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FPGA Lab 1 and 2

These labs covered the basics of implementing digital circuitry using a field-programmable gate array (FPGA). We reviewed how one builds the program in Quartus and compiles it onto the FPGA. We also reviewed how one can constructs complex circuits very easily in Quartus and show the result using a 7-segment display. This lab was very helpful in providing the necessary building blocks for future projects involving FPGAs as it showed how one can encode the necessary logic to execute a desired task.

Planes toy models

The standard picture of the evolution of substructure in the Universe involves the collapse of dark matter into halos, which may host luminous galaxy. Such halos may exist within the bounds of larger halos; in these cases the galaxies they may host are typically called satellite galaxies, and their evolution differs substantially from galaxies that are not satellites in ways not fully understood. Analysis of the spatial and kinematic distributions of such galaxies can inform our ideas of how satellites and the systems in which they are found evolve. Substantial evidence exists that satellite galaxies are not isotropically distributed around their hosts. \cite{West2000,Bailin_2008}. This is also seen in simulations; subhaloes of hosts typically are typically distributed anisotropiclly in both position and velocity space \cite{VDB99,Knebe,Zentner_2005,Faltenbacher_2010}.

Local group satellites are highly anisotropically distributed both around the Milky Way and M31. The disk-like arrangement of MW satellites was first pointed out by \citet{Lynden-Bell74}. Later studies argued further for the existence of a disk-like structure of Milky Way satellites \cite{Metz07,Metz09}, and argued that the MW satellite disk was rotationally supported \cite{Metz08}. \citet{Kroupa_2005} further argues that the distribution of satellite galaxies around the MW is not predicted by LCDM. Around M31, dramatic evidence has been found for a disk of satellites, many of which exhibit coherent rotation along the line of sight \cite{Ibata_2013}. The M31 structure seems particularly difficult to square with our picture of galaxy evolution; \cite{Ibata_2014} argues that \cite{Ibata_2014} that alignments similar to the one found around M31 are essentially non-existant in numerical simulations.

Much recent work has gone into investigating the possibility of similar satellite distributions around galaxies outside of the local group. Recently, work by \citet{Ibata_2014} (hereafter I14) pointed to the possibility of corotation seen in diametrically opposed satellite pairs in Sloan Digital Sky Survey (SDSS), finding 20 out of 22 oppositely aligned satellite pairs corotating along the line of sight. This result was contested by \citet{Cautun14}, arguing that the results of \citet{Ibata_2014} are strongly dependant on selection criteria and are not robust. The original authors then claimed that less-massive satellites than originally considered exhibit a spacial over-density consistent with the claimed existence of co-rotating sturctures frequently seen in SDSS \cite{2014arXiv1411.3718I}. Still, the consensus on the prevelence of co-rotating satellite disks in the non-local Universe is unclear.

In this paper we examine kinematic evidence for the existence of rotating planes. We compare the kinematic results we obtain from selection criteria modelled after that of I14 to simple numerical models of satellite behavior. The structure of the paper is as follows: In Section [sec:data] we discuss the selection of the observational sample and the presense of the co-rotation signal. In Section [sec:models] we introduce our numerical models and compare the mock observations derived from the models to the true observational data. In Section [sec:discuss] we discuss our results in the context of the search for M31-like planes elsewhere in the Universe. Throughout our analysis, we employ a *Λ* cold dark matter (*Λ*CDM) cosmology with WMAP7+BAO+H0 parameters *Ω*_{Λ} = 0.73, *Ω*_{m} = 0.27, and *h* = 0.70 \cite{Komatsu_2011}, and unless otherwise noted all logarithms are base 10.

Properties of Thiotimoline

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Inverse and Exchange Matrix, Quantum Mechanics, Slater Determinants

For a 3x3 non-singular matrix *A* with a determinant |*A*| defined by \begin{equation}
A=\begin{bmatrix}
a_{11} & a_{12} & a_{13} \\ a_{21} & a_{22} & a_{23} \\ a_{31} & a_{32} & a_{33}
\end{bmatrix}
\end{equation} we can calculate the inverse as \begin{equation}
A^{-1}=\frac{1}{|A|}
\begin{bmatrix}
\begin{vmatrix} a_{22} & a_{23} \\ a_{32} & a_{33}\end{vmatrix} &
\begin{vmatrix} a_{13} & a_{12} \\ a_{33} & a_{32}\end{vmatrix} &
\begin{vmatrix} a_{12} & a_{13} \\ a_{22} & a_{23}\end{vmatrix} \\
\begin{vmatrix} a_{23} & a_{21} \\ a_{33} & a_{31}\end{vmatrix} &
\begin{vmatrix} a_{11} & a_{13} \\ a_{31} & a_{33}\end{vmatrix} &
\begin{vmatrix} a_{13} & a_{11} \\ a_{23} & a_{21}\end{vmatrix} \\
\begin{vmatrix} a_{21} & a_{22} \\ a_{31} & a_{32}\end{vmatrix} &
\begin{vmatrix} a_{12} & a_{11} \\ a_{32} & a_{31}\end{vmatrix} &
\begin{vmatrix} a_{11} & a_{12} \\ a_{21} & a_{22}\end{vmatrix}
\end{bmatrix}
\end{equation}

If we define an operation that is *R**C**R*_{ij}(*A*):=*R*_{ij}, remove the *i*^{th} column and the *j*^{th} row of *A*, then this is expressible as \begin{equation}
A^{-1}=\begin{bmatrix}
|R_{11}| & |R_{12}J| & |R_{13}| \\ |R_{21}J| & |R_{22}| & |R_{23}J| \\ |R_{31}| & |R_{32}J| & |R_{33}|
\end{bmatrix}
\end{equation}

Where \begin{equation} J=\begin{bmatrix} 0 & 1 \\ 1 & 0 \end{bmatrix} \end{equation}

Clearly the condition for a right multiplication of the *J* matrix being *i* + *j* = *o**d**d*.

Alternatively \begin{equation} |A|(A^{-1})_{ij}=|R_{ij}J^{(i+j-1)}|=|J^{(i+j-1)R_{ij}}| \end{equation}

This likely works because for any 2x2 matrix |*A*|= − |*A**J*_{2}|= − |*J*_{2}*A*|=|*J*_{2}*A**J*_{2}|. This property |*A*|= − |*A**J*_{2}| also appears to hold for a 3x3 matrix.

Extrapolating backwards for a two by two matrix we get the correct formula on the proviso we define *J*_{1} ≡ −1. This makes some sense, as for any *J*_{n}*J*_{n} = *I* and *J*_{n}*J*_{n}*A* = *A*.

We can further extrapolate to the inverse of a 1x1 matrix *A* = *A*_{11}, taking the *R*_{11} element to be the zero matrix, the determinant of this matrix is 1 and the reciprocal of the determinant of *A* is then just the reciprocal of *A*_{11}, which again is the inverse of the 1x1 matrix.

Proof *J*_{1} = −1:

For any *J*_{n}, *n* > 1, |*J*_{n}|= − 1 as *J*_{n} is defined to be an antidiagonal matrix.

|*A**B*|=|*A*||*B*|.

Therefore |*A**J*_{n}|= − |*A*|.

If one extrapolates to the case *n* = 1, For the above to remain true, *J*_{1} = −1

Looking at the same formula we can define four 3x3 matrices, top left, top right, bottom left, bottom right \begin{equation} A^{TL}=\begin{bmatrix} a_{22} & a_{13} & a_{12} \\ a_{23} & a_{11} & a_{13} \\ a_{21} & a_{12} & a_{11} \end{bmatrix} \\ A^{TR}=\begin{bmatrix} a_{23} & a_{12} & a_{13} \\ a_{21} & a_{13} & a_{11} \\ a_{22} & a_{11} & a_{12} \end{bmatrix} \\ A^{BL}=\begin{bmatrix} a_{32} & a_{33} & a_{22} \\ a_{33} & a_{31} & a_{23} \\ a_{31} & a_{32} & a_{21} \end{bmatrix} \\ A^{BR}=\begin{bmatrix} a_{33} & a_{32} & a_{23} \\ a_{31} & a_{33} & a_{21} \\ a_{32} & a_{31} & a_{22} \end{bmatrix} \end{equation}

These matrices are constructed from the rows of the original matrix as such, if R_i is the ith row of the original matrix, and P_n is an operator which cycles that row forward n times we have \begin{equation} A^{TL}=\begin{bmatrix} R_2^TP_2 & R_1^TP_1 & R_1^TP_2 \end{bmatrix} =A^{r(211)}_{p(212)}\\ A^{TR}=\begin{bmatrix} R_2^TP_1 & R_1^TP_2 & R_1^TP_1 \end{bmatrix} =A^{r(211)}_{p(121)}\\ A^{BL}=\begin{bmatrix} R_3^TP_2 & R_3^TP_1 & R_2^TP_2 \end{bmatrix} =A^{r(332)}_{p(212)}\\ A^{BR}=\begin{bmatrix} R_3^TP_1 & R_3^TP_2 & R_2^TP_1 \end{bmatrix} =A^{r(332)}_{p(121)} \end{equation}

These matricies are then such that \begin{equation} \frac{1}{|A|}(A^{TL} \circ A^{BR} - A^{TR} \circ A^{BL}) = A^{-1} \end{equation}

Where ∘ is the Hadamard product or element-wise product.

APPLYING MEMORY FORENSICS TO ROOTKIT DETECTION

and 1 collaborator

Igor Korkin **1** , Ivan Nesterov **2**

**1** National Research Nuclear University Moscow Engineering & Physics Institute (NRNU MEPhI), Moscow, 115409, Russia

**2** Moscow Institute of Physics and Technology (MIPT), Moscow Region 141700, Russia

# Corresponding author: igor.korkin@gmail.com

PDF-version and slides - https://www.academia.edu/7380266/Applying_Memory_Forensics_to_Rootkit_Detection

Measurements of Index of Refraction of the Whistler Wave Using Appleton's Equation

and 2 collaborators

Radio emission from the ionosphere can produce a whistling sound in the audio frequency that can be heard[1]. The whistling sounds are described as groups of descending tones which are called the whistler mode. When lightning hits the southern hemisphere it produces a range of radio waves, some of which can travel along the earths magnetic field lines from the southern hemisphere to the northern hemisphere[1].These waves are called extraordinary waves .The extraordinary waves emit two solutions to the wave equation named L and R waves.The L and R refer to left and right hand circularly polarized. The waves that describe the whistling sound are R waves and they will be detected in the north and the different frequencies of these waves will travel at different speeds. For $\omega<\frac{\omega_{ce}}{2}$ the phase and group velocities increase with frequency, where $\omega_{ce}=\frac{eB}{m}$ is the electron cyclotron frequency[1]. Due to this, the lower frequencies will arrive at the northern hemisphere later than the higher frequencies will, causing the descending tone in the whistler mode. These R waves waves that travel along the magnetic field lines are called whistler waves and these waves can only propagate for $\omega<\frac{\omega_ce}{2}$. This lab seeks out to measure the dispersion relation of the whistler waves and to find the wave patterns theoretically and experimentally in the inductively coupled plasma device using Appletons equation.

Mode Test By GMM and Excess Mass Methods

and 2 collaborators

\label{sec:methods}

\label{sec:methods-gmm}

GMM (Gaussian mixture modeling) method maximizes the likelihood of the data set using EM (expectation-maximization) method.

1. Assume that data has unimodal distribution: **x** ∼ *N*(*μ*, *σ*^{2}). Calculate *μ* and *σ*^{2}

2. Assume that data has bimodal distribution: **x** ∼ *N*(*μ*_{1}, *μ*_{2}, *σ*_{1}^{2}, *σ*_{2}^{2}, *p*)

Initial guess: *μ*_{1} = *μ* − *σ*, *μ*_{2} = *μ* + *σ*, *σ*_{1}^{2} = *σ*_{2}^{2} = *σ*^{2}, *p* = 0.5

*n*= number of observations

*θ* = (*μ*_{1}, *μ*_{2}, *σ*_{1}, *σ*_{2}, *p*) **z** = (*z*_{1}, ..., *z*_{n}) categorical vector, *z*_{i} = 1, 2

**x** = (*x*_{1}, ..., *x*_{n}) observations, (*x*_{i}|*z*_{i} = 1)∼*N*(*μ*_{1}, *σ*_{1}^{2}), (*x*_{i}|*z*_{i} = 2)∼*N*(*μ*_{2}, *σ*_{2}^{2})

*E-step* *P*(*z*_{1})=*p*, *P*(*z*_{2})=1 − *p*

Marginal likelihood: *L*(**θ**; **x**; **z**)=*P*(**x**, **z**|**θ**)=$\prod\limits_{i=1}^n P(Z_i=z_i)f(x_i|\mu_{j}, \sigma^2_{j})$

*Q*(**θ**|**θ**^{(t)})=*E*_{z|x, θ(t)}(log*L*(**θ**; **x**; **z**))

$T^{(t)}_{j,i}=P(Z_i=j|X_i=x_i,\theta^{(t)})=\frac{P(z_{j})f(x_i|\mu^{(t)}_{j}, \sigma^{2(t)}_{j})}{p^{(t)} f(x_i|\mu^{(t)}_{1}, \sigma^{2(t)}_{1})+(1-p^{(t)})f(x_i|\mu^{(t)}_{2}, \sigma^{2(t)}_{2})}$

$Q(\mathbf{\theta}|\mathbf{\theta^{(t)}})=E_{\textbf{z}|\textbf{x},\mathbf{\theta^{(t)}}}(\log L(\mathbf{\theta};\textbf{x};\textbf{z})) = \sum\limits_{i=1}^n E[( \log L(\mathbf{\theta};x_{i};z_{i})] =$

$= \sum\limits_{i=1}^n \sum\limits_{j=1}^2 T^{(t)}_{j,i}[\log P(z_{j}) -\frac{1}{2}\log(2\pi) - \frac{1}{2}\log\sigma^{2}_{j} - \frac{(x_{i}-\mu_{j})^2}{2\sigma^{2}_{j}}]$

*M-step* *θ*^{(t + 1)} = argmax*Q*(*θ*|*θ*^{(t)})

$\hat{p}^{(t+1)} = \frac{1}{n} \sum\limits_{i=1}^n T^{(t)}_{1,i}$, $\mu^{(t+1)}_{1} = \frac{\sum\limits_{i=1}^n T^{(t)}_{1,i}x_i}{\sum\limits_{i=1}^n T^{(t)}_{1,i}}$, $\sigma^{2(t+1)}_{1} = \frac{\sum\limits_{i=1}^n T^{(t)}_{1,i}(x_i-\mu^{(t+1)}_{1})^2}{\sum\limits_{i=1}^n T^{(t)}_{1,i}}$

Continue iterations t until |log*L*^{(t + 1)} − log*L*^{(t)}|<10^{−3}

Conclusion about data is made based on 3 tests. *H*_{0} distribution is unimodal, *H*_{1} distribution is bimodal:

1. LRT (Likelihood ratio test) −2ln*λ* = 2[ln*L*_{bimodal} − ln*L*_{unimodal}]∼*χ*^{2} (LRT is the main test among all 3 tests for making conclusion about bimodality of data. The bigger −2ln*λ* is, the more we are convinced that distribution is bimodal).

2. (Bandwidth test) $D = \frac {|\mu_1 - \mu_2|}{(\sigma^2_1+\sigma^2_2)/2)^{0.5}}$ (*D*(*d**i**s**t**a**n**c**e*)>2 is necessary for a clear separation of 2 peaks).

3. (Kurtosis test) *k**u**r**t**o**s**i**s* < 0 should be negative for a bimodal distribution.

In some hard cases *D* and *k**u**r**t**o**s**i**s* fail to detect bimodality. That is why our main test is LRT. For example on the next 2 plots distributions are bimodal, however on 1 plot D<2 (it is hard to distinguish 2 peaks) and on the 2 plot kurtosis is positive and that corresponds to unimodal distribution (it happens because distribution is biased):

Molecular dynamics simulation of single crystal copper with silver impurities.

and 1 collaborator

Through molecular dynamics simulations we have investigated the behavior of a single crystal copper dopped with silver impurities (0.1, 0.2 and 0.4 at % Ag) ranged at different temperatures (0.1, 100 and 300 K) under the action the stress tensor . The stress tensor is applied along of the surface in the crystallographic plane(100). Silver atoms are placed randomly on the copper, by replacing. The simulation shows thermodynamic stability properties and altering the sample fractures the crystal structure of this .

The Internet as a (WorldWide) Telescope

What famous observatory has no lens and no mirror? Such research institutions weren't uncommon in centuries past - Claudius Ptolemy constructed such an observatory at Alexandria in the 2nd century, and in the 16th century, Tycho Brahe built Uraniborg ("the castle of Urania") and Stjerneborg ("star castle") to study the night sky. Now the modern age has its own version: the internet.

The wealth of astronomical data available online grows every day, collected from spacecraft such as Hubble, Spitzer, and Chandra, as well as smaller, groundbased observatories around the globe. And there's a portal through which anyone can access these data to view the universe in its multiwavelength glory: the WorldWide Telescope (WWT).

This software runs on almost any computer or tablet via its web browser. You can also download an application to your Windows desktop. The WorldWide Telescope accesses the internet's amazing treasure-trove to provide beautiful all-sky imagery at dozens of wavelengths, as well as detailed images of many celestial targets. In addition, it offers links to in-depth information about individual objects, using diverse databases ranging from Wikipedia to NASA's Astrophysics Data System, which holds all astronomical literature published since the 1800s. WWT basically functions as an interactive web browser for the sky, a sky browser of sorts. Oh, and it's free.

Proposal to join LSST at LUPM

and 4 collaborators

The Large Synoptic Survey Telescope (LSST) is a wide-field, ground-based telescope, designed to image a substantial fraction of the sky in six optical bands every few nights. It is planned to operate for a decade, starting in 2021, allowing the stacked images to detect galaxies to redshifts well beyond unity. The LSST is designed to achieve a very broad science roadmap, that can be articulated around four major science themes:

Probing Dark Energy and Dark Matter;

Taking an inventory of the Solar system;

Exploring the transient optical sky;

Mapping the Milky Way.

This document outlines the current work plan that the LSST team at LUPM is putting forward to officially join the LSST project and efficiently start their scientific and technical activities. It is intended to serve as a support to the Scientific Council of LUPM, in preparation to the review on October 1-2 2014. In the first part of the document, we summarize the LSST project, the Dark Energy Science Collaboration (DESC), and the LSST-France activities. The second part shortly introduces the LUPM team, and we devote the third section to a presentation of the LSST project and activities at LUPM.

N-Body Simulation of a Proto-Solar System with a Neptune-like Object

#Introduction

The widely-accepted explanation for the initial formation of the Solar System is known as the Nebular Hypothesis, that the Sun formed from a collapsing, dense region of an interstellar molecular cloud, with the remainder of material gravitationally accreting and flattening into an orbiting circular disk. This excess material eventually coalesced to form the small solar system bodies, including planets, moons, asteroids, and comets. After their initial formation, however, the orbital parameters of small bodies were not static. Due to complex gravitational interactions and interchanges of orbital energy between particles, planets, remaining small-bodies, and particles experienced 'migration' – periods during which their orbital parameters evolved substantially, particularly in their orbital radii (Semi-Major Axis). Migration is believed to account for the current configuration of planets in the solar system, including the gas giants. Additionally, it offers a likely explanation for the small orbital radii and, consequently, short orbital periods of “Hot Jupiter” planets which have been detected in extrasolar planetary systems, as it suggests that their orbits may have undergone an inward migration and eventual stabilization. Evidence suggests that migration could account for the current orbit of Neptune, since the orbit periods of a number of small solar system bodies appear to be in resonance, which must be the result of gravitational interactions with Neptune.

A numerical simulation of a gas-less, solar-like proto-planetary disk was performed by Rodney S Gomes et. al. (Planetary Migration in a Planetesimal Disk: Why Did Neptune Stop at 30 AU? - 2004) to investigate Neptune's migration. The result was an outward migration of Neptune, which stabilized at a semi-major axis of approximately 30 AU from the central star, remarkably close to it's actual semi-major axis of 29.21 AU. Migration was found to be sensitive to the mass density of the proto-planetary disk. Outlying material, representing an initially close-in 'Kuiper Belt', quickly dispersed and lost a significant portion of its mass before Neptune stabilized into its final orbit, thus placing Neptune, effectively, on the edge of the disk after it ceased migrating. This result was obtained by setting the initial radius of the disk to ~35 AU, with a linear mass density of ~1.5 Earth masses per AU. When the mass density of the disk was increased (relatively massive disk), Neptune showed a runaway migration out to very large distances, due to interaction with particles that continually “fed” its migration. In a previous simulation of 10,000 particles, with a disk which encompassed 60 Earth masses of material between 20 and 45 AU, and and r^-(1.5) surface density profile, Gomes (2003) observed an outward migration of Neptune and stabilization at 45 AU.

MagPen: A Novel Method of Digitizing Notes Using Magnets

and 1 collaborator

This paper presents a novel method of digitizing notes and/or diagrams that are drawn on a sheet of paper. Most modern phones contain magnetometers that output the strength of the surrounding magnetic field in the x, y, and z direction. If a magnet is brought closer to the device (and the magnetometer), the values from the magnetometer will be altered. By determining the change in the altered magnetic field, we can determine the position of the magnet. With the position, we can determine the location of the magnet relative to the phone. We have created a magnet based pen (MagPen) and built an android application that allows users to write notes on a sheet of paper while their mobile phone automatically digitizes. Users will also be able to perform certain actions using the button on the pen and select various pen attributes using the MagPen.

**Author Keywords**

Pen input, magnetometer, mobile devices, notes

**ACM Classification Keywords**

H.5.2 [Information interfaces and presentation]: User

Interfaces: Input Devices and Strategies.

Master thesis research proposal: How do daily household practices affect food wastage? Empirical insights from 100 Dutch households in the context of the 100 100 100 campaign

Name: Robert Orzanna

Title: How do daily household practices affect food wastage? Empirical insights from 100 Dutch households in the context of the 100 100 100 campaign

Contact: r.orzanna@students.uu.nl

Supervisor: Prof. dr. Ernst Worrell

2^nd reader: dr. ir. Wina Crijns-Graus

Exo II: Modelling Phase Curves of Hot Jupiter Planets and Implications for Habitable Planets

and 1 collaborator

For centuries, humans have wondered if there is intelligent life elsewhere in the universe. With the advent of telescopes capable of detecting planets around other stars, exoplanets, we would like to determine if these planets are capable of harboring life. In our solar system, spacecrafts and landers have been sent to our terrestrial neighbors to look for life. Sample return missions, though costly in both time and money, are one sure fire way to discover if a material ever has, ever could, or contains any familiar life. Barring that, in situ measurement from landers are next best. For exoplanets, these methods are impossible. Therefore, we use remote sensing techniques. What light should we look for to detect life?

Life, as we know it, requires certain surface and atmospheric conditions. We require oxygen to breathe, ozone to protect us from harmful rays, and liquid water on the surface to serve as a catalyst for biochemical reactions. These signatures of life can be detected in the spectrum of a planetary atmosphere. To understand how biology can affect the atmosphere it is critical to understand atmospheres in habitable and non-habitable situations. Ideally a spectrum would reveal features related to water and ozone. Direct imaging of a planet would be ideal. Both of these techniques rely on the planet being bright enough and distant enough from its star to resolve them separately. The systems for which these techniques have been applied are few in number. Conversely, there are a number of photometric surveys searching for and characterizing exoplanets.

Kepler’s high-precision light curves have provided a cornucopia of information buried within the noise of other surveys. Not only are they able to provide a measure of stellar limb darkening, the period of the planet, the size of the planet, and the orbital semi-major axis, but these light curves may also provide information about the temperature, albedo, and even mass of the planet.

In our project, we will demonstrate what can be learned from the albedo and temperature for several well-known exoplanets. We will introduce the components of light curves and their relationship to the geometry of the system. We later discuss the atmospheric implications for these planets, and finally what a potentially habitable terrestrial planet would look like.

Introduction to Complexity Science: On my desire to deepen my understanding of the complexity of sustainability lifestyles

Every day I see myself confronted with the same challenging question: “ hinders people to live more sustainably and what can be my contribution to help overcoming the barriers to let them adopt more sustainable lifestyles?" As a current Master student of *Sustainable Development: Energy & Resources* at Utrecht University I am excited and passionate to accept this challenge. I am currently devoting my master thesis on food wastage in Dutch households, presenting a complex interaction with environmental implications and behavioural aspects for stimulating change. Beginning of November 2014, I attended a summer school in Barcelona dedicated to sustainable lifestyles transitions. Similar to complexity being used as a buzzword, so is sustainability. Its concept is all-inclusive and its boundaries when used in different contexts frequently unclear. To me, complexity manifests as the challenge of sustainable development for the required widespread adoption of mindful human activities. While it was frequently stated that unsustainabilities can be overcome by technical innovation and thus the dominant contribution of natural sciences and engineering, the focus has more and more shifted to acknowledging the importance of individual human lifestyles transitions.

In memory of a remarkable course on *Sustainable Development: Integrating Perspectives* by Bert de Vries, henceforth I believe that sustaining solutions can only be found with inclusive systems thinking, trans- and inter-disciplinary in nature.

Aside this background, I am very excited to work together with inspiring colleagues from particularly Eastern cultures in which holistic systems thinking has found its roots already several millennia ago. In conclusion, I would like to receive the opportunity of joining an inter-disciplinary team, working together to find inspirations for my prospective work as a PhD student on behavioural changes and sustainability lifestyles in response to demanding questions such as the following:

How to adapt systems to stimulate adaptive changes from an individual perspective?

How can models and simulation tools be designed to study sustainability lifestyle behaviour of people in complex systems?

How can evolutionary algorithms contribute to a better understanding of how sustainable lifestyle practices replicate over time?

PhD Orientation Proposal: Exploring Sustainable Lifestyles

In this orientation proposal I want to outline my interests and motivations for a PhD in the research area of sustainable lifestyles. I will be reviewing the research foci of three different research institutes: (1) The Collaborative Centre for Sustainable Consumption and Production, (2) the Future Food interdisciplinary research initiative at Utrecht University, and (3) the Strategic Communication Group at Wageningen University. I will contextualise their research activities with my own interests to provide research questions for prospective investigation.

Results from Fake Single Component Galaxies Tests

and 2 collaborators

The fake galaxy models are generated by the **Sersic** function in GalSim package based on parameters from an input catalog. The procedures can be summarized into following steps:

- Input magnitude is converted into flux using calibrations extracted from HSC pipeline; and the input effective radius is converted into pixel unit (reff_pix).
- Using input flux and reff_pix, a GalSim.Sersic object is generated with its flux truncated at 10 times of the reff_pix. Even when the Sersic index is high, the output image still is a reasonable size without losing much flux at outer radii.
- Using input axis ratio (b/a), simple q=b/a shear has been applied to the Sersic object to turn it into an elliptical model. Since GalSim perserve the total area, the real major-axis half-light radii of the output model becomes reff_pix / sqrt(b/a).
- Using input position angle (PA), the elliptical Sersic object is rotated.
- PSF convolution is applied to the model using the PSF image extracted from HSC data products at the desired location.
- An output image of the models is generated using the GalSim drawImage function.

We have tested these GalSim models by applying Galfit to the images generated in exactly the same way. The results prove that our models are reliable.

To make sure that the fake galaxies we inject on the images are as realistic as possible, we choose to use the models of COSMOS galaxies from \cite{Mandelbaum_2014}. The catalog is based on Exponential (Exp), De Vaucouleurs (Dev), and single Sersic component (Sersic) fitting of galaxies with \(I_{F814W} \le 23.5\ mag\) on the ACS high-resolution (0.03''/pix) images.

From the full COSMOS catalog, we select appropriate Exp, Dev, and Sersic models according to the following standards:

- Exp models: \(mag \le 23.0\), \(b/a \ge 0.4\), \(2.0 \le R_e \le 20.0\), and \(MADEXP\_DEV > 1.0\); This gives 9630 models in the catalog.
- Dev models: \(mag \le 23.0\), \(b/a \ge 0.5\), \(2.0 \le R_e \le 20.0\), and \(MADEXP\_DEV \le 1.0\); This gives 6390 models in the catalog.
- Sersic models: \(mag \le 23.0\), \(b/a \ge 0.4\), \(3.0 \le R_e \le 20.0\), and \(0.8 \le n_{Sersic} \le 4.0\); This gives 7523 models in the catalog.

The MADEXP_DEV is the ratio of MAD (Median absolute deviation) of the Exp and Dev models. MADEXP_DEV smaller than 1.0 indicates that the galaxy is more Exp-like; larger than 1.0 means it is more Dev-like. The cut at low axis ratio and low Sersic index is simply because GalSim sometimes fails to generate such model due to the maximum iterations allowed.

At this point, we only work on single frame images. A group of 22 "clean" images are selected from the visit=1236 COSMOS-UDEEP i-band data for this test. These images are from CCDs that are close to the center of the camera. And, we visually check the images to ensure that the contamination from bright saturated stars is at minimum.

For each run, 50 models are randomly selected from the input catalog, and are injected into these 22 images at random pixel positions. The galaxies and pixel positions are the same for each CCD. The calibration parameters and PSF models are extracted at the exact X-Y locations, and are passed to the funcation that generates the fake galaxy image. Appropriate noise is also added to the models before we put them on the images. We make sure the random image coordinates are not too close to the edge, but do not put special effort into avoiding real objects on the images. The X-Y coordinates of these fake galaxies, along with their ID, are recorded in the header of the images.

After that, the fake-injected images are passed to the pipeline for source detection and photometric measurements. We cross-match the X-Y coordinates of the fake objects with the ones estimated by the pipeline using a 2 pixel maximun separation. For the ones return a multiple-match, we keep the one with the smallest separation (Claire has tried a different approach, which is keep all the matched objects. It has very small impact on the results). Meanwhile, we also keep record of the ones without any matched objects.

To make sure that the input models sample the intrinsic distributions of key parameters of the COSMOS galaxy models, we repeat this process 9 times. The same model can be selected in different runs, but only rarely. In general, we have 420-440 different models for Exp, Dev, and Sersic cases. For each model, the average, median, and standard deviation of important photometric parameters are estimated from all the detections (for most cases >15 out of 22), and are used to compared with the input values. Normally, for each run, 5-7% of the fake objects (22 CCDs x 50 Models = 1100 Fake objects) are without any match within 2 pixels. Most of these cases are due to the faintness of the model and/or proximity to bright objects.

At this point, we focus on comparing the input parameters with the magnitude, size, and shape measured by the CModel method in the pipeline. We do notice that, among all the fake objected injected in each run, 6-8% of them have failed CModel photometry. It is not clear what exactly cause this problem. To make the comparison more related to the photometric measurement itself, we furthur exclude all matched detections with \(nChild > 0\) (normally, >10/22).

Prospectus and Annotated Bibliography

Given the high precision of analysis techniques implemented at the LHC at Cern, there has been increasing opportunity to discover theories beyond the current model of fundamental physics. One such theory for physics “beyond the Standard Model” is known as Supersymmetry and proposes an additional symmetry to be added to space-time, allowing for a family of particles that are an exact duplicate (except for this quantity, labeled R) to those found in the Standard Model. Associated with the extension is a corresponding conservation law in supersymmetric interactions known as ‘R-parity’ \cite{Martin_2010}. R-parity conserving decays have been in high focus since they provide an explanation for the massive amount of dark energy foundr, estimated to be close to 73% \cite{Lahanas_2007}\cite{Garrett_2011}. Since R needs to be conserved, the lightest supersymmetric particle (LSP for short) would not be able to decay to any other particle other than itself and would explain the massive amount of seemingly stable dark matter \cite{Lahanas_2007}. For this reason, there has been a large effort to look for data that resemble R-parity conserving modes, without much attention towards R-parity violating decays.

Over the past two years, I performed an analysis looking for data that resembles a signal that is consistent with a supersymmetric decay. My target process is a supersymmetric top decaying to oppositely charged W-bosons one of which decays to a positive muon and an anti-b quark, and the second decays to a b-quark and negatively charged muon. I chose to look for a particular decay that resembles a standard model interaction with well understood backgrounds because I assumed that the process would behave similarly, except for this additional symmetry which I ignored as part of the analysis. Therefore, I chose a process whose major backgrounds were well modeled using current Monte Carlo methods.

One variable that affects the rate at which this occurs is the mass of the supersymmetric top quark \cite{Dolgov_2006}. Since this quantity has not be measured, the goal of my research was to to calculate a cutoff mass at which I can say there is enough data to prove/disprove the theory at a mass lower than a certain value. I did this by performing a comparison between the expected numbers if the theory were true to the numbers found in the data sample. Since the probability at which the decay happens decreases as the supersymmetric top mass increase, there should be a point at which the numbers flip from being too high to too low. The point at which this flip occurs is the “cutoff” point where I can say below which the data does not have enough events to support the theory.

The data came from the latest set published by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider at CERN in Switzerland. At the core of the design is a superconducting solenoid magnet that is 6m in diameter,13m long, and generates a 4T field which is used to determine the charge of the particle. On the outside of the magnet is an electromagnetic calorimeter (ECAL) which is designed to measure electromagnetic deposits. After the products of the decay have passed through the ECAL, they reach the hadronic calorimeter (HCAL) which absorbs most of the energy left in the collision. The particles that do make it through the HCAL are either neutrinos or muons. The muons are detected and collected in a separate configuration around the magnet composed of a drift tube and cathode-strip detector \cite{AUFFRAY_2002}\cite{Sguazzoni_2008}.

The result of this analysis will provide future researchers with a better sense of possible values for the mass of the supersymmetric top and possibly allow for the creation of more specialized detectors that focus on higher mass regions than the calculated cutoff.

**Measurement of ttbar\cite{Aad_2014}**

This paper provides a lot of important background information concerning the major backgrounds for the standard model version of my decay. Since it specifically focuses on ttbar production, it discusses many of the issues that I encountered while performing the analsysis. This paper will be useful in both the backbrgound section to provide appropriate info as well as guide me during my analysis of the data.

**Stops and neutrino mass hierarchy \cite{Marshall_2014}**

This paper outlines the correlation between supersymmetric top decau paramters and the neutrino mass hierarchy. This paper will prove to be useful during the section dedicated towards future research as it shows a way for this analysis to provide guidance towards research in the future.

**Previous serches for R-parity violation \cite{Stoye_2010}**

This paper discusses previous searches for R-parity violation and will be used in my background section to discuss the current state of ressearch in the field.

**A general summary of susy searches at LHC \cite{Paige_1999}**

Whereas the previous paper discusses more current efforts to search for SUSY, this paper provides an outlook on the field when it was first being discuessed. By looking at the original papers, the original reasons for pursuing particular lines of reseaerch becomes much more clear. This paper will be referenced in my introduction for a description of the field before we knew where to look.

**Dark matter considering MSSM \cite{Trotta_2007}**

This paper will also go in my introduction and provides a link between dark matter and the MSSM model. By providing this sort of information, it is clear that the hole I am filling with my research is not commonly considered due to the attractiveness of other theories, increasing the usefullness of my research.

**Dark Matter Primer \cite{Martin_2010}**

This paper will be referenced in my introduction and provides a different viewpoint on the Dark Matter problem as it stands in modern astro physics. By highlighting this issue I am able to drive home the importance of my research.

**LSP as DM Candidate \cite{Dolgov_2006}**

This paper describes the viability of the LSP as a dark matter candidate and will be referenced in my introduction to provide additional background material.

**Detector physics at the LHC \cite{AUFFRAY_2002}\cite{Sguazzoni_2008}**

These two papers provide a detailed description of the two technologies that are used in the CMS detector. By looking at the details of the construction, I am able to notice possible shortcomings of the experiment and find ways in which it can be improved. This paper will be refernced in my introduction as well as briefly in the section concern data acquisition.

A Gender Problem? In Academia?

Friday, an op-ed piece *actually* titled “Academic Science Isn’t Sexist” went up on the *New York Times* blog (a version appeared in the Sunday Review). It was about academic research and the lack of sexism therein. The two editorialists are co-authors on a recently released analysis on the subject (it *is* beautifully open access, and much of the raw data is available).

The piece and the paper claim sexism has largely waned in academic research, the result of shifts from a previously sexist, male-dominated academy. Further, that any remaining incongruities between male and female enrollment, advancement, and achievement are artifacts and anecdotal. Academic research is completely gender-blind now. Any differences are largely the product of society-at-large and earlier life decisions (like the choice to play with dolls/cute animals versus trucks/destructive robots).

Huh.

The response from the science blogging community and Twittersphere was immediate and is still on-going. Jonathan Eisen responded Halloween night, soon after the piece was posted. His immediate critique was of the acknowledgement of reports of “physical aggression” in the op-ed piece, without ever addressing these in their data or analysis (even the 60+ page research paper is short on coverage). The assumption: they are also anecdotal? So everything is actually fine?

Probably not (<- this article details accounts of *sexual misconduct in field work* involving biology, anthropology, and other social sciences, disciplines the authors above highlight as *largely welcoming and open to women*). Emily Willingham provides excellent analysis of the data presented in the paper and in the broader debate at hand. It turns out there are numerous discrepancies and avoided topics of analysis (e.g. salary figures often had statistically significant differences by gender; women more often reported lack of inclusion; more details in her impeccable post).

Likewise, Matthew Francis covered the story, emphasizing the need to actively address these still-existent problems and not ignore them: the importance of even a little explicit encouragement of female students in the face of implicit discouragement (like he sees in his native field of physics) is often all that’s needed. The ever-emphatic PZ Myers rounds out the debate by breaking down the major reasoning and assumptions in the original paper, with characteristic gusto.

So what exactly were the original authors thinking?

A handful of distributed scientists were able to challenge the key arguments of their paper, using their data and citations, in free time over the weekend.

Talk about peer-review.

Seriously though, what were they thinking? I would *like to think* that this was actually a brilliantly orchestrated publicity stunt to get more attention on this critical issue. **After all, who is going to blog/tweet/counter-op-ed “Academic Science is Slightly Less Sexist than when Male Academics could still Smoke in Their Offices”?** Because when you look at the data, the background on this issue, and the immediate response from the community, it’s obvious academic research isn’t now some utopian meritocracy brimming with equality. There is still institutional and systemic biases. Whether its gender, race, sexual-preference, or need related, or tied up in the archaic publishing system that is all too easily gamed, we have a long way to go before things can be considered “fair”. What might a fair system even look like?

Gamma Knife Problem

and 3 collaborators

Stereotactic radiosurgery delivers a single high dose of ionizing radiation to a radiographically well-defined, small intracranial 3D brain tumor without delivering any significant fraction of the prescribed dose to the surrounding brain tissue. Three modalities are commonly used in this area; they are the gamma knife unit, heavy charged particle beams, and external high-energy photon beams from linear accelerators.\cite{aoyama2006stereotactic}

The gamma knife unit delivers a single high dose of ionizing radiation emanating from 201 cobalt-60 unit sources through a heavy helmet. All 201 beams simultaneously intersect at the isocenter, resulting in a spherical (approximately) dose distribution at the effective dose levels. Irradiating the isocenter to deliver dose is termed a “shot.” Shots can be represented as different spheres. Four interchangeable outer collimator helmets with beam channel diameters of 4, 8, 14, and 18 mm are available for irradiating different size volumes. For a target volume larger than one shot, multiple shots can be used to cover the entire target. In practice, most target volumes are treated with 1 to 15 shots. The target volume is a bounded, three-dimensional digital image that usually consists of millions of points.

In geometry, circle packing is the study of the arrangement of circles (of equal or varying sizes) on a given surface such that no overlapping occurs and so that all circles touch another. The associated packing density of an arrangement is the proportion of the surface covered by the circles. In two dimensional Euclidean space, the optimal lattice arrangement of identically-sized circles with the highest density is the hexagonal packing arrangement, a result that was proven by Lagrange.\cite{chang2010simple} Generalizations can also be made of higher dimensions – this is called “sphere packing,” which usually deals only with identical spheres. We dealt only with circles for our first model for simplicity.

Optimization of hot dog vendor location for college student convenience

and 3 collaborators

Business site selection has always been high-stakes: the opening of a new business location has extremely large monetary implications. Location can impact margins, response to competition, and effective exploitation of possible market segments \cite{Clarke_2013}\cite{Cliquet_2013}\cite{Ghosh_1983}. It is also well-established that convenience is a significant factor in consumer decisions, especially those regarding food \cite{Bonke_1996}. In a university setting, decisions such as food vendor placement become particularly important, as daily food is the second highest consumer expenditure for college students \cite{Adams_1997}. In the present study, these understandings were incorporated into a decision procedure regarding the position of a hypothetical hot dog vendor on a college campus, in which convenience for students was evaluated using spatial information.

A map was given of a college campus showing the walking paths and dormitories and approximate distances between the intersections (Figure 1). We were asked to answer questions about the location of a hot dog vender:

Where on campus should you set up your stand?

How does your location change if you set up two stands?

Suppose A and C are female dorms and D, E, and F are male dorms. How would your location change if 30 percent of females and 80 percent of males are likely to eat at your stand?

Suppose the path between B and C and the path between E and D go uphill and that it is twice as hard to walk uphill as downhill. How would your choice change?

We propose an algorithm that determines the most convenient location as the position that minimizes the distance between the dormitories and the hot dog vendor location.

Supplemental Material for WASP: allele-specific methods for unbiased discovery of molecular quantitative trait loci

and 1 collaborator

To detect differences in molecular phenotypes from sequencing data it is essential to remove read mapping biases, which are a major source of false positives. The WASP read mapping pipeline accomplishes this task by ensuring that the mapping of each individual read is unbiased.