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mhjensen committed Dec 30, 2023
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97 changes: 8 additions & 89 deletions doc/LectureNotes/_build/html/_sources/schedule.md
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Expand Up @@ -6,106 +6,25 @@ This course will be delivered in a hybrid mode, with online and on site lectures
2. Three hours of laboratory sessions for work on computational projects and exercises. There will also be fully digital laboratory sessions for those who cannot attend. The first two weeks lectures and labs will be online;
3. Two projects which are graded and count 1/2 each of the final grade;
4. The course is offered as a FYS4411 (Master of Science level) and a FYS9411 (PhD level) course;
5. Videos of teaching material are available via the links at https://www.uio.no/studier/emner/matnat/fys/FYS4411/v21/timeplan/index.html#FOR;
6. Weekly emails with summary of activities will be mailed to all participants;
5. Weekly emails with summary of activities will be mailed to all participants;


## Teaching schedule with links to material


### Week 4, January 23-27, 2023
### Week 3, January 15-19, 2024
- Introduction to the course and start variational Monte Carlo
- Video of Lecture at https://youtu.be/2wg5rDJ7bek
- Video of Lecture at https://youtu.be/
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week1/html/week1.html

### Week 5, January 30-February 3, 2023
### Week 4, January 22-26, 2024
- Building a variational Monte Carlo program, Metropolis algorithm
- Video of Lecture at https://www.youtube.com/watch?v=wUULie1JWk4
- Video of Lecture at https://www.youtube.com/
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week2/html/week2.html

### Week 6, February 6-10, 2023
### Week 5, January 29-February 2, 2024
- Metropolis sampling and Importance Sampling
- Video of lecture at https://youtu.be/9_pPGtwlF4s
- Video of lecture at https://www.youtube.com/
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week3/html/week3.html

### Week 7, February 13-17, 2023

- Video of lecture at https://youtu.be/JPmU4BWTd2Y
- Importance sampling, Fokker-Planck and Langevin Equations
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week4/html/week4.html

### Week 8, February 20-24, 2023

- Video of lecture at https://youtu.be/KieUu9ni60w
- Optimization, gradient descent methods and finalization of discussion on importance sampling
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week5/html/week5.html


### Week 9, February 27-March 3, 2023

- Lab session only


### Week 10, March 6-10, 2023

- Gradient Descent and optmization
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week7/html/week7.html
- Video of lecture at https://youtu.be/-iBHxpE9byQ

### Week 11, March 13-17, 2023

- Resampling methods, Blocking and Bootstrapping
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week8/html/week8.html
- Video of lecture at https://youtu.be/0gk6wtdlh0g

### Week 12, March 20-24, 2023

- Video of lecture at https://youtu.be/zbxvPJ5YxR8
- Blocking and bootstrap techniques for resampling
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week9/html/week9.html


### Week 13, March 27-31, 2023

- High-performance computing
- Final discussion of project 1 and summary of first part of semester
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week10/html/week10.html
- Video of lecture at https://youtu.be/XqL8qhpKKQs

### Week 14, April 3-7, 2023

- No lectures, university closed

### Week 15, April 10-14, 2023

- Discussions of project 2
- Video of lecture at https://youtu.be/z32jQkNLqxo
- Project 2 descriptions at http://compphysics.github.io/ComputationalPhysics2/doc/

### Week 16, April 17-21, 2023

- Deep learning and quantum many-body systems, Boltzmann machines
- Video of lecture at https://youtu.be/SibaquLChg8
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week13/html/week13.html


### Week 17, April 24-28, 2023

- Deep learning and Bolztmann Machines
- Video of lecture at https://youtu.be/u20rSipMoyE
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week14/html/week14.html


### Week 18, May 1-5, 2023

- Deep learning and quantum many-body systems, implementing neural networks
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week15/html/week15.html
- Video of lecture at https://youtu.be/KOIMlsSAt1E

### Week 19, May 9-13, 2023


- Summary of course and last lecture and lab session
- Lecture Material at http://compphysics.github.io/ComputationalPhysics2/doc/pub/week16/html/week16.html


### Week 7 and later will be updated soon
35 changes: 1 addition & 34 deletions doc/LectureNotes/_build/html/_sources/textbooks.md
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Expand Up @@ -80,7 +80,7 @@ Here we list several useful Python libraries we strongly recommend (if you use a



### How do I run MPI/OpneMP on a PC/Laptop? MPI =====
### How do I run MPI/OpneMP on a PC/Laptop? MPI
To install MPI is rather easy on hardware running unix/linux as operating systems, follow simply the instructions from the "OpenMPI website":"https://www.open-mpi.org/". See also subsequent slides.
When you have made sure you have installed MPI on your PC/laptop,
- Compile with mpicxx/mpic++ or mpif90
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## Face coverings.
As of now this is not required, but the situation may change. If face covering will be required during the semester, we will fill in more details.

## Physical distancing
We will be practicing physical distancing in the classroom dedicated to the lab sessions. Thus, everybody should maintain at least one meter distance between themselves and others (excluding those with whom they live). This applies to all aspects of the classroom setting, including seating arrangements, informal conversations, and dialogue between teachers and students.


## Personal Hygiene
All participants attending the laboratory sessions must maintain proper hygiene and health practices, including:
* frequently wash with soap and water or, if soap is unavailable, using hand sanitizer with at least 60% alcohol;
* Routinely cleaning and sanitizing living spaces and/or workspace;
* Using the bend of the elbow or shoulder to shield a cough or sneeze;
* Refraining from shaking hands;

## Adherence to Signage and Instructions
Course participants will (a) look for instructional signs posted by UiO or public health authorities, (b) observe instructions from UiO or public health authorities that are emailed to my “uio.no” account, and (c) follow those instructions.
The relevant links are https://www.uio.no/om/hms/korona/index.html and https://www.uio.no/om/hms/korona/retningslinjer/veileder-smittevern.html

## Self-Monitoring
Students will self-monitor for flu-like symptoms (for example, cough, shortness of breath, difficulty breathing, fever, sore throat or loss of taste or smell). If a student experiences any flu-like symptoms, they will stay home and contact a health care provider to determine what steps should be taken.
## Exposure to COVID-19
If a student is exposed to someone who is ill or has tested positive for the COVID-19 virus, they will stay home, contact a health care provider and follow all public health recommendations. You may also contact the study administration of the department where you are registered as student.
## Compliance and reporting
Those who come to UiO facilities must commit to the personal responsibility necessary for us to remain as safe as possible, including following the specific guidelines outlined in this syllabus and provided by UiO more broadly (see links below here).

## Additional information
See https://www.uio.no/om/hms/korona/index.html and https://www.uio.no/om/hms/korona/retningslinjer/veileder-smittevern.html. For English version, click on the relevant link.






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