EVIDENCE FOR PHASE TRANSITIONS CAUSED BY RADIAL FLUCTUATIONS IN AN SU(2)×U(1) LATTICE GAUGE-HIGGS THEORY

1988 ◽  
Vol 03 (01) ◽  
pp. 23-31 ◽  
Author(s):  
Yasuko Munehisa
Keyword(s):  
Monte Carlo ◽  
Phase Transitions ◽  
Degrees Of Freedom ◽  
Gauge Coupling ◽  
Higgs Field ◽  
Critical Surface ◽  
Monte Carlo Techniques ◽  
Full Theory ◽  
Lattice Gauge ◽  
Symmetric Region

Using Monte Carlo techniques, we study the phase structure of a radially active SU(2)×U(1) lattice gauge-fundamental Higgs theory in its strong U(1) gauge-coupling limit. Our results give first evidence for a critical surface induced by radial fluctuations of the Higgs field, which would extend inside the symmetric region of the full SU(2)×U(1) gauge-Higgs theory. The weak SU (2) gauge-coupling limit of the full theory, the radially active version of the SU(2)global×U(1)local gauge-Higgs theory, is also studied numerically. In this limit, we found no essential effect due to the radial degrees of freedom of the Higgs field.

MONTE-CARLO ANALYSIS OF THE ABELIAN SURFACE GAUGE MODEL

1992 ◽  
Vol 07 (18) ◽  
pp. 1601-1607 ◽  
Author(s):  
M. BAIG ◽  
A. TRIAS
Keyword(s):  
Monte Carlo ◽  
Phase Structure ◽  
Three Dimensional ◽  
Monte Carlo Analysis ◽  
Abelian Surface ◽  
Gauge Model ◽  
Monte Carlo Techniques ◽  
Gauge Models ◽  
Lattice Gauge ◽  
Duality Relations

We present the first numerical results from a lattice formulation of the Abelian surface gauge model which accounts for three-index fields required in theories based on an antisymmetrical potential. For this purpose we have defined a lattice gauge model in such a way that field variables are assigned to the plaquettes and the interaction is defined through elementary three-dimensional cubes. The phase structure of the Abelian Z(2) case has been determined using Monte-Carlo techniques. Duality relations to spin and gauge models are also studied.

QCD GLUEBALLS WITHIN A COUPLED CLUSTER APPROACH

2001 ◽  
Vol 15 (10n11) ◽  
pp. 1732-1735 ◽  
Author(s):  
D. SCHÜTTE ◽  
A. WICHMANN ◽  
V. WETHKAMP
Keyword(s):  
Field Theory ◽  
Monte Carlo ◽  
Ground State ◽  
Cluster Method ◽  
Coupled Cluster ◽  
Gauge Field Theory ◽  
Coupled Cluster Method ◽  
Cluster Approach ◽  
Monte Carlo Techniques ◽  
Lattice Gauge

The validity of the coupled cluster method is studied within the lattice gauge field theory given by a SU(2) pure glue theory in 2+1 dimensions. Satisfactory convergence is observed for the ground state, but the method is less successful for the prediction of glueballs. We propose to improve the coupled cluster method for excited state by combining it with standard Monte-Carlo techniques which potentially cure the non-hermiticity problems caused by the truncation.

scholarly journals On the Structure of the Vacuum in Quantum Gravity: A View from the Asymptotic Safety Scenario

Universe ◽  
2019 ◽  
Vol 5 (8) ◽  
pp. 182 ◽  
Author(s):  
Alfio Bonanno
Keyword(s):  
Quantum Gravity ◽  
Degrees Of Freedom ◽  
Vacuum State ◽  
Critical Surface ◽  
Asymptotic Safety ◽  
Quantum Chromo Dynamics ◽  
Full Theory ◽  
Higher Derivative ◽  
Quadratic Gravity ◽  
Non Gaussian

Although the Asymptotic Safety scenario is one of the most promising approaches to quantum gravity, little attention has been devoted to the issue of the vacuum state. Higher derivative operators often appear on the ultraviolet critical surface around the non-Gaussian fixed point generating additional degrees of freedom which can render the standard vacuum unstable. When this happens, translation and rotational symmetries can be spontaneously broken and a new set of symmetries can show up at the level of the effective action. In this work, it will be argued that a “kinetic condensate” characterizes the vacuum state of asymptotically safe quadratic gravity theories. If this scenario is realized in the full theory, the vacuum state of gravity is the gravitational analogous to the Savvidy vacuum in Quantum Chromo-Dynamics (QCD).

Calculation and computation

2021 ◽  
pp. 217-252
Author(s):  
James P. Sethna
Keyword(s):  
Monte Carlo ◽  
Perturbation Theory ◽  
Phase Transitions ◽  
Ising Model ◽  
Low Temperature ◽  
Markov Chains ◽  
Detailed Balance ◽  
Reaction Rates ◽  
Temperature Expansion ◽  
Monte Carlo Techniques

This chapter introduces Monte-Carlo techniques to simulate the equilibrium properties of complex systems, and perturbative techniques to calculate their behavior as an expansion about solvable limits. It uses the Ising model as a description of magnets, of binary alloys, and of the liquid-gas transition. It introduces Markov chains and detailed balance as providing a guarantee that Monte-Carlo methods converge to equilibrium. To analyze phases and phase transitions, it introduces a 27-term low-temperature expansion for the magnetization of the Ising model. Inside phases, perturbation theory converges; at phase transitions, it cannot. Exercises simulate the behavior of the Ising model and cellular function. They explore equilibration algorithms and calculation of low temperature expansions. And they apply Markov chains to coin flips, unicycles, fruit flies, chemical reaction rates, and DNA replication.

LATTICE SU(2) GAUGE-HIGGS SYSTEM IN ANALYTIC TREATMENT

1987 ◽  
Vol 02 (03) ◽  
pp. 199-203 ◽  
Author(s):  
XI-TE ZHENG ◽  
JIE WANG ◽  
ZU-GUO TAN
Keyword(s):  
Phase Transition ◽  
Phase Diagram ◽  
Monte Carlo ◽  
Phase Transitions ◽  
Monte Carlo Simulations ◽  
Higgs Field ◽  
Fundamental Representation ◽  
Arbitrary Length ◽  
Analytic Treatment ◽  
Five Dimension

The phase diagrams of SU(2) gauge-Higgs model with Higgs field of arbitrary length in the fundamental representation in four and five dimension are studied analytically. A method for determining phase transition lines is proposed. All qualitative features of the phase diagram obtained by Monte Carlo simulations are obtained analytically, and the order of phase transitions can be determined definitely.

Bayesian Estimation of DSGE Models

2015 ◽  
Author(s):  
Edward P. Herbst ◽  
Frank Schorfheide
Keyword(s):  
Monte Carlo ◽  
Sequential Monte Carlo ◽  
Likelihood Function ◽  
Academic Research ◽  
Dynamic Stochastic General Equilibrium ◽  
Computational Techniques ◽  
Dsge Models ◽  
Monte Carlo Techniques ◽  
Dynamic Stochastic ◽  
Theoretical Foundations

Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. The book is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

Neutron dose evaluation of Elekta Linac at two energies (10 & 18 MV) by MCNP code and comparison with experimental measurements

2014 ◽  
Vol 6 (1) ◽  
pp. 1006-1015
Author(s):  
Negin Shagholi ◽  
Hassan Ali ◽  
Mahdi Sadeghi ◽  
Arjang Shahvar ◽  
Hoda Darestani ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Measurement Data ◽  
Calculated Data ◽  
High Energy ◽  
Neutron Dose ◽  
Dose Assessment ◽  
Photon Flux ◽  
Dose Equivalent ◽  
Monte Carlo Techniques ◽  
Neutron Dose Equivalent

Medical linear accelerators, besides the clinically high energy electron and photon beams, produce other secondary particles such as neutrons which escalate the delivered dose. In this study the neutron dose at 10 and 18MV Elekta linac was obtained by using TLD600 and TLD700 as well as Monte Carlo simulation. For neutron dose assessment in 2020 cm2 field, TLDs were calibrated at first. Gamma calibration was performed with 10 and 18 MV linac and neutron calibration was done with 241Am-Be neutron source. For simulation, MCNPX code was used then calculated neutron dose equivalent was compared with measurement data. Neutron dose equivalent at 18 MV was measured by using TLDs on the phantom surface and depths of 1, 2, 3.3, 4, 5 and 6 cm. Neutron dose at depths of less than 3.3cm was zero and maximized at the depth of 4 cm (44.39 mSvGy-1), whereas calculation resulted  in the maximum of 2.32 mSvGy-1 at the same depth. Neutron dose at 10 MV was measured by using TLDs on the phantom surface and depths of 1, 2, 2.5, 3.3, 4 and 5 cm. No photoneutron dose was observed at depths of less than 3.3cm and the maximum was at 4cm equal to 5.44mSvGy-1, however, the calculated data showed the maximum of 0.077mSvGy-1 at the same depth. The comparison between measured photo neutron dose and calculated data along the beam axis in different depths, shows that the measurement data were much more than the calculated data, so it seems that TLD600 and TLD700 pairs are not suitable dosimeters for neutron dosimetry in linac central axis due to high photon flux, whereas MCNPX Monte Carlo techniques still remain a valuable tool for photonuclear dose studies.

Reversibly Sampling Conformations and Binding Modes Using Molecular Darting

2020 ◽  
Author(s):  
Samuel C. Gill ◽  
David Mobley
Keyword(s):  
Monte Carlo ◽  
Ligand Binding ◽  
Binding Sites ◽  
Degrees Of Freedom ◽  
Dynamics Simulation ◽  
Hiv Integrase ◽  
Binding Modes ◽  
System A ◽  
Multiple Binding ◽  
Internal Degrees Of Freedom

<div>Sampling multiple binding modes of a ligand in a single molecular dynamics simulation is difficult. A given ligand may have many internal degrees of freedom, along with many different ways it might orient itself a binding site or across several binding sites, all of which might be separated by large energy barriers. We have developed a novel Monte Carlo move called Molecular Darting (MolDarting) to reversibly sample between predefined binding modes of a ligand. Here, we couple this with nonequilibrium candidate Monte Carlo (NCMC) to improve acceptance of moves.</div><div>We apply this technique to a simple dipeptide system, a ligand binding to T4 Lysozyme L99A, and ligand binding to HIV integrase in order to test this new method. We observe significant increases in acceptance compared to uniformly sampling the internal, and rotational/translational degrees of freedom in these systems.</div>

scholarly journals Stochastic Order and Generalized Weighted Mean Invariance

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 662
Author(s):  
Mateu Sbert ◽  
Jordi Poch ◽  
Shuning Chen ◽  
Víctor Elvira
Keyword(s):  
Monte Carlo ◽  
Probability Distributions ◽  
Stochastic Order ◽  
Arithmetic Mean ◽  
Stochastic Orders ◽  
Arithmetic Means ◽  
Increasing Convex Order ◽  
Monte Carlo Techniques ◽  
Multiple Importance Sampling ◽  
Invariance Properties

In this paper, we present order invariance theoretical results for weighted quasi-arithmetic means of a monotonic series of numbers. The quasi-arithmetic mean, or Kolmogorov–Nagumo mean, generalizes the classical mean and appears in many disciplines, from information theory to physics, from economics to traffic flow. Stochastic orders are defined on weights (or equivalently, discrete probability distributions). They were introduced to study risk in economics and decision theory, and recently have found utility in Monte Carlo techniques and in image processing. We show in this paper that, if two distributions of weights are ordered under first stochastic order, then for any monotonic series of numbers their weighted quasi-arithmetic means share the same order. This means for instance that arithmetic and harmonic mean for two different distributions of weights always have to be aligned if the weights are stochastically ordered, this is, either both means increase or both decrease. We explore the invariance properties when convex (concave) functions define both the quasi-arithmetic mean and the series of numbers, we show its relationship with increasing concave order and increasing convex order, and we observe the important role played by a new defined mirror property of stochastic orders. We also give some applications to entropy and cross-entropy and present an example of multiple importance sampling Monte Carlo technique that illustrates the usefulness and transversality of our approach. Invariance theorems are useful when a system is represented by a set of quasi-arithmetic means and we want to change the distribution of weights so that all means evolve in the same direction.

Sign in / Sign up

Export Citation Format

Share Document