2,863 research outputs found
Learning to predict arbitrary quantum processes
We present an efficient machine learning (ML) algorithm for predicting any
unknown quantum process over qubits. For a wide range of
distributions on arbitrary -qubit states, we show that this ML
algorithm can learn to predict any local property of the output from the
unknown process , with a small average error over input states
drawn from . The ML algorithm is computationally efficient even
when the unknown process is a quantum circuit with exponentially many gates.
Our algorithm combines efficient procedures for learning properties of an
unknown state and for learning a low-degree approximation to an unknown
observable. The analysis hinges on proving new norm inequalities, including a
quantum analogue of the classical Bohnenblust-Hille inequality, which we derive
by giving an improved algorithm for optimizing local Hamiltonians. Overall, our
results highlight the potential for ML models to predict the output of complex
quantum dynamics much faster than the time needed to run the process itself.Comment: 10 pages, 1 figure + 38-page appendix; v2: Added a figure and fixed a
minor formatting issu
Lateralized occipito-temporal N1 responses to images of salient distorted finger postures
For humans as social beings, other people’s hands are highly visually conspicuous. Exceptionally striking are hands in other than natural configuration which have been found to elicit distinct brain activation. Here we studied response strength and lateralization of this activation using event-related potentials (ERPs), in particular, occipitotemporal N1 responses as correlates of activation in extrastriate body area. Participants viewed computer-generated images of hands, half of them showing distorted fingers, the other half showing natural fingers. As control stimuli of similar geometric complexity, images of chairs were shown, half of them with distorted legs, half with standard legs. The contrast of interest was between distorted and natural/standard stimuli. For hands, stronger N1 responses were observed for distorted (vs natural) stimuli from 170 ms post stimulus. Such stronger N1 responses were found for distorted hands and absent for distorted chairs, therefore likely unrelated to visuospatial processing of the unusual distorted shapes. Rather, N1 modulation over both hemispheres - but robustly right-lateralized - could reflect distorted hands as emotionally laden stimuli. The results are in line with privileged visual processing of hands as highly salient body parts, with distortions engaging neural resources that are especially activated for biological stimuli in social perception
Retraction and Generalized Extension of Computing with Words
Fuzzy automata, whose input alphabet is a set of numbers or symbols, are a
formal model of computing with values. Motivated by Zadeh's paradigm of
computing with words rather than numbers, Ying proposed a kind of fuzzy
automata, whose input alphabet consists of all fuzzy subsets of a set of
symbols, as a formal model of computing with all words. In this paper, we
introduce a somewhat general formal model of computing with (some special)
words. The new features of the model are that the input alphabet only comprises
some (not necessarily all) fuzzy subsets of a set of symbols and the fuzzy
transition function can be specified arbitrarily. By employing the methodology
of fuzzy control, we establish a retraction principle from computing with words
to computing with values for handling crisp inputs and a generalized extension
principle from computing with words to computing with all words for handling
fuzzy inputs. These principles show that computing with values and computing
with all words can be respectively implemented by computing with words. Some
algebraic properties of retractions and generalized extensions are addressed as
well.Comment: 13 double column pages; 3 figures; to be published in the IEEE
Transactions on Fuzzy System
Gender differences in ankylosing spondylitis-associated cumulative healthcare utilization: a population-based cohort study
BACKGROUND: Ankylosing spondylitis (AS) is one of the most common rheumatic diseases with gender differences in prevalence and clinical presentation. This study aimed to examine whether such gender differences are correlated with cumulative healthcare utilization in Taiwan. METHODS: The National Health Insurance Research Database supplied claim records of one million individuals from 1996 to 2007. Selected cases included patients aged >16 years. Certified rheumatologists diagnosed the patients in three or more visits and gave prescriptions for AS. Multivariate adjusted logistic regression analyses were used to calculate the influence of gender on cumulative healthcare utilization associated with AS. RESULTS: The study included 228 women and 636 men. After adjustment for potential confounding factors, men had more cumulative outpatient visits associated with AS (odds ratio, 1.59; 95% confidence interval, 1.13 -2.23; p = 0.008). Men also exhibited a trend for higher frequency of AS-related hospitalization (p = 0.054). CONCLUSION: Men are more likely to have high cumulative AS-associated healthcare utilization than women. Further investigation of the causal factors is warranted
Local minima in quantum systems
Finding ground states of quantum many-body systems is known to be hard for
both classical and quantum computers. As a result, when Nature cools a quantum
system in a low-temperature thermal bath, the ground state cannot always be
found efficiently. Instead, Nature finds a local minimum of the energy. In this
work, we study the problem of finding local minima in quantum systems under
thermal perturbations. While local minima are much easier to find than ground
states, we show that finding a local minimum is computationally hard for
classical computers, even when the task is to output a single-qubit observable
at any local minimum. In contrast, we prove that a quantum computer can always
find a local minimum efficiently using a thermal gradient descent algorithm
that mimics the cooling process in Nature. To establish the classical hardness
of finding local minima, we consider a family of two-dimensional Hamiltonians
such that any problem solvable by polynomial-time quantum algorithms can be
reduced to finding ground states of these Hamiltonians. We prove that for such
Hamiltonians, all local minima are global minima. Therefore, assuming quantum
computation is more powerful than classical computation, finding local minima
is classically hard and quantumly easy.Comment: 9+80 pages, 4 figure
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