25,200 research outputs found
Proliferation of Post-Newtonian, Non-Relativistic Theories
Theoreticians have formulated a set of fundamental criteria that any theory of gravity should satisfy, two purely theoretical and two that are based on experimental evidence. Thus, a theory must be complete (capable of analyzing from the "first principles" the result of any experiment of interest), self-consistent (its prediction for the outcome of each experiment must be unique), relativistic (at the limit when gravity is neglected compared to other physical interactions, non-gravitational laws of physics must be reduced to special relativity laws), and with the correct Newtonian limit (within the limits of weak gravitational fields and slow motions, they must reproduce Newton's laws).
DOI: 10.13140/RG.2.2.27848.2688
The new path of law : from theory of chaos to theory of law
From chaos to chaos theory, from the primordial perception of the world as disorderly to the scientific research of disorder a long distance has been covered. This path implies openness of mind and scientific boldness which connect mythological perceptions of the world with philosophical and scientific interpretations of phenomena throughout the world in a quite distinctive way resting on the creation of a model and application of computing. Owing to this, for the first time instead of asking What awaits us in the future? we can ask What can be done in the future? and get a reliable scientific answer to the question
Theoretical and computational tools to model multistable gene regulatory networks
The last decade has witnessed a surge of theoretical and computational models
to describe the dynamics of complex gene regulatory networks, and how these
interactions can give rise to multistable and heterogeneous cell populations.
As the use of theoretical modeling to describe genetic and biochemical circuits
becomes more widespread, theoreticians with mathematics and physics backgrounds
routinely apply concepts from statistical physics, non-linear dynamics, and
network theory to biological systems. This review aims at providing a clear
overview of the most important methodologies applied in the field while
highlighting current and future challenges, and includes hands-on tutorials to
solve and simulate some of the archetypical biological system models used in
the field. Furthermore, we provide concrete examples from the existing
literature for theoreticians that wish to explore this fast-developing field.
Whenever possible, we highlight the similarities and differences between
biochemical and regulatory networks and classical systems typically studied in
non-equilibrium statistical and quantum mechanics.Comment: 73 pages, 12 figure
Towards a Theory-Guided Benchmarking Suite for Discrete Black-Box Optimization Heuristics: Profiling EA Variants on OneMax and LeadingOnes
Theoretical and empirical research on evolutionary computation methods
complement each other by providing two fundamentally different approaches
towards a better understanding of black-box optimization heuristics. In
discrete optimization, both streams developed rather independently of each
other, but we observe today an increasing interest in reconciling these two
sub-branches. In continuous optimization, the COCO (COmparing Continuous
Optimisers) benchmarking suite has established itself as an important platform
that theoreticians and practitioners use to exchange research ideas and
questions. No widely accepted equivalent exists in the research domain of
discrete black-box optimization.
Marking an important step towards filling this gap, we adjust the COCO
software to pseudo-Boolean optimization problems, and obtain from this a
benchmarking environment that allows a fine-grained empirical analysis of
discrete black-box heuristics. In this documentation we demonstrate how this
test bed can be used to profile the performance of evolutionary algorithms.
More concretely, we study the optimization behavior of several EA
variants on the two benchmark problems OneMax and LeadingOnes. This comparison
motivates a refined analysis for the optimization time of the EA
on LeadingOnes
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