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This paper explores the problem of 3D human pose estimation from only low-level acoustic signals. The existing active acoustic sensing-based approach for 3D human pose estimation implicitly assumes that the target user is positioned along a line between loudspeakers and a microphone. Because reflection and diffraction of sound by the human body cause subtle acoustic signal changes compared to sound obstruction, the existing model degrades its accuracy significantly when subjects deviate from this line, limiting its practicality in real-world scenarios. To overcome this limitation, we propose a novel method composed of a position discriminator and reverberation-resistant model. The former predicts the standing positions of subjects and applies adversarial learning to extract subject position-invariant features. The latter utilizes acoustic signals before the estimation target time as references to enhance robustness against the variations in sound arrival times due to diffraction and reflection. We construct an acoustic pose estimation dataset that covers diverse human locations and demonstrate through experiments that our proposed method outperforms existing approaches., Comment: Accepted at BMVC2024

Diffusion mechanism design, which investigate how to incentivise agents to invite as many colleagues to a multi-agent decision making as possible, is a new research paradigm at the intersection between microeconomics and computer science. In this paper we extend traditional facility location games into the model of diffusion mechanism design. Our objective is to completely understand to what extent of anonymity/voter-relevance we can achieve, along with strategy-proofness and Pareto efficiency when voters strategically invite collegues. We define a series of anonymity properties applicable to the diffusion mechanism design model, as well as parameterized voter-relevance properties for guaranteeing reasonably-fair decision making. We obtained two impossibility theorems and two existence theorems, which partially answer the question we have raised in the beginning of the paper, Comment: To appear in Proceedings of WALCOM-25

Among various topological insulators, Sn-doped Bi$_{1.1}$Sb$_{0.9}$Te$_{2}$S stands out for its exceptional properties. It has a wide energy gap and typically exhibits a well-isolated Dirac point and a Fermi level positioned within the gap. The samples we present display metallic-like low-temperature resistivity attributed to surface states, pronounced quantum oscillations observable even at 40 K, and a Fermi level located approximately 100 meV above the Dirac point. In this work, we report an unusual effect: a strong temperature dependence of the quantum oscillation frequency, which decreases by around 10\% between 2 and 40 K. This reduction significantly exceeds the expected effects of the Sommerfeld and topological corrections for Dirac quasi-particles, which could account for only one-eighth of the observed change. We attribute this change to the temperature-induced renormalization of the bulk band gap size due to electron-phonon interactions, which in turn affect the position of the surface Dirac point within the gap. Furthermore, we propose that in this compound, surface quantum oscillations can serve as a precise tool for investigating the low-temperature evolution of the bulk band gap size., Comment: 7 pages, 3 figures

We performed shot analyses of X-ray and optical sub-second flares observed during the low/hard state of the 2018 outburst in MAXI J1820$+$070. Optical shots were less spread than X-ray shots. The amplitude of X-ray shots was the highest at the onset of the outburst, and they faded at the transition to the intermediate state. The timescale of shots was $\sim$0.2 s, and we detected the abrupt spectral hardening synchronized with this steep flaring event. The time evolution of optical shots was not similar to that of X-ray shots. These results suggest that accreting gas blobs triggered a series of magnetic reconnections at the hot inner accretion flow in the vicinity of the black hole, which enhanced X-ray emission and generated flaring events. The rapid X-ray spectral hardening would be caused by this kind of magnetic activity. Also, the synchrotron emission not only at the hot flow but also at the jet plasma would contribute to the optical rapid variability. We also found that the low/hard state exhibited six different phases in the hardness-intensity diagram and the correlation plot between the optical flux and the X-ray hardness. The amplitude and duration of X-ray shots varied in synchrony with these phases. This time variation may provide key information about the evolution of the hot flow, the low-temperature outer disk, and the jet-emitting plasma., Comment: 16 pages, 7 figures, accepted for publication in PASJ

The modern Hopfield network, proposed by Krotov and Hopfield, is a mathematical generalization of the Hopfield network, which is a basic model of associative memory that employs higher-order interactions. This study introduces an open quantum model for discrete modern Hopfield networks that generalizes the open quantum Hopfield network. Our model integrates dissipative quantum spin systems, governed by quantum master equations, with classical hopping terms and additional quantum effects through a transverse field. We analytically examined the behavior of the stable fixed points and numerically determined the phase diagram. The results demonstrated qualitatively distinct behaviors from the open quantum Hopfield network, showing that the ferromagnetic and limit cycle phases have additional stable fixed points., Comment: 8pages, 6figures

We further develop the BPS/CFT correspondence between quiver W-algebras/$qq$-characters and partition functions of gauge origami. We introduce $qq$-characters associated with multi-dimensional partitions with nontrivial boundary conditions which we call Donaldson--Thomas (DT) $qq$-characters. They are operator versions of the equivariant DT vertices of toric Calabi--Yau three and four-folds. Moreover, we revisit the construction of the D8 $qq$-characters with no boundary conditions and give a quantum algebraic derivation of the sign rules of the magnificent four partition function. We also show that under the proper sign rules, the D6 and D8 $qq$-characters with no boundary conditions all commute with each other and discuss its physical interpretation., Comment: 66+13 pages

We present the first numerical calculation of the virtual photon polarization and assess the feasibility of measuring the polarization via the anisotropic decay $\gamma^{*} \rightarrow \mu\mu$ using the LHC-ALICE detector. In presence of intense magnetic fields generated in high-energy non-central heavy-ion collisions that exceed the critical magnetic field intensity of quantum electrodynamics (QED), prompt virtual photons are predicted to decay anisotropically into lepton pairs, which we call virtual photon polarization. Using a relativistic resistive magnetohydrodynamics model, we computed the time evolution of the magnetic field and used these results to estimate the averaged polarization by calculating the vacuum polarization under the influence of the magnetic field at specific times. The estimated polarization deviates from zero with a statistical significance of $0.07\sigma$ with the data statistics collected from 2010 to 2011 and $0.15\sigma$ with the one from 2015 to 2018. It is understandable that the magnetic field could not be detected through polarization due to low statistical significance. With the data collecting the ongoing ALICE run from 2023 to 2026, the statistics dramatically increase by the upgraded LHC and the new data processing system. Thereby we expect that the statistical significance could reach $\sim 1.7\sigma$, resulting in a promising probe for detecting the intense magnetic fields., Comment: 7 pages, 4 figures

One-proton emission from the $^{102}$Sb nucleus is discussed, assuming an inert $^{100}$Sn core and the valence proton and neutron. There are experimentally measured bound states in the $^{100}$Sn-neutron system, whereas no particle-bound $^{100}$Sn-proton state has been observed. With time-dependent three-body calculations, the $1^+$ ground state of $^{102}$Sb is suggested as a possible proton emitter. This conclusion is reached by assuming a weakening effect on the proton-neutron ($pn$) interaction with respect to a bare deuteron. An analogous phenomenon is necessary to reproduce the empirical binding energies of $^{42}$Sc and $^{18}$F. Continuous shift from the unbound to bound regions by changing the $pn$-interaction strength is demonstrated. The lower limit of lifetime is evaluated as $\tau \gtrsim 4.4 \times 10^{-18}$ seconds in the no-$pn$-interaction limit. However, the actual lifetime is expected as longer with a finite $pn$ interaction. Observation of a resonant state in $^{102}$Sb and its decay would provide a benchmark of the $pn$-pairing correlation., Comment: 6 pages, 6 figures, 4 tables

Out-of-distribution (OOD) detection is a critical issue for the stable and reliable operation of systems using a deep neural network (DNN). Although many OOD detection methods have been proposed, it remains unclear how the differences between in-distribution (ID) and OOD samples are generated by each processing step inside DNNs. We experimentally clarify this issue by investigating the layer dependence of feature representations from multiple perspectives. We find that intrinsic low dimensionalization of DNNs is essential for understanding how OOD samples become more distinct from ID samples as features propagate to deeper layers. Based on these observations, we provide a simple picture that consistently explains various properties of OOD samples. Specifically, low-dimensional weights eliminate most information from OOD samples, resulting in misclassifications due to excessive attention to dataset bias. In addition, we demonstrate the utility of dimensionality by proposing a dimensionality-aware OOD detection method based on alignment of features and weights, which consistently achieves high performance for various datasets with lower computational cost., Comment: This preprint has not undergone peer review (when applicable) or any post-submission improvements or corrections. The Version of Record of this contribution is published in ECML PKDD 2024, and is available online at https://doi.org/10.1007/978-3-031-70341-6_9

The motion of two-dimensional incompressible and viscous fluids in doubly periodic domains is often used as a numerical model to investigate the dynamics and statistical properties of two-dimensional (2d) turbulence. In the study of 2d turbulence, it is important to describe interactions of coherent vortex structures of various sizes in turbulent flows, but identifying such vortex structures accurately from complex flow patterns is not easy. In this paper, we provide a classification theory for the topological structure of particle orbits generated by two-dimensional Hamiltonian flows on a flat torus $\mathbb{T}^2$, which is a mathematical model of 2d incompressible and viscous flows. Based on this theory, we show that the global orbit structure of every Hamiltonian flow is converted into a planar tree, called {\it a partially Cyclically-Ordered rooted Tree (COT)}, and its string expression (COT representation). Applying the conversion algorithm to snapshots of two-dimensional free-decaying turbulence and enstrophy cascade turbulence, we demonstrate that the topological structure of a complex flow pattern can be represented by a simple tree and a sequence of letters by the conversion algorithm, thereby extracting coherent vortex structures successfully from the viewpoint of topology.

We study a universal approximation property of ODENet and ResNet. The ODENet is a map from an initial value to the final value of an ODE system in a finite interval. It is considered a mathematical model of a ResNet-type deep learning system. We consider dynamical systems with vector fields given by a single composition of the activation function and an affine mapping, which is the most common choice of the ODENet or ResNet vector field in actual machine learning systems. We show that such an ODENet and ResNet with a restricted vector field can uniformly approximate ODENet with a general vector field., Comment: 14 pages

Acceleration of positive muons from thermal energy to $100~$keV has been demonstrated. Thermal muons were generated by resonant multi-photon ionization of muonium atoms emitted from a sheet of laser-ablated aerogel. The thermal muons were first electrostatically accelerated to $5.7~$keV, followed by further acceleration to 100 keV using a radio-frequency quadrupole. The transverse normalized emittance of the accelerated muons in the horizontal and vertical planes were $0.85 \pm 0.25 ~\rm{(stat.)}~^{+0.22}_{-0.13} ~\rm{(syst.)}~\pi~$mm$\cdot$mrad and $0.32\pm 0.03~\rm{(stat.)} ^{+0.05}_{-0.02} ~\rm{(syst.)}~\pi~$mm$\cdot$mrad, respectively. The measured emittance values demonstrated phase space reduction by a factor of $2.0\times 10^2$ (horizontal) and $4.1\times 10^2$ (vertical) allowing good acceleration efficiency. These results pave the way to realize the first-ever muon accelerator for a variety of applications in particle physics, material science, and other fields.

Facility location games provide an abstract model of mechanism design. In such games, a mechanism takes a profile of $n$ single-peaked preferences over an interval as an input and determines the location of a facility on the interval. In this paper, we restrict our attention to distance-based single-peaked preferences and focus on a well-known class of parameterized mechanisms called ordered weighted average methods, which is proposed by Yager in 1988 and contains several practical implementations such as the standard average and the Olympic average. We comprehensively analyze their performance in terms of both incentives and fairness. More specifically, we provide necessary and sufficient conditions on their parameters to achieve strategy-proofness, non-obvious manipulability, individual fair share, and proportional fairness, respectively.

While end-to-end multi-channel electroencephalography (EEG) learning approaches have shown significant promise, their applicability is often constrained in neurological diagnostics, such as intracranial EEG resources. When provided with a single-channel EEG, how can we learn representations that are robust to multi-channels and scalable across varied tasks, such as seizure prediction? In this paper, we present SplitSEE, a structurally splittable framework designed for effective temporal-frequency representation learning in single-channel EEG. The key concept of SplitSEE is a self-supervised framework incorporating a deep clustering task. Given an EEG, we argue that the time and frequency domains are two distinct perspectives, and hence, learned representations should share the same cluster assignment. To this end, we first propose two domain-specific modules that independently learn domain-specific representation and address the temporal-frequency tradeoff issue in conventional spectrogram-based methods. Then, we introduce a novel clustering loss to measure the information similarity. This encourages representations from both domains to coherently describe the same input by assigning them a consistent cluster. SplitSEE leverages a pre-training-to-fine-tuning framework within a splittable architecture and has following properties: (a) Effectiveness: it learns representations solely from single-channel EEG but has even outperformed multi-channel baselines. (b) Robustness: it shows the capacity to adapt across different channels with low performance variance. Superior performance is also achieved with our collected clinical dataset. (c) Scalability: With just one fine-tuning epoch, SplitSEE achieves high and stable performance using partial model layers., Comment: This paper has been accepted by ICDM2024

Color Lie algebras, which were introduced by Ree, are a graded extension of Lie (super)algebras by an abelian group. We show that the color Lie algebras can be used to construct universal weight systems for knot invariants of of Vassiliev and Kontsevich. As a simple example, we take $\mathbb{Z}_2 \times \mathbb{Z}_2$ as the grading group and consider the four-dimensional color Lie algebra called $A1_{\epsilon}$. The weight system constructed from $A1_{\epsilon}$ is studied in some detail and some relations between the weights, such as the recurrence relation for chord diagrams, are derived. These relations show that the weight system from $A1_{\epsilon}$ is a hybrid of those from $sl(2)$ and $gl(1|1)$., Comment: 28 pages, many figures

Automatic rapport estimation in social interactions is a central component of affective computing. Recent reports have shown that the estimation performance of rapport in initial interactions can be improved by using the participant's personality traits as the model's input. In this study, we investigate whether this findings applies to interactions between friends by developing rapport estimation models that utilize nonverbal cues (audio and facial expressions) as inputs. Our experimental results show that adding Big Five features (BFFs) to nonverbal features can improve the estimation performance of self-reported rapport in dyadic interactions between friends. Next, we demystify how BFFs improve the estimation performance of rapport through a comparative analysis between models with and without BFFs. We decompose rapport ratings into perceiver effects (people's tendency to rate other people), target effects (people's tendency to be rated by other people), and relationship effects (people's unique ratings for a specific person) using the social relations model. We then analyze the extent to which BFFs contribute to capturing each effect. Our analysis demonstrates that the perceiver's and the target's BFFs lead estimation models to capture the perceiver and the target effects, respectively. Furthermore, our experimental results indicate that the combinations of facial expression features and BFFs achieve best estimation performances not only in estimating rapport ratings, but also in estimating three effects. Our study is the first step toward understanding why personality-aware estimation models of interpersonal perception accomplish high estimation performance., Comment: 9 pages, 5 figures

A strong coupling between electric polarization and elastic deformation in solids is an important factor in creating useful electromechanical nanodevices. Such coupling is typically allowed in insulating materials with inversion symmetry breaking as exemplified by the piezoelectric effect in ferroelectric materials. Therefore, materials with metallicity and centrosymmetry have tended to be out of scope in this perspective. Here, we report the observation of giant elastic deformation by the application of an alternating electric current in topological semimetals (V,Mo)Te2, regardless of the centrosymmetry. Considering the crystal and band structures and the asymmetric measurement configurations in addition to the absence of the electromechanical effect in a trivial semimetal TiTe2, the observed effect is discussed in terms of a Berry-phase-derived converse flexoelectric effect in metals. The observation of the flexoelectric effect in topological semimetals paves a way for a new type of nanoscale electromechanical sensors and energy harvesting., Comment: 11 pages, 4 figures

Magnetic structures of the noncentrosymmetric magnet Sr$_2$MnSi$_2$O$_7$ were examined through neutron diffraction for powder and single-crystalline samples, as well as magnetometry measurements. All allowed magnetic structures under the space group $P\bar{4}2_1 m$ with the magnetic wavevector $\vec{q}_{\rm m}=(0,0,1/2)$~r.l.u., were analysed via irreducible representation and magnetic space group approaches. The compound is refined to have in-plane magnetic moments within the magnetic space group $Cmc2_1.1^{\prime}_c$ (\#36.177) under zero field, which can be altered to $P2_1 2_1 2_1.1^{\prime}_c$ (\#19.28) above $\mu_0 H=0.067(5)$~T to align induced weak-ferromagnetic components within one layer on the $ab$-plane. All refined parameters are provided following the recent framework based upon the magnetic space group, which better conveys when exchanging crystallographic information for commensurate magnetic structures., Comment: 7 pages, 4 figures

To investigate the role of the excitons for the origin of the pressure-induced phase transition (BGT) from the black-colored insulator (BI) to the golden-yellow-colored metal (GM) of samarium monosulfide (SmS), optical reflectivity, Sm $3d$ X-ray absorption spectroscopy (XAS), and X-ray diffraction (XRD) with the creation of excitons by photoexcitation (PE) are reported. In the pump-probe reflectivity measurement, following a huge reflectivity change of about 22 %, three different relaxation times with a vibration component were observed. The fast component with the relaxation time ($\tau$) of less than 1 ps is due to the excitation and relaxation of electrons into the conduction band, and the slowest one with $\tau > {\rm several} 100$ ps originates from the appearance of the photo-induced (PI) state. The components with $\tau \sim 10$ ps and vibration originate from the appearance of the PI state and the interference between the reflection lights at the sample surface and the boundary between the BI and PI states, suggesting that the electronic structure of the PI phase is different from that of the BI state. XAS spectra indicate that the Sm mean valence is shifted from the Sm$^{2+}$ dominant to the intermediate between Sm$^{2+}$ and Sm$^{3+}$ by PE but did not change to that of the GM phase across BGT, consistent with the reflectivity data. The XRD result after PE shows that the PI state has much less lattice contraction than the GM phase. These results suggest that the BGT cannot be achieved solely by creating excitons after PE but requires other effects, such as a lattice contraction., Comment: 9 pages, 5 figures

We investigate T-duality transformation on an almost bi-hermitian space with torsion. By virtue of the Buscher rule, we completely describe not only the covariant derivative of geometrical objects but also the Nijenhuis tensor. We apply this description to string sigma model whose target space is a T-dualized system from an integrable bi-hermitian space with isometry. We find that hermiticity is not a sufficient condition to preserve integrability under T-duality transformations. However, in the presence of the K\"{a}hler condition, the T-dualized almost complex structures keep integrable even though they become no longer covariantly constant. We also observe that the form of $H$-flux is suitable for string compactification scenarios., Comment: 33 pages, references added, discussions improved

We present near-infrared high-dispersion spectroscopic observations of Europa using the Infrared Camera and Spectrograph (IRCS) onboard the Subaru Telescope, seeking direct evidence of water plumes on Europa and exploring spatial variations in plume activity. Using high spectral/spatial resolution and sensitivity of Subaru/IRCS, our observations have enabled a spatially resolved search for water plumes on Europa. Within our detection limits and time of observation, we found no evidence for the presence of water emission. For a rotation temperature of 50 K, we derived an upper limit on the H$_{2}$O abundance of 9.46$\times$10$^{19}$ - 5.92$\times$10$^{20}$ m$^{-2}$ in each divided slit area and 4.61$\times$10$^{19}$ m$^{-2}$ in the entire area covered by the slit. This upper limit lies below the inferred water abundance from previous UV observations by the Hubble Space Telescope (HST), while being less sensitive by a factor of three compared to the Keck telescope and by one order of magnitude or more than the James Webb Space Telescope (JWST) observations. Our results align with previous studies and demonstrate that using Subaru/IRCS is an effective strategy for searching for water plumes on Europa with high spatial resolution. Continued observations across different surface areas and orbital phases are essential to fully characterize Europa's plume activity and complement upcoming space missions., Comment: 8 pages, 7 figures. Accepted for publication in PASJ

Recent observations of core-collapse supernovae revealed that the existence of dense circumstellar matter (CSM) around their progenitors is ubiquitous. Interaction of supernova ejecta with such a dense CSM is a potential production sight of high-energy cosmic rays (CRs), gamma-rays, and neutrinos. We estimate the gamma-ray and neutrino signals from SN 2023ixf, a core-collapse supernova occurred in a nearby galaxy M101, which exhibits signatures of the interaction with the confined dense CSM. Using radiation-hydrodynamic simulation model calibrated by the optical and ultraviolet observations of SN 2023ixf, we find that the CRs cannot be accelerated in the early phase because the sharp velocity jump at the shock disappears due to strong radiation pressure. Roughly 4 days after the explosion, the collisionless sub-shock is formed in the CSM, which enables the CR production and leads to gamma-ray and neutrino emissions. The shock sweeps up the entire dense CSM roughly 9 days after the explosion, which ceases the high-energy radiation. Based on this scenario, we calculate the gamma-ray and neutrino signals, which have a peak around 9 days after the explosion. We can constrain the cosmic-ray production efficiency to be less than 30\% by comparing our prediction to the Fermi-LAT data. Future multi-messenger observations with an enlarged sample of nearby supernovae will provide a better constraint on the cosmic-ray production efficiency in the early phases of supernovae., Comment: 9 pages, 5 figures

Let $R$ be a commutative Noetherian ring of dimension $d$. In this paper, we first show that some power of the cohomology annihilator annihilates the $(d+1)$-th Ext modules for all finitely generated modules when either $R$ admits a dualizing complex or $R$ is local. Next, we study the Jacobian ideal of affine algebras over a field and equicharacteristic complete local rings, and characterize the equidimensionality of the ring in terms of the singular locus and the closed subsets defined by the cohomology annihilator and the Jacobian ideal., Comment: 16 pages

Data augmentation is known to contribute significantly to the robustness of machine learning models. In most instances, data augmentation is utilized during the training phase. Test-Time Augmentation (TTA) is a technique that instead leverages these data augmentations during the testing phase to achieve robust predictions. More precisely, TTA averages the predictions of multiple data augmentations of an instance to produce a final prediction. Although the effectiveness of TTA has been empirically reported, it can be expected that the predictive performance achieved will depend on the set of data augmentation methods used during testing. In particular, the data augmentation methods applied should make different contributions to performance. That is, it is anticipated that there may be differing degrees of contribution in the set of data augmentation methods used for TTA, and these could have a negative impact on prediction performance. In this study, we consider a weighted version of the TTA based on the contribution of each data augmentation. Some variants of TTA can be regarded as considering the problem of determining the appropriate weighting. We demonstrate that the determination of the coefficients of this weighted TTA can be formalized in a variational Bayesian framework. We also show that optimizing the weights to maximize the marginal log-likelihood suppresses candidates of unwanted data augmentations at the test phase.

This paper introduces an analog spiking neuron that utilizes time-domain information, i.e., a time interval of two signal transitions and a pulse width, to construct a spiking neural network (SNN) for a hardware-friendly physical reservoir computing (RC) on a complementary metal-oxide-semiconductor (CMOS) platform. A neuron with leaky integrate-and-fire is realized by employing two voltage-controlled oscillators (VCOs) with opposite sensitivities to the internal control voltage, and the neuron connection structure is restricted by the use of only 4 neighboring neurons on the 2-dimensional plane to feasibly construct a regular network topology. Such a system enables us to compose an SNN with a counter-based readout circuit, which simplifies the hardware implementation of the SNN. Moreover, another technical advantage thanks to the bottom-up integration is the capability of dynamically capturing every neuron state in the network, which can significantly contribute to finding guidelines on how to enhance the performance for various computational tasks in temporal information processing. Diverse nonlinear physical dynamics needed for RC can be realized by collective behavior through dynamic interaction between neurons, like coupled oscillators, despite the simple network structure. With behavioral system-level simulations, we demonstrate physical RC through short-term memory and exclusive OR tasks, and the spoken digit recognition task with an accuracy of 97.7% as well. Our system is considerably feasible for practical applications and also can be a useful platform for studying the mechanism of physical RC.

Measuring 3D geometric structures of indoor scenes requires dedicated depth sensors, which are not always available. Echo-based depth estimation has recently been studied as a promising alternative solution. All previous studies have assumed the use of echoes in the audible range. However, one major problem is that audible echoes cannot be used in quiet spaces or other situations where producing audible sounds is prohibited. In this paper, we consider echo-based depth estimation using inaudible ultrasonic echoes. While ultrasonic waves provide high measurement accuracy in theory, the actual depth estimation accuracy when ultrasonic echoes are used has remained unclear, due to its disadvantage of being sensitive to noise and susceptible to attenuation. We first investigate the depth estimation accuracy when the frequency of the sound source is restricted to the high-frequency band, and found that the accuracy decreased when the frequency was limited to ultrasonic ranges. Based on this observation, we propose a novel deep learning method to improve the accuracy of ultrasonic echo-based depth estimation by using audible echoes as auxiliary data only during training. Experimental results with a public dataset demonstrate that our method improves the estimation accuracy., Comment: ICIP 2024

We introduce a method that ensures efficient computation of one-dimensional quantum systems with long-range interactions across all temperatures. Our algorithm operates within a quasi-polynomial runtime for inverse temperatures up to $\beta={\rm poly}(\ln(n))$. At the core of our approach is the Density Matrix Renormalization Group algorithm, which typically does not guarantee efficiency. We have created a new truncation scheme for the matrix product operator of the quantum Gibbs states, which allows us to control the error analytically. Additionally, our method is applied to simulate the time evolution of systems with long-range interactions, achieving significantly better precision than that offered by the Lieb-Robinson bound., Comment: 7 pages + 9 pages Supplementary materials, 1 figure

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

Acoustoplasmonic resonators, such as nanobars and crosses, are efficient acousto-optical transducers. The excitation of mechanical modes in these structures strongly depends on the spatial profile of the eigenmodes of the resonator. Using a system of two identical gold elongated bars placed on a silicon dioxide substrate, we examine how breaking mirror symmetries affects the optical and acoustic properties to provide insights in the design of acoustoplasmonic metasurfaces for nonsymmetric acousto-optical transducers. Our findings show that, the absence of mirror symmetries affects differently the optical and nanomechanical response. Broken mirror symmetries not only couple nanomechanical modes existing in single bars, but introduces new torsional resonant modes.

Relaxation rates provide important characteristics both for classical and quantum processes. Essentially they control how fast the system thermalizes, equilibrates, {decoheres, and/or dissipates}. Moreover, very often they are directly accessible to be measured in the laboratory and hence they define key physical properties of the system. Experimentally measured relaxation rates can be used to test validity of a particular theoretical model. Here we analyze a fundamental question: {\em does quantum mechanics provide any nontrivial constraint for relaxation rates?} We prove the conjecture formulated a few years ago that any quantum channel implies that a maximal rate is bounded from above by the sum of all the relaxation rates divided by the dimension of the Hilbert space. It should be stressed that this constraint is universal (it is valid for all quantum systems with finite number of energy levels) and it is tight (cannot be improved). In addition, the constraint plays an analogous role to the seminal Bell inequalities and the well known Leggett-Garg inequalities (sometimes called temporal Bell inequalities). Violations of Bell inequalities rule out local hidden variable models, and violations of Leggett-Garg inequalities rule out macrorealism. Similarly, violations of the bound rule out completely positive-divisible evolution., Comment: 16 pages, no figures

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 present a detailed study of the MASTER OT J030227.28+191754.5 outburst in 2021-2022, reaching an amplitude of 10.2 mag and a duration of 60 d. The detections of (1) the double-peaked optical emission lines, and (2) the early and ordinary superhumps, established that MASTER OT J030227.28+191754.5 is an extremely energetic WZ Sge-type dwarf nova (DN). Based on the superhump observations, we obtained its orbital period and mass ratio as 0.05986(1) d and 0.063(1), respectively. These are within a typical range of low-mass-ratio DNe. According to the binary parameters derived based on the thermal-tidal instability model, our analyses showed that (1) the standard disk model requires an accretion rate $\simeq$ 10$^{20}$ g s$^{-1}$ to explain its peak optical luminosity and (2) large mass was stored in the disk at the outburst onset. These cannot be explained solely by the impact of its massive ($\gtrsim$ 1.15 M$_\odot$) primary white dwarf implied by Kimura et al. (2023). Instead, we propose that the probable origin of this enormously energetic DN outburst is the even lower quiescence viscosity than other WZ Sge-type DNe. This discussion is qualitatively valid for most possible binary parameter spaces unless the inclination is low ($\lesssim 40^\circ$) enough for the disk to be bright explaining the outburst amplitude. Such low inclinations, however, would not allow detectable amplitude of early superhumps in the current thermal-tidal instability model. The optical spectra at outburst maximum showed the strong emission lines of Balmer, He I, and He II series whose core is narrower than $\sim 800$ km s$^{-1}$. Considering its binary parameters, a Keplerian disk cannot explain this narrow component, but the presumable origin is disk winds., Comment: 23 pages, 13 figures, 2 tables. Accepted by PASJ. Part of the online supplemental information is included

We consider the problem of fair allocation of indivisible items with subsidies when agents have weighted entitlements. After highlighting several important differences from the unweighted case, we present several results concerning weighted envy-freeability including general characterizations, algorithms for achieving and testing weighted envy-freeability, lower and upper bounds of the amount of subsidies for envy-freeable allocations, and algorithms for achieving weighted envy-freeability along with other properties., Comment: 26 pages, 1 Table, 1 Figure

We undertake an analysis of Fredholm determinants arising from kernels whose defining functions satisfy a Schr\"odinger type equation. When this defining function is the Airy one, the evaluation of the corresponding Fredholm determinant yields the notorious Tracy-Widom distribution [hep-th/9211141], which has found many applications in numerous domains. In this paper, we unveil a generalization of the Tracy-Widom distribution for a generic class of defining functions. Furthermore, we bring forth a direct application of our upshot and survey the relation between the framework which we employ and isomonodromic systems., Comment: 44 Pages. Added references

For simple graphs $G$ and $H$, the Hom complex $\mathrm{Hom}(G,H)$ is a polyhedral complex whose vertices are the graph homomorphisms $G\to H$. It is known that $\mathrm{Hom}(G,H)$ is homotopy equivalent to a disjoint union of points and circles when both $G$ and $H$ are cycles. We generalize this known result by showing that $\mathrm{Hom}(G,H)$ is homotopy equivalent to a disjoint union of points and circles whenever $G$ is connected and $H$ is a cycle., Comment: 11 pages, 4 figures

We explore visual prompt injection (VPI) that maliciously exploits the ability of large vision-language models (LVLMs) to follow instructions drawn onto the input image. We propose a new VPI method, "goal hijacking via visual prompt injection" (GHVPI), that swaps the execution task of LVLMs from an original task to an alternative task designated by an attacker. The quantitative analysis indicates that GPT-4V is vulnerable to the GHVPI and demonstrates a notable attack success rate of 15.8%, which is an unignorable security risk. Our analysis also shows that successful GHVPI requires high character recognition capability and instruction-following ability in LVLMs., Comment: 8 pages, 6 figures, Accepted to NAACL 2024 SRW

Expressibility is a crucial factor of a Parameterized Quantum Circuit (PQC). In the context of Variational Quantum Algorithms (VQA) based Quantum Machine Learning (QML), a QML model composed of highly expressible PQC and sufficient number of qubits is theoretically capable of approximating any arbitrary continuous function. While much research has explored the relationship between expressibility and learning performance, as well as the number of layers in PQCs, the connection between expressibility and PQC structure has received comparatively less attention. In this paper, we analyze the connection between expressibility and the types of quantum gates within PQCs using a Gradient Boosting Tree model and SHapley Additive exPlanations (SHAP) values. Our analysis is performed on 1,615 instances of PQC derived from 19 PQC topologies, each with 2-18 qubits and 1-5 layers. The findings of our analysis provide guidance for designing highly expressible PQCs, suggesting the integration of more RX or RY gates while maintaining a careful balance with the number of CNOT gates. Furthermore, our evaluation offers an additional evidence of expressibility saturation, as observed by previous studies., Comment: 8 pages, 9 figures

Little Strings are a type of non-gravitational quantum theories that contain extended degrees of freedom, but behave like ordinary Quantum Field Theories at low energies. A particular class of such theories in six dimensions is engineered as the world-volume theory of an M5-brane on a circle that probes a transverse orbifold geometry. Its low energy limit is a supersymmetric gauge theory that is described by a quiver in the shape of the Dynkin diagram of the affine extension of an ADE-group. While the so-called $\widehat{A}$-type Little String Theories (LSTs) are very well studied, much less is known about the $\widehat{D}$-type, where for example the Seiberg-Witten curve (SWC) is only known in the case of the $\widehat{D}_4$ theory. In this work, we provide a general construction of this curve for arbitrary $\widehat{D}_{M}$ that respects all symmetries and dualities of the LST and is compatible with lower-dimensional results in the literature. For $M=4$ our construction reproduces the same curve as previously obtained by other methods. The form in which we cast the SWC for generic $\widehat{D}_M$ allows to study the behaviour of the LST under modular transformations and provides insights into a dual formulation as a circular quiver gauge theory with nodes of $Sp(M-4)$ and $SO(2M)$., Comment: 30 pages

We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers., Comment: 50 pages, 10 figures, 4 tables

The generation of propagating acoustic waves is essential for telecommunication applications, quantum technologies, and sensing. Up to now, the electrical generation has been at the core of most implementations, but is technologically limited to a few gigahertz. Overcoming this frequency limit holds the prospect of faster modulators, quantum acoustics at higher working temperatures, nanoacoustic sensing from smaller volumes. Alternatively, the optical excitation of acoustic resonators has unlocked frequencies up to 1 THz, but in most cases, the acoustic energy cannot be efficiently extracted from the resonator into a propagating wave. Here, we demonstrate a quasi-continuous and coherent source of 20 GHz acoustic phonons, based on a ridge waveguide, structured in the vertical direction as a high-Q acousto-optic resonator. The high frequency phonons propagate up to 20 $\mu$m away from the source, with a decay rate of $\sim$1.14 dB/$\mu$m. We demonstrate the coherence between acoustic phonons generated from two distant sources through spatio-temporal interference. This concept could be scaled up to a larger number of sources, which enable a new generation of optically programmed, reconfigurable nanoacoustic devices and applications.

Let $\Lambda$ be a finite dimensional algebra with an action by a finite group $G$ and $A:= \Lambda *G$ the skew group algebra. One of our main results asserts that the canonical restriction-induction adjoint pair of the skew group algebra extension $\Lambda \subset A$ induces a poset isomorphism between the poset of $G$-stable support $\tau$-tilting modules over $\Lambda$ and that of $(\!\!\!\mod G)$-stable support $\tau$-tilting modules over $A$. We also establish a similar poset isomorphism of posets of appropriate classes of silting complexes over $\Lambda$ and $A$. These two results generalize and unify preceding results by Huang-Zhang, Breaz-Marcus-Modoi and the second and the third authors. Moreover, we give a practical condition under which $\tau$-tilting finiteness and silting discreteness of $\Lambda$ are inherited to those of $A$. As applications we study $\tau$-tilting theory and silting theory of the (generalized) preprojective algebras and the folded mesh algebras. Among other things, we determine the posets of support $\tau$-tilting modules and of silting complexes over preprojective algebra $\Pi(\Bbb{L}_{n})$ of type $\Bbb{L}_{n}$., Comment: 2nd version: minor corrections

The dual-phase liquid argon time projection chamber is presently one of the leading technologies to search for dark matter particles with masses below 10 GeV/c$^2$. This was demonstrated by the DarkSide-50 experiment with approximately 50 kg of low-radioactivity liquid argon as target material. The next generation experiment DarkSide-20k, currently under construction, will use 1,000 times more argon and is expected to start operation in 2027. Based on the DarkSide-50 experience, here we assess the DarkSide-20k sensitivity to models predicting light dark matter particles, including Weakly Interacting Massive Particles (WIMPs) and sub-GeV/c$^2$ particles interacting with electrons in argon atoms. With one year of data, a sensitivity improvement to dark matter interaction cross-sections by at least one order of magnitude with respect to DarkSide-50 is expected for all these models. A sensitivity to WIMP--nucleon interaction cross-sections below $1\times10^{-42}$ cm$^2$ is achievable for WIMP masses above 800 MeV/c$^2$. With 10 years exposure, the neutrino fog can be reached for WIMP masses around 5 GeV/c$^2$., Comment: submitted to Nature Communications

The $^{246}$Cm(n,$\gamma$) and $^{248}$Cm(n,$\gamma$) cross-sections have been measured at the Experimental Area 2 (EAR2) of the n_TOF facility at CERN with three C$_6$D$_6$ detectors. This measurement is part of a collective effort to improve the capture cross-section data for Minor Actinides (MAs), which are required to estimate the production and transmutation rates of these isotopes in light water reactors and innovative reactor systems. In particular, the neutron capture in $^{246}$Cm and $^{248}$Cm open the path for the formation of other Cm isotopes and heavier elements such as Bk and Cf and the knowledge of (n,$\gamma$) cross-sections of these Cm isotopes plays an important role in the transport, transmutation and storage of the spent nuclear fuel. The reactions $^{246}$Cm(n,$\gamma$) and $^{248}$Cm(n,$\gamma$) have been the two first capture measurements analyzed at n_TOF EAR2. Until this experiment and two recent measurements performed at J-PARC, there was only one set of data of the capture cross-sections of $^{246}$Cm and $^{248}$Cm, that was obtained in 1969 in an underground nuclear explosion experiment. In the measurement at n_TOF a total of 13 resonances of $^{246}$Cm between 4 and 400 eV and 5 of $^{248}$Cm between 7 and 100 eV have been identified and fitted. The radiative kernels obtained for $^{246}$Cm are compatible with JENDL-5, but some of them are not with JENDL-4, which has been adopted by JEFF-3.3 and ENDF/B-VIII.0. The radiative kernels obtained for the first three $^{248}$Cm resonances are compatible with JENDL-5, however, the other two are not compatible with any other evaluation and are 20% and 60% larger than JENDL-5.

Binary neutron-star (BNS) mergers are accompanied by multi-messenger emissions, including gravitational wave (GW), neutrino, and electromagnetic signals. Some fraction of BNS mergers may result in a rapidly spinning magnetar as a remnant, which can enhance both the EM and neutrino emissions. In this study, we model the neutrino emissions from such systems and discuss the prospects for detecting the neutrinos coincident with GW signatures. We consider a scenario where a magnetar remnant drives a pulsar wind using its spin energy. The wind interacts with the surrounding kilonova ejecta, forming a nebula filled with non-thermal photons. Ions and nuclei extracted from the magnetar's surface can be accelerated in the polar-cap and the termination-shock regions. We investigate the neutrino fluences resulting from photomeson interactions, where accelerated CR protons interact with the photons in the nebula. Our findings indicate that the peak neutrino fluence is $\sim 10^{-2}\rm GeV~cm^{-2}$ for a source at $40$ Mpc, which is reached approximately $\mathcal{O}( 1-10\ {\rm days})$ post merger. Finally, we examine the potential for GW-triggered stacking searches with IceCube-Gen2 using next-generation GW detectors such as the Cosmic Explorer (CE) and the Einstein Telescope (ET). We conclude that, assuming an optimistic neutrino emission model, a combination of CE+ET would offer a high probability of neutrino detection from these sources within an operational timescale of $\sim 20$ years. In case of non-detection, $2 \sigma$ level constraints on model parameters can be established within similar joint operation timescales., Comment: 21 pages, 8 figures

The purpose of this study is twofold. First, we revisit a shape optimization reformulation of a prototypical shape inverse problem and briefly propose a simple yet efficient numerical approach for solving the minimization problem. Second, we examine the existence, uniqueness, and continuous dependence of a classical solution to a Hele-Shaw-like system, derived from the continuous setting of a numerical discretization of the shape optimization reformulation for the shape inverse problem. The analysis is based on the methods developed by G. I. Bizhanova and V. A. Solonnikov in "On Free Boundary Problems for Second Order Parabolic Equations" (Algebra Anal. 12 (6) (2000) 98-139) and also by V. A. Solonnikov in "Lectures on Evolution Free Boundary Problems: Classical Solutions" (Lect. Notes Math., Springer, 2003, pp. 123-175)., Comment: 60 pages, 5 figures

Global vegetation structure mapping is critical for understanding the global carbon cycle and maximizing the efficacy of nature-based carbon sequestration initiatives. Moreover, vegetation structure mapping can help reduce the impacts of climate change by, for example, guiding actions to improve water security, increase biodiversity and reduce flood risk. Global satellite measurements provide an important set of observations for monitoring and managing deforestation and degradation of existing forests, natural forest regeneration, reforestation, biodiversity restoration, and the implementation of sustainable agricultural practices. In this paper, we explore the effectiveness of fine-tuning of a geospatial foundation model to estimate above-ground biomass (AGB) using space-borne data collected across different eco-regions in Brazil. The fine-tuned model architecture consisted of a Swin-B transformer as the encoder (i.e., backbone) and a single convolutional layer for the decoder head. All results were compared to a U-Net which was trained as the baseline model Experimental results of this sparse-label prediction task demonstrate that the fine-tuned geospatial foundation model with a frozen encoder has comparable performance to a U-Net trained from scratch. This is despite the fine-tuned model having 13 times less parameters requiring optimization, which saves both time and compute resources. Further, we explore the transfer-learning capabilities of the geospatial foundation models by fine-tuning on satellite imagery with sparse labels from different eco-regions in Brazil.

Binary neutron star (BNS) mergers can be sources of ultrahigh-energy (UHE) cosmic rays and potential emitters of UHE neutrinos. The upcoming and current radio neutrino detectors like the Giant Radio Array for Neutrino Detection (GRAND), IceCube-Gen2 Radio, and the Radio Neutrino Observatory in Greenland (RNO-G) are projected to reach the required sensitivities to search for these neutrinos. In particular, in conjunction with the next-generation of gravitational wave (GW) detectors like Cosmic Explorer (CE) and Einstein Telescope (ET), GW-triggered stacking searches can be performed with the UHE neutrino detectors. In this work, we explore the prospects of such searches by implementing in our analysis an upper distance limit based on the sky-localization capabilities of the GW detectors from which meaningful triggers can be collected. We find that if each GW burst is associated with a total isotropic-equivalent energy of $\sim 10^{50} - 10^{51}$ erg emitted in UHE neutrinos, along with a corresponding beaming fraction of $1$\%, GRAND and IceCube-Gen2 Radio have a large probability ($\sim 99$\%) to detect a coincident neutrino event using the joint combination of CE+ET in a timescale of less than 15 years of operation for our fiducial choice of parameters. In case of nondetections, the parameter spaces can be constrained at $3\sigma$ level in similar timescales of operation. We also highlight and discuss the prospects of such joint radio neutrino detector network, their importance, and their role in facilitating synergic GW and neutrino observations in the next era of multimessenger astrophysics., Comment: 18 pages, 6 figures