118 research outputs found
Redundancy and error resilience in Boolean Networks
We consider the effect of noise in sparse Boolean Networks with redundant
functions. We show that they always exhibit a non-zero error level, and the
dynamics undergoes a phase transition from non-ergodicity to ergodicity, as a
function of noise, after which the system is no longer capable of preserving a
memory if its initial state. We obtain upper-bounds on the critical value of
noise for networks of different sparsity.Comment: 4 pages, 5 figure
Parametrised Complexity of Model Checking and Satisfiability in Propositional Dependence Logic
In this paper, we initiate a systematic study of the parametrised complexity
in the field of Dependence Logics which finds its origin in the Dependence
Logic of V\"a\"an\"anen from 2007. We study a propositional variant of this
logic (PDL) and investigate a variety of parametrisations with respect to the
central decision problems. The model checking problem (MC) of PDL is
NP-complete. The subject of this research is to identify a list of
parametrisations (formula-size, treewidth, treedepth, team-size, number of
variables) under which MC becomes fixed-parameter tractable. Furthermore, we
show that the number of disjunctions or the arity of dependence atoms
(dep-arity) as a parameter both yield a paraNP-completeness result. Then, we
consider the satisfiability problem (SAT) showing a different picture: under
team-size, or dep-arity SAT is paraNP-complete whereas under all other
mentioned parameters the problem is in FPT. Finally, we introduce a variant of
the satisfiability problem, asking for teams of a given size, and show for this
problem an almost complete picture.Comment: Update includes refined result
Making Classical Ground State Spin Computing Fault-Tolerant
We examine a model of classical deterministic computing in which the ground
state of the classical system is a spatial history of the computation. This
model is relevant to quantum dot cellular automata as well as to recent
universal adiabatic quantum computing constructions. In its most primitive
form, systems constructed in this model cannot compute in an error free manner
when working at non-zero temperature. However, by exploiting a mapping between
the partition function for this model and probabilistic classical circuits we
are able to show that it is possible to make this model effectively error free.
We achieve this by using techniques in fault-tolerant classical computing and
the result is that the system can compute effectively error free if the
temperature is below a critical temperature. We further link this model to
computational complexity and show that a certain problem concerning finite
temperature classical spin systems is complete for the complexity class
Merlin-Arthur. This provides an interesting connection between the physical
behavior of certain many-body spin systems and computational complexity.Comment: 24 pages, 1 figur
Random geometric complexes
We study the expected topological properties of Cech and Vietoris-Rips
complexes built on i.i.d. random points in R^d. We find higher dimensional
analogues of known results for connectivity and component counts for random
geometric graphs. However, higher homology H_k is not monotone when k > 0. In
particular for every k > 0 we exhibit two thresholds, one where homology passes
from vanishing to nonvanishing, and another where it passes back to vanishing.
We give asymptotic formulas for the expectation of the Betti numbers in the
sparser regimes, and bounds in the denser regimes. The main technical
contribution of the article is in the application of discrete Morse theory in
geometric probability.Comment: 26 pages, 3 figures, final revisions, to appear in Discrete &
Computational Geometr
Algebraic Theory of Promise Constraint Satisfaction Problems, First Steps
What makes a computational problem easy (e.g., in P, that is, solvable in
polynomial time) or hard (e.g., NP-hard)? This fundamental question now has a
satisfactory answer for a quite broad class of computational problems, so
called fixed-template constraint satisfaction problems (CSPs) -- it has turned
out that their complexity is captured by a certain specific form of symmetry.
This paper explains an extension of this theory to a much broader class of
computational problems, the promise CSPs, which includes relaxed versions of
CSPs such as the problem of finding a 137-coloring of a 3-colorable graph
Critical exponents for random knots
The size of a zero thickness (no excluded volume) polymer ring is shown to
scale with chain length in the same way as the size of the excluded volume
(self-avoiding) linear polymer, as , where . The
consequences of that fact are examined, including sizes of trivial and
non-trivial knots.Comment: 4 pages, 0 figure
Abundance of unknots in various models of polymer loops
A veritable zoo of different knots is seen in the ensemble of looped polymer
chains, whether created computationally or observed in vitro. At short loop
lengths, the spectrum of knots is dominated by the trivial knot (unknot). The
fractional abundance of this topological state in the ensemble of all
conformations of the loop of segments follows a decaying exponential form,
, where marks the crossover from a mostly unknotted
(ie topologically simple) to a mostly knotted (ie topologically complex)
ensemble. In the present work we use computational simulation to look closer
into the variation of for a variety of polymer models. Among models
examined, is smallest (about 240) for the model with all segments of the
same length, it is somewhat larger (305) for Gaussian distributed segments, and
can be very large (up to many thousands) when the segment length distribution
has a fat power law tail.Comment: 13 pages, 6 color figure
Tightness of slip-linked polymer chains
We study the interplay between entropy and topological constraints for a
polymer chain in which sliding rings (slip-links) enforce pair contacts between
monomers. These slip-links divide a closed ring polymer into a number of
sub-loops which can exchange length between each other. In the ideal chain
limit, we find the joint probability density function for the sizes of segments
within such a slip-linked polymer chain (paraknot). A particular segment is
tight (small in size) or loose (of the order of the overall size of the
paraknot) depending on both the number of slip-links it incorporates and its
competition with other segments. When self-avoiding interactions are included,
scaling arguments can be used to predict the statistics of segment sizes for
certain paraknot configurations.Comment: 10 pages, 6 figures, REVTeX
Static-Memory-Hard Functions, and Modeling the Cost of Space vs. Time
A series of recent research starting with (Alwen and Serbinenko, STOC 2015) has deepened our understanding of the notion of memory-hardness in cryptography — a useful property of hash functions for deterring large-scale password-cracking attacks — and has shown memory-hardness to have intricate connections with the theory of graph pebbling. Definitions of memory-hardness are not yet unified in the somewhat nascent field of memory-hardness, however, and the guarantees proven to date are with respect to a range of proposed definitions. In this paper, we observe two significant and practical considerations that are not analyzed by existing models of memory-hardness, and propose new models to capture them, accompanied by constructions based on new hard-to-pebble graphs. Our contribution is two-fold, as follows.
First, existing measures of memory-hardness only account for dynamic memory usage (i.e., memory read/written at runtime), and do not consider static memory usage (e.g., memory on disk). Among other things, this means that memory requirements considered by prior models are inherently upper-bounded by a hash function’s runtime; in contrast, counting static memory would potentially allow quantification of much larger memory requirements, decoupled from runtime. We propose a new definition of static-memory-hard function (SHF) which takes static memory into account: we model static memory usage by oracle access to a large preprocessed string, which may be considered part of the hash function description. Static memory requirements are complementary to dynamic memory requirements: neither can replace the other, and to deter large-scale password-cracking attacks, a hash function will benefit from being both dynamic memory-hard and static-memory-hard. We give two SHF constructions based on pebbling. To prove static-memory-hardness, we define a new pebble game (“black-magic pebble game”), and new graph constructions with optimal complexity under our proposed measure. Moreover, we provide a prototype implementation of our first SHF construction (which is based on pebbling of a simple “cylinder” graph), providing an initial demonstration of practical feasibility for a limited range of parameter settings.
Secondly, existing memory-hardness models implicitly assume that the cost of space and time are more or less on par: they consider only linear ratios between the costs of time and space. We propose a new model to capture nonlinear time-space trade-offs: e.g., how is the adversary impacted when space is quadratically more expensive than time? We prove that nonlinear tradeoffs can in fact cause adversaries to employ different strategies from linear tradeoffs. Finally, as an additional contribution of independent interest, we present an asymptotically tight graph construction that achieves the best possible space complexity up to log log n-factors for an existing memory-hardness measure called cumulative complexity in the sequential pebbling model
Oblivious tight compaction in O(n) time with smaller constant
Oblivious compaction is a crucial building block for hash-based oblivious RAM. Asharov et al. recently gave a O(n) algorithm for oblivious tight compaction. Their algorithm is deterministic and asymptotically optimal, but it is not practical to implement because the implied constant is . We give a new algorithm for oblivious tight compaction that runs in time . As part of our construction, we give a new result in the bootstrap percolation of random regular graphs
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