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Related papers: Transfer Functions for the DAMA Experiments

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Understanding the function of network motifs in an attempt to gain insight into how their combinations create larger reaction networks that drive cellular functions, has been a longstanding pursuit of systems biology. One specific objective…

Molecular Networks · Quantitative Biology 2025-09-24 Nguyen H. N. Tran , Federico Frascoli , Andrew H. A. Clayton

The physics of low subthreshold devices is interpreted in terms of a gate dependent change in their mode averaged transmission function, in addition to a capacitive shift in their overall mode spectrum. Accordingly, we explore a variety of…

Mesoscale and Nanoscale Physics · Physics 2015-10-06 Avik W. Ghosh

Systems switching between different dynamical phases is an ubiquitous phenomenon. The general understanding of such a process is limited. To this end, we present a general expression that captures fluctuations of a system exhibiting a…

Statistical Mechanics · Physics 2024-12-05 Ion Santra , Kristian Stølevik Olsen , Deepak Gupta

The electron transmission through a {\it closed} Aharonov-Bohm mesoscopic solid-state interferometer, with a quantum dot (QD) on one of the paths, is calculated exactly for a simple model. Although the conductance is an even function of the…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 Amnon Aharony , Ora Entin-Wohlman , Yoseph Imry

The electron transmission $T$ is evaluated through waveguides, in which the strength of the spin-orbit interaction(SOI) $\alpha$ is varied periodically, using the transfer-matrix technique. It is shown that $T$ exhibits a {\it…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 X. F. Wang , P. Vasilopoulos

We present parton distribution functions which include a quantitative estimate of its uncertainties. The parton distribution functions are optimized with respect to deep inelastic proton data, expressing the uncertainties as a density…

High Energy Physics - Phenomenology · Physics 2007-05-23 Walter T. Giele , Stephane A. Keller , David A. Kosower

This paper continues the preceding paper on the problem of quantum dynamics on the lattice. Firstly we consider the multiple reflections of the wave function (Loschmidt echo). The phenomenon of wave function concentration on the impurity…

Mesoscale and Nanoscale Physics · Physics 2013-02-13 V. N. Likhachev , T. Yu. Astakhova , G. A. Vinogradov

Distributed aggregation allows the derivation of a given global aggregate property from many individual local values in nodes of an interconnected network system. Simple aggregates such as minima/maxima, counts, sums and averages have been…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-04-09 Miguel Borges , Paulo Jesus , Carlos Baquero , Paulo Sérgio Almeida

Transfer learning from natural image datasets, particularly ImageNet, using standard large models and corresponding pretrained weights has become a de-facto method for deep learning applications to medical imaging. However, there are…

Computer Vision and Pattern Recognition · Computer Science 2019-10-31 Maithra Raghu , Chiyuan Zhang , Jon Kleinberg , Samy Bengio

Predictive design and optimization methods for controlled quantum systems depend on the accuracy of the system model. Any distortion of the input fields in an experimental platform alters the model accuracy and eventually disturbs the…

Quantum Physics · Physics 2023-06-29 Juhi Singh , Robert Zeier , Tommaso Calarco , Felix Motzoi

To ensure reliability, power transformers are monitored for partial discharge (PD) events, which are symptoms of transformer failure. Since failures can have catastrophic cascading consequences, it is critical to preempt them as early as…

Machine Learning · Computer Science 2022-10-25 Jonathan Wang , Kesheng Wu , Alex Sim , Seongwook Hwangbo

A characteristic feature of functional data is the presence of phase variability in addition to amplitude variability. Existing functional regression methods do not handle time variability in an explicit and efficient way. In this paper we…

Methodology · Statistics 2014-04-22 Daniel Gervini

Dark matter in the form of particles from a hidden mirror sector has recently been proposed as an explanation for the DAMA annual modulation signal. Here one assumes that there exists a small mixing between photons and mirror photons. We…

Astrophysics · Physics 2007-05-23 Saibal Mitra

We study the statistics of quantum transmission through a one-dimensional disordered system modelled by a sequence of independent scattering units. Each unit is characterized by its length and by its action, which is proportional to the…

Statistical Mechanics · Physics 2007-11-06 D. Boose , J. M. Luck

We analyze the communication efficiency of quantum information transfer along unmodulated spin chains by computing the communication rates of various protocols. The effects of temporal correlations are discussed, showing that they can be…

Quantum Physics · Physics 2011-11-09 Davide Rossini , Vittorio Giovannetti , Rosario Fazio

If dark matter is composed of new fundamental particles, Earth's orbital motion around the Sun may induce an annual modulation in the rate at which these particles interact in a terrestrial detector. The DAMA collaboration has identified at…

High Energy Physics - Phenomenology · Physics 2021-10-27 Douglas Q. Adams , Sunniva Jacobsen , Chris Kelso

The DAMA experiment clearly observes a small oscillatory signal. The observed yearly modulation is in phase with the Earth's motion around the Sun. Recent reference [Vavra, 2014] suggested that the DAMA experiment observes a WIMP of much…

Instrumentation and Methods for Astrophysics · Physics 2014-01-28 J. Va'vra

Fourier transform has become a basic tool for analyzing biological signals 1,2,3. Mostly a fast Fourier transform is computed for a finite sequence of data sample 4. This is the standard way apparatuses and modern computerized technology…

Quantitative Methods · Quantitative Biology 2008-04-01 Silvia Solis Ortiz , Rafael G. Campos , Julian Felix , Octavio Obregon

Control design for linear, time-invariant mechanical systems typically requires an accurate low-order approximation in the low frequency range. For example a series expansion of the transfer function around zero consisting of a mass,…

Optimization and Control · Mathematics 2024-05-02 Hans Zwart , Daniël W. M. Veldman , Sahar F. Sharifi

We consider the transfer learning problem in the high dimensional linear regression setting, where the feature dimension is larger than the sample size. To learn transferable information, which may vary across features or the source…

Machine Learning · Statistics 2024-11-26 Zelin He , Ying Sun , Jingyuan Liu , Runze Li