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1

Godwal, B. K. "Computational condensed matter physics." Bulletin of Materials Science 22, no. 5 (August 1999): 877–84. http://dx.doi.org/10.1007/bf02745548.

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2

Stephen, David T., Hendrik Poulsen Nautrup, Juani Bermejo-Vega, Jens Eisert, and Robert Raussendorf. "Subsystem symmetries, quantum cellular automata, and computational phases of quantum matter." Quantum 3 (May 20, 2019): 142. http://dx.doi.org/10.22331/q-2019-05-20-142.

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Quantum phases of matter are resources for notions of quantum computation. In this work, we establish a new link between concepts of quantum information theory and condensed matter physics by presenting a unified understanding of symmetry-protected topological (SPT) order protected by subsystem symmetries and its relation to measurement-based quantum computation (MBQC). The key unifying ingredient is the concept of quantum cellular automata (QCA) which we use to define subsystem symmetries acting on rigid lower-dimensional lines or fractals on a 2D lattice. Notably, both types of symmetries are treated equivalently in our framework. We show that states within a non-trivial SPT phase protected by these symmetries are indicated by the presence of the same QCA in a tensor network representation of the state, thereby characterizing the structure of entanglement that is uniformly present throughout these phases. By also formulating schemes of MBQC based on these QCA, we are able to prove that most of the phases we construct are computationally universal phases of matter, in which every state is a resource for universal MBQC. Interestingly, our approach allows us to construct computational phases which have practical advantages over previous examples, including a computational speedup. The significance of the approach stems from constructing novel computationally universal phases of matter and showcasing the power of tensor networks and quantum information theory in classifying subsystem SPT order.
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3

McClintock, Peter V. E. "Experimental and Computational Techniques in Soft Condensed Matter Physics, edited by Jeffrey Olafsen." Contemporary Physics 52, no. 5 (September 2011): 486. http://dx.doi.org/10.1080/00107514.2011.580058.

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4

Karney, Charles F. F. "Modern computational techniques in plasma physics." Physics of Plasmas 5, no. 5 (May 1998): 1632–35. http://dx.doi.org/10.1063/1.872831.

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5

Schultz, D. R., P. S. Krstic, T. Minami, M. S. Pindzola, F. J. Robicheaux, J. P. Colgan, S. D. Loch, et al. "Computational atomic physics for plasma edge modeling." Contributions to Plasma Physics 44, no. 13 (April 2004): 247–51. http://dx.doi.org/10.1002/ctpp.200410036.

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6

Janatipour, Najmeh, Zabiollah Mahdavifar, Siamak Noorizadeh, and Fazel Shojaei. "Modifying the electronic and geometrical properties of mono/bi-layer graphite-like BC2N via alkali metal (Li, Na) adsorption and intercalation: computational approach." New Journal of Chemistry 43, no. 33 (2019): 13122–33. http://dx.doi.org/10.1039/c9nj02260k.

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7

Probert, Matt. "Symmetry and Condensed Matter Physics – A Computational Approach, by M. El-Batanouny and F. Wooten." Contemporary Physics 51, no. 5 (September 2010): 457–58. http://dx.doi.org/10.1080/00107510903395937.

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8

BINDER, K. "LARGE-SCALE SIMULATIONS IN CONDENSED MATTER PHYSICS —THE NEED FOR A TERAFLOP COMPUTER." International Journal of Modern Physics C 03, no. 03 (June 1992): 565–81. http://dx.doi.org/10.1142/s0129183192000373.

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The introduction of vector processors {“supercomputers” with a performance in the range of 109 floating point operations (1 GFLOP) per second} has had an enormous impact on computational condensed matter physics. The possibility of a substantially enhanced performance by massively parallel processors (“teraflop” machines with 1012 floating point operations per second) will allow satisfactory treatment of a large range of important scientific problems which have to a great extent thus far escaped numerical resolution. The present paper describes only a few examples (out of a long list of interesting research problems!) for which the availability of “teraflops” will allow spectacular progress, i.e., the modelling of dense macromolecular systems and metallic alloys by molecular dynamics and Monte Carlo simulations.
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9

Pursky, O. I., T. V. Dubovyk, V. O. Babenko, V. F. Gamaliy, R. A. Rasulov, and R. P. Romanenko. "Computational method for studying the thermal conductivity of molecular crystals in the course of condensed matter physics." Journal of Physics: Conference Series 1840, no. 1 (March 1, 2021): 012015. http://dx.doi.org/10.1088/1742-6596/1840/1/012015.

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10

Smit, Berend. "Computational physics in petrochemical industry." Physica Scripta T66 (January 1, 1996): 80–84. http://dx.doi.org/10.1088/0031-8949/1996/t66/010.

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11

Poliukhin, A. S., S. A. Dyachkov, A. A. Malyugin, and P. R. Levashov. "A wide-range semiclassical self-consistent average atom model." Physics of Plasmas 30, no. 1 (January 2023): 012711. http://dx.doi.org/10.1063/5.0130872.

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The discovery of material properties at extremes, which are essential for high energy density physics development, requires the most advanced experimental facilities, theories, and computations. Nowadays, it is possible to model properties of matter in such conditions using the state-of-the-art density functional theory (DFT) or path-integral Monte Carlo approaches with remarkable precision. However, fundamental and computational limitations of these methods impede their practical usage, while wide-range thermodynamic and transport models of plasma are required. As a consequence, an average atom (AA) framework is still relevant today and has been attracting more and more attention lately. The self-consistent field and electron density in an atomic cell is usually obtained using the Thomas–Fermi (TF), Hartree–Fock, Kohn–Sham approaches, or their extensions. In this study, we present the AA model, where semiclassical wave functions are used for bound states, while free electrons are approximated by the TF model with a thermodynamically consistent energy boundary. The model is compared in various regions of temperatures and pressures with the reference data: the Saha model for rarefied plasma, DFT for warm dense matter, and experimental shock Hugoniot data. It is demonstrated that a single AA model may provide a reasonable agreement with the established techniques at low computational cost and with stable convergence of the self-consistent field.
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12

Qin, Mingpu, Thomas Schäfer, Sabine Andergassen, Philippe Corboz, and Emanuel Gull. "The Hubbard Model: A Computational Perspective." Annual Review of Condensed Matter Physics 13, no. 1 (March 10, 2022): 275–302. http://dx.doi.org/10.1146/annurev-conmatphys-090921-033948.

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The Hubbard model is the simplest model of interacting fermions on a lattice and is of similar importance to correlated electron physics as the Ising model is to statistical mechanics or the fruit fly to biomedical science. Despite its simplicity, the model exhibits an incredible wealth of phases, phase transitions, and exotic correlation phenomena. Although analytical methods have provided a qualitative description of the model in certain limits, numerical tools have shown impressive progress in achieving quantitative accurate results over the past several years. This article gives an introduction to the model, motivates common questions, and illustrates the progress that has been achieved over recent years in revealing various aspects of the correlation physics of the model.
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13

SOMMA, ROLANDO, HOWARD BARNUM, EMANUEL KNILL, GERARDO ORTIZ, and LORENZO VIOLA. "GENERALIZED ENTANGLEMENT AND QUANTUM PHASE TRANSITIONS." International Journal of Modern Physics B 20, no. 19 (July 30, 2006): 2760–69. http://dx.doi.org/10.1142/s0217979206035266.

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Quantum phase transitions in matter are characterized by qualitative changes in some correlation functions of the system, which are ultimately related to entanglement. In this work, we study the second-order quantum phase transitions present in models of relevance to condensed-matter physics by exploiting the notion of generalized entanglement [Barnum et al., Phys. Rev. A 68, 032308 (2003)]. In particular, we focus on the illustrative case of a one-dimensional spin-1/2 Ising model in the presence of a transverse magnetic field. Our approach leads to tools useful for distinguishing between the ordered and disordered phases in the case of broken-symmetry quantum phase transitions. Possible extensions to the study of other kinds of phase transitions as well as of the relationship between generalized entanglement and computational efficiency are also discussed.
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14

Ivanov, M. S., and S. F. Gimelshein. "COMPUTATIONAL HYPERSONIC RAREFIED FLOWS." Annual Review of Fluid Mechanics 30, no. 1 (January 1998): 469–505. http://dx.doi.org/10.1146/annurev.fluid.30.1.469.

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15

SUGAR, R. L. "NUMERICAL STUDIES OF MANY ELECTRON SYSTEMS." International Journal of Modern Physics C 01, no. 02n03 (September 1990): 215–32. http://dx.doi.org/10.1142/s0129183190000128.

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The numerical simulation of many electron systems in condensed matter physics is described. Numerical algorithms are discussed in detail, and results are presented from simulations of the Hubbard model in two and three dimensions.
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16

Morley, P. D., and D. J. Buettner. "Dark matter in the local group of galaxies." International Journal of Modern Physics D 26, no. 07 (January 19, 2017): 1750069. http://dx.doi.org/10.1142/s0218271817500699.

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We describe the neutrino flavor ([Formula: see text], [Formula: see text], [Formula: see text]) masses as [Formula: see text] [Formula: see text] with [Formula: see text] and probably [Formula: see text]. The quantity [Formula: see text] is the degenerate neutrino mass. Because neutrino flavor is not a quantum number, this degenerate mass appears in the neutrino equation-of-state [P. D. Morley and D. J. Buettner, Int. J. Mod. Phys. D (2014), doi:10.1142/s0218271815500042.]. We apply a Monte Carlo computational physics technique to the Local Group (LG) of galaxies to determine an approximate location for a Dark Matter embedding Condensed Neutrino Object (CNO) [P. D. Morley and D. J. Buettner, Int. J. Mod. Phys. D (2016), doi:10.1142/s0218271816500899.]. The calculation is based on the rotational properties of the only spiral galaxies within the LG: M31, M33 and the Milky Way. CNOs could be the Dark Matter everyone is looking for and we estimate the CNO embedding the LG to have a mass 5.17[Formula: see text] M[Formula: see text] and a radius 1.316 Mpc, with the estimated value of [Formula: see text] eV[Formula: see text]/c2. The up-coming KATRIN experiment [https://www.katrin.kit.edu.] will either be the definitive result or eliminate condensed neutrinos as a Dark Matter candidate.
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17

Söderlind, Per, G. Kotliar, K. Haule, P. M. Oppeneer, and D. Guillaumont. "Computational modeling of actinide materials and complexes." MRS Bulletin 35, no. 11 (November 2010): 883–88. http://dx.doi.org/10.1557/mrs2010.715.

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In spite of being rare, actinide elements provide the building blocks for many fascinating condensed-matter systems, both from an experimental and theoretical perspective. Experimental observations of actinide materials are difficult because of rarity, toxicity, radioactivity, and even safety and security. Theory, on the other hand, has its own challenges. Complex crystal and electronic structures are often encountered in actinide materials, as well as pronounced electron correlation effects. Consequently, theoretical modeling of actinide materials and their 5f electronic states is very difficult. Here, we review recent theoretical efforts to describe and sometimes predict the behavior of actinide materials and complexes, such as phase stability including density functional theory (DFT), DFT in conjunction with an additional Coulomb repulsion U (DFT+U), and DFT in combination with dynamical mean-field theory (DFT+DMFT).
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18

Hurst, Jérôme, Paul-Antoine Hervieux, and Giovanni Manfredi. "Phase-space methods for the spin dynamics in condensed matter systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, no. 2092 (March 20, 2017): 20160199. http://dx.doi.org/10.1098/rsta.2016.0199.

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Using the phase-space formulation of quantum mechanics, we derive a four-component Wigner equation for a system composed of spin- fermions (typically, electrons) including the Zeeman effect and the spin–orbit coupling. This Wigner equation is coupled to the appropriate Maxwell equations to form a self-consistent mean-field model. A set of semiclassical Vlasov equations with spin effects is obtained by expanding the full quantum model to first order in the Planck constant. The corresponding hydrodynamic equations are derived by taking velocity moments of the phase-space distribution function. A simple closure relation is proposed to obtain a closed set of hydrodynamic equations. This article is part of the themed issue ‘Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces’.
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19

Maung, Aung Phone, and Chung Hao Hsu. "A Study on Phonon-Mediated Thermal Transport and Lattice Thermal Conductivity Prediction Using First-Principles Calculations." Key Engineering Materials 847 (June 2020): 120–26. http://dx.doi.org/10.4028/www.scientific.net/kem.847.120.

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The systematic theoretical approaches and atomistic simulation programs to predict thermal properties of crystalline nanostructured materials within first-principles framework are studied here. Recent progress in computational power has enabled an accurate and reliable way to investigate nanoscale thermal transport in crystalline materials using first-principles based calculations. Extracting a large set of anharmonic force constants with low computational effort remains a big challenge in lattice dynamics and condensed-matter physics. This paper focuses on recent progress in first-principles phonon calculations for semiconductor materials and summarizes advantages and limitations of each approach and simulation programs by comparing accuracy of numerical solutions, computational load and calculating feasibility to a wide range of crystalline materials. This work also reviews and presents the coupling model of first-principles molecular dynamic (FPMD) approach that can extract anharmonic force constants directly and solution of linearized Boltzmann transport equation to predict phonon-mediated lattice thermal conductivity of crystalline materials.
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20

METWALLY, NASSER, M. ABDEL-ATY, and M. SEBAWE ABDALLA. "CONTROLLING THE QUANTUM COMPUTATIONAL SPEED." International Journal of Modern Physics B 22, no. 24 (September 30, 2008): 4143–51. http://dx.doi.org/10.1142/s0217979208049029.

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The speed of quantum computation is investigated through the time evolution of the speed of the orthogonality. The external field components for classical treatment besides the detuning and the coupling parameters for quantum treatment play important roles on the computational speed. It has been shown that the number of photons has no significant effect on the speed of computation. However, it is very sensitive to the variation in both detuning and the interaction coupling parameters.
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21

Xu, Ziyang, Lijuan Gao, Pengyu Chen, and Li-Tang Yan. "Diffusive transport of nanoscale objects through cell membranes: a computational perspective." Soft Matter 16, no. 16 (2020): 3869–81. http://dx.doi.org/10.1039/c9sm02338k.

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Clarifying the diffusion dynamics of nanoscale objects with cell membrane is critical for revealing fundamental physics in biological systems. This perspective highlights the advances in computational and theoretical aspects of this emerging field.
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22

Reardon, Jonathan, Joseph A. Schetz, and K. Todd Lowe. "Computational Modeling of Total-Temperature Probes." Journal of Thermophysics and Heat Transfer 31, no. 3 (July 2017): 609–20. http://dx.doi.org/10.2514/1.t4991.

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23

Lee, Seongbok, D. M. Bylander, Suck Whan Kim, and Leonard Kleinman. "Computational search for the real tetragonalB50." Physical Review B 45, no. 7 (February 15, 1992): 3248–51. http://dx.doi.org/10.1103/physrevb.45.3248.

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24

Schneider, Kai, and Oleg V. Vasilyev. "Wavelet Methods in Computational Fluid Dynamics." Annual Review of Fluid Mechanics 42, no. 1 (January 2010): 473–503. http://dx.doi.org/10.1146/annurev-fluid-121108-145637.

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25

Boris, J. P. "New Directions in Computational Fluid Dynamics." Annual Review of Fluid Mechanics 21, no. 1 (January 1989): 345–85. http://dx.doi.org/10.1146/annurev.fl.21.010189.002021.

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26

Rubin, S. G., and J. C. Tannehill. "Parabolized/Reduced Navier-Stokes Computational Techniques." Annual Review of Fluid Mechanics 24, no. 1 (January 1992): 117–44. http://dx.doi.org/10.1146/annurev.fl.24.010192.001001.

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27

Turkel, E. "PRECONDITIONING TECHNIQUES IN COMPUTATIONAL FLUID DYNAMICS." Annual Review of Fluid Mechanics 31, no. 1 (January 1999): 385–416. http://dx.doi.org/10.1146/annurev.fluid.31.1.385.

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28

Wang, Meng, Jonathan B. Freund, and Sanjiva K. Lele. "COMPUTATIONAL PREDICTION OF FLOW-GENERATED SOUND." Annual Review of Fluid Mechanics 38, no. 1 (January 2006): 483–512. http://dx.doi.org/10.1146/annurev.fluid.38.050304.092036.

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29

Cai, Zi. "Symmetries and effect of time dimension in non-equilibrium quantum matter." Acta Physica Sinica 70, no. 23 (2021): 230310. http://dx.doi.org/10.7498/aps.70.20211741.

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Non-equilibrium quantum many-body systems have attracted considerable attention in the past decades. The scope of the research of this kind of novel system involves interdisciplinary research of condensed matter, atomic and molecular physics, quantum optics, quantum information and quantum computation, as well as the non-equilibrium statistical physics. The non-equilibrium phenomena emerging from the aforementioned quantum systems can exhibit rich and universal behaviors, which have far from being well understood due to the novelties and complexities of these systems, and hence the quantum many-body physics becomes the research highlight. At the same time, with the rapid development of quantum techniques, the understanding of these complex systems is of important practical significance due to their potential applications in quantum computation and quantum manipulation. In this paper, we show our recent progress of non-equilibrium quantum many-body systems. We focus on the novel phenomena closely related to the temporary symmetry breaking, including the exotic quantum matter, quasi-particles as well as the dynamical universality classes in non-equilibrium quantum many-body systems.
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30

Giruzzi, G., J. Garcia, J. F. Artaud, V. Basiuk, J. Decker, F. Imbeaux, Y. Peysson, and M. Schneider. "Advances on modelling of ITER scenarios: physics and computational challenges." Plasma Physics and Controlled Fusion 53, no. 12 (November 14, 2011): 124010. http://dx.doi.org/10.1088/0741-3335/53/12/124010.

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31

Kösters, Dominique J., Bryan A. Kortman, Irem Boybat, Elena Ferro, Sagar Dolas, Roberto Ruiz de Austri, Johan Kwisthout, et al. "Benchmarking energy consumption and latency for neuromorphic computing in condensed matter and particle physics." APL Machine Learning 1, no. 1 (March 1, 2023): 016101. http://dx.doi.org/10.1063/5.0116699.

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The massive use of artificial neural networks (ANNs), increasingly popular in many areas of scientific computing, rapidly increases the energy consumption of modern high-performance computing systems. An appealing and possibly more sustainable alternative is provided by novel neuromorphic paradigms, which directly implement ANNs in hardware. However, little is known about the actual benefits of running ANNs on neuromorphic hardware for use cases in scientific computing. Here, we present a methodology for measuring the energy cost and compute time for inference tasks with ANNs on conventional hardware. In addition, we have designed an architecture for these tasks and estimate the same metrics based on a state-of-the-art analog in-memory computing (AIMC) platform, one of the key paradigms in neuromorphic computing. Both methodologies are compared for a use case in quantum many-body physics in two-dimensional condensed matter systems and for anomaly detection at 40 MHz rates at the Large Hadron Collider in particle physics. We find that AIMC can achieve up to one order of magnitude shorter computation times than conventional hardware at an energy cost that is up to three orders of magnitude smaller. This suggests great potential for faster and more sustainable scientific computing with neuromorphic hardware.
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32

Luo, Yu-Chen, and Xiao-Peng Li. "Quantum simulation of interacting fermions." Acta Physica Sinica 71, no. 22 (2022): 226701. http://dx.doi.org/10.7498/aps.71.20221756.

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Fermions are basic building blocks in the standard model. Interactions among these elementary particles determine how they assemble and consequently form various states of matter in our nature. Simulating fermionic degrees of freedom is also a central problem in condensed matter physics and quantum chemistry, which is crucial to understanding high-temperature superconductivity, quantum magnetism and molecular structure and functionality. However, simulating interacting fermions by classical computing generically face the minus sign problem, encountering the exponential computation complexity. Ultracold atoms provide an ideal experimental platform for quantum simulation of interacting fermions. This highly-controllable system enables the realizing of nontrivial fermionic models, by which the physical properties of the models can be obtained by measurements in experiment. This deepens our understanding of related physical mechanisms and help determine the key parameters. In recent years, there have been versatile experimental studies on quantum ground state physics, finite temperature thermal equilibrium, and quantum many-body dynamics, in fermionic quantum simulation systems. Quantum simulation offers an access to the physical problems that are intractable on the classical computer, including studying macroscopic quantum phenomena and microscopic physical mechanisms, which demonstrates the quantum advantages of controllable quantum systems. This paper briefly introduces the model of interacting fermions describing the quantum states of matter in such a system. Then we discuss various states of matter, which can arise in interacting fermionic quantum systems, including Cooper pair superfluids and density-wave orders. These exotic quantum states play important roles in describing high-temperature superconductivity and quantum magnetism, but their simulations on the classical computers have exponentially computational cost. Related researches on quantum simulation of interacting fermions in determining the phase diagrams and equation of states reflect the quantum advantage of such systems.
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33

Hasnip, Philip J., Keith Refson, Matt I. J. Probert, Jonathan R. Yates, Stewart J. Clark, and Chris J. Pickard. "Density functional theory in the solid state." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2011 (March 13, 2014): 20130270. http://dx.doi.org/10.1098/rsta.2013.0270.

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Density functional theory (DFT) has been used in many fields of the physical sciences, but none so successfully as in the solid state. From its origins in condensed matter physics, it has expanded into materials science, high-pressure physics and mineralogy, solid-state chemistry and more, powering entire computational subdisciplines. Modern DFT simulation codes can calculate a vast range of structural, chemical, optical, spectroscopic, elastic, vibrational and thermodynamic phenomena. The ability to predict structure–property relationships has revolutionized experimental fields, such as vibrational and solid-state NMR spectroscopy, where it is the primary method to analyse and interpret experimental spectra. In semiconductor physics, great progress has been made in the electronic structure of bulk and defect states despite the severe challenges presented by the description of excited states. Studies are no longer restricted to known crystallographic structures. DFT is increasingly used as an exploratory tool for materials discovery and computational experiments, culminating in ex nihilo crystal structure prediction, which addresses the long-standing difficult problem of how to predict crystal structure polymorphs from nothing but a specified chemical composition. We present an overview of the capabilities of solid-state DFT simulations in all of these topics, illustrated with recent examples using the CASTEP computer program.
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34

Cornille, B. S., M. T. Beidler, S. Munaretto, B. E. Chapman, D. Del-Castillo-Negrete, N. C. Hurst, J. S. Sarff, and C. R. Sovinec. "Computational study of runaway electrons in MST tokamak discharges with applied resonant magnetic perturbation." Physics of Plasmas 29, no. 5 (May 2022): 052510. http://dx.doi.org/10.1063/5.0087314.

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A numerical study of magnetohydrodynamics (MHD) and tracer-particle evolution investigates the effects of resonant magnetic perturbations (RMPs) on the confinement of runaway electrons (REs) in tokamak discharges conducted in the Madison Symmetric Torus. In computational results of applying RMPs having a broad toroidal spectrum but a single poloidal harmonic, m = 1 RMP does not suppress REs, whereas m = 3 RMP achieves significant deconfinement but not the complete suppression obtained in the experiment [Munaretto et al., Nuclear Fusion 60, 046024 (2020)]. MHD simulations with the NIMROD code produce sawtooth oscillations, and the associated magnetic reconnection can affect the trajectory of REs starting in the core region. Simulations with m = 3 RMP produce chaotic magnetic topology over the outer region, but the m = 1 RMP produces negligible changes in field topology, relative to applying no RMP. Using snapshots of the MHD simulation fields, full-orbit relativistic electron test particle computations with KORC show [Formula: see text] loss from the m = 3 RMP compared to the [Formula: see text] loss from the m = 1 RMP. Test particle computations of the m = 3 RMP in the time-evolving MHD simulation fields show correlation between MHD activity and late-time particle losses, but total electron confinement is similar to computations using magnetic-field snapshots.
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35

Yang, M., D. del-Castillo-Negrete, G. Zhang, and M. T. Beidler. "A divergence-free constrained magnetic field interpolation method for scattered data." Physics of Plasmas 30, no. 3 (March 2023): 033901. http://dx.doi.org/10.1063/5.0138905.

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An interpolation method to evaluate magnetic fields, given its unstructured and scattered magnetic data, is presented. The method is based on the reconstruction of the global magnetic field using a superposition of orthogonal functions. The coefficients of the expansion are obtained by minimizing a cost function defined as the L2 norm of the difference between the ground truth and the reconstructed magnetic field evaluated on the training data. The divergence-free condition is incorporated as a constraint in the cost function, allowing the method to achieve arbitrarily small errors in the magnetic field divergence. An exponential decay of the approximation error is observed and compared with the less favorable algebraic decay of local splines. Compared to local methods involving computationally expensive search algorithms, the proposed method exhibits a significant reduction of the computational complexity of the field evaluation, while maintaining a small error in the divergence even in the presence of magnetic islands and stochasticity. Applications to the computation of Poincaré sections using data obtained from numerical solutions of the magnetohydrodynamic equations in toroidal geometry are presented and compared with local methods currently in use.
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36

Dressler, Marco. "Computational Rheology." Applied Rheology 12, no. 6 (December 1, 2002): 280–81. http://dx.doi.org/10.1515/arh-2002-0032.

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37

Nance, Robert P., Brian R. Hollis, Thomas J. Horvath, Stephen J. Alter, and H. A. Hassan. "Computational Study of Hypersonic Transitional Wake Flow." Journal of Thermophysics and Heat Transfer 13, no. 2 (April 1999): 236–42. http://dx.doi.org/10.2514/2.6441.

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38

Chinappi, Mauro, Fabio Cecconi, and Carlo Massimo Casciola. "Computational analysis of maltose binding protein translocation." Philosophical Magazine 91, no. 13-15 (May 2011): 2034–48. http://dx.doi.org/10.1080/14786435.2011.557670.

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39

Campbell, Eric J., and Prosenjit Bagchi. "A computational model of amoeboid cell swimming." Physics of Fluids 29, no. 10 (October 2017): 101902. http://dx.doi.org/10.1063/1.4990543.

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Huang, Jialong, Chi Wang, Lijie Chang, Ya Zhang, Zhebin Wang, Lin Yi, and Wei Jiang. "Computational characterization of electron-beam-sustained plasma." Physics of Plasmas 26, no. 6 (June 2019): 063502. http://dx.doi.org/10.1063/1.5091466.

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41

Abraham, Farid F. "Computational statistical mechanics methodology, applications and supercomputing." Advances in Physics 35, no. 1 (January 1986): 1–111. http://dx.doi.org/10.1080/00018738600101851.

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42

Roache, P. J. "QUANTIFICATION OF UNCERTAINTY IN COMPUTATIONAL FLUID DYNAMICS." Annual Review of Fluid Mechanics 29, no. 1 (January 1997): 123–60. http://dx.doi.org/10.1146/annurev.fluid.29.1.123.

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43

Agarwal, Ramesh. "COMPUTATIONAL FLUID DYNAMICS OF WHOLE-BODY AIRCRAFT." Annual Review of Fluid Mechanics 31, no. 1 (January 1999): 125–69. http://dx.doi.org/10.1146/annurev.fluid.31.1.125.

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44

Kim, H. D., J. H. Lee, T. Setoguchi, and S. Matsuo. "Computational analysis of a variable ejector flow." Journal of Thermal Science 15, no. 2 (June 2006): 140–44. http://dx.doi.org/10.1007/s11630-006-0140-5.

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45

Hu, H., S. S. Wu, and S. C. M. Yu. "Computational studies of lobed forced mixer flows." Journal of Thermal Science 7, no. 1 (March 1998): 22–28. http://dx.doi.org/10.1007/s11630-998-0021-1.

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46

Ali, Karmina K., Resat Yilmazer, and M. S. Osman. "Extended Calogero-Bogoyavlenskii-Schiff equation and its dynamical behaviors." Physica Scripta 96, no. 12 (November 15, 2021): 125249. http://dx.doi.org/10.1088/1402-4896/ac35c5.

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Abstract In this paper, we consider an extended Calogero-Bogoyavlenskii-Schiff (eCBS) equation. Based on a logarithmic derivative transform and with the aid of symbolic computation, we construct complex multiple solitons for this nonlinear model. Also, by using a symbolic computational method, one-lump solution, two-soliton solution, localized and breather wave solution, as well as a periodic wave solution and multiple wave solutions are obtained. The constraint conditions which ensure the validity of the wave structures are also reported. Besides, the graphs of the solution attained are recorded in 3D graphs by fixing parameters to discuss their dynamical properties. The achieved outcomes show that the applied computational strategy is direct, efficient, concise and can be implemented in more complex phenomena with the assistant of symbolic computations.
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47

Hutter, Jürg, Marcella Iannuzzi, Florian Schiffmann, and Joost VandeVondele. "cp2k: atomistic simulations of condensed matter systems." Wiley Interdisciplinary Reviews: Computational Molecular Science 4, no. 1 (June 13, 2013): 15–25. http://dx.doi.org/10.1002/wcms.1159.

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48

Dovesi, Roberto, Alessandro Erba, Roberto Orlando, Claudio M. Zicovich-Wilson, Bartolomeo Civalleri, Lorenzo Maschio, Michel Rérat, et al. "Quantum-mechanical condensed matter simulations with CRYSTAL." Wiley Interdisciplinary Reviews: Computational Molecular Science 8, no. 4 (March 4, 2018): e1360. http://dx.doi.org/10.1002/wcms.1360.

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49

Mazumder, Sandip. "Modeling Full-Scale Monolithic Catalytic Converters: Challenges and Possible Solutions." Journal of Heat Transfer 129, no. 4 (July 24, 2006): 526–35. http://dx.doi.org/10.1115/1.2709655.

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Modeling full-scale monolithic catalytic converters using state-of-the-art computational fluid dynamics algorithms and techniques encounters a classical multiscale problem: the channels within the monolith have length scales that are ∼1–2 mm, while the converter itself has a length scale that is ∼5–10 cm. This necessitates very fine grids to resolve all the length scales, resulting in few million computational cells. When complex heterogeneous chemistry is included, the computational problem becomes all but intractable unless massively parallel computation is employed. Two approaches to address this difficulty are reviewed, and their effectiveness demonstrated for the computation of full-scale catalytic converters with complex chemistry. The first approach is one where only the larger scales are resolved by a grid, while the physics at the smallest scale (channel scale) are modeled using subgrid scale models whose development entails detailed flux balances at the “imaginary” fluid–solid interfaces within each computational cell. The second approach makes use of the in situ adaptive tabulation algorithm, after significant reformulation of the underlying mathematics, to accelerate computation of the surface reaction boundary conditions. Preliminary results shown here for a catalytic combustion application involving 19 species and 24 reactions indicate that both methods have the potential of improving computational efficiency by several orders of magnitude.
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Corsi, Pietro, Álvaro González García, Elia Roma, Tecla Gasperi, and Barbara Capone. "Coarse graining and adsorption in bottlebrush–colloid mixtures." Soft Matter 17, no. 13 (2021): 3681–87. http://dx.doi.org/10.1039/d1sm00141h.

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