12,123 research outputs found
Resonant Quantum Search with Monitor Qubits
We present an algorithm for the generalized search problem (searching
marked items among items) based on a continuous Hamiltonian and exploiting
resonance. This resonant algorithm has the same time complexity
as the Grover algorithm. A natural extension of the algorithm, incorporating
auxiliary "monitor" qubits, can determine precisely, if it is unknown. The
time complexity of our counting algorithm is , similar to the best
quantum approximate counting algorithm, or better, given appropriate physical
resources.Comment: 12 pages, 1 figur
Berry phase induced dimerization in one-dimensional quadrupolar systems
We investigate the effect of the Berry phase on quadrupoles that occur for
example in the low-energy description of spin models. Specifically we study
here the one-dimensional bilinear-biquadratic spin-one model. An open question
for many years about this model is whether it has a non-dimerized fluctuating
nematic phase. The dimerization has recently been proposed to be related to
Berry phases of the quantum fluctuations. We use an effective low-energy
description to calculate the scaling of the dimerization according to this
theory, and then verify the predictions using large scale density-matrix
renormalization group (DMRG) simulations, giving good evidence that the state
is dimerized all the way up to its transition into the ferromagnetic phase. We
furthermore discuss the multiplet structure found in the entanglement spectrum
of the ground state wave functions.Comment: 4.5 pages + 4 pages supplementary material, 4 figure
Understanding Opportunities in Social Entrepreneurship: A Critical Realist Abstraction
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper extends social entrepreneurship (SE) research by drawing upon a critical realist perspective to analyse dynamic structure/agency relations in SE opportunity emergence, illustrated by empirical evidence. Our findings demonstrate an agential aspect (opportunity actualisation following a path-dependent seeding-growing-shaping process) and a structural aspect (institutional, cognitive and embedded structures necessary for SE opportunity emergence) related to SE opportunities. These structures provide three boundary conditions for SE agency: institutional discrimination, an SE belief system and social feasibility. Within this paper, we develop a novel theoretical framework to analyse SE opportunities plus, an applicable tool to advance related empirical research
Quantum Frenkel-Kontorova Model
This paper gives a review of our recent work on the quantum Frenkel-Kontorova
model. Using the squeezed state theory and the quantum Monte Carlo method, we
have studied the effects of quantum fluctuations on the Aubry transition and
the behavior of the ground state wave function. We found that quantum
fluctuations renormalize the sinusoidal standard map to a sawtooth map.
Although quantum fluctuations have smeared the Aubry transition, the remnants
of this transition are still discernible. The ground state wave function also
changes from an extended state to a localized state. The squeezed state results
agree very well with those from the Monte Carlo and mean field studies.Comment: 20 pages in elsart.sty, 11 eps figure
Meta-Learning For Vision-and-Language Cross-lingual Transfer
Current pre-trained vison-language models (PVLMs) achieve excellent
performance on a range of multi-modal datasets. Recent work has aimed at
building multilingual models, and a range of novel multilingual multi-modal
datasets have been proposed. Current PVLMs typically perform poorly on these
datasets when used for multi-modal zero-shot or few-shot cross-lingual
transfer, especially for low-resource languages. To alleviate this problem, we
propose a novel meta-learning fine-tuning framework. Our framework makes
current PVLMs rapidly adaptive to new languages in vision-language scenarios by
designing MAML in a cross-lingual multi-modal manner. Experiments show that our
method boosts the performance of current state-of-the-art PVLMs in both
zero-shot and few-shot cross-lingual transfer on a range of vision-language
understanding tasks and datasets (XVNLI, xGQA, MaRVL, xFlicker&C
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