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Relativistic magnetized jets, originating near black holes, are observed to exhibit sub-structured flows. In this study, we present synthetic synchrotron emission signatures for different lines of sight and frequencies, derived from three-dimensional relativistic magneto-hydrodynamic simulations of pc-scale AGN jets. These simulations apply different injection nozzles, injecting steady, variable, and precessing jets. Extending our previous study, here, we have developed a bridge to connect jet dynamics and particle acceleration within relativistic shocks with non-thermal radiation dominant in jets. The emission is derived from Lagrangian particles - injected into the jet and following the fluid - accelerated through diffusive shock acceleration and subsequently cooled by emitting energy via synchrotron and inverse-Compton processes. Overall, the different shocks structures lead to the formation of numerous localized emission patterns - interpreted as jet knots. These knot patterns can fade or flare, also as a consequence of merging or Doppler boosting, leading to jet variability. We find knots with high-enough pattern speed supposed to be visible as superluminal motion <~5c. Synchrotron spectra of all jets reveal double-humped structures, reflecting multiple electron populations characterized by the nature of underlying shock and their age. The precessing jet is the most powerful emitter, featuring a spectrum flatter than the steady and the variable jet. The emission, although essentially governed by the acceleration through shocks, depends on the cooling history of the particle as well. Overall, the continuous re-acceleration of electrons through shocks along the jet we found, is an essential prerequisite for observing extended jet emission over large time-scales and length-scales., Comment: Submitted to The Astrophysical Journal (ApJ)

We perform the first search for $C\!P$ violation in ${D_{(s)}^{+}\to{}K_{S}^{0}K^{-}\pi^{+}\pi^{+}}$ decays. We use a combined data set from the Belle and Belle II experiments, which study $e^+e^-$ collisions at center-of-mass energies at or near the $\Upsilon(4S)$ resonance. We use 980 fb$^{-1}$ of data from Belle and 428 fb$^{-1}$ of data from Belle~II. We measure six $C\!P$-violating asymmetries that are based on triple products and quadruple products of the momenta of final-state particles, and also the particles' helicity angles. We obtain a precision at the level of 0.5% for $D^+\to{}K_{S}^{0}K^{-}\pi^{+}\pi^{+}$ decays, and better than 0.3% for $D^+_{s}\to{}K_{S}^{0}K^{-}\pi^{+}\pi^{+}$ decays. No evidence of $C\!P$ violation is found. Our results for the triple-product asymmetries are the most precise to date for singly-Cabibbo-suppressed $D^+$ decays. Our results for the other asymmetries are the first such measurements performed for charm decays., Comment: 21 pages, 10 figures

High-fidelity direct numerical simulation of turbulent flows for most real-world applications remains an outstanding computational challenge. Several machine learning approaches have recently been proposed to alleviate the computational cost even though they become unstable or unphysical for long time predictions. We identify that the Fourier neural operator (FNO) based models combined with a partial differential equation (PDE) solver can accelerate fluid dynamic simulations and thus address computational expense of large-scale turbulence simulations. We treat the FNO model on the same footing as a PDE solver and answer important questions about the volume and temporal resolution of data required to build pre-trained models for turbulence. We also discuss the pitfalls of purely data-driven approaches that need to be avoided by the machine learning models to become viable and competitive tools for long time simulations of turbulence.

Machine unlearning aims to efficiently eliminate the influence of specific training data, known as the forget set, from the model. However, existing unlearning methods for Large Language Models (LLMs) face a critical challenge: they rely solely on negative feedback to suppress responses related to the forget set, which often results in nonsensical or inconsistent outputs, diminishing model utility and posing potential privacy risks. To address this limitation, we propose a novel approach called Alternate Preference Optimization (AltPO), which combines negative feedback with in-domain positive feedback on the forget set. Additionally, we introduce new evaluation metrics to assess the quality of responses related to the forget set. Extensive experiments show that our approach not only enables effective unlearning but also avoids undesirable model behaviors while maintaining overall model performance.

In the 1970s, Fulling, Davies, and Unruh demonstrated that the vacuum state perceived by an inertial observer in Minkowski space appears as a thermal bath to a uniformly accelerated observer. We explore the transformation of the Wigner distribution of a real scalar field from an inertial to a Rindler frame, utilizing both Minkowski and Unruh modes. We present a general expression for the reduced Wigner distribution for a specific set of massless scalar field configurations, and validate it against known distributions within this set. This includes arbitrary Gaussian states of Unruh-Minkowski modes, the Minkowski vacuum state, the Rindler vacuum, and the thermal bath of Unruh particles. Additionally, we analyze several other distributions, such as a uniform momentum distribution, a slight deviation from the Minkowski vacuum, and a distribution with a Fermionic component in the Rindler frame. The conclusions are discussed., Comment: 34 pages, 3 figures

Research on microwave signal measurement techniques is risen, driven by the expanding urgent demands of wireless communication, global positioning systems, remote sensing and 6G networks. In stark contrast with traditional electronic-based realization, the implementations of microwave signal measurement systems based on integrated compact photonic chip have exhibited distinct advantages in high operation bandwidth, light weight, and strong immunity to electromagnetic interference. However, although numerous integrated microwave photonic signal measurement systems have been reported, measurement bandwidth of the majority of them is still below 30 GHz due to the bandwidth limitation of electro-optical modulators (EOMs). Furthermore, previous studies often are more focused on the measurement of one single parameter (typically the frequency) of microwave signals, which has hindered their practical application in complex situations. Here, an integrated photonic microwave multi-parameter measurement system composed of microwave frequency measurement module and microwave phase amplitude measurement module based on thin-film lithium niobate (TFLN) platform is reported. Utilizing this system, not only the ultra-high bandwidth (up to 60GHz) of microwave frequency, phase and amplitude measurement with low root-mean-squares errors (450MHz, 3.43{\deg} and 1.64% of the measurement for frequency, phase and amplitude, respectively), but also the time-domain reconstruction of sinusoidal microwave signals is achieved. This demonstration further broadens the application of integrated TFLN photonic devices in microwave signal measurement technology to address the bandwidth bottleneck of the ever-growing microwave networks in the future information society., Comment: 23 pages,3 figures

Continuous superradiance using a narrow optical transition has the potential to improve the short-term stability of state-of-the-art optical clocks. Even though pulsed superradiant emission on a mHz linewidth clock transition has been shown, true continuous operation, without Fourier limitation, has turned out to be extremely challenging. The trade-off between maintaining a high atomic flux while minimizing decoherence effects presents a significant obstacle. Here, we discuss the design of a machine that could overcome this problem by combining a high-flux continuous beam of ultra cold strontium atoms with a bowtie cavity for the generation of superradiant lasing. To evaluate the feasibility of our design, we present simulation results for continuous high-efficiency cooling, loading, and pumping to the upper lasing state inside the bowtie cavity. We then present two different models for stimulating the generated superradiant field by taking into account position-dependent shifts, collisional decoherence, light shifts, and atom loss. Finally, we estimate a laser linewidth of less than 100 mHz, limited by atom number fluctuations, and resulting in an output power of hundreds of fW., Comment: 20 pages, 9 figures

Despite advances in the development of quantum computers, the practical application of quantum algorithms remains outside the current range of so-called noisy intermediate-scale quantum devices. Now and beyond, quantum circuit compilation (QCC) is a crucial component of any quantum algorithm execution. Besides translating a circuit into hardware-specific gates, it can optimize circuit depth and adapt to noise. Variational quantum circuit compilation (VQCC) optimizes the parameters of an ansatz according to the goal of reproducing a given unitary transformation. In this work, we present a VQCC-objective function called the quantum Wasserstein compilation (QWC) cost function based on the quantum Wasserstein distance of order 1. We show that the QWC cost function is upper bound by the average infidelity of two circuits. An estimation method based on measurements of local Pauli-observable is utilized in a generative adversarial network to learn a given quantum circuit. We demonstrate the efficacy of the QWC cost function by compiling a single-layer hardware efficient ansatz (HEA) as both the target and the ansatz and comparing other cost functions such as the Loschmidt echo test (LET) and the Hilbert-Schmidt test (HST). Finally, our experiments demonstrate that QWC as a cost function can mitigate the barren plateaus for the particular problem we consider., Comment: 12 pages, 8 figures

Convolutional Neural Networks (CNNs) have made remarkable strides; however, they remain susceptible to vulnerabilities, particularly in the face of minor image perturbations that humans can easily recognize. This weakness, often termed as 'attacks', underscores the limited robustness of CNNs and the need for research into fortifying their resistance against such manipulations. This study introduces a novel Non-Uniform Illumination (NUI) attack technique, where images are subtly altered using varying NUI masks. Extensive experiments are conducted on widely-accepted datasets including CIFAR10, TinyImageNet, and CalTech256, focusing on image classification with 12 different NUI attack models. The resilience of VGG, ResNet, MobilenetV3-small and InceptionV3 models against NUI attacks are evaluated. Our results show a substantial decline in the CNN models' classification accuracy when subjected to NUI attacks, indicating their vulnerability under non-uniform illumination. To mitigate this, a defense strategy is proposed, including NUI-attacked images, generated through the new NUI transformation, into the training set. The results demonstrate a significant enhancement in CNN model performance when confronted with perturbed images affected by NUI attacks. This strategy seeks to bolster CNN models' resilience against NUI attacks.

The broad physics reach of the LUX-ZEPLIN (LZ) experiment covers rare phenomena beyond the direct detection of dark matter. We report precise measurements of the extremely rare decay of $^{124}$Xe through the process of two-neutrino double electron capture (2$\nu$2EC), utilizing a $1.39\,\mathrm{kg} \times \mathrm{yr}$ isotopic exposure from the first LZ science run. A half-life of $T_{1/2}^{2\nu2\mathrm{EC}} = (1.09 \pm 0.14_{\text{stat}} \pm 0.05_{\text{sys}}) \times 10^{22}\,\mathrm{yr}$ is observed with a statistical significance of $8.3\,\sigma$, in agreement with literature. First empirical measurements of the KK capture fraction relative to other K-shell modes were conducted, and demonstrate consistency with respect to recent signal models at the $1.4\,\sigma$ level., Comment: 15 pages, 3 figures

A one-size-fits-all paradigm that only adapts the scale and immediate outcome of climate investment to economic circumstances will provide a short-lived, economically inadequate response to climate issues; given the limited resources allocated to green finance, it stands to reason that the shortcomings of this will be exacerbated by the fact that it comes at the cost of long-term, self-perpetuating, systemic solutions. Financial commitments that do not consider the capital structure of green finance in an economy will cumulatively dis-aggregate the economic cost of climate investment, to erode the competitive advantage of the most innovative economies, while simultaneously imposing the greatest financial burden on economies that are most vulnerable to the impact of climate change; such disaggregation will also leave 'middle' economies in a state of flux - honouring similar financial commitments to vulnerable or highly developed peers, but unable to generate comparable return, yet sufficiently insulated from the impact of extreme climate phenomena to not organically develop solutions. In the face of these changing realities, green innovation needs to expand beyond technology and address systemic inefficiencies - lack of clear responsibility, ambiguously defined commitments, and inadequate checks & balances to name a few. Clever application of financial engineering demonstrates promise, and simple measures like carbon-credit exchanges have been effective in mitigating imperfections at the grassroots level. We believe that information- and incentive-centric systemic advancements can usher a fresh wave of green innovation that stands on the shoulders of giants to ensure effective implementation of technological breakthroughs; economic development that will create an international community equipped with a robust framework to deal with long-term crises in a strategic manner.

A direct observation of the deuteron-deuteron (DD) fusion reaction at thermal meV energies, although theoretically possible, is not succeeded up to now. The electron screening effect that reduces the repulsive Coulomb barrier between reacting nuclei in metallic environments by several hundreds of eV and is additionally increased by crystal lattice defects in the hosting material, leads to strongly enhanced cross sections which means that this effect might be studied in laboratories. Here we present results of the 2H(d,p)3H reaction measurements performed on a ZrD2 target down to the lowest deuteron energy in the center mass system of 675 eV, using an ultra-high vacuum accelerator system, recently upgraded to achieve high beam currents at very low energies. The experimental thick target yield, decreasing over seven orders of magnitude for lowering beam energies, could be well described by the electron screening energy of 340 eV, which is much higher than the value of about 100 eV for a defect free material. At the energies below 2.5 keV, a constant plateau yield value could be observed. As indicated by significantly increased energies of emitted protons, this effect can be associated with the thermal DD fusion. A theoretical model explains the experimental observations by creation of ion tracks induced in the target by projectiles, and a high phonon density which locally increases temperature above the melting point. The nuclear reaction rate taking into account recently observed DD threshold resonance agrees very well with the experimental data.

The discovery of a new, strong reaction channel of the deuteron-deuteron fusion at very low energies might have major consequences for the construction of a future clean and efficient energy source. Following the first theoretical and experimental indications for the existence of the deuteron-deuteron threshold resonance in the $^4$He nucleus and its dominant decay by the internal $e^+e^-$ pair creation, we present here an extensive experimental study confirming emission of high-energy electrons and positrons. A simultaneous use of Si charged particle detectors of different thicknesses and large volume NaI(Tl) and HPGe detectors has allowed for the first time to determine the branching ratio between emitted protons, neutrons and $e^+e^-$ pairs for deuteron energies down to 5 keV. The high-energy positrons could be unambiguously detected by their bremsstrahlung spectra and annihilation radiation, supported by the Monte Carlo Geant4 simulations. The theoretical calculations, based on a destructive interference between the threshold resonance and the known broad resonance in $^4$He, agree very well with experimentally observed increase of branching ratios for lowering projectile energies. The partial width of the threshold resonance for the $e^+e^-$ pair creation should be at least 10 times larger than that of the proton channel.

Since the dawn of scanning probe microscopy (SPM), tapping or intermittent contact mode has been one of the most widely used imaging modes. Manual optimization of tapping mode not only takes a lot of instrument and operator time, but also often leads to frequent probe and sample damage, poor image quality and reproducibility issues for new types of samples or inexperienced users. Despite wide use, optimization of tapping mode imaging is an extremely hard problem, ill-suited to either classical control methods or machine learning. Here we introduce a reward-driven workflow to automate the optimization of SPM in the tapping mode. The reward function is defined based on multiple channels with physical and empirical knowledge of good scans encoded, representing a sample-agnostic measure of image quality and imitating the decision-making logic employed by human operators. This automated workflow gives optimal scanning parameters for different probes and samples and gives high-quality SPM images consistently in the attractive mode. This study broadens the application and accessibility of SPM and opens the door for fully automated SPM., Comment: 20 pages, 6 figures

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

This paper introduces a Virtual Immunohistochemistry Multiplex staining (VIMs) model designed to generate multiple immunohistochemistry (IHC) stains from a single hematoxylin and eosin (H&E) stained tissue section. IHC stains are crucial in pathology practice for resolving complex diagnostic questions and guiding patient treatment decisions. While commercial laboratories offer a wide array of up to 400 different antibody-based IHC stains, small biopsies often lack sufficient tissue for multiple stains while preserving material for subsequent molecular testing. This highlights the need for virtual IHC staining. Notably, VIMs is the first model to address this need, leveraging a large vision-language single-step diffusion model for virtual IHC multiplexing through text prompts for each IHC marker. VIMs is trained on uniplex paired H&E and IHC images, employing an adversarial training module. Testing of VIMs includes both paired and unpaired image sets. To enhance computational efficiency, VIMs utilizes a pre-trained large latent diffusion model fine-tuned with small, trainable weights through the Low-Rank Adapter (LoRA) approach. Experiments on nuclear and cytoplasmic IHC markers demonstrate that VIMs outperforms the base diffusion model and achieves performance comparable to Pix2Pix, a standard generative model for paired image translation. Multiple evaluation methods, including assessments by two pathologists, are used to determine the performance of VIMs. Additionally, experiments with different prompts highlight the impact of text conditioning. This paper represents the first attempt to accelerate histopathology research by demonstrating the generation of multiple IHC stains from a single H&E input using a single model trained solely on uniplex data., Comment: Accepted to MICCAI Workshop 2024

We study unital $\infty$-operads by their arity restrictions. Given $k \geq 1$, we develop a model for unital $k$-restricted $\infty$-operads, which are variants of $\infty$-operads which has only $(\leq k)$-arity morphisms, as complete Segal presheaves on closed $k$-dendroidal trees, which are closed trees build from corollas with valences $\leq k$. Furthermore, we prove that the restriction functors from unital $\infty$-operads to unital $k$-restricted $\infty$-operads admit fully faithful left and right adjoints by showing that the left and right Kan extensions preserve complete Segal objects. Varying $k$, the left and right adjoints give a filtration and a co-filtration for any unital $\infty$-operads by $k$-restricted $\infty$-operads., Comment: 19 pages, comments are welcome

We present a measurement of $|V_{ub}|$ from a simultaneous study of the charmless semileptonic decays $B^0\to\pi^- \ell^+ \nu_{\ell}$ and $B^+\to\rho^0 \ell^+\nu_{\ell}$, where $\ell = e, \mu$. This measurement uses a data sample of 387 million $B\overline{B}$ meson pairs recorded by the Belle~II detector at the SuperKEKB electron-positron collider between 2019 and 2022. The two decays are reconstructed without identifying the partner $B$ mesons. We simultaneously measure the differential branching fractions of $B^0\to\pi^- \ell^+ \nu_{\ell}$ and $B^+\to\rho^0 \ell^+\nu_{\ell}$ decays as functions of $q^2$ (momentum transfer squared). From these, we obtain total branching fractions $B(B^0\to\pi^- \ell^+ \nu_{\ell}) = (1.516 \pm 0.042 (\mathrm{stat}) \pm 0.059 (\mathrm{syst})) \times 10^{-4}$ and $B(B^+\to\rho^0 \ell^+\nu_{\ell}) = (1.625 \pm 0.079 (\mathrm{stat}) \pm 0.180 (\mathrm{syst})) \times 10^{-4}$. By fitting the measured $B^0\to\pi^- \ell^+ \nu_{\ell}$ partial branching fractions as functions of $q^2$, together with constraints on the non-perturbative hadronic contribution from lattice QCD calculations, we obtain $|V_{ub}|$ = $(3.93 \pm 0.09 \pm 0.13 \pm 0.19) \times 10^{-3}$. Here, the first uncertainty is statistical, the second is systematic, and the third is theoretical.

Reward-based finetuning is crucial for aligning language policies with intended behaviors (e.g., creativity and safety). A key challenge here is to develop steerable language models that trade-off multiple (conflicting) objectives in a flexible and efficient manner. This paper presents Conditioned Language Policy (CLP), a general framework for finetuning language models on multiple objectives. Building on techniques from multi-task training and parameter-efficient finetuning, CLP can learn steerable models that effectively trade-off conflicting objectives at inference time. Notably, this does not require training or maintaining multiple models to achieve different trade-offs between the objectives. Through an extensive set of experiments and ablations, we show that the CLP framework learns steerable models that outperform and Pareto-dominate the current state-of-the-art approaches for multi-objective finetuning., Comment: 40 pages

Large language models (LLMs) have shown remarkable performance on many different Natural Language Processing (NLP) tasks. Prompt engineering plays a key role in adding more to the already existing abilities of LLMs to achieve significant performance gains on various NLP tasks. Prompt engineering requires composing natural language instructions called prompts to elicit knowledge from LLMs in a structured way. Unlike previous state-of-the-art (SoTA) models, prompt engineering does not require extensive parameter re-training or fine-tuning based on the given NLP task and thus solely operates on the embedded knowledge of LLMs. Additionally, LLM enthusiasts can intelligently extract LLMs' knowledge through a basic natural language conversational exchange or prompt engineering, allowing more and more people even without deep mathematical machine learning background to experiment with LLMs. With prompt engineering gaining popularity in the last two years, researchers have come up with numerous engineering techniques around designing prompts to improve accuracy of information extraction from the LLMs. In this paper, we summarize different prompting techniques and club them together based on different NLP tasks that they have been used for. We further granularly highlight the performance of these prompting strategies on various datasets belonging to that NLP task, talk about the corresponding LLMs used, present a taxonomy diagram and discuss the possible SoTA for specific datasets. In total, we read and present a survey of 44 research papers which talk about 39 different prompting methods on 29 different NLP tasks of which most of them have been published in the last two years.

Monte Carlo tree search (MCTS) is one of the most capable online search algorithms for sequential planning tasks, with significant applications in areas such as resource allocation and transit planning. Despite its strong performance in real-world deployment, the inherent complexity of MCTS makes it challenging to understand for users without technical background. This paper considers the use of MCTS in transportation routing services, where the algorithm is integrated to develop optimized route plans. These plans are required to meet a range of constraints and requirements simultaneously, further complicating the task of explaining the algorithm's operation in real-world contexts. To address this critical research gap, we introduce a novel computation tree logic-based explainer for MCTS. Our framework begins by taking user-defined requirements and translating them into rigorous logic specifications through the use of language templates. Then, our explainer incorporates a logic verification and quantitative evaluation module that validates the states and actions traversed by the MCTS algorithm. The outcomes of this analysis are then rendered into human-readable descriptive text using a second set of language templates. The user satisfaction of our approach was assessed through a survey with 82 participants. The results indicated that our explanatory approach significantly outperforms other baselines in user preference., Comment: Accepted by the Proceedings of the 27th European Conference on Artificial Intelligence (ECAI)

We report measurements of time-dependent $CP$ asymmetries in $B^0 \to K^0_S \pi^0 \gamma$ decays based on a data sample of $(388\pm6)\times10^6$ $B\bar{B}$ events collected at the $\Upsilon(4S)$ resonance with the Belle II detector. The Belle II experiment operates at the SuperKEKB asymmetric-energy $e^+e^-$ collider. We measure decay-time distributions to determine $CP$-violating parameters $S$ and $C$. We determine these parameters for two ranges of $K^0_S \pi^0$ invariant mass: $m(K^0_S \pi^0)\in (0.8, 1.0)$ $GeV/c^2$, which is dominated by $B^0 \to K^{*0} (\to K^0_S \pi^0) \gamma$ decays, and a complementary region $m(K^0_S \pi^0)\in (0.6, 0.8)\cup(1.0, 1.8)$ $GeV/c^2$. Our results have improved precision as compared to previous measurements and are consistent with theory predictions., Comment: 10 pages, 4 figures

We present measurements of $B^{+}\rightarrow\rho^{+}\gamma$ and $B^{0}\rightarrow\rho^{0}\gamma$ decays using a combined data sample of $772 \times 10^6$ $B\overline{B}$ pairs collected by the Belle experiment and $387\times 10^6$ $B\overline{B}$ pairs collected by the Belle II experiment in $e^{+}e^{-}$ collisions at the $\Upsilon (4S)$ resonance. After an optimized selection, a simultaneous fit to the Belle and Belle II data sets yields $114\pm 12$ $B^{+}\rightarrow\rho^{+}\gamma$ and $99\pm 12$ $B^{0}\rightarrow\rho^{0}\gamma$ decays. The measured branching fractions are $(13.1^{+2.0 +1.3}_{-1.9 -1.2})\times 10^{-7}$ and $(7.5\pm 1.3^{+1.0}_{-0.8})\times 10^{-7}$ for $B^{+}\rightarrow\rho^{+}\gamma$ and $B^{0}\rightarrow\rho^{0}\gamma$ decays, respectively, where the first uncertainty is statistical and the second is systematic. We also measure the isospin asymmetry $A_{\rm I}(B\rightarrow\rho\gamma)=(10.9^{+11.2 +7.8}_{-11.7 -7.3})\%$ and the direct CP asymmetry $A_{CP}(B^{+}\rightarrow\rho^{+}\gamma)=(-8.2\pm 15.2^{+1.6}_{-1.2})\%$., Comment: 12 pages, 4 figures

We present a search for the baryon number $B$ and lepton number $L$ violating decays $\tau^- \rightarrow \Lambda \pi^-$ and $\tau^- \rightarrow \bar{\Lambda} \pi^-$ produced from the $e^+e^-\to \tau^+\tau^-$ process, using a 364 fb$^{-1}$ data sample collected by the Belle~II experiment at the SuperKEKB collider. No evidence of signal is found in either decay mode, which have $|\Delta(B-L)|$ equal to $2$ and $0$, respectively. Upper limits at 90\% credibility level on the branching fractions of $\tau^- \rightarrow \Lambda\pi^-$ and $\tau^- \rightarrow \bar{\Lambda}\pi^-$ are determined to be $4.7 \times 10^{-8}$ and $4.3 \times 10^{-8}$, respectively., Comment: 8 pages, 4 figures

We report the first evidence for the $h_{b}(\text{2P}) \to \Upsilon(\text{1S})\eta$ transition with a significance of $3.5$ standard deviations. The decay branching fraction is measured to be $\mathcal{B}[h_{b}(\text{2P}) \to \Upsilon(\text{1S})\eta]=(7.1 ~^{+3.7} _{-3.2}\pm 0.8)\times10^{-3}$, which is noticeably smaller than expected. We also set upper limits on $\pi^0$ transitions of $\mathcal{B}[h_{b}(\text{2P}) \to \Upsilon(\text{1S})\pi^0] < 1.8\times10^{-3}$, and $\mathcal{B}[h_{b}(\text{1P})\to \Upsilon(\text{1S})\pi^0] < 1.8\times10^{-3}$, at the $90\%$ confidence level. These results are obtained with a $131.4$~fb$^{-1}$ data sample collected near the $\Upsilon(\text{5S})$ resonance with the Belle detector at the KEKB asymmetric-energy $e^+e^-$ collider., Comment: to be submitted to PRL

In this paper we propose and analyse a new formulation and pointwise divergence-free mixed finite element methods for the numerical approximation of Darcy--Brinkman equations in vorticity--velocity--pressure form, coupled with a transport equation for thermal energy with viscous dissipative effect and mixed Navier-type boundary conditions. The solvability analysis of the continuous and discrete problems is significantly more involved than usual as it hinges on Banach spaces needed to properly control the advective and dissipative terms in the non-isothermal energy balance equation. We proceed by decoupling the set of equations and use the Banach fixed-point theorem in combination with the abstract theory for perturbed saddle-point problems. Some of the necessary estimates are straightforward modifications of well-known results, while other technical tools require a more elaborated analysis. The velocity is approximated by Raviart--Thomas elements, the vorticity uses N\'ed\'elec spaces of the first kind, the pressure is approximated by piecewise polynomials, and the temperature by continuous and piecewise polynomials of one degree higher than pressure. Special care is needed to establish discrete inf-sup conditions since the curl of the discrete vorticity is not necessarily contained in the discrete velocity space, therefore suggesting to use two different Raviart--Thomas interpolants. A discrete fixed-point argument is used to show well-posedness of the Galerkin scheme. Error estimates in appropriate norms are derived, and a few representative numerical examples in 2D and 3D and with mixed boundary conditions are provided.

Voluntary donation of private information for altruistic purposes, such as advancing research, is common. However, concerns about data misuse and leakage may deter individuals from donating their information. While prior research has indicated that Privacy Enhancement Technologies (PETs) can alleviate these concerns, the extent to which these techniques influence willingness to donate data remains unclear. This study conducts a vignette survey (N=485) to examine people's willingness to donate medical data for developing new treatments under four privacy guarantees: data expiration, anonymization, use restriction, and access control. The study explores two mechanisms for verifying these guarantees: self-auditing and expert auditing, and evaluates the impact on two types of data recipient entities: for-profit and non-profit institutions. Our findings reveal that the type of entity collecting data strongly influences respondents' privacy expectations, which in part influence their willingness to donate data. Respondents have such high expectations of the privacy provided by non-profit entities that explicitly stating the privacy protections provided makes little adjustment to those expectations. In contrast, statements about privacy bring respondents' expectations of the privacy provided by for-profit entities nearly in-line with non-profit expectations. We highlight the risks of these respective results as well as the need for future research to better align technical community and end-user perceptions about the effectiveness of auditing PETs and to effectively set expectations about the efficacy of PETs in the face of end-user concerns about data breaches.

A series of data samples was collected with the Belle~II detector at the SuperKEKB collider from March 2019 to June 2022. We determine the integrated luminosities of these data samples using three distinct methodologies involving Bhabha ($e^+e^- \to e^+e^-(n\gamma)$), digamma ($e^+e^- \to \gamma\gamma(n\gamma)$), and dimuon ($e^+e^- \to \mu^+ \mu^- (n\gamma)$) events. The total integrated luminosity obtained with Bhabha, digamma, and dimuon events is ({426.88} $\pm$ 0.03 $\pm$ {2.61})~fb$^{-1}$, ({429.28} $\pm$ 0.03 $\pm$ {2.62})~fb$^{-1}$, and ({423.99} $\pm$ 0.04 $\pm$ {3.83})~fb$^{-1}$, where the first uncertainties are statistical and the second are systematic. The resulting total integrated luminosity obtained from the combination of the three methods is ({427.87 $\pm$ 2.01})~fb$^{-1}$., Comment: 12 pages, 3 figures; accepted for publication in Chinese Physics C

We report a study of the hadronic transitions $\chi_{bJ}(2P)\to\omega\Upsilon(1S)$, with $\omega\to\pi^{+}\pi^{-}\pi^{0}$, using $28.2\times10^6~\Upsilon(3S)$ mesons recorded by the Belle detector. We present the first evidence for the near--threshold transition $\chi_{b0}(2P)\to\omega\Upsilon(1S)$, the analog of the charm sector decay $\chi_{c1}(3872)\to\omega J/\psi$, with a branching fraction of $B\big(\chi_{b0}(2P)\to\omega\Upsilon(1S)\big) = \big(0.55\pm0.19\pm0.07\big)\%$. We also obtain branching fractions of $B\big(\chi_{b1}(2P)\to\omega\Upsilon(1S)\big) = \big(2.39{}^{+0.20}_{-0.19}\pm0.24\big)\%$ and $B\big(\chi_{b2}(2P)\to\omega\Upsilon(1S)\big) = \big(0.47{}^{+0.13}_{-0.12}\pm0.06\big)\%$, confirming the measurement of the $\omega$ transitions of the $J=1,2~P$--wave states. The ratio for the $J=2$ to $J=1$ transitions is also measured and found to differ by 3.3 standard deviations from the expected value in the QCD multipole expansion., Comment: 6 pages, 2 figures

Terahertz (THz) magnonics represent the notion of mathematical algebraic operations of magnons such as addition and subtraction in THz regime which is an emergent dissipationless ultrafast alternative to existing data processing technologies. Spin waves on antiferromagnets with a twist in spin order host such magnons in THz regime, which possess advantage of higher processing speeds, additional polarization degree of freedom and longer propagation lengths compared to that of gigahertz magnons in ferromagnets. While interaction among THz magnons is the crux of algebra operations, it requires magnetic orders with closely spaced magnon modes for easier experimental realization of their interactions. Herein, rich wealth of magnons spanning a narrow energy range of 0.4 to 10 meV is unraveled in Co4Ta2O9 using magneto-THz spectroscopy. Rare multitude of ten excitation modes, either of magnons or hybrid magnon-phonon modes is presented. Among other attributes, spin lattice interaction suggests a correlation among spin and local lattice distortion, magnetostriction, and magnetic exchange interaction signifying a THz magnetoelectric effect. This unification of structural, magnetic and dielectric facets, and their magnetic field control in a narrow spectrum unwinds the mechanism underneath the system's complexity while the manifestation of multitude of spin excitation modes is a potential source to design multiple channels in spin-wave computing based devices.

The complexity of interactions between the crystal-field and unusual non-collinear spin arrangement in non-trivial magnets demands novel tools to unravel the mystery underneath. In this work, we study such interaction dynamics of crystal-field-excitations (CFE) and low-energy magnetic excitations in orthochromite TmCrO3 with controls of temperature and magnetic field using high-resolution magneto-terahertz (THz) time-domain spectroscopy. The THz energy spectrum spanning 0.5-10 meV possesses a low-frequency spin-excitation (magnon) mode and a multitude of CFE modes at 10 K, all of which uniquely embody a range of phenomena. For the magnon mode, a temperature dependence of peak frequency is induced by magnetic interactions between Tm and Cr subsystems. While a change from blue- to red-shift of peak frequency of this mode marks the magnetization reversal transition, the spin reorientation temperature and change of magnetic anisotropy are depicted by different features of field- and temperature-dependent peak frequency dynamics. The modes corresponding to CFE are robust and laden with a multitude of sub-modes which are attributes of non-trivial interactions across different transitions. These modes are suppressed only upon substitution of Tb3+ at Tm3+ site, which suggests a dominant role of single-ion anisotropy in controlling entire THz excitations spectra. Overall, this remarkable range of phenomena seen through the unique lens of all-optical THz tools provides deeper insights into the origin of magnetic phases in systems with complex interactions between rare-earth and transition metal ions and provides a multitude of a novel combination of closely spaced modes for emerging hybrid spin-wave computation., Comment: The main copy of the manuscript includes 21 pages with 7 figures

Recent efforts to scale Transformer models have demonstrated rapid progress across a wide range of tasks (Wei et al., 2022). However, fine-tuning these models for downstream tasks is expensive due to their large parameter counts. Parameter-efficient fine-tuning (PEFT) approaches have emerged as a viable alternative by allowing us to fine-tune models by updating only a small number of parameters. In this work, we propose a general framework for parameter efficient fine-tuning (PEFT), based on structured unrestricted-rank matrices (SURM) which can serve as a drop-in replacement for popular approaches such as Adapters and LoRA. Unlike other methods like LoRA, SURMs provides more flexibility in finding the right balance between compactness and expressiveness. This is achieved by using low displacement rank matrices (LDRMs), which hasn't been used in this context before. SURMs remain competitive with baselines, often providing significant quality improvements while using a smaller parameter budget. SURMs achieve 5-7% accuracy gains on various image classification tasks while replacing low-rank matrices in LoRA. It also results in up to 12x reduction of the number of parameters in adapters (with virtually no loss in quality) on the GLUE benchmark., Comment: Work in progress

We theoretically investigate the trARPES spectrum and optical Hall conductivity in periodically driven twisted bilayer graphene, considering both steady-state and "projected" occupations of the Floquet state. In periodically driven pre-thermalized systems, steady-state occupation of Floquet states is predicted to occur when coupled to a bath, while these states have projected occupation instantaneously after the driving starts. We study how these two regimes can give markedly different responses in optical transport properties. In particular, our results show that steady-state occupation leads to near-quantized optical Hall conductivity for a range of driving parameters in twisted bilayer graphene, whereas projected occupation leads to non-quantized values. We discuss the experimental feasibility of probing such non-equilibrium states in twisted bilayer graphene., Comment: 14 pages, comments are welcome

Machine unlearning is the process of efficiently removing the influence of a training data instance from a trained machine learning model without retraining it from scratch. A popular subclass of unlearning approaches is exact machine unlearning, which focuses on techniques that explicitly guarantee the removal of the influence of a data instance from a model. Exact unlearning approaches use a machine learning model in which individual components are trained on disjoint subsets of the data. During deletion, exact unlearning approaches only retrain the affected components rather than the entire model. While existing approaches reduce retraining costs, it can still be expensive for an organization to retrain a model component as it requires halting a system in production, which leads to service failure and adversely impacts customers. To address these challenges, we introduce an exact unlearning framework -- Sequence-aware Sharded Sliced Training (S3T), designed to enhance the deletion capabilities of an exact unlearning system while minimizing the impact on model's performance. At the core of S3T, we utilize a lightweight parameter-efficient fine-tuning approach that enables parameter isolation by sequentially training layers with disjoint data slices. This enables efficient unlearning by simply deactivating the layers affected by data deletion. Furthermore, to reduce the retraining cost and improve model performance, we train the model on multiple data sequences, which allows S3T to handle an increased number of deletion requests. Both theoretically and empirically, we demonstrate that S3T attains superior deletion capabilities and enhanced performance compared to baselines across a wide range of settings., Comment: Work in Progress

It is still under intensive discussion, how magnetoelectric coupling actually occurs at the atomic scale in multiferroic BiFeO3. Nuclear solid-state techniques monitor local fields at the atomic scale. Using such an approach, we show that, contrary to our own expectation, ferroelectric and magnetic ordering in bismuth ferrite (BiFeO3 or BFO) decouple at the unit-cell level. Time differential perturbed angular correlation (TDPAC) data at temperatures below, close, and above the magnetic N\'eel temperature show that the coupling of the ferroelectric order to magnetization is completely absent at the bismuth site. It is common understanding that the antiferromagnetic order and the cycloidal ordering due to the Dzyaloshinskii-Moriya interaction generate a net zero magnetization of the sample cancelling any magnetoelectric effect at the macroscopic level. Our previous data show that a very large coupling of magnetic moment and electrical distortions arises on the magnetic sub-lattice (Fe-site). The oxygen octahedra around the iron site experience a large tilt due to the onset of magnetic ordering. Nevertheless, the Bi-containing complementary sub-lattice carrying the ferroelectric order is practically unaffected by this large structural change in its direct vicinity. The magnetoelectric coupling thus vanishes already at the unit cell level. These experimental results agree well with an ab-initio density functional theory (DFT) calculation., Comment: 23 pages, 14 figures

We search for excited charmed baryons in the $\Lambda_c^+\eta$ system using a data sample corresponding to an integrated luminosity of 980 $\rm fb^{-1}$. The data were collected by the Belle detector at the KEKB $e^{+}$$e^{-}$ asymmetric-energy collider. No significant signals are found in the $\Lambda_c^+\eta$ mass spectrum, including the known $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$. Clear $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ signals are observed in the $pD^0$ mass spectrum. We set upper limits at 90\% credibility level on ratios of branching fractions of $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ decaying to $\Lambda_c^+\eta$ relative to $\Sigma_c(2455)\pi$ of $<0.13$ for the $\Lambda_c(2880)^+$ and $<1.11$ for the $\Lambda_c(2940)^+$. We measure ratios of branching fractions of $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ decaying to $pD^0$ relative to $\Sigma_c(2455)\pi$ of $0.75 \pm 0.03(\text{stat.}) \pm 0.07(\text{syst.})$ for the $\Lambda_c(2880)^+$ and $3.59 \pm 0.21(\text{stat.}) \pm 0.56(\text{syst.})$ for the $\Lambda_c(2940)^+$., Comment: 10 pages, 4 figures, accepted for publication as a Regular Article in Physical Review D

We present a new class of fast polylog-linear algorithms based on the theory of structured matrices (in particular low displacement rank) for integrating tensor fields defined on weighted trees. Several applications of the resulting fast tree-field integrators (FTFIs) are presented, including (a) approximation of graph metrics with tree metrics, (b) graph classification, (c) modeling on meshes, and finally (d) Topological Transformers (TTs) (Choromanski et al., 2022) for images. For Topological Transformers, we propose new relative position encoding (RPE) masking mechanisms with as few as three extra learnable parameters per Transformer layer, leading to 1.0-1.5%+ accuracy gains. Importantly, most of FTFIs are exact methods, thus numerically equivalent to their brute-force counterparts. When applied to graphs with thousands of nodes, those exact algorithms provide 5.7-13x speedups. We also provide an extensive theoretical analysis of our methods., Comment: Preprint. Comments welcome

In the era of state-of-the-art space-borne telescopes, high-resolution ground-based observation has emerged as a crucial method for characterizing exoplanets, providing essential insights into their atmospheric compositions. In the optical and NIR regions, high-resolution spectroscopy has been powerful for hot Jupiters (HJ) and ultra-hot Jupiters (UHJ) during their primary transits, as it can probe molecules with better sensitivity. Here, we focus on a comparative simulation study of WASP-76 b (UHJ) and WASP-77 A b (HJ) for different number of transits, utilizing three ground-based spectrographs (GIANO-B (TNG), CARMENES (CAHA), and ANDES (E-ELT)) with varying instrumental parameters, spectral coverages, and resolutions. We aim to evaluate the feasibility of the upcoming ground-based European Extremely Large Telescope (E-ELT) in probing molecules from planet atmospheres and how it surpasses other ground-based observatories in terms of detectability. With the 1-D model, petitCODE, we have self-consistently simulated the atmospheric pressure-temperature profiles, which are subsequently integrated into the 1-D chemical kinetics model, VULCAN, to evolve the atmospheric chemistry. High-resolution spectra are obtained by performing line-by-line radiative transfer using petitRADTRANS. Finally, we use the resulting spectra to assess the detectability (sigma_det) of molecular bands, employing the ground-based noise simulator SPECTR. Utilizing cross-correlation spectroscopy, we have successfully demonstrated the robust consistency between our simulation study and real-time observations for both planets. ANDES excels overall in molecular detection due to its enhanced instrumental architecture, reinforcing E-ELT's importance for studying exoplanet atmospheres. Additionally, our theoretical simulations predict the detection of CO, NH3, and H2S on WASP-76 b atmosphere with a sigma_det> 3., Comment: Accepted for publication in the Astrophysical Journal; 25 pages (18 figures and 4 tables)

Air pollution kills 7 million people annually. The brick manufacturing industry accounts for 8%-14% of air pollution in the densely populated Indo-Gangetic plain. Due to the unorganized nature of brick kilns, policy violation detection, such as proximity to human habitats, remains challenging. While previous studies have utilized computer vision-based machine learning methods for brick kiln detection from satellite imagery, they utilize proprietary satellite data and rarely focus on compliance with government policies. In this research, we introduce a scalable framework for brick kiln detection and automatic compliance monitoring. We use Google Maps Static API to download the satellite imagery followed by the YOLOv8x model for detection. We identified and hand-verified 19579 new brick kilns across 9 states within the Indo-Gangetic plain. Furthermore, we automate and test the compliance to the policies affecting human habitats, rivers and hospitals. Our results show that a substantial number of brick kilns do not meet the compliance requirements. Our framework offers a valuable tool for governments worldwide to automate and enforce policy regulations for brick kilns, addressing critical environmental and public health concerns., Comment: The PI was not in favor of making the work public on arXiv as the content is not yet ready to be released

Stochastic resetting has emerged as a useful strategy to reduce the completion time for a broad class of first passage processes. In the canonical setup, one intermittently resets a given system to its initial configuration only to start afresh and continue evolving in time until the target goal is met. This is, however, an instantaneous process and thus less feasible for any practical purposes. A crucial generalization in this regard is to consider a finite-time return process which has significant ramifications to the first passage properties. Intriguingly, it has recently been shown that for diffusive search processes, returning in finite but stochastic time can gain significant speed-up over the instantaneous resetting process. Unlike diffusion which has a diverging mean completion time, in this paper, we ask whether this phenomena can also be observed for a first passage process with finite mean completion time. To this end, we explore the set-up of a classical drift-diffusive search process in one dimension with stochastic resetting and further assume that the return phase is modulated by a potential $U(x)=\lambda |x|$ with $\lambda>0$. For this process, we compute the mean first passage time exactly and underpin its characteristics with respect to the resetting rate and potential strength. We find a unified phase space that allows us to explore and identify the system parameter regions where stochastic return supersedes over both the underlying process and the process under instantaneous resetting. Furthermore and quite interestingly, we find that for a range of parameters the mean completion time under stochastic return protocol can be reduced further than the \textit{optimally restarted} instantaneous processes. We thus believe that resetting with stochastic returns can serve as a better optimization strategy owing to its dominance over classical first passage under resetting., Comment: Preliminary version