The Physics Nobel Prize in 2019 has just been announced.
The 2019 Physics Noble prize one-half goes to James Peebles (Canadian American Physicist) for the "theoretical discoveries in physical cosmology", other half jointly to Michel Mayor and Didier Quer Queloz for the discovery of an exoplanet orbiting a solar-type star"
The official site says:
The 2019 Nobel Prize in Physics are awarded ”for contributions to our understanding of the evolution of the universe and Earth’s place in the cosmos”, with one half to James Peebles “for theoretical discoveries in physical cosmology” and the other half jointly to Michel Mayor and Didier Queloz “for the discovery of an exoplanet orbiting a solar-type star.”
Nobel prize in Physics is awarded each year for the fundamental contribution in Physics.
Here are three Professor's short biography (from wiki)
"Prof. Peebles OM FRS (born April 25, 1935) is a Canadian-American physicist and theoretical cosmologist who is currently the Albert Einstein Professor Emeritus of Science at Princeton University.[1][2] He is widely regarded as one of the world's leading theoretical cosmologists in the period since 1970, with major theoretical contributions to primordial nucleosynthesis, dark matter, the cosmic microwave background, and structure formation. His three textbooks (Physical Cosmology, 1971; Large Scale Structure of the Universe, 1980; Principles of Physical Cosmology, 1993) have been standard references in the field."
"Prof. Michel G.E. Mayor (born 12 January 1942, Lausanne) is a Swiss astrophysicist and professor emeritus at the University of Geneva's Department of Astronomy.[1] He formally retired in 2007, but remains active as a researcher at the Observatory of Geneva. He is co-winner of the 2010 Viktor Ambartsumian International Prize,[2] and the winner of the 2015 Kyoto Prize. Together with Didier Queloz in 1995 he discovered 51 Pegasi b, the first extrasolar planet orbiting a sun-like star, 51 Pegasi.[3] Mayor holds MS in Physics from the University of Lausanne (1966) and PhD in Astronomy from the Geneva Observatory (1971). His thesis also had an article called "Essay on the kinematical properties of stars in the solar vicinity: possible relation with the galactic spiral structure." He was a researcher at the Institute of Astronomy at the University of Cambridge in 1971. Subsequently, he spent sabbatical semesters at the European Southern Observatory (ESO) in northern Chile and at the Institute for Astronomy of the University of Hawaii system."
"Didier Queloz (born February 23, 1966) is a Swiss astronomer with a prolific record in finding extrasolar planets in the Astrophysics Group of the Cavendish Laboratory, Cambridge, and also at the University of Geneva. In 1995 Queloz was a Ph.D. student at the University of Geneva when he and Michel Mayor, his doctoral advisor, discovered the first exoplanet around a main sequence star.[1] Queloz performed an analysis on 51 Pegasi using radial velocity measurements (Doppler spectroscopy), and was astonished to find a planet with an orbital period of 4.2 days. He had been performing the analysis as an exercise to hone his skills.[2] The planet, 51 Pegasi b, challenged the then accepted views of planetary formation, being a hot Jupiter or roaster. He has received the 2011 BBVA Foundation Frontiers of Knowledge Award of Basic Sciences (co-winner with Michel Mayor) for developing new astronomical instruments and experimental techniques that led to the first observation of planets outside the solar system. In 2017 he received the Wolf Prize in Physics.[3]. In 2019 he received the Nobel Prize."
Recently, there is a post titled "Google reports quantum supremacy in draft paper" regarding a pre-print (a draft that would be published in a journal) reporting a Quantum Computer.
The report said that it takes only 200 seconds by the quantum computer containing 53 qubits which would otherwise take 10,000 years if ordinary supercomputer is used.
Amazing...
Physics world reports, "Quantum supremacy, whereby a quantum computer solves a problem in a significantly shorter time than a conventional (classical) computer, may have been achieved for the first time."
It is a collaborative work of scientists from google, Quantum Artificial Intelligence Lab.
It is mentioned that now the pre-print has been removed from the site.
Online learning platforms such as Coursera, Edx are great. They have high quality courses of diverse topics from well-reputed universities around the world. The professors and instructors are often well known and famous in their field. The problem is that the fees is not affordable to get the certificate after finishing the course. It is often priced at least $100 which is huge for most of the countries. I have tried many courses and finished most of the parts. But, when it comes to getting certificate, it becomes difficult. While there is an option to submit for fee withdrawal, I have not tried it. Their online degree courses are also highly priced. But, I definitely value these platforms for offering free courses free of cost. It costs only if you need certificate. Personally, I want to improve my skills, whether it to be programming skills, mathematics, communication skills, etc. But, some times the certificate is important to showcase your skills.
As an alternatives, some learning platforms provide very good courses for learning new topics. However, some of them are predatory and their charging models very. They often change the price of the course based on automatically changing algorithm. The price is fixed on the learner's interest on the courses.
Here are some strategies that I learnt you may follow before purchasing any course in such platforms:
Log in to your account from Firefox browser with duckduckgo search engine. Because, they don't track your personal information.
Don't add the course to your wish-list. This causes higher prices of courses. This happened to me. I added a number of courses in wish-list. The price never went down $15. Then, when I removed the courses from wish-list, the price of the courses was reduced below $10.
If you find a good course try to look for the instructor's coupon. Because, as for as this platform is concerned what the instructors are getting is very small amount. So, use coupons from the instructors and use to help the instructors.
"The molecular dynamics problem is generally treated as a coupled set of differential equations. The system of differential equation is discretized by choosing a discrete time step. Given the position and velocity of each particle at one time step, molecular dynamics simulation algorithms estimate these values at the next time step."
"The Time step is a crucial parameter in MD simulations as it determines the accuracy and efficiency of the numerical integration scheme. By default, the time step is typically set to 1 fs or less (in Q-Chem, 1 a.u. which is 0.0242 fs) in a number of codes.
"The central point is that a larger time step, although it may at first glance improve the efficiency of the simulation, increases the error in the numerical integration scheme of the equations of motion. The underlying assumption that the atomic forces are approximately constant during one integration step is not valid any more. Essentially, the chosen time step should be small enough to resolve the highest vibrational frequencies of the atoms (i.e. it should be much smaller than the smallest vibrational period), so if you have light atoms (e.g. hydrogen), you will generally be required to use a smaller time step than if you have only heavy atoms (such as gold). A smaller time step size may also be necessary if you have different elements in your calculation, if the temperature is high, or if the atoms are far away from their equilibrium configuration, i.e if large forces act on the particles. For most systems a safe choice to start, if you do not know what time step to use, is 1 fs. Larger timestep values can then be assessed by monitoring the conservation of the total energy in an NVE simulation under the conditions of interest."
pip install --upgrade --user ase /home/user/...../pip/_vendor/requests/__init__.py:83: RequestsDependencyWarning: Old version of cryptography ([1, 2, 3]) may cause slowdown. warnings.warn(warning, RequestsDependencyWarning) Collecting ase Downloading https://files.pythonhosted.org/packages/b4/52/df21f492fbd/ase-3.18.0.tar.gz (1.8MB) 100% |████████████████████████████████| 1.8MB 21.2MB/s Complete output from command python setup.py egg_info: Python 3.5 or later is required! ---------------------------------------- Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-install-tSeI9W/ase/ You are using pip version 18.0, however version 19.2.3 is available. You should consider upgrading via the 'pip install --upgrade pip' command.
Then, I tried since "Python 3.5 or later is required!" is given.
pip3 install --upgrade --user ase
Now, I get
Installing collected packages: ase Found existing installation: ase 3.17.0 Uninstalling ase-3.17.0: Successfully uninstalled ase-3.17.0 Successfully installed ase-3.18.0
(Earlier I have installed ase 3.17.0. Now it is updated to 3.18.0)
Then I tested the installation using
ase test
========== Summary ========== Number of tests 317 Passes: 229 Failures: 0 Errors: 0 Skipped: 88 ============================= Test suite passed! Time elapsed: 167.4 s
I have a PBS script to run jobs. The name is specified by #PBS -N tag.
But, if you want to run a number of files (100s, 1000s), it may be tedious to edit submit-jobs file for each file. Instead one can use this onliner to assign name to each jobs.
For example,
#For foo_bar_abc_1_01_geh_file.in, the Job Name should be test01,
#For foo_bar_abc_1_02_geh_file.in, the Job Name should be test02,
#For foo_bar_abc_1_100_geh_file.in, the Job Name should be test100,
etc.
for f in foo*.in; do qsub -N test$(echo $f|cut -d_ -f5) -v infile=$f run.pbs; done
Recently, I used permanent marker mistakenly instead of white-board marker. How to remove this writing?
1. If the writing is a few words or letters, you can use whiteboard marker (of any color) to write on the letters written by permanent marker. Then you can use clean cloth the remove. Now all will be gone.
2. If you have written the whole white board and you can use the first method, you can use fallowing procedure.
You can use pencil eraser to remove the writing.
3. Use Acetone. Acetone (250 ml) can be bought for about 2 USD. Use a pure cotton cloth and dip in acetone so that the cloth become wet. Then, gently rub on the board where the marker is written. This will clean the board completely. Make sure that acetone bottle is closed tight. Otherwise, it will evaporate quickly. You can use tissue papers too instead of a cloth.
4. You can use any alcohol and use method 3 by using a clean cloth.
For each number that is created using range(0,100), I created xyz coordinates to generate guess structures for my calculations. The structure of the script is as follow.
for numPoints in range(0, 101):
#do something to create x0, y0 and cons0 (xyz coordinates for a molecule)
np.savetxt(fname_template.format(i=numPoints), np.c_[x0,y0,cons0],delimiter=' ',fmt='%10f')
fname_template = "Subarray.{i}.txt" for i, sarr in enumerate(sub_arr): np.savetxt(fname_template.format(i=i), sarr, fmt='%s') To create the file name I've used the new string formatting. Otherwise you can concatenate strings with + as "Subarray."+str(i)+".txt", but you have to make sure that all the elements that you concatenate are strings.
