Skip to main content Accessibility help
×
Hostname: page-component-8448b6f56d-42gr6 Total loading time: 0 Render date: 2024-04-19T16:14:20.150Z Has data issue: false hasContentIssue false

References

Published online by Cambridge University Press:  17 November 2017

Federico Becca
Affiliation:
National Research Council (CNR)
Sandro Sorella
Affiliation:
Scuola Internazionale Superiore di Studi Avanzati, Trieste
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allen, M. P., and Tildesley, D. J. 1987. Computer Simulation of Liquids. Oxford University Press.
Anderson, H. 1986. Metropolis, Monte Carlo and the MANIAC. Los Alamos Science, 14, 96–108.Google Scholar
Anderson, J. B. 1975. Random walk simulation of the Schrödinger equation: He+. J. Chem. Phys., 63, 1499–1503.Google Scholar
Anderson, J. B. 1976. Quantum chemistry by random walk. J. Chem. Phys., 65, 4121–4127.Google Scholar
Anderson, P. W. 1987. The resonating valence bond state in La2CuO4 and superconductiv- ity. Science, 235, 1196–1198.Google Scholar
Anderson, P. W., Baskaran, G., Zou, Z., and Hsu, T. 1987. Resonating-valence-bond theory of phase transitions and superconductivity in La2CuO4-based compounds. Phys. Rev. Lett., 58, 2790–2793.Google Scholar
Aoki, H., Tsuji, N., Eckstein, M., Kollar, M., Oka, T., and Werner, P. 2014. Non-equilibrium dynamical mean-field theory and its applications. Rev. Mod. Phys., 86, 779–837.Google Scholar
Arovas, D., Schrieffer, J. R., and Wilczek, F. 1984. Fractional statistics and the quantum Hall effect. Phys. Rev. Lett., 53, 722–723.Google Scholar
Bajdich, M., Mitas, L., Drobny, G., Wagner, L. K., and Schmidt, K. E. 2006. Pfaffian pairing wave functions in electronic-structure quantum Monte Carlo simulations. Phys. Rev. Lett., 96, 130201.Google Scholar
Bajdich, M., Mitas, L., Wagner, L. K., and Schmidt, K. E. 2008. Pfaffian pairing and backflow wave functions for electronic-structure quantum Monte Carlo methods. Phys. Rev. B, 77, 115112.Google Scholar
Baldereschi, A. 1973. Mean-value point in the Brillouin zone. Phys. Rev. B, 7, 5212–5215.Google Scholar
Bardeen, J., Cooper, L. N., and Schrieffer, J. R. 1957. Theory of superconductivity. Phys. Rev., 108, 1175–1204.Google Scholar
Baroni, S., and Moroni, S. 1998. Reptation quantum Monte Carlo. arXiv:cond-mat/ 9808213.
Bartlett, R. J. 1981. Many-body perturbation theory and coupled cluster theory for electron correlation in molecules. Ann. Rev. Phys. Chem., 32, 359–401.Google Scholar
Baskaran, G., and Anderson, P. W. 1988. Gauge theory of high-temperature superconduc- tors and strongly correlated Fermi systems. Phys. Rev. B, 37, 580–583.Google Scholar
Bethe, H. 1931. Zur Theorie der metalle. I. eigenwerte und eigenfunktionen der linearen atomkette. Z. Phys., 71, 205–226.Google Scholar
Bouchaud, J. P., Georges, A., and Lhuillier, C. 1988. Pair wave functions for strongly cor- related fermions and their determinantal representation. J. Phys. (Paris), 49, 553–559.Google Scholar
Calandra Buonaura, M., and Sorella, S. 1998. Numerical study of the two-dimensional Heisenberg model using a Green function Monte Carlo technique with a fixed number of walkers. Phys. Rev. B, 57, 11446–11456.Google Scholar
Capello, M., Becca, F., Fabrizio, M., Sorella, S., and Tosatti, E. 2005. Variational description of Mott insulators. Phys. Rev. Lett., 94, 026406.Google Scholar
Capello, M., Becca, F., Yunoki, S., and Sorella, S. 2006. Unconventional metal-insulator transition in two dimensions. Phys. Rev. B, 73, 245116.Google Scholar
Capello, M., Becca, F., Fabrizio, M., and Sorella, S. 2007. Superfluid to Mott-insulator transition in Bose-Hubbard models. Phys. Rev. Lett., 99, 056402.Google Scholar
Capello, M., Becca, F., Fabrizio, M., and Sorella, S. 2008. Mott transition in bosonic systems: insights from the variational approach. Phys. Rev. B, 77, 144517.Google Scholar
Capriotti, L., Becca, F., Parola, A., and Sorella, S. 2001. Resonating valence bond wave functions for strongly frustrated spin systems. Phys. Rev. Lett., 87, 097201.Google Scholar
Carleo, G., Becca, F., Schiro, M., and Fabrizio, M. 2012. Localization and glassy dynamics of many-body quantum system. Sci. Rep., 2, 243.Google Scholar
Carleo, G., Becca, F., Sanchez-Palencia, L., Sorella, S., and Fabrizio, M. 2014. Light-cone effect and supersonic correlations in one- and two-dimensional bosonic superfluids. Phys. Rev. A, 89, 031602.Google Scholar
Casula, M., Filippi, C., and Sorella, S. 2005. Diffusion Monte Carlo method with lattice regularization. Phys. Rev. Lett., 95, 100201.Google Scholar
Ceperley, D., Chester, G. V., and Kalos, M.H. 1977. Monte Carlo simulation of a many- fermion study. Phys. Rev. B, 16, 3081–3099.Google Scholar
Ceperley, D. M. 1991. Fermion nodes. J. Stat. Phys., 63, 1237–1267.Google Scholar
Ceperley, D. M., and Alder, B. J. 1980. Ground state of the electron gas by a stochastic method. Phys. Rev. Lett., 45, 566–569.Google Scholar
Corboz, P., Rice, T. M., and Troyer, M. 2014. Competing states in the t-J model: uniform d-wave state versus stripe state. Phys. Rev. Lett., 113, 046402.Google Scholar
Daley, A. J., Kollath, C., Schollwöck, U., and Vidal, G. 2004. Time-dependent density- matrix renormalization-group using adaptive effective Hilbert spaces. J. Stat. Mech.: Theor. Exp., P04005.
Dirac, P. A. M. 1930. Note on exchange phenomena in the Thomas atom. Math. Proc. Cambridge Philos. Soc., 26, 376–385.Google Scholar
Dongarra, J., and Sullivan, F. 2000. Guest editors' introduction: the top 10 algorithms. Comput. Sci Eng., 2, 22–23.Google Scholar
Dovesi, R., Orlando, R., Erba, A., Zicovich-Wilson, C. M., Civalleri, B., Casassa, S., Maschio, L., Ferrabone, M., De La Pierre, M., D'Arco, P., Noel, Y., Causa`, M., Rerat, M., and Kirtman, B. 2014. CRYSTAL14: a program for the ab initio investigation of crystalline solids. Int. J. Quantum Chem., 114, 1287–1317.Google Scholar
Eichenberger, D., and Baeriswyl, D. 2007. Superconductivity and antiferromagnetism in the two-dimensional Hubbard model: a variational study. Phys. Rev. B, 76, 180504.Google Scholar
Eisert, J., Cramer, M., and Plenio, M. B. 2010. Area laws for the entanglement entropy. Rev. Mod. Phys., 82, 277–306.Google Scholar
Faddeev, L. D., and Takhtajan, L. A. 1981. What is the spin of a spin wave? Phys. Lett. A, 85, 375–377.Google Scholar
Fahy, S., and Hamann, D. R. 1991. Diffusive behavior of states in the Hubbard-Stratonovich transformation. Phys. Rev. B, 43, 765–779.Google Scholar
Fano, G., Ortolani, F., and Colombo, E. 1986. Configuration-interaction calculations on the fractional quantum Hall effect. Phys. Rev. B, 34, 2670–2680.Google Scholar
Fazekas, P. 1999. Lecture Notes on Electron Correlation and Magnetism. World Scientifi.
Fazekas, P., and Anderson, P. W. 1974. On the ground state properties of the anisotropic triangular antiferromagnet. Phil. Mag., 30, 423–440.Google Scholar
Ferrenberg, A. M., Landau, D. P., and Wong, Y. J. 1992. Monte Carlo simulations: Hidden errors from “good” random number generators. Phys. Rev. Lett., 69, 3382–3384.Google Scholar
Fetter, A. L., and Walecka, J. D. 2003. Quantum Theory of Many-Particle Systems. Dover Publications Inc.
Feynman, R. P. 1954. Atomic theory of the two-fluid model of liquid Helium. Phys. Rev., 94, 262–277.Google Scholar
Feynman, R. P., and Cohen, M. 1956. Energy spectrum of the excitations in liquid Helium. Phys. Rev., 102, 1189–1204.Google Scholar
Filippi, C., and Umrigar, C. 1996. Multiconfiguration wave functions for quantum Monte Carlo calculations of first-row diatomic molecules. J. Chem. Phys., 105, 213–226.Google Scholar
Foulkes, W. M. C., Mitas, L., Needs, R. J., and Rajagopal, G. 2001. Quantum Monte Carlo simulations of solids. Rev. Mod. Phys., 73, 33–83.Google Scholar
Gnedenko, B. V. 2014. The Theory of Probability. Martino Fine Books.
Gnedenko, B. V., and Kolmogorov, A. N. 1954. Limit Distributions for Sums of Independent Random Variables. Addison-Wesley.
Gros, C. 1988. Superconductivity in correlated wave functions. Phys. Rev. B, 38, 931–934.Google Scholar
Gros, C. 1989. Physics of projected wave functions. Ann. Phys., 189, 53–88.Google Scholar
Gros, C., Joynt, R., and Rice, T. M. 1987. Antiferromagnetic correlations in almost- localized Fermi liquids. Phys. Rev. B, 36, 381–393.Google Scholar
Gubernatis, J., Kawashima, N., and Werner, P. 2016. Quantum Monte Carlo methods: algorithms for lattice models. Cambridge University Press.
Gutzwiller, M. C. 1963. Effect of correlation on the ferromagnetism of transition metals. Phys. Rev. Lett., 10, 159–162.Google Scholar
Haldane, F. D. M. 1983. Fractional quantization of the Hall effect: a hierarchy of incompressible quantum fluid states. Phys. Rev. Lett., 51, 605–608.Google Scholar
Haldane, F. D. M. 1988. Exact Jastrow-Gutzwiller resonating-valence-bond ground state of the spin-1/2 antiferromagnetic Heisenberg chain with 1/r2 exchange. Phys. Rev. Lett., 60, 635–638.Google Scholar
Haldane, F. D. M. 1991. “Spinon gas” description of the S = 1/2 Heisenberg chain with inverse-square exchange: exact spectrum and thermodynamics. Phys. Rev. Lett., 66, 1529–1532.Google Scholar
Haldane, F. D. M., and Rezayi, E. H. 1985. Periodic Laughlin-Jastrow wave functions for the fractional quantized Hall effect. Phys. Rev. B, 60, 2529–2531.Google Scholar
Harju, A., Barbiellini, B., Siljamaki, S., Nieminen, R. M., and Ortiz, G. 1997. Stochastic gradient approximation: an efficient method to optimize many-body wave functions. Phys. Rev. Lett., 79, 1173–1177.Google Scholar
Hastings, W. K. 1970. Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97–109.Google Scholar
Heitler, W., and London, F. 1927. Wechselwirkung neutraler atome und homöopolare bindung nach der quantenmechanik. Z. Phys., 44, 455–472.Google Scholar
Hirsch, J. E. 1985. Two-dimensional Hubbard model: numerical simulation study. Phys. Rev. B, 31, 4403–4419.Google Scholar
Hu, W.-J., Becca, F., and Sorella, S. 2012. Absence of static stripes in the two-dimensional t-J model determined using an accurate and systematic quantum Monte Carlo approach. Phys. Rev. B, 85, 081110.Google Scholar
Hubbard, J. 1959. Calculation of partition functions. Phys. Rev. Lett., 3, 77–78.Google Scholar
Hubbard, J. 1963. Electron correlations in narrow energy bands. Proc. Royal Soc. of London, 276, 238–257.Google Scholar
Ido, K., Ohgoe, T., and Imada, M. 2015. Time-dependent many-variable variational Monte Carlo method for non-equilibrium strongly correlated electron systems. Phys. Rev. B, 92, 245106.Google Scholar
Imada, M., Fujimori, A., and Tokura, Y. 1998. Metal-insulator transitions. Rev. Mod. Phys., 70, 1039–1263.Google Scholar
Iqbal, Y., Becca, F., and Poilblanc, D. 2011. Projected wave function study of Z2 spin liquids on the kagome lattice for the spin-1/2 quantum Heisenberg antiferromagnet. Phys. Rev. B, 84, 020407.Google Scholar
Jain, J. K. 2012. Composite Fermions. Cambridge University Press.
Jastrow, R. 1955. Many-body problem with strong forces. Phys. Rev., 98, 1479–1484.Google Scholar
Kalos, M. H., Levesque, D., and Verlet, L. 1974. Helium at zero temperature with hard-sphere and other forces. Phys. Rev. A, 9, 2178–2195.Google Scholar
Kanamori, J. 1963. Electron correlation and ferromagnetism of transition metals. Prog. Theor. Phys., 30, 275–289.Google Scholar
Kaneko, R., Tocchio, L. F., Valenti, R., Becca, F., and Gros, C. 2016. Spontaneous symmetry breaking in correlated wave functions. Phys. Rev. B, 93, 125127.Google Scholar
Kim, J., Esler, K. P., McMinis, J., Morales, M. A., Clark, B. K., Shulenburger, L., and D. M., Ceperley. 2012. Hybrid algorithms in quantum Monte Carlo. J. Phys.: Conf. Ser., 402, 012008.Google Scholar
Kivelson, S. A., Rokhsar, D. S., and Sethna, J. P. 1987. Topology of the resonating valence-bond state: solitons and high-Tc superconductivity. Phys. Rev. B, 35, 8865– 8868.Google Scholar
Knuth, D. 1997. The Art of Computer Programming. Addison-Wesley.
Krauth, W. 2006. Statistical Mechanics: Algorithms and Computations. Oxford University Press.
Krauth, W., Caffarel, M., and Bouchaud, J. 1992. Gutzwiller wave function for a model of strongly interacting bosons. Phys. Rev. B, 45, 3137–3140.Google Scholar
Kwon, Y., Ceperley, D. M., and Martin, R. M. 1993. Effects of three-body and backflow correlations in the two-dimensional electron gas. Phys. Rev. B, 48, 12037–12046.Google Scholar
Kwon, Y., Ceperley, D. M., and Martin, R. M. 1998. Effects of backflow correlation in the three-dimensional electron gas: quantum Monte Carlo study. Phys. Rev. B, 58, 6800–6806.Google Scholar
Laughlin, R. B. 1983. Anomalous quantum Hall effect: an incompressible quantum fluid with fractionally charged excitations. Phys. Rev. Lett., 50, 1395–1398.Google Scholar
Lee, P. A., Nagaosa, N., and Wen, X.-G. 2006. Doping a Mott insulator: physics of high- temperature superconductivity. Rev. Mod. Phys., 78, 17–85.Google Scholar
Liang, S., Doucot, B., and Anderson, P. W. 1988. Some new variational resonating-valence- bond-type wave functions for the spin-1/2 antiferromagnetic Heisenberg model on a square lattice. Phys. Rev. Lett., 61, 365–368.Google Scholar
Lieb, E. H., and Wu, F. Y. 1968. Absence of Mott transition in an exact solution of the short-range, one-band model in one dimension. Phys. Rev. Lett., 20, 1445–1448.Google Scholar
Lin, C., Zong, F. H., and Ceperley, D. M. 2001. Twist-averaged boundary conditions in continuum quantum Monte Carlo algorithms. Phys. Rev. E, 64, 016702.Google Scholar
Loh, E. Y., Gubernatis, J. E., Scalettar, R. T., White, S. R., Scalapino, D. J., and Sugar, R. L. 1990. Sign problem in the numerical simulation of many-electron systems. Phys. Rev. B, 41, 9301–9307.Google Scholar
Marchi, M., Azadi, S., Casula, M., and Sorella, S. 2009. Resonating valence bond wave function with molecular orbitals: Application to first-row molecules. J. Chem. Phys., 131, 154116.Google Scholar
Marshall, W. 1955. Antiferromagnetism. Proc. R. Soc. London Ser., A 232, 48–68.Google Scholar
Martin, R. M. 2004. Electronic Structure: Basic Theory and Practical Methods. Cambridge University Press.
Martin, R.M., Reining, L., and Ceperley, D.M. 2016. Interacting Electrons: Theory and Computational Approaches. Cambridge University Press.
Mazzola, G., and Sorella, S. 2017. Accelerating ab initio molecular dynamics and probing the weak dispersive forces in dense liquid Hydrogen. Phys. Rev. Lett., 118, 015703.Google Scholar
McMillan, W. L. 1965. Ground State of Liquid He4. Phys. Rev., 138, A442–A451.Google Scholar
Metropolis, N. 1987. The beginning of the Monte Carlo method. Los Alamos Science, 15, 125–130.Google Scholar
Metropolis, N., and Ulam, S. 1949. The Monte Carlo method. J. Am. Stat. Ass., 44, 335–341.Google Scholar
Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A., and Teller, E. 1957. Equations of state calculations by fast computing machines. J. Chem. Phys., 21, 1087–1092.Google Scholar
Meyer, C. D. 2000. Matrix Analysis and Applied Linear Algebra. SIAM.
Moore, G., and Read, N. 1991. Nonabelions in the fractional quantum Hall effect. Nucl. Phys. B, 360, 362–396.Google Scholar
Moroni, S., and Baroni, S. 1999. Reptation quantum Monte Carlo: A method for unbi- ased ground-state averages and imaginary-time correlations. Phys. Rev. Lett., 82, 4745–4748.Google Scholar
Moskowitz, J. W., Schmidt, K. E., Lee, M. A., and Kalos, M. H. 1982. A new look at correlation energy in atomic and molecular systems. II: the application of the Green's function Monte Carlo method to LiH. J. Chem. Phys., 77, 349–355.Google Scholar
Mott, N. F. 1949. The basis of the electron theory of metals, with special reference to the transition metals. Proc. Phys. Soc. (London), 62, 416–422.Google Scholar
Mott, N. F. 1990. Metal-Insulator Transitions. Taylor and Francis.
Nagaoka, Y. 1966. Ferromagnetism in a narrow, almost half-filled s band. Phys. Rev., 147, 392–405.Google Scholar
Needs, R. J., Towler, M. D., Drummond, N. D., and Lopez Rıos, P. 2010. Continuum variational and diffusion quantum Monte Carlo calculations. J. Phys.: Condens. Matter, 22, 023201.Google Scholar
Nelson, E. 1966. Derivation of the Schrödinger equation from Newtonian mechanics. Phys. Rev., 150, 1079–1085.Google Scholar
Neuscamman, E. 2012. Size consistency error in the antisymmetric geminal power wave function can be completely removed. Phys. Rev. Lett., 109, 203001.Google Scholar
Neuscamman, E., Umrigar, C. J., and Chan, G.K.-L. 2012. Optimizing large parameter sets in variational quantum Monte Carlo. Phys. Rev. B, 85, 045103.Google Scholar
Nightingale, M. P., and Melik-Alaverdian, V. 2001. Optimization of ground- and excited- state wave functions and van der Waals clusters. Phys. Rev. Lett., 87, 043401.Google Scholar
Norris, J. R. 1997. Markov Chains. Cambridge Series in Statistical and Probabilistic Mathematics.
Nozieres, P. 1964. Theory of Interacting Fermi Systems. New York: W.A. Benjamin.
Ortiz, G., Ceperley, D. M., and Martin, R. M. 1993. New stochastic method for systems with broken time-reversal symmetry: 2D fermions in a magnetic field. Phys. Rev. Lett., 71, 2777–2780.Google Scholar
Oshikawa, M., and Senthil, T. 2006. Fractionalization, topological order, and quasiparticle statistics. Phys. Rev. Lett., 96, 060601.Google Scholar
Pandharipande, V. R., and Itoh, N. 1973. Effective mass of 3He in liquid 4He. Phys. Rev. A, 8, 2564–2566.Google Scholar
Parisi, G. 1984. Prolegomena to any future computer evaluation of the QCD mass spectrum. Pages 531–541 of: Progress in Gauge Field Theory. NATO ASI Series, vol. 115. Springe.
Parisi, G., and Wu, Y.-S. 1981. Perturbation theory without gauge fixing. Sci. Sinica, 24, 483–496.Google Scholar
Pauling, L. 1960. The Nature of the Chemical Bond. Cornell University Press.
Pierleoni, C., and Ceperley, D. M. 2005. Computational methods in coupled electronion Monte Carlo simulations. ChemPhysChem, 6, 1872–1878.Google Scholar
Pitaevskii, L., and Stringari, S. 1991. Uncertainly principle, quantum fluctuations, and broken symmetries. J. Low Temp. Phys., 85, 377–388.Google Scholar
Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. 2007. Numerical Recipes 3rd edition: The Art of Scientific Computing. Cambridge University Press.
Read, N., and Chakraborty, B. 1989. Statistics of the excitations of the resonating-valence- bond state. Phys. Rev. B, 40, 7133–7140.Google Scholar
Read, N., and Rezayi, E. 1999. Beyond paired quantum Hall states: Parafermions and incompressible states in the first excited Landau level. Phys. Rev. B, 59, 8084–8092.Google Scholar
Reger, J. D., and Young, A. P. 1988. Monte Carlo simulations of the spin-1/2 Heisenberg antiferromagnet on a square lattice. Phys. Rev. B, 37, 5978–5981.Google Scholar
Reynolds, P. J., Ceperley, D. M., Alder, B. J., and Lester, Jr. 1982. Fixednode quantum Monte Carlo for molecules. J. Chem. Phys., 77, 5593–5603.Google Scholar
Ring, P., and Schuck, P. 2004. The Nuclear Many-body Problem. Springer-Verlag. Rokhsar, D. S., and Kotliar, B. G. 1991. Gutzwiller projection for bosons. Phys. Rev. B, 44, 10328–10332.Google Scholar
Schmidt, K. E., and Pandharipande, V. R. 1979. New variational wave function for liquid 3He. Phys. Rev. B, 19, 2504–2519.Google Scholar
Schollwöck, U. 2005. The density-matrix renormalization group. Rev. Mod. Phys., 77, 259–315.Google Scholar
Schollwöck, U. 2011. The density-matrix renormalization group in the age of matrix product states. Ann. Phys., 326, 96–192.Google Scholar
Schrieffer, J. R. 1964. Theory of Superconductivity. New York: W.A. Benjamin.
Senthil, T., and Fisher, M. P. A. 2000. Z2 gauge theory of electron fractionalization in strongly correlated systems. Phys. Rev. B, 62, 7850–7881.Google Scholar
Shastry, B. S. 1988. Exact solution of an S = 1/2 Heisenberg antiferromagnetic chain with long-ranged interactions. Phys. Rev. Lett., 60, 639–642.Google Scholar
Slater, J. C. 1930. The electronic structure of metals. Rev. Mod. Phys., 6, 209–280.Google Scholar
Sorella, S. 1998. Green function Monte Carlo with stochastic reconfiguration. Phys. Rev. Lett., 80, 4558–4561.Google Scholar
Sorella, S. 2001. Generalized Lanczos algorithm for variational quantum Monte Carlo. Phys. Rev. B, 64, 024512.Google Scholar
Sorella, S. 2002. Effective Hamiltonian approach for strongly correlated lattice models. arXiv:cond-mat/0201388.
Sorella, S. 2005. Wave function optimization in the variational Monte Carlo method. Phys. Rev. B, 71, 241103.Google Scholar
Sorella, S., Baroni, S., Car, R., and Parrinello, M. 1989. A novel technique for the simulation of interacting fermion systems. Europhys. Lett., 8, 663–668.Google Scholar
Sorella, S., Martins, G. B., Becca, F., Gazza, C., Capriotti, L., Parola, A., and Dagotto, E. 2002. Superconductivity in the two-dimensional t-J model. Phys. Rev. Lett., 88, 117002.Google Scholar
Sorella, S., Casula, M., and Rocca, D. 2007. Weak binding between two aromatic rings: Feeling the van der Waals attraction by quantum Monte Carlo methods. J. Chem. Phys., 127, 014105.Google Scholar
Sorella, S., Devaux, N., Dagrada, M., Mazzola, G., and Casula, M. 2015. Geminal embedding scheme for optimal atomic basis set construction in correlated calculations. J. Chem. Phys., 143, 244112.Google Scholar
Stewart, G. R. 1984. Heavy-fermion systems. Rev. Mod. Phys., 56, 755–787.Google Scholar
Stratonovich, R. L. 1957. A method for the computation of quantum distribution functions. Doklady Akad. Nauk S.S.S.R., 115, 1097–1100.Google Scholar
Sutherland, B. 1971. Exact results for a quantum many-body problem in one dimension. Phys. Rev. A, 4, 2019–2021.Google Scholar
Sutherland, B. 1975. Model for a multicomponent quantum system. Phys. Rev. B, 12, 3795–3805.Google Scholar
Suzuki, M. 1976a. Generalized Trotter's formula and systematic approximants of expo- nential operators and inner derivations with applications to many-body problems. Commun. Math. Phys., 51, 183–190.Google Scholar
Suzuki, M. 1976b. Relationship between d-dimensional quantal spin systems and (d + 1)- dimensional Ising systems. Prog. Theor. Phys., 56, 1454–1469.Google Scholar
Szabo, A., and Ostlund, N. S. 1996. Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory. Dover Publications Inc.
Tasaki, H. 1998. From Nagaoka's ferromagnetism to flat-band ferromagnetism and beyond. Prog. Theor. Phys., 99, 489–548.Google Scholar
ten Haaf, D. F. B., van Bemmel, H. J. M., van Leeuwen, J. M. J., van Saarloos, W., and Ceperley, D. M. 1995. Proof of upper bound in fixed-node Monte Carlo for lattice fermions. Phys. Rev. B, 51, 13039–13045.Google Scholar
Tocchio, L. F., Becca, F., Parola, A., and Sorella, S. 2008. Role of backflow correlations for the nonmagnetic phase of the t-tl Hubbard model. Phys. Rev. B, 78, 041101.Google Scholar
Tocchio, L. F., Becca, F., and Gros, C. 2011. Backflow correlations in the Hubbard model: An efficient tool for the study of the metal-insulator transition and the large-U limit. Phys. Rev. B, 83, 195138.Google Scholar
Toulouse, J., and Umrigar, C. J. 2007. Optimization of quantum Monte Carlo wave functions by energy minimization. J. Chem. Phys., 126, 084102.Google Scholar
Trivedi, N., and Ceperley, D. M. 1989. Green-function Monte Carlo study of quantum antiferromagnets. Phys. Rev. B, 40, 2737–2740.Google Scholar
Trivedi, N., and Ceperley, D. M. 1990. Ground-state correlations of quantum antiferromag- nets: a Green-function Monte Carlo study. Phys. Rev. B, 41, 4552–4569.Google Scholar
Trotter, H. F. 1959. On the product of semi-groups of operators. Proc. Am. Math. Soc., 10, 545–551.Google Scholar
Tuckerman, M. E. 2010. Statistical Mechanics: Theory and Molecular Simulation. Oxford University Press.
Umrigar, C. J., and Filippi, C. 2005. Energy and variance optimization of many-body wave functions. Phys. Rev. Lett., 94, 150201.Google Scholar
Umrigar, C. J., Wilson, K. G., and Wilkins, J. W. 1988. Optimized trial wave functions for quantum Monte Carlo calculations. Phys. Rev. Lett., 60, 1719–1722.Google Scholar
Umrigar, C. J., Nightingale, M. P., and Runge, K. J. 1993. A diffusion Monte Carlo algorithm with very small timestep errors. J. Chem. Phys., 99, 2865–2890.Google Scholar
Umrigar, C. J., Toulouse, J., Filippi, C., Sorella, S., and Hennig, R. G. 2007. Alleviation of the fermion-sign problem by optimization of many-body wave functions. Phys. Rev. Lett., 98, 110201.Google Scholar
Wagner, L. K., Bajdich, M., and Mitas, L. 2009. QWalk: A quantum Monte Carlo program for electronic structure. J. Comp. Phys., 228, 3390–3404.Google Scholar
Wen, X.-G. 1991. Topological orders and Chern-Simons theory in strongly correlated quantum liquid. Int. J. Mod. Phys. B, 5, 1641–1648.Google Scholar
Wen, X.-G., and Niu, Q. 1990. Ground-state degeneracy of the fractional quantum Hall states in the presence of a random potential and on high-genus Riemann surfaces. Phys. Rev. B, 41, 9377–9396.Google Scholar
White, S. R. 1992. Density matrix formulation for quantum renormalization groups. Phys. Rev. Lett., 69, 2863–2866.Google Scholar
White, S. R, and Feiguin, A. 2004. Real-time evolution using the density matrix renormal- ization group. Phys. Rev. Lett., 93, 076401.Google Scholar
White, S. R., and Scalapino, D.J. 1998. Density matrix renormalization group study of the striped phase in the 2D t-J model. Phys. Rev. Lett., 80, 1272–1275.Google Scholar
Wigner, E., and Seitz, F. 1934. On the constitution of metallic Sodium. II. Phys. Rev., 46, 509–524.Google Scholar
Yokoyama, H., and Shiba, H. 1987a. Variational Monte Carlo studies of Hubbard model. I. J. Phys. Soc. Jpn., 56, 1490–1506.Google Scholar
Yokoyama, H., and Shiba, H. 1987b. Variational Monte Carlo studies of Hubbard model. II. J. Phys. Soc. Jpn., 56, 3582–3592.Google Scholar
Yokoyama, H., and Shiba, H. 1990. Variational Monte Carlo studies of Hubbard model. III. Intersite correlation effects. J. Phys. Soc. Jpn., 59, 3669–3686.Google Scholar
Young, P. 2012. Everything you wanted to know about data analysis and fitting but were afraid to ask. arXiv:1210.3781.
Zhang, F. C., and Rice, T. M. 1988. Effective Hamiltonian for the superconducting Cu oxides. Phys. Rev. B, 37, 3759–3761.Google Scholar
Zhang, S., Carlson, J., and Gubernatis, J. E. 1995. Constrained path quantum Monte Carlo method for fermion ground states. Phys. Rev. Lett., 74, 3652–3655.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • References
  • Federico Becca, Sandro Sorella, Scuola Internazionale Superiore di Studi Avanzati, Trieste
  • Book: Quantum Monte Carlo Approaches for Correlated Systems
  • Online publication: 17 November 2017
  • Chapter DOI: https://doi.org/10.1017/9781316417041.015
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • References
  • Federico Becca, Sandro Sorella, Scuola Internazionale Superiore di Studi Avanzati, Trieste
  • Book: Quantum Monte Carlo Approaches for Correlated Systems
  • Online publication: 17 November 2017
  • Chapter DOI: https://doi.org/10.1017/9781316417041.015
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • References
  • Federico Becca, Sandro Sorella, Scuola Internazionale Superiore di Studi Avanzati, Trieste
  • Book: Quantum Monte Carlo Approaches for Correlated Systems
  • Online publication: 17 November 2017
  • Chapter DOI: https://doi.org/10.1017/9781316417041.015
Available formats
×