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Commit be3dc51f authored by Bas Nijholt's avatar Bas Nijholt
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add paragraph sentences

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## Core latex/pdflatex auxiliary files:
*.aux
*.lof
*.log
*.lot
*.fls
*.out
*.toc
*.fmt
*.fot
*.cb
*.cb2
.*.lb
## Intermediate documents:
*.dvi
*.xdv
*-converted-to.*
# these rules might exclude image files for figures etc.
# *.ps
# *.eps
# *.pdf
## Generated if empty string is given at "Please type another file name for output:"
.pdf
## Bibliography auxiliary files (bibtex/biblatex/biber):
*.bbl
*.bcf
*.blg
*-blx.aux
*-blx.bib
*.run.xml
## Build tool auxiliary files:
*.fdb_latexmk
*.synctex
*.synctex(busy)
*.synctex.gz
*.synctex.gz(busy)
*.pdfsync
## Auxiliary and intermediate files from other packages:
# algorithms
*.alg
*.loa
# achemso
acs-*.bib
# amsthm
*.thm
# beamer
*.nav
*.pre
*.snm
*.vrb
# changes
*.soc
# cprotect
*.cpt
# elsarticle (documentclass of Elsevier journals)
*.spl
# endnotes
*.ent
# fixme
*.lox
# feynmf/feynmp
*.mf
*.mp
*.t[1-9]
*.t[1-9][0-9]
*.tfm
#(r)(e)ledmac/(r)(e)ledpar
*.end
*.?end
*.[1-9]
*.[1-9][0-9]
*.[1-9][0-9][0-9]
*.[1-9]R
*.[1-9][0-9]R
*.[1-9][0-9][0-9]R
*.eledsec[1-9]
*.eledsec[1-9]R
*.eledsec[1-9][0-9]
*.eledsec[1-9][0-9]R
*.eledsec[1-9][0-9][0-9]
*.eledsec[1-9][0-9][0-9]R
# glossaries
*.acn
*.acr
*.glg
*.glo
*.gls
*.glsdefs
# gnuplottex
*-gnuplottex-*
# gregoriotex
*.gaux
*.gtex
# htlatex
*.4ct
*.4tc
*.idv
*.lg
*.trc
*.xref
# hyperref
*.brf
# knitr
*-concordance.tex
# TODO Comment the next line if you want to keep your tikz graphics files
*.tikz
*-tikzDictionary
# listings
*.lol
# makeidx
*.idx
*.ilg
*.ind
*.ist
# minitoc
*.maf
*.mlf
*.mlt
*.mtc[0-9]*
*.slf[0-9]*
*.slt[0-9]*
*.stc[0-9]*
# minted
_minted*
*.pyg
# morewrites
*.mw
# nomencl
*.nlg
*.nlo
*.nls
# pax
*.pax
# pdfpcnotes
*.pdfpc
# sagetex
*.sagetex.sage
*.sagetex.py
*.sagetex.scmd
# scrwfile
*.wrt
# sympy
*.sout
*.sympy
sympy-plots-for-*.tex/
# pdfcomment
*.upa
*.upb
# pythontex
*.pytxcode
pythontex-files-*/
# thmtools
*.loe
# TikZ & PGF
*.dpth
*.md5
*.auxlock
# todonotes
*.tdo
# easy-todo
*.lod
# xmpincl
*.xmpi
# xindy
*.xdy
# xypic precompiled matrices
*.xyc
# endfloat
*.ttt
*.fff
# Latexian
TSWLatexianTemp*
## Editors:
# WinEdt
*.bak
*.sav
# Texpad
.texpadtmp
# Kile
*.backup
# KBibTeX
*~[0-9]*
# auto folder when using emacs and auctex
./auto/*
*.el
# expex forward references with \gathertags
*-tags.tex
# standalone packages
*.sta
# generated if using elsarticle.cls
*.spl
paper.pdf: paper.tex
pdflatex paper.tex
bibtex paper
pdflatex paper.tex
paper.tex:
pandoc -s --filter pandoc-fignos --filter pandoc-citeproc --filter pandoc-crossref --natbib paper.md -o paper.tex --bibliography paper.bib --template revtex.template
name: revtex-markdown-paper
channels:
- conda-forge
dependencies:
- python
- pandoc
- pandoc-crossref
- pip:
- pandoc-fignos
@article{nijholt2016orbital,
title={Orbital effect of magnetic field on the Majorana phase diagram},
author={Nijholt, Bas and Akhmerov, Anton R},
journal={Physical Review B},
volume={93},
number={23},
pages={235434},
year={2016},
publisher={APS}
}
paper.md 0 → 100755
---
title: 'Adaptive, tools for adaptive parallel sampling of mathematical functions'
journal: 'PeerJ'
author:
- name: Tinkerer
affiliation:
- Kavli Institute of Nanoscience, Delft University of Technology, P.O. Box 4056, 2600 GA Delft, The Netherlands
email: not_anton@antonakhmerov.org
abstract: |
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
bibliography: references.bib
acknowledgements: |
We'd like to thank ...
contribution: |
Bla
...
# Introduction
#### Simulations are costly and often require sampling a region in parameter space
#### Chosing new points based on existing data improves the simulation efficiency
<!-- examples here -->
#### We describe a class of algorithms replying on local criteria for sampling which allow for easy parallelization and have a low overhead
<!-- This is useful for intermediary cost simulations. -->
#### We provide a reference implementation, the Adaptive package, and demonstrate its performance
# Review of adaptive sampling
#### Experiment design uses Bayesian sampling because the computational costs are not a limitation
<!-- high dimensional functions -->
#### Plotting and low dimensional integration uses local sampling
<!-- can refer to Mathematica's implementation -->
#### PDE solvers and computer graphics use adaptive meshing
<!-- hydrodynamics anisotropic meshing paper ref -->
# Design constraints and the general algorithm
#### We aim to sample low dimensional low to intermediate cost functions in parallel
<!-- because of curse of dimensionality -->
<!-- fast functions don't require adaptive -->
<!-- When your function evaluation is very expensive, full-scale Bayesian sampling will perform better, however, there is a broad class of simulations that are in the right regime for Adaptive to be beneficial. -->
#### We propose to use a local loss function as a criterion for chosing the next point
#### As an example interpoint distance is a good loss function in one dimension
<!-- Plot here -->
#### In general local loss functions only have a logarithmic overhead
#### With many points, due to the loss being local, parallel sampling incurs no additional cost
# Loss function design
#### A failure mode of such algorithms is sampling only a small neighborhood of one point
<!-- example of distance loss on singularities -->
#### A solution is to regularize the loss such that this would avoided
<!-- like resolution loss which limits the size of an interval -->
#### Adding loss functions allows for balancing between multiple priorities
<!-- i.e. area + line simplification -->
#### A desireble property is that eventually all points should be sampled
<!-- exploration vs. explotation -->
# Examples
## Line simplification loss
#### The line simplification loss is based on an inverse Visvalingam’s algorithm
<!-- https://bost.ocks.org/mike/simplify/ -->
## A parallelizable adaptive integration algorithm based on cquad
#### The `cquad` algorithm belongs to a class that is parallelizable
## isosurface sampling
# Implementation and benchmarks
<!-- API description -->
#### The learner abstracts a loss based priority queue
#### The runner orchestrates the function evaluation
# Possible extensions
#### Anisotropic triangulation would improve the algorithm
#### Learning stochastic functions is promising direction
#### Experimental control needs to deal with noise, hysteresis, and the cost for changing parameters
<!-- We can include things like:
* Asymptotically complexity of algorithms
* Setting of the problem, which classes of problems can be handled with Adaptive
* Loss-functions examples (maybe include [Adaptive quantum dots](https://chat.quantumtinkerer.tudelft.nl/chat/channels/adaptive-quantum-dots))
* Trials, statistics (such as measuring timings)
* Line simplification algorithm as a general criterium
* Desirable properties of loss-functions
* List potential applications
-->
\ No newline at end of file
\documentclass[english, twocolumn, 10pt, aps, superscriptaddress, floatfix, prb, citeautoscript]{revtex4-1}
\pdfoutput=1
\usepackage[utf8]{inputenc}
\usepackage[T1]{fontenc}
\usepackage{verbatim}
\usepackage{units}
\usepackage{mathtools}
\usepackage{amsmath}
\usepackage{amssymb}
\usepackage{graphicx}
\usepackage{wasysym}
\usepackage{layouts}
\usepackage{siunitx}
\usepackage{bm}
\usepackage{xcolor}
\usepackage[colorlinks, citecolor={blue!50!black}, urlcolor={blue!50!black}, linkcolor={red!50!black}]{hyperref}
\usepackage{bookmark}
\usepackage{tabularx}
\usepackage{microtype}
\usepackage{babel}
\hypersetup{pdfauthor={$for(author)$$author.name$$sep$, $endfor$},pdftitle={$if(title)$$title$$endif$}}
\setcounter{secnumdepth}{4}
\setcounter{tocdepth}{4}
\DeclareMathOperator{\e}{e}
\DeclareMathOperator{\de}{d\!}
\DeclareMathOperator{\Tr}{Tr}
\DeclareMathOperator{\diag}{diag}
\DeclareMathOperator{\Res}{Res}
\DeclareMathOperator{\sgn}{sgn}
\DeclareMathOperator{\Pf}{Pf}
\DeclareMathOperator{\Det}{Det}
\DeclareMathOperator{\rank}{rank}
\DeclareMathOperator{\im}{Im}
\DeclareMathOperator{\re}{Re}
\newcommand{\kx}{k_x}
\newcommand{\ky}{k_y}
\newcommand{\meff}{m_\text{eff}}
\newcounter{CommentNumber}
% \renewcommand{\paragraph}[1]{\stepcounter{CommentNumber}\belowpdfbookmark{#1}{\arabic{CommentNumber}}}
\DeclarePairedDelimiter\abs{\lvert}{\rvert}
\DeclarePairedDelimiter\norm{\lVert}{\rVert}
\makeatletter
\let\oldabs\abs
\def\abs{\@ifstar{\oldabs}{\oldabs*}}
\let\oldnorm\norm
\def\norm{\@ifstar{\oldnorm}{\oldnorm*}}
\makeatother
\newcommand{\ev}[1]{\langle#1\rangle}
\newcommand{\bra}[1]{\langle#1|}
\newcommand{\ket}[1]{|#1\rangle}
\newcommand{\bracket}[2]{\langle#1|#2\rangle}
\newcolumntype{L}[1]{>{\raggedright\arraybackslash}p{#1}}
\newcolumntype{C}[1]{>{\centering\arraybackslash}p{#1}}
\newcolumntype{R}[1]{>{\raggedleft\arraybackslash}p{#1}}
% workaround for https://github.com/jgm/pandoc/issues/2392#issuecomment-140114736
\renewcommand{\citep}{\cite}
\begin{document}
\title{$if(title)$$title$$endif$}
$for(author)$
$if(author.name)$
\author{$author.name$}
\email[Electronic address: ]{$author.email$}
$for(author.affiliation)$
\affiliation{$author.affiliation$}
$endfor$
$endif$
$endfor$
\date{\today}
$if(abstract)$
\begin{abstract}
$abstract$
\end{abstract}
$endif$
\flushbottom
\maketitle
$body$
$if(acknowledgements)$
\section*{Acknowledgements}
$acknowledgements$
$endif$
$if(contribution)$
\section*{Author contributions statement}
$contribution$
$endif$
$if(additionalinformation)$
\section*{Additional information}
$additionalinformation$
$additionalinformation$
$endif$
\bibliographystyle{apsrev4-1}
\bibliography{$bibliography$}
\end{document}
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