COURSE UNIT TITLE

: DARK MATTER RESEARCH

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
PHY 5107 DARK MATTER RESEARCH ELECTIVE 3 0 0 7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR MUHAMMED DENIZ

Offered to

PHYSICS
PHYSICS

Course Objective

Serve as an accessible bridge between the theory and the modern up-to-date experiments on dark matter searches including direct detection as well as the collider and indirect detections. In addition, learn the basic concepts of particles physics, astrophysics and cosmology.

Learning Outcomes of the Course Unit

1   Learning the history and evidence for the existence of Dark Matter.
2   Learning Particle Physics connection with the Dark Matter concepts in Astronomy and Astrophysics.
3   Learning direct detection of Dark Matter.
4   Learning indirect detection techniques and collider searches for dark matter.
5   A good understanding for recent hot topics and further to discussion in the international conference.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Dark Matter Physics and Overview
2 Evidence for Dark Matter - Galaxies and Clusters
3 Abundance of Dark Matter - CMB,BBN and LSS phenomenon
4 The particle zoo - Mass ranged from axions to MACHOs
5 Techniques for direct detection of WIMPs
6 1. Midterm
7 Recent Experiments: super-CDMS, XENON100, DAMA and others
8 Tension between null experiments and annual modulation results
9 Event rate calculation for Spin-independent and spin-dependent models and data analysis
10 Underground environment and background understanding
11 2. Midterm
12 Collider probes of Dark Matter
13 Indirect detection for Dark Matter
14 Models beyond the Standard Model and Future detection techniques and perspective

Recomended or Required Reading

Textbook(s):
Gianfranco Bertone (2010), PARTICLE DARK MATTER Observations, Models and Searches, 1st edition, Cambridge University Press, New York.

Supplementary Book(s):
1. Lefteris Papantonopoulos (2007), The invisible Universe: Dark Matter and Dark Energy, Springer, Berlin Heidelberg.
2. Robert H. Sanders, (2010), THE DARK MATTER PROBLEM A Historical Perspective, 1st edition, Cambridge University Press, New York.
3. Ken Freeman and Geoff McNamara, (2006), In Search of Dark Matter, Springer, in association with Praxis Publishing, Chichester, UK.

References:
1. J.D. Lewin, P.F. Smith,(1996), Review of mathematics, numerical factors and corrections for dark matter experiments based on elastic nucleus recoil , Astroparticle Physics, 87-112.
2. Marco Cirelli, (2012), Indirect Searches for Dark Matter: a status review, Proceeding of Lepton-Photon 2011, Mumbai, India. arXiv: 1202.1454

Planned Learning Activities and Teaching Methods

1. Method of Expression
2. Question & Answer Techniques
3. Discussion
4. Homework

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE 1 MIDTERM EXAM 1
2 MTE 2 MIDTERM EXAM 2
3 PRS PRESENTATION
4 FCG FINAL COURSE GRADE
5 FIN FINAL EXAM PRS * 0.15 + MTE 1 +MTE 2/2 * 0.25 + MAKRFIN * 0.60
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) PRS * 0.15 + MAKRMTE 1 +MTE 2/2 * 0.25 + RST * 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

1. Midterm report and assignments are taken as the achievements of students for the semester.
2. Final exam will be added to the success of the study of midterms and assignments, thereby the student's success will be determined.

Language of Instruction

English

Course Policies and Rules

1. 70% of the participation of classes is mandatory.
2. Students, who do not participate in Midterm exams and not do regular assignments, are not allowed to enter the final exam.
3. Every trial of cheating will be punished according to disciplinary proceedings.

Contact Details for the Lecturer(s)

muhammed.deniz@deu.edu.tr

Office Hours

Monday at 13: 00 - 15: 00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Practice (Reflection) 3 3 9
Preparations before/after weekly lectures 12 5 60
Preparing assignments 6 5 30
Preparation for midterm exam 2 5 10
Preparation for final exam 1 5 5
Final 1 3 3
Midterm 2 3 6
Quiz etc. 6 3 18
TOTAL WORKLOAD (hours) 177

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15553332253
LO.25555544545
LO.35445544545
LO.45445544545
LO.55555555545