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In this paper, we propose a topology optimization (TO) framework where the design is parameterized by a set of convex polygons. Extending feature mapping methods in TO, the representation allows for direct extraction of the geometry. In addition, the method allows one to impose geometric constraints such as feature size control directly on the polygons that are otherwise difficult to impose in density or level set based approaches. The use of polygons provides for more more varied shapes than simpler primitives like bars, plates, or circles. The polygons are defined as the feasible set of a collection of halfspaces. Varying the halfspace's parameters allows for us to obtain diverse configurations of the polygons. Furthermore, the halfspaces are differentiably mapped onto a background mesh to allow for analysis and gradient driven optimization. The proposed framework is illustrated through numerous examples of 2D structural compliance minimization TO. Some of the key limitations and future research are also summarized.

We compare the predictions of the GUMICS$-$4 global magnetohydrodynamic model for the interaction of the solar wind with the Earth's magnetosphere with Cluster~SC3 measurements for over one year, from January 29, 2002, to February 2, 2003. In particular, we compare model predictions with the north/south component of the magnetic field ($B_{z}$) seen by the magnetometer, the component of the velocity along the Sun-Earth line ($V_{x}$), and the plasma density as determined from a top hat plasma spectrometer and the spacecraft's potential from the electric field instrument. We select intervals in the solar wind, the magnetosheath, and the magnetosphere where these instruments provided good-quality data, and the model correctly predicted the region in which the spacecraft is located. We determine the location of the bow shock, the magnetopause, and the neutral sheet from the spacecraft measurements and compare these locations to those predicted by the simulation. The GUMICS$-$4 model agrees well with the measurements in the solar wind however its accuracy is worse in the magnetosheath. The simulation results are not realistic in the magnetosphere. The bow shock location is predicted well, however, the magnetopause location is less accurate. The neutral sheet positions are located quite accurately thanks to the special solar wind conditions when the $B_{y}$ component of the interplanetary magnetic field is small., Comment: submitted to the AGU Space Weather, 51 pages, 19 figures, 8 tables

Computation of topological charges of the Schwarzschild and charged black holes in AdS in canonical and grand canonical ensembles allows for a classification of the phase transition points via the Bragg-Williams off-shell free energy. We attempt a topological classification of the critical points and the equilibrium phases of the dual gauge theory via a phenomenological matrix model, which captures the features of the ${\cal{N}}=4$, $SU(N)$ Super Yang-Mills theory on $S^3$ at finite temperature at large $N$. With minimal modification of parameters, critical points of the matrix model at finite chemical potential can be classified as well. The topological charges of locally stable and unstable dynamical phases of the system turn out to be opposite to each other, totalling to zero, and this matches the analysis in the bulk., Comment: v1: 23 pages, 17 figures; v2: 27 pages, 18 figures, 2 Appendices, version to appear in JHEP

Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the need for new technology to support the reading process grows. In contrast to the process of finding papers, which has been transformed by Internet technology, the experience of reading research papers has changed little in decades. The PDF format for sharing research papers is widely used due to its portability, but it has significant downsides including: static content, poor accessibility for low-vision readers, and difficulty reading on mobile devices. This paper explores the question "Can recent advances in AI and HCI power intelligent, interactive, and accessible reading interfaces -- even for legacy PDFs?" We describe the Semantic Reader Project, a collaborative effort across multiple institutions to explore automatic creation of dynamic reading interfaces for research papers. Through this project, we've developed ten research prototype interfaces and conducted usability studies with more than 300 participants and real-world users showing improved reading experiences for scholars. We've also released a production reading interface for research papers that will incorporate the best features as they mature. We structure this paper around challenges scholars and the public face when reading research papers -- Discovery, Efficiency, Comprehension, Synthesis, and Accessibility -- and present an overview of our progress and remaining open challenges.

Optical conductivity measurements may provide access to distinct signatures of Floquet electronic phases, which are described theoretically by their quasienergy band structures. We characterize experimental observables of the Floquet graphene antidot lattice (FGAL), which we introduced previously [Phys. Rev. B 104, 174304 (2021)]. On the basis of Floquet linear response theory, the real and imaginary parts of the longitudinal and Hall optical conductivity are computed as a function of probe frequency. We find that the number and positions of peaks in the response function are distinctive of the different Floquet electronic phases, and identify multiple properties with no equilibrium analog. First, for several intervals of probe frequencies, the real part of the conductivity becomes negative. We argue this is indicative of a subversion of the usual Joule heating mechanism: The Floquet drive causes the material to amplify the power of the probe, resulting in gain. Additionally, while the Hall response vanishes at equilibrium, the real and imaginary parts of the Floquet Hall conductivity are non-zero and can be as large as the longitudinal components. Lastly, driving-induced localization tends to reduce the overall magnitude of and to flatten out the optical conductivity signal. From an implementation standpoint, a major advantage of the FGAL is that the above-bandwidth driving limit is reached with photon energies that are at least twenty times lower than that required for the intrinsic material, allowing for significant band renormalization at orders-of-magnitude smaller intensities. Our work provides the necessary tools for experimentalists to map reflectance data to particular Floquet phases for this novel material.

We review recent studies of contact and thermodynamic geometry for black holes in AdS spacetimes in the extended thermodynamics framework. The cosmological constant gives rise to the notion of pressure $P = -\Lambda / 8 \pi$ and, subsequently a conjugate volume $V$, thereby leading to a close analogy with hydrostatic thermodynamic systems. To begin with, we review the contact geometry approach to thermodynamics in general and then consider thermodynamic metrics constructed as the Hessians of various thermodynamic potentials. We then study their correspondence to statistical ensembles for systems with two-dimensional spaces of equilibrium states. From the zeroes and divergences of the curvature scalar obtained from the metric, we carefully analyze the issue of ensemble non-equivalence and show certain complimentary behaviors in the description of a thermodynamic system. Following a thorough analysis of the familiar van der Waals system, we turn our attention to black holes in extended phase space. Considering the example of charged AdS black holes, we discuss the generic features of their thermodynamic geometry in detail. The relationship of the thermodynamic curvature(s) with critical points as well as microscopic interactions in black holes is also briefly explored. We finally set up the thermodynamic geometry for finite temperature gauge theories dual to black holes in AdS via holographic correspondence and comment on recent progress., Comment: Comments are welcome

The volume of scientific output is creating an urgent need for automated tools to help scientists keep up with developments in their field. Semantic Scholar (S2) is an open data platform and website aimed at accelerating science by helping scholars discover and understand scientific literature. We combine public and proprietary data sources using state-of-the-art techniques for scholarly PDF content extraction and automatic knowledge graph construction to build the Semantic Scholar Academic Graph, the largest open scientific literature graph to-date, with 200M+ papers, 80M+ authors, 550M+ paper-authorship edges, and 2.4B+ citation edges. The graph includes advanced semantic features such as structurally parsed text, natural language summaries, and vector embeddings. In this paper, we describe the components of the S2 data processing pipeline and the associated APIs offered by the platform. We will update this living document to reflect changes as we add new data offerings and improve existing services., Comment: 8 pages, 6 figures

In the presence of strong electronic spin correlations, the hyperfine interaction imparts long-range coupling between nuclear spins. Efficient protocols for the extraction of such complex information about electron correlations via magnetic response are not well known. Here, we study how machine learning can extract material parameters and help interpret magnetic response experiments. A low-dimensional representation that classifies the total interaction strength is discovered by unsupervised learning. Supervised learning generates models that predict the spatial extent of electronic correlations and the total interaction strength. Our work demonstrates the utility of artificial intelligence in the development of new probes of quantum systems, with applications to experimental studies of strongly correlated materials., Comment: 14 pages, 12 figures

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License.

Local and nonlocal differential resistance measurements on Hall bars defined in AlO$_x$/KTaO$_3$ heterostructures show anomalous behavior that depends on the crystal orientation and the applied back gate voltage. The local differential resistance is asymmetric in the dc bias current, with an antisymmetric component that grows with decreasing gate voltage. More surprisingly, a large nonlocal differential resistance is observed that extends between measurement probes that are separated by 100s of microns. The potential source of this anomalous behavior is discussed.

Nuclear magnetic resonance (NMR) experiments can reveal local properties in materials, but are often limited by the low signal-to-noise ratio. Spin squeezed states have an improved resolution below the Heisenberg limit in one of the spin components, and have been extensively used to improve the sensitivity of atomic clocks, for example. Interacting and entangled spin ensembles with non-linear coupling are a natural candidate for implementing squeezing. Here, we propose measurement of the spin-squeezing parameter that itself can act as a local probe of emergent orders in quantum materials. In particular, we demonstrate how to investigate an anisotropic electric field gradient via its coupling to the nuclear quadrupole moment. While squeezed spin states are pure, the squeezing parameter can be estimated for both pure and mixed states. We evaluate the range of fields and temperatures for which a thermal-equilibrium state is sufficient to improve the resolution in an NMR experiment and probe relevant parameters of the quadrupole Hamiltonian, including its anisotropy.

There has been intense recent interest in the two-dimensional electron gases (2DEGs) that form at the surfaces and interfaces of KTaO$_3$ (KTO), with the discovery of superconductivity at temperatures significantly higher than those of similar 2DEGs based on SrTiO$_3$ (STO). Here we demonstrate that KTO 2DEGs fabricated under conditions that suppress the superconductivity show a large spontaneous Hall effect at low temperatures. The transverse response is asymmetric in an applied perpendicular magnetic field and becomes hysteretic at millikelvin temperatures. The hysteresis is due to long range magnetic order arising from local Ta$^{4+}$ moments. However, the most striking features of the data are the asymmetry of the transverse response and the large spontaneous transverse resistance at zero field, which can be a significant fraction of the longitudinal resistance and depends on crystal orientation. Both effects are due to the presence of a dominant contribution to the transverse response that is symmetric in perpendicular field, suggesting that its origin is topological in nature. We argue that this contribution arises from Berry curvature dipoles coupled with nonequilibrium conditions induced by the measuring current., Comment: 6 Pages of main text with 6 figures, includes supplementary materials

Fluid-flow devices with low dissipation, but high contact area, are of importance in many applications. A well-known strategy to design such devices is multi-scale topology optimization (MTO), where optimal microstructures are designed within each cell of a discretized domain. Unfortunately, MTO is computationally very expensive since one must perform homogenization of the evolving microstructures, during each step of the homogenization process. As an alternate, we propose here a graded multiscale topology optimization (GMTO) for designing fluid-flow devices. In the proposed method, several pre-selected but size-parameterized and orientable microstructures are used to fill the domain optimally. GMTO significantly reduces the computation while retaining many of the benefits of MTO. In particular, GMTO is implemented here using a neural-network (NN) since: (1) homogenization can be performed off-line, and used by the NN during optimization, (2) it enables continuous switching between microstructures during optimization, (3) the number of design variables and computational effort is independent of number of microstructure used, and, (4) it supports automatic differentiation, thereby eliminating manual sensitivity analysis. Several numerical results are presented to illustrate the proposed framework.

The energy of an Andreev bound state in a clean normal metal in contact with two superconductors disperses with the difference $\Delta \phi$ in the superconducting phase between the superconductors in much the same way as the energies of electrons in a one-dimensional crystal disperse with the crystal momentum $k$ of the electrons. A normal metal with $n$ superconductors maps on to a $n-1$ dimensional crystal, each dimension corresponding to the phase difference $\phi_i$ between a specific pair of superconductors. The resulting band structure as a function of the phase differences $\{\Delta \phi_i\}$ has been proposed to have a topological nature, with gapped regions characterized by different Chern numbers separated by regions where the gap in the quasiparticle spectrum closes. A similar complex evolution of the quasiparticle spectrum with $\{\Delta \phi_i\}$ has also been predicted for diffusive normal metals in contact with multiple superconductors. Here we show that the variation of the density of states at the Fermi energy of such a system can be directly probed by relatively simple conductance measurements, allowing rapid characterization of the energy spectrum., Comment: 4 pages, 4 figures

Stability is an important characteristic of network models that has implications for other desirable aspects such as controllability. The stability of a Boolean network depends on various factors, such as the topology of its wiring diagram and the type of the functions describing its dynamics. In this paper, we study the stability of linear Boolean networks by computing Derrida curves and quantifying the number of attractors and cycle lengths imposed by their network topologies. Derrida curves are commonly used to measure the stability of Boolean networks and several parameters such as the average in-degree K and the output bias p can indicate if a network is stable, critical, or unstable. For random unbiased Boolean networks there is a critical connectivity value Kc=2 such that if KKc networks operate in the chaotic regime. Here, we show that for linear networks, which are the least canalizing and most unstable, the phase transition from order to chaos already happens at an average in-degree of Kc=1. Consistently, we also show that unstable networks exhibit a large number of attractors with very long limit cycles while stable and critical networks exhibit fewer attractors with shorter limit cycles. Additionally, we present theoretical results to quantify important dynamical properties of linear networks. First, we present a formula for the proportion of attractor states in linear systems. Second, we show that the expected number of fixed points in linear systems is 2, while general Boolean networks possess on average one fixed point. Third, we present a formula to quantify the number of bijective linear Boolean networks and provide a lower bound for the percentage of this type of network., Comment: 18 pages, 3 figures

We present a multi-modal spectroscopic paradigm that enables independent measurement of charge and spin degrees of freedom (DOF) in strongly correlated materials. This spin-based technique probes symmetry-specific Hamiltonian parameters by analyzing how the time delay between applied pulses ($\tau$) affects the response. We demonstrate ways in which charge DOF that couple through the quadrupolar interaction (inversion symmetric) can be independently measured even in the presence of large magnetic noise (inversion asymmetric). The method quantifies both the strength of the interactions and its distribution (noise). We provide protocols to directly and independently measure the distribution of interaction strengths, even when the average value of the interaction is zero. By independently measuring distributions of different forms of disorder, this methodology can elucidate which microscopic symmetry drives a phase transition. We discuss potential applications to study complex phase transitions in strongly interacting quantum materials., Comment: 14 pages, 6 figures

Using the Bragg-Williams construction of an off-shell free energy we compute the topological charge of the Hawking-Page transition point for black holes in AdS. A computation following from a related off-shell effective potential in the boundary gauge dual matches the value of topological charge obtained in the bulk. We also compute the topological charges of the equilibrium phases of these systems, which follow from the saddle points of the appropriate free energy. The locally stable and unstable phases turn out to have topological charges opposite to each other, with the total being zero, in agreement with the result obtained from a related construction [arXiv:2208.01932]., Comment: 14 pages, 6 figures

Dynamic nuclear polarization (DNP) is a method of enhancing NMR signals via the transfer of polarization from electron spins to nuclear spins using on-resonance microwave (MW) irradiation. In most cases, monochromatic continuous-wave (MCW) MW irradiation is used. Recently, several groups have shown that the use of frequency modulation of the MW irradiation can result in an additional increase in DNP enhancement above that obtained with MCW. The effect of frequency modulation on the solid effect (SE) and the cross effect (CE) has previously been studied using the stable organic radical 4-hydroxy TEMPO (TEMPOL) at temperatures under 20 K. Here, in addition to the SE and CE, we discuss the effect of frequency modulation on the Overhauser effect (OE) and the truncated CE (tCE) in the room-temperature $^{13}$C-DNP of diamond powders. We recently showed that diamond powders can exhibit multiple DNP mechanisms simultaneously due to the heterogeneity of P1 (substitutional nitrogen) environments within diamond crystallites. We explore the enhancement obtained via the two most important parameters for frequency modulation 1) Modulation frequency, $f_{m}$ (how fast the modulation frequency is varied) and 2) Modulation amplitude, $\Delta\omega$ (the magnitude of the change in microwave frequency) influence the enhancement obtained via each mechanism. Frequency modulation during DNP not only allows us to improve DNP enhancement, but also gives us a way to control which DNP mechanism is most active. By choosing the appropriate modulation parameters, we can selectively enhance some mechanisms while simultaneously suppressing others.

Continued advances in superconducting qubit performance require more detailed understandings of the many sources of decoherence. Within these devices, two-level systems arise due to defects, interfaces, and grain boundaries, and are thought to be a major source of qubit decoherence at millikelvin temperatures. In addition to Al, Nb is a commonly used metalization layer for superconducting qubits. Consequently, a significant effort is required to develop and qualify processes that mitigate defects in Nb films. As the fabrication of complete superconducting qubits and their characterization at millikelvin temperatures is a time and resource intensive process, it is desirable to have measurement tools that can rapidly characterize the properties of films and evaluate different treatments. Here we show that measurements of the variation of the superconducting critical temperature $T_c$ with an applied external magnetic field $H$ (of the phase boundary $T_c - H$) performed with very high resolution show features that are directly correlated with the structure of the Nb films. In combination with x-ray diffraction measurements, we show that one can even distinguish variations quality and crystal orientation of the grains in a Nb film by small but reproducible changes in the measured superconducting phase boundary.

We use microwave-induced dynamic nuclear polarization (DNP) of the substitutional nitrogen defects (P1 centers) in diamond to hyperpolarize bulk $^{13}$C nuclei in both single crystal and powder samples at room temperature at 3.34 T. The large ($>100$-fold) enhancements demonstrated correspond to a greater than 10,000 fold improvement in terms of signal averaging of the 1\% abundant $^{13}$C spins. The DNP was performed using low-power solid state sources under static (non-spinning) conditions. The DNP spectrum (DNP enhancement as a function of microwave frequency) of diamond powder shows features that broadly correlate with the EPR spectrum. A well-defined negative Overhauser peak and two solid effect peaks are observed for the central ($m_I=0$) manifold of the $^{14}$N spins. Previous low temperature measurements in diamond had measured a positive Overhauser enhancement in this manifold. Frequency-chirped millimeter-wave excitation of the electron spins is seen to significantly improve the enhancements for the two outer nuclear spin manifolds ($m_I = \pm 1$) and to blur some of the sharper features associated with the central manifolds. The outer lines are best fit using a combination of the cross effect and a truncated cross effect -- which is known to mimic features of an Overhauser effect. Similar features are also observed in experiments on single crystal samples. The observation of all of these mechanisms in a single material system under the same experimental conditions is likely due to the significant heterogeneity of the high pressure, high temperature (HPHT) type Ib diamond samples used. Large room temperature DNP enhancements at fields above a few Tesla enable spectroscopic studies with better chemical shift resolution under ambient conditions.

The topological classification of critical points of black holes in 4D Einstein-Gauss-Bonnet gravity coupled to Born-Infeld theory is investigated. Considered independently, Born-infeld corrections to the Einstein action alter the topological charge of critical points of the charged AdS black hole system, whereas the Gauss-Bonnet corrections do not. For the combined system though, the total topological charge of the Einstein-Gauss-Bonnet theory is unaltered in the presence of Born-Infeld coupling., Comment: v1: 14 pages, 5 figures; v2: 17 pages, 7 figures, minor changes, matches published version

Microstructures, i.e., architected materials, are designed today, typically, by maximizing an objective, such as bulk modulus, subject to a volume constraint. However, in many applications, it is often more appropriate to impose constraints on other physical quantities of interest. In this paper, we consider such generalized microstructural optimization problems where any of the microstructural quantities, namely, bulk, shear, Poisson ratio, or volume, can serve as the objective, while the remaining can serve as constraints. In particular, we propose here a neural-network (NN) framework to solve such problems. The framework relies on the classic density formulation of microstructural optimization, but the density field is represented through the NN's weights and biases. The main characteristics of the proposed NN framework are: (1) it supports automatic differentiation, eliminating the need for manual sensitivity derivations, (2) smoothing filters are not required due to implicit filtering, (3) the framework can be easily extended to multiple-materials, and (4) a high-resolution microstructural topology can be recovered through a simple post-processing step. The framework is illustrated through a variety of microstructural optimization problems.

We compute logarithmic corrections to the black hole entropy $S_{\rm bh}$ in a holographic set up where the cosmological constant $\Lambda$ and Newton's constant $G_D$ are taken to be thermodynamic parameters, related to variations in bulk pressure \(P\) and central charge \(c\). In the bulk, the logarithmic corrections are of the form: $\mathcal{S} = S_{\rm bh} - k \ln S_{\rm bh} + \cdots$ arising due to fluctuations in thermodynamic volume, induced by a variable $\Lambda$, in addition to energy fluctuations. We explicitly compute this coefficient $k$ for the BTZ black hole and show that the result matches with the one coming from the logarithmic corrections to the Cardy's formula. We propose an entropy function in the CFT, which exactly reproduces the logarithmic corrections to black hole entropy in arbitrary dimensions., Comment: 5 pages