The CMV Matrix and the Generalized Lanczos Process

The two sister cytomegaloviruses (CMVs), human and murine CMV, have both evolved immune evasion functions that interfere with the major histocompatibility complex class I (MHC-I) pathway of antigen processing and presentation and are effectual in the early (E) phase of virus gene expression. However, studies on murine CMV have shown that E-phase immune evasion is leaky. An E-phase protein involved in immune evasion, namely m04-gp34, was found to simultaneously account for an antigenic peptide presented by the MHC-I molecule Dd. Recent work has demonstrated the induction of protective immunity specific for the E-phase protein M84-p65, one of two murine CMV homologues of the human CMV matrix protein UL83-pp65. In this study, the identification of the MHC-I Kd-restricted M84 peptide 297AYAGLFTPL305 is documented. This peptide is the third antigenic peptide described for murine CMV and the second that escapes immunosubversive mechanisms.

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MANY MASSES ON ONE STROKE: ECONOMIC COMPUTATION OF QUARK PROPAGATORS

International Journal of Modern Physics C ◽

10.1142/s0129183195000538 ◽

1995 ◽

Vol 06 (05) ◽

pp. 627-638 ◽

Cited By ~ 92

Author(s):

ANDREAS FROMMER ◽

BERTOLD NÖCKEL ◽

STEPHAN GÜSKEN ◽

THOMAS LIPPERT ◽

KLAUS SCHILLING

Keyword(s):

Mass Matrix ◽

Computational Effort ◽

Lattice Quantum Chromodynamics ◽

Normal Equations ◽

Wilson Fermion ◽

Quark Masses ◽

Lanczos Process ◽

Lattice Quantum ◽

Minimal Residual ◽

Better Than

The computational effort in the calculation of Wilson fermion quark propagators in Lattice Quantum Chromodynamics can be considerably reduced by exploiting the Wilson fermion matrix structure in inversion algorithms based on the non-symmetric Lanczos process. We consider two such methods: QMR (quasi minimal residual) and BCG (biconjugate gradients). Based on the decomposition M/κ = 1/κ−D of the Wilson mass matrix, using QMR, one can carry out inversions on a whole trajectory of masses simultaneously, merely at the computational expense of a single propagator computation. In other words, one has to compute the propagator corresponding to the lightest mass only, while all the heavier masses are given for free, at the price of extra storage. Moreover, the symmetry γ5M = M†γ5 can be used to cut the computational effort in QMR and BCG by a factor of two. We show that both methods then become — in the critical regime of small quark masses — competitive to BiCGStab and significantly better than the standard MR method, with optimal relaxation factor, and CG as applied to the normal equations.

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A STOPPING RULE FOR THE CONJUGATE GRADIENT REGULARIZATION METHOD APPLIED TO INVERSE PROBLEMS IN ACOUSTICS

Journal of Computational Acoustics ◽

10.1142/s0218396x06003116 ◽

2006 ◽

Vol 14 (04) ◽

pp. 397-414 ◽

Cited By ~ 3

Author(s):

THOMAS DELILLO ◽

TOMASZ HRYCAK

Keyword(s):

Conjugate Gradient ◽

A Priori ◽

A Priori Information ◽

Parameter Choice ◽

Regularization Algorithm ◽

Lanczos Process ◽

Choice Strategy ◽

Priori Information ◽

The One ◽

Parameter Choice Strategy

We present a novel parameter choice strategy for the conjugate gradient regularization algorithm which does not assume a priori information about the magnitude of the measurement error. Our approach is to regularize within the Krylov subspaces associated with the normal equations. We implement conjugate gradient via the Lanczos bidiagonalization process with reorthogonalization, and then we construct regularized solutions using the SVD of a bidiagonal projection constructed by the Lanczos process. We compare our method with the one proposed by Hanke and Raus and illustrate its performance with numerical experiments, including detection of acoustic boundary vibrations.

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