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This paper introduces the hypothetical track-length fitting algorithm, a novel method for measuring the kinetic energies of ionizing particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

OpenSciEd is a set of Creative Commons licensed, standards aligned curriculum and teacher professional learning materials that will be available for grades K-12. Using a storyline model that gives students the responsibility of "figuring out" science phenomena by engaging in science practices and classroom discussion to achieve consensus, OpenSciEd "empowers educators to go beyond traditional science teaching methods." This instructional model is ambitious for teachers, who must serve as facilitators and continually adapt instruction in response to directions students take. Because of this instructional shift, districts must also shift in how they adopt and implement science curriculum. Among the aims of the OpenSciEd Research Community, led by Digital Promise with support from the Carnegie Corporation of New York, is to develop and disseminate resources that support advancement of OpenSciEd-enabled research. Toward this goal, Digital Promise has released this report that synthesizes perspectives from OpenSciEd practitioners on their needs. The report identifies: (1) supports that teachers need to enact OpenSciEd with integrity, engage all their students, and gather evidence of students' standards-based learning outcomes; (2) ways districts can achieve deep, sustained adoption and meet their teachers' needs; and (3) potential research questions and opportunities for innovation that can improve OpenSciEd implementation in districts and classrooms. [This report was produced in collaboration with OpenSciEd.]

Absorption is a crucial parameter in shaping wave propagation dynamics, yet achieving ultra-broadband absorption remains highly challenging, particularly in balancing low-frequency and broad bandwidth. Here, we present a metamaterial absorber (MMA) capable of achieving simultaneous spectral coverage across a seven-octave range of near-perfect absorption from 100 Hz to 12,800 Hz by engineering the quality-factor-weighted (Q-weighted) mode density. The Q-weighted mode density considers mode density, resonant frequencies, radiative loss, and intrinsic loss of multiple resonant modes, providing a comprehensive approach to govern broadband absorption properties. By optimizing the number of resonant modes and managing intrinsic losses, our approach achieves an intensive Q-weighted mode density across an ultra-wide bandwidth, enabling ultra-broadband absorption with high efficiency. These findings significantly advance the bandwidth capabilities of state-of-the-art MMAs and pave the way for the development of ultra-broadband metamaterial devices across various wave systems.

A B-mode polarization signal in the cosmic microwave background is widely regarded as smoking gun evidence for gravitational waves produced during inflation. Here we demonstrate that tensor perturbations from a cosmological phase transition in the post-inflationary universe can nearly mimic the characteristic shape and power of inflationary predictions across a range of observable angular scales. Although phase transitions arise from subhorizon physics, they nevertheless exhibit a white noise power spectrum on superhorizon scales. Thus, while B-mode power is suppressed on these large scales, it is not necessarily negligible. For viable phase transition parameters, the maximal B-mode amplitude at multipole moments around the recombination peak can be comparable to nearly all single-field inflationary predictions that can be tested with current and future experiments. This approximate degeneracy can be broken if a signal is measured at different angular scales, since the inflationary power spectrum is nearly scale invariant while the phase transition predicts a distinct suppression of power on large scales., Comment: 11 pages, 4 figures

Blazars are beamed active galactic nuclei known for their strong multi-wavelength variability on timescales from years down to minutes. We aim to investigate the suitability of the twisting jet model presented in previous works to explain the multi-wavelength behaviour of BL Lacertae, the prototype of one of the blazar classes. According to this model, the jet is inhomogeneous, curved, and twisting, and the long-term variability is due to changes in the Doppler factor due to variations in the orientation of the jet-emitting regions. We analysed optical data of the source obtained during monitoring campaigns organised by the Whole Earth Blazar Telescope (WEBT) in 2019-2022, together with radio data from the WEBT and other teams, and gamma-ray data from the Fermi satellite. In this period, BL Lacertae underwent an extraordinary activity phase, reaching its historical optical and gamma-ray brightness maxima. The application of the twisting jet model to the source light curves allows us to infer the wiggling motion of the optical, radio, and gamma-ray jet-emitting regions. The optical-radio correlation shows that the changes in the radio viewing angle follow those in the optical viewing angle by about 120 days, and it suggests that the jet is composed of plasma filaments, which is in agreement with some radio high-resolution observations of other sources. The gamma-ray emitting region is found to be co-spatial with the optical one, and the analysis of the gamma-optical correlation is consistent with both the geometric interpretation and a synchrotron self-Compton (SSC) origin of the high-energy photons. We propose a geometric scenario where the jet is made up of a pair of emitting plasma filaments in a sort of double-helix curved rotating structure, whose wiggling motion produces changes in the Doppler beaming and can thus explain the observed multi-wavelength long-term variability., Comment: In press for A&A

Dissipationless localized bound states of open quantum systems are significantly robust to decoherence and have potential applications in quantum technologies. In this work, the decoherence dynamics and dissipationless localized bound states of a two-mode open quantum system are investigated. The conditions for the emergence of dissipationless localized bound states are analytically solved, and the corresponding critical system-environment couplings under different values of the inter-mode coupling and the detuning are determined. The decoherence dynamics of the system under such conditions are analyzed and dissipationless coherence between the different localized bound states against decoherence is clearly shown. This may provide a new avenue to develop dissipationless quantum technology for quantum operations., Comment: 10 pages, 6 figures

We present a new method for the verification of quantum circuits based on a novel symbolic representation of sets of quantum states using level-synchronized tree automata (LSTAs). LSTAs extend classical tree automata by labeling each transition with a set of choices, which are then used to synchronize subtrees of an accepted tree. Compared to the traditional tree automata, LSTAs have an incomparable expressive power while maintaining important properties, such as closure under union and intersection, and decidable language emptiness and inclusion. We have developed an efficient and fully automated symbolic verification algorithm for quantum circuits based on LSTAs. The complexity of supported gate operations is at most quadratic, dramatically improving the exponential worst-case complexity of an earlier tree automata-based approach. Furthermore, we show that LSTAs are a promising model for parameterized verification, i.e., verifying the correctness of families of circuits with the same structure for any number of qubits involved, which principally lies beyond the capabilities of previous automated approaches. We implemented this method as a C++ tool and compared it with three symbolic quantum circuit verifiers and two simulators on several benchmark examples. The results show that our approach can solve problems with sizes orders of magnitude larger than the state of the art.

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips, present in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV energy scale using reconstructed blips in data from the MicroBooNE LArTPC at Fermilab. We observe a concentration of low energy ($<$3 MeV) blips around fiberglass mechanical support struts along the TPC edges with energy spectrum features consistent with the Compton edge of 2.614 MeV $^{208}$Tl decay $\gamma$ rays. These features are used to verify proper calibration of electron energy scales in MicroBooNE's data to few percent precision and to measure the specific activity of $^{208}$Tl in the fiberglass composing these struts, $(11.7 \pm 0.2 ~\text{(stat)} \pm 2.8~\text{(syst)})$ Bq/kg. Cosmogenically-produced blips above 3 MeV in reconstructed energy are used to showcase the ability of large LArTPCs to distinguish between low-energy proton and electron energy depositions. An enriched sample of low-energy protons selected using this new particle discrimination technique is found to be smaller in data than in dedicated CORSIKA cosmic ray simulations, suggesting either incorrect CORSIKA modeling of incident cosmic fluxes or particle transport modeling issues in Geant4., Comment: 19 pages, 15 figures total including the supplementary material section

In this work, we establish modular parameterizations for two general formulas for $\frac{1}{\pi}$ that subsume conjectural Ramanujan type formulas due to Z.-W. Sun, which have remained open since 2011. As an application of this, in a conceptual way we interpret how Sun's conjectural formulas arise and can be verified, as well as recover other cases that were proved by Cooper, Wan and Zudilin.

In this work, we study the cosmological effects of a tower of warm dark matter states on the cosmic microwave background (CMB) and on large-scale structure (LSS). For concreteness, we consider the $N$naturalness model, which is a proposed mechanism to solve the Higgs hierarchy problem. In this framework, the sector of particles of the Standard Model is copied $N$ times where the Higgs mass-squared value is the only parameter that changes between sectors. The other sectors are similar to our own, except their particles are proportionally heavier and cooler compared to the Standard Model sector. Since each sector is extremely weakly coupled to other sectors, direct observations of the new particles are not expected. The addition of new photon-like species and new neutrino-like species, however, can be detected through the CMB and in LSS data. These additional neutrinos form a tower of states with increasing mass and decreasing temperature compared to the SM neutrinos. This tower causes a more gradual suppression of the matter power spectrum across different comoving wavenumbers than a single warm dark matter state would. We quantitatively explore these effects in the $N$naturalness model and compute the parameter space allowed by the Planck 2018, weak lensing, and Lyman-$\alpha$ datasets. Depending on the underlying parameters, Planck 2018 and weak lensing data can require $N$naturalness to be tuned at the $10\%$ level for Dirac neutrinos and at the $5\%$ level for Majorana neutrinos. The additional neutrino states are crucial in constraining the model, particularly through their suppression of the power spectrum at small scales. The inclusion of many warm dark matter species is computationally very challenging and we make detailed assessments of our approximations and comment on potential future improvements., Comment: 36 pages, 15 captioned figures, 4 tables

Context: Theoretical models of early accretion during the formation process of massive stars have predicted that HII regions exhibit radio variability on timescales of decades. However, large-scale searches for such temporal variations with sufficient sensitivity have not yet been carried out. Aims: We aim to identify HII regions with variable radio wavelength fluxes and to investigate the properties of the identified objects, especially those with the highest level of variability. Methods: We compared the peak flux densities of 86 ultracompact HII (UCHII) regions measured by the GLOSTAR and CORNISH surveys and identified variables that show flux variations higher than 30% over ~8 yr timespan between these surveys. Results: We found a sample of 38 variable UCHII regions, which is the largest sample identified to date. The overall occurrence of variability is 44$\pm$5%, suggesting that variation in UCHII regions is significantly more common than prediction. The variable UCHII regions are found to be younger than non-variable UCHII regions, all of them meeting the size criterion of hypercompact (HC) HII regions. We studied the 7 UCHII regions (the ``Top7'') that show the highest variability with variations > 100%. The Top7 variable UCHII regions are optically thick at 4--8 GHz and compact, suggesting they are in a very early evolutionary stage of HCHII or UCHII regions. There is a significant correlation between variability and the spectral index of the radio emission. No dependence is observed between the variations and the properties of the sources' natal clumps traced by submillimeter continuum emission from dust, although variable HII regions are found in clumps at an earlier evolutionary stage., Comment: 11pages, 7 figures, accepted for publication in Astronomy & Astrophysics

The synthesis of binary nanocrystal superlattices (BNSLs) enables the targeted integration of orthogonal physical properties, like photoluminescence and magnetism, into a single superstructure, unlocking a vast design space for multifunctional materials. Yet, the formation mechanism of BNSLs remains poorly understood, restricting the use of simulation to predict the structure and properties of the superlattices. Here, we use a combination of in situ scattering and molecular simulation to elucidate the self-assembly of two common BNSLs through emulsion templating. Our self-assembly experiments reveal that no intermediate structures precede the formation of the final binary phases, indicating that their formation proceeds through classical nucleation. Using simulations, we find that, despite the formation of AlB2 and NaZn13 typically being attributed to entropy, their self-assembly is most consistent with the nanocrystals possessing short-range interparticle attraction, which we find can dramatically accelerate nucleation kinetics in BNSLs. We also find homogenous, classical nucleation in simulation, corroborating our experiments. These results establish a robust correspondence between experiment and theory, paving the way towards a priori prediction of BNSLs.

We extend the construction of the semigroup of the two-dimensional delta-Bose gas in Gu, Quastel, and Tsai (2021) (based on Rajeev (1999) and Dimock and Rajeev (2004)) to a weighted $L^2$ space that allows exponentially growing functions. We further show that the semigroup of the mollified delta-Bose gas converges strongly to that of the delta-Bose gas., Comment: 10 pages

Earth's magnetotail, and the plasma sheet embedded in it, is a highly dynamic region that is coupled to both the solar wind and to the inner magnetosphere. As a consequence of this coupling, the plasma sheet undergoes explosive energy releases in the form of substorms. A substorm is initiated when reconnection is triggered within a thin current sheet, initiating a complex chain of phenomena. One consequence of these phenomena is heating of thermal electrons and acceleration of energetic (non-thermal) electrons. The upper-energy limit as well as the spatial scale size of the electron acceleration regions are ongoing mysteries in magnetotail physics because current missions can only offer us a glimpse into the numerous magnetotail phenomena ranging from electron- to global-scales occurring in this extensive system. Observational difficulties aside, these energetic electrons also provide a significant source of seed electrons for the Van Allen Radiation belts. Here we demonstrate a unique approach to study plasma sheet electron acceleration. We combine Magnetospheric Multiscale (MMS) Mission high-altitude observations with Electron Losses and Fields Investigation (ELFIN) low-altitude observations, to quantify the upper-energy extent and radial scale of a burst of plasma sheet electrons that mapped to 30 Earth radii. We find that the plasma sheet locally accelerated electrons to 2-3 MeV energies -- far higher than previously anticipated -- and scattered them into the atmospheric loss cone. Interestingly, high-altitude observations of the plasma sheet at 17 Earth radii showed only the usual substorm signatures: bursty bulk flows and dipolarizing flux bundles -- demonstrating that this burst was 1) intense, 2) localized to the far magnetotail, and 3) likely accelerated by a very efficient mechanism.

We investigate the production of axion-like particles (ALPs) in stellar cores, where they interact with electromagnetic fields and electrons, with typical masses between $\mathcal O(0.1)$ and $\mathcal O(10)$ keV. These low-energy ALPs are gravitationally trapped in the orbits of stars and subsequently decay into two photons that we detect as monochromatic X-ray lines. We propose to search for these gravitationally trapped ALPs in the Alpha Centauri binary system, our closest stellar neighbor, using sensitive X-ray detectors like Chandra and eROSITA. Our search for ALP decay signals in the energy range of 0.2 keV to 10 keV yielded null results, thus establishing the most stringent limits on ALP interactions to date. Specifically, if ALPs are mainly produced by Compton or bremsstrahlung processes (ALP-electron coupling $g_{aee}$ being significant), we have improved the limits on the ALP-photon coupling $g_{a\gamma\gamma}$ by two to three orders of magnitude, in ALP mass range between 0.2 keV to 5 keV, compared to previous measurements, including those from GW170817, SN 2023ixf, and other sources., Comment: 8 pages, 3 figures

We explored the Patrol Security Game (PSG), a robotic patrolling problem modeled as an extensive-form Stackelberg game, where the attacker determines the timing, location, and duration of their attack. Our objective is to devise a patrolling schedule with an infinite time horizon that minimizes the attacker's payoff. We demonstrated that PSG can be transformed into a combinatorial minimax problem with a closed-form objective function. By constraining the defender's strategy to a time-homogeneous first-order Markov chain (i.e., the patroller's next move depends solely on their current location), we proved that the optimal solution in cases of zero penalty involves either minimizing the expected hitting time or return time, depending on the attacker model, and that these solutions can be computed efficiently. Additionally, we observed that increasing the randomness in the patrol schedule reduces the attacker's expected payoff in high-penalty cases. However, the minimax problem becomes non-convex in other scenarios. To address this, we formulated a bi-criteria optimization problem incorporating two objectives: expected maximum reward and entropy. We proposed three graph-based algorithms and one deep reinforcement learning model, designed to efficiently balance the trade-off between these two objectives. Notably, the third algorithm can identify the optimal deterministic patrol schedule, though its runtime grows exponentially with the number of patrol spots. Experimental results validate the effectiveness and scalability of our solutions, demonstrating that our approaches outperform state-of-the-art baselines on both synthetic and real-world crime datasets., Comment: Under review of TCPS

We investigate coding schemes that map source symbols into multisets of an alphabet set. Such a formulation of source coding is an alternative approach to the traditional framework and is inspired by an object tracking problem over proximity sensor networks. We define a \textit{multiset combinatorial Gray code} as a mulitset code with fixed multiset cardinality that possesses combinatorial Gray code characteristic. For source codes that are organized as a grid, namely an integer lattice, we propose a solution by first constructing a mapping from the grid to the alphabet set, the codes are then defined as the images of rectangular blocks in the grid of fixed dimensions. We refer to the mapping as a \textit{color mapping} and the code as a \textit{color multiset code}. We propose the idea of product multiset code that enables us to construct codes for high dimensional grids based on 1-dimensional (1D) grids. We provide a detailed analysis of color multiset codes on 1D grids, focusing on codes that require the minimal number of colors. To illustrate the application of such a coding scheme, we consider an object tracking problem on 2D grids and show its efficiency, which comes from exploiting transmission parallelism. Some numerical results are presented to conclude the paper., Comment: 30 pages, 4 figures

Aiming to accelerate the training of large deep neural models (DNN) in an energy-efficient way, an analog in-memory computing (AIMC) accelerator emerges as a solution with immense potential. In AIMC accelerators, trainable weights are kept in memory without the need to move from memory to processors during the training, reducing a bunch of overhead. However, although the in-memory feature enables efficient computation, it also constrains the use of data parallelism since copying weights from one AIMC to another is expensive. To enable parallel training using AIMC, we propose synchronous and asynchronous pipeline parallelism for AIMC accelerators inspired by the pipeline in digital domains. This paper provides a theoretical convergence guarantee for both synchronous and asynchronous pipelines in terms of both sampling and clock cycle complexity, which is non-trivial since the physical characteristic of AIMC accelerators leads to analog updates that suffer from asymmetric bias. The simulations of training DNN on real datasets verify the efficiency of pipeline training.

The critical two-dimensional Stochastic Heat Flow (SHF) is the scaling limit of the directed polymers in random environments and the noise-mollified Stochastic Heat Equation (SHE), at the critical dimension of two and near the critical temperature. The work of Caravenna, Sun, and Zygouras (2023) proved that the discrete polymers converge to a universal (model-independent) limit, thereby identifying the limit as the SHF. In this work, we take a different approach: We formulate a set of axioms for the SHF, prove the uniqueness in law under these axioms, and also prove the existence by showing that the noise-mollified SHE converges to the SHF under this formulation. The set consists of three axioms commonly seen in stochastic flows and one axiom about the first four moments of the SHF over every time interval., Comment: 27 pages, 3 figures

We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and generation of personalized videos based on a user's image. Our models set a new state-of-the-art on multiple tasks: text-to-video synthesis, video personalization, video editing, video-to-audio generation, and text-to-audio generation. Our largest video generation model is a 30B parameter transformer trained with a maximum context length of 73K video tokens, corresponding to a generated video of 16 seconds at 16 frames-per-second. We show multiple technical innovations and simplifications on the architecture, latent spaces, training objectives and recipes, data curation, evaluation protocols, parallelization techniques, and inference optimizations that allow us to reap the benefits of scaling pre-training data, model size, and training compute for training large scale media generation models. We hope this paper helps the research community to accelerate progress and innovation in media generation models. All videos from this paper are available at https://go.fb.me/MovieGenResearchVideos.

We use a custom-made calibrator to measure individual detectors' polarization angles of BICEP3, a small aperture telescope observing the cosmic microwave background (CMB) at 95GHz from the South Pole. We describe our calibration strategy and the statistical and systematic uncertainties associated with the measurement. We reach an unprecedented precision for such measurement on a CMB experiment, with a repeatability for each detector pair of $0.02\deg$. We show that the relative angles measured using this method are in excellent agreement with those extracted from CMB data. Because the absolute measurement is currently limited by a systematic uncertainty, we do not derive cosmic birefringence constraints from BICEP3 data in this work. Rather, we forecast the sensitivity of BICEP3 sky maps for such analysis. We investigate the relative contributions of instrument noise, lensing, and dust, as well as astrophysical and instrumental systematics. We also explore the constraining power of different angle estimators, depending on analysis choices. We establish that the BICEP3 2-year dataset (2017--2018) has an on-sky sensitivity to the cosmic birefringence angle of $\sigma = 0.078\deg$, which could be improved to $\sigma = 0.055\deg$ by adding all of the existing BICEP3 data (through 2023). Furthermore, we emphasize the possibility of using the BICEP3 sky patch as a polarization calibration source for CMB experiments, which with the present data could reach a precision of $0.035\deg$. Finally, in the context of inflation searches, we investigate the impact of detector-to-detector variations in polarization angles as they may bias the tensor-to-scalar ratio r. We show that while the effect is expected to remain subdominant to other sources of systematic uncertainty, it can be reliably calibrated using polarization angle measurements such as the ones we present in this paper., Comment: 29 Pages, 17 Figures, 6 Tables, as submitted to PRD

A dual-operation mode SNSPD is demonstrated. In the conventional Geiger SNSPD mode the sensor operates at temperatures well below the critical temperature, Tc, working as an event counter without sensitivity to the number of photons impinging the sensor. In the calorimetric mode, the detector is operated at temperatures just below Tc and displays photon-number sensitivity for wavelengths in the optical spectrum. In this energy sensitive mode, photon absorption causes Joule heating of the SNSPD that becomes partially resistive without the presence of latching. Depending on the application, by tuning the sample temperature and bias current using the same readout system, the SNSPD can readily switch between the two modes. In the calorimetric mode, SNSPD recovery times shorter than the ones in the Geiger mode are observed, reaching values as low as 580ps. Dual-mode SNSPD's may provide significant advancements in spectroscopy and calorimetry, where precise timing, photon counting and energy resolution are required., Comment: Manuscript prepared for APL

Fast radio bursts (FRBs) are transient radio bursts of extragalactic origin characterized by millisecond durations and high luminosities. We report on observations of FRB 20240114A conducted with the Robert C. Byrd Green Bank Telescope (GBT) at frequencies ranging from 720 to 920 MHz. A total of 429 bursts were detected, with a single observation recording 359 bursts over 1.38 hours, corresponding to a burst rate of 260 bursts per hour. The average rotation measures (RMs) were $349.2 \pm 1.0$ rad m$^{-2}$ on February 23, 2024, and $360.4 \pm 0.4$ rad m$^{-2}$ on March 1, 2024. Of the 297 bursts with detected RMs, 72% have a linear polarization fraction greater than 90%, and 14% exhibit circular polarization with a signal-to-noise ratio $> 5$. Our sample also displayed polarization angle swings. We compare the linear polarization of FRB 20240114A with that of FRB 20201124A, FRB 20220912A, and non-repeating FRBs. The mean linear polarization fraction for non-repeating FRBs is 58%. In contrast, the mean linear polarization fraction for the three repeating FRBs is 94%, which is significantly higher than that of the non-repeating FRBs. Under the T-test, the three repeating FRBs have similar linear polarization distributions, but these distributions differ from those of the non-repeating FRBs. This suggests that non-repeating FRBs may have different emission mechanisms or are subject to depolarization., Comment: 42 pages, 5 figures. arXiv admin note: text overlap with arXiv:2304.14671

This paper addresses the synthesis of reactive systems that enforce hard constraints while optimizing for quality-based soft constraints. We build on recent advancements in combining reactive synthesis with example-based guidance to handle both types of constraints in stochastic, oblivious environments accessible only through sampling. Our approach constructs examples that satisfy LTL-based hard constraints while maximizing expected rewards-representing the soft constraints-on samples drawn from the environment. We formally define this synthesis problem, prove it to be NP-complete, and propose an SMT-based solution, demonstrating its effectiveness with a case study., Comment: 19 pages, serve as complete version for reference

Adverse weather image restoration aims to remove unwanted degraded artifacts, such as haze, rain, and snow, caused by adverse weather conditions. Existing methods achieve remarkable results for addressing single-weather conditions. However, they face challenges when encountering unpredictable weather conditions, which often happen in real-world scenarios. Although different weather conditions exhibit different degradation patterns, they share common characteristics that are highly related and complementary, such as occlusions caused by degradation patterns, color distortion, and contrast attenuation due to the scattering of atmospheric particles. Therefore, we focus on leveraging common knowledge across multiple weather conditions to restore images in a unified manner. In this paper, we propose a Triplet Attention Network (TANet) to efficiently and effectively address all-in-one adverse weather image restoration. TANet consists of Triplet Attention Block (TAB) that incorporates three types of attention mechanisms: Local Pixel-wise Attention (LPA) and Global Strip-wise Attention (GSA) to address occlusions caused by non-uniform degradation patterns, and Global Distribution Attention (GDA) to address color distortion and contrast attenuation caused by atmospheric phenomena. By leveraging common knowledge shared across different weather conditions, TANet successfully addresses multiple weather conditions in a unified manner. Experimental results show that TANet efficiently and effectively achieves state-of-the-art performance in all-in-one adverse weather image restoration. The source code is available at https://github.com/xhuachris/TANet-ACCV-2024., Comment: 17 pages (ACCV 2024)

We present a transmission spectrum of the misaligned hot Jupiter WASP-15b from 2.8--5.2 microns observed with JWST's NIRSpec/G395H grating. Our high signal to noise data, which has negligible red noise, reveals significant absorption by H$_2$O ($4.2\sigma$) and CO$_2$ ($8.9\sigma$). From independent data reduction and atmospheric retrieval approaches, we infer that WASP-15b's atmospheric metallicity is super-solar ($\gtrsim 15\times$ solar) and its C/O is consistent with solar, that together imply planetesimal accretion. Our GCM simulations for WASP-15b suggest that the C/O we measure at the limb is likely representative of the entire photosphere due to the mostly uniform spatial distribution of H$_2$O, CO$_2$ and CO. We additionally see evidence for absorption by SO$_2$ and absorption at 4.9$\mu$m, for which the current leading candidate is OCS, albeit with several caveats. If confirmed, this would be the first detection of OCS in an exoplanet atmosphere and point towards complex photochemistry of sulphur-bearing species in the upper atmosphere. These are the first observations from the BOWIE-ALIGN survey which is using JWST's NIRSpec/G395H instrument to compare the atmospheric compositions of aligned/low-obliquity and misaligned/high-obliquity hot Jupiters around F stars above the Kraft break. The goal of our survey is to determine whether the atmospheric composition differs across two populations of planets that have likely undergone different migration histories (disc versus disc-free) as evidenced by their obliquities (aligned versus misaligned)., Comment: 24 pages, 23 figures, 6 tables. Submitted to MNRAS

We show that for any pair of long enough parallel geodesics in a random group $G_\ell(m,d)$ with $m$ generators at density $d<1/6$, there is a van Kampen diagram having only one layer of faces. Using this result, we give an upper bound, depending only on $d$, of the number of pairwise parallel geodesics in $G_\ell(m,d)$ when $d<1/6$. As an application, we show that the minimal stable length of $G_\ell(m,d)$ at $d<1/6$ is exactly $1$., Comment: 21 pages

This paper examines the phenomenon of probabilistic robustness overestimation in TRADES, a prominent adversarial training method. Our study reveals that TRADES sometimes yields disproportionately high PGD validation accuracy compared to the AutoAttack testing accuracy in the multiclass classification task. This discrepancy highlights a significant overestimation of robustness for these instances, potentially linked to gradient masking. We further analyze the parameters contributing to unstable models that lead to overestimation. Our findings indicate that smaller batch sizes, lower beta values (which control the weight of the robust loss term in TRADES), larger learning rates, and higher class complexity (e.g., CIFAR-100 versus CIFAR-10) are associated with an increased likelihood of robustness overestimation. By examining metrics such as the First-Order Stationary Condition (FOSC), inner-maximization, and gradient information, we identify the underlying cause of this phenomenon as gradient masking and provide insights into it. Furthermore, our experiments show that certain unstable training instances may return to a state without robust overestimation, inspiring our attempts at a solution. In addition to adjusting parameter settings to reduce instability or retraining when overestimation occurs, we recommend incorporating Gaussian noise in inputs when the FOSC score exceed the threshold. This method aims to mitigate robustness overestimation of TRADES and other similar methods at its source, ensuring more reliable representation of adversarial robustness during evaluation.

This study explores a relationship between the CO luminosity-full width at half-maximum linewidth linear relation (i.e. the CO LFR) and mean galaxy property of the local star-forming galaxy sample in the xCOLDGASS data base, via a mathematical statement. The whole data base galaxies were separated into two subsamples based on their stellar masses and redshifts, being a help to examine the dependence issue of the CO LFR. Selecting the galaxy data with a stringent requirement was also implemented in order to assure the validly of the CO LFR. An algorithm of the linear regression was conducted with the data of the subsample. An assessment about the linear correlation manifested a valid CO LFR occurs in the selected galaxy of the subsample, and the intercept of the CO LFR may be related with the mean galaxy properties such as the molecular gas fraction and galaxy size. For the finding on the intercept of the CO LFR, we aligned that intercept with those galaxy properties via the involvement of a $\psi$ parameter. On evaluating the $\psi$ value with our local star-forming galaxy sample, we numerically determined a relationship between the statistical result and the galaxy property in a different stellar mass range. It also shows a possible method on estimating galaxy property., Comment: 10 pages, 3 tables, 2 figures; we sincerely appreciate the suggestion of the referee and the acceptance of the MNRAS. Y-HW is greatly grateful to all the co-authors for their works on his articles

The detection of fast radio bursts (FRBs) in radio astronomy is a complex task due to the challenges posed by radio frequency interference (RFI) and signal dispersion in the interstellar medium. Traditional search algorithms are often inefficient, time-consuming, and generate a high number of false positives. In this paper, we present DRAFTS, a deep learning-based radio fast transient search pipeline. DRAFTS integrates object detection and binary classification techniques to accurately identify FRBs in radio data. We developed a large, real-world dataset of FRBs for training deep learning models. The search test on FAST real observation data demonstrates that DRAFTS performs exceptionally in terms of accuracy, completeness, and search speed. In the re-search of FRB 20190520B observation data, DRAFTS detected more than three times the number of bursts compared to Heimdall, highlighting the potential for future FRB detection and analysis., Comment: 20 pages, 10 figures, submitted

The total variation (TV) method is an image denoising technique that aims to reduce noise by minimizing the total variation of the image, which measures the variation in pixel intensities. The TV method has been widely applied in image processing and computer vision for its ability to preserve edges and enhance image quality. In this paper, we propose an improved TV model for image denoising and the associated numerical algorithm to carry out the procedure, which is particularly effective in removing several types of noises and their combinations. Our improved model admits a unique solution and the associated numerical algorithm guarantees the convergence. Numerical experiments are demonstrated to show improved effectiveness and denoising quality compared to other TV models. Such encouraging results further enhance the utility of the TV method in image processing.

The precision measurements of the muon magnetic moment and the $W$ boson mass have sparked interest in the potential deviations from standard model (SM) predictions. While it may be premature to attribute any excesses in these precision measurements to new physics, they do offer a valuable indication of potential directions for physics beyond the SM. Additionally, the particle nature of dark matter (DM) remains a crucial enigma. Despite the absence of any definitive DM signal in direct detection and collider experiments, the Galactic Center GeV $\gamma$-ray excess and the AMS-02 antiproton ($\overline{p}$) excess could potentially offer hints related to the evidence of DM. Motivated by these observations, we propose a simple DM model that addresses all these issues. This model extends the SM by incorporating singlet and doublet Dirac fermion fields, along with a doublet complex scalar field. For the viable parameter regions in this model, we find that future upgrades of the Large Hadron Collider and DM direct detection experiments can only partially probe them, while future high-energy muon colliders hold promise for exploring the unexplored parameter space., Comment: 33 pages, 10 figures, 2 tables. Comments are welcome

The Ly$\alpha$ emission has emerged as a powerful tool for probing diffuse gas within the large-scale structure of the universe. In this paper, we investigate cosmic Ly$\alpha$ emission by post-processing cosmological simulations from \texttt{IllustrisTNG} and \texttt{THESAN} project. Specifically, we calculate the Ly$\alpha$ emission from galaxies, circum-galactic medium (CGM) and inter-galactic medium (IGM) across various redshifts. Our results show that IGM alone is significantly under the current observational upper limits. Meanwhile, CGM overshoots the observed galaxy contribution at $z \lesssim 0.5$ indicating that either the escape fraction for the inner CGM is less than unity or the current photoionization equilibrium treatment with an approximate self-shielding prescription is less accurate. The galaxy component also overshoots at low redshift, indicating that the escape fraction has strong evolution caused by an evolving halo mass function and dust growth distribution, that agrees with observationally inferred escape fractions. Furthermore, our findings suggest that the Ly$\alpha$ emission from diffuse gas (CGM+IGM) peaked at $z \sim 4$ and diminishes toward lower redshift. The Ly$\alpha$ emission from diffuse gas mainly originates through the collisional excitation of hot plasma. By comparing models with observation, our predicted Ly$\alpha$ emission from diffuse gas remains $\sim 6$ times fainter than the observed cosmic Ly$\alpha$ emission at $z=1-3$. However, future large telescopes may hold great promise to detect Ly$\alpha$ emission from diffuse gas toward $z>3$.

We consider the existence and $L^q$ gradient estimates for perturbed Stokes systems with divergence-free critical drift in a bounded Lipschitz domain in $\mathbb{R}^n$, $n \ge 3$. The first two results assume the drift is either in $L^n$ or sufficiently small in weak $L^n$. The third result assumes the drift is in weak $L^n$ without smallness, and obtain results for $q$ close to 2.

Human emotional expression is inherently dynamic, complex, and fluid, characterized by smooth transitions in intensity throughout verbal communication. However, the modeling of such intensity fluctuations has been largely overlooked by previous audio-driven talking-head generation methods, which often results in static emotional outputs. In this paper, we explore how emotion intensity fluctuates during speech, proposing a method for capturing and generating these subtle shifts for talking-head generation. Specifically, we develop a talking-head framework that is capable of generating a variety of emotions with precise control over intensity levels. This is achieved by learning a continuous emotion latent space, where emotion types are encoded within latent orientations and emotion intensity is reflected in latent norms. In addition, to capture the dynamic intensity fluctuations, we adopt an audio-to-intensity predictor by considering the speaking tone that reflects the intensity. The training signals for this predictor are obtained through our emotion-agnostic intensity pseudo-labeling method without the need of frame-wise intensity labeling. Extensive experiments and analyses validate the effectiveness of our proposed method in accurately capturing and reproducing emotion intensity fluctuations in talking-head generation, thereby significantly enhancing the expressiveness and realism of the generated outputs.

Latent diffusion models (LDMs) have made significant advancements in the field of image generation in recent years. One major advantage of LDMs is their ability to operate in a compressed latent space, allowing for more efficient training and deployment. However, despite these advantages, challenges with LDMs still remain. For example, it has been observed that LDMs often generate high-frequency details and complex compositions imperfectly. We hypothesize that one reason for these flaws is due to the fact that all pre- and post-training of LDMs are done in latent space, which is typically $8 \times 8$ lower spatial-resolution than the output images. To address this issue, we propose adding pixel-space supervision in the post-training process to better preserve high-frequency details. Experimentally, we show that adding a pixel-space objective significantly improves both supervised quality fine-tuning and preference-based post-training by a large margin on a state-of-the-art DiT transformer and U-Net diffusion models in both visual quality and visual flaw metrics, while maintaining the same text alignment quality.

The BICEP3 and BICEP Array polarimeters are small-aperture refracting telescopes located at the South Pole designed to measure primordial gravitational wave signatures in the Cosmic Microwave Background (CMB) polarization, predicted by inflation. Constraining the inflationary signal requires not only excellent sensitivity, but also careful control of instrumental systematics. Both instruments use antenna-coupled orthogonally polarized detector pairs, and the polarized sky signal is reconstructed by taking the difference in each detector pair. As a result, the differential response between detectors within a pair becomes an important systematic effect we must control. Additionally, mapping the intensity and polarization response in regions away from the main beam can inform how sidelobe levels affect CMB measurements. Extensive calibration measurements are taken in situ every austral summer for control of instrumental systematics and instrument characterisation. In this work, we detail the set of beam calibration measurements that we conduct on the BICEP receivers, from deep measurements of main beam response to polarized beam response and sidelobe mapping. We discuss the impact of these measurements for instrumental systematics studies and design choices for future CMB receivers., Comment: 13 pages, 7 figures, 1 table, Proceedings paper SPIE 2024

We propose an algorithm for evolving spiral curves on a planar domain by normal velocities depending on the so-called crystalline curvatures. The algorithm uses a minimizing movement approach and relies on a special level set method for embedding the spirals. We present numerical simulations and comparisons demonstrating the efficacy of the proposed numerical algorithm., Comment: 45pages, 17 figures

The characterization of young planets (< 300 Myr) is pivotal for understanding planet formation and evolution. We present the 3-5$\mu$m transmission spectrum of the 17 Myr, Jupiter-size ($R$ $\sim$10$R_{\oplus}$) planet, HIP 67522 b, observed with JWST/NIRSpec/G395H. To check for spot contamination, we obtain a simultaneous $g$-band transit with SOAR. The spectrum exhibits absorption features 30-50% deeper than the overall depth, far larger than expected from an equivalent mature planet, and suggests that HIP 67522 b's mass is $<$20 $M_{\oplus}$ irrespective of cloud cover and stellar contamination. A Bayesian retrieval analysis returns a mass constraint of $13.8\pm1.0M_{\oplus}$. This challenges the previous classification of HIP 67522 b as a hot Jupiter and instead, positions it as a precursor to the more common sub-Neptunes. With a density of $<$0.10g/cm$^{3}$, HIP 67522 b is one of the lowest density planets known. We find strong absorption from H$_{2}$O and CO$_{2}$ ($\ge7\sigma$), a modest detection of CO (3.5$\sigma$), and weak detections of H$_2$S and SO$_2$ ($\simeq2\sigma$). Comparisons with radiative-convective equilibrium models suggest supersolar atmospheric metallicities and solar-to-subsolar C/O ratios, with photochemistry further constraining the inferred atmospheric metallicity to 3$\times$10 Solar due to the amplitude of the SO$_2$ feature. These results point to the formation of HIP 67522 b beyond the water snowline, where its envelope was polluted by icy pebbles and planetesimals. The planet is likely experiencing substantial mass loss (0.01-0.03 M$_{\oplus}$ Myr$^{-1}$), sufficient for envelope destruction within a Gyr. This highlights the dramatic evolution occurring within the first 100 Myr of its existence., Comment: Accepted for publication in The Astronomical Journal; 32 pages, 18 figures, 7 tables

We report the fabrication and characteristics of GaAs/Si p+/n+ heterojunction tunnel diodes. These diodes were fabricated via grafting the freestanding single-crystalline p-type degenerately doped GaAs (4E19 cm-3) nanomembrane (NM) onto single-crystalline n-type Si (5E19 cm-3) substrate. At the heterointerface, an amorphous ultrathin oxygen-enriched layer (UOL) was intentionally engineered through chemical oxidation and atomic layer deposition (ALD). Scanning transmission electron microscopy (STEM) confirmed the formation of the UOL and the single crystallinity of the grafted junction. The resulting tunnel diodes consistently exhibited negative differential resistance (NDR) behavior at room temperature, with a high maximum peak-to-valley current ratio (PVCR) of 36.38, valley voltages ranging from 1.3 to 1.8 V, and a peak tunneling current density of 0.95 kA/cm2. This study not only highlights the critical roles of the UOL as both an interface improvement layer and a quantum tunneling medium, but also establishes "semiconductor grafting" as an effective and versatile method for high-performance, lattice-mismatched heterojunction devices., Comment: 4 pages, 5 figures

The trend toward using increasingly large arrays of antenna elements continues. However, fitting more antennas into the limited space available on user equipment (UE) within the currently popular Frequency Range 1 spectrum presents a significant challenge. This limitation constrains the capacity scaling gains for end users, even when networks can support a higher number of antennas. To address this issue, we explore a user-centric collaborative MIMO approach, termed UE-CoMIMO, which leverages several fixed or portable devices within a personal area to form a virtually expanded antenna array. This paper develops a comprehensive mathematical framework to analyze the performance of UE-CoMIMO. Our analytical results demonstrate that UE-CoMIMO can significantly enhance the system's effective channel response within the current communication system without requiring extensive modifications. Further performance improvements can be realized by optimizing the phase shifters on the expanded antenna arrays at the collaborative devices. These findings are corroborated by ray-tracing simulations. Beyond the simulations, we implemented these collaborative devices and successfully conducted over-the-air validation in a real 5G environment, showcasing the practical potential of UE-CoMIMO. Several practical perspectives are discussed, highlighting the feasibility and benefits of this approach in real-world scenarios., Comment: 13 pages, 11 figures, this work has been submitted to IEEE for possible publication

Building on the success of deep learning models in cardiovascular structure segmentation, increasing attention has been focused on improving generalization and robustness, particularly in small, annotated datasets. Despite recent advancements, current approaches often face challenges such as overfitting and accuracy limitations, largely due to their reliance on large datasets and narrow optimization techniques. This paper introduces the UU-Mamba model, an extension of the U-Mamba architecture, designed to address these challenges in both cardiac and vascular segmentation. By incorporating Sharpness-Aware Minimization (SAM), the model enhances generalization by targeting flatter minima in the loss landscape. Additionally, we propose an uncertainty-aware loss function that combines region-based, distribution-based, and pixel-based components to improve segmentation accuracy by capturing both local and global features. While the UU-Mamba model has already demonstrated great performance, further testing is required to fully assess its generalization and robustness. We expand our evaluation by conducting new trials on the ImageCAS (coronary artery) and Aorta (aortic branches and zones) datasets, which present more complex segmentation challenges than the ACDC dataset (left and right ventricles) used in our previous work, showcasing the model's adaptability and resilience. We confirm UU-Mamba's superior performance over leading models such as TransUNet, Swin-Unet, nnUNet, and nnFormer. Moreover, we provide a more comprehensive evaluation of the model's robustness and segmentation accuracy, as demonstrated by extensive experiments.

Discretely self-similar solutions to Oberbeck-Boussinesq system with Newtonian gravitational field for large discretely self-similar initial data are constructed in this note, extending the construction of Brandolese and Karch (arXiv:2311.01093) on self-similar solutions. It follows the approach of Bradshaw and Tsai (Ann.~Henri Poincar\'e 2017) and find an explicit a priori bound for the deviation from suitably revised profiles in similarity variables.

We consider the possibility of indirect detection of dark sector processes by investigating a novel form of interaction between ambient dark matter (DM) and primordial black holes (PBHs). The basic scenario we envisage is that the ambient DM is ``dormant'', \ie, it has interactions with the SM, but its potential for an associated SM signal is not realized for various reasons. We argue that the presence of PBHs with active Hawking radiation (independent of any DM considerations) can act as a catalyst in this regard by overcoming the aforementioned bottlenecks. The central point is that PBHs radiate all types of particles, whether in the standard model (SM) or beyond (BSM), which have a mass at or below their Hawking temperature. The emission of such radiation is ``democratic" (up to the particle spin), since it is based on a coupling of sorts of gravitational origin. In particular, such shining of (possibly dark sector) particles onto ambient DM can then activate the latter into giving potentially observable SM signals. We illustrate this general mechanism with two specific models. First, we consider asymmetric DM, which is characterized by an absence of ambient anti-DM, and consequently the absence of DM indirect detection signals. In this case, PBHs can ``resurrect'' such a signal by radiating anti-DM, which then annihilates with ambient DM in order to give SM particles such as photons. In our second example, we consider the PBH emission of dark gauge bosons which can excite ambient DM into a heavier state (which is, again, not ambient otherwise), this heavier state later decays back into DM and photons. Finally, we demonstrate that we can obtain observable signals of these BSM models from asteroid-mass PBHs (Hawking radiating currently with $\sim \mathcal{O}(\mathrm{MeV})$ temperatures) at gamma-ray experiments such as AMEGO-X., Comment: 19 pages + 3 appendices, 9 figures

Over 700 bright millisecond-duration radio transients, known as Fast Radio Bursts (FRBs), have been identified to date. Nevertheless, the origin of FRBs remains unknown. The two repeating FRBs (FRB 20121102A and FRB 20190520B) have been verified to be associated with persistent radio sources (PRSs), making them the best candidates to study the nature of FRBs. Monitoring the variability in PRSs is essential for understanding their physical nature. We conducted 22 observations of the PRSs linked to FRB 20121102A and FRB 20190520B using the Karl G. Jansky Very Large Array (VLA), to study their variability. We have observed significant flux variability for the PRSs of FRB 20121102A and FRB 20190520B, with a confidence level exceeding 99.99%, based on the observations covering the longest timescale recorded to date. The observed variability of the two PRSs exhibits no significant difference in amplitude across both short and long timescales. We found that the radio-derived star formation rates of the two FRB hosts are significantly higher than those measured by the optical $H_{\alpha}$ emissions, indicating that their host galaxies are highly obscured or most radio emissions are not from star formation processes. The observed timescale of PRS flux evolution constrained the magnetic field of FRB 20121102A with $B_\parallel\gtrsim1~{\rm mG}$ and FRB 20190520B with $B_\parallel\gtrsim0.1~{\rm mG}$., Comment: 16 pages, 7 figures, accepted by ApJ

Despite the significant progress made in code generation with large language models, challenges persist, especially with hardware description languages such as Verilog. This paper first presents an analysis of fine-tuned LLMs on Verilog coding, with synthetic data from prior methods. We identify two main issues: difficulties in handling non-textual representations (Karnaugh maps, state-transition diagrams and waveforms) and significant variability during training with models randomly making "minor" mistakes. To address these limitations, we enhance data curation by creating correct-by-construction data targeting non-textual representations. Additionally, we introduce an automated framework that generates error reports from various model checkpoints and injects these errors into open-source code to create targeted code repair data. Our fine-tuned Starcoder2-15B outperforms prior state-of-the-art results by 3.8%, 10.9%, 6.6% for pass@1 on VerilogEval-Machine, VerilogEval-Human, and RTLLM.

We revisit the problem of motion planning in the Gaussian belief space. Motivated by the fact that most existing sampling-based planners suffer from high computational costs due to the high-dimensional nature of the problem, we propose an approach that leverages a deep learning model to predict optimal path candidates directly from the problem description. Our proposed approach consists of three steps. First, we prepare a training dataset comprising a large number of input-output pairs: the input image encodes the problem to be solved (e.g., start states, goal states, and obstacle locations), whereas the output image encodes the solution (i.e., the ground truth of the shortest path). Any existing planner can be used to generate this training dataset. Next, we leverage the U-Net architecture to learn the dependencies between the input and output data. Finally, a trained U-Net model is applied to a new problem encoded as an input image. From the U-Net's output image, which is interpreted as a distribution of paths,an optimal path candidate is reconstructed. The proposed method significantly reduces computation time compared to the sampling-based baseline algorithm.

Rb-82 is a radioactive isotope widely used for cardiac PET imaging. Despite numerous benefits of 82-Rb, there are several factors that limits its image quality and quantitative accuracy. First, the short half-life of 82-Rb results in noisy dynamic frames. Low signal-to-noise ratio would result in inaccurate and biased image quantification. Noisy dynamic frames also lead to highly noisy parametric images. The noise levels also vary substantially in different dynamic frames due to radiotracer decay and short half-life. Existing denoising methods are not applicable for this task due to the lack of paired training inputs/labels and inability to generalize across varying noise levels. Second, 82-Rb emits high-energy positrons. Compared with other tracers such as 18-F, 82-Rb travels a longer distance before annihilation, which negatively affect image spatial resolution. Here, the goal of this study is to propose a self-supervised method for simultaneous (1) noise-aware dynamic image denoising and (2) positron range correction for 82-Rb cardiac PET imaging. Tested on a series of PET scans from a cohort of normal volunteers, the proposed method produced images with superior visual quality. To demonstrate the improvement in image quantification, we compared image-derived input functions (IDIFs) with arterial input functions (AIFs) from continuous arterial blood samples. The IDIF derived from the proposed method led to lower AUC differences, decreasing from 11.09% to 7.58% on average, compared to the original dynamic frames. The proposed method also improved the quantification of myocardium blood flow (MBF), as validated against 15-O-water scans, with mean MBF differences decreased from 0.43 to 0.09, compared to the original dynamic frames. We also conducted a generalizability experiment on 37 patient scans obtained from a different country using a different scanner., Comment: 15 Pages, 10 Figures, 5 tables. Paper Under review. Oral Presentation at IEEE MIC 2023