I am interested in developing efficient algorithms to make sense of large amounts of noisy data, extract information from observations, estimate signals from measurements. This effort spans several disciplines including statistics, computer science, information theory, machine learning.
I am also working on applications of these techniques to healthcare data analytics.

Academic Appointments

Professional Education

  • PhD, Scuola Normale Superiore, Pisa, Italy (2001)

2017-18 Courses

Stanford Advisees

All Publications

  • Localization from Incomplete Noisy Distance Measurements FOUNDATIONS OF COMPUTATIONAL MATHEMATICS Javanmard, A., Montanari, A. 2013; 13 (3): 297-345
  • The phase transition of matrix recovery from Gaussian measurements matches the minimax MSE of matrix denoising. Proceedings of the National Academy of Sciences of the United States of America Donoho, D. L., Gavish, M., Montanari, A. 2013; 110 (21): 8405-8410


    Let X(0) be an unknown M by N matrix. In matrix recovery, one takes n < MN linear measurements y(1),…,y(n) of X(0), where y(i) = Tr(A(T)iX(0)) and each A(i) is an M by N matrix. A popular approach for matrix recovery is nuclear norm minimization (NNM): solving the convex optimization problem min ||X||*subject to y(i) =Tr(A(T)(i)X) for all 1 ≤ i ≤ n, where || · ||* denotes the nuclear norm, namely, the sum of singular values. Empirical work reveals a phase transition curve, stated in terms of the undersampling fraction δ(n,M,N) = n/(MN), rank fraction ρ=rank(X0)/min {M,N}, and aspect ratio β=M/N. Specifically when the measurement matrices Ai have independent standard Gaussian random entries, a curve δ*(ρ) = δ*(ρ;β) exists such that, if δ > δ*(ρ), NNM typically succeeds for large M,N, whereas if δ < δ*(ρ), it typically fails. An apparently quite different problem is matrix denoising in Gaussian noise, in which an unknown M by N matrix X(0) is to be estimated based on direct noisy measurements Y =X(0) + Z, where the matrix Z has independent and identically distributed Gaussian entries. A popular matrix denoising scheme solves the unconstrained optimization problem min|| Y-X||(2)(F)/2+λ||X||*. When optimally tuned, this scheme achieves the asymptotic minimax mean-squared error M(ρ;β) = lim(M,N → ∞)inf(λ)sup(rank(X) ≤ ρ · M)MSE(X,X(λ)), where M/N → . We report extensive experiments showing that the phase transition δ*(ρ) in the first problem, matrix recovery from Gaussian measurements, coincides with the minimax risk curve M(ρ)=M(ρ;β) in the second problem, matrix denoising in Gaussian noise: δ*(ρ)=M(ρ), for any rank fraction 0 < ρ < 1 (at each common aspect ratio β). Our experiments considered matrices belonging to two constraint classes: real M by N matrices, of various ranks and aspect ratios, and real symmetric positive-semidefinite N by N matrices, of various ranks.

    View details for DOI 10.1073/pnas.1306110110

    View details for PubMedID 23650360

  • Iterative Coding for Network Coding IEEE TRANSACTIONS ON INFORMATION THEORY Montanari, A., Urbanke, R. L. 2013; 59 (3): 1563-1572
  • Factor models on locally tree-like graphs Annals of Probability Dembo, A., Montanari, A., Sun, N. 2013
  • Finding Hidden Cliques of Size in Nearly Linear Time Deshpande, Y., Montanari, A. 2013
  • Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory Javanmard, A., Montanari, A. 2013
  • Confidence Intervals and Hypothesis Testing for High-Dimensional Regression Javanmard, A., Montanari, A. 2013
  • High Dimensional Robust M-Estimation: Asymptotic Variance via Approximate Message Passing Donoho, D., Montanari, A. 2013
  • Lossy Compression of Discrete Sources via the Viterbi Algorithm IEEE TRANSACTIONS ON INFORMATION THEORY Jalali, S., Montanari, A., Weissman, T. 2012; 58 (4): 2475-2489
  • The LASSO Risk for Gaussian Matrices IEEE TRANSACTIONS ON INFORMATION THEORY Bayati, M., Montanari, A. 2012; 58 (4): 1997-2017
  • The weak limit of Ising models on locally tree-like graphs PROBABILITY THEORY AND RELATED FIELDS Montanari, A., Mossel, E., Sly, A. 2012; 152 (1-2): 31-51
  • Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing IEEE International Symposium on Information Theory Donoho, D. L., Javanmard, A., Montanari, A. IEEE. 2012
  • Universality in Polytope Phase Transitions and Message Passing Algorithms Bayati, M., Lelarge, M., Montanari, A. 2012
  • The noise sensitivity phase transition in compressed sensing IEEE Transactions on Information Theory Donoho, D., L., Maleki, A., Montanari, A. 2012
  • Graphical Models Concepts in Compressed Sensing in Compressed Sensing Montanari, A. Cambridge university PRess. 2012: 1
  • ACCELERATED TIME-OF-FLIGHT MASS SPECTROMETRY IEEE Statistical Signal Processing Workshop (SSP) Ibrahimi, M., Montanari, A., Moore, G. S. IEEE. 2012: 432–435
  • Subsampling at Information Theoretically Optimal Rates IEEE International Symposium on Information Theory Javanmard, A., Montanari, A. IEEE. 2012
  • Universality in Polytope Phase Transitions and Iterative Algorithms IEEE International Symposium on Information Theory Bayati, M., Lelarge, M., Montanari, A. IEEE. 2012
  • The Noise-Sensitivity Phase Transition in Compressed Sensing IEEE TRANSACTIONS ON INFORMATION THEORY Donoho, D. L., Maleki, A., Montanari, A. 2011; 57 (10): 6920-6941

    View details for DOI 10.1214/10-AAP729

    View details for Web of Science ID 000297027800003

  • Applications of the Lindeberg Principle in Communications and Statistical Learning IEEE TRANSACTIONS ON INFORMATION THEORY Korada, S. B., Montanari, A. 2011; 57 (4): 2440-2450
  • The Dynamics of Message Passing on Dense Graphs, with Applications to Compressed Sensing IEEE International Symposium on Information Theory Bayati, M., Montanari, A. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2011: 764–85

    View details for DOI 10.1137/090755862

    View details for Web of Science ID 000292302000024

  • Gossip PCA Korada, S., Montanari, A., Oh, S. 2011
  • Factor models on locally tree-like graphs Dembo, A., Montanari, A., Sun, N. 2011
  • Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising Donoho, D., Johnstone, I., Montanari, A. 2011
  • Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing Donoho, D., Javanmard, A., Montanari, A. 2011
  • Distributed Storage for Intermittent Energy Sources: Control Design and Performance Limits Kanoria, Y., Montanari, A., Tse, D., Zhang, B. 2011
  • Fast Convergence of Natural Bargaining Dynamics in Exchange Networks 22nd Annual ACM/SIAM Symposium on Discrete Algorithms Kanoria, Y., Bayati, M., Borgs, C., Chayes, J., Montanari, A. SIAM. 2011: 1518–1537
  • Localization from Incomplete Noisy Distance Measurements IEEE International Symposium on Information Theory (ISIT) Javanmard, A., Montanari, A. IEEE. 2011: 1584–1588
  • Compressed Sensing over l(p)-balls: Minimax Mean Square Error IEEE International Symposium on Information Theory (ISIT) Donoho, D., Johnstone, I., Maleki, A., Montanari, A. IEEE. 2011: 129–133
  • Information Theoretic Limits on Learning Stochastic Differential Equations IEEE International Symposium on Information Theory (ISIT) Bento, J., Ibrahimi, M., Montanari, A. IEEE. 2011: 855–859
  • Subexponential convergence for information aggregation on regular trees 50th IEEE Conference of Decision and Control (CDC)/European Control Conference (ECC) Kanoria, Y., Montanari, A. IEEE. 2011: 5317–5322
  • The spread of innovations in social networks PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Montanari, A., Saberi, A. 2010; 107 (47): 20196-20201


    Which network structures favor the rapid spread of new ideas, behaviors, or technologies? This question has been studied extensively using epidemic models. Here we consider a complementary point of view and consider scenarios where the individuals' behavior is the result of a strategic choice among competing alternatives. In particular, we study models that are based on the dynamics of coordination games. Classical results in game theory studying this model provide a simple condition for a new action or innovation to become widespread in the network. The present paper characterizes the rate of convergence as a function of the structure of the interaction network. The resulting predictions differ strongly from the ones provided by epidemic models. In particular, it appears that innovation spreads much more slowly on well-connected network structures dominated by long-range links than in low-dimensional ones dominated, for example, by geographic proximity.

    View details for DOI 10.1073/pnas.1004098107

    View details for Web of Science ID 000284529000013

    View details for PubMedID 21076030

  • Matrix Completion from Noisy Entries JOURNAL OF MACHINE LEARNING RESEARCH Keshavan, R. H., Montanari, A., Oh, S. 2010; 11: 2057-2078
  • Matrix Completion From a Few Entries IEEE TRANSACTIONS ON INFORMATION THEORY Keshavan, R. H., Montanari, A., Oh, S. 2010; 56 (6): 2980-2998

    View details for DOI 10.1214/09-AAP627

    View details for Web of Science ID 000283529500007

  • Regularization for Matrix Completion 2010 IEEE International Symposium on Information Theory Keshavan, R. H., Montanari, A. IEEE. 2010: 1503–1507
  • Learning Networks of Stochastic Differential Equations Bento, J., Ibrahimi, M., Montanari, A. 2010
  • Tight Thresholds for Cuckoo Hashing via XORSAT Dietzfelbinger, M., Goerdt, A., Mitzenmacher, M., Montanari, A., Pagh, R., Rink, M. 2010
  • Gibbs Measures and Phase Transitions on Sparse Random Graphs Brazilian Journal of Probability and Statistics Dembo, A., Montanari, A. 2008 Brazilian School of Probability. 2010: 1
  • Ising models on locally tree-like graphs Annals of Applied Probability Dembo, A., Montanari, A. 2010
  • Fast Convergence of Natural Bargaining Dynamics in Exchange Networks Kanoria, Y., Bayati, M., Borgs, C., Chayes, J., Montanari, A. 2010
  • The LASSO risk: asymptotic results and real world examples Bayati, M., Bento, J., Montanari, A. 2010
  • Majority dynamics on trees and the dynamic cavity method Annals of Applied Probability Kanoria, Y., Montanari, A. 2010
  • The Spread of Innovations in Social Networks Montanari, A., Saberi, A. 2010
  • Graphical Models Concepts in Compressed Sensing Montanari, A. 2010
  • The dynamics of message passing on dense graphs, with applications to compressed sensing 2010 IEEE International Symposium on Information Theory Bayati, M., Montanari, A. IEEE. 2010: 1528–1532
  • Tight Thresholds for Cuckoo Hashing via XORSAT 37th International Colloquium on Automata, Languages and Programming Dietzfelbinger, M., Goerdt, A., Mitzenmacher, M., Montanari, A., Pagh, R., Rink, M. SPRINGER-VERLAG BERLIN. 2010: 213–225
  • On the deletion channel with small deletion probability 2010 IEEE International Symposium on Information Theory Kanoria, Y., Montanari, A. IEEE. 2010: 1002–1006
  • An Empirical Scaling Law for Polar Codes 2010 IEEE International Symposium on Information Theory Korada, S. B., Montanari, A., Telatar, E., Urbanke, R. IEEE. 2010: 884–888
  • Message-passing algorithms for compressed sensing PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Donoho, D. L., Maleki, A., Montanari, A. 2009; 106 (45): 18914-18919


    Compressed sensing aims to undersample certain high-dimensional signals yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to be recovered is sufficiently sparse in a known basis. Currently, the best known sparsity-undersampling tradeoff is achieved when reconstructing by convex optimization, which is expensive in important large-scale applications. Fast iterative thresholding algorithms have been intensively studied as alternatives to convex optimization for large-scale problems. Unfortunately known fast algorithms offer substantially worse sparsity-undersampling tradeoffs than convex optimization. We introduce a simple costless modification to iterative thresholding making the sparsity-undersampling tradeoff of the new algorithms equivalent to that of the corresponding convex optimization procedures. The new iterative-thresholding algorithms are inspired by belief propagation in graphical models. Our empirical measurements of the sparsity-undersampling tradeoff for the new algorithms agree with theoretical calculations. We show that a state evolution formalism correctly derives the true sparsity-undersampling tradeoff. There is a surprising agreement between earlier calculations based on random convex polytopes and this apparently very different theoretical formalism.

    View details for DOI 10.1073/pnas.0909892106

    View details for Web of Science ID 000271637500010

    View details for PubMedID 19858495

  • The Generalized Area Theorem and Some of its Consequences IEEE TRANSACTIONS ON INFORMATION THEORY Measson, C., Montanari, A., Richardson, T. J., Urbanke, R. 2009; 55 (11): 4793-4821
  • Finite-Length Scaling for Iteratively Decoded LDPC Ensembles IEEE TRANSACTIONS ON INFORMATION THEORY Amraoui, A., Montanari, A., Richardson, T., Urbanke, R. 2009; 55 (2): 473-498
  • Low-rank Matrix Completion with Noisy Observations: a Quantitative Comparison 47th Annual Allerton Conference on Communication, Control, and Computing Keshavan, R. H., Montanari, A., Oh, S. IEEE. 2009: 1216–1222
  • Generating Random Graphs with Large Girth Bayati, M., Montanari, A., Saberi, A. 2009
  • Matrix Completion from a Few Entries Keshavan, R., Montanari, A., Oh, S. 2009
  • Matrix Completion from Noisy Entries Keshavan, R., Montanari, A., Oh, S. 2009
  • Which graphical models are difficult to learn? Bento, J., Montanari, A. 2009
  • Information, Physics, and Computation Mezard, M., Montanari, A. Oxford University Press. 2009
  • An Implementable Scheme for Universal Lossy Compression of Discrete Markov Sources Jalali, S., Montanari, A., Weissman, T. 2009
  • Matrix Completion from a Few Entries IEEE International Symposium on Information Theory (ISIT 2009) Keshavan, R. H., Oh, S., Montanari, A. IEEE. 2009: 324–328
  • Convergence to Equilibrium in Local Interaction Games 50th Annual IEEE Symposium on Foundations of Computer Science Montanari, A., Saberi, A. IEEE COMPUTER SOC. 2009: 303–312
  • An Iterative Scheme for Near Optimal and Universal Lossy Compression IEEE Information Theory Workshop on Networking and Information Theory Jalali, S., Montanari, A., Weissman, T. IEEE. 2009: 231–235
  • Generating random Tanner-graphs with large girth IEEE Information Theory Workshop (ITW) Bayati, M., Keshavan, R., Montanari, A., Oh, S., Saberi, A. IEEE. 2009: 154–157
  • Generating Random Graphs with Large Girth 20th Annual ACM-SIAM Symposium on Discrete Algorithms Bayati, M., Montanari, A., Saberi, A. SIAM. 2009: 566–575
  • Maxwell Construction: The Hidden Bridge Between Iterative and Maximum a Posteriori Decoding IEEE TRANSACTIONS ON INFORMATION THEORY Measson, C., Montanari, A., Urbanke, R. 2008; 54 (12): 5277-5307
  • Estimating random variables from random sparse observations EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS Montanari, A. 2008; 19 (4): 385-403

    View details for DOI 10.1002/ett.1289

    View details for Web of Science ID 000257012200005

  • Clusters of solutions and replica symmetry breaking in random k-satisfi ability JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT Montanari, A., Ricci-Tersenghi, F., Semerjian, G. 2008
  • Counter Braids IEEE Information Theory Workshop Lu, Y., Montanari, A., Prabhakar, B. IEEE. 2008: 220–221
  • Finite Size Scaling for the Core of Large Random Hypergraphs Annals of Applied Probability Dembo, A., Montanari, A. 2008
  • Learning Low Rank Matrices from O(n) Entries 46th Annual Allerton Conference on Communication, Control and Computing Keshavan, R. H., Montanari, A., Oh, S. IEEE. 2008: 1365–1372
  • Computing the threshold shift for general channels IEEE International Symposium on Information Theory Ezri, J., Urbanke, R., Montanari, A., Oh, S. IEEE. 2008: 1448–1452
  • An Implementable Scheme for Universal Lossy Compression of Discrete Markov Sources 19th Data Compression Conference Jalali, S., Montanari, A., Weissman, T. IEEE COMPUTER SOC. 2008: 292–301
  • The Slope Scaling Parameter for General Channels, Decoders, and Ensembles IEEE International Symposium on Information Theory Ezri, J., Montanari, A., Oh, S., Urbanke, R. IEEE. 2008: 1443–1447
  • Counter Braids: A Novel Counter Architecture for Per-Flow Measurement International Conference on Measurement and Modeling of Computer Systems Lu, Y., Montanari, A., Prabhakar, B., Dharmapurikar, S., Kabbani, A. ASSOC COMPUTING MACHINERY. 2008: 121–32
  • Counter Braids: Asymptotic Optimality of the Message Passing Decoding Algorithm 46th Annual Allerton Conference on Communication, Control and Computing Lu, Y., Montanari, A., Prabhakar, B. IEEE. 2008: 209–216
  • Smooth compression, Gallager bound and Nonlinear sparse-graph codes IEEE International Symposium on Information Theory Montanari, A., Mossel, E. IEEE. 2008: 2474–2478
  • How to find good finite-length codes: from art towards science 4th International Symposium on Turbo Codes and Related Topics Amraoui, A., Montanari, A., Urbanke, R. WILEY-BLACKWELL. 2007: 491–508

    View details for DOI 10.1002/ett.1182

    View details for Web of Science ID 000248443400007

  • A simple one dimensional glassy Kac model JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT Montanari, A., Sinton, A. 2007
  • Gibbs states and the set of solutions of random constraint satisfaction problems PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Krzakala, F., Montanari, A., Ricci-Tersenghi, F., Semerjian, G., Zdeborova, L. 2007; 104 (25): 10318-10323


    An instance of a random constraint satisfaction problem defines a random subset (the set of solutions) of a large product space chiN (the set of assignments). We consider two prototypical problem ensembles (random k-satisfiability and q-coloring of random regular graphs) and study the uniform measure with support on S. As the number of constraints per variable increases, this measure first decomposes into an exponential number of pure states ("clusters") and subsequently condensates over the largest such states. Above the condensation point, the mass carried by the n largest states follows a Poisson-Dirichlet process. For typical large instances, the two transitions are sharp. We determine their precise location. Further, we provide a formal definition of each phase transition in terms of different notions of correlation between distinct variables in the problem. The degree of correlation naturally affects the performances of many search/sampling algorithms. Empirical evidence suggests that local Monte Carlo Markov chain strategies are effective up to the clustering phase transition and belief propagation up to the condensation point. Finally, refined message passing techniques (such as survey propagation) may also beat this threshold.

    View details for DOI 10.1073/pnas.0703685104

    View details for Web of Science ID 000247500000006

    View details for PubMedID 17567754

  • Asymptotic rate versus design rate IEEE International Symposium on Information Theory Measson, C., Montanari, A., Urbanke, R. IEEE. 2007: 1541–1545
  • Detailed Network Measurements Using Sparse Graph Counters: The Theory Lu, Y., Montanari, A., Prabhakar, B. 2007
  • TP Decoding Lu, Y., Montanari, A., Measson, C. 2007
  • Counting Good Truth Assignmants for Random Satisfiability Formulae Montanari, A., Shah, D. 2007
  • Solving Constraint Satisfaction Problems through Belief Propagation-guided Decimation Montanari, A., Ricci-Tersenghi, F., Semerjian, G. 2007
  • Modern Coding Theory: The Statistical Mechanics and Computer Science Point of View Les Houches Summer School on Mathematical Statistical Physics Montanari, A., Urbanke, R. Elsevier. 2007: 1
  • A generalization of the finite-length scaling approach beyond the BEC IEEE International Symposium on Information Theory Ezri, J., Montanari, A., Urbanke, R. IEEE. 2007: 1011–1015
  • Reconstruction for models on random graphs 48th Annual IEEE Symposium on Foundations of Computer Science Gerschenfeld, A., Montanari, A. IEEE COMPUTER SOC. 2007: 194–204
  • Precision electroweak measurements on the Z resonance PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS Schael, S., Barate, R., Bruneliere, R., Buskulic, D., De Bonis, I., Decamp, D., Ghez, P., Goy, C., Jezequel, S., Lees, J. P., Lucotte, A., Martin, F., Merle, E., Minard, M. N., Nief, J. Y., Odier, P., Pietrzyk, B., Trocme, B., Bravo, S., Casado, M. P., Chmeissani, M., Comas, P., Crespo, J. M., Fernandez, E., Fernandez-Bosman, M., Garrido, L., Grauges, E., Juste, A., Martinez, M., Merino, G., Miquel, R., Mir, L. M., Orteu, S., Pacheco, A., Park, I. C., Perlas, J., Riu, I., Ruiz, H., Sanchez, F., Colaleo, A., Creanza, D., De Filippis, N., de Palma, M., Iaselli, G., Maggi, G., Maggi, M., Nuzzo, S., Ranieri, A., Raso, G., Ruggieri, F., Selvaggi, G., Silvestris, L., Tempesta, P., Tricomi, A., Zito, G., Huang, X., Lin, J., Ouyang, Q., Wang, T., Xie, Y., Xu, R., Xue, S., Zhang, J., Zhang, L., Zhao, W., Abbaneo, D., Bazarko, A., Becker, U., Boix, G., Bird, F., Blucher, E., Bonvicini, B., Bright-Thomas, P., Barklow, T., Buchmuller, O., Cattaneo, M., Cerutti, F., Ciulli, V., Clerbaux, B., Drevermann, H., Forty, R. W., Frank, M., Greening, T. C., Hagelberg, R., Halley, A. W., Gianotti, F., Girone, M., Hansen, J. B., Harvey, J., Jacobsen, R., Hutchcroft, D. E., Janot, R., JOST, B., Knobloch, J., Kado, M., Lehraus, I., Lazeyras, P., Maley, R., Mato, P., May, J., Moutussi, A., Pepe-Altarelli, M., Ranjard, F., Rolandi, L., Schlatter, D., Schmitt, B., Schneider, O., Tejessy, W., Teubert, F., Tomalin, I. R., Tournefier, E., Veenhof, R., Valassi, A., Wiedenmann, W., Wright, A. E., Ajaltouni, Z., Badaud, F., Chazelle, G., Deschamps, O., Dessagne, S., Falvard, A., Ferdi, C., Fayolle, D., Gay, P., Guicheney, C., Henrard, P., Jousset, J., Michel, B., Monteil, S., Montret, J. C., Pallin, D., Pascolo, J. M., Perret, P., Podlyski, F., Bertelsen, H., Fernley, T., Hansen, J. D., Hansen, J. R., Hansen, P. H., Kraan, A. C., Lindahl, A., Mollerud, R., Nilsson, B. S., Rensch, B., Waananen, A., Daskalakis, G., Kyriakis, A., Markou, C., Simopoulou, E., Siotis, I., Vayaki, A., Zachariadou, K., Blondel, A., Bonneaud, G., Brient, J. C., Machefert, E., Rouge, A., Rumpf, M., Swynghedauw, M., Tanaka, R., Verderi, M., Videau, H., Ciulli, V., Focardi, E., Parrini, G., Zachariadou, K., Corden, M., Georgiopoulos, C., Antonelli, A., Antonelli, M., Bencivenni, G., Bologna, G., Bossi, F., Campana, P., Capon, G., Cerutti, F., Chiarella, V., Felici, G., Laurelli, P., Mannocchi, G., Murtas, G. P., Passalacqua, L., Picchi, P., Colrain, P., Ten Have, I., Hughes, I. S., Kennedy, J., Knowles, I. G., Lynch, J. G., Morton, W. T., Negus, P., O'Shea, V., Raine, C., Reeves, P., Scarr, J. M., Smith, K., Thompson, A. S., Turnbull, R. M., Wasserbaech, S., Buchmuller, O., Cavanaugh, R., Dhamotharan, S., Geweniger, C., Hanke, P., Hansper, G., Hepp, V., Kluge, E. E., Putzer, A., Sommer, J., Stenzel, H., Tittel, K., Werner, W., Wunsch, M., Beuselinck, R., Binnie, D. M., Cameron, W., Davies, G., Dornan, P. J., Goodsir, S., Marinelli, N., Martin, E. B., NASH, J., Nowell, J., Rutherford, S. A., Sedgbeer, J. K., THOMPSON, J. C., White, R., Williams, M. D., Ghete, V. M., Girtler, P., Kneringer, E., Kuhn, D., Rudolph, G., Bouhova-Thacker, E., Bowdery, C. K., Buck, P. G., Clarke, D. P., Ellis, G., Finch, A. J., Foster, F., Hughes, G., Jones, R. W., Keemer, N. R., Pearson, M. R., Robertson, N. A., Sloan, T., Smizanska, M., Snow, S. W., Williams, M. I., van der Aa, O., Delaere, C., Leibenguth, G., Lemaitre, V., Bauerdick, L. A., Blumenschein, U., van Gemmeren, P., Giehl, I., Holldorfer, F., Jakobs, K., Kasemann, M., Kayser, F., Kleinknecht, K., Muller, A. S., Quast, G., Renk, B., Rohne, E., Sander, H. G., Schmeling, S., Wachsmuth, H., Wanke, R., Zeitnitz, C., Ziegler, T., Aubert, J. J., Benchouk, C., Bonissent, A., Carr, J., Coyle, P., Curtil, C., Ealet, A., Etienne, F., Fouchez, D., Motsch, F., Payre, P., Rousseau, D., Tilquin, A., Talby, M., Thulasides, M., Aleppo, M., Antonelli, M., Ragusa, F., Buscher, V., David, A., Dietl, H., Ganis, G., Huttmann, K., Lutjens, G., Mannert, C., Manner, W., Moser, H. G., Settles, R., Seywerd, H., Stenzel, H., Villegas, M., Wiedenmann, W., Wolf, G., Azzurri, P., Boucrot, J., Callot, O., Chen, S., Cordier, A., Davier, M., Duflot, L., Grivaz, J. F., Heusse, P., Jacholkowska, A., Le Diberder, F., Lefrancois, J., Mutz, A. M., Schune, M. H., Serin, L., Veillet, J. J., Videau, I., Zerwas, D., Azzurri, P., Bagliesi, G., Bettarini, S., Boccali, T., Bozzi, C., Calderini, G., Dell'Orso, R., Fantechi, R., Ferrante, I., Fidecaro, F., Foa, L., Giammanco, A., Giassi, A., Gregorio, A., Ligabue, F., Lusiani, A., Marrocchesi, P. S., Messineo, A., Palla, F., Rizzo, G., Sanguinetti, G., Sciaba, A., Sguazzoni, G., Spagnolo, P., Steinberger, J., Tenchini, R., Venturi, A., Vannini, C., Venturi, A., Verdini, P. G., Awunor, O., Blair, G. A., Cowan, G., Garcia-Bellido, A., Green, M. G., Medcalf, T., Misiejuk, A., Strong, J. A., Teixeira-Dias, P., Botterill, D. R., Clifft, R. W., Edgecock, T. R., Edwards, M., Haywood, S. J., Norton, P. R., Tomalin, I. R., Ward, J. J., Bloch-Devaux, B., Boumediene, D., Colas, P., Emery, S., Fabbro, B., Kozanecki, W., Lancon, E., Lemaire, M. C., Locci, E., Perez, P., Rander, J., Renardy, J. F., Roussarie, A., Schuller, J. P., Schwindling, J., Tuchming, B., Vallage, B., Black, S. N., Dann, J. H., Kim, H. 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A., Pistolesi, E., Plyaskin, V., Pohl, M., Pojidaev, V., Postema, H., Pothier, J., Produit, N., Prokofiev, D. O., Prokofiev, D., Quartieri, J., Rahal-Callot, G., Rahaman, M. A., Raics, P., Raja, N., Ramelli, R., Rancoita, P. G., Ranieri, R., Raspereza, A., Razis, P., Ren, D., Rescigno, M., Reucroft, S., van Rhee, T., Riemann, S., Riles, K., Robohm, A., Rodin, J., Roe, B. P., Romero, L., Rosca, A., Rosemann, C., Rosenbleck, C., Rosier-Lees, S., Roth, S., Rubio, J. A., RUGGIERO, G., Ruschmeier, D., Rykaczewski, H., Sakharov, A., Saremi, S., Sarkar, S., Salicio, J., Sanchez, E., Sanders, M. P., Sarakinos, M. E., Schafer, C., Schegelsky, V., Schmidt-Kaerst, S., Schmitz, D., Schopper, H., Schotanus, D. J., Schwering, G., Sciacca, C., Sciarrino, D., Seganti, A., Servoli, L., Shevchenko, S., Shivarov, N., Shoutko, V., Shumilov, E., Shvorob, A., Siedenburg, T., Son, D., Smith, B., Souga, C., Spillantini, P., Steuer, M., Stickland, D. P., Stone, A., Stone, H., Stoyanov, B., Straessner, A., Sudhakar, K., Sultanov, G., Sun, L. Z., Sushkov, S., Suter, H., Swain, J. D., Szillasi, Z., Sztaricskai, T., Tang, X. W., Tarjan, P., Tauscher, L., Taylor, L., Tellili, B., Teyssier, D., Timmermans, C., Ting, S. C., Ting, S. M., Tonwar, S. C., TOTH, J., Tully, C., Tung, K. L., Uchida, Y., Ulbricht, J., Uwer, U., Valente, E., Van de Walle, R. T., Vasquez, R., Veszpremi, V., Vesztergombi, G., Vetlitsky, I., Vicinanza, D., Viertel, G., Villa, S., Vivargent, M., Vlachos, S., Vodopianov, I., Vogel, H., Vogt, H., Vorobiev, I., Vorobyov, A. A., Vorvolakos, A., Wadhwa, M., Wallraff, W., Wang, Q., Wang, X. L., Wang, Z. M., Weber, A., Weber, M., Wienemann, P., Wilkens, H., Wu, S. X., Wynhoff, S., Xia, L., Xu, Z. Z., Yamamoto, J., Yang, B. Z., Yang, C. G., Yang, H. J., Yang, M., Ye, J. B., Yeh, S. C., You, J. M., Zalite, A., Zalite, Y., Zhang, Z. P., Zhao, J., Zhu, G. Y., Zhu, R. Y., Zhuang, H. L., Zichichi, A., Zilizi, G., Zimmermann, B., Zoller, M., Abbiendi, G., Acton, P. D., Ainsley, C., Akesson, P. F., Alexander, G., Allison, J., Allport, P. P., Altekamp, N., Amaral, P., Ametewee, K., Anagnostou, G., Anderson, K. J., Anderson, S., Arcelli, S., Armitage, J. C., Asai, S., Ashby, S. F., Ashton, P., Astbury, A., Axen, D., Azuelos, G., Bahan, G. A., Bailey, I., Baines, J. T., Ball, A. H., Banks, J., Barberio, E., Barillari, T., Barker, G. J., Barlow, R. J., Barnett, S., Bartoldus, R., Batley, R. J., Beaudoin, G., Bechtle, P., Bechtluft, J., Beck, A., Becker, J., Beeston, C., Behnke, T., Bell, A. N., Bell, K. W., Bell, P. J., Bella, G., Bellerive, A., Benelli, G., Bentvelsen, S., Berlich, P., Bethke, S., Biebel, O., Binder, U., Blobel, V., Bloodworth, I. J., Bloomer, J. E., Bock, P., Boden, B., Bohme, J., Boeriu, O., Bonacorsi, D., Bosch, H. M., Bougerolle, S., Bouterneur, M., Bouwens, B. T., Brabson, B. B., Braibant, S., Breuker, H., Bright-Thomas, P., Brigliadori, L., Brown, R. M., Brun, R., Burgin, R., Buesser, K., Buijs, A., Burckhart, H. J., Burgard, C., Cammin, J., Campana, S., Capiluppi, P., Carnegie, R. K., Caron, B., Carter, A. A., Carter, J. R., Chang, C. Y., Charlesworth, C., Charlton, D. G., Chrin, J. T., Chrisman, D., Chu, S. L., Ciocca, C., Clarke, P. E., Clay, E., Clayton, J. C., Cohen, I., Collins, W. J., Conboy, J. E., Cooke, O. C., Cooper, M., Couch, M., Couchman, J., Coupland, M., Silva, E. D., Coxe, R. L., Csilling, A., Cuffiani, M., Dado, S., Dallapiccola, C., Dallavalle, G. M., Dallison, S., Darling, C., de Jong, S., De Roeck, A., De Wolf, E. A., Debu, P., Deng, H., Deninno, M. M., Dervan, P., Desch, K., Dieckmann, A., Dienes, B., Dittmar, M., Dixit, M. S., Donkers, M., Doucet, M., Dubbert, J., Duboscq, J. E., Duchovni, E., Duckeck, G., Duerdoth, I. P., Dumas, D. J., Eckerlin, G., Edwards, J. E., Elcombe, P. A., Estabrooks, P. G., Etzion, E., Evans, H. G., Evans, M., Fabbri, F., Fanti, M., Fath, P., Feld, L., Ferrari, P., Fiedler, F., Fierro, M., Fincke-Keeler, M., Fischer, H. M., Fleck, I., Folman, R., Fong, D. G., Ford, M., Foucher, M., Frey, A., Furtjes, A., Fukui, H., Fukunaga, C., Futyan, D. I., Gagnon, P., Gaidot, A., Ganel, O., Gary, J. W., Gascon, J., Gascon-Shotkin, S. M., Gaycken, G., Geddes, N. I., Geich-Gimbel, C., Gensler, S. W., Gentit, F. X., Geralis, T., Giacomelli, G., Giacomelli, P., Giacomelli, R., Gibson, V., Gibson, W. R., Gillies, J. D., Gingrich, D. M., Giunta, M., Glenzinski, D., Goldberg, J., Goodrick, M. J., Gorn, W., Graham, K., Grandi, C., Grant, F. C., Gross, E., Grunhaus, J., Gruwe, M., Gunther, P. O., Gupta, A., Hagemann, J., Hajdu, C., Hamann, M., Hanson, G. G., Hansroul, M., Hapke, M., Harder, K., Harel, A., Hargrovet, C. K., Harin-Dirac, M., Harrison, P. F., Hart, P. A., Hartmann, C., Hattersley, P. M., Hauschild, M., Hawkes, C. M., Hawkings, R., Heflin, E., Hemingway, R. J., Hensel, C., Herten, G., Heuer, R. D., Hildreth, M. D., Hill, J. C., Hillier, S. J., Hilse, T., Hinshaw, D. A., Ho, C., Hoare, J., Hobbs, J. D., Hobson, P. R., Hochman, D., Hocker, A., Hoffman, K., Holl, B., Homer, R. J., Honma, A. K., Horvath, D., Hossain, K. R., Hou, S. R., Howard, R., Howarth, C. P., Huntemeyer, P., Hughes-Jones, R. E., Humbert, R., Hutchcroft, D. E., Igo-Kemenes, P., Ihssen, H., Imrie, D. C., Ingram, M., Ishii, K., Jacob, F. R., Janissen, A. C., Jawahery, A., Jeffreys, P. W., Jeremie, H., Jimack, M., Jobes, M., Joly, T., Jones, C. R., Jones, G., Jones, M., Jones, R. W., Jost, U., Jovanovic, P., Jui, C., Jobes, M., Joly, A., Jones, C. R., Jones, G., Jones, M., Jones, R. W., Jost, U., Jovanovic, P., Jui, C., Junk, T. R., Kanaya, N., KANZAKI, J., Karapetian, G., Karlen, D., Kartvelishvili, V., Kawagoe, K., Kawamoto, T., Keeler, R. K., Kellogg, R. G., Kennedy, B. W., Kim, D. H., King, B. J., Kirk, J., Klein, K., Kleinwort, C., Klem, D. E., Klier, A., Kluth, S., Kobayashi, T., Kobel, M., Kopke, L., Koetke, D. S., Kokott, T. P., Komamiya, S., Kormos, L., Kowalewski, R., Kramer, T., Kral, J. F., Kress, T., Kreutzmann, H., Krieger, P., von Krogh, J., Kroll, J., Krop, D., Kruger, K., Kuhl, T., Kupper, M., Kuwano, M., Kyberd, P., Lafferty, G. D., Lafoux, H., Lahmann, R., Lai, W. P., Lamarche, F., Landsman, H., Lanske, D., Larson, W. J., Lauber, J., Lautenschlager, S. R., Lawson, I., Layter, J. G., Lazic, D., Le Du, P., Leblanc, P., Lee, A. M., Lefebvre, E., Lehto, M. H., Leins, A., Lellouch, D., Lennert, P., Leroy, C., Lessard, L., Letts, J., Levegrun, S., Levinson, L., Lewis, C., Liebisch, R., Lillich, J., Littlewood, C., Lloyd, A. W., Lloyd, S. L., Loebinger, F. K., Long, G. D., Lorah, J. M., Lorazo, B., Losty, M. J., Lou, X. C., Lu, J., Ludwig, A., Ludwig, J., Luig, A., Macchiolo, A., Macpherson, A., Mader, W., Mattig, P., Malik, A., Mannelli, M., Marcellini, S., Marchant, T. E., Maringer, G., Markus, C., Martin, A., Martin, J. P., Martinez, G., Masetti, G., Mashimo, T., Matthews, W., Maur, U., McDonald, W. J., McGowan, R. F., McKenna, J., Mckigney, E. A., McMahon, T. J., McNab, A. I., McNutt, J., McPherson, A. C., McPherson, R. A., Meijers, F., Mendez-Lorenzo, P., Menges, W., Menke, S., Menszner, D., Merritt, F. S., Mes, H., Meyer, J., Meyer, N., Michelini, A., Middleton, R. P., Mihara, S., Mikenberg, G., Mildenberger, J., Miller, D. J., Milstene, C., Mir, R., Moed, S., Mohr, W., Moisan, C., Montanari, A., Mori, T., Morii, M., Moss, M. W., Mouthuy, T., Muller, U., Murphy, P. G., Mutter, A., Nagai, K., NAKAMURA, I., Nanjo, H., Neal, H. A., Nellen, B., Nguyen, H. H., Nijjhar, B., Nisius, R., Nozaki, M., Oakham, F. G., Odorici, F., Ogg, M., Ogren, H. O., Oh, A., Oh, H., Okpara, A., Oldershaw, N. J., OMORI, T., O'Neale, S. W., O'Neill, B. P., Oram, C. J., Oreglia, M. J., Orito, S., Pahl, C., Palinkas, J., Palmonari, F., Pansart, J. P., Panzer-Steindel, B., Paschievici, P., Pasztor, G., Pater, J. R., Patrick, G. N., Pawley, S. J., Paz-Jaoshvili, N., Pearce, M. J., Petzold, S., Pfeifenschneider, P., Pfister, P., Pilcher, J. E., Pinfold, J., Pitman, D., Plane, D. E., Poffenberger, P., Poli, B., Polok, J., Pooth, O., Posthaus, A., Pouladdej, A., del Poz, L. A., Prebys, E., Pritchard, T. W., Przybycien, M., Przysiezniak, H., Quadt, A., Quast, G., Rabbertz, K., Raith, B., Redmond, M. W., Rees, D. L., Rembser, C., Renkel, P., Richards, G. E., Rick, H., Rigby, D., Riles, K., Robins, S. A., Robinson, D., Rodning, N., Rollnik, A., Roney, J. M., Rooke, A., Ros, E., Rosati, S., Roscoe, K., Rossberg, S., Rossi, A. M., Rosvick, M., Routenburg, P., Rozen, Y., Runge, K., Runolfsson, O., Ruppel, U., Rust, D. R., Rylko, R., Sachs, K., Saeki, T., Sahr, O., Sanghera, S., Sarkisyan, E. K., Sasaki, M., Sbarra, C., Schaile, A. D., Schaile, O., Schappert, W., Scharf, F., Scharff-Hansen, P., Schenk, P., Schieck, J., Schmitt, B., von der Schmitt, H., Schmitt, S., Schorner-Sadenius, T., Schreiber, S., Schroder, M., Schutz, P., Schultz-Coulon, H. C., Schulz, M., Schumacher, M., Schwarz, J., Schwick, C., Schwiening, J., Scott, W. G., Settles, M., Seuster, R., Shears, T. G., Shen, B. C., Shepherd-Themistocleous, C. H., Sherwood, P., Shypit, R., Simon, A., Singh, P., Siroli, G. P., Sittler, A., Skillman, A., Skuja, A., Smith, A. M., Smith, T. J., Snow, G. A., Sobie, R., Soldner-Rembold, S., Spagnolo, S., Spano, F., Springer, R. W., Sproston, M., Stahl, A., Starks, M., Steiert, M., Stephens, K., Steuerer, J., Stier, H. E., Stockhausen, B., Stoll, K., Strohmer, R., Strom, D., Strumia, F., Stumpf, L., Surrow, B., Szymanski, P., Tafirout, R., Takeda, H., Takeshita, T., Talbot, S. D., Tanaka, S., Taras, P., Tarem, S., Tasevsky, M., Taylor, R. J., Tecchio, M., Teixeira-Dias, P., Tesch, N., Teuscher, R., Thackray, N. J., Thiergen, M., Thomas, J., Thomson, M. A., von Torne, E., Torrence, E., Towers, S., Toya, D., Trocsanyi, Z., Tran, P., Transtromer, G., Trefzger, T., Tresilian, N. J., Trigger, I., Tscheulin, M., Tsukamoto, T., Tsur, E., Turcot, A. S., Tumer-Watson, M. F., Tysarczyk-Niemeyer, G., Ueda, I., Ujvari, B., Utzat, P., Vachon, B., Van den Plas, D., Van Kooten, R., VanDalen, G. J., Vannerem, P., Vasseur, G., Vertesi, R., Verzocchi, M., Vikas, P., Vincter, M., Virtue, C. J., Vokurka, E. H., Vollmer, C. F., Voss, H., Vossebeld, J., Wackerle, F., Wagner, A., Wagner, D. L., Wahl, C., Walker, J. P., Waller, D., Ward, C. P., Ward, D. R., Ward, J. J., Watkins, P. M., Watson, A. T., Watson, N. K., Weber, M., Weber, P., Weisz, S., Wels, P. S., Wengler, T., Wermes, N., Wetterling, D., Weymann, M., Whalley, M. A., White, J. S., Wilkens, B., Wilson, J. A., Wilson, G. W., Wingerter, I., Winterer, V. H., Wlodek, T., Wolf, G., Wood, N. C., Wotton, S., Wyatt, T. R., Yaari, R., Yamashita, S., Yang, Y., Yeaman, A., Yekutieli, G., Yurko, M., Zacek, V., Zacharov, I., Zer-Zion, D., Zeuner, W., Zivkovic, L., Zorn, G. T., Abe, K., Abe, K., Abe, T., Abt, I., Acton, P. D., Adam, I., Agnew, G., Akagi, T., Akimoto, H., Allen, N. J., Ash, W. W., Aston, D., Bacchetta, N., Baird, K. G., Baltay, C., Band, H. R., Barakat, M. B., Baranko, G. J., Bardon, O., Barklow, T. L., Bashindzhagian, G. L., Battiston, R., Bauer, J. M., Bazarko, A. O., Bean, A., Bellodi, G., Ben-David, R., Benvenuti, A. C., Berger, R., Biasini, M., Bienz, T., Bilei, G. M., Bisello, D., Blaylock, G., Bogart, J., Bolen, B., Bolton, T., Bower, G. R., Brau, J. E., Breidenbach, M., Bugg, W. M., Burke, D., Burnett, T. H., Burrows, P. N., Busza, W., Calcaterra, A., Caldwell, D. O., Camanzi, B., Carpinelli, M., Carr, J., Cassell, R., Castaldi, R., Castro, A., Cavalli-Sforza, M., Chadwick, G. B., Chou, A., Church, E., Claus, R., Cohn, H. O., Coller, J. A., Convery, M. R., Cook, V., Cotton, R., Cowan, R. F., Coyle, P. A., Coyne, D. G., Crawford, G., D'Oliveira, A., Damerell, C. J., Daoudi, M., Dasu, S., De Groot, N., de Sangro, R., De Simone, P., De Simone, S., Dell'Orso, R., Dervan, P. J., Dima, M., Dong, D. N., Doser, M., Du, P. Y., Dubois, R., Duboscq, J. E., Eigen, G., Eisenstein, B. I., Elia, R., Erdos, E., Erofeeva, I., Eschenburg, V., Etzion, E., Fahey, S., Falciai, D., Fan, C., Fernandez, J. P., Fero, M. J., Flood, K., Frey, R., Friedman, J. I., Furuno, K., Garwin, E. L., Gillman, T., Gladding, G., Gonzalez, S., Hallewell, G. D., Hart, E. L., Harton, J. L., Hasan, A., Hasegawa, Y., Hasuko, K., Hedges, S., Hertzbach, S. S., Hildreth, M. D., Hitlin, D. G., Honma, A., Huber, J. S., Huffer, M. E., Hughes, E. W., Huynh, X., Hwang, H., Iwasaki, M., Iwasaki, Y., Izen, J. M., Jackson, D. J., Jacques, P., Jaros, J. A., Jiang, Z. Y., Johnson, A. S., Johnson, J. R., Johnson, R. A., Junk, T., Kajikawa, R., Kalelkar, M., Kamyshkov, Y. A., Kang, H. J., Karliner, I., Kawahara, H., Kelsey, M. H., Kendall, H. W., Kim, Y. D., King, M., King, R., Kofler, R., Krishna, N. M., Kwon, Y., Labs, J. F., Kroeger, R. S., Langston, M., Lath, A., Lauber, J. A., Leith, D. W., Lia, V., Lin, C., Liu, M. X., Loreti, M., Lu, A., Lynch, H. L., Ma, J., Mancinelli, G., Manly, S., Mantovani, G., Markiewicz, T. W., Maruyama, T., Masuda, H., Mazzucato, H., McGowan, J. F., McKemey, A. K., Meadows, B. T., Messner, R., Mockett, P. M., Moffeit, K. C., Moore, T. B., Morii, M., Mours, B., Muller, D., Mueller, G., Murzin, V., Nagamine, T., Narita, S., Nauenberg, U., Neal, H., Nesom, G., Nussbaum, M., Ohnishi, Y., Oishi, N., Onoprienko, D., Osborne, L. S., Panvini, R. S., Park, C. H., Park, H., Pavel, T. J., Peruzzi, I., Pescara, L., Piccolo, M., Piemontese, L., Pieroni, E., Pitts, K. T., Plano, R. J., Prepost, R., Prescott, C. Y., Punkar, G., Quigley, J., Ratcliff, B. N., Reeves, K., Reeves, T. W., Reidy, J., Reinertsen, P. L., Rensing, P. E., Rochester, L. S., Rothberg, J. E., Rowson, P. C., Russell, J. J., Saxton, O. H., Schalk, T., Schindler, R. H., Schneekloth, U., Schumm, B. A., Schwiening, J., Seiden, A., Sen, S., Serbo, V. V., Servoli, L., Shaevitz, M. H., Shank, J. T., Shapiro, G., Sherden, D. J., Shmakov, K. D., Simopoulos, C., Sinev, N. B., Smith, S. R., Smy, M. B., Snyder, J. A., Sokoloff, M. D., Staengle, H., Stahl, A., Starner, P., Steiner, H., Steiner, R., Strauss, M. G., Su, D., Suekane, F., Sugiyama, A., Suzuki, A., Suzuki, S., Swartz, M., Szumilo, A., Takahashi, T., Taylor, F. E., Thaler, J. J., Thom, J., Torrence, E., Trandafir, A. I., Turk, J. D., Usher, T., Va'vra, J., Vannini, C., Vella, E., Venuti, J. P., Verdier, R., Verdini, P. G., Wagner, D. L., Wagner, S. R., Waite, A. P., Walston, S., Wang, J., Watts, S. J., Weidemann, A. W., Weiss, E. R., Whitaker, J. S., White, S. L., Wickens, F. J., Williams, D. A., Williams, D. C., Williams, S. H., Willocq, S., Wilson, R. J., Wisniewski, W. J., Wittlin, J. L., Woods, M., Word, G. B., Wright, T. R., Wyss, J., Yamamoto, R. K., Yamartino, J. M., Yang, X. Q., Yashima, J., Yellin, S. J., Young, C. C., Yuta, H., Zapalac, G., Zdarko, R. W., Zeitlin, C., Zhou, J. 2006; 427 (5-6): 257-454
  • How to Find Good Finite-Length Codes: From Art Towards Science European Transactions on Telecommunications Amraoui, A., Montanari, A., Urbanke, R. 2006
  • Finite-Length Scaling for Gallager A Ezri, J., Montanari, A., Urbanke, R. 2006
  • Two Lectures on Iterative Coding and Statistical Mechanics Les Houches Summer School on Mathematical Statistical Physics Montanari, A. Elsevier. 2006: 1
  • The Asymptotic Error Floor of LDPC Ensembles Under BP Decoding Montanari, A. 2006
  • Analysis of Belief propagation for Non-Linear Problems: The Example of CDMA (or: How to Prove Tanaka's Formula) Montanari, A., Tse, D. 2006
  • Approximate analysis of search algorithms with “physical” methods Phase Transitions and Algorithmic Complexity Cocco, S., Monasson, R., Montanari, A., Semerjian, G. Oxford. 2006: 1
  • Why We Can Not Surpass Capacity: The Matching Condition Measson, C., Montanari, A., Urbanke, R. 2005
  • From Large Scale Rearrangements to Mode Coupling Phenomenology Physical Review Letters Montanari, A., Semerjian, G. 2005
  • How to Compute Loop Corrections to Bethe Approximation Journal of Statistical Mechanics Montanari, A., Rizzo, T. 2005
  • Tight bounds for LDPC and LDGM codes under MAP decoding IEEE Transactions on Information Theory Montanari, A. 2005
  • Belief Propagation Based Multi–User Detection Montanari, A., Prabhakar, B., Tse, D. 2005
  • Finite-Length Scaling and Finite-Length Shift for Low-Density Parity-Check Codes Amraoui, A., Montanari, A., Richardson, T., Urbanke, R. 2004
  • Instability of one-step replica-symmetry-broken phase in satisfiability problems Journal of Physics A Montanari, A., Parisi, G., Ricci-Tersenghi, F. 2004
  • Tight bounds for LDPC codes under MAP decoding Montanari, A. 2004
  • On the stochastic dynamics of disordered spin models Journal of Statistical Physics Semerjian, G., Cugliandolo, L., F., Montanari, A. 2004
  • The Phase Diagram of Random Heteropolymers Physical Review Letters Montanari, A., Mueller, M., Mezard, M. 2004
  • Glassy phases in Random Heteropolymers with correlated sequences Journal of Chemical Physics Mueller, M., Montanari, A., Mezard, M. 2004
  • On the cooling-schedule dependence of the dynamics of mean-field glasses Physical Review B Montanari, A., Ricci-Tersenghi, F. 2004
  • Life Above Threshold: From List Decoding to Area Theorem and MSE Measson, C., Montanari, A., Richardson, T., Urbanke, R. 2004
  • Finite-length scaling for iteratively decoded LDPC ensembles Amraoui, A., Montanari, A., Richardson, T., Urbanke, R. 2003
  • A microscopic description of the aging dynamics: fluctuation-dissipation relations, effective temperature and heterogeneities Physical Review Letters Montanari, A., Ricci-Tersenghi, F. 2003
  • Alternative translation techniques for propositional and first-order modal logics JOURNAL OF AUTOMATED REASONING Montanari, A., POLICRITI, A., Slanina, M. 2002; 28 (4): 397-415
  • The dynamic phase transition for decoding algorithms Physical Review E Franz, S., Leone, M., Montanari, A., Ricci-Tersenghi, F. 2002; 66
  • Optimizing searches via rare events Physical Review Letters Montanari, A., Zecchina, R. 2002
  • Discrete non-Abelian groups and asymptotically free models Caracciolo, S., Montanari, A., Pelissetto, A. 2001
  • The glassy phase of Gallager codes The European Physical Journal B Montanari, A. 2001
  • Statistical mechanics and turbo codes Montanari, A., Sourlas, N. 2001
  • Finite-size scaling and metastable states of good codes Montanari, A. 2001
  • Asymptotically free models and discrete non-Abelian groups Physics Letters B Caracciolo, S., Montanari, A., Pelissetto, A. 2001
  • Hairpin formation and elongation of biomolecules Physical Review Letters Montanari, A., Mezard, M. 2001
  • Spin models on Platonic solids and asymptotic freedom Caracciolo, S., Montanari, A., Pelissetto, A. 2001
  • A guided tour through some extensions of the event calculus COMPUTATIONAL INTELLIGENCE Cervesato, I., Franceschet, M., Montanari, A. 2000; 16 (2): 307-347
  • Turbo codes: the phase transition The European Physical Journal B Montanari, A. 2000
  • The statistical mechanics of turbo codes The European Physical Journal B Montanari, A., Sourlas, N. 2000
  • Operator product expansion on the lattice: a numerical test in the two-dimensional non-linear sigma-model Journal of High Energy Physics Caracciolo, S., Montanari, A., Pelissetto, A. 2000
  • A general modal framework for the Event Calculus and its skeptical and credulous variants JOURNAL OF LOGIC PROGRAMMING Cervesato, I., Montanari, A. 1999; 38 (2): 111-164
  • Testing the efficiency of different improvement programs Nuclear Physics B Caracciolo, S., Montanari, A., Pelissetto, A. 1999
  • Composite operators from operator product expansion: what can go wrong? Caracciolo, S., Montanari, A., Pelissetto, A. 1999
  • Event Calculus with explicit quantifiers 5th International Workshop on Temporal Representation and Reasoning Cervesato, I., Franceschet, M., Montanari, A. I E E E, COMPUTER SOC PRESS. 1998: 81–88
  • Operator product expansion and non-perturbative renormalization Caracciolo, S., Montanari, A., Pelissetto, A. 1998
  • Improved actions for the two-dimensional sigma-model Caracciolo, S., Montanari, A., Pelissetto, A. 1997
  • COEVAL AR-40/AR-39 AGES OF 65.0 MILLION YEARS AGO FROM CHICXULUB CRATER MELT ROCK AND CRETACEOUS-TERTIARY BOUNDARY TEKTITES SCIENCE Swisher, C. C., GrajalesNishimura, J. M., Montanari, A., MARGOLIS, S. V., Claeys, P., Alvarez, W., Renne, P., CedilloPardo, E., Maurrasse, F. J., Curtis, G. H., Smit, J., McWilliams, M. O. 1992; 257 (5072): 954-958


    (40)Ar/(39)Ar dating of drill core samples of a glassy melt rock recovered from beneath a massive impact breccia contained within the 180-kilometer subsurface Chicxulub crater in Yucatán, Mexico, has yielded well-behaved incremental heating spectra with a mean plateau age of 64.98 +/- 0.05 million years ago (Ma). The glassy melt rock of andesitic composition was obtained from core 9 (1390 to 1393 meters) in the Chicxulub 1 well. The age of the melt rock is virtually indistinguishable from (40)Ar/(39)Ar ages obtained on tektite glass from Beloc, Haiti, and Arroyo el Mimbral, northeastern Mexico, of 65.01 +/- 0.08 Ma (mean plateau age for Beloc) and 65.07 +/- 0.10 Ma (mean total fusion age for both sites). The (40)Ar/(39)Ar ages, in conjunction with geochemical and petrological similarities, strengthen the recent suggestion that the Chicxulub structure is the source for the Haitian and Mexican tektites and is a viable candidate for the Cretaceous-Tertiary boundary impact site.

    View details for Web of Science ID A1992JH82700032

    View details for PubMedID 17789640