345 research outputs found
The six-point remainder function to all loop orders in the multi-Regge limit
We present an all-orders formula for the six-point amplitude of planar
maximally supersymmetric N=4 Yang-Mills theory in the leading-logarithmic
approximation of multi-Regge kinematics. In the MHV helicity configuration, our
results agree with an integral formula of Lipatov and Prygarin through at least
14 loops. A differential equation linking the MHV and NMHV helicity
configurations has a natural action in the space of functions relevant to this
problem---the single-valued harmonic polylogarithms introduced by Brown. These
functions depend on a single complex variable and its conjugate, w and w*,
which are quadratically related to the original kinematic variables. We
investigate the all-orders formula in the near-collinear limit, which is
approached as |w|->0. Up to power-suppressed terms, the resulting expansion may
be organized by powers of log|w|. The leading term of this expansion agrees
with the all-orders double-leading-logarithmic approximation of Bartels,
Lipatov, and Prygarin. The explicit form for the sub-leading powers of log|w|
is given in terms of modified Bessel functions.Comment: 25 pages, 1 figur
Impression management and formation on Facebook: A lens model approach
To extend research on online impression formation and warranting theory, the present investigation reports a Brunswick lens model analysis of Facebook profiles. Facebook users’ (N = 100) personality (i.e., extraversion, agreeableness, conscientiousness, neuroticism, openness) was self-reported. Facebook users’ profiles were then content analyzed for the presence and rate of 53 cues. Observers (N = 35), who were strangers to profile owners, estimated profile owner personality. Results indicate that observers could accurately estimate profile owners’ extraversion, agreeableness, and conscientiousness. For all personality traits except neuroticism, unique profile cues were diagnostic warrants of personality (i.e., indicative of profile owner personality and used to estimate personality by strangers). The results are discussed in relation to warranting theory, impression formation, and lens model research
Easy over Hard: A Case Study on Deep Learning
While deep learning is an exciting new technique, the benefits of this method
need to be assessed with respect to its computational cost. This is
particularly important for deep learning since these learners need hours (to
weeks) to train the model. Such long training time limits the ability of (a)~a
researcher to test the stability of their conclusion via repeated runs with
different random seeds; and (b)~other researchers to repeat, improve, or even
refute that original work.
For example, recently, deep learning was used to find which questions in the
Stack Overflow programmer discussion forum can be linked together. That deep
learning system took 14 hours to execute. We show here that applying a very
simple optimizer called DE to fine tune SVM, it can achieve similar (and
sometimes better) results. The DE approach terminated in 10 minutes; i.e. 84
times faster hours than deep learning method.
We offer these results as a cautionary tale to the software analytics
community and suggest that not every new innovation should be applied without
critical analysis. If researchers deploy some new and expensive process, that
work should be baselined against some simpler and faster alternatives.Comment: 12 pages, 6 figures, accepted at FSE201
sk_p: a neural program corrector for MOOCs
We present a novel technique for automatic program correction in MOOCs,
capable of fixing both syntactic and semantic errors without manual, problem
specific correction strategies. Given an incorrect student program, it
generates candidate programs from a distribution of likely corrections, and
checks each candidate for correctness against a test suite.
The key observation is that in MOOCs many programs share similar code
fragments, and the seq2seq neural network model, used in the natural-language
processing task of machine translation, can be modified and trained to recover
these fragments.
Experiment shows our scheme can correct 29% of all incorrect submissions and
out-performs state of the art approach which requires manual, problem specific
correction strategies
Bootstrapping six-gluon scattering in planar super-Yang-Mills theory
We describe the hexagon function bootstrap for solving for six-gluon
scattering amplitudes in the large limit of super-Yang-Mills
theory. In this method, an ansatz for the finite part of these amplitudes is
constrained at the level of amplitudes, not integrands, using boundary
information. In the near-collinear limit, the dual picture of the amplitudes as
Wilson loops leads to an operator product expansion which has been solved using
integrability by Basso, Sever and Vieira. Factorization of the amplitudes in
the multi-Regge limit provides additional boundary data. This bootstrap has
been applied successfully through four loops for the maximally helicity
violating (MHV) configuration of gluon helicities, and through three loops for
the non-MHV case.Comment: 15 pages, 3 figures, 2 tables; contribution to the proceedings of
Loops and Legs in Quantum Field Theory, 27 April - 2 May 2014, Weimar,
Germany; v2, reference adde
- …