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In this paper, we introduce a new class of score-based generative models (SGMs) designed to handle high-cardinality data distributions by leveraging concepts from mean-field theory. We present mean-field chaos diffusion models (MF-CDMs), which address the curse of dimensionality inherent in high-cardinality data by utilizing the propagation of chaos property of interacting particles. By treating high-cardinality data as a large stochastic system of interacting particles, we develop a novel score-matching method for infinite-dimensional chaotic particle systems and propose an approximation scheme that employs a subdivision strategy for efficient training. Our theoretical and empirical results demonstrate the scalability and effectiveness of MF-CDMs for managing large high-cardinality data structures, such as 3D point clouds.

This paper studies performative risk minimization, a formulation of stochastic optimization under decision-dependent distributions. We consider the general case where the performative risk can be non-convex, for which we develop efficient parameter-free optimistic optimization-based methods. Our algorithms significantly improve upon the existing Lipschitz bandit-based method in many aspects. In particular, our framework does not require knowledge about the sensitivity parameter of the distribution map and the Lipshitz constant of the loss function. This makes our framework practically favorable, together with the efficient optimistic optimization-based tree-search mechanism. We provide experimental results that demonstrate the numerical superiority of our algorithms over the existing method and other black-box optimistic optimization methods.

We report recent progress in data analysis on the two point correlation functions which will be prerequisite to obtain semileptonic form factors for the $B_{(s)} \to D_{(s)}\ell\nu$ decays. We use a MILC HISQ ensemble for the measurement. We use the HISQ action for light quarks, and the Oktay-Kronfeld (OK) action for the heavy quarks ($b$ and $c$). We used a sequential Bayesian method for the data analysis. Here we test the new fitting methodology of Benjamin J.~Choi in a completely independent manner., Comment: 9 pages, 7 figures, Lattice 2023 proceedings

We present recent progress in calculating the semileptonic form factors $h_{A_1}(w)$ for the $\bar{B} \to D^{\ast} \ell \bar{\nu}$ decays. We use the Oktay-Kronfeld (OK) action for the charm and bottom valence quarks and the HISQ action for light quarks. We adopt the Newton method combined with the scanning method to find a good initial guess for the $\chi^2$ minimizer in the fitting of the 2pt correlation functions. The main advantage is that the Newton method lets us to consume all the time slices allowed by the physical positivity. We report the first, reliable, but preliminary results for $h_{A_1}(w)/\rho_{A_1}$ at zero recoil ($w=1$). Here we use a MILC HISQ ensemble ($a = 0.12$ fm, $M_{\pi}$ = 220 MeV, and $N_f = 2 + 1 + 1$ flavors)., Comment: 9 pages, 3 figures, Lattice 2023 proceeding

We present a summary of the full calculation of the axial, scalar and tensor flavor diagonal charges of the nucleon carried out using Wilson-clover fermions on eight ensembles generated using 2+1+1-flavors of highly improved staggered quarks (HISQ) by the MILC collaboration. We also give results for the $3\times 3$ matrix of renormalization factors between the RI-sMOM and $\overline{\rm MS}$ scheme for the 2+1 flavor theory that include flavor mixing. Preliminary results for $g_{A,S,T}^{u,d,s}$ are presented in the $\overline{\rm MS}$ scheme at scale 2 GeV., Comment: 9 pages, 9 figures, Contribution to the 40th International Symposium on Lattice Field Theory (Lattice 2023)

We present non-perturbative lattice calculations of the low-lying meson and baryon spectrum of the SU(4) gauge theory with fundamental fermion constituents. This theory is one instance of stealth dark matter, a class of strongly coupled theories, where the lowest mass stable baryon is the dark matter candidate. This work constitutes the first milestone in the program to study stealth dark matter self-interactions. Here, we focus on reducing excited state contamination in the single baryon channel by applying the Laplacian Heaviside method, as well as projecting our baryon operators onto the irreducible representations of the octahedral group. We compare our resulting spectrum to previous work involving Gaussian smeared non-projected operators and find good agreement with reduced statistical uncertainties. We also present the spectrum of the low-lying odd-parity baryons for the first time., Comment: 19 pages, 9 figures

We report recent progress on $\varepsilon_K$ evaluated directly from the standard model (SM) with lattice QCD inputs such as $\hat{B}_K$, $|V_{cb}|$, $|V_{us}|$, $|V_{ud}|$, $\xi_0$, $\xi_2$, $\xi_\text{LD}$, $f_K$, and $m_c$. We find that the standard model with exclusive $|V_{cb}|$ and lattice QCD inputs describes only 66\% of the experimental value of $|\varepsilon_K|$ and does not explain its remaining 34\%, which corresponds to a strong tension in $|\varepsilon_K|$ at the $4.9\sigma \sim 3.9\sigma$ level between the SM theory and experiment. We also find that this tension disappears when we use the inclusive value of $|V_{cb}|$ obtained using the heavy quark expansion based on the QCD sum rule approach., Comment: 11 pages, 8 tables, 4 figures, Lattice 2023 proceedings. arXiv admin note: substantial text overlap with arXiv:2301.12375, arXiv:2202.11473. references are added

Recent advances in generative diffusion models have enabled text-controlled synthesis of realistic and diverse images with impressive quality. Despite these remarkable advances, the application of text-to-image generative models in computer vision for standard visual recognition tasks remains limited. The current de facto approach for these tasks is to design model architectures and loss functions that are tailored to the task at hand. In this paper, we develop a unified language interface for computer vision tasks that abstracts away task-specific design choices and enables task execution by following natural language instructions. Our approach involves casting multiple computer vision tasks as text-to-image generation problems. Here, the text represents an instruction describing the task, and the resulting image is a visually-encoded task output. To train our model, we pool commonly-used computer vision datasets covering a range of tasks, including segmentation, object detection, depth estimation, and classification. We then use a large language model to paraphrase prompt templates that convey the specific tasks to be conducted on each image, and through this process, we create a multi-modal and multi-task training dataset comprising input and output images along with annotated instructions. Following the InstructPix2Pix architecture, we apply instruction-tuning to a text-to-image diffusion model using our constructed dataset, steering its functionality from a generative model to an instruction-guided multi-task vision learner. Experiments demonstrate that our model, dubbed InstructCV, performs competitively compared to other generalist and task-specific vision models. Moreover, it exhibits compelling generalization capabilities to unseen data, categories, and user instructions., Comment: ICLR 2024; Code is available at https://github.com/AlaaLab/InstructCV

Real-world graphs naturally exhibit hierarchical or cyclical structures that are unfit for the typical Euclidean space. While there exist graph neural networks that leverage hyperbolic or spherical spaces to learn representations that embed such structures more accurately, these methods are confined under the message-passing paradigm, making the models vulnerable against side-effects such as oversmoothing and oversquashing. More recent work have proposed global attention-based graph Transformers that can easily model long-range interactions, but their extensions towards non-Euclidean geometry are yet unexplored. To bridge this gap, we propose Fully Product-Stereographic Transformer, a generalization of Transformers towards operating entirely on the product of constant curvature spaces. When combined with tokenized graph Transformers, our model can learn the curvature appropriate for the input graph in an end-to-end fashion, without the need of additional tuning on different curvature initializations. We also provide a kernelized approach to non-Euclidean attention, which enables our model to run in time and memory cost linear to the number of nodes and edges while respecting the underlying geometry. Experiments on graph reconstruction and node classification demonstrate the benefits of generalizing Transformers to the non-Euclidean domain., Comment: 19 pages, 7 figures

For realistic talking head generation, creating natural head motion while maintaining accurate lip synchronization is essential. To fulfill this challenging task, we propose DisCoHead, a novel method to disentangle and control head pose and facial expressions without supervision. DisCoHead uses a single geometric transformation as a bottleneck to isolate and extract head motion from a head-driving video. Either an affine or a thin-plate spline transformation can be used and both work well as geometric bottlenecks. We enhance the efficiency of DisCoHead by integrating a dense motion estimator and the encoder of a generator which are originally separate modules. Taking a step further, we also propose a neural mix approach where dense motion is estimated and applied implicitly by the encoder. After applying the disentangled head motion to a source identity, DisCoHead controls the mouth region according to speech audio, and it blinks eyes and moves eyebrows following a separate driving video of the eye region, via the weight modulation of convolutional neural networks. The experiments using multiple datasets show that DisCoHead successfully generates realistic audio-and-video-driven talking heads and outperforms state-of-the-art methods. Project page: https://deepbrainai-research.github.io/discohead/, Comment: Accepted to ICASSP 2023

We present recent updates for $\varepsilon_K$ determined directly from the standard model (SM) with lattice QCD inputs such as $\hat{B}_K$, $|V_{cb}|$, $|V_{us}|$, $\xi_0$, $\xi_2$, $\xi_\text{LD}$, $f_K$, and $m_c$. We find that the standard model with exclusive $|V_{cb}|$ and other lattice QCD inputs describes only 65% of the experimental value of $|\varepsilon_K|$ and does not explain its remaining 35%, which leads to a strong tension in $|\varepsilon_K|$ at the $5.1\sigma \sim 3.9\sigma$ level between the SM theory and experiment. We also find that this tension disappears when we use the inclusive value of $|V_{cb}|$ obtained using the heavy quark expansion based on the QCD sum rule approach, although this inclusive tension is small ($\approx 1.4\sigma$) but keeps increasing as time goes on., Comment: 10 pages, 6 figures, 8 tables, Lattice 2022 proceeding. arXiv admin note: substantial text overlap with arXiv:2202.11473, arXiv:1912.03024, acknowledgement updated

This talk provides an update on the calculation of matrix elements of flavor diagonal axial, scalar and tensor quark bilinear operators between the nucleon ground state. The simulations are done using Wilson-clover fermions on a sea of eight 2+1+1-flavor HISQ ensembles generated by the MILC collaboration. We discuss the signal in the sum of the connected and disconnected contributions for the up, down and strange quarks, control over fits to remove excited state contamination, and the simultaneous chiral-continuum fit used to extract the charges., Comment: 9 pages, 9 figures, Contribution to the 39th International Symposium on Lattice Field Theory (Lattice2022). arXiv admin note: text overlap with arXiv:2203.09584

This talk summarizes the progress made since Lattice 2021 in understanding and controlling the contributions of towers of multihadron excited states with mass gaps starting lower than of radial excitations, and in increasing our confidence in the extraction of ground state nucleon matrix elements. The most clear evidence for multihadron excited state contributions (ESC) is in axial/pseudoscalar form factors that are required to satisfy the PCAC relation between them. The talk examines the broader question--which and how many of the theoretically allowed positive parity states $N(\textbf p)\pi(-\textbf p)$, $N(\textbf 0)\pi(\textbf 0)\pi(\textbf 0)$, $N(\textbf p)\pi(\textbf 0)$, $N(\textbf 0)\pi(\textbf p),\ \ldots$ make significant contributions to a given nucleon matrix element? New data for the axial, electric and magnetic form factors are presented. They continue to show trends observed in Ref[1]. The N${}^2$LO $\chi$PT analysis of the ESC to the pion-nucleon sigma term, $\sigma_{\pi N}$, has been extended to include the $\Delta$ as an explicit degree of freedom [2]. The conclusion reached in Ref [3] that $N \pi$ and $N \pi \pi$ states each contribute about 10 MeV to $\sigma_{\pi N}$, and the consistency between the lattice result with $N \pi$ state included and the phenomenological estimate is not changed by this improvement., Comment: 10 pages, 5 figures. Talk presented at the 39th International Symposium on Lattice Field Theory (LATTICE2022) 8-3 August, 2022 Bonn, Germany. arXiv admin note: text overlap with arXiv:2203.05647

Contribution from the USQCD Collaboration to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021)., Comment: 27 pp. main text, 4 pp. appendices, 29 pp. references, 1 p. index

Asset allocation using reinforcement learning has advantages such as flexibility in goal setting and utilization of various information. However, existing asset allocation methods do not consider the following viewpoints in solving the asset allocation problem. First, State design without considering portfolio management and financial market characteristics. Second, Model Overfitting. Third, Model training design without considering the statistical structure of financial time series data. To solve the problem of the existing asset allocation method using reinforcement learning, we propose a new reinforcement learning asset allocation method. First, the state of the portfolio managed by the model is considered as the state of the reinforcement learning agent. Second, Monte Carlo simulation data are used to increase training data complexity to prevent model overfitting. These data can have different patterns, which can increase the complexity of the data. Third, Monte Carlo simulation data are created considering various statistical structures of financial markets. We define the statistical structure of the financial market as the correlation matrix of the assets constituting the financial market. We show experimentally that our method outperforms the benchmark at several test intervals.

Recently, the application of advanced machine learning methods for asset management has become one of the most intriguing topics. Unfortunately, the application of these methods, such as deep neural networks, is difficult due to the data shortage problem. To address this issue, we propose a novel approach using neural networks to construct a portfolio of exchange traded funds (ETFs) based on the financial statement data of their components. Although a number of ETFs and ETF-managed portfolios have emerged in the past few decades, the ability to apply neural networks to manage ETF portfolios is limited since the number and historical existence of ETFs are relatively smaller and shorter, respectively, than those of individual stocks. Therefore, we use the data of individual stocks to train our neural networks to predict the future performance of individual stocks and use these predictions and the portfolio deposit file (PDF) to construct a portfolio of ETFs. Multiple experiments have been performed, and we have found that our proposed method outperforms the baselines. We believe that our approach can be more beneficial when managing recently listed ETFs, such as thematic ETFs, of which there is relatively limited historical data for training advanced machine learning methods.

The finance industry has adopted machine learning (ML) as a form of quantitative research to support better investment decisions, yet there are several challenges often overlooked in practice. (1) ML code tends to be unstructured and ad hoc, which hinders cooperation with others. (2) Resource requirements and dependencies vary depending on which algorithm is used, so a flexible and scalable system is needed. (3) It is difficult for domain experts in traditional finance to apply their experience and knowledge in ML-based strategies unless they acquire expertise in recent technologies. This paper presents Shai-am, an ML platform integrated with our own Python framework. The platform leverages existing modern open-source technologies, managing containerized pipelines for ML-based strategies with unified interfaces to solve the aforementioned issues. Each strategy implements the interface defined in the core framework. The framework is designed to enhance reusability and readability, facilitating collaborative work in quantitative research. Shai-am aims to be a pure AI asset manager for solving various tasks in financial markets., Comment: 5 pages, 2 figures

We report our progress in data analysis on two-point correlation functions of the $B$ meson using sequential Bayesian method. The data set of measurement is obtained using the Oktay-Kronfeld (OK) action for the bottom quarks (valence quarks) and the HISQ action for the light quarks on the MILC HISQ lattices. We find that the old initial guess for the $\chi^2$ minimizer in the fitting code is poor enough to slow down the analysis somewhat. In order to find a better initial guess, we adopt the Newton method. We find that the Newton method provides a natural test to check whether the $\chi^2$ minimizer finds a local minimum or the global minimum, and it also reduces the number of iterations dramatically., Comment: 10 pages, 2 figures, 5 tables, Lattice 2021 proceeding

We summarize recent evidence, both from lattice QCD and chiral perturbation theory, that suggests that larger-than-expected excited-state contamination could be the reason for the tension between phenomenological determinations and previous direct lattice-QCD calculations of the pion--nucleon sigma term $\sigma_{\pi N}$. In addition, we extend the $\chi$PT analysis by calculating the corrections due to including the $\Delta(1232)$ resonance as an explicit degree of freedom. This correction is found to be small, thereby corroborating the excited-state effects found in the $\Delta$-less calculation and the result for $\sigma_{\pi N}$., Comment: Includes new analysis of $\Delta$ corrections to excited-state contamination. Contribution to the 10th International Workshop on Chiral Dynamics

This talk provides an update on the calculation of matrix elements of flavor diagonal axial, scalar and tensor quark bilinear operators between the nucleon ground state. The simulations are done using Wilson-clover fermions on a sea of eight 2+1+1-flavor HISQ ensembles generated by the MILC collaboration. We discuss the signal in the connected and disconnected contributions, calculation of the renormalization constants and mixing in the RI-sMOM scheme, and control over the simultaneous chiral-continuum-finite-volume fit used to extract the final charges., Comment: 9 pages 8 figures. Contribution to the 38th International Symposium on Lattice Field Theory, LATTICE2021 26th-30th July, 2021

The exponentially falling signal-to-noise ratio in all nucleon correlation functions, and the presence of towers of multihadron excited states with relatively small mass gaps makes extraction of matrix elements of various operators within the ground state nucleon challenging. Theoretically, the allowed positive parity states with the smallest mass gaps are the $N(\bm p)\pi(-\bm p)$, $N(\bm 0)\pi(\bm 0)\pi(\bm 0)$, $N(\bm p)\pi(\bm 0)$, $N(\bm 0)\pi(\bm p),\ \ldots$, states. A priori, the contribution of these states arises at one loop in chiral perturbation theory ($\chi$PT), however, in many cases the contributions are enhanced. In this talk, I will review four such cases: the correlation functions from which the axial form factors, electric and magnetic form factors, the $\Theta$-term contribution to neutron electric dipole moment (nEDM), and the pion-nucleon sigma term are extracted. Including appropriate multihadron states in the analysis can lead to significantly different results compared to standard analyses with the mass gaps taken from fits to 2-point functions. The $\chi$PT case for $N \pi$ states is the most clear in the axial/pseudoscalar form factors which need to satisfy the PCAC relation between them. Our analyses, supported by $\chi$PT, suggests similarly large effects in the calculations of the $\Theta$-term and the pion-nucleon sigma term that have significant phenomenological implications., Comment: 9 pages 6 figures. Contribution to the 38th International Symposium on Lattice Field Theory, LATTICE2021 26th-30th July, 2021

We present recent updates for $\varepsilon_K$ determined directly from the standard model (SM) with lattice QCD inputs such as $\hat{B}_K$, $|V_{cb}|$, $|V_{us}|$, $\xi_0$, $\xi_2$, $\xi_\text{LD}$, $f_K$, and $m_c$. We find that the standard model with exclusive $|V_{cb}|$ and other lattice QCD inputs describes only 66\% of the experimental value of $|\varepsilon_K|$ and does not explain its remaining 34\%, which leads to a strong tension in $|\varepsilon_K|$ at the $4.5\sigma \sim 3.7\sigma$ level between the SM theory and experiment. We also find that this tension disappears when we use the inclusive value of $|V_{cb}|$ obtained using the heavy quark expansion based on the QCD sum rule approach., Comment: 10 pages, 5 figures, Lattice 2021 proceedings, arXiv admin note: text overlap with arXiv:1912.03024, the referee's suggestions incorporated

We present our recent high precision calculations (Phys. Rev. D102 (2020) no.5, 054512 and JHEP 04 (2021) 044, JHEP 21 (2020) 004) of the first moment of nucleon isovector polarized, unpolarized and transversity distributions, i.e., momentum fraction, helicity and transversity moment, respectively. We use the standard method for the calculation of these moments (via matrix elements of twist two operators), and carry out a detailed analysis of the sources of systematic uncertainty, in particular of excited state contributions. Our calculations have been performed using two different lattice setups (Clover-on-HISQ and Clover-on-Clover), each with several ensembles. They give consistent results that are in agreement with global fit analyses., Comment: 9 pages, 4 figures, Proceedings of the 38th International Symposium on Lattice Field Theory, LATTICE2021

We present preliminary results for strange and charm contributions to nucleon charges and moments. The scalar, axial and tensor charges, and unpolarized first moments are calculated using clover-on-HISQ formulation and cover four lattice spacings, $a=\{0.06,0.09,0.12, 0.15\}$~fm, and three pion masses, $M_\pi=\{310,220,130\}$~MeV. The renormalization factors are calculated nonperturbatively using the RI-sMOM scheme. We carry out a chiral and continuum extrapolation to obtain physical results., Comment: Proceeding for LATTICE2021 conference

We present an analysis of the pion-nucleon $\sigma$-term, $\sigma_{\pi N}$, using six ensembles with 2+1+1-flavor highly improved staggered quark action generated by the MILC collaboration. The most serious systematic effect in lattice calculations of nucleon correlation functions is the contribution of excited states. We estimate these using chiral perturbation theory ($\chi$PT), and show that the leading contribution to the isoscalar scalar charge comes from N$\pi$ and N$\pi\pi$ states. Therefore, we carry out two analyses of lattice data to remove excited-state contamination, the standard one and a new one including N$\pi$ and N$\pi\pi$ states. We find that the standard analysis gives $\sigma_{\pi N} = 41.9(4.9)$ MeV, consistent with previous lattice calculations, while our preferred $\chi$PT-motivated analysis gives $\sigma_{\pi N} = 59.6(7.4)$ MeV, which is consistent with phenomenological values obtained using $\pi$N scattering data. Our data on one physical pion mass ensemble was crucial for exposing this difference, therefore, calculations on additional physical mass ensembles are needed to confirm our result and resolve the tension between lattice QCD and phenomenology., Comment: 15 pages, 9 figures (Updated to published version)

A variety of effective face-swap and face-reenactment methods have been publicized in recent years, democratizing the face synthesis technology to a great extent. Videos generated as such have come to be called deepfakes with a negative connotation, for various social problems they have caused. Facing the emerging threat of deepfakes, we have built the Korean DeepFake Detection Dataset (KoDF), a large-scale collection of synthesized and real videos focused on Korean subjects. In this paper, we provide a detailed description of methods used to construct the dataset, experimentally show the discrepancy between the distributions of KoDF and existing deepfake detection datasets, and underline the importance of using multiple datasets for real-world generalization. KoDF is publicly available at https://moneybrain-research.github.io/kodf in its entirety (i.e. real clips, synthesized clips, clips with adversarial attack, and metadata)., Comment: Accepted to ICCV 2021

We present high statistics results for the isovector nucleon charges and form factors using seven ensembles of 2+1-flavor Wilson-clover fermions. The axial and pseudoscalar form factors obtained on each ensemble satisfy the PCAC relation once the lowest energy $N\pi$ excited state is included in the spectral decomposition of the correlation functions used for extracting the ground state matrix elements. Similarly, we find evidence that the $N\pi\pi $ excited state contributes to the correlation functions with the vector current, consistent with the vector meson dominance model. The resulting form factors are consistent with the Kelly parameterization of the experimental electric and magnetic data. Our final estimates for the isovector charges are $g_{A}^{u-d} = 1.31(06)(05)_{sys}$, $g_{S}^{u-d} = 1.06(10)(06)_{sys}$, and $g_{T}^{u-d} = 0.95(05)(02)_{sys}$, where the first error is the overall analysis uncertainty and the second is an additional combined systematic uncertainty. The form factors yield: (i) the axial charge radius squared, ${\langle r_A^2 \rangle}^{u-d}=0.428(53)(30)_{sys}\ {\rm fm}^2$, (ii) the induced pseudoscalar charge, $g_P^\ast=7.9(7)(9)_{sys}$, (iii) the pion-nucleon coupling $g_{\pi {\rm NN}} = 12.4(1.2)$, (iv) the electric charge radius squared, ${\langle r_E^2 \rangle}^{u-d} = 0.85(12)(19)_{sys} \ {\rm fm}^2$, (v) the magnetic charge radius squared, ${\langle r_M^2 \rangle}^{u-d} = 0.71(19)(23)_{\rm sys} \ {\rm fm}^2$, and (vi) the magnetic moment $\mu^{u-d} = 4.15(22)(10)_{\rm sys}$. All our results are consistent with phenomenological/experimental values but with larger errors. Lastly, we present a Pad\'e parameterization of the axial, electric and magnetic form factors over the range $0.04< Q^2 <1$ GeV${}^2$ for phenomenological studies., Comment: 84 pages, 39 figures, 24 tables. This is the version published by PRD

High statistics results for the isovector momentum fraction, $\langle x \rangle_{u-d}$, helicity moment, $\langle x \rangle_{\Delta u-\Delta d}$, and the transversity moment, $\langle x\rangle_{\delta u-\delta d}$, of the nucleon are presented using seven ensembles of gauge configurations generated by the JLab/W&M/LANL/MIT collaborations using $2+1$-flavors of dynamical Wilson-clover quarks. Attention is given to understanding and controlling the contributions of excited states. The final results are obtained using a simultaneous fit in the lattice spacing $a$, pion mass $M_\pi$ and the finite volume parameter $M_\pi L$ keeping leading order corrections. The data show no significant dependence on the lattice spacing and some evidence for finite-volume corrections. The main variation is with $M_\pi$, whose magnitude depends on the mass gap of the first excited state used in the analysis. Our final results, in the $\overline{\rm MS}$ scheme at 2 GeV, are $\langle x \rangle_{u-d} = 0.160(16)(20)$, $\langle x \rangle_{\Delta u-\Delta d} = 0.192(13)(20)$ and $\langle x \rangle_{\delta u-\delta d} = 0.215(17)(20)$, where the first error is the overall analysis uncertainty assuming excited-state contributions have been removed, and the second is an additional systematic uncertainty due to possible residual excited-state contributions. These results are consistent with other recent lattice calculations and phenomenological global fit values., Comment: 28 pages, 11 figures, 12 tables. arXiv admin note: text overlap with arXiv:2005.13779

We present results on the isovector momentum fraction, $\langle x \rangle_{u-d}$, helicity moment, $\langle x \rangle_{\Delta u-\Delta d}$, and the transversity moment, $\langle x \rangle_{\delta u-\delta d}$, of the nucleon obtained using nine ensembles of gauge configurations generated by the MILC collaboration using $2+1+1$-flavors of dynamical highly improved staggered quarks (HISQ). The correlation functions are calculated using the Wilson-Clover action and the renormalization of the three operators is carried out nonperturbatively on the lattice in the RI${}^\prime$-MOM scheme. The data have been collected at lattice spacings $a \approx 0.15,\ 0.12,\ 0.09,$ and 0.06 fm and $M_\pi \approx 310,\ 220$ and 135 MeV, which are used to obtain the physical values using a simultaneous chiral-continuum-finite-volume fit. The final results, in the $\overline{MS}$ scheme at 2 GeV, are $\langle x \rangle_{u-d} = 0.173(14)(07)$, $\langle x \rangle_{\Delta u-\Delta d} = 0.213(15)(22)$ and $\langle x \rangle_{\delta u-\delta d} = 0.208(19)(24)$, where the first error is the overall analysis uncertainty and the second is an additional systematic uncertainty due to possible residual excited-state contributions. These results are consistent with other recent lattice calculations and phenomenological global fit values., Comment: 18 pages, 8 figures. Final published version

We report recent progress in calculating semileptonic form factors for the $\bar{B} \to D^\ast \ell \bar{\nu}$ and $\bar{B} \to D \ell \bar{\nu}$ decays using the Oktay-Kronfeld (OK) action for bottom and charm quarks. We use the second order in heavy quark effective power counting $\mathcal{O}(\lambda^2)$ improved currents in this work. The HISQ action is used for the light spectator quarks. We analyzed four $2+1+1$-flavor MILC HISQ ensembles with $a\approx 0.09\,\mathrm{fm}$, $0.12\,\mathrm{fm}$ and $M_\pi \approx 220\,\mathrm{MeV}$, $310\,\mathrm{MeV}$: $a09m220$, $a09m310$, $a12m220$, $a12m310$. Preliminary results for $B\to D^\ast\ell\nu$ decays form factor $h_{A_1}(w)$ at zero recoil ($w=1$) are reported. Preliminary results for $B \to D\,\ell\nu$ decays form factors $h_\pm(w)$ over a kinematic range $1

We present recent progress in the lattice calculation of leptonic decay constants for $B_{(s)}$ and $D_{(s)}$ mesons using the Oktay-Kronfeld (OK) action for charm and bottom valence quarks, whose masses are tuned non-perturbatively. The calculations are done on 6 HISQ ensembles generated by the MILC collaboration with $N_f=2+1+1$ flavors. We also use the HISQ action for the light spectator quarks. Results are presented for the ratios $f_{B_s}/f_B$ and $f_{D_s}/f_D$, which reflect $SU(3)$ flavor symmetry breaking, and are independent of the renormalization constants of the axial currents., Comment: 7 pages, 10 figures, Lattice 2019 proceeding