273 research outputs found
Space--Time Tradeoffs for Subset Sum: An Improved Worst Case Algorithm
The technique of Schroeppel and Shamir (SICOMP, 1981) has long been the most
efficient way to trade space against time for the SUBSET SUM problem. In the
random-instance setting, however, improved tradeoffs exist. In particular, the
recently discovered dissection method of Dinur et al. (CRYPTO 2012) yields a
significantly improved space--time tradeoff curve for instances with strong
randomness properties. Our main result is that these strong randomness
assumptions can be removed, obtaining the same space--time tradeoffs in the
worst case. We also show that for small space usage the dissection algorithm
can be almost fully parallelized. Our strategy for dealing with arbitrary
instances is to instead inject the randomness into the dissection process
itself by working over a carefully selected but random composite modulus, and
to introduce explicit space--time controls into the algorithm by means of a
"bailout mechanism"
High rate locally-correctable and locally-testable codes with sub-polynomial query complexity
In this work, we construct the first locally-correctable codes (LCCs), and
locally-testable codes (LTCs) with constant rate, constant relative distance,
and sub-polynomial query complexity. Specifically, we show that there exist
binary LCCs and LTCs with block length , constant rate (which can even be
taken arbitrarily close to 1), constant relative distance, and query complexity
. Previously such codes were known to exist
only with query complexity (for constant ), and
there were several, quite different, constructions known.
Our codes are based on a general distance-amplification method of Alon and
Luby~\cite{AL96_codes}. We show that this method interacts well with local
correctors and testers, and obtain our main results by applying it to suitably
constructed LCCs and LTCs in the non-standard regime of \emph{sub-constant
relative distance}.
Along the way, we also construct LCCs and LTCs over large alphabets, with the
same query complexity , which additionally have
the property of approaching the Singleton bound: they have almost the
best-possible relationship between their rate and distance. This has the
surprising consequence that asking for a large alphabet error-correcting code
to further be an LCC or LTC with query
complexity does not require any sacrifice in terms of rate and distance! Such a
result was previously not known for any query complexity.
Our results on LCCs also immediately give locally-decodable codes (LDCs) with
the same parameters
Random Unitaries Give Quantum Expanders
We show that randomly choosing the matrices in a completely positive map from
the unitary group gives a quantum expander. We consider Hermitian and
non-Hermitian cases, and we provide asymptotically tight bounds in the
Hermitian case on the typical value of the second largest eigenvalue. The key
idea is the use of Schwinger-Dyson equations from lattice gauge theory to
efficiently compute averages over the unitary group.Comment: 14 pages, 1 figur
A PCP Characterization of AM
We introduce a 2-round stochastic constraint-satisfaction problem, and show
that its approximation version is complete for (the promise version of) the
complexity class AM. This gives a `PCP characterization' of AM analogous to the
PCP Theorem for NP. Similar characterizations have been given for higher levels
of the Polynomial Hierarchy, and for PSPACE; however, we suggest that the
result for AM might be of particular significance for attempts to derandomize
this class.
To test this notion, we pose some `Randomized Optimization Hypotheses'
related to our stochastic CSPs that (in light of our result) would imply
collapse results for AM. Unfortunately, the hypotheses appear over-strong, and
we present evidence against them. In the process we show that, if some language
in NP is hard-on-average against circuits of size 2^{Omega(n)}, then there
exist hard-on-average optimization problems of a particularly elegant form.
All our proofs use a powerful form of PCPs known as Probabilistically
Checkable Proofs of Proximity, and demonstrate their versatility. We also use
known results on randomness-efficient soundness- and hardness-amplification. In
particular, we make essential use of the Impagliazzo-Wigderson generator; our
analysis relies on a recent Chernoff-type theorem for expander walks.Comment: 18 page
Approximately coloring graphs without long induced paths
It is an open problem whether the 3-coloring problem can be solved in
polynomial time in the class of graphs that do not contain an induced path on
vertices, for fixed . We propose an algorithm that, given a 3-colorable
graph without an induced path on vertices, computes a coloring with
many colors. If the input graph is
triangle-free, we only need many
colors. The running time of our algorithm is if the input
graph has vertices and edges
Inapproximability of maximal strip recovery
In comparative genomic, the first step of sequence analysis is usually to
decompose two or more genomes into syntenic blocks that are segments of
homologous chromosomes. For the reliable recovery of syntenic blocks, noise and
ambiguities in the genomic maps need to be removed first. Maximal Strip
Recovery (MSR) is an optimization problem proposed by Zheng, Zhu, and Sankoff
for reliably recovering syntenic blocks from genomic maps in the midst of noise
and ambiguities. Given genomic maps as sequences of gene markers, the
objective of \msr{d} is to find subsequences, one subsequence of each
genomic map, such that the total length of syntenic blocks in these
subsequences is maximized. For any constant , a polynomial-time
2d-approximation for \msr{d} was previously known. In this paper, we show that
for any , \msr{d} is APX-hard, even for the most basic version of the
problem in which all gene markers are distinct and appear in positive
orientation in each genomic map. Moreover, we provide the first explicit lower
bounds on approximating \msr{d} for all . In particular, we show that
\msr{d} is NP-hard to approximate within . From the other
direction, we show that the previous 2d-approximation for \msr{d} can be
optimized into a polynomial-time algorithm even if is not a constant but is
part of the input. We then extend our inapproximability results to several
related problems including \cmsr{d}, \gapmsr{\delta}{d}, and
\gapcmsr{\delta}{d}.Comment: A preliminary version of this paper appeared in two parts in the
Proceedings of the 20th International Symposium on Algorithms and Computation
(ISAAC 2009) and the Proceedings of the 4th International Frontiers of
Algorithmics Workshop (FAW 2010
Electromagnetic Excitations and Responses in Nuclei from First Principles
We discuss the role of clustering on monopole, dipole, and quadrupole
excitations in nuclei in the framework of the ab initio symmetry-adapted
no-core shell model (SA-NCSM). The SA-NCSM starts from nucleon-nucleon
potentials and, by exploring symmetries known to dominate the nuclear dynamics,
can reach nuclei up through the calcium region by accommodating ultra-large
model spaces critical to descriptions of clustering and collectivity. The
results are based on calculations of electromagnetic sum rules and discretized
responses using the Lanczos algorithm, that can be used to determine response
functions, and for 4He are benchmarked against exact solutions of the
hyperspherical harmonics method. In particular, we focus on He, Be, and O
isotopes, including giant resonances and monopole sum rules.Comment: 6 pages, 4 figures, Proceedings of the Fourth International Workshop
on State of the Art in Nuclear Cluster Physics, Galveston, TX, USA, May
13-18, 201
Dynamic hierarchies in temporal directed networks
The outcome of interactions in many real-world systems can be often explained
by a hierarchy between the participants. Discovering hierarchy from a given
directed network can be formulated as follows: partition vertices into levels
such that, ideally, there are only forward edges, that is, edges from upper
levels to lower levels. In practice, the ideal case is impossible, so instead
we minimize some penalty function on the backward edges. One practical option
for such a penalty is agony, where the penalty depends on the severity of the
violation. In this paper we extend the definition of agony to temporal
networks. In this setup we are given a directed network with time stamped
edges, and we allow the rank assignment to vary over time. We propose 2
strategies for controlling the variation of individual ranks. In our first
variant, we penalize the fluctuation of the rankings over time by adding a
penalty directly to the optimization function. In our second variant we allow
the rank change at most once. We show that the first variant can be solved
exactly in polynomial time while the second variant is NP-hard, and in fact
inapproximable. However, we develop an iterative method, where we first fix the
change point and optimize the ranks, and then fix the ranks and optimize the
change points, and reiterate until convergence. We show empirically that the
algorithms are reasonably fast in practice, and that the obtained rankings are
sensible
Electromagnetic Excitations and Responses in Nuclei from First Principles
We discuss the role of clustering on monopole, dipole, and quadrupole
excitations in nuclei in the framework of the ab initio symmetry-adapted
no-core shell model (SA-NCSM). The SA-NCSM starts from nucleon-nucleon
potentials and, by exploring symmetries known to dominate the nuclear dynamics,
can reach nuclei up through the calcium region by accommodating ultra-large
model spaces critical to descriptions of clustering and collectivity. The
results are based on calculations of electromagnetic sum rules and discretized
responses using the Lanczos algorithm, that can be used to determine response
functions, and for 4He are benchmarked against exact solutions of the
hyperspherical harmonics method. In particular, we focus on He, Be, and O
isotopes, including giant resonances and monopole sum rules.Comment: 6 pages, 4 figures, Proceedings of the Fourth International Workshop
on State of the Art in Nuclear Cluster Physics, Galveston, TX, USA, May
13-18, 201
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