100 world physics experts to meet at Depok

Depok, West of Java (ANTARA News) – No less than 100 world class physics experts from 24 countries will join a world conference held at the University of Indonesia (UI) campus, from Tuesday (Aug 19) through Saturday (Aug 23), a spokesperson of the university said here on Monday.

“This conference will be attended by some 100 participants from 24 countries. These people are outstanding physicians mostly from the MIT (Massachusetts Institute of Technology)in the U.S and from Tokyo University in Japan. Japan will send 30 percent, the highest number, and Indonesia will be represented by 8 physicians,” UI spokeswoman Devi Rahmawati, told ANTARA News

She said the conference themed “The Fourth Asia-Pacific Conference on Few-Body Problems in Physics 2008” (APFB08), and scheduled to be opened by Minister of Research and Technology Kusmayanto Kadiman along with Rector of UI Gumilar R Somantri and Dean of Science School Adi Basukriadi.

She also explained that the conference to be held in Depok is the fourth for “few-body” problems in physics for the Asia-Pacific region.

The first conference held in 1999 at Tokyo, Japan. The next was held in 2002 in Shanghai, China, and the third was in 2005 in Nakhon Ratchasima, Thailand.

Devi further said the organizers have received a list of 94 abstracts which will be delivered on orally or in posters.

During the five-day meeting, the participants will discuss the latest techniques to solve “few-body” problems in physics and the latest findings in physics, she said. (*)(http://www.antara.co.id)

Breaking News From Broken Symmetries : Nobel Prize in Physics 2008

The breaking news of this year in physics is a honor to three physicists who working on the spontaneous symmetries breaking. One of them is Prof. Y. Nambu from the Enrico Fermi Institute, University of Chicago ,who got a half of the sharing prize. He got a prize for the discovery of the mechanism of spontaneous broken symmetry in subatomic physics. The second is Prof. Makoto Kobayashi from the High Energy Accelerator Research Organization, Japan and the third one is Prof. Toshihide Maskawa from Kyoto University. Each of them got quarter of the sharing prize. Both proposed the theory for the discovery of the origin of the broken symmetry which predicts the existence of at least three families of quarks in nature.

Anyway, in the standard model, spontaneous symmetry breaking is accomplished by using the Higgs boson and is responsible for the masses of the W and Z bosons. A slightly more technical presentation of this mechanism is given in the article on the Yukawa interaction, where it is shown how spontaneous symmetry breaking can be used to give mass to fermions. The picture on the right side is a famous “Mexican Hat” which describe the spontaneous symmetry broken.

Bayesian Analysis in Kaon Photoproduction

Angular distributions of differential cross sections from the latest CLAS data sets ~\cite{bradford}, for the reaction ${\gamma}+p

{\rightarrow} K^{+} + {\Lambda}$ have been analyzed using associated Legendre polynomials. This analysis is based upon theoretical calculations in Ref.~\cite{fasano} where all sixteen observables in kaon photoproduction can be classified into four Legendre classes. Each observable can be described by an expansion of associated Legendre polynomial functions. One of the questions to be addressed is how many associated Legendre polynomials are required to describe the data. In this preliminary analysis, we used data models with different numbers of associated Legendre polynomials. We then compared these models by calculating posterior probabilities of the models. We found that the CLAS data set needs no more than four associated Legendre polynomials to describe the differential cross section data. In addition, we also show the extracted coefficients of the best model.

Introduction
Significant information on the structure of the nucleon can be obtained by studying its excitation spectrum. Over the last few decades, a large amount information about the spectrum of the nucleon has been collected. Most of this information has been extracted from pion-induced and pion photoproduction reactions. However, pionic reactions may have biased the information on the existence of certain resonances. Constituent quark model calculations predict a much richer resonance spectrum than has been observed in pion production experiments~\cite{capstick}. Predicted resonances which have not been observed are called “missing” resonances. Instead, the constituent quark model also predicts that these “missing” resonances may couple strongly to K$\Lambda$ and K$\Sigma$ channels or other final states involving vector mesons~\cite{capstick,mart1,mart2}. Since performing kaon-hyperon, kaon-nucleon or hyperon-nucleon scattering experiments is a daunting task, kaon photoproduction on the nucleon appears to be a good alternative solution~\cite{mart1,mart2}.

Experiments on kaon photoproduction and electroproduction started in the 1960s. However the old experimental data are often inconsistent and have large error bars. In recent years a large amount of data for kaon photoproduction has been collected. High statistics data from CLAS, for differential cross sections, recoil polarization, $C_{x}$ and $C_{z}$ double polarizations for the reaction $\gamma + p \rightarrow K^{+} + \Lambda$ have been published~\cite{bradford,bradfor2}. Additional experimental data have also been measured by SAPHIR~\cite{glander,tran,glander2}, LEPS~\cite{sumihama,zegers} and GRAAL~\cite{leres}.

Several previous analyses have been applied to the results of these experiments, such as Isobar models~\cite{mart1,mart2,ireland,janssen,janssen2} and Coupled channel models~\cite{shyklar,usov,penner}. However different theoretical model calculations often produce very different predictions. In Ref.\cite{fasano} all sixteen observables in kaon photoproduction were shown to be classified into the classes ${\cal L}_0(\hat{{\bf I}};\hat{{\bf E}};\hat{{\bf C_{z’}}};\hat{{\bf
L_{z’}}})$, ${\cal L}_{1a}(\hat{{\bf P}}; \hat{{\bf H}}; \hat{{\bf C_{x’}}}; \hat{{\bfL_{x’}}})$, ${\cal L}_{1b}(\hat{{\bf T}}; \hat{{\bf F}}; \hat{{\bf O_{x’}}};\hat{{\bf T_{z’}}})$ and ${\cal L}_2(\hat{{\bf {\Sigma}}}; \hat{{\bf G}}; \hat{{\bf O_{z’}}}; \hat{{\bf T_{x’}}})$, where each class is an expansion in a different set of associated Legendre polynomials. What is not apparent is how many terms in each expansion are required. This work attempts to address the issue by examining data models with different numbers of terms, and calculating which one has the greatest posterior probability. In this article we only focus on the differential cross section observables, which are described by the associated Legendre class ${\cal L}_0$. (PTPH)

Who was the Reverend Thomas Bayes?

Bayes, Thomas (b. 1702, London – d. 1761, Tunbridge Wells, Kent), mathematician who first used probability inductively and established a mathematical basis for probability inference (a means of calculating, from the number of times an event has not occured, the probability that it will occur in future trials).

He set down his findings on probability in “Essay Towards Solving a Problem in the Doctrine of Chances” (1763), published posthumously in the Philosophical Transactions of the Royal Society of London.

The only works he is known to have published in his lifetime are Divine Benevolence, or an Attempt to Prove That the Principal End of the Divine Providence and Government is the Happiness of His Creatures (1731) and An Introduction to the Doctrine of Fluxions, and a Defence of the Mathematicians Against the Objections of the Author of the Analyst (1736) which countered attacks by Bishop Berkeley on the logical foundations of Newton’s calculus.

Here is some more information about Bayes taken from the book The Official Guide to Bunhill Fields. Bunhill Fields is a park in London, England where Bayes is buried (see The Burial Place of Bayes below).

He was a Presbyterian minister in Tunbridge Wells from 1731, son of the Rev. Joshua Bayes, a Nonconformist minister. It is thought that his election to the Royal Society might have been based on a tract of 1736 in which Bayes defended the views and philosophy of Sir Isaac Newton. A notebook of his exists, and includes a method of finding the time and place of conjunction of two planets, notes on weights and measures, a method of differentiation, and logarithms.

Thomas Bayes’ contributions are immortalized by naming a fundamental proposition in probability, called Bayes Rule, after him. (The following is quoted from the Encyclopaedia Britannica)

Bayesian Analysis

What is Bayesian Analysis?

What we now know as Bayesian statistics has not had a clear run since 1763. Although Bayes’s method was enthusiastically taken up by Laplace and other leading probabilists of the day, it fell into disrepute in the 19th century because they did not yet know how to handle prior probabilities properly. The first half of the 20th century saw the development of a completely different theory, now called frequentist statistics. But the flame of Bayesian thinking was kept alive by a few thinkers such as Bruno de Finetti in Italy and Harold Jeffreys in England. The modern Bayesian movement began in the second half of the 20th century, spearheaded by Jimmy Savage in the USA and Dennis Lindley in Britain, but Bayesian inference remained extremely difficult to implement until the late 1980s and early 1990s when powerful computers became widely accessible and new computational methods were developed. The subsequent explosion of interest in Bayesian statistics has led not only to extensive research in Bayesian methodology but also to the use of Bayesian methods to address pressing questions in diverse application areas such as astrophysics, weather forecasting, health care policy, and criminal justice.

Scientific hypotheses typically are expressed through probability distributions for observable scientific data. These probability distributions depend on unknown quantities called parameters. In the Bayesian paradigm, current knowledge about the model parameters is expressed by placing a probability distribution on the parameters, called the “prior distribution”, often written as

When new data y become available, the information they contain regarding the model parameters is expressed in the “likelihood,” which is proportional to the distribution of the observed data given the model parameters, written as
This information is then combined with the prior to produce an updated probability distribution called the “posterior distribution,” on which all Bayesian inference is based. Bayes’ Theorem, an elementary identity in probability theory, states how the update is done mathematically: the posterior is proportional to the prior times the likelihood, or more precisely,

In theory, the posterior distribution is always available, but in realistically complex models, the required analytic computations often are intractable. Over several years, in the late 1980s and early 1990s, it was realized that methods for drawing samples from the posterior distribution could be very widely applicable.

There are many reasons for adopting Bayesian methods, and their applications appear in diverse fields. Many people advocate the Bayesian approach because of its philosophical consistency. Various fundamental theorems show that if a person wants to make consistent and sound decisions in the face of uncertainty, then the only way to do so is to use Bayesian methods. Others point to logical problems with frequentist methods that do not arise in the Bayesian framework. On the other hand, prior probabilities are intrinsically subjective — your prior information is different from mine — and many statisticians see this as a fundamental drawback to Bayesian statistics. Advocates of the Bayesian approach argue that this is inescapable, and that frequentist methods also entail subjective choices, but this has been a basic source of contention between the `fundamentalist’ supporters of the two statistical paradigms for at least the last 50 years. In contrast, it is more the pragmatic advantages of the Bayesian approach that have fuelled its strong growth over the last 20 years, and are the reason for its adoption in a rapidly growing variety of fields. Powerful computational tools allow Bayesian methods to tackle large and complex statistical problems with relative ease, where frequentist methods can only approximate or fail altogether. Bayesian modelling methods provide natural ways for people in many disciplines to structure their data and knowledge, and they yield direct and intuitive answers to the practitioner’s questions.

There are many varieties of Bayesian analysis. The fullest version of the Bayesian paradigm casts statistical problems in the framework of decision making. It entails formulating subjective prior probabilities to express pre-existing information, careful modelling of the data structure, checking and allowing for uncertainty in model assumptions, formulating a set of possible decisions and a utility function to express how the value of each alternative decision is affected by the unknown model parameters. But each of these components can be omitted. Many users of Bayesian methods do not employ genuine prior information, either because it is insubstantial or because they are uncomfortable with subjectivity. The decision-theoretic framework is also widely omitted, with many feeling that statistical inference should not really be formulated as a decision. So there are varieties of Bayesian analysis and varieties of Bayesian analysts. But the common strand that underlies this variation is the basic principle of using Bayes’ theorem and expressing uncertainty about unknown parameters probabilistically. (quoted from http://www.bayesian.org/ ).

KELVIN 2007

Lord Kelvin was a giant of the 19^th Century Science, his fundamental contributions to thermal physics, electromagnetism and optics being matched by practical achievements ranging from undersea amplifiers to marine compasses.

In Glasgow, where Kelvin held the chair of Natural Philosophy for over 50 years, we plan to celebrate the 100^th anniversary of his death by inviting four leading scientists to look where the fields Kelvin started are now and where they are going. Sir Michael Berry will talk on vortices in light, Ed Hinds on cold atoms, Wilson Sibbett on telecommunications and Denis Weaire on Foams and Kelvin’s Legacy. The event will be chaired by the current holder of the Kelvin Chair, David Saxon.

This event will be held in the recently renovated Kelvin Gallery within the historic buildings of Glasgow University and adjacent to the Huntarian Gallery and Kelvin Exhibition.

Asia -Pacific Few Body 2008 Conference 2008

I was very glad to attend the Asia-Pacific Few Body 2008 in my own country. This conference, i thought the biggest conference in nuclear physics which there was in Indonesia as long as i knew. That was one reason why i attended this conference. Another reason is because i got funding support from department, so i can back to Indonesia with free beside attend the conference :). Anyway, the conference started on 19-23 August in Indonesia University. The chairmans of local committee are Dr. Imam Fachruddin and Prof. Dr. Terry Mart. This conference attended the physicist from many country such as Japan, USA, Germany, Iran, Australia, Thailand, UK. Almost all of the participant presented about N-N interaction (two body), N-N-N interaction (three body), Kaon Photoproduction as well as the experimental.(PTPH)

Kesulitan sebanding dengan Tahun

Minum teh dan membaca beberapa surat kabar baik media cetak maupun online adalah hal yang biasa saya lakukan setiap pagi. Hari ini (15/03/2008) saya surat kabar online yang pertama saya buka adalah detiK.com. Front page pada detik.com banyak dihujani dengan berita hujan di daerah Jakarta, Bogor dan sekitarnya. Selain itu, mengenai beberapa berita didaerah, kebetulan hari ini berita yang diliput adalah dari Surabaya. Berita ini menjadi fokus perhatian dan perenungan saya hari ini. Berita yang diliput adalah karena adanya seorang bapak mencuri helm di salah satu mal di Surabaya guna membeli susu untuk anak semata wayangnya. Selain itu, persis dibawah berita ini juga diberitakan bahwa mahasiswa ITS melakukan pencurian Laptop di sebuah toko elekronik di Surabaya. Singkat cerita, kedua pelaku kejahatan ini, ditangkap oleh polisi dan kasusnya akan diproses sesuai hukum yang berlaku.

Sesuai dengan apa yang diberitakan detik.com, pelaku akan diganjar hukuman kurang lebih 7 tahun penjara. Saya berpikir sekejap, seandainya bapak anak perempuan yang mencuri susu diganjar hukuman penjara bagaimana nasib anaknya tersebut? terlepas dari apa yang dilakukan oleh si sang Bapak. Hal ini membuat saya sangat terenyuh sekali. Satu hal yang terpikir dibenak saya adalah apa penyebab orang tersebut melakukan hal tersebut? Kalo memang benar orang tersebut melakukan kejahatan karena untuk susu anaknya, saya pikir ganjaran tetap diberikan tetapi pemerintah perlu memperhatikan nasib si anak kecil yang serta merta menjadi korban.

Selain itu, pikiran saya juga berkelana yang berhenti pada satu titik dimana saya memikirkan bahwa kehidupan di Indonesia saat ini memang dan benar-benar sangat sulit sekali. Saya berpikir untuk itu saya perlu melakukan sesuatu untuk diri saya, artinya saya perlu meng-konstrain diri saya untuk tidak lebih besar pasak daripada tiang. Saya menyadari bahwa pendapatan saya juga tidak sama seperti orang kebanyakan hidup di Jakarta yang hidup kebanyakkan dengan life style dan komsumsi yang tinggi. Lebih ekstrim lagi, saya berpikir lebih baik tidak mengikuti life style tapi saya bisa hidup dengan nyaman dan damai serta tenang. Life style yang tidak terkontrol, saya pikir adalah salah satu penyebab masalah kesulitan di masyarakat kita saat ini.

Anyway, terus apa hubungannya dengan kesulitan sebanding dengan tahun apa ya? dari apa yang saya baca dan amati dari beberapa media online adalah bahwa kesulitan di masyarakat “sepertinya” semakin susah sekali dari tahun ke tahun sepertinya sebanding…artinya tahun meningkat ke angka 2008, masalah kehidupan dimasyarakat semakin saja bertambah (kesimpulan ini dibuat hanya sebagai hipotesis saja dan tidak berdasarakan analysis ato sebagainya). Terus terang saya disini juga tidak menyalahkan pemerintah ato meniadakan usaha dan pencapaian yang telah dilakukan pemerintah ato siapapun tetapi saya ingin mengajak kita melalui tulisan dan perenungan saya adalah : Sebenarnya secara tidak kita sadari adalah bahwa yang membuat masalah bagi kita adalah kita sendiri. Oleh karena itu kenapa kita tidak untuk mencoba “menahan keinginan-keinginan” kita, saya tahu bahwa tingkat kepuasan kita pasti terusik. Untuk itu, saya menyarankan lakukan sesuatu yang lain, yang berbiaya rendah tetapi kepuasan anda bisa terwujudkan.

 

 

 

 

 

Glasgow Mathematica 2008

Two days ago, i attended the Glasgow Mathematica Conference 2008. This conference separate being two sessions. One session was Mathematica training. In this session, we were introduced and explained what is Mathematica software, how to write command/code in Mathematica. In the last of each topics, we then got some exercises to write them in Mathematica code which were related with the each topics. I thought this exercise was very improtant to remember the code. In addition, in this session all of us assumed as Mathematica beginner.

By the way, attendant which attended this conference come from difference area research such computing science, biology molecular, engineering, nuclear physics, etc. To be honest, I myself have one reason to attend this conference, i wish i can use this software in my future research.

I think this software is very useful to solve long equation or simply the long equation and make a graph for that equation. Instead this software can also be used in simple programming to solve the equation which can not solve analytically. But to be honest, i really don’t know that this software is very useful for me actually, because i have never used this software before. But I always keep in mind that this software can be useful for my next or future research. So i just let myself know let us see what happened for the next after i attended this conference.

The second one was a Conference session. I did not follow this session because i was not interesting. Therefore, I backed to my office to continue my work that day. So i could not tell you what happened in this session. In this article, i hope you can get some useful information to yourself about Mathematica. There is one thing, you should know that Mathematica can be used for animation with simple programming. You don’t need to learn another programming language such as Fortran, C++ , etc. In addition, you don’t need to spend a lot of time to learn them.

Fifth International Conference on PERSPECTIVES IN HADRONIC PHYSICS

Foto pada Fifth International Conference on PERSPECTIVES IN HADRONIC PHYSICS, Particle-Nucleus and Nucleus-Nucleus Scattering at Relativistic Energies, Trieste Italy, 22 – 26 May 2006. From left to right, Suing Paccha Ruben Dario ( Equator), Roy J. Glauber (USA), Arnau Rios (SPAIN) and me. Roy J. Glauber attended this conference to give a talk about the quantum theory of optical coherence.Many nuclear physicist and theorist attended this conference to give a talk about their working. Nuclear theorist presented about Deep Inelastic Scattering (DIS), nucleus-nucleus interaction such as proton-neutron interaction, proton-proton interaction, and nuclear matter. Later, nuclear physics or experimentalist presented what they measured in their experiment and explained the challenge or opportunity which they are going to do in their next experiment. They also offered the nuclear theorist to submit proposal to them for doing collaboration.

Through Deep Inelastic Scattering, the nuclear theorist tried to study and understand the interaction between quarks in protons and neutrons on the nucleus. Another presenter talked about extreme density in nuclear matter and neutron star properties and Pentaquark.