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Among the known isotope effects in chemistry, electron spin conversion by nuclear spin is a potent mechanism governing the reactions of radical pairs. For the electron transfer between nonradical(s), this spin conversion does not work, and other isotope effects have been presumed to have negligible contributions. However, we have observed a nuclear-state-dependence anomaly in ion charge state distributions in the thermalization of energetic atomic ions in helium gas, the process between nonradical(s). It could be understood to arise from the change in the stability of the intermediate quasi-molecule state of the electron transfer caused by the difference in nuclear states. This should prompt a reconsideration of the influence of atomic nuclei on interatomic and intermolecular interactions., Comment: 12 pages of the main part and 4 pages of supplementary, 5 figures and 3 tables

$^{187}$Ta ($Z=73$, $N=114$) is located in the neutron-rich $A \approx 190$ region where a prolate-to-oblate shape transition via triaxial softness is predicted to take place. A preceding work on the $K^{\pi} = (25/2^-)$ isomer and a rotational band to which the isomer decays carried out by the same collaboration revealed that axial symmetry is slightly violated in this nucleus. This paper focuses on a higher-lying isomer, which was previously identified at 2933(14) keV by mass measurements with the Experimental Storage Ring at GSI. The isomer of interest has been populated by a multi-nucleon transfer reaction with a $^{136}$Xe primary beam incident on a natural tungsten target, using the KEK Isotope Separation System at RIKEN. New experimental findings obtained in the present paper include the internal and external $\beta$-decay branches from the high-spin isomer and a revised half-life of 136(24) s. The evaluated hindrances for $K$-forbidden transitions put constraints on the spin-parity assignment, which can be interpreted as being ascribed to a prolate shape with a five-quasiparticle configuration by model calculations., Comment: 9 pages, 5 figures

Dissipative Kerr soliton microcombs have inspired various intriguing applications such as spectroscopy, ranging, telecommunication, and high purity microwave generation. Mechanically actuated soliton microcombs provide enhanced controllability and flexibility for Kerr solitons, thus enabling technological progress to be made on such practical applications. Here, we present architectures for coherent dual-comb techniques and ultralow-noise microwave generation by exploiting the mechanical actuation of ultrahigh-Q crystalline microresonators. By unifying a pump laser, we demonstrate highly coherent dual-soliton combs using distinct resonators with slightly different repetition rates. We also report significant phase noise reduction achieved by directly generating Kerr solitons from a sub-Hz linewidth ultrastable laser. This study paves the way for further advancements in a wide variety of applications based on Kerr soliton microcombs.

We report on the development of a low-energy positron diffraction (LEPD) experimental station for surface structure analysis using a linac-based slow-positron beam. LEPD, the positron counterpart of low-energy electron diffraction (LEED), offers higher accuracy in surface structure determination. The station enables acquisition of LEPD I-V curves within a few hours, allowing measurements before surface degradation occurs. It consists of two ultra-high vacuum (UHV) chambers: one for sample preparation and the other for LEPD observations. The preparation chamber includes an Ar+ sputtering system, a triple-pocket electron beam evaporator, three gas introduction systems, additional user-configurable ports, and a LEED/Auger electron spectroscopy (AES) system. Sample manipulators enable rapid cooling, precise positioning, and orientation adjustments. In the preparation chamber, the manipulator also supports direct current heating up to 1200 {\deg}C. The sample holder is compatible with the LEPD station at SPF-A4 and the ARPES station at PF BL-13B, both located at the Tsukuba campus of the Institute of Materials Structure Science (IMSS), KEK. Design concepts and experimental demonstrations are presented., Comment: 23 pages, 7 figures

Simulating open quantum systems is an essential technique for understanding complex physical phenomena and advancing quantum technologies. Some quantum algorithms for simulating Lindblad dynamics achieve logarithmically short circuit depth in terms of accuracy $\varepsilon$ by coherently encoding all possible jump processes with a large ancilla consumption. Minimizing the space complexity while achieving such a logarithmic depth remains an important challenge. In this work, we present a quantum algorithm for simulating general Lindblad dynamics with multiple jump operators aimed at an observable estimation, that achieves both a logarithmically short circuit depth and a minimum ancilla size. Toward simulating an exponentially accurate Taylor expansion of the Lindblad propagator to ensure the circuit depth of $\mathcal{O} (\log(1/\varepsilon))$, we develop a novel random circuit compilation method that leverages dissipative processes with only a single jump operator; importantly, the proposed method requires the minimal-size, $4 + \lceil \log M \rceil$, ancilla qubits where each single jump operator has at most $M$ Pauli strings. This work represents a significant step towards making open quantum system simulations more feasible on early fault-tolerant quantum computing devices.

DarkSide-20k is a novel liquid argon dark matter detector currently under construction at the Laboratori Nazionali del Gran Sasso (LNGS) of the Istituto Nazionale di Fisica Nucleare (INFN) that will push the sensitivity for Weakly Interacting Massive Particle (WIMP) detection into the neutrino fog. The core of the apparatus is a dual-phase Time Projection Chamber (TPC), filled with \SI{50} {tonnes} of low radioactivity underground argon (UAr) acting as the WIMP target. NUV-HD-Cryo Silicon Photomultipliers (SiPM)s designed by Fondazione Bruno Kessler (FBK) (Povo, Trento, Italy) were selected as the photon sensors covering two $10.5~\text{m}^2$ Optical Planes, one at each end of the TPC, and a total of $5~\text{m}^2$ photosensitive surface for the liquid argon veto detectors. This paper describes the Quality Assurance and Quality Control (QA/QC) plan and procedures accompanying the production of FBK~NUV-HD-Cryo SiPM wafers manufactured by LFoundry s.r.l. (Avezzano, AQ, Italy). SiPM characteristics are measured at 77~K at the wafer level with a custom-designed probe station. As of May~2024, 603 of the 1400 production wafers (43\% of the total) for DarkSide-20k were tested, including wafers from all 57 production Lots. The wafer yield is $93.6\pm2.5$\%, which exceeds the 80\% specification defined in the original DarkSide-20k production plan.

Recent studies showed that topologically trivial insulators may have fractionally quantized corner charges due to the topological invariant called a filling anomaly. Such crystal shapes in three dimensions are restricted to vertex-transitive polyhedra, which are classified into spherical and cylindrical families. The previous works derived formulas of the fractional corner charge for the spherical family, which corresponds to the tetrahedral and cubic space groups (SGs). In this study, we derive all the corner charge formulas for the cylindrical family, which corresponds to the orthorhombic, tetragonal, hexagonal, and trigonal crystal shapes. We show that all the real-space formulas of the filling anomaly for the cylindrical SGs are universally determined by the total charges at the Wyckoff position (WP) 1a. Moreover, we derive the k-space formulas of the corner charge for the cylindrical cases with time-reversal symmetry (TRS). From our results, we also show that CsLi$_{2}$Cl_{3}, KN_{3}, and Li_{3}N are candidate materials with a quantized corner charge by using the ab initio calculations. Together with our previous work, we exhaust corner charge formulas for all the SGs and crystal shapes having quantized corner charges., Comment: 17 pages, 8 figures

We consider D-branes in the Dabholkar-Park (DP) background, a $9$d orientifold theory obtained by gauging symmetry in the type~IIB string theory compactified on a circle. Using anomalies in the world-sheet theory, we provide physical insights into the classification of stable D-branes by relative KR-theory. The nature, such as stability, of D-branes wrapping along the compactified circle can be extracted from information about $1$d Majorana fermions on the boundary of the world-sheet. These Majorana fermions need to be introduced to consistently perform the GSO projection and the orientifold. We also construct D-brane states in the DP background. The spectrum of D-branes characterized by the relative KR-theory is correctly reproduced from the D-brane states., Comment: 23 pages

Within the context of the ALICE ITS3 collaboration, a set of MAPS small-scale test structures were developed using the 65 nm TPSCo CMOS imaging process with the upgrade of the ALICE inner tracking system as its primary focus. One such sensor, the Circuit Exploratoire 65 nm (CE-65), and its evolution the CE-65v2, were developed to explore charge collection properties for varying configurations including collection layer process (standard, blanket, modified with gap), pixel pitch (15, 18, \SI{22.5}{\micro\meter}), and pixel geometry (square vs hexagonal/staggered). In this work the characterisation of the CE-65v2 chip, based on $^{55}$Fe lab measurements and test beams at CERN SPS, is presented. Matrix gain uniformity up to the $\mathcal{O}$(5\%) level was demonstrated for all considered chip configurations. The CE-65v2 chip achieves a spatial resolution of under \SI{2}{\micro\meter} during beam tests. Process modifications allowing for faster charge collection and less charge sharing result in decreased spatial resolution, but a considerably wider range of operation, with both the \SI{15}{\micro\meter} and \SI{22.5}{\micro\meter} chips achieving over 99\% efficiency up to a $\sim$180 e$^{-}$ seed threshold. The results serve to validate the 65 nm TPSCo CMOS process, as well as to motivate design choices in future particle detection experiments., Comment: 7 pages, 12 figures; Proceedings for iWoRiD 2024 (Lisbon)

We investigated the influence of the Eddington ratio on sub-parsec-scale outflows in active galactic nuclei (AGNs) with supermassive black holes (SMBHs) masses of $10^7$ M$_{\odot}$ using two-dimensional radiation hydrodynamics simulations. When the range of Eddington ratio, $\gamma_{\rm Edd} > 10^{-3}$, the radiation force exceeds the gas pressure, leading to stronger outflows and larger dust sublimation radius. Although the sub-parsec-scale outflows is a time-dependence phenomena, our simulations demonstrated that the radial distributions can be well explained by the steady solutions of the spherically symmetric stellar winds. The dynamic structure of sub-parsec-scale outflows is influenced by the dust sublimation radius and the critical radii determined by the dynamical equilibrium condition. Although significantly affecting the outflow velocity, the Eddington ratio exerts minimal effects on temperature and number density distribution. Furthermore, our analytical solutions highlight the importance of the dust sublimation scale as a crucial determinant of terminal velocity and column density in dusty outflows. Through comparisons of our numerical model with the obscuring fraction observed in nearby AGNs, we revealed insights into the Eddington ratio dependence and the tendency towards the large obscuring fraction of the dusty and dust-free gases. The analytical solutions are expected to facilitate an understanding of the dynamical structure and radiation structures along the line of sight and their viewing angles from observations of ionized outflows., Comment: 22 pages, 10 figures, accepted for publication in ApJ

If a scalar field couples to the Ricci scalar with a large non-minimal coupling, the Standard Model coupling parameters can differ above and below an intermediate field range of the scalar due to the non-renormalizability. In this paper, we study, for the first time, the threshold effects on a gauge coupling in both Metric and Palatini formulations of gravity. We find that the gauge coupling naturally jumps around this intermediate scale since counter terms for the renormalization behave so. If the gauge coupling becomes strong with a large scalar field value due to this effect, there can be an enhanced small instanton contribution, the dilute gas approximation of which is justified because the gauge sector decouples when the scalar wave mode is very short. Using these findings, we discuss the QCD axion quality problem, the heavy QCD axion, the QCD axion abundance, and the suppression of isocurvature perturbations. We show that axion physics may differ substantially from na\"{i}ve expectations when we introduce a large non-minimal coupling for any scalar field., Comment: 25 pages, 4 figures, v2: version submitted to journal

Fashion aesthetic evaluation is the task of estimating how well the outfits worn by individuals in images suit them. In this work, we examine the zero-shot performance of GPT-4V on this task for the first time. We show that its predictions align fairly well with human judgments on our datasets, and also find that it struggles with ranking outfits in similar colors. The code is available at https://github.com/st-tech/gpt4v-fashion-aesthetic-evaluation.

The Xenon-Argon Technology (X-ArT) collaboration presents a study on the dynamics of pure and xenon-doped liquid argon (LAr) scintillation. Using two types of silicon photomultipliers sensitive to different wavelength ranges, we identify a long-lived extreme ultraviolet (EUV) radiative component that enhances the light yield. This component is present in both pure and xenon-doped LAr, becoming more pronounced at higher xenon concentrations, where it complements the traditional collisional energy transfer process. To explain this mechanism, we develop a comprehensive model of the Xe-doped LAr scintillation process that integrates both collisional and radiative contributions. Additionally, we investigate how xenon doping affects LAr scintillation light yield and pulse shape discrimination. Finally, we hypothesize that the EUV component may explain the emission of spurious electrons, a known challenge in light dark matter searches using noble liquids. By characterizing the scintillation dynamics in Xe-doped LAr, identifying the long-lived EUV component, and exploring the potential origin of spurious electrons, this work lays the groundwork for optimizing detector performance and advancing the design and sensitivity of future noble liquids particle detectors., Comment: 20 pages, 11 figures

We propose a method to numerically determine the location of a critical point in general systems using the finite-size scaling of Lee-Yang zeros. This method makes use of the fact that the ratios of Lee-Yang zeros on various spatial volumes intersect at the critical point. While the method is similar to the Binder-cumulant analysis, it is advantageous in suppressing the finite-volume effects arising from the mixing of variables in general systems. We show that the method works successfully for numerically locating the CP in the three-dimensional three-state Potts model with a nonzero external field., Comment: 6 pages, 3 figures, Minor changes

Recent research on explainable recommendation generally frames the task as a standard text generation problem, and evaluates models simply based on the textual similarity between the predicted and ground-truth explanations. However, this approach fails to consider one crucial aspect of the systems: whether their outputs accurately reflect the users' (post-purchase) sentiments, i.e., whether and why they would like and/or dislike the recommended items. To shed light on this issue, we introduce new datasets and evaluation methods that focus on the users' sentiments. Specifically, we construct the datasets by explicitly extracting users' positive and negative opinions from their post-purchase reviews using an LLM, and propose to evaluate systems based on whether the generated explanations 1) align well with the users' sentiments, and 2) accurately identify both positive and negative opinions of users on the target items. We benchmark several recent models on our datasets and demonstrate that achieving strong performance on existing metrics does not ensure that the generated explanations align well with the users' sentiments. Lastly, we find that existing models can provide more sentiment-aware explanations when the users' (predicted) ratings for the target items are directly fed into the models as input. We will release our code and datasets upon acceptance.

We define twelve equivalence relations on $\mathbb{Z}^{m}$ ($m\geq2$) by means of Fox's $\mathbb{Z}$-colorings of (classical, virtual, or pure) $m$-braids and $(m,m)$-tangles. One of them corresponds to the Hurwitz action of the $m$-braid group on $\mathbb{Z}^m$. The aim of this paper is to characterize the equivalence relations completely. As an application, we construct an invariant $d(G)$ of a spatial Euler graph $G$, and give the calculation for some family of spatial $\theta_4$-graphs., Comment: 46 pages

We present X-ray observations of the upper atmospheric density disturbance caused by the explosive eruption of the Hunga Tonga-Hunga Ha'apai (HTHH) volcano on 15 January 2022. From 14 January to 16 January, the Chinese X-ray astronomy satellite, Insight-HXMT, was observing the supernova remnant Cassiopeia A. The X-ray data obtained during Earth's atmospheric occultations allowed us to measure neutral densities in the altitude range of ~90-150 km. The density profiles above 110 km altitude obtained before the major eruption are in reasonable agreement with expectations by both GAIA and NRLMSIS 2.0 models. In contrast, after the HTHH eruption, a severe density depletion was found up to ~1,000 km away from the epicenter, and a relatively weak depletion extending up to ~7,000 km for over 8 hr after the eruption. In addition, density profiles showed wavy structures with a typical length scale of either ~20 km (vertical) or ~1,000 km (horizontal). This may be caused by Lamb waves or gravity waves triggered by the volcanic eruption., Comment: 14 pages, 4 figures, accepted for publication in Geophysical Research Letters

The isotopic compositions of samples returned from Cb-type asteroid Ryugu and Ivuna-type (CI) chondrites are distinct from other carbonaceous chondrites, which has led to the suggestion that Ryugu and CI chondrites formed in a different region of the accretion disk, possibly around the orbits of Uranus and Neptune. We show that, like for Fe, Ryugu and CI chondrites also have indistinguishable Ni isotope anomalies, which differ from those of other carbonaceous chondrites. We propose that this unique Fe and Ni isotopic composition reflects different accretion efficiencies of small FeNi metal grains among the carbonaceous chondrite parent bodies. The CI chondrites incorporated these grains more efficiently, possibly because they formed at the end of the disk's lifetime, when planetesimal formation was also triggered by photoevaporation of the disk. Isotopic variations among carbonaceous chondrites may thus reflect fractionation of distinct dust components from a common reservoir, implying CI chondrites and Ryugu may have formed in the same region of the accretion disk as other carbonaceous chondrites., Comment: Published open access in Science Advances

JASMINE is a Japanese planned space mission that aims to reveal the formation history of our Galaxy and discover habitable exoEarths. For these objectives, the JASMINE satellite performs high-precision astrometric observations of the Galactic bulge and high-precision transit monitoring of M-dwarfs in the near-infrared (1.0-1.6 microns in wavelength). For feasibility studies, we develop an image simulation software named JASMINE-imagesim, which produces realistic observation images. This software takes into account various factors such as the optical point spread function (PSF), telescope jitter caused by the satellite's attitude control error (ACE), detector flat patterns, exposure timing differences between detector pixels, and various noise factors. As an example, we report a simulation for the feasibility study of astrometric observations using JASMINE-imagesim. The simulation confirms that the required position measurement accuracy of 4 mas for a single exposure of 12.5-mag objects is achievable if the telescope pointing jitter uniformly dilutes the PSF across all stars in the field of view. On the other hand, the simulation also demonstrates that the combination of realistic pointing jitter and exposure timing differences in the detector can significantly degrade accuracy and prevent achieving the requirement. This means that certain countermeasures against this issue must be developed. This result implies that this kind of simulation is important for mission planning and advanced developments to realize more realistic simulations help us to identify critical issues and also devise effective solutions., Comment: 13 pages, 7 figures, 1 table

We study the energetics of bursting activity in a magnetar under the `Dzhanibekov effect,' described by the classical mechanics of rigid bodies. The magnetar's rotation axis suddenly flips due to this effect, resulting in a sudden rise of the Euler force. The outer layer of magnetar, called the crust, can plastically flow and eventually break due to the Euler force. Then, the degenerate electrons burst open from the braking region like a balloon burst. We find that the pair plasma formation can be ignited inside the crust, and its radiation can be similar to the observed bursts from soft gamma-ray repeaters. At the beginning of this bursting phenomenon, the self-discharge effect of the electron streaming may induce a strong resistive electric field, accelerating the ions. We also find that the maximum energy of the accelerated ions possibly reaches $\sim$ZeV within a timescale of $\sim1$~ps. If $\gtrsim2$~\% of magnetars in nearby galaxies are undergoing this scenario, the observed cosmic-ray flux at $>100$~EeV can be explained., Comment: submitted to PTEP (13 pages of the main text with a single column, 4 figures, 22 pages in total)

A search for proton decay into $e^+/\mu^+$ and a $\eta$ meson has been performed using data from a 0.373 Mton$\cdot$year exposure (6050.3 live days) of Super-Kamiokande. Compared to previous searches this work introduces an improved model of the intranuclear $\eta$ interaction cross section, resulting in a factor of two reduction in uncertainties from this source and $\sim$10\% increase in signal efficiency. No significant data excess was found above the expected number of atmospheric neutrino background events resulting in no indication of proton decay into either mode. Lower limits on the proton partial lifetime of $1.4\times\mathrm{10^{34}~years}$ for $p\rightarrow e^+\eta$ and $7.3\times\mathrm{10^{33}~years}$ for $p\rightarrow \mu^+\eta$ at the 90$\%$ C.L. were set. These limits are around 1.5 times longer than our previous study and are the most stringent to date.

In this work, we address the challenge of developing automatic evaluation metrics for image captioning, with a particular focus on robustness against hallucinations. Existing metrics are often inadequate for handling hallucinations, primarily due to their limited ability to compare candidate captions with multifaceted reference captions. To address this shortcoming, we propose DENEB, a novel supervised automatic evaluation metric specifically robust against hallucinations. DENEB incorporates the Sim-Vec Transformer, a mechanism that processes multiple references simultaneously, thereby efficiently capturing the similarity between an image, a candidate caption, and reference captions. To train DENEB, we construct the diverse and balanced Nebula dataset comprising 32,978 images, paired with human judgments provided by 805 annotators. We demonstrated that DENEB achieves state-of-the-art performance among existing LLM-free metrics on the FOIL, Composite, Flickr8K-Expert, Flickr8K-CF, Nebula, and PASCAL-50S datasets, validating its effectiveness and robustness against hallucinations., Comment: ACCV 2024

In variational algorithms, quantum circuits are conventionally parametrized with respect to single-qubit gates. In this study, we parameterize a generalized controlled gate and propose an algorithm to estimate the optimal parameters for locally minimizing the cost value, where we extend the free quaternion selection method, an optimization method for a single-qubit gate. To benchmark the performance, we apply the proposed method to various optimization problems, including the Variational Quantum Eigensolver (VQE) for Ising and molecular Hamiltonians, Variational Quantum Algorithms (VQA) for fidelity maximization, and unitary compilation of time evolution operators. In these applications, the proposed method shows efficient optimization and greater expressibility with shallower circuits than other methods. Furthermore, this method is also capable of generalizing and fully optimizing particle-number-conserving gates, which are in demand in chemical systems applications. Taking advantage of this property, we have actually approximated time evolution operators of molecular Hamiltonian and simulated the dynamics with shallower circuits in comparison to the standard implementation by Trotter decomposition., Comment: 21 pages, 15 figures

In this work, we propose a fashion item recommendation model that incorporates hyperbolic geometry into user and item representations. Using hyperbolic space, our model aims to capture implicit hierarchies among items based on their visual data and users' purchase history. During training, we apply a multi-task learning framework that considers both hyperbolic and Euclidean distances in the loss function. Our experiments on three data sets show that our model performs better than previous models trained in Euclidean space only, confirming the effectiveness of our model. Our ablation studies show that multi-task learning plays a key role, and removing the Euclidean loss substantially deteriorates the model performance., Comment: This work was presented at the CVFAD Workshop at CVPR 2024

Despite numerous studies on cerebral arterial blood flow, there has not yet been a comprehensive description of hemodynamics in patients undergoing debranching thoracic endovascular aortic repair (dTEVAR), a promising surgical option for aortic arch aneurysms. A phase delay of the flow rate in the left vertebral artery (LVA) in patients after dTEVAR compared to those before was experimentally observed, while the phase in the right vertebral artery (RVA) remained almost the same before and after surgery. Since this surgical intervention included stent graft implantation and extra-anatomical bypass, it was expected that the intracranial hemodynamic changes due to dTEVAR were coupled with fluid flow and pulse waves in cerebral arteries. To clarify this issue, A one-dimensional model (1D) was used to numerically investigate the relative contribution (i.e., local vessel stiffness and flow path changes) of the VA flow rate to the phase difference. The numerical results demonstrated a phase delay of flow rate in the LVA but not the RVA in postoperative patients undergoing dTEVAR relative to preoperative patients. The results further showed that the primary factor affecting the phase delay of the flow rate in the LVA after surgery compared to that before was the bypass, i.e., alteration of flow path, rather than stent grafting, i.e., the change in local vessel stiffness. The numerical results provide insights into hemodynamics in postoperative patients undergoing dTEVAR, as well as knowledge about therapeutic decisions.

Objective: This paper introduces a novel PET imaging methodology called 3-dimensional positron imaging (3D{\pi}), which integrates total-body (TB) coverage, time-of-flight (TOF) technology, ultra-low dose imaging capabilities, and ultra-fast readout electronics inspired by emerging technology from the DarkSide collaboration. Approach: The study evaluates the performance of 3D{\pi} using Monte Carlo simulations based on NEMA NU 2-2018 protocols. The methodology employs a homogenous, monolithic scintillator composed of liquid argon (LAr) doped with xenon (Xe) with silicon photomultipliers (SiPM) operating at cryogenic temperatures. Main results: Significant enhancements in system performance are observed, with the 3D{\pi} system achieving a noise equivalent count rate (NECR) of 3.2 Mcps which is approximately two times higher than uEXPLORER's peak NECR (1.5 Mcps) at 17.3 (kBq/mL). Spatial resolution measurements show an average FWHM of 2.7 mm across both axial positions. The system exhibits superior sensitivity, with values reaching 373 kcps/MBq with a line source at the center of the field of view. Additionally, 3D{\pi} achieves a TOF resolution of 151 ps at 5.3 kBq/mL, highlighting its potential to produce high-quality images with reduced noise levels. Significance: The study underscores the potential of 3D{\pi} in improving PET imaging performance, offering the potential for shorter scan times and reduced radiation exposure for patients. The Xe-doped LAr offers advantages such as fast scintillation, enhanced light yield, and cost-effectiveness. Future research will focus on optimizing system geometry and further refining reconstruction algorithms to exploit the strengths of 3D{\pi} for clinical applications., Comment: 8 pages, 8 figures, 6 tables

DarkSide-20k (DS-20k) is a dark matter detection experiment under construction at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. It utilises ~100 t of low radioactivity argon from an underground source (UAr) in its inner detector, with half serving as target in a dual-phase time projection chamber (TPC). The UAr cryogenics system must maintain stable thermodynamic conditions throughout the experiment's lifetime of >10 years. Continuous removal of impurities and radon from the UAr is essential for maximising signal yield and mitigating background. We are developing an efficient and powerful cryogenics system with a gas purification loop with a target circulation rate of 1000 slpm. Central to its design is a condenser operated with liquid nitrogen which is paired with a gas heat exchanger cascade, delivering a combined cooling power of >8 kW. Here we present the design choices in view of the DS-20k requirements, in particular the condenser's working principle and the cooling control, and we show test results obtained with a dedicated benchmarking platform at CERN and LNGS. We find that the thermal efficiency of the recirculation loop, defined in terms of nitrogen consumption per argon flow rate, is 95 % and the pressure in the test cryostat can be maintained within $\pm$(0.1-0.2) mbar. We further detail a 5-day cool-down procedure of the test cryostat, maintaining a cooling rate typically within -2 K/h, as required for the DS-20k inner detector. Additionally, we assess the circuit's flow resistance, and the heat transfer capabilities of two heat exchanger geometries for argon phase change, used to provide gas for recirculation. We conclude by discussing how our findings influence the finalisation of the system design, including necessary modifications to meet requirements and ongoing testing activities., Comment: 45 pages, 24 figures

We study the problem \emph{Gathering} for $n$ autonomous mobile robots in synchronous settings with a persistent memory called \emph{light}. It is well known that Gathering is impossible in the basic model ($OBLOT$) where robots have no lights, even if the system is semi-synchronous (called SSYNCH). Gathering becomes possible, however, if each robot has a light of some type that can be set to a constant number of colors. In the $FCOM$ model, the robots can only see the lights of other robots. In the $FSTA$ model, each robot can only observe its own light. In the $LUMI$ model, all robots can see all lights. This paper focuses on $FSTA$ robots with 2-colored lights in synchronous settings. We show that 2-color $FSTA$ and $FCOM$ robots cannot solve Gathering in SSYNCH without additional conditions, even with rigid movement and agreement of chirality and the minimum moving distance. We also improve the condition of the previous gathering algorithm for $FSTA$ robots with 2-color working in SSYNCH., Comment: 16 pages, 3 figures. arXiv admin note: text overlap with arXiv:1811.12068

We included the intrinsic line profiles of the strongest fluorescent lines in the X-ray radiative transfer code SKIRT to model the cold-gas structure and kinematics based on high-resolution line observations from XRISM/Resolve and Athena/X-IFU. The intrinsic line profiles of the Ka and Kb lines of Cr, Mn, Fe, Co, Ni, and Cu were implemented based on a multi-Lorentzian parameterisation and line energies are sampled from these Lorentzian components during the radiative transfer routine. In the optically thin regime, the SKIRT results match the intrinsic line profiles as measured in the laboratory. With a more complex 3D model that also includes kinematics, we find that the intrinsic line profiles are broadened and shifted to an extent that will be detectable with XRISM/Resolve; this model also demonstrates the importance of the intrinsic line shapes for constraining kinematics. We find that observed line profiles directly trace the cold-gas kinematics, without any additional radiative transfer effects. With the advent of the first XRISM/Resolve data, this update to the X-ray radiative transfer framework of SKIRT is timely and provides a unique tool for constraining the velocity structure of cold gas from X-ray microcalorimeter spectra., Comment: 6 pages, 3 figures, accepted for publication in Astronomy & Astrophysics

Self-supervised learning for image denoising problems in the presence of denaturation for noisy data is a crucial approach in machine learning. However, theoretical understanding of the performance of the approach that uses denatured data is lacking. To provide better understanding of the approach, in this paper, we analyze a self-supervised denoising algorithm that uses denatured data in depth through theoretical analysis and numerical experiments. Through the theoretical analysis, we discuss that the algorithm finds desired solutions to the optimization problem with the population risk, while the guarantee for the empirical risk depends on the hardness of the denoising task in terms of denaturation levels. We also conduct several experiments to investigate the performance of an extended algorithm in practice. The results indicate that the algorithm training with denatured images works, and the empirical performance aligns with the theoretical results. These results suggest several insights for further improvement of self-supervised image denoising that uses denatured data in future directions.

Acquiring plausible pathways on high-dimensional structural distributions is beneficial in several domains. For example, in the drug discovery field, a protein conformational pathway, i.e. a highly probable sequence of protein structural changes, is useful to analyze interactions between the protein and the ligands, helping to create new drugs. Recently, a state-of-the-art method in drug discovery was presented, which efficiently computes protein pathways using latent variables obtained from an isometric auto-encoding of the space of 3D density maps associated to protein conformations. However, our preliminary experiments show that there is room to significantly reduce the computing time. In this study, we use the Mapper algorithm, which is a Topological Data Analysis method, and present a novel variant to extract plausible conformational pathways from the isometric latent space with comparatively short running time. The extracted pathways are visualized as paths on the resulting Mapper graph. The methodological novelties are described as follows: firstly, the filter function of the Mapper algorithm is optimized so as to extract the pathways via minimization of an energy loss defined on the Mapper graph itself, while filter functions taken in the classical Mapper algorithm are fixed beforehand. The optimization is with respect to parameters of a deep neural network in the filter. Secondly, the clustering method, which defines the vertices and edges of the Mapper graph, of our algorithm, is designed by incorporating domain prior knowledge to assist the extraction. In our numerical experiments, based on an isometric latent space built on the common 50S-ribosomal dataset, the resulting Mapper graph successfully includes all the well-recognized plausible pathways. Moreover, our running time is much shorter than the above state-of-the-art counterpart.

Human--robot co-carrying tasks demonstrate their potential in both industrial and everyday applications by leveraging the strengths of both parties. Effective control of robots in these tasks requires minimizing position and velocity errors to complete the shared tasks while also managing the energy level within the closed-loop systems to prevent potential dangers such as instability and unintended force exertion. However, this collaboration scenario poses numerous challenges due to varied human intentions in adapting to workspace characteristics, leading to human--robot conflicts and safety incidents. In this paper, we develop a robot controller that enables the robot partner to re-plan its path leveraging conflict information, follow co-carrying motions accurately, ensure passivity, and regular the energy of the closed-loop system. A cooperation control framework for human--robot co-carrying tasks is constructed by utilizing admittance control and time-varying Passive Velocity Field Control with a fractional exponent energy compensation control term. By measuring the interaction force, the desired trajectory of co-carrying tasks for the robot partner is first generated using admittance control. Thereafter, the new Passive Velocity Field Control with the energy compensation feature is designed to track the desired time-varying trajectory and guarantee passivity. Furthermore, the proposed approach ensures that the system's kinetic energy converges to the desired level within a finite time interval, which is critical for time-critical applications. Numerical simulation demonstrates the efficiency of the proposed cooperation control method through four collaborative transportation scenarios., Comment: 14 pages, 9 figures. This is a preprint of an article submitted for consideration in IEEE Transactions on Robotics

There is a growing demand for simulators for the research and development of maritime autonomous surface ships (MASS) and the approval of autonomous navigation algorithms. Simulators are used for purposes such as evaluation and training and are taken on various configurations accordingly. The ship maneuvering mathematical model used in such a simulator is an important element that characterizes the simulator. In this paper, we discuss the dynamic model of the hull and its position in the simulator that will be required for MASSs in the future. It also discusses guidelines for selecting an appropriate model, which has not been discussed extensively in previous studies. Finally, we discuss the functional requirements that simulators should have., Comment: 21 pages, 3 figures, Submitted to Journal of Marine Science and Technology

Advancing defensive mechanisms against adversarial attacks in generative models is a critical research topic in machine learning. Our study focuses on a specific type of generative models - Variational Auto-Encoders (VAEs). Contrary to common beliefs and existing literature which suggest that noise injection towards training data can make models more robust, our preliminary experiments revealed that naive usage of noise augmentation technique did not substantially improve VAE robustness. In fact, it even degraded the quality of learned representations, making VAEs more susceptible to adversarial perturbations. This paper introduces a novel framework that enhances robustness by regularizing the latent space divergence between original and noise-augmented data. Through incorporating a paired probabilistic prior into the standard variational lower bound, our method significantly boosts defense against adversarial attacks. Our empirical evaluations demonstrate that this approach, termed Robust Augmented Variational Auto-ENcoder (RAVEN), yields superior performance in resisting adversarial inputs on widely-recognized benchmark datasets.

Digital human models of motion sickness have been actively developed, among which models based on subjective vertical conflict (SVC) theory are the most actively studied. These models facilitate the prediction of motion sickness in various scenarios such as riding in a car. Most SVC theory models predict the motion sickness incidence (MSI), which is defined as the percentage of people who would vomit with the given specific motion stimulus. However, no model has been developed to describe milder forms of discomfort or specific symptoms of motion sickness, even though predicting milder symptoms is important for applications in automobiles and daily use vehicles. Therefore, the purpose of this study was to build a computational model of symptom progression of vestibular motion sickness based on SVC theory. We focused on a model of vestibular motion sickness with six degrees-of-freedom (6DoF) head motions. The model was developed by updating the output part of the state-of-the-art SVC model, termed the 6DoF-SVC (IN1) model, from MSI to the MIsery SCale (MISC), which is a subjective rating scale for symptom progression. We conducted an experiment to measure the progression of motion sickness during a straight fore-aft motion. It was demonstrated that our proposed method, with the parameters of the output parts optimized by the experimental results, fits well with the observed MISC.

We have studied the gradient-flow equations in information geometry from a point-particle perspective. Based on the motion of a null (or light-like) particle in a curved space, we have rederived the Hamiltonians which describe the gradient-flows in information geometry., Comment: 14 pages, 1 figure, accepted to EPJB

In quantum mechanics, measuring the expectation value of a general observable has an inherent statistical uncertainty that is quantified by variance or mean squared error of measurement outcome. While the uncertainty can be reduced by averaging several samples, the number of samples should be minimized when each sample is very costly. This is especially the case for fault-tolerant quantum computing that involves measurement of multiple observables of non-trivial states in large quantum systems that exceed the capabilities of classical computers. In this work, we provide an adaptive quantum algorithm for estimating the expectation values of $M$ general observables within root mean squared error $\varepsilon$ simultaneously, using $\mathcal{O}(\varepsilon^{-1}\sqrt{M}\log M)$ queries to a state preparation oracle of a target state. This remarkably achieves the scaling of Heisenberg limit $1/\varepsilon$, a fundamental bound on the estimation precision in terms of mean squared error, together with the sublinear scaling of the number of observables $M$. The proposed method is an adaptive version of the quantum gradient estimation algorithm and has a resource-efficient implementation due to its adaptiveness. Specifically, the space overhead in the proposed method is $\mathcal{O}(M)$ which is independent from the estimation precision $\varepsilon$ unlike non-iterative algorithms. In addition, our method can avoid the numerical instability problem for constructing quantum circuits in a large-scale task (e.g., $\varepsilon\ll 1$ in our case), which appears in the actual implementation of many algorithms relying on quantum signal processing techniques. Our method paves a new way to precisely understand and predict various physical properties in complicated quantum systems using quantum computers.

Deep learning has become a de facto method of choice for speech enhancement tasks with significant improvements in speech quality. However, real-time processing with reduced size and computations for low-power edge devices drastically degrades speech quality. Recently, transformer-based architectures have greatly reduced the memory requirements and provided ways to improve the model performance through local and global contexts. However, the transformer operations remain computationally heavy. In this work, we introduce WaveUNet squeeze-excitation Res2 (WSR)-based metric generative adversarial network (WSR-MGAN) architecture that can be efficiently implemented on low-power edge devices for noise suppression tasks while maintaining speech quality. We utilize multi-scale features using Res2Net blocks that can be related to spectral content used in speech-processing tasks. In the generator, we integrate squeeze-excitation blocks (SEB) with multi-scale features for maintaining local and global contexts along with gated recurrent units (GRUs). The proposed approach is optimized through a combined loss function calculated over raw waveform, multi-resolution magnitude spectrogram, and objective metrics using a metric discriminator. Experimental results in terms of various objective metrics on VoiceBank+DEMAND and DNS-2020 challenge datasets demonstrate that the proposed speech enhancement (SE) approach outperforms the baselines and achieves state-of-the-art (SOTA) performance in the time domain.

In quantum computation, amplitude estimation is a fundamental subroutine that is utilized in various quantum algorithms. A general important task of such estimation problems is to characterize the estimation lower bound, which is referred to as quantum Cram\'er-Rao bound (QCRB), and to construct an optimal estimator that achieves QCRB. This paper studies the amplitude estimation in the presence of depolarizing noise with unknown intensity. The main difficulty in this problem is that the optimal measurement depends on both the unknown quantum state and the amplitude we aim to estimate. To deal with these issues, we utilize the variational quantum circuits to approximate the (unknown) optimal measurement basis combined with the 2-step adaptive estimation strategy which was proposed in the quantum estimation theory.We numerically show that the proposed method can nearly attain the QCRB., Comment: 14 pages, 7 figures

Traffic predictions play a crucial role in intelligent transportation systems. The rapid development of IoT devices allows us to collect different kinds of data with high correlations to traffic predictions, fostering the development of efficient multi-modal traffic prediction models. Until now, there are few studies focusing on utilizing advantages of multi-modal data for traffic predictions. In this paper, we introduce a novel temporal attentive cross-modality transformer model for long-term traffic predictions, namely xMTrans, with capability of exploring the temporal correlations between the data of two modalities: one target modality (for prediction, e.g., traffic congestion) and one support modality (e.g., people flow). We conducted extensive experiments to evaluate our proposed model on traffic congestion and taxi demand predictions using real-world datasets. The results showed the superiority of xMTrans against recent state-of-the-art methods on long-term traffic predictions. In addition, we also conducted a comprehensive ablation study to further analyze the effectiveness of each module in xMTrans., Comment: Accepted at MDM 2024

We developed the X-ray, Gamma-ray and Relativistic Electron detector (XGRE) onboard the TARANIS satellite, to investigate high-energy phenomena associated with lightning discharges such as terrestrial gamma-ray flashes and terrestrial electron beams. XGRE consisted of three sensors. Each sensor has one layer of LaBr$_{3}$ crystals for X-ray/gamma-ray detections, and two layers of plastic scintillators for electron and charged-particle discrimination. Since 2018, the flight model of XGRE was developed, and validation and calibration tests, such as a thermal cycle test and a calibration test with the sensors onboard the satellite were performed before the launch of TARANIS on 17 November 2020. The energy range of the LaBr$_{3}$ crystals sensitive to X-rays and gamma rays was determined to be 0.04-11.6 MeV, 0.08-11.0 MeV, and 0.08-11.3 MeV for XGRE1, 2, and 3, respectively. The energy resolution at 0.662 MeV (full width at half maximum) was to be 20.5%, 25.9%, and 28.6%, respectively. Results from the calibration test were then used to validate a simulation model of XGRE and TARANIS. By performing Monte Carlo simulations with the verified model, we calculated effective areas of XGRE to X-rays, gamma rays, electrons, and detector responses to incident photons and electrons coming from various elevation and azimuth angles., Comment: 25 pages, 20 figures, 1 table, published in Journal of Astronomical Telescopes, Instruments, and Systems. Copyright 2024 Society of Photo-Optical Instrumentation Engineers (SPIE)