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        <h1 class="text-center">Artificial General Intelligence Research & News</h1>

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                    <h5 class="card-title">The Moving Discontinuous Galerkin Method with Interface Condition Enforcement for Robust Simulations of High-Speed Viscous Flows</h5>
                    <p class="card-text">The moving discontinuous Galerkin method with interface condition enforcement (MDG-ICE) is a high-order, r-adaptive method that treats the grid as a variable and weakly enforces the conservation law, constitutive law, and corresponding interface conditions in order to implicitly fit high-gradient flow features. In this paper, we introduce nonlinear solver strategies to more robustly and efficiently compute high-speed viscous flows. Specifically, we incorporate an anisotropic grid regularization based on the mesh-implied metric into the nonlinear least-squares solver that inhibits grid motion in directions with small element length scales. Furthermore, we develop an adaptive elementwise regularization strategy that locally scales the regularization terms as needed to maintain grid validity. We apply the proposed MDG-ICE formulation to test cases involving viscous shocks and/or boundary layers, including Mach 17.6 hypersonic viscous flow over a circular cylinder and Mach 5 hypersonic viscous flow over a sphere, which are very challenging test cases for conventional numerical schemes on simplicial grids. Even without artificial dissipation, the computed solutions are free from spurious oscillations and yield highly symmetric surface heat-flux profiles.</p>
                    <a href="http://arxiv.org/abs/2311.00701v1" class="btn btn-primary" target="_blank">Read more</a>
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                    <h5 class="card-title">Generalized Narain Theories Decoded: Discussions on Eisenstein series, Characteristics, Orbifolds, Discriminants and Ensembles in any Dimension</h5>
                    <p class="card-text">We study a class of newly-introduced CFTs associated with even quadratic forms of general signature, which we call generalized Narain theories. We first summarize the properties of these theories. We then consider orbifolds of these theories, thereby obtaining a large class of non-supersymmetric CFTs with exactly marginal deformations. We then discuss ensemble averages of such theories over their moduli space, and obtain a modular form associated with the quadratic form and an element of the discriminant group. The modular form can be written as a Poincare series, which contains novel invariants of lens spaces and suggests the interpretation of the holographic bulk as a theory of anyons.</p>
                    <a href="http://arxiv.org/abs/2311.00699v1" class="btn btn-primary" target="_blank">Read more</a>
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                    <h5 class="card-title">Crystalline topological defects within response theory</h5>
                    <p class="card-text">Lattice defects have interesting effects in some quantum Hamiltonians. Here we show how topological crystalline defects can produce qualitatively new effects by coupling to electric field probes such as Raman scattering, even when they do not appear in the low-energy Hamiltonian but rather only in the probe response theory. To show this we consider an antiferromagnetic spin-1/2 model $H_{spin}$ on a zigzag chain. Crystalline domain walls between two zigzag domains appear as at most local defects in $H_{spin}$, but as topological (not locally creatable) defects in the Raman operator $R$ of inelastic photon scattering. Using TEBD numerics, bosonization, and mean field, we show that a finite density of crystalline domain walls shifts the entire Raman signal to produce an effective gap. This lattice-defect-induced Raman gap closes and reopens in applied magnetic fields. We discuss the effect in terms of photons sensing the lattice defects within $R$ as spin-dimerization domain walls, with $Z_2$ character, and a resulting shift of the probed wavevector from $q=0$ to $\\pi+\\delta q$, giving an $\\textit{O}(1)$ change in contrast to local defects. The magneto-Raman singularity from topological lattice defects here relies on the $H_{spin}$ spinon liquid state, suggesting future applications using lattice topological defects to modify response-theory operators independently of $H$ and thereby generate new probes of quantum phases.</p>
                    <a href="http://arxiv.org/abs/2311.00698v1" class="btn btn-primary" target="_blank">Read more</a>
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        <h2>News References</h2>
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                    <h5 class="card-title">Artificial General Intelligence Is Already Here</h5>
                    <p class="card-text">Artificial General Intelligence (AGI) means many different things to different people, but the most important parts of it have already been...</p>
                    <a href="https://www.noemamag.com/artificial-general-intelligence-is-already-here" class="btn btn-primary" target="_blank">Read more</a>
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                    <h5 class="card-title">Artificial General Intelligence: Friend or Foe?</h5>
                    <p class="card-text">Although narrow AI does a remarkable job predicting natural disasters, strong AI will be much better and more accurate. By feeding information...</p>
                    <a href="https://www.g2.com/articles/artificial-general-intelligence" class="btn btn-primary" target="_blank">Read more</a>
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                    <h5 class="card-title">Artificial General Intelligence (AGI) And The Coming Wave</h5>
                    <p class="card-text">This years Wall Street Journal Tech Live event heralds the arrival of Artificial General Intelligence (AGI) and a glimpse into the future.</p>
                    <a href="https://www.forbes.com/sites/randybean/2023/10/24/artificial-general-intelligence-agi-and-the-coming-wave/" class="btn btn-primary" target="_blank">Read more</a>
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                    <h5 class="card-title">AGI Utopia or Dystopia: What's the Real Story?</h5>
                    <p class="card-text">While we've made significant strides in AI research, the question of whether we will ever achieve AGI is a complex and multifaceted one.</p>
                    <a href="https://www.cmswire.com/digital-experience/the-quest-for-achieving-artificial-general-intelligence/" class="btn btn-primary" target="_blank">Read more</a>
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                    <h5 class="card-title">Good chance that AI will achieve Artificial General Intelligence in 5 years, says Google AI Boss</h5>
                    <p class="card-text">Shane Legg, co-founder of Google's DeepMind AI Lab in 2001 had predicted that by 2028, AI will achieve AGI or Artificial General...</p>
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