15,942 research outputs found
Ground-state properties of the disordered Hubbard model in two dimensions
We study the interplay between electron correlation and disorder in the
two-dimensional Hubbard model at half-filling by means of a variational wave
function that can interpolate between Anderson and Mott insulators. We give a
detailed description of our improved variational state and explain how the
physics of the Anderson-Mott transition can be inferred from equal-time
correlations functions, which can be easily computed within the variational
Monte Carlo scheme. The ground-state phase diagram is worked out in both the
paramagnetic and the magnetic sector. Whereas in the former a direct
second-order Anderson-Mott transition is obtained, when magnetism is allowed
variationally, we find evidence for the formation of local magnetic moments
that order before the Mott transition. Although the localization length
increases before the Mott transition, we have no evidence for the stabilization
of a true metallic phase. The effect of a frustrating next-nearest-neighbor
hopping is also studied in some detail. In particular, we show that
has two primary effects. The first one is the narrowing of the
stability region of the magnetic Anderson insulator, also leading to a
first-order magnetic transition. The second and most important effect of a
frustrating hopping term is the development of a ``glassy'' phase at strong
couplings, where many paramagnetic states, with disordered local moments, may
be stabilized.Comment: 13 pages and 16 figure
Monte Carlo algorithms are very effective in finding the largest independent set in sparse random graphs
The effectiveness of stochastic algorithms based on Monte Carlo dynamics in
solving hard optimization problems is mostly unknown. Beyond the basic
statement that at a dynamical phase transition the ergodicity breaks and a
Monte Carlo dynamics cannot sample correctly the probability distribution in
times linear in the system size, there are almost no predictions nor intuitions
on the behavior of this class of stochastic dynamics. The situation is
particularly intricate because, when using a Monte Carlo based algorithm as an
optimization algorithm, one is usually interested in the out of equilibrium
behavior which is very hard to analyse. Here we focus on the use of Parallel
Tempering in the search for the largest independent set in a sparse random
graph, showing that it can find solutions well beyond the dynamical threshold.
Comparison with state-of-the-art message passing algorithms reveals that
parallel tempering is definitely the algorithm performing best, although a
theory explaining its behavior is still lacking.Comment: 14 pages, 12 figure
ECLAS CONFERENCE GHENT 2018 Landscapes of Conflict
ProducciĂłn CientĂficaThroughout the twentieth century, Friuli Venezia Giulia, the north-eastern region of Italy that borders Austria and Slovenia, played a strategic wartime role. From the Great War to the Cold War, the installation of defensive works including barracks, fortifications and infrastructure distinguished the territory. A significant rationalization in the territory and modification in the organizational structure of the Armed Forces took place from the end of the Cold War, through the EU expansion to the countries located on the north-eastern border of Italy, and up to the Army’s transformation from conscription to voluntary service. The town of Casarsa della Delizia represents a case of important significance due to the presence of the “Trieste” barracks, a settlement of extensive and significant environmental impact, a part of which has not been used for years, becoming over time a landscape-abandonment issue, on which action is needed. The paper focuses on the proposals to recover this former military area as a new integrated part of the city, merging the necessity of saving the past heritage and developing a new landscape vision, bringing together the historical and contemporary ways of living and promoting urban regeneration complex operations.European Joint Doctorate “urbanHIST”. European Union. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie SkĹ‚odowska-Curie grant agreement No 721933
Yet another approach to the Gough-Stewart platform forward kinematics
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The forward kinematics of the Gough-Stewart platform, and their simplified versions in which some leg endpoints coalesce, has been typically solved using variable elimination methods. In this paper, we cast doubts on whether this is the easiest way to solve the problem. We will see how the indirect approach in which the length of some extra virtual legs is first computed leads to important simplifications. In particular, we provide a procedure to solve 30 out of 34 possible topologies for a Gough-Stewart platform without variable elimination.Peer ReviewedPostprint (author's final draft
A new approach to the spatio-temporal pattern identification in neuronal multi-electrode registrations
A lot of methods were created in last decade for the spatio-temporal analysis of multi-electrode array (MEA) neuronal data sets. All these methods were implemented starting from a channel to channel analysis, with a great computational effort and onerous spatial pattern recognition task. 
Our idea is to approach the MEA data collection from a different point of view, i.e. considering all channels simultaneously. We transform the 2D plus time MEA signal in a mono-dimensional plus time signal and elaborate it as a normal 1D signal, using the Space-Amplitude Transform method. 
This geometrical transformation is completely invertible and allows to employ very fast processing algorithms. 

One-loop topological expansion for spin glasses in the large connectivity limit
We apply for the first time a new one-loop topological expansion around the
Bethe solution to the spin-glass model with field in the high connectivity
limit, following the methodological scheme proposed in a recent work. The
results are completely equivalent to the well known ones, found by standard
field theoretical expansion around the fully connected model (Bray and Roberts
1980, and following works). However this method has the advantage that the
starting point is the original Hamiltonian of the model, with no need to define
an associated field theory, nor to know the initial values of the couplings,
and the computations have a clear and simple physical meaning. Moreover this
new method can also be applied in the case of zero temperature, when the Bethe
model has a transition in field, contrary to the fully connected model that is
always in the spin glass phase. Sharing with finite dimensional model the
finite connectivity properties, the Bethe lattice is clearly a better starting
point for an expansion with respect to the fully connected model. The present
work is a first step towards the generalization of this new expansion to more
difficult and interesting cases as the zero-temperature limit, where the
expansion could lead to different results with respect to the standard one.Comment: 8 pages, 1 figur
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