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Understanding the screening mass of pseudoscalar mesons at finite temperature and magnetic field is crucial for comprehending the behavior of strongly interacting matter under extreme conditions, such as those found in the early universe or inside neutron stars. Additionally, in heavy ion collisions, strong magnetic fields are generated, which could significantly influence the properties of the quark-gluon plasma. The study of these screening masses provides insight into the modifications of mesonic properties in such environments, which is essential for the theoretical understanding of Quantum Chromodynamics (QCD) phase transitions and the properties of the quark-gluon plasma. Here, we present continuum estimated lattice QCD results on the screening mass of neutral pseudoscalar mesons at finite temperatures and nonzero magnetic fields. The simulations used (2+1)-flavor lattice QCD simulations using physical quark masses employing the HISQ/tree action. The continuum estimation was carried out using lattices having temporal extents $N_\tau$ = 8, 12, and 16, all having aspect ratio $N_\sigma/N_\tau$ = 4. The investigated temperature ranges from 145 MeV to 166 MeV, while the magnetic field strength varies from 0 to 1 GeV$^2$. We discuss the dependence of the screening masses of various neutral pseudoscalar mesons on temperature, magnetic field strength, and quark mass.

We investigate the effects of temperature $T$ and external magnetic fields $eB$ on the chiral condensates and screening masses of neutral pseudoscalar mesons, including $\pi^0$, $K^0$, and $\eta_{s\bar{s}}^0$, in (2+1)-flavor lattice QCD with physical quark masses. The chiral condensates are intrinsically connected to the screening masses via Ward-Takahashi identities, with the latter characterizing the inverse of the spatial correlation length in the pseudoscalar channel. Using highly improved staggered quarks, we perform simulations on lattices with temporal extents $N_\tau = 8, 12, 16$ and an aspect ratio of 4, covering five temperatures from 145 MeV to 166 MeV. For each temperature, eight magnetic field strengths are simulated, reaching up to $eB \sim 0.8$ GeV$^2$. These simulations allow us to provide continuum estimates for the chiral condensates and screening masses. We observe intricate behavior in the light ($ud$), strange-light ($ds$) and strange ($s$) quark condensates as functions of the magnetic field and temperature, reflecting the competition between magnetic catalysis and inverse magnetic catalysis effects. This complex behavior is also mirrored in the screening masses of the neutral pseudoscalar mesons. Notably, the screening masses of $\pi^0$ and $K^0$ exhibit a non-monotonic dependence on $eB$, closely following the variations in their corresponding chiral condensates. Meanwhile, the screening mass of $\eta_{s\bar{s}}^0$ decreases monotonically with increasing $eB$. These findings provide valuable insights for understanding the behavior of QCD in a thermomagnetic medium and can serve as benchmarks for low-energy QCD models and effective theories.

We present a method to calculate the pion screening mass in 2+1-flavor lattice QCD to $\mathcal{O}(\mu^2_\ell)$, where $\mu_\ell$ is the isoscalar chemical potential. Our approach is based on the expression for the free theory pion screening correlator for massless quarks. We use the Taylor expansion method to calculate the screening correlator to $\mathcal{O}(\mu^4_\ell)$. We then extract the $\mathcal{O}(\mu^2_\ell)$ Taylor coefficient of the screening mass from the Taylor coefficients of the correlator, for two temperatures in the range 2 - 3 GeV. Our calculations were done using the Highly Improved Staggered Quark action, and the strange and light quark masses were set respectively to their physical and nearly physical values, corresponding to meson masses $M_{\bar{s}s}=686$ MeV and $M_\pi=160$ MeV., Comment: Contribution to the proceedings of The 40th International Symposium on Lattice Field Theory (Lattice 2023), July 31st - August 4th, 2023, Fermi National Accelerator Laboratory, USA

We present a method to compute the responses of meson screening masses to the chemical potential by Taylor expanding the correlator using lattice QCD simulation. We start by comparing the free theory lattice results with the analytical expression. Then, using symmetry arguments, we obtain an expression for the correlator in a series of the chemical potential at finite temperature. Using this, we obtain the lowest order correction to the screening mass at a finite chemical potential for temperatures around 2.5 GeV. Our lattice analysis is limited to isoscalar chemical potential for the pseudoscalar channel. The calculations were performed using (2+1)-flavors of the Highly Improved Staggered Quark (HISQ/tree) action, with the ratio of the strange quark mass to the light quark mass $m_s/m_\ell=20$ corresponding to pion masses of 160 MeV., Comment: 18 pages, 15 figures; updated version of the paper

Knowledge of the screening masses at finite chemical potential can provide insight into the nature of the QCD phase diagram. However, lattice studies at finite chemical potential suffer from the well-known issue of the sign problem, which has made the calculation of observables such as screening correlators and screening masses at finite chemical potential quite challenging. One way to proceed is by expanding the observable in a Taylor series in the chemical potential and hence calculating the finite-density corrections to the observable. In this talk, we will use this approach to calculate the screening mass of the pseudoscalar meson at finite temperatures and chemical potential by expanding the screening correlator in a Taylor series in the chemical potential. We will present our results for the second derivative of the screening mass w.r.t. the chemical potential. Our calculation was done on $64^3 \times 8$ lattices generated using the (2+1) HISQ/tree action., Comment: Proceedings of Science submission 2022

We investigate the problem of autonomous racing among teams of cooperative agents that are subject to realistic racing rules. Our work extends previous research on hierarchical control in head-to-head autonomous racing by considering a generalized version of the problem while maintaining the two-level hierarchical control structure. A high-level tactical planner constructs a discrete game that encodes the complex rules using simplified dynamics to produce a sequence of target waypoints. The low-level path planner uses these waypoints as a reference trajectory and computes high-resolution control inputs by solving a simplified formulation of a racing game with a simplified representation of the realistic racing rules. We explore two approaches for the low-level path planner: training a multi-agent reinforcement learning (MARL) policy and solving a linear-quadratic Nash game (LQNG) approximation. We evaluate our controllers on simple and complex tracks against three baselines: an end-to-end MARL controller, a MARL controller tracking a fixed racing line, and an LQNG controller tracking a fixed racing line. Quantitative results show our hierarchical methods outperform the baselines in terms of race wins, overall team performance, and compliance with the rules. Qualitatively, we observe the hierarchical controllers mimic actions performed by expert human drivers such as coordinated overtaking, defending against multiple opponents, and long-term planning for delayed advantages.

We develop a hierarchical controller for head-to-head autonomous racing. We first introduce a formulation of a racing game with realistic safety and fairness rules. A high-level planner approximates the original formulation as a discrete game with simplified state, control, and dynamics to easily encode the complex safety and fairness rules and calculates a series of target waypoints. The low-level controller takes the resulting waypoints as a reference trajectory and computes high-resolution control inputs by solving an alternative formulation approximation with simplified objectives and constraints. We consider two approaches for the low-level planner, constructing two hierarchical controllers. One approach uses multi-agent reinforcement learning (MARL), and the other solves a linear-quadratic Nash game (LQNG) to produce control inputs. The controllers are compared against three baselines: an end-to-end MARL controller, a MARL controller tracking a fixed racing line, and an LQNG controller tracking a fixed racing line. Quantitative results show that the proposed hierarchical methods outperform their respective baseline methods in terms of head-to-head race wins and abiding by the rules. The hierarchical controller using MARL for low-level control consistently outperformed all other methods by winning over 90% of head-to-head races and more consistently adhered to the complex racing rules. Qualitatively, we observe the proposed controllers mimicking actions performed by expert human drivers such as shielding/blocking, overtaking, and long-term planning for delayed advantages. We show that hierarchical planning for game-theoretic reasoning produces competitive behavior even when challenged with complex rules and constraints.

We present lattice QCD results for mesonic screening masses in the temperature range 140 MeV $\lesssim T \lesssim$ 2500 MeV. Our calculations were carried out using (2+1)-flavors of the Highly Improved Staggered Quark (HISQ) action, with a physical value for the strange quark mass and two values of the light quark mass corresponding to pion masses of 160 MeV and 140 MeV. Continuum-extrapolated results were obtained using calculations with a variety of lattice spacings corresponding to temporal lattice extents $N_\tau = 6 - 16$. We discuss the implications of these results for the effective restoration of various symmetries in the high temperature phase of QCD, as well as the approach toward the perturbative limit., Comment: Corrected some errors pertaining to the discussion on emergent SU(2)CS and SU(4) symmetries