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GotThatData
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-  {
-    "title": "Transistors based on Novel 2-D Monolayer Semiconductors Bi2O2Se, InSe,   and MoSi2N4 for Enhanced Logic Density Scaling",
-    "authors": [
-      "Keshari Nandan",
-      "Ateeb Naseer",
-      "Amit Agarwal",
-      "Somnath Bhowmick",
-      "Yogesh S. Chauhan"
-    ],
-    "summary": "Making ultra-short gate-length transistors significantly contributes to scaling the contacted gate pitch. This, in turn, plays a vital role in achieving smaller standard logic cells for enhanced logic density scaling. As we push the boundaries of miniaturization, it is intriguing to consider that the ultimate limit of contacted gate pitch could be reached with remarkable 1 nm gate-length transistors. Here, we identify InSe, Bi2O2Se, and MoSi2N4 as potential two-dimensional semiconductors for 1 nm transistors with low contact resistance and outstanding interface properties. We employ a fully self-consistent ballistic quantum transport model starting from first-principle calculations. Our simulations show that the interplay between electrostatics and quantum tunneling influences the performance of these devices over the device design space. MoSi2N4 channels have the best immunity to quantum tunneling, and Bi2O2Se channel devices have the best electrostatics. We show that for a channel length of 12 nm, all the devices can deliver I_$ON$/I_$OFF$ > 10^3 , suitable for electronic applications, and Bi2O2Se is the best-performing channel material.",
-    "published_date": "2024-12-02T00:27:27Z",
-    "updated_date": "2024-12-15T01:00:18Z",
-    "arxiv_id": "2412.01016v2",
-    "primary_category": "cond-mat.mes-hall",
-    "categories": [
-      "cond-mat.mes-hall",
-      "cond-mat.mtrl-sci",
-      "physics.app-ph",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2412.01016v2",
-    "abstract_url": "http://arxiv.org/abs/2412.01016v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2412.01016v2.pdf"
-  },
-  {
-    "title": "Goodbye Christoffel Symbols: A Flexible and Efficient Approach for   Solving Physical Problems in Curved Spaces",
-    "authors": [
-      "Miguel A. Herrada"
-    ],
-    "summary": "Traditional methods for solving physical equations in curved spaces, especially in fluid mechanics and general relativity, rely heavily on the use of Christoffel symbols. These symbols provide the necessary corrections to account for curvature in differential geometries but lead to significant computational complexity, particularly in numerical simulations. In this paper, we propose a novel, simplified approach that obviates the need for Christoffel symbols by symbolic programming and advanced numerical methods.   Our approach is based on defining a symbolic mapping between Euclidean space and curved coordinate systems, enabling the transformation of spatial and temporal derivatives through Jacobians and their inverses. This eliminates the necessity of using Christoffel symbols for defining local bases and tensors, allowing for the direct application of physical laws in Cartesian coordinates even when solving problems in curved spaces.   We demonstrate the robustness and flexibility of our method through several examples, including the derivation of the Navier-Stokes equations in cylindrical coordinates, the modeling of complex flows in bent cylindrical tubes, and the breakup of viscoelastic fluid threads. These examples highlight how our method simplifies the numerical formulation while maintaining accuracy and efficiency. Additionally, we explore how these advancements benefit free-surface flows, where mapping physical 3D domains to a simpler computational domain is essential for solving moving boundary problems.",
-    "published_date": "2024-10-30T12:12:11Z",
-    "updated_date": "2024-10-30T12:12:11Z",
-    "arxiv_id": "2410.22957v1",
-    "primary_category": "physics.flu-dyn",
-    "categories": [
-      "physics.flu-dyn",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2410.22957v1",
-    "abstract_url": "http://arxiv.org/abs/2410.22957v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2410.22957v1.pdf"
-  },
-  {
-    "title": "Generative Flow Networks in Covariant Loop Quantum Gravity",
-    "authors": [
-      "Joseph Bunao",
-      "Pietropaolo Frisoni",
-      "Athanasios Kogios",
-      "Jared Wogan"
-    ],
-    "summary": "Spin foams arose as the covariant (path integral) formulation of quantum gravity depicting transition amplitudes between different quantum geometry states. As such, they provide a scheme to study the no boundary proposal, specifically the nothing to something transition and compute relevant observables using high performance computing (HPC). Following recent advances, where stochastic algorithms (Markov Chain Monte Carlo-MCMC) were used, we employ Generative Flow Networks, a newly developed machine learning algorithm to compute the expectation value of the dihedral angle for a 4-simplex and compare the results with previous works.",
-    "published_date": "2024-07-26T18:27:15Z",
-    "updated_date": "2024-07-26T18:27:15Z",
-    "arxiv_id": "2407.19036v1",
-    "primary_category": "gr-qc",
-    "categories": [
-      "gr-qc",
-      "hep-th",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2407.19036v1",
-    "abstract_url": "http://arxiv.org/abs/2407.19036v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2407.19036v1.pdf"
-  },
-  {
-    "title": "Predicting atmospheric turbulence for secure quantum communications in   free space",
-    "authors": [
-      "Tareq Jaouni",
-      "Lukas Scarfe",
-      "Fr\u00e9d\u00e9ric Bouchard",
-      "Mario Krenn",
-      "Khabat Heshami",
-      "Francesco Di Colandrea",
-      "Ebrahim Karimi"
-    ],
-    "summary": "Atmospheric turbulence is the main barrier to large-scale free-space quantum communication networks. Aberrations distort optical information carriers, thus limiting or preventing the possibility of establishing a secure link between two parties. For this reason, forecasting the turbulence strength within an optical channel is highly desirable, as it allows for knowing the optimal timing to establish a secure link in advance. Here, we train a Recurrent Neural Network, TAROCCO, to predict the turbulence strength within a free-space channel. The training is based on weather and turbulence data collected over 9 months for a 5.4 km intra-city free-space link across the City of Ottawa. The implications of accurate predictions from our network are demonstrated in a simulated high-dimensional Quantum Key Distribution protocol based on orbital angular momentum states of light across different turbulence regimes. TAROCCO will be crucial in validating a free-space channel to optimally route the key exchange for secure communications in real experimental scenarios.",
-    "published_date": "2024-06-20T22:38:13Z",
-    "updated_date": "2024-06-20T22:38:13Z",
-    "arxiv_id": "2406.14768v1",
-    "primary_category": "quant-ph",
-    "categories": [
-      "quant-ph",
-      "physics.comp-ph",
-      "physics.optics"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2406.14768v1",
-    "abstract_url": "http://arxiv.org/abs/2406.14768v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2406.14768v1.pdf"
-  },
-  {
-    "title": "Building imaginary-time thermal field theory with artificial neural   networks",
-    "authors": [
-      "Tian Xu",
-      "Lingxiao Wang",
-      "Lianyi He",
-      "Kai Zhou",
-      "Yin Jiang"
-    ],
-    "summary": "In this study, we introduce a novel approach in quantum field theories to estimate the action using the artificial neural networks (ANNs). The estimation is achieved by learning on system configurations governed by the Boltzmann factor, $e^{-S}$ at different temperatures within the imaginary time formalism of thermal field theory. We focus on 0+1 dimensional quantum field with kink/anti-kink configurations to demonstrate the feasibility of the method. The continuous-mixture autoregressive networks (CANs) enable the construction of accurate effective actions with tractable probability density estimation. Our numerical results demonstrate that this methodology not only facilitates the construction of effective actions at specified temperatures but also adeptly estimates the action at intermediate temperatures using data from both lower and higher temperature ensembles. This capability is especially valuable for the detailed exploration of phase diagrams.",
-    "published_date": "2024-05-17T02:16:14Z",
-    "updated_date": "2024-10-08T10:22:34Z",
-    "arxiv_id": "2405.10493v2",
-    "primary_category": "hep-lat",
-    "categories": [
-      "hep-lat",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2405.10493v2",
-    "abstract_url": "http://arxiv.org/abs/2405.10493v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2405.10493v2.pdf"
-  },
-  {
-    "title": "Delayed Electron-Ion Entanglement Revealed with Zero Area Pulses",
-    "authors": [
-      "Axel Stenquist",
-      "Jan Marcus Dahlstr\u00f6m"
-    ],
-    "summary": "The Grobe--Eberly doublet phenomenon occurs in photoelectron distributions when the remaining ion is dressed by a field. As was recently shown, the doublet can be interpreted as a signature of quantum entanglement between photoelectrons and strongly coupled ions. However, the dressed state nature of the ion prevents detection of the entanglement by straightforward coincidence detection. Here, we find that odd (zero-area) envelopes can substantially delay the generation of entanglement, but also modify the dynamics such that the doublet transforms into unique channel-resolved photoelectron distributions. Because these distributions can be used to correlate with the internal state of the ion, our proposed scheme opens up for detection of quantum entanglement, between photoelectrons and stongly-coupled ions, without a need for quantum phase measurements.",
-    "published_date": "2024-05-06T10:39:25Z",
-    "updated_date": "2024-07-08T09:52:24Z",
-    "arxiv_id": "2405.03339v2",
-    "primary_category": "quant-ph",
-    "categories": [
-      "quant-ph",
-      "math-ph",
-      "math.MP",
-      "physics.atom-ph",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2405.03339v2",
-    "abstract_url": "http://arxiv.org/abs/2405.03339v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2405.03339v2.pdf"
-  },
-  {
-    "title": "Towards quantum gravity with neural networks: Solving quantum Hamilton   constraints of 3d Euclidean gravity in the weak coupling limit",
-    "authors": [
-      "Hanno Sahlmann",
-      "Waleed Sherif"
-    ],
-    "summary": "We consider 3-dimensional Euclidean gravity in the weak coupling limit of Smolin and show that it is BF-theory with $\\text{U(1)}^3$ as a Lie group. The theory is quantised using loop quantum gravity methods. The kinematical degrees of freedom are truncated, on account of computational feasibility, by fixing a graph and deforming the algebra of the holonomies to impose a cutoff on the charge vectors. This leads to a quantum theory related to $\\text{U}_q \\text{(1)}^3$ BF-theory. The effect of imposing the cutoff on the charges is examined. We also implement the quantum volume operator of 3d loop quantum gravity. Most importantly we compare two constraints for the quantum model obtained: a master constraint enforcing curvature and Gauss constraint, as well as a combination of a quantum Hamilton constraint constructed using Thiemann's strategy and the Gauss master constraint. The two constraints are solved using the neural network quantum state ansatz, demonstrating its ability to explore models which are out of reach for exact numerical methods. The solutions spaces are quantitatively compared and although the forms of the constraints are radically different, the solutions turn out to have a surprisingly large overlap. We also investigate the behavior of the quantum volume in solutions to the constraints.",
-    "published_date": "2024-05-01T17:50:06Z",
-    "updated_date": "2024-05-01T17:50:06Z",
-    "arxiv_id": "2405.00661v1",
-    "primary_category": "gr-qc",
-    "categories": [
-      "gr-qc",
-      "hep-th",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2405.00661v1",
-    "abstract_url": "http://arxiv.org/abs/2405.00661v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2405.00661v1.pdf"
-  },
-  {
-    "title": "Tensor approximation of functional differential equations",
-    "authors": [
-      "Abram Rodgers",
-      "Daniele Venturi"
-    ],
-    "summary": "Functional Differential Equations (FDEs) play a fundamental role in many areas of mathematical physics, including fluid dynamics (Hopf characteristic functional equation), quantum field theory (Schwinger-Dyson equation), and statistical physics. Despite their significance, computing solutions to FDEs remains a longstanding challenge in mathematical physics. In this paper we address this challenge by introducing new approximation theory and high-performance computational algorithms designed for solving FDEs on tensor manifolds. Our approach involves approximating FDEs using high-dimensional partial differential equations (PDEs), and then solving such high-dimensional PDEs on a low-rank tensor manifold leveraging high-performance parallel tensor algorithms. The effectiveness of the proposed approach is demonstrated through its application to the Burgers-Hopf FDE, which governs the characteristic functional of the stochastic solution to the Burgers equation evolving from a random initial state.",
-    "published_date": "2024-03-07T23:22:07Z",
-    "updated_date": "2024-03-07T23:22:07Z",
-    "arxiv_id": "2403.04946v1",
-    "primary_category": "math.NA",
-    "categories": [
-      "math.NA",
-      "cs.NA",
-      "math-ph",
-      "math.MP",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2403.04946v1",
-    "abstract_url": "http://arxiv.org/abs/2403.04946v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2403.04946v1.pdf"
-  },
-  {
-    "title": "Feynman Diagrams as Computational Graphs",
-    "authors": [
-      "Pengcheng Hou",
-      "Tao Wang",
-      "Daniel Cerkoney",
-      "Xiansheng Cai",
-      "Zhiyi Li",
-      "Youjin Deng",
-      "Lei Wang",
-      "Kun Chen"
-    ],
-    "summary": "We propose a computational graph representation of high-order Feynman diagrams in Quantum Field Theory (QFT), applicable to any combination of spatial, temporal, momentum, and frequency domains. Utilizing the Dyson-Schwinger and parquet equations, our approach effectively organizes these diagrams into a fractal structure of tensor operations, significantly reducing computational redundancy. This approach not only streamlines the evaluation of complex diagrams but also facilitates an efficient implementation of the field-theoretic renormalization scheme, crucial for enhancing perturbative QFT calculations. Key to this advancement is the integration of Taylor-mode automatic differentiation, a key technique employed in machine learning packages to compute higher-order derivatives efficiently on computational graphs. To operationalize these concepts, we develop a Feynman diagram compiler that optimizes diagrams for various computational platforms, utilizing machine learning frameworks. Demonstrating this methodology's effectiveness, we apply it to the three-dimensional uniform electron gas problem, achieving unprecedented accuracy in calculating the quasiparticle effective mass at metal density. Our work demonstrates the synergy between QFT and machine learning, establishing a new avenue for applying AI techniques to complex quantum many-body problems.",
-    "published_date": "2024-02-28T03:45:55Z",
-    "updated_date": "2024-02-28T03:45:55Z",
-    "arxiv_id": "2403.18840v1",
-    "primary_category": "hep-th",
-    "categories": [
-      "hep-th",
-      "cond-mat.str-el",
-      "cs.LG",
-      "hep-ph",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2403.18840v1",
-    "abstract_url": "http://arxiv.org/abs/2403.18840v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2403.18840v1.pdf"
-  },
-  {
-    "title": "Towards quantum gravity with neural networks: Solving the quantum   Hamilton constraint of U(1) BF theory",
-    "authors": [
-      "Hanno Sahlmann",
-      "Waleed Sherif"
-    ],
-    "summary": "In the canonical approach of loop quantum gravity, arguably the most important outstanding problem is finding and interpreting solutions to the Hamiltonian constraint. In this work, we demonstrate that methods of machine learning are in principle applicable to this problem. We consider $U(1)$ BF theory in 3 dimensions, quantized with loop quantum gravity methods. In particular, we formulate a master constraint corresponding to Hamilton and Gauss constraints using loop quantum gravity methods. To make the problem amenable for numerical simulation we fix a graph and introduce a cutoff on the kinematical degrees of freedom, effectively considering $U_q(1)$ BF theory at a root of unity. We show that the Neural Network Quantum State (NNQS) ansatz can be used to numerically solve the constraints efficiently and accurately. We compute expectation values and fluctuations of certain observables and compare them with exact results or exact numerical methods where possible. We also study the dependence on the cutoff.",
-    "published_date": "2024-02-16T12:16:04Z",
-    "updated_date": "2024-10-17T07:37:51Z",
-    "arxiv_id": "2402.10622v2",
-    "primary_category": "gr-qc",
-    "categories": [
-      "gr-qc",
-      "hep-th",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2402.10622v2",
-    "abstract_url": "http://arxiv.org/abs/2402.10622v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2402.10622v2.pdf"
-  },
-  {
-    "title": "Neural Networks Asymptotic Behaviours for the Resolution of Inverse   Problems",
-    "authors": [
-      "Luigi Del Debbio",
-      "Manuel Naviglio",
-      "Francesco Tarantelli"
-    ],
-    "summary": "This paper presents a study of the effectiveness of Neural Network (NN) techniques for deconvolution inverse problems relevant for applications in Quantum Field Theory, but also in more general contexts. We consider NN's asymptotic limits, corresponding to Gaussian Processes (GPs), where non-linearities in the parameters of the NN can be neglected. Using these resulting GPs, we address the deconvolution inverse problem in the case of a quantum harmonic oscillator simulated through Monte Carlo techniques on a lattice. In this simple toy model, the results of the inversion can be compared with the known analytical solution. Our findings indicate that solving the inverse problem with a NN yields less performing results than those obtained using the GPs derived from NN's asymptotic limits. Furthermore, we observe the trained NN's accuracy approaching that of GPs with increasing layer width. Notably, one of these GPs defies interpretation as a probabilistic model, offering a novel perspective compared to established methods in the literature. Our results suggest the need for detailed studies of the training dynamics in more realistic set-ups.",
-    "published_date": "2024-02-14T17:42:24Z",
-    "updated_date": "2024-02-15T12:07:13Z",
-    "arxiv_id": "2402.09338v2",
-    "primary_category": "physics.comp-ph",
-    "categories": [
-      "physics.comp-ph",
-      "cs.AI",
-      "hep-lat",
-      "hep-th"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2402.09338v2",
-    "abstract_url": "http://arxiv.org/abs/2402.09338v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2402.09338v2.pdf"
-  },
-  {
-    "title": "The geodesic dispersion phenomenon in random fields dynamics",
-    "authors": [
-      "Alexandre L. M. Levada"
-    ],
-    "summary": "Random fields are ubiquitous mathematical structures in physics, with applications ranging from thermodynamics and statistical physics to quantum field theory and cosmology. Recent works on information geometry of Gaussian random fields proposed mathematical expressions for the components of the metric tensor of the underlying parametric space, allowing the computation of the curvature in each point of the manifold. In this study, our hypothesis is that time irreversibility in Gaussian random fields dynamics is a direct consequence of intrinsic geometric properties (curvature) of their parametric space. In order to validate this hypothesis, we compute the components of the metric tensor and derive the twenty seven Christoffel symbols of the metric to define the Euler-Lagrange equations, a system of partial differential equations that are used to build geodesic curves in Riemannian manifolds. After that, by the application of the fourth-order Runge-Kutta method and Markov Chain Monte Carlo simulation, we numerically build geodesic curves starting from an arbitrary initial point in the manifold. The obtained results show that, when the system undergoes phase transitions, the geodesic curve obtained by time reversing the computational simulation diverges from the original curve, showing a strange effect that we called the geodesic dispersion phenomenon, which suggests that time irreversibility in random fields is related to the intrinsic geometry of their parametric space.",
-    "published_date": "2024-01-25T19:31:55Z",
-    "updated_date": "2024-05-02T20:01:50Z",
-    "arxiv_id": "2401.14482v3",
-    "primary_category": "cs.IT",
-    "categories": [
-      "cs.IT",
-      "math-ph",
-      "math.IT",
-      "math.MP",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2401.14482v3",
-    "abstract_url": "http://arxiv.org/abs/2401.14482v3",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2401.14482v3.pdf"
-  },
-  {
-    "title": "Speeding up Fermionic Lattice Calculations with Photonic Accelerated   Inverters",
-    "authors": [
-      "Felipe Attanasio",
-      "Marc Bauer",
-      "Jelle Dijkstra",
-      "Timoteo Lee",
-      "Jan M. Pawlowski",
-      "Wolfram Pernice"
-    ],
-    "summary": "Lattice field theory (LFT) is the standard non-perturbative method to perform numerical calculations of quantum field theory. However, the typical bottleneck of fermionic lattice calculations is the inversion of the Dirac matrix. This inversion is solved by iterative methods, like the conjugate gradient algorithm, where matrix-vector multiplications (MVMs) are the main operation. Photonic integrated circuits excel in performing quick and energy-efficient MVMs, but at the same time, they are known to have low accuracy. This can be overcome by using mixed precision methods. In this paper, we explore the idea of using photonic technology to fulfil the demand for computational power of fermionic lattice calculations. These methods have the potential to reduce computation costs by one order of magnitude. Because of the hybrid nature of these methods, we call these 'photonic accelerated inverters (PAIs)'.",
-    "published_date": "2024-01-25T14:22:49Z",
-    "updated_date": "2024-01-25T14:22:49Z",
-    "arxiv_id": "2401.14200v1",
-    "primary_category": "hep-lat",
-    "categories": [
-      "hep-lat",
-      "physics.app-ph",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2401.14200v1",
-    "abstract_url": "http://arxiv.org/abs/2401.14200v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2401.14200v1.pdf"
-  },
-  {
-    "title": "MatsubaraFunctions.jl: An equilibrium Green's function library in the   Julia programming language",
-    "authors": [
-      "Dominik Kiese",
-      "Anxiang Ge",
-      "Nepomuk Ritz",
-      "Jan von Delft",
-      "Nils Wentzell"
-    ],
-    "summary": "The Matsubara Green's function formalism stands as a powerful technique for computing the thermodynamic characteristics of interacting quantum many-particle systems at finite temperatures. In this manuscript, our focus centers on introducing MatsubaraFunctions.jl, a Julia library that implements data structures for generalized n-point Green's functions on Matsubara frequency grids. The package's architecture prioritizes user-friendliness without compromising the development of efficient solvers for quantum field theories in equilibrium. Following a comprehensive introduction of the fundamental types, we delve into a thorough examination of key facets of the interface. This encompasses avenues for accessing Green's functions, techniques for extrapolation and interpolation, as well as the incorporation of symmetries and a variety of parallelization strategies. Examples of increasing complexity serve to demonstrate the practical utility of the library, supplemented by discussions on strategies for sidestepping impediments to optimal performance.",
-    "published_date": "2023-09-21T22:30:59Z",
-    "updated_date": "2023-11-28T14:01:14Z",
-    "arxiv_id": "2309.12511v2",
-    "primary_category": "cond-mat.str-el",
-    "categories": [
-      "cond-mat.str-el",
-      "cond-mat.stat-mech",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2309.12511v2",
-    "abstract_url": "http://arxiv.org/abs/2309.12511v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2309.12511v2.pdf"
-  },
-  {
-    "title": "Molecular Hessian matrices from a machine learning random forest   regression algorithm",
-    "authors": [
-      "Giorgio Domenichini",
-      "Christoph Dellago"
-    ],
-    "summary": "In this article we present a machine learning model to obtain fast and accurate estimates of the molecular Hessian matrix. In this model, based on a random forest, the second derivatives of the energy with respect to redundant internal coordinates are learned individually. The internal coordinates together with their specific representation guarantee rotational and translational invariance. The model is trained on a subset of the QM7 data set, but is shown to be applicable to larger molecules picked from the QM9 data set. From the predicted Hessian it is also possible to obtain reasonable estimates of the vibrational frequencies, normal modes and zero point energies of the molecules.",
-    "published_date": "2023-07-31T09:22:08Z",
-    "updated_date": "2023-07-31T09:22:08Z",
-    "arxiv_id": "2307.16512v1",
-    "primary_category": "physics.chem-ph",
-    "categories": [
-      "physics.chem-ph",
-      "physics.bio-ph",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2307.16512v1",
-    "abstract_url": "http://arxiv.org/abs/2307.16512v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2307.16512v1.pdf"
-  },
-  {
-    "title": "A symmetry and Noether charge preserving discretization of initial value   problems",
-    "authors": [
-      "Alexander Rothkopf",
-      "Jan Nordstr\u00f6m"
-    ],
-    "summary": "Taking insight from the theory of general relativity, where space and time are treated on the same footing, we develop a novel geometric variational discretization for second order initial value problems (IVPs). By discretizing the dynamics along a world-line parameter, instead of physical time directly, we retain manifest translation symmetry and conservation of the associated continuum Noether charge. A non-equidistant time discretization emerges dynamically, realizing a form of automatic adaptive mesh refinement (AMR), guided by the system symmetries. Using appropriately regularized summation by parts finite difference operators, the continuum Noether charge, defined via the Killing vector associated with translation symmetry, is shown to be exactly preserved in the interior of the simulated time interval. The convergence properties of the approach are demonstrated with two explicit examples.",
-    "published_date": "2023-07-10T11:28:03Z",
-    "updated_date": "2023-07-10T11:28:03Z",
-    "arxiv_id": "2307.04490v1",
-    "primary_category": "math.NA",
-    "categories": [
-      "math.NA",
-      "cs.NA",
-      "hep-lat",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2307.04490v1",
-    "abstract_url": "http://arxiv.org/abs/2307.04490v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2307.04490v1.pdf"
-  },
-  {
-    "title": "Fully general relativistic simulations of rapidly rotating quark stars:   Oscillation modes and universal relations",
-    "authors": [
-      "Kenneth Chen",
-      "Lap-Ming Lin"
-    ],
-    "summary": "(Abridged) Numerical simulation of strange quark stars (QSs) is challenging due to the strong density discontinuity at the stellar surface. In this paper, we report successful simulations of rapidly rotating QSs and study their oscillation modes in full general relativity. Building on top of the numerical relativity code \\texttt{Einstein Toolkit}, we implement a positivity-preserving Riemann solver and a dust-like atmosphere to handle the density discontinuity at the surface. We demonstrate the robustness of our numerical method by performing stable evolutions of rotating QSs close to the Keplerian limit and extracting their oscillation modes. We focus on the quadrupolar $l=|m|=2$ $f$-mode and study whether they can still satisfy the universal relations recently proposed for rotating neutron stars (NSs). We find that two of the three proposed relations can still be satisfied by rotating QSs. For the remaining broken relation, we propose a new relation to unify the NS and QS data by invoking the dimensionless spin parameter $j$. The onsets of secular instabilities for rotating QSs are also studied by analyzing the $f$-mode frequencies. Same as the result found previously for NSs, we find that QSs become unstable to the Chandrasekhar-Friedman-Schutz instability when the angular velocity of the star $\\Omega \\approx 3.4 \\sigma_0$ for sequences of constant central energy density, where $\\sigma_0$ is the mode frequency of the corresponding nonrotating configurations. For the viscosity-driven instability, we find that QSs become unstable when $j\\approx 0.881$ for both sequences of constant central energy density and constant baryon mass. Such a high value of $j$ cannot be achieved by realistic rotating NSs before reaching the Keplerian limit.",
-    "published_date": "2023-07-04T09:38:49Z",
-    "updated_date": "2023-09-01T16:57:34Z",
-    "arxiv_id": "2307.01598v2",
-    "primary_category": "gr-qc",
-    "categories": [
-      "gr-qc",
-      "astro-ph.HE",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2307.01598v2",
-    "abstract_url": "http://arxiv.org/abs/2307.01598v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2307.01598v2.pdf"
-  },
-  {
-    "title": "Boltzmann machines and quantum many-body problems",
-    "authors": [
-      "Yusuke Nomura"
-    ],
-    "summary": "Analyzing quantum many-body problems and elucidating the entangled structure of quantum states is a significant challenge common to a wide range of fields. Recently, a novel approach using machine learning was introduced to address this challenge. The idea is to \"embed\" nontrivial quantum correlations (quantum entanglement) into artificial neural networks. Through intensive developments, artificial neural network methods are becoming new powerful tools for analyzing quantum many-body problems. Among various artificial neural networks, this topical review focuses on Boltzmann machines and provides an overview of recent developments and applications.",
-    "published_date": "2023-06-29T12:00:23Z",
-    "updated_date": "2023-11-01T14:54:02Z",
-    "arxiv_id": "2306.16877v3",
-    "primary_category": "cond-mat.str-el",
-    "categories": [
-      "cond-mat.str-el",
-      "cond-mat.dis-nn",
-      "physics.comp-ph",
-      "quant-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2306.16877v3",
-    "abstract_url": "http://arxiv.org/abs/2306.16877v3",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2306.16877v3.pdf"
-  },
-  {
-    "title": "Sequential Flipping: A Donor-Acceptor Exchange Mechanism in Water Trimer",
-    "authors": [
-      "Xinrui Yang",
-      "Rui Liu",
-      "Ruiqi Xu",
-      "Zhigang Wang"
-    ],
-    "summary": "The donor-acceptor exchange (DAE) is a significant hydrogen bond network rearrangement (HBNR) mechanism because it can lead to the change of hydrogen bond direction. In this work, we report a new DAE mechanism found in water trimer that is realized by sequential flipping (SF) of all molecules rather than the well-known proton transfer (PT) process. Meanwhile, the SF process has a much smaller potential barrier (0.262 eV) than the previously predicted collective rotation process (about 1.7 eV), implying that SF process is a main flipping process that can lead to DAE. Importantly, high-precision ab initio calculations show that SF-DAE can make the water ring to show a clear chiral difference from PT-DAE, which brings the prospect of distinguishing the two confusing processes based on circular dichroism spectra. The reaction rate analysis including the quantum tunneling indicates an obvious temperature-dependent competitive relationship between SF and PT processes, specifically, the SF process dominates above 65 K, while the PT process dominates below 65 K. Therefore, in most cases, the contribution for DAE mainly comes from the flipping process, rather than the PT process as previously thought. Our work enriches the understanding of the DAE mechanism in water trimer and provides a piece of the jigsaw that has been sought to the HBNR mechanism.",
-    "published_date": "2023-06-20T01:51:13Z",
-    "updated_date": "2023-06-20T01:51:13Z",
-    "arxiv_id": "2306.11234v1",
-    "primary_category": "physics.chem-ph",
-    "categories": [
-      "physics.chem-ph",
-      "physics.atm-clus",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2306.11234v1",
-    "abstract_url": "http://arxiv.org/abs/2306.11234v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2306.11234v1.pdf"
-  },
-  {
-    "title": "The Expressivity of Classical and Quantum Neural Networks on   Entanglement Entropy",
-    "authors": [
-      "Chih-Hung Wu",
-      "Ching-Che Yen"
-    ],
-    "summary": "Analytically continuing the von Neumann entropy from R\\'enyi entropies is a challenging task in quantum field theory. While the $n$-th R\\'enyi entropy can be computed using the replica method in the path integral representation of quantum field theory, the analytic continuation can only be achieved for some simple systems on a case-by-case basis. In this work, we propose a general framework to tackle this problem using classical and quantum neural networks with supervised learning. We begin by studying several examples with known von Neumann entropy, where the input data is generated by representing $\\text{Tr} \\rho_A^n$ with a generating function. We adopt KerasTuner to determine the optimal network architecture and hyperparameters with limited data. In addition, we frame a similar problem in terms of quantum machine learning models, where the expressivity of the quantum models for the entanglement entropy as a partial Fourier series is established. Our proposed methods can accurately predict the von Neumann and R\\'enyi entropies numerically, highlighting the potential of deep learning techniques for solving problems in quantum information theory.",
-    "published_date": "2023-05-01T18:00:01Z",
-    "updated_date": "2023-05-01T18:00:01Z",
-    "arxiv_id": "2305.00997v1",
-    "primary_category": "hep-th",
-    "categories": [
-      "hep-th",
-      "physics.comp-ph",
-      "quant-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2305.00997v1",
-    "abstract_url": "http://arxiv.org/abs/2305.00997v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2305.00997v1.pdf"
-  },
-  {
-    "title": "Numerical approach to the black-to-white hole transition",
-    "authors": [
-      "Pietropaolo Frisoni"
-    ],
-    "summary": "We outline an algorithm to compute numerically the black-to-white hole transition amplitude, using the loop quantum gravity covariant formulation and the Lorentzian Engle-Pereira-Rovelli-Livine model. We apply the algorithm to calculate the crossing time of the transition in the deep quantum regime, comparing our result with previous analytical estimates of the same physical observable in the semiclassical limit. Furthermore, we show how to evaluate the crossing time analytically using an alternative approach with respect to the one currently present in the literature. This method requires much easier calculations and emphasizes that the crossing time does not depend on the extrinsic geometry of the transition.",
-    "published_date": "2023-04-05T18:41:29Z",
-    "updated_date": "2023-06-15T18:30:47Z",
-    "arxiv_id": "2304.02691v2",
-    "primary_category": "gr-qc",
-    "categories": [
-      "gr-qc",
-      "physics.comp-ph",
-      "quant-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2304.02691v2",
-    "abstract_url": "http://arxiv.org/abs/2304.02691v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2304.02691v2.pdf"
-  },
-  {
-    "title": "Locality-constrained autoregressive cum conditional normalizing flow for   lattice field theory simulations",
-    "authors": [
-      "Dinesh P. R."
-    ],
-    "summary": "Normalizing flow-based sampling methods have been successful in tackling computational challenges traditionally associated with simulating lattice quantum field theories. Further works have incorporated gauge and translational invariance of the action integral in the underlying neural networks, which have led to efficient training and inference in those models. In this paper, we incorporate locality of the action integral which leads to simplifications to the input domain of conditional normalizing flows that sample constant time sub-lattices in an autoregressive process, dubbed local-Autoregressive Conditional Normalizing Flow (l-ACNF). We find that the autocorrelation times of l-ACNF models outperform an equivalent normalizing flow model on the full lattice by orders of magnitude when sampling $\\phi^{4}$ theory on a 2 dimensional lattice.",
-    "published_date": "2023-04-04T13:55:51Z",
-    "updated_date": "2023-04-04T13:55:51Z",
-    "arxiv_id": "2304.01798v1",
-    "primary_category": "hep-lat",
-    "categories": [
-      "hep-lat",
-      "physics.comp-ph",
-      "stat.ML"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2304.01798v1",
-    "abstract_url": "http://arxiv.org/abs/2304.01798v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2304.01798v1.pdf"
-  },
-  {
-    "title": "The teaching from entanglement: 2D SU(2) antiferromagnet to valence bond   solid deconfined quantum critical points are not conformal",
-    "authors": [
-      "Yuan Da Liao",
-      "Gaopei Pan",
-      "Weilun Jiang",
-      "Yang Qi",
-      "Zi Yang Meng"
-    ],
-    "summary": "The deconfined quantum critical point (DQCP) -- the enigmatic incarnation of the quantum phase transition beyond the Landau-Ginzburg-Wilson paradigm of symmetries and their spontaneous breaking -- has been proposed and actively pursued for more than two decades. Various 2D quantum many-body lattice models, both in spin/boson and fermion representations have been tested with the state-of-the-art numerical techniques and field-theoretical analyses, and yet, the conclusion is still controversial. Experimental realizations of DQCP in the quantum magnet SrCu$_2$(BO$_3$)$_2$ and superconducting quantum criticality in 2D material have either shown first order transition or intermediate phase. The tension between the lattice scale details and the requirement from continuum limit, manifested in the form of the inconsistent critical scaling behavior and violations of generic conformal bootstrap bound, has not been resolved. Here we solve these decades-long controversies from the new and fundamental perspective of the quantum entanglement. We develop the incremental algorithm to compute the entanglement entropy at a fermionic DQCP with unprecedentedly accurate data and reveal the universal coefficient of the logarithmic correction therein is negative and at odds with positivity requirement of the conformal field theory. Together with results in other 2D DQCP lattice models (both in fermion and spin systems), our discoveries clearly demonstrate the 2D SU(2) antiferromagnet to valence bond solid DQCPs are not conformal fixed point and naturally explain the experimental difficulties in finding them. This marks the end of the beginning of unambiguous finding of the quantum phase transitions truely beyond the Landau-Ginzburg-Wilson paradigm, since its suggestion two decades ago.",
-    "published_date": "2023-02-23T02:21:03Z",
-    "updated_date": "2023-05-01T12:34:06Z",
-    "arxiv_id": "2302.11742v2",
-    "primary_category": "cond-mat.str-el",
-    "categories": [
-      "cond-mat.str-el",
-      "cond-mat.stat-mech",
-      "math-ph",
-      "math.MP",
-      "physics.comp-ph",
-      "quant-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2302.11742v2",
-    "abstract_url": "http://arxiv.org/abs/2302.11742v2",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2302.11742v2.pdf"
-  },
-  {
-    "title": "Analysis of Black Hole Solutions in Parabolic Class Using Neural   Networks",
-    "authors": [
-      "Ehsan Hatefi",
-      "Armin Hatefi",
-      "Roberto J. L\u00f3pez-Sastre"
-    ],
-    "summary": "In this paper, we introduce a numerical method based on Artificial Neural Networks (ANNs) for the analysis of black hole solutions to the Einstein-axion-dilaton system in a high dimensional parabolic class. Leveraging a profile root-finding technique based on General Relativity we describe an ANN solver to directly tackle the system of ordinary differential equations. Through our extensive numerical analysis, we demonstrate, for the first time, that there is no self-similar critical solution for the parabolic class in the high dimensions of space-time. Specifically, we develop $95\\%$ ANN-based confidence intervals for all the solutions in their domains. At the $95\\%$ confidence level, our ANN estimators confirm that there is no black hole solution in higher dimensions, hence the gravitational collapse does not occur. Results provide some doubts about the universality of the Choptuik phenomena. Therefore, we conclude that the fastest-growing mode of the perturbations that determine the critical exponent does not exist for the parabolic class in the high dimensions.",
-    "published_date": "2023-02-09T13:13:01Z",
-    "updated_date": "2023-07-23T11:09:50Z",
-    "arxiv_id": "2302.04619v4",
-    "primary_category": "gr-qc",
-    "categories": [
-      "gr-qc",
-      "hep-th",
-      "math-ph",
-      "math.MP",
-      "physics.comp-ph",
-      "physics.data-an"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2302.04619v4",
-    "abstract_url": "http://arxiv.org/abs/2302.04619v4",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2302.04619v4.pdf"
-  },
-  {
-    "title": "New methods for analytical calculation of elliptic integrals, applied in   various physical problems",
-    "authors": [
-      "Bogdan G. Dimitrov"
-    ],
-    "summary": "A short review will be made of elliptic integrals, widely applied in GPS (Global Positioning System) communications (accounting for General Relativity Theory-effects), cosmology, Black hole physics and celestial mechanics. Then a novel analytical method for calculation of zero-order elliptic integrals in the Legendre form will be presented, based on the combination of several methods from the theory of elliptic functions: 1. the recurrent system of equations for higher-order elliptic integrals in two different representations. 2. uniformization of four-dimensional algebraic equations by means of the Weierstrass elliptic function 3.a variable transformation, inversely (quadratically) proportional to a new variable. The developed method is a step forward towards constructing analytical methods, which can improve the precision of the calculation of elliptic integrals, necessary both for theoretical and experimental problems.",
-    "published_date": "2022-12-26T20:51:21Z",
-    "updated_date": "2022-12-26T20:51:21Z",
-    "arxiv_id": "2301.00643v1",
-    "primary_category": "gr-qc",
-    "categories": [
-      "gr-qc",
-      "math-ph",
-      "math.MP",
-      "physics.comp-ph"
-    ],
-    "pdf_url": "http://arxiv.org/pdf/2301.00643v1",
-    "abstract_url": "http://arxiv.org/abs/2301.00643v1",
-    "local_pdf_path": "data\\arxiv\\pdfs\\computational_physics\\2301.00643v1.pdf"
-  }
-]

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