1,601 research outputs found
(Tissue) P Systems with Vesicles of Multisets
We consider tissue P systems working on vesicles of multisets with the very
simple operations of insertion, deletion, and substitution of single objects.
With the whole multiset being enclosed in a vesicle, sending it to a target
cell can be indicated in those simple rules working on the multiset. As
derivation modes we consider the sequential mode, where exactly one rule is
applied in a derivation step, and the set maximal mode, where in each
derivation step a non-extendable set of rules is applied. With the set maximal
mode, computational completeness can already be obtained with tissue P systems
having a tree structure, whereas tissue P systems even with an arbitrary
communication structure are not computationally complete when working in the
sequential mode. Adding polarizations (-1, 0, 1 are sufficient) allows for
obtaining computational completeness even for tissue P systems working in the
sequential mode.Comment: In Proceedings AFL 2017, arXiv:1708.0622
(Tissue) P Systems with Vesicles of Multisets
We consider tissue P systems working on vesicles of multisets with the very
simple operations of insertion, deletion, and substitution of single objects.
With the whole multiset being enclosed in a vesicle, sending it to a target
cell can be indicated in those simple rules working on the multiset. As
derivation modes we consider the sequential mode, where exactly one rule is
applied in a derivation step, and the set maximal mode, where in each
derivation step a non-extendable set of rules is applied. With the set maximal
mode, computational completeness can already be obtained with tissue P systems
having a tree structure, whereas tissue P systems even with an arbitrary
communication structure are not computationally complete when working in the
sequential mode. Adding polarizations (-1, 0, 1 are sufficient) allows for
obtaining computational completeness even for tissue P systems working in the
sequential mode.Comment: In Proceedings AFL 2017, arXiv:1708.0622
One-Membrane P Systems with Activation and Blocking of Rules
We introduce new possibilities to control the application of rules based on
the preceding applications, which can be de ned in a general way for (hierarchical) P
systems and the main known derivation modes. Computational completeness can be
obtained even for one-membrane P systems with non-cooperative rules and using both
activation and blocking of rules, especially for the set modes of derivation.
When we allow the application of rules to in
uence the application of rules in previous
derivation steps, applying a non-conservative semantics for what we consider to be a
derivation step, we can even \go beyond Turing"
A new P-Lingua toolkit for agile development in membrane computing
Membrane computing is a massively parallel and non-deterministic bioinspired computing paradigm whose models are called P systems. Validating and testing such models is a challenge which is being overcome by developing simulators. Regardless of their heterogeneity, such simulators require to read and interpret the models to be simulated. To this end, P-Lingua is a high-level P system definition language which has been widely used in the last decade. The P-Lingua ecosystem includes not only the language, but also libraries and software tools for parsing and simulating membrane computing models. Each version of P-Lingua supported new types or variants of P systems. This leads to a shortcoming: Only a predefined list of variants can be used, thus making it difficult for researchers to study custom ones. Moreover, derivation modes cannot be user-defined, i.e, the way in which P system computations should be generated is determined by the simulation algorithm in the source code.
The main contribution of this paper is a completely new design of the P-Lingua language, called P-Lingua 5, in which the user can define custom variants and derivation modes, among other improvements such as including procedural programming and simulation directives. It is worth mentioning that it has backward-compatibility with previous versions of the language. A completely new set of command-line tools is provided for parsing and simulating P-Lingua 5 files. Finally, several examples are included in this paper covering the most common P system types.Agencia Estatal de InvestigaciĂłn TIN2017-89842-
Theory of coupled neuronal-synaptic dynamics
In neural circuits, synaptic strengths influence neuronal activity by shaping
network dynamics, and neuronal activity influences synaptic strengths through
activity-dependent plasticity. Motivated by this fact, we study a
recurrent-network model in which neuronal units and synaptic couplings are
interacting dynamic variables, with couplings subject to Hebbian modification
with decay around quenched random strengths. Rather than assigning a specific
role to the plasticity, we use dynamical mean-field theory and other techniques
to systematically characterize the neuronal-synaptic dynamics, revealing a rich
phase diagram. Adding Hebbian plasticity slows activity in chaotic networks and
can induce chaos in otherwise quiescent networks. Anti-Hebbian plasticity
quickens activity and produces an oscillatory component. Analysis of the
Jacobian shows that Hebbian and anti-Hebbian plasticity push locally unstable
modes toward the real and imaginary axes, explaining these behaviors. Both
random-matrix and Lyapunov analysis show that strong Hebbian plasticity
segregates network timescales into two bands with a slow, synapse-dominated
band driving the dynamics, suggesting a flipped view of the network as synapses
connected by neurons. For increasing strength, Hebbian plasticity initially
raises the complexity of the dynamics, measured by the maximum Lyapunov
exponent and attractor dimension, but then decreases these metrics, likely due
to the proliferation of stable fixed points. We compute the marginally stable
spectra of such fixed points as well as their number, showing exponential
growth with network size. In chaotic states with strong Hebbian plasticity, a
stable fixed point of neuronal dynamics is destabilized by synaptic dynamics,
allowing any neuronal state to be stored as a stable fixed point by halting the
plasticity. This phase of freezable chaos offers a new mechanism for working
memory.Comment: 20 pages, 9 figure
The Capabilities of Chaos and Complexity
To what degree could chaos and complexity have organized a Peptide or RNA World of crude yet necessarily integrated protometabolism? How far could such protolife evolve in the absence of a heritable linear digital symbol system that could mutate, instruct, regulate, optimize and maintain metabolic homeostasis? To address these questions, chaos, complexity, self-ordered states, and organization must all be carefully defined and distinguished. In addition their cause-and-effect relationships and mechanisms of action must be delineated. Are there any formal (non physical, abstract, conceptual, algorithmic) components to chaos, complexity, self-ordering and organization, or are they entirely physicodynamic (physical, mass/energy interaction alone)? Chaos and complexity can produce some fascinating self-ordered phenomena. But can spontaneous chaos and complexity steer events and processes toward pragmatic benefit, select function over non function, optimize algorithms, integrate circuits, produce computational halting, organize processes into formal systems, control and regulate existing systems toward greater efficiency? The question is pursued of whether there might be some yet-to-be discovered new law of biology that will elucidate the derivation of prescriptive information and control. âSystemâ will be rigorously defined. Can a low-informational rapid succession of Prigogineâs dissipative structures self-order into bona fide organization
REGULAR LANGUAGES: TO FINITE AUTOMATA AND BEYOND - SUCCINCT DESCRIPTIONS AND OPTIMAL SIMULATIONS
\uc8 noto che i linguaggi regolari \u2014 o di tipo 3 \u2014 sono equivalenti agli automi a stati finiti. Tuttavia, in letteratura sono presenti altre caratterizzazioni di questa classe di linguaggi, in termini di modelli riconoscitori e grammatiche. Per esempio, limitando le risorse computazionali di modelli pi\uf9 generali, quali grammatiche context-free, automi a pila e macchine di Turing, che caratterizzano classi di linguaggi pi\uf9 ampie, \ue8 possibile ottenere modelli che generano o riconoscono solamente i linguaggi regolari. I dispositivi risultanti forniscono delle rappresentazioni alternative dei linguaggi di tipo 3, che, in alcuni casi, risultano significativamente pi\uf9 compatte rispetto a quelle dei modelli che caratterizzano la stessa classe di linguaggi. Il presente lavoro ha l\u2019obiettivo di studiare questi modelli formali dal punto di vista della complessit\ue0 descrizionale, o, in altre parole, di analizzare le relazioni tra le loro dimensioni, ossia il numero di simboli utilizzati per specificare la loro descrizione. Sono presentati, inoltre, alcuni risultati connessi allo studio della famosa domanda tuttora aperta posta da Sakoda e Sipser nel 1978, inerente al costo, in termini di numero di stati, per l\u2019eliminazione del nondeterminismo dagli automi stati finiti sfruttando la capacit\ue0 degli automi two-way deterministici di muovere la testina avanti e indietro sul nastro di input.It is well known that regular \u2014 or type 3 \u2014 languages are equivalent to finite automata. Nevertheless, many other characterizations of this class of languages in terms of computational devices and generative models are present in the literature. For example, by suitably restricting more general models such as context-free grammars, pushdown automata, and Turing machines, that characterize wider classes of languages, it is possible to obtain formal models that generate or recognize regular languages only. The resulting formalisms provide alternative representations of type 3 languages that may be significantly more concise than other models that share the same expressing power. The goal of this work is to investigate these formal systems from a descriptional complexity perspective, or, in other words, to study the relationships between their sizes, namely the number of symbols used to write down their descriptions. We also present some results related to the investigation of the famous question posed by Sakoda and Sipser in 1978, concerning the size blowups from nondeterministic finite automata to two-way deterministic finite automata
Membrane systems with limited parallelism
Membrane computing is an emerging research field that belongs to the more general area of molecular computing, which deals with computational models inspired from bio-molecular processes. Membrane computing aims at defining models, called membrane systems or P systems, which abstract the functioning and structure of the cell. A membrane system consists of a hierarchical arrangement of membranes delimiting regions, which represent various compartments of a cell, and with each region containing bio-chemical elements of various types and having associated evolution rules, which represent bio-chemical processes taking place inside the cell.
This work is a continuation of the investigations aiming to bridge membrane computing (where in a compartmental cell-like structure the chemicals to evolve are placed in compartments defined by membranes) and brane calculi (where one considers again a compartmental cell-like structure with the chemicals/proteins placed on the membranes themselves). We use objects both in compartments and on membranes (the latter are called proteins), with the objects from membranes evolving under the control of the proteins. Several possibilities are considered (objects only moved across membranes or also changed during this operation, with the proteins only assisting the move/change or also changing themselves). Somewhat expected, computational universality is obtained for several combinations of such possibilities.
We also present a method for solving the NP-complete SAT problem using P systems with proteins on membranes. The SAT problem is solved in O(nm) time, where n is the number of boolean variables and m is the number of clauses for an instance written in conjunctive normal form. Thus, we can say that the solution for each given instance is obtained in linear time. We succeeded in solving SAT by a uniform construction of a deterministic P system which uses rules involving objects in regions, proteins on membranes, and membrane division.
Then, we investigate the computational power of P systems with proteins on membranes in some particular cases: when only one protein is placed on a membrane, when the systems have a minimal number of rules, when the computation evolves in accepting or computing mode, etc.
This dissertation introduces also another new variant of membrane systems that uses context-free rewriting rules for the evolution of objects placed inside compartments of a cell, and symport rules for communication between membranes. The strings circulate across membranes depending on their membership to regular languages given by means of regular expressions. We prove that these rewriting-symport P systems generate all recursively enumerable languages. We investigate the computational power of these newly introduced P systems for three particular forms of the regular expressions that are used by the symport rules. A characterization of ET0L languages is obtained in this context
Computing the Noncomputable
We explore in the framework of Quantum Computation the notion of
computability, which holds a central position in Mathematics and Theoretical
Computer Science. A quantum algorithm that exploits the quantum adiabatic
processes is considered for the Hilbert's tenth problem, which is equivalent to
the Turing halting problem and known to be mathematically noncomputable.
Generalised quantum algorithms are also considered for some other mathematical
noncomputables in the same and of different noncomputability classes. The key
element of all these algorithms is the measurability of both the values of
physical observables and of the quantum-mechanical probability distributions
for these values. It is argued that computability, and thus the limits of
Mathematics, ought to be determined not solely by Mathematics itself but also
by physical principles.Comment: Extensively revised and enlarged with: 2 new subsections, 4 new
figures, 1 new reference, and a short biography as requested by the journal
edito
Gravitational Collapse in Turbulent Molecular Clouds. I. Gasdynamical Turbulence
Observed molecular clouds often appear to have very low star formation
efficiencies and lifetimes an order of magnitude longer than their free-fall
times. Their support is attributed to the random supersonic motions observed in
them. We study the support of molecular clouds against gravitational collapse
by supersonic, gas dynamical turbulence using direct numerical simulation.
Computations with two different algorithms are compared: a particle-based,
Lagrangian method (SPH), and a grid-based, Eulerian, second-order method
(ZEUS). The effects of both algorithm and resolution can be studied with this
method. We find that, under typical molecular cloud conditions, global collapse
can indeed be prevented, but density enhancements caused by strong shocks
nevertheless become gravitationally unstable and collapse into dense cores and,
presumably, stars. The occurance and efficiency of local collapse decreases as
the driving wave length decreases and the driving strength increases. It
appears that local collapse can only be prevented entirely with unrealistically
short wave length driving, but observed core formation rates can be reproduced
with more realistic driving. At high collapse rates, cores are formed on short
time scales in coherent structures with high efficiency, while at low collapse
rates they are scattered randomly throughout the region and exhibit
considerable age spread. We suggest that this naturally explains the observed
distinction between isolated and clustered star formation.Comment: Minor revisions in response to referee, thirteen figures, accepted to
Astrophys.
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