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Accurately generating images of human bodies from text remains a challenging problem for state of the art text-to-image models. Commonly observed body-related artifacts include extra or missing limbs, unrealistic poses, blurred body parts, etc. Currently, evaluation of such artifacts relies heavily on time-consuming human judgments, limiting the ability to benchmark models at scale. We address this by proposing BodyMetric, a learnable metric that predicts body realism in images. BodyMetric is trained on realism labels and multi-modal signals including 3D body representations inferred from the input image, and textual descriptions. In order to facilitate this approach, we design an annotation pipeline to collect expert ratings on human body realism leading to a new dataset for this task, namely, BodyRealism. Ablation studies support our architectural choices for BodyMetric and the importance of leveraging a 3D human body prior in capturing body-related artifacts in 2D images. In comparison to concurrent metrics which evaluate general user preference in images, BodyMetric specifically reflects body-related artifacts. We demonstrate the utility of BodyMetric through applications that were previously infeasible at scale. In particular, we use BodyMetric to benchmark the generation ability of text-to-image models to produce realistic human bodies. We also demonstrate the effectiveness of BodyMetric in ranking generated images based on the predicted realism scores.

Traffic flow prediction is a big challenge for transportation authorities as it helps plan and develop better infrastructure. State-of-the-art models often struggle to consider the data in the best way possible, as well as intrinsic uncertainties and the actual physics of the traffic. In this study, we propose a novel framework to incorporate travel times between stations into a weighted adjacency matrix of a Graph Neural Network (GNN) architecture with information from traffic stations based on their data availability. To handle uncertainty, we utilized the Adaptive Conformal Prediction (ACP) method that adjusts prediction intervals based on real-time validation residuals. To validate our results, we model a microscopic traffic scenario and perform a Monte-Carlo simulation to get a travel time distribution for a Vehicle Under Test (VUT), and this distribution is compared against the real-world data. Experiments show that the proposed model outperformed the next-best model by approximately 24% in MAE and 8% in RMSE and validation showed the simulated travel time closely matches the 95th percentile of the observed travel time value., Comment: This manuscript has been accepted at the IEEE International Transportation Systems Conference (ITSC) 2024 which will be held September 24- 27, 2024 in Edmonton, Canada

We develop new approximate compilation schemes that significantly reduce the expense of compiling the Quantum Approximate Optimization Algorithm (QAOA) for solving the Max-Cut problem. Our main focus is on compilation with trapped-ion simulators using Pauli-$X$ operations and all-to-all Ising Hamiltonian $H_\text{Ising}$ evolution generated by Molmer-Sorensen or optical dipole force interactions, though some of our results also apply to standard gate-based compilations. Our results are based on principles of graph sparsification and decomposition; the former reduces the number of edges in a graph while maintaining its cut structure, while the latter breaks a weighted graph into a small number of unweighted graphs. Though these techniques have been used as heuristics in various hybrid quantum algorithms, there have been no guarantees on their performance, to the best of our knowledge. This work provides the first provable guarantees using sparsification and decomposition to improve quantum noise resilience and reduce quantum circuit complexity. For quantum hardware that uses edge-by-edge QAOA compilations, sparsification leads to a direct reduction in circuit complexity. For trapped-ion quantum simulators implementing all-to-all $H_\text{Ising}$ pulses, we show that for a $(1-\epsilon)$ factor loss in the Max-Cut approximation ($\epsilon>0)$, our compilations improve the (worst-case) number of $H_\text{Ising}$ pulses from $O(n^2)$ to $O(n\log(n/\epsilon))$ and the (worst-case) number of Pauli-$X$ bit flips from $O(n^2)$ to $O\left(\frac{n\log(n/\epsilon)}{\epsilon^2}\right)$ for $n$-node graphs. We demonstrate significant reductions in noise are obtained in our new compilation approaches using theory and numerical calculations for trapped-ion hardware. We anticipate these approximate compilation techniques will be useful tools in a variety of future quantum computing experiments.

In this paper we determine the masses of $I(J^P)=0\left(3/2^+\right)$ and $0\left(3/2^-\right)$ $\Omega$-baryon ground states using lattice QCD. We utilise Wilson-clover ensembles with $2+1$ dynamical quark flavours generated by the CLS consortium along a trajectory with a constant trace of the quark-mass matrix. We show that N$^3$LO $\text{SU}(3)_f$ chiral perturbation theory expressions describe the ground-state masses with positive-parity well, and we use them to set the lattice scale. Methodologically, our combination of gauge-fixed wall sources and the generalized Pencil of Functions allows for high-precision determinations of the lattice spacing at a relative error of around $0.3\%$ with controlled excited-state contamination. The fit we perform allows for the continuum value of $t_0$ to vary, thereby determining this quantity with a comparable level of precision to that of the lattice scale. Using the resulting scales our measurement of the negative-parity $\Omega^{3/2^{-}}$ state is found to be consistent with the recently-discovered $\Omega(2012)^-$, which can therefore be assigned the quantum numbers $I(J^P)=0\left(3/2^-\right)$., Comment: 29 pages, 7 figures

This work presents technical details of determining the finite-volume energy spectra for the scattering amplitude of the coupled-channel $\pi\Sigma - \bar{K}N$ from lattice QCD data. The importance of reliably extracting such spectra lies in the crucial dependence of the hadronic scattering amplitudes analysis on the energy spectrum when using L\"{u}scher's formalism. Results of the methods used are presented and the final finite-volume spectra are shown. The analysis of the scattering amplitude based on these results, exhibits a two-pole structure for the $\Lambda(1405)$, a virtual bound state below the $\pi\Sigma$ threshold and a resonance pole right below the $\bar{K}N$ threshold.

Recent results studying the masses and widths of low-lying baryon resonances in lattice QCD are presented. The $S$-wave $N\pi$ scattering lengths for both total isospins $I = 1/2$ and $I = 3/2$ are inferred from the finite-volume spectrum below the inelastic threshold together with the $I = 3/2$ $P$-wave containing the $\Delta(1232)$ resonance. A lattice QCD computation employing a combined basis of three-quark and meson-baryon interpolating operators with definite momentum to determine the coupled channel $\Sigma\pi$-$N\overline{K}$ scattering amplitude in the $\Lambda(1405)$ region is also presented. Our results support the picture of a two-pole structure suggested by theoretical approaches based on $SU(3)$ chiral symmetry and unitarity., Comment: 5 pages, 3 figures, talk presented at the 20th International Conference on Hadron Spectroscopy and Structure (HADRON 2023) in Genova, Italy, June 5th to 9th 2023

A lattice QCD computation of the coupled channel $\pi\Sigma-\bar{K}N$ scattering amplitudes in the $\Lambda(1405)$ region is detailed. Results are obtained using a single ensemble of gauge field configurations with $N_{\rm f} = 2+1$ dynamical quark flavors and $m_{\pi} \approx 200$ MeV and $m_K\approx487$ MeV. Hermitian correlation matrices using both single baryon and meson-baryon interpolating operators for a variety of different total momenta and irreducible representations are used. Several parametrizations of the two-channel scattering $K$-matrix are utilized to obtain the scattering amplitudes from the finite-volume spectrum. The amplitudes, continued to the complex energy plane, exhibit a virtual bound state below the $\pi\Sigma$ threshold and a resonance pole just below the $\bar{K}N$ threshold., Comment: 18 pages, 11 figures, 14 tables. Final version accepted for publication in PRD with post-publication corrections

This letter presents the first lattice QCD computation of the coupled channel $\pi\Sigma-\bar{K}N$ scattering amplitudes at energies near $1405\,{\rm MeV}$. These amplitudes contain the resonance $\Lambda(1405)$ with strangeness $S=-1$ and isospin, spin, and parity quantum numbers $I(J^P)=0(1/2^-)$. However, whether there is a single resonance or two nearby resonance poles in this region is controversial theoretically and experimentally. Using single-baryon and meson-baryon operators to extract the finite-volume stationary-state energies to obtain the scattering amplitudes at slightly unphysical quark masses corresponding to $m_\pi\approx200$ MeV and $m_K\approx487$ MeV, this study finds the amplitudes exhibit a virtual bound state below the $\pi\Sigma$ threshold in addition to the established resonance pole just below the $\bar{K}N$ threshold. Several parametrizations of the two-channel $K$-matrix are employed to fit the lattice QCD results, all of which support the two-pole picture suggested by $SU(3)$ chiral symmetry and unitarity., Comment: 7 pages, 4 figures, and 1 table. Includes various corrections made during the last stages before publication

We use $n_f=2+1$ Wilson-clover gauge-field ensembles from the CLS consortium in a Lattice NRQCD setup to predict the binding energy of a $I(J^P)=0(1^+)$ $ud\bar{b}\bar{b}$ tetraquark and a $\frac{1}{2}(1^+)$ $\ell s\bar{b}\bar{b}$ tetraquark. We determine the binding energies with respect to the relevant $BB^*$ and $B_sB^*$ thresholds respectively to be $112.0(13.2)$ MeV for the $ud\bar{b}\bar{b}$, and $46.4(12.3)$ MeV for the $\ell s\bar{b}\bar{b}$. We also determine the ground-state $J^P=0^+$ $B_{s0}^*$ and $1^+$ $B_{s1}$ mesons to lie $75.4(14.0)$ and $78.7(13.9)$ MeV below the $BK$ and $B^*K$ thresholds respectively. Our errors are entirely dominated by systematics due to discretisation effects. To achieve these measurements, we performed a neural network based nonperturbative tuning of the Lattice NRQCD Hamiltonian's parameters against the basic bottomonium spectrum. For all lattice spacings considered we can reproduce the continuum splittings of low-lying bottomonia. It is worth remarking that our nonperturbative tuning parameters deviate from 1 by significant amounts, particularly the term $c_2$., Comment: 48 pages, 16 figures

Recent data mining research has focused on the analysis of social media text, content and networks to identify suicide ideation online. However, there has been limited research on the temporal dynamics of users and suicide ideation. In this work, we use time-to-event modeling to identify which subreddits have a higher association with users transitioning to posting on r/suicidewatch. For this purpose we use a Cox proportional hazards model that takes as input text and subreddit network features and outputs a probability distribution for the time until a Reddit user posts on r/suicidewatch. In our analysis we find a number of statistically significant features that predict earlier transitions to r/suicidewatch. While some patterns match existing intuition, for example r/depression is positively associated with posting sooner on r/suicidewatch, others were more surprising (for example, the average time between a high risk post on r/Wishlist and a post on r/suicidewatch is 10.2 days). We then discuss these results as well as directions for future research.

Following the publication of the new measurement of the anomalous magnetic moment of the muon, the discrepancy between experiment and the theory prediction from the $g-2$ theory initiative has increased to $4.2\,\sigma$. Recent lattice QCD calculations predict values for the hadronic vacuum polarization contribution that are larger than the data-driven estimates, bringing the Standard Model prediction closer to the experimental measurement. Euclidean time windows in the time-momentum representation of the hadronic vacuum polarization contribution to the muon $g-2$ can help clarify the discrepancy between the phenomenological and lattice predictions. We present our calculation of the intermediate distance window contribution using $N_\mathrm{f}=2+1$ flavors of O$(a)$ improved Wilson quarks. We employ ensembles at six lattice spacings below $0.1\,$fm and pion masses down to the physical value. We present a detailed study of the continuum limit, using two discretizations of the vector current and two independent sets of improvement coefficients. Our result at the physical point displays a tension of $3.9\,\sigma$ with a recent evaluation of the intermediate window based on the data-driven method., Comment: 10 pages, 5 figures, Proceedings of the 39th International Symposium on Lattice Field Theory, 8th-13th August 2022, Bonn, Germany

Hawkes processes are point process models that have been used to capture self-excitatory behavior in social interactions, neural activity, earthquakes and viral epidemics. They can model the occurrence of the times and locations of events. Here we develop a new class of spatiotemporal Hawkes processes that can capture both triggering and clustering behavior and we provide an efficient method for performing inference. We use a log-Gaussian Cox process (LGCP) as prior for the background rate of the Hawkes process which gives arbitrary flexibility to capture a wide range of underlying background effects (for infectious diseases these are called endemic effects). The Hawkes process and LGCP are computationally expensive due to the former having a likelihood with quadratic complexity in the number of observations and the latter involving inversion of the precision matrix which is cubic in observations. Here we propose a novel approach to perform MCMC sampling for our Hawkes process with LGCP background, using pre-trained Gaussian Process generators which provide direct and cheap access to samples during inference. We show the efficacy and flexibility of our approach in experiments on simulated data and use our methods to uncover the trends in a dataset of reported crimes in the US., Comment: 8 Figures, 27 pages without references, 3 pages of references

To protect against naturally occurring or adversely induced congestion in the Internet, we propose the concept of flyover reservations, a fundamentally new approach for addressing the availability demands of critical low-volume applications. In contrast to path-based reservation systems, flyovers are fine-grained "hop-based" bandwidth reservations on the level of individual autonomous systems. We demonstrate the scalability of this approach experimentally through simulations on large graphs. Moreover, we introduce Helia, a protocol for secure flyover reservation setup and data transmission. We evaluate Helia's performance based on an implementation in DPDK, demonstrating authentication and forwarding of reservation traffic at 160 Gbps. Our security analysis shows that Helia can resist a large variety of powerful attacks against reservation admission and traffic forwarding. Despite its simplicity, Helia outperforms current state-of-the-art reservation systems in many key metrics.

Euclidean time windows in the integral representation of the hadronic vacuum polarization contribution to the muon $g-2$ serve to test the consistency of lattice calculations and may help in tracing the origins of a potential tension between lattice and data-driven evaluations. In this paper, we present results for the intermediate time window observable computed using O($a$) improved Wilson fermions at six values of the lattice spacings below 0.1\,fm and pion masses down to the physical value. Using two different sets of improvement coefficients in the definitions of the local and conserved vector currents, we perform a detailed scaling study which results in a fully controlled extrapolation to the continuum limit without any additional treatment of the data, except for the inclusion of finite-volume corrections. To determine the latter, we use a combination of the method of Hansen and Patella and the Meyer-Lellouch-L\"uscher procedure employing the Gounaris-Sakurai parameterization for the pion form factor. We correct our results for isospin-breaking effects via the perturbative expansion of QCD+QED around the isosymmetric theory. Our result at the physical point is $a_\mu^{\mathrm{win}}=(237.30\pm0.79_{\rm stat}\pm1.22_{\rm syst})\times10^{-10}$, where the systematic error includes an estimate of the uncertainty due to the quenched charm quark in our calculation. Our result displays a tension of 3.9$\sigma$ with a recent evaluation of $a_\mu^{\mathrm{win}}$ based on the data-driven method., Comment: 43 pages, 9 figures, 10 tables; version accepted for publication: extended discussion of finite-volume corrections. Results and conclusions unchanged

We generalize the Quantum Approximate Optimization Algorithm (QAOA) of Farhi et al. (2014) to allow for arbitrary separable initial states with corresponding mixers such that the starting state is the most excited state of the mixing Hamiltonian. We demonstrate this version of QAOA, which we call QAOA-warmest, by simulating Max-Cut on weighted graphs. We initialize the starting state as a warm-start using $2$ and $3$-dimensional approximations obtained using randomized projections of solutions to Max-Cut's semi-definite program, and define a warm-start dependent custom mixer. We show that these warm-starts initialize the QAOA circuit with constant-factor approximations of $0.658$ for $2$-dimensional and $0.585$ for $3$-dimensional warm-starts for graphs with non-negative edge weights, improving upon previously known trivial (i.e., $0.5$ for standard initialization) worst-case bounds at $p=0$. These factors in fact lower bound the approximation achieved for Max-Cut at higher circuit depths, since we also show that QAOA-warmest with any separable initial state converges to Max-Cut under the adiabatic limit as $p\rightarrow \infty$. However, the choice of warm-starts significantly impacts the rate of convergence to Max-Cut, and we show empirically that our warm-starts achieve a faster convergence compared to existing approaches. Additionally, our numerical simulations show higher quality cuts compared to standard QAOA, the classical Goemans-Williamson algorithm, and a warm-started QAOA without custom mixers for an instance library of $1148$ graphs (upto $11$ nodes) and depth $p=8$. We further show that QAOA-warmest outperforms the standard QAOA of Farhi et al. in experiments on current IBM-Q and Quantinuum hardware.

We present a preliminary analysis of $I=1$ $\pi\,\pi$ scattering at the physical point. We make use of the stochastic variant of the distillation framework (also known as sLapH) to compute the relevant two-point correlation matrices using a basis of single and multihadron interpolating operators to estimate the low energy spectra. We perform the L\"uscher analysis to determine the scattering phase shift which is finding good agreement with the experimentally obtained phase shifts., Comment: 9 pages, 5 figures, 1 table, Proceeding for The 38th International Symposium on Lattice Field Theory, LATTICE2021, 26th-30th July, 2021, Zoom/Gather@Massachusetts Institute of Technology

We present an update of the scale setting for $N_f=2+1$ flavor QCD using gradient flow scales and pseudo-scalar decay constants. We analyze the latest ensembles with $2+1$ flavors of non-perturbatively improved Wilson fermions generated by CLS for improved precision. Special care is taken to correct for mistuning by measuring directly the mass derivatives of the various observables. We determine $t_0$ with input taken from a combination of leptonic decay rates of the Pion and the Kaon., Comment: 10 pages, 6 figures, The 38th International Symposium on Lattice Field Theory, LATTICE2021

We present a relativistic heavy-quark action tuning for the charm sector on ensembles generated by the CLS consortium. We tune a particular 5-parameter action in an entirely non-perturbative and -- up to the chosen experimental input -- model-independent way using machine learning and the continuum experimental charmonium ground-state masses with various quantum numbers. In the end we are reasonably successful; obtaining a set of simulation parameters that we then verify produces the expected spectrum. In the future, we will use this action for finite-volume calculations of hadron-hadron scattering., Comment: 22 pages, 7 figures

Progress in computing various meson-baryon scattering amplitudes is presented on a single ensemble from the Coordinated Lattice Simulations (CLS) consortium with $m_\pi=200$ MeV and $N_f=2+1$ dynamical fermions. The finite-volume L\"uscher approach is employed to determine the lowest few partial waves from ground- and excited-state energies computed from correlation matrices rotated in a single pivot using a generalized eigenvector solution. This analysis requires evaluating matrices of correlation functions between single- and two-hadron interpolating operators which are projected onto definite spatial momenta and finite-volume irreducible representations. The stochastic LapH method is used to estimate all needed quark propagators. Preliminary results are presented for $I=\frac{1}{2}, \frac{3}{2}$ $N\pi$ amplitudes including the $\Delta(1232)$ resonance and the $I=0$ $S$-wave amplitude with unit strangeness relevant for the $\Lambda(1405)$., Comment: The 38th International Symposium on Lattice Field Theory, LATTICE2021 26th-30th July, 2021 Zoom/Gather@Massachusetts Institute of Technology 9 pages, 4 figures

Charmonium-like resonances and bound states with isospin zero and $J^{PC}=0^{++},~1^{--},~2^{++},~3^{--}$ are extracted on the lattice. Coupled $D\bar D$ and $D_s\bar D_s$ scattering suggests three charmonium-like states with $J^{PC}=0^{++}$ in addition to $\chi_{c0}(1P)$: a so far unobserved $D\bar D$ bound state just below threshold, a conventional resonance likely related to $\chi_{c0}(3860)/\chi_{c0}(2P)$ and a narrow resonance just below the $D_s\bar D_s$ threshold with a large coupling to $D_s\bar D_s$ likely related to $X(3915)/\chi_{c0}(3930)$. One-channel $D\bar D$ scattering renders resonances and bound states with $J^{PC}= 1^{--},~2^{++},~3^{--}$ related to the observed conventional charmonia. Lattice QCD ensembles from the CLS consortium with $m_{\pi}\simeq 280$ MeV are utilized., Comment: 9 pages, talk presented at LATTICE2021, July 2021, v2: affiliations modified

Synthesizing images of a person in novel poses from a single image is a highly ambiguous task. Most existing approaches require paired training images; i.e. images of the same person with the same clothing in different poses. However, obtaining sufficiently large datasets with paired data is challenging and costly. Previous methods that forego paired supervision lack realism. We propose a self-supervised framework named SPICE (Self-supervised Person Image CrEation) that closes the image quality gap with supervised methods. The key insight enabling self-supervision is to exploit 3D information about the human body in several ways. First, the 3D body shape must remain unchanged when reposing. Second, representing body pose in 3D enables reasoning about self occlusions. Third, 3D body parts that are visible before and after reposing, should have similar appearance features. Once trained, SPICE takes an image of a person and generates a new image of that person in a new target pose. SPICE achieves state-of-the-art performance on the DeepFashion dataset, improving the FID score from 29.9 to 7.8 compared with previous unsupervised methods, and with performance similar to the state-of-the-art supervised method (6.4). SPICE also generates temporally coherent videos given an input image and a sequence of poses, despite being trained on static images only., Comment: International Conference on Computer Vision (ICCV)

Fine-grained zero-shot learning task requires some form of side-information to transfer discriminative information from seen to unseen classes. As manually annotated visual attributes are extremely costly and often impractical to obtain for a large number of classes, in this study we use DNA as side information for the first time for fine-grained zero-shot classification of species. Mitochondrial DNA plays an important role as a genetic marker in evolutionary biology and has been used to achieve near-perfect accuracy in the species classification of living organisms. We implement a simple hierarchical Bayesian model that uses DNA information to establish the hierarchy in the image space and employs local priors to define surrogate classes for unseen ones. On the benchmark CUB dataset, we show that DNA can be equally promising yet in general a more accessible alternative than word vectors as a side information. This is especially important as obtaining robust word representations for fine-grained species names is not a practicable goal when information about these species in free-form text is limited. On a newly compiled fine-grained insect dataset that uses DNA information from over a thousand species, we show that the Bayesian approach outperforms state-of-the-art by a wide margin., Comment: Accepted to NeurIPS 2021

Nonlinear Robust Model Predictive Control (RMPC) provides a very promising solution to the problem of automatic emergency maneuvering, which is capable of handling multiple possibly conflicting objectives of robustness and performance. Even though RMPC gives a suboptimal solution, the key challenge in real-time implementation is that it is computationally very demanding. In this paper a real-time capable robust tube MPC based framework for steering control during emergency obstacle avoidance maneuver is presented. The novelty of this framework lies in the robust integration of path planning and path following tasks of autonomous vehicles. A simulation study showcases the robust performance improvements due to the proposed strategy over a non-robust MPC in different extreme maneuvering scenarios.

We present results for the isovector electromagnetic form factors of the nucleon computed on the CLS ensembles with $N_f=2+1$ flavors of $\mathcal{O}(a)$-improved Wilson fermions and an $\mathcal{O}(a)$-improved vector current. The analysis includes ensembles with four lattice spacings and pion masses ranging from 130 MeV up to 350 MeV and mainly targets the low-$Q^2$ region. In order to remove any bias from unsuppressed excited-state contributions, we investigate several source-sink separations between 1.0 fm and 1.5 fm and apply the summation method as well as explicit two-state fits. The chiral interpolation is performed by applying covariant chiral perturbation theory including vector mesons directly to our form factor data, thus avoiding an auxiliary parametrization of the $Q^2$ dependence. At the physical point, we obtain $\mu=4.71(11)_{\mathrm{stat}}(13)_{\mathrm{sys}}$ for the nucleon isovector magnetic moment, in good agreement with the experimental value and $\langle r_\mathrm{M}^2\rangle~=~0.661(30)_{\mathrm{stat}}(11)_{\mathrm{sys}}\,~\mathrm{fm}^2$ for the corresponding square-radius, again in good agreement with the value inferred from the $ep$-scattering determination [Bernauer et~al., Phys. Rev. Lett., 105, 242001 (2010)] of the proton radius. Our estimate for the isovector electric charge radius, $\langle r_\mathrm{E}^2\rangle = 0.800(25)_{\mathrm{stat}}(22)_{\mathrm{sys}}\,~\mathrm{fm}^2$, however, is in slight tension with the larger value inferred from the aforementioned $ep$-scattering data, while being in agreement with the value derived from the 2018 CODATA average for the proton charge radius.

We present the first lattice investigation of coupled-channel $D\bar D$ and $D_s\bar D_s$ scattering in the $J^{PC}=0^{++}$ and $2^{++}$ channels. The scattering matrix for partial waves $l=0,2$ and isospin zero is determined using multiple volumes and inertial frames via L\"uscher's formalism. Lattice QCD ensembles from the CLS consortium with $m_{\pi}\simeq280$ MeV, $a \simeq 0.09 $ fm and $L/a=24,~32$ are utilized. The resulting scattering matrix suggests the existence of three charmonium-like states with $J^{PC}=0^{++}$ in the energy region ranging from slightly below $2m_D$ up to 4.13 GeV. We find a so far unobserved $D\bar D$ bound state just below threshold and a $D\bar D$ resonance likely related to $\chi_{c0}(3860)$, which is believed to be $\chi_{c0}(2P)$. In addition, there is an indication for a narrow $0^{++}$ resonance just below the $D_s\bar D_s$ threshold with a large coupling to $D_s\bar D_s$ and a very small coupling to $D\bar D$. This resonance is possibly related to the narrow $X(3915)$/$\chi_{c0}(3930)$ observed in experiment also just below $D_s\bar D_s$. The partial wave $l=2$ features a resonance likely related to $\chi_{c2}(3930)$. We work with several assumptions, such as the omission of $J/\psi\omega$, $\eta_c\eta$ and three-particle channels. Only statistical uncertainties are quantified, while the extrapolations to the physical quark-masses and the continuum limit are challenges for the future., Comment: 41 pages, 16 figures; JHEP version, corrected typo concerning the uncertainty in Fig 5c

We study the Quantum Approximate Optimization Algorithm (QAOA) in the context of the Max-Cut problem. Near-term (noisy) quantum devices are only able to (accurately) execute QAOA at low circuit depths while QAOA requires a relatively high circuit-depth in order to "see" the whole graph. We introduce a classical pre-processing step that initializes QAOA with a biased superposition of all possible cuts in the graph, referred to as a warm-start. In particular, our initialization informs QAOA by a solution to a low-rank semidefinite programming relaxation of the Max-Cut problem. Our experimental results show that this variant of QAOA, called QAOA-Warm, is able to outperform standard QAOA on lower circuit depths with less training time (in the optimization stage for QAOA's variational parameters). We provide experimental evidence as well as theoretical intuition on performance of the proposed framework.

Opioid overdose rates have increased in the United States over the past decade and reflect a major public health crisis. Modeling and prediction of drug and opioid hotspots, where a high percentage of events fall in a small percentage of space-time, could help better focus limited social and health services. In this work we present a spatial-temporal point process model for drug overdose clustering. The data input into the model comes from two heterogeneous sources: 1) high volume emergency medical calls for service (EMS) records containing location and time, but no information on the type of non-fatal overdose and 2) fatal overdose toxicology reports from the coroner containing location and high-dimensional information from the toxicology screen on the drugs present at the time of death. We first use non-negative matrix factorization to cluster toxicology reports into drug overdose categories and we then develop an EM algorithm for integrating the two heterogeneous data sets, where the mark corresponding to overdose category is inferred for the EMS data and the high volume EMS data is used to more accurately predict drug overdose death hotspots. We apply the algorithm to drug overdose data from Indianapolis, showing that the point process defined on the integrated data outperforms point processes that use only homogeneous EMS (AUC improvement .72 to .8) or coroner data (AUC improvement .81 to .85).We also investigate the extent to which overdoses are contagious, as a function of the type of overdose, while controlling for exogenous fluctuations in the background rate that might also contribute to clustering. We find that drug and opioid overdose deaths exhibit significant excitation, with branching ratio ranging from .72 to .98.

We develop a fully Bayesian, logistic tracking algorithm with the purpose of providing classification results that are unbiased when applied uniformly to individuals with differing sensitive variable values. Here, we consider bias in the form of differences in false prediction rates between the different sensitive variable groups. Given that the method is fully Bayesian, it is well suited for situations where group parameters or logistic regression coefficients are dynamic quantities. We illustrate our method, in comparison to others, on both simulated datasets and the well-known ProPublica COMPAS dataset.

We review the present status of the Standard Model calculation of the anomalous magnetic moment of the muon. This is performed in a perturbative expansion in the fine-structure constant $\alpha$ and is broken down into pure QED, electroweak, and hadronic contributions. The pure QED contribution is by far the largest and has been evaluated up to and including $\mathcal{O}(\alpha^5)$ with negligible numerical uncertainty. The electroweak contribution is suppressed by $(m_\mu/M_W)^2$ and only shows up at the level of the seventh significant digit. It has been evaluated up to two loops and is known to better than one percent. Hadronic contributions are the most difficult to calculate and are responsible for almost all of the theoretical uncertainty. The leading hadronic contribution appears at $\mathcal{O}(\alpha^2)$ and is due to hadronic vacuum polarization, whereas at $\mathcal{O}(\alpha^3)$ the hadronic light-by-light scattering contribution appears. Given the low characteristic scale of this observable, these contributions have to be calculated with nonperturbative methods, in particular, dispersion relations and the lattice approach to QCD. The largest part of this review is dedicated to a detailed account of recent efforts to improve the calculation of these two contributions with either a data-driven, dispersive approach, or a first-principle, lattice-QCD approach. The final result reads $a_\mu^\text{SM}=116\,591\,810(43)\times 10^{-11}$ and is smaller than the Brookhaven measurement by 3.7$\sigma$. The experimental uncertainty will soon be reduced by up to a factor four by the new experiment currently running at Fermilab, and also by the future J-PARC experiment. This and the prospects to further reduce the theoretical uncertainty in the near future-which are also discussed here-make this quantity one of the most promising places to look for evidence of new physics., Comment: 196 pages, 103 figures, version published in Phys. Rept., bib files for the citation references are available from: https://muon-gm2-theory.illinois.edu

A combination of federal and state-level decision making has shaped the response to COVID-19 in the United States. In this paper we analyze the Twitter narratives around this decision making by applying a dynamic topic model to COVID-19 related tweets by U.S. Governors and Presidential cabinet members. We use a network Hawkes binomial topic model to track evolving sub-topics around risk, testing and treatment. We also construct influence networks amongst government officials using Granger causality inferred from the network Hawkes process.