method of the hybrid logic for undirected graphs. Our main result is to show the completeness theorem and the termination property of the tableau method, which leads us to prove the decidability., Comment: 12 pages, 3 figures, the conference 'AWPL 2024' proceeding

Human mobility data offers valuable insights for many applications such as urban planning and pandemic response, but its use also raises privacy concerns. In this paper, we introduce the Hierarchical and Multi-Resolution Network (HRNet), a novel deep generative model specifically designed to synthesize realistic human mobility data while guaranteeing differential privacy. We first identify the key difficulties inherent in learning human mobility data under differential privacy. In response to these challenges, HRNet integrates three components: a hierarchical location encoding mechanism, multi-task learning across multiple resolutions, and private pre-training. These elements collectively enhance the model's ability under the constraints of differential privacy. Through extensive comparative experiments utilizing a real-world dataset, HRNet demonstrates a marked improvement over existing methods in balancing the utility-privacy trade-off.

We present a novel and simple picture of the generation dynamics of coherent longitudinal optical (LO) phonons and LO-phonon-plasmon-coupled (LOPC) modes by the ultrafast infrared pump-pulses in gallium arsenide (GaAs) employing the low-temperature approximation. LO phonons exhibit a pronounced coupling with plasmons formed by the optically excited electrons in the excited states of GaAs. This coupling results in the coherent oscillation of the LOPC modes in the excited states. The pump pulse also induces stimulated Raman scattering, which generates the coherent LO-phonon oscillation in the ground state. This picture is incorporated into a simplified model, and the time evolution of the density operator is calculated using the Lindblad-type quantum master equation. The theoretical results explain well the reported experimental results on the coherent oscillation of LO phonons and LOPC modes observed through transient reflection measurements. Above all, our model provides a natural reason for the simultaneous manifestation of the LO phonons and the LOPC modes., Comment: 6+2 pages, 3 figures

Generating images from text has become easier because of the scaling of diffusion models and advancements in the field of vision and language. These models are trained using vast amounts of data from the Internet. Hence, they often contain undesirable content such as copyrighted material. As it is challenging to remove such data and retrain the models, methods for erasing specific concepts from pre-trained models have been investigated. We propose a novel concept-erasure method that updates the text encoder using few-shot unlearning in which a few real images are used. The discussion regarding the generated images after erasing a concept has been lacking. While there are methods for specifying the transition destination for concepts, the validity of the specified concepts is unclear. Our method implicitly achieves this by transitioning to the latent concepts inherent in the model or the images. Our method can erase a concept within 10 s, making concept erasure more accessible than ever before. Implicitly transitioning to related concepts leads to more natural concept erasure. We applied the proposed method to various concepts and confirmed that concept erasure can be achieved tens to hundreds of times faster than with current methods. By varying the parameters to be updated, we obtained results suggesting that, like previous research, knowledge is primarily accumulated in the feed-forward networks of the text encoder. Our code is available at \url{https://github.com/fmp453/few-shot-erasing}, Comment: 25 pages, 28 figures, accepted by BMVC2024

No state of matter can be defined categorically by what it is not; yet spin liquids are often conjectured to exist based on the nonexistence of magnetic order as $T \to 0$. An emerging concept designed to circumvent this ambiguity is to categorically identify each spin liquid type by using its spectrum of spontaneous spin noise. Here we introduce such a spectroscopy to spin liquid studies by considering Ca$_{10}$Cr$_7$O$_{28}$. This is a spin liquid, but whether classical or quantum and in which specific state, are unknown. By enhancing the flux-noise spectrometry techniques introduced for magnetic monopole noise studies, here we measure the time and temperature dependence of spontaneous flux $\varPhi(t,T)$ and thus magnetization $M(t,T)$ of Ca$_{10}$Cr$_7$O$_{28}$ samples. The resulting power spectral density of magnetization noise $S_M(\omega,T)$ along with its correlation function $C_M(t,T)$, reveal intense spin fluctuations spanning frequencies $0.1\ \mathrm{Hz} \leq \omega/2\pi \leq 50\ \mathrm{kHz}$, and that $S_M(\omega,T)\propto \omega^{-\alpha(T)}$ with $0.84 < \alpha(T) < 1.04$. Predictions for quantum spin liquids yield a frequency-independent spin-noise spectrum, clearly inconsistent with this phenomenology However, when compared to Monte Carlo simulations for a 2D spiral spin liquid state that are accurately parameterized to describe Ca$_{10}$Cr$_7$O$_{28}$, comprehensive quantitative correspondence with the data including $S_M(\omega,T)$, $C_M(t,T)$ and magnetization variance $\sigma_M^2(T)$ fingerprint the state of Ca$_{10}$Cr$_7$O$_{28}$ as a spiral spin liquid., Comment: 42 pages, 4 main figures, 8 supplementary figures, 2 supplementary movies

We have measured the critical current density, superconducting coherence length, and superconducting transition temperature on single-domain, epitaxially-grown Nb(110)/Au(111)/Nb(110) trilayers, all showing non-monotonic behavior as a function of the thickness of the Au layer. To reveal the underlying physical mechanism, we apply the first-principles-based microscopic theory of inhomogeneous relativistic superconductivity which predicts quantitatively the superconducting properties. As a result of the confinement in the growth direction, quantum-well states appear in the Au layer which yields a complex structure of Andreev states in the superconducting state. It is shown how the quantum-well states modify the quasiparticle spectrum and the Josephson supercurrent. Our study reveals the coexistence of the two superconducting phases in the Au layer, the usual intraband s-wave phase and an additional non-uniform phase stemming from interband pairing (without magnetic field). These results indicate the rich interplay between quantum-size and proximity effects, suggesting the possibility of modifying superconducting transport properties by exploiting thickness-dependent quantum size effect

Preceding a core-collapse supernova, various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande via inverse beta decay interactions. Once these pre-supernova neutrinos are observed, an early warning of the upcoming core-collapse supernova can be provided. In light of this, KamLAND and Super-Kamiokande, both located in the Kamioka mine in Japan, have been monitoring pre-supernova neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and Super-Kamiokande on pre-supernova neutrino detection. A pre-supernova alert system combining the KamLAND detector and the Super-Kamiokande detector was developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-supernova neutrino signal from a 15 M$_{\odot}$ star within 510 pc of the Earth, at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hours in advance., Comment: Resubmitted to ApJ. 22 pages, 16 figures, for more information about the combined pre-supernova alert system, see https://www.lowbg.org/presnalarm/

Neutrinos from very nearby supernovae, such as Betelgeuse, are expected to generate more than ten million events over 10\,s in Super-Kamokande (SK). At such large event rates, the buffers of the SK analog-to-digital conversion board (QBEE) will overflow, causing random loss of data that is critical for understanding the dynamics of the supernova explosion mechanism. In order to solve this problem, two new DAQ modules were developed to aid in the observation of very nearby supernovae. The first of these, the SN module, is designed to save only the number of hit PMTs during a supernova burst and the second, the Veto module, prescales the high rate neutrino events to prevent the QBEE from overflowing based on information from the SN module. In the event of a very nearby supernova, these modules allow SK to reconstruct the time evolution of the neutrino event rate from beginning to end using both QBEE and SN module data. This paper presents the development and testing of these modules together with an analysis of supernova-like data generated with a flashing laser diode. We demonstrate that the Veto module successfully prevents DAQ overflows for Betelgeuse-like supernovae as well as the long-term stability of the new modules. During normal running the Veto module is found to issue DAQ vetos a few times per month resulting in a total dead time less than 1\,ms, and does not influence ordinary operations. Additionally, using simulation data we find that supernovae closer than 800~pc will trigger Veto module resulting in a prescaling of the observed neutrino data., Comment: 28 pages, 18 figures. Submitted to PTEP

We propose efficient algorithms for classically simulating Gaussian unitaries and measurements applied to non-Gaussian initial states. The constructions are based on decomposing the non-Gaussian states into linear combinations of Gaussian states. We use an extension of the covariance matrix formalism to efficiently track relative phases in the superpositions of Gaussian states. We get an exact simulation that scales quadratically with the number of Gaussian states required to represent the initial state and an approximate simulation algorithm that scales linearly with the degree. We define measures of non-Gaussianty quantifying this simulation cost, which we call the Gaussian rank and the Gaussian extent. From the perspective of quantum resource theories, we investigate the properties of this type of non-Gaussianity measure and compute optimal decomposition for states relevant to continuous-variable quantum computing.

Gibbs-preserving operations have been studied as one of the standard free processes in quantum thermodynamics. Although they admit a simple mathematical structure, their operational significance has been unclear due to the potential hidden cost to implement them using an operatioanlly motivated class of operations, such as thermal operations. Here, we show that this hidden cost can be infinite -- we present a family of Gibbs-preserving operations that cannot be implemented by thermal operations aided by any finite amount of quantum coherence. Our result implies that there are uncountably many Gibbs-preserving operations that require unbounded thermodynamic resources to implement, raising a question about employing Gibbs-preserving operations as available thermodynamics processes. This finding is a consequence of the general lower bounds we provide for the coherence cost of approximately implementing a certain class of Gibbs-preserving operations with a desired accuracy. We find that our lower bound is almost tight, identifying a quantity -- related to the energy change caused by the channel to implement -- as a fundamental quantifier characterizing the coherence cost for the approximate implementation of Gibbs-preserving operations., Comment: 17 pages, 1 figure

Subsequent to the previous paper [Tak5], we are concerned with the classification of complex prime $\mathbb{Q}$-Fano $3$-folds of anti-canonical codimension 4 which are produced, as weighted complete intersections of appropriate weighted projectivizations of certain affine varieties related with $\mathbb{P}^{2}\times\mathbb{P}^{2}$-fibrations. Such affine varieties or their appropriate weighted projectivizations (possibly allowing some coordinates have weights $0$) are called key varieties for prime $\mathbb{Q}$-Fano 3-folds. The purpose of this paper is to give new constructions of a $14$-dimensional affine variety $\Upsilon_{\mathbb{A}}^{14}$ and a $15$-dimensional affine variety $\Pi_{\mathbb{A}}^{15}$ related with $\mathbb{P}^{2}\times\mathbb{P}^{2}$-fibration, which were constructed and were shown to be key varieties in the papers [Tak3,Tak4] and [Tay]. It is well-known that the affine cone of the Segre embedded $\mathbb{P}^{2}\times\mathbb{P}^{2}$ is defined as the null loci of the so called $\sharp$-mapping of a 9-dimensional nondegenerate quadratic Jordan algebra $J$ of a cubic form. Inspired with this fact, we construct $\Upsilon_{\mathbb{A}}^{14}$ and $\Pi_{\mathbb{A}}^{15}$ in the same way coordinatizing $J$ with 9 and 10 parameters, respectively. The coordinatization with $9$ parameters is derived by using a fixed primitive idempotent, and the associated Peirce decomposition. The coordinatization with $10$ parameters is derived from the construction of a quadratic Jordan subalgebra generated by $\sharp$-products of two elements due to Petersson [Pe1]., Comment: a few minor changes

We introduce a quantum extension of dynamic programming, a fundamental computational method for efficiently solving recursive problems using memory. Our innovation lies in showing how to coherently generate unitaries of recursion steps using memorized intermediate quantum states. We find that quantum dynamic programming yields an exponential reduction in circuit depth for a large class of fixed-point quantum recursions, including a known recursive variant of the Grover's search. Additionally, we apply quantum dynamic programming to a recently proposed double-bracket quantum algorithm for diagonalization to obtain a new protocol for obliviously preparing a quantum state in its Schmidt basis, providing a potential pathway for revealing entanglement structures of unknown quantum states., Comment: 6 + 23 pages, 1 figure

We present the results of the charge ratio ($R$) and polarization ($P^{\mu}_{0}$) measurements using the decay electron events collected from 2008 September to 2022 June by the Super-Kamiokande detector. Because of its underground location and long operation, we performed high precision measurements by accumulating cosmic-ray muons. We measured the muon charge ratio to be $R=1.32 \pm 0.02$ $(\mathrm{stat.}{+}\mathrm{syst.})$ at $E_{\mu}\cos \theta_{\mathrm{Zenith}}=0.7^{+0.3}_{-0.2}$ $\mathrm{TeV}$, where $E_{\mu}$ is the muon energy and $\theta_{\mathrm{Zenith}}$ is the zenith angle of incoming cosmic-ray muons. This result is consistent with the Honda flux model while this suggests a tension with the $\pi K$ model of $1.9\sigma$. We also measured the muon polarization at the production location to be $P^{\mu}_{0}=0.52 \pm 0.02$ $(\mathrm{stat.}{+}\mathrm{syst.})$ at the muon momentum of $0.9^{+0.6}_{-0.1}$ $\mathrm{TeV}/c$ at the surface of the mountain; this also suggests a tension with the Honda flux model of $1.5\sigma$. This is the most precise measurement ever to experimentally determine the cosmic-ray muon polarization near $1~\mathrm{TeV}/c$. These measurement results are useful to improve the atmospheric neutrino simulations., Comment: 29 pages, 45 figures

The first loading of gadolinium (Gd) into Super-Kamiokande in 2020 was successful, and the neutron capture efficiency on Gd reached 50\%. To further increase the Gd neutron capture efficiency to 75\%, 26.1 tons of $\rm Gd_2(\rm SO_4)_3\cdot \rm 8H_2O$ was additionally loaded into Super-Kamiokande (SK) from May 31 to July 4, 2022. As the amount of loaded $\rm Gd_2(\rm SO_4)_3\cdot \rm 8H_2O$ was doubled compared to the first loading, the capacity of the powder dissolving system was doubled. We also developed new batches of gadolinium sulfate with even further reduced radioactive impurities. In addition, a more efficient screening method was devised and implemented to evaluate these new batches of $\rm Gd_2(\rm SO_4)_3\cdot \rm 8H_2O$. Following the second loading, the Gd concentration in SK was measured to be $333.5\pm2.5$ ppm via an Atomic Absorption Spectrometer (AAS). From the mean neutron capture time constant of neutrons from an Am/Be calibration source, the Gd concentration was independently measured to be 332.7 $\pm$ 6.8(sys.) $\pm$ 1.1(stat.) ppm, consistent with the AAS result. Furthermore, during the loading the Gd concentration was monitored continually using the capture time constant of each spallation neutron produced by cosmic-ray muons,and the final neutron capture efficiency was shown to become 1.5 times higher than that of the first loaded phase, as expected., Comment: 34 pages, 13 figures, submitted to Nuclear Inst. and Methods in Physics Research, A

Among multi-messenger observations of the next galactic core-collapse supernova, Super-Kamiokande (SK) plays a critical role in detecting the emitted supernova neutrinos, determining the direction to the supernova (SN), and notifying the astronomical community of these observations in advance of the optical signal. On 2022, SK has increased the gadolinium dissolved in its water target (SK-Gd) and has achieved a Gd concentration of 0.033%, resulting in enhanced neutron detection capability, which in turn enables more accurate determination of the supernova direction. Accordingly, SK-Gd's real-time supernova monitoring system (Abe te al. 2016b) has been upgraded. SK_SN Notice, a warning system that works together with this monitoring system, was released on December 13, 2021, and is available through GCN Notices (Barthelmy et al. 2000). When the monitoring system detects an SN-like burst of events, SK_SN Notice will automatically distribute an alarm with the reconstructed direction to the supernova candidate within a few minutes. In this paper, we present a systematic study of SK-Gd's response to a simulated galactic SN. Assuming a supernova situated at 10 kpc, neutrino fluxes from six supernova models are used to characterize SK-Gd's pointing accuracy using the same tools as the online monitoring system. The pointing accuracy is found to vary from 3-7$^\circ$ depending on the models. However, if the supernova is closer than 10 kpc, SK_SN Notice can issue an alarm with three-degree accuracy, which will benefit follow-up observations by optical telescopes with large fields of view., Comment: 38 pages, 29 figures, 6 tables

Topological swirling spin textures, such as skyrmions and merons, have recently attracted much attention as a unique building block for high-density magnetic information devices. The controlled transformation among different types of such quasi-particles is an important challenge, while it was previously achieved only in a few non-centrosymmetric systems characterized by Dzyaloshinskii-Moriya interaction. Here, we report an experimental discovery of multi-step topological transitions among a variety of meron and skyrmion crystal states in a centrosymmetric magnet GdRu$_2$Ge$_2$. By performing the detailed magnetic structure analysis based on resonant X-ray and neutron scattering experiments as well as electron transport measurements, we have found that this compound hosts periodic lattice of elliptic skyrmions, meron/anti-meron pairs, and circular skyrmions as a function of external magnetic field. The diameter of these objects is as small as 2.7 nm, which is almost two orders of magnitude smaller than typical non-centrosymmetric magnets. Such an intricate manner of topological magnetic transitions are well reproduced by a theoretical model considering the competition between RKKY interactions at inequivalent wave vectors. The present findings demonstrate that even a simple centrosymmetric magnet with competing interactions can be a promising material platform to realize a richer variety of nanometric magnetic quasi-particles with distinctive symmetry and topology, whose stability may be tunable by various external stimuli., Comment: to appear in Nature Physics

Inelastic neutron scattering (INS) measurements of powder D$_3(^{7}$Li)($^{193}$Ir)$_2$O$_6$ reveal low energy magnetic excitations with a scattering cross section that is broad in $|Q|$ and consistent with a Kitaev spin-liquid (KSL) state. The magnetic nature of the excitation spectrum is demonstrated by longitudinally polarized neutron studies. The total magnetic moment of 1.7(2)$\mu_B$/Ir inferred from the total magnetic scattering cross section is consistent with the effective moment inferred from magnetic susceptibility data and expectations for the $J_{\rm eff}=1/2$ single ion state. The rise in the dynamic correlation function ${\cal S}(Q,\omega)$ for $\hbar\omega<5~$meV can be described by a nearest-neighbor Kitaev model with interaction strength $K\approx-13(5)$~meV. Exchange disorder associated with the mixed D-Li site could play an important role in stabilizing the low $T$ quantum fluctuating state., Comment: 5 pages, 4 figures

We develop the general framework of virtual resource distillation -- an alternative distillation strategy proposed in [Phys. Rev. Lett. 132, 050203 (2024)], which extends conventional quantum resource distillation by integrating the power of classical postprocessing. The framework presented here is applicable not only to quantum states, but also dynamical quantum objects such as quantum channels and higher-order processes. We provide a general characterization and benchmarks for the performance of virtual resource distillation in the form of computable semidefinite programs as well as several operationally motivated quantities. We apply our general framework to various concrete settings of interest, including standard resource theories such as entanglement, coherence, and magic, as well as settings involving dynamical resources such as quantum memory, quantum communication, and non-Markovian dynamics. The framework of probabilistic distillation is also discussed., Comment: 22 pages, 5 figures. Published version. Companion paper to arXiv:2303.00955, where the framework is introduced and some results on virtual resource distillation of quantum states are presented. Some of the content of this submission was originally a part of arXiv:2303.00955v1

Explainable AI (XAI) has demonstrated the potential to help reinforcement learning (RL) practitioners to understand how RL models work. However, XAI for users who do not have RL expertise (non-RL experts), has not been studied sufficiently. This results in a difficulty for the non-RL experts to participate in the fundamental discussion of how RL models should be designed for an incoming society where humans and AI coexist. Solving such a problem would enable RL experts to communicate with the non-RL experts in producing machine learning solutions that better fit our society. We argue that abstracted trajectories, that depicts transitions between the major states of the RL model, will be useful for non-RL experts to build a mental model of the agents. Our early results suggest that by leveraging a visualization of the abstracted trajectories, users without RL expertise are able to infer the behavior patterns of RL., Comment: 14pages, 11figures

Photonic integrated circuits are emerging as a promising platform for accelerating matrix multiplications in deep learning, leveraging the inherent parallel nature of light. Although various schemes have been proposed and demonstrated to realize such photonic matrix accelerators, the in-situ training of artificial neural networks using photonic accelerators remains challenging due to the difficulty of direct on-chip backpropagation on a photonic chip. In this work, we propose a silicon microring resonator (MRR) optical crossbar array with a symmetric structure that allows for simple on-chip backpropagation, potentially enabling the acceleration of both the inference and training phases of deep learning. We demonstrate a $4 \times 4$ circuit on a Si-on-insulator (SOI) platform and use it to perform inference tasks of a simple neural network for classifying Iris flowers, achieving a classification accuracy of 93.3%. Subsequently, we train the neural network using simulated on-chip backpropagation and achieve an accuracy of 91.1% in the same inference task after training. Furthermore, we simulate a convolutional neural network (CNN) for handwritten digit recognition, using a $9 \times 9$ MRR crossbar array to perform the convolution operations. This work contributes to the realization of compact and energy-efficient photonic accelerators for deep learning.

The increasing demand for intelligent systems capable of interpreting and reasoning about visual content requires the development of large Vision-and-Language Models (VLMs) that are not only accurate but also have explicit reasoning capabilities. This paper presents a novel approach to develop a VLM with the ability to conduct explicit reasoning based on visual content and textual instructions. We introduce a system that can ask a question to acquire necessary knowledge, thereby enhancing the robustness and explicability of the reasoning process. To this end, we developed a novel dataset generated by a Large Language Model (LLM), designed to promote chain-of-thought reasoning combined with a question-asking mechanism. The dataset covers a range of tasks, from common ones like caption generation to specialized VQA tasks that require expert knowledge. Furthermore, using the dataset we created, we fine-tuned an existing VLM. This training enabled the models to generate questions and perform iterative reasoning during inference. The results demonstrated a stride toward a more robust, accurate, and interpretable VLM, capable of reasoning explicitly and seeking information proactively when confronted with ambiguous visual input.