Monday, December 19, 2011

Bayesian probability

practically nobody took very seriously the CDF claim.......Tommaso: I will claim based on the above that according to Prof. D'Agostini, Prof. Matt Strassler is "practically nobody", since he is not convinced.

An acoustical difference of opinion with regard too, Nobody?

What is the probability of the observed acoustic data given that each of two

possible phrases spoken?

Hmmmmm.......One is a shop keeper and one is a customer?

***

Bayesian probability is one of the different interpretations of the concept of probability and belongs to the category of evidential probabilities. The Bayesian interpretation of probability can be seen as an extension of logic that enables reasoning with propositions whose truth or falsity is uncertain. To evaluate the probability of a hypothesis, the Bayesian probabilist specifies some prior probability, which is then updated in the light of new, relevant data.^[1]

The Bayesian interpretation provides a standard set of procedures and formulae to perform this calculation. Bayesian probability interprets the concept of probability as " a probability p is an abstract concept, a quantity that we assign theoretically, for the purpose of representing a state of knowledge, or that we calculate from previously assigned probabilities,"^[2] in contrast to interpreting it as a frequency or a "propensity" of some phenomenon.
The term "Bayesian" refers to the 18th century mathematician and theologian Thomas Bayes (1702–1761), who provided the first mathematical treatment of a non-trivial problem of Bayesian inference.^[3] Nevertheless, it was the French mathematician Pierre-Simon Laplace (1749–1827) who pioneered and popularised what is now called Bayesian probability.^[4]

Broadly speaking, there are two views on Bayesian probability that interpret the probability concept in different ways. According to the objectivist view, the rules of Bayesian statistics can be justified by requirements of rationality and consistency and interpreted as an extension of logic.^[2]^[5] According to the subjectivist view, probability measures a "personal belief".^[6] Many modern machine learning methods are based on objectivist Bayesian principles.^[7] In the Bayesian view, a probability is assigned to a hypothesis, whereas under the frequentist view, a hypothesis is typically tested without being assigned a probability.

Bayesian methodology

In general, Bayesian methods are characterized by the following concepts and procedures:

The use of hierarchical models and marginalization over the values of nuisance parameters. In most cases, the computation is intractable, but good approximations can be obtained using Markov chain Monte Carlo methods.
The sequential use of the Bayes' formula: when more data become available after calculating a posterior distribution, the posterior becomes the next prior.
In frequentist statistics, a hypothesis is a proposition (which must be either true or false), so that the (frequentist) probability of a frequentist hypothesis is either one or zero. In Bayesian statistics, a probability can be assigned to a hypothesis.

Objective and subjective Bayesian probabilities

Broadly speaking, there are two views on Bayesian probability that interpret the 'probability' concept in different ways. For objectivists, probability objectively measures the plausibility of propositions, i.e. the probability of a proposition corresponds to a reasonable belief everyone (even a "robot") sharing the same knowledge should share in accordance with the rules of Bayesian statistics, which can be justified by requirements of rationality and consistency.^[2]^[5] Requirements of rationality and consistency are also important for subjectivists, for which the probability corresponds to a 'personal belief'.^[6] For subjectivists however, rationality and consistency constrain the probabilities a subject may have, but allow for substantial variation within those constraints. The objective and subjective variants of Bayesian probability differ mainly in their interpretation and construction of the prior probability.

History

Main article: History of statistics#Bayesian statistics

The term Bayesian refers to Thomas Bayes (1702–1761), who proved a special case of what is now called Bayes' theorem in a paper titled "An Essay towards solving a Problem in the Doctrine of Chances".^[8] In that special case, the prior and posterior distributions were Beta distributions and the data came from Bernoulli trials. It was Pierre-Simon Laplace (1749–1827) who introduced a general version of the theorem and used it to approach problems in celestial mechanics, medical statistics, reliability, and jurisprudence.^[9] Early Bayesian inference, which used uniform priors following Laplace's principle of insufficient reason, was called "inverse probability" (because it infers backwards from observations to parameters, or from effects to causes).^[10] After the 1920s, "inverse probability" was largely supplanted by a collection of methods that came to be called frequentist statistics.^[10]

In the 20th century, the ideas of Laplace were further developed in two different directions, giving rise to objective and subjective currents in Bayesian practice. In the objectivist stream, the statistical analysis depends on only the model assumed and the data analysed.^[11] No subjective decisions need to be involved. In contrast, "subjectivist" statisticians deny the possibility of fully objective analysis for the general case.
In the 1980s, there was a dramatic growth in research and applications of Bayesian methods, mostly attributed to the discovery of Markov chain Monte Carlo methods, which removed many of the computational problems, and an increasing interest in nonstandard, complex applications.^[12] Despite the growth of Bayesian research, most undergraduate teaching is still based on frequentist statistics.^[13] Nonetheless, Bayesian methods are widely accepted and used, such as in the fields of machine learning^[7] and talent analytics.

Justification of Bayesian probabilities

The use of Bayesian probabilities as the basis of Bayesian inference has been supported by several arguments, such as the Cox axioms, the Dutch book argument, arguments based on decision theory and de Finetti's theorem.

Axiomatic approach

Richard T. Cox showed that^[5] Bayesian updating follows from several axioms, including two functional equations and a controversial hypothesis of differentiability. It is known that Cox's 1961 development (mainly copied by Jaynes) is non-rigorous, and in fact a counterexample has been found by Halpern.^[14] The assumption of differentiability or even continuity is questionable since the Boolean algebra of statements may only be finite.^[15] Other axiomatizations have been suggested by various authors to make the theory more rigorous.^[15]

Dutch book approach

The Dutch book argument was proposed by de Finetti, and is based on betting. A Dutch book is made when a clever gambler places a set of bets that guarantee a profit, no matter what the outcome is of the bets. If a bookmaker follows the rules of the Bayesian calculus in the construction of his odds, a Dutch book cannot be made.

However, Ian Hacking noted that traditional Dutch book arguments did not specify Bayesian updating: they left open the possibility that non-Bayesian updating rules could avoid Dutch books. For example, Hacking writes^[16] "And neither the Dutch book argument, nor any other in the personalist arsenal of proofs of the probability axioms, entails the dynamic assumption. Not one entails Bayesianism. So the personalist requires the dynamic assumption to be Bayesian. It is true that in consistency a personalist could abandon the Bayesian model of learning from experience. Salt could lose its savour."

In fact, there are non-Bayesian updating rules that also avoid Dutch books (as discussed in the literature on "probability kinematics" following the publication of Richard C. Jeffrey's rule). The additional hypotheses sufficient to (uniquely) specify Bayesian updating are substantial, complicated, and unsatisfactory.^[17]

Decision theory approach

A decision-theoretic justification of the use of Bayesian inference (and hence of Bayesian probabilities) was given by Abraham Wald, who proved that every admissible statistical procedure is either a Bayesian procedure or a limit of Bayesian procedures.^[18] Conversely, every Bayesian procedure is admissible.^[19]

Personal probabilities and objective methods for constructing priors

Following the work on expected utility theory of Ramsey and von Neumann, decision-theorists have accounted for rational behavior using a probability distribution for the agent. Johann Pfanzagl completed the Theory of Games and Economic Behavior by providing an axiomatization of subjective probability and utility, a task left uncompleted by von Neumann and Oskar Morgenstern: their original theory supposed that all the agents had the same probability distribution, as a convenience.^[20] Pfanzagl's axiomatization was endorsed by Oskar Morgenstern: "Von Neumann and I have anticipated" the question whether probabilities "might, perhaps more typically, be subjective and have stated specifically that in the latter case axioms could be found from which could derive the desired numerical utility together with a number for the probabilities (cf. p. 19 of The Theory of Games and Economic Behavior). We did not carry this out; it was demonstrated by Pfanzagl ... with all the necessary rigor".^[21]

Ramsey and Savage noted that the individual agent's probability distribution could be objectively studied in experiments. The role of judgment and disagreement in science has been recognized since Aristotle and even more clearly with Francis Bacon. The objectivity of science lies not in the psychology of individual scientists, but in the process of science and especially in statistical methods, as noted by C. S. Peirce.^{[citation needed]} Recall that the objective methods for falsifying propositions about personal probabilities have been used for a half century, as noted previously. Procedures for testing hypotheses about probabilities (using finite samples) are due to Ramsey (1931) and de Finetti (1931, 1937, 1964, 1970). Both Bruno de Finetti and Frank P. Ramsey acknowledge^{[citation needed]} their debts to pragmatic philosophy, particularly (for Ramsey) to Charles S. Peirce.

The "Ramsey test" for evaluating probability distributions is implementable in theory, and has kept experimental psychologists occupied for a half century.^[22] This work demonstrates that Bayesian-probability propositions can be falsified, and so meet an empirical criterion of Charles S. Peirce, whose work inspired Ramsey. (This falsifiability-criterion was popularized by Karl Popper.^[23]^[24])

Modern work on the experimental evaluation of personal probabilities uses the randomization, blinding, and Boolean-decision procedures of the Peirce-Jastrow experiment.^[25] Since individuals act according to different probability judgements, these agents' probabilities are "personal" (but amenable to objective study).
Personal probabilities are problematic for science and for some applications where decision-makers lack the knowledge or time to specify an informed probability-distribution (on which they are prepared to act). To meet the needs of science and of human limitations, Bayesian statisticians have developed "objective" methods for specifying prior probabilities.

Indeed, some Bayesians have argued the prior state of knowledge defines the (unique) prior probability-distribution for "regular" statistical problems; cf. well-posed problems. Finding the right method for constructing such "objective" priors (for appropriate classes of regular problems) has been the quest of statistical theorists from Laplace to John Maynard Keynes, Harold Jeffreys, and Edwin Thompson Jaynes: These theorists and their successors have suggested several methods for constructing "objective" priors:

Each of these methods contributes useful priors for "regular" one-parameter problems, and each prior can handle some challenging statistical models (with "irregularity" or several parameters). Each of these methods has been useful in Bayesian practice. Indeed, methods for constructing "objective" (alternatively, "default" or "ignorance") priors have been developed by avowed subjective (or "personal") Bayesians like James Berger (Duke University) and José-Miguel Bernardo (Universitat de València), simply because such priors are needed for Bayesian practice, particularly in science.^[26] The quest for "the universal method for constructing priors" continues to attract statistical theorists.^[26]

Thus, the Bayesian statistican needs either to use informed priors (using relevant expertise or previous data) or to choose among the competing methods for constructing "objective" priors.

Notes

^ Paulos, John Allen. The Mathematics of Changing Your Mind, New York Times (US). August 5, 2011; retrieved 2011-08-06
^ ^a ^b ^c Jaynes, E.T. "Bayesian Methods: General Background." In Maximum-Entropy and Bayesian Methods in Applied Statistics, by J. H. Justice (ed.). Cambridge: Cambridge Univ. Press, 1986
^ Stigler, Stephen M. (1986) The history of statistics. Harvard University press. pg 131.
^ Stigler, Stephen M. (1986) The history of statistics., Harvard University press. pg 97-98, pg 131.
^ ^a ^b ^c Cox, Richard T. Algebra of Probable Inference, The Johns Hopkins University Press, 2001
^ ^a ^b de Finetti, B. (1974) Theory of probability (2 vols.), J. Wiley & Sons, Inc., New York
^ ^a ^b Bishop, C.M. Pattern Recognition and Machine Learning. Springer, 2007
^ McGrayne, Sharon Bertsch. (2011). The Theory That Would Not Die, p. 10. at Google Books
^ Stigler, Stephen M. (1986) The history of statistics. Harvard University press. Chapter 3.
^ ^a ^b Fienberg, Stephen. E. (2006) When did Bayesian Inference become "Bayesian"? Bayesian Analysis, 1 (1), 1–40. See page 5.
^ Bernardo, J.M. (2005), Reference analysis, Handbook of statistics, 25, 17–90
^ Wolpert, R.L. (2004) A conversation with James O. Berger, Statistical science, 9, 205–218
^ Bernardo, José M. (2006) A Bayesian mathematical statistics primer. ICOTS-7
^ Halpern, J. A counterexample to theorems of Cox and Fine, Journal of Artificial Intelligence Research, 10: 67-85.
^ ^a ^b Dupré, Maurice J., Tipler, Frank T. New Axioms For Bayesian Probability, Bayesian Analysis (2009), Number 3, pp. 599-606
^ Hacking (1967, Section 3, page 316), Hacking (1988, page 124)
^ van Frassen, B. (1989) Laws and Symmetry, Oxford University Press. ISBN 0198248601
^ Wald, Abraham. Statistical Decision Functions. Wiley 1950.
^ Bernardo, José M., Smith, Adrian F.M. Bayesian Theory. John Wiley 1994. ISBN 0-471-92416-4.
^ Pfanzagl (1967, 1968)
^ Morgenstern (1976, page 65)
^ Davidson et al. (1957)
^ "Karl Popper" in Stanford Encyclopedia of Philosophy
^ Popper, Karl. (2002) The Logic of Scientific Discovery 2nd Edition, Routledge ISBN 0415278430 (Reprint of 1959 translation of 1935 original) Page 57.
^ Pierce & Jastrow (1885)
^ ^a ^b Bernardo, J. M. (2005). Reference Analysis. Handbook of Statistics 25 (D. K. Dey and C. R. Rao eds). Amsterdam: Elsevier, 17-90

References

Berger, James O. (1985). Statistical Decision Theory and Bayesian Analysis. Springer Series in Statistics (Second ed.). Springer-Verlag. ISBN 0-387-96098-8.
Bernardo, José M.; Smith, Adrian F. M. (1994). Bayesian Theory. Wiley. ISBN 047149464x.
Bickel, Peter J.; Doksum, Kjell A. (2001). Mathematical statistics, Volume 1: Basic and selected topics (Second (updated printing 2007) of the Holden-Day 1976 ed.). Pearson Prentice–Hall. ISBN 013850363X. MR 443141.
Davidson, Donald; Suppes, Patrick; Siegel, Sidney (1957). Decision-Making: An Experimental Approach. Stanford University Press.
de Finetti, Bruno. "Probabilism: A Critical Essay on the Theory of Probability and on the Value of Science," (translation of 1931 article) in Erkenntnis, volume 31, September 1989.
de Finetti, Bruno (1937) "La Prévision: ses lois logiques, ses sources subjectives," Annales de l'Institut Henri Poincaré,
de Finetti, Bruno. "Foresight: its Logical Laws, Its Subjective Sources," (translation of the 1937 article in French) in H. E. Kyburg and H. E. Smokler (eds), Studies in Subjective Probability, New York: Wiley, 1964.
de Finetti, Bruno (1974–5). Theory of Probability. A Critical Introductory Treatment, (translation by A.Machi and AFM Smith of 1970 book) 2 volumes. Wiley ISBN 0471201413, ISBN 0471201421
DeGroot, Morris (2004) Optimal Statistical Decisions. Wiley Classics Library. (Originally published 1970.) ISBN 0-471-68029-X.
Hacking, Ian (December 1967). "Slightly More Realistic Personal Probability". Philosophy of Science 34 (4): 311–325. doi:10.1086/288169. JSTOR 186120. Partly reprinted in: Gärdenfors, Peter and Sahlin, Nils-Eric. (1988) Decision, Probability, and Utility: Selected Readings. 1988. Cambridge University Press. ISBN 0521336589
Hajek, A. and Hartmann, S. (2010): "Bayesian Epistemology", in: Dancy, J., Sosa, E., Steup, M. (Eds.) (2001) A Companion to Epistemology, Wiley. ISBN 1405139005 Preprint
Hald, Anders (1998). A History of Mathematical Statistics from 1750 to 1930. New York: Wiley. ISBN 0471179124.
Hartmann, S. and Sprenger, J. (2011) "Bayesian Epistemology", in: Bernecker, S. and Pritchard, D. (Eds.) (2011) Routledge Companion to Epistemology. Routledge. ISBN 10415962196 (Preprint)
Howson, C.; Urbach, P. (2005). Scientific Reasoning: the Bayesian Approach (3rd ed.). Open Court Publishing Company. ISBN 978-0812695786.
Jaynes E.T. (2003) Probability Theory: The Logic of Science, CUP. ISBN 9780521592710 (Link to Fragmentary Edition of March 1996).
McGrayne, Sharon Bertsch. (2011). The Theory That Would Not Die: How Bayes' Rule Cracked The Enigma Code, Hunted Down Russian Submarines, & Emerged Triumphant from Two Centuries of Controversy. New Haven: Yale University Press. 13-ISBN 9780300169690/10-ISBN 0300169698; OCLC 670481486
Morgenstern, Oskar (1978). "Some Reflections on Utility". In Andrew Schotter. Selected Economic Writings of Oskar Morgenstern. New York University Press. pp. 65–70. ISBN 9780814777718.
Pierce, C.S. and Jastrow J. (1885). "On Small Differences in Sensation". Memoirs of the National Academy of Sciences 3: 73–83.
Pfanzagl, J (1967). "Subjective Probability Derived from the Morgenstern-von Neumann Utility Theory". In Martin Shubik. Essays in Mathematical Economics In Honor of Oskar Morgenstern. Princeton University Press. pp. 237–251.
Pfanzagl, J. in cooperation with V. Baumann and H. Huber (1968). "Events, Utility and Subjective Probability". Theory of Measurement. Wiley. pp. 195–220.
Ramsey, Frank Plumpton (1931) "Truth and Probability" (PDF), Chapter VII in The Foundations of Mathematics and other Logical Essays, Reprinted 2001, Routledge. ISBN 0415225469,
Stigler, Stephen M. (1990). The History of Statistics: The Measurement of Uncertainty before 1900. Belknap Press/Harvard University Press. ISBN 0-674-40341-X.
Stigler, Stephen M. (1999) Statistics on the Table: The History of Statistical Concepts and Methods. Harvard University Press. ISBN 0-674-83601-4

External links

On-line textbook: Information Theory, Inference, and Learning Algorithms, by David MacKay, has many chapters on Bayesian methods, including introductory examples; arguments in favour of Bayesian methods (in the style of Edwin Jaynes); state-of-the-art Monte Carlo methods, message-passing methods, and variational methods; and examples illustrating the intimate connections between Bayesian inference and data compression.
An Intuitive Explanation of Bayesian Reasoning A very gentle introduction by Eliezer Yudkowsky
An on-line introductory tutorial to Bayesian probability from Queen Mary University of London
James Franklin The Science of Conjecture: Evidence and Probability Before Pascal, history from a Bayesian point of view.
Bayes’ Rule: A Tutorial Introduction by JV Stone.

Sunday, December 18, 2011

Snow Angel

Object Names: S106, Sh2-106, Sharpless 2-106
Image Type: Astronomical/Illustration

Credit: NASA, ESA, and the Hubble Heritage Team (STScI/AURA)

December 15, 2011: The bipolar star-forming region, called Sharpless 2-106, or S106 for short, looks like a soaring, celestial snow angel. The outstretched "wings" of the nebula record the contrasting imprint of heat and motion against the backdrop of a colder medium. Twin lobes of super-hot gas, glowing blue in this image, stretch outward from the central star. This hot gas creates the "wings" of our angel. A ring of dust and gas orbiting the star acts like a belt, cinching the expanding nebula into an "hourglass" shape. See: Hubble Serves Up a Holiday Snow Angel

Friday, December 16, 2011

Keeping Research Exciting

Comet LoveJoy

Comet Lovejoy seen by SOHO

“On average, new Kreutz-group comets are discovered every few days by SOHO, but from the ground they are much rarer to see or discover,” says Karl Battams, Naval Research Laboratory, who curates the Sun-grazing comets webpage. See Also: The beginning of the end for comet Lovejoy

One instrument watching for the comet was the Solar Dynamics Observatory (SDO), which adjusted its cameras in order to watch the trajectory. Not only does this help with comet research, but it also helps orient instruments on SDO -- since the scientists know where the comet is based on other spacecraft, they can finely determine the position of SDO's mirrors. This first clip from SDO from the evening of Dec 15, 2011 shows Comet Lovejoy moving in toward the sun.

Comet Lovejoy survived its encounter with the sun. The second clip shows the comet exiting from behind the right side of the sun, after an hour of travel through its closest approach to the sun. By tracking how the comet interacts with the sun's atmosphere, the corona, and how material from the tail moves along the sun's magnetic field lines, solar scientists hope to learn more about the corona. This movie was filmed by the Solar Dynamics Observatory in 171 Angstrom wavelength, which is typically shown in yellow.

Credit: NASA/SDO

The Very Latest SOHO Images

Wednesday, December 14, 2011

Explanation on Quantum Gravity in a Nutshell

Although Aristotle in general had a more empirical and experimental attitude than Plato, modern science did not come into its own until Plato's Pythagorean confidence in the mathematical nature of the world returned with Kepler, Galileo, and Newton. For instance, Aristotle, relying on a theory of opposites that is now only of historical interest, rejected Plato's attempt to match the Platonic Solids with the elements -- while Plato's expectations are realized in mineralogy and crystallography, where the Platonic Solids occur naturally.Plato and Aristotle, Up and Down-Kelley L. Ross, Ph.D.

The goal of string theory is to explain the "?" in the above diagram.

I enjoyed the Livescribe demonstration by Clifford of Asymptotia along with the explanation for Quantum Gravity. The two pillars for me were very emblematic with regards to "pillars of science." This as well as the arch is very fitting to me of what becomes self evident. If under such an examination of the two areas Clifford is talking about, Quantum Mechanics and General Relativity then are the attempts at unification.

The Yorck Project: 10.000 Meisterwerke der Malerei. DVD-ROM, 2002. ISBN 3936122202. Distributed by DIRECTMEDIA Publishing GmbH.

That question mark can be demonstrated above as to where in the location in Cliffords diagrams is related to the Aristotelian Arch in my view?

See:

Tuesday, December 13, 2011

Higgs Update Today

Backgrounder:

Guido Tonelli(CMS spokesperson) Higgs update English 1404258

Fabiola Gianotti (ATLAS spokesperson) Higgs update English 1403055

Heuer with Gianotti and Tonelli

See:

Higgs Update Today: Inconclusive, As Expected

Firm Evidence Of A Higgs Boson At Last!

See Also:

Possible Hints of the Higgs Remain in Latest Analyses

Possible signs of the Higgs remain in latest analyses

Fermilab scientist Don Lincoln describes the concept of how the search for the Higgs boson is accomplished. The latest data is revealed! Several large experimental groups are ht on the trail of this elusive subatomic particle which is thought to explain the origins of particle mass.

Friday, December 09, 2011

Tools For Cern Public Annoucement

CERN PUBLIC SEMINAR

Tuesday, December 13, 2011 from 14:00 to 16:00 (Europe/Zurich)
at CERN ( Main Auditorium )

Tuesday, December 13, 2011

14:00 - 14:30 Update on the Standard Model Higgs searches in ATLAS 30'

Speaker: Fabiola Gianotti
14:30 - 15:00 Update on the Standard Model Higgs searches in CMS 30'

Speaker: Guido TONELLI
15:00 - 16:00 Joint question session 1h0'

Located at Indico Cern Conference

***

See:

See Also:

Thursday, December 08, 2011

Kepler-22b


Images credit: NASA/Ames/JPL-Caltech This image is an artist's conception of planet Kepler-22b, a planet known to comfortably circle in the habitable zone of a sun-like star. It is the first planet that NASA's Kepler mission has confirmed to orbit in a star's habitable zone -- the region around a star where liquid water, a requirement for life on Earth, could persist. The planet is 2.4 times the size of Earth, making it the smallest yet found to orbit in the middle of the habitable zone of a star like our sun. See: Kepler-22b, Super-Earth in the habitable zone of a Sun-like Star

Bolshoi Simulation: WMAP Explorer

Bolshoi Simulation Visualization from UC-HPACC on Vimeo. Watch With Music.

Visualization of the dark matter in 1/1000 of the gigantic Bolshoi cosmological simulation, zooming in on a region centered on the dark matter halo of a very large cluster of galaxies. Visualized by Chris Henze, NASA Ames Research Center. This visualization was narrated in the National Geographic TV special "Inside the Milky Way". It was used with the piece "Dark Matter" in Bjork's Biophilia concert.

The Bolshoi simulation is the most accurate cosmological simulation of the evolution of the large-scale structure of the universe yet made (“bolshoi” is the Russian word for “great” or “grand”). The first two of a series of research papers describing Bolshoi and its implications have been accepted for publication in the Astrophysical Journal. The first data release of Bolshoi outputs, including output from Bolshoi and also the BigBolshoi or MultiDark simulation of a volume 64 times bigger than Bolshoi, has just been made publicly available to the world’s astronomers and astrophysicists. See: Introduction: The Bolshoi Simulation

See Also:

Wednesday, December 07, 2011

Gordon Kane Post on Reference Frame

Fig.3 Revisionist History and String Theory and the Real World

See: "Learning from theory and data about our string vacuum"

***

Also for viewing:

NAS Produces Animations of Dark Matter for Planetarium Shows

***

The newly-installed Alpha Magnetic Spectrometer-2 (AMS)

Description

Excerpt from "Alpha Magnetic Spectrometer - A Physics Experiment on the International Space Station" by Dr. Sam Ting: The Alpha Magnetic Spectrometer (AMS-02) is a state-of-the-art particle physics detector constructed, tested and operated by an international team composed of 60 institutes from 16 countries and organized under United States Department of Energy (DOE) sponsorship. The AMS-02 will use the unique environment of space to advance knowledge of the universe and lead to the understanding of the universe's origin by searching for antimatter, dark matter and measuring cosmic rays.

Experimental evidence indicates that our Galaxy is made of matter; however, there are more than 100 hundred million galaxies in the universe and the Big Bang theory of the origin of the universe requires equal amounts of matter and antimatter. Theories that explain this apparent asymmetry violate other measurements. Whether or not there is significant antimatter is one of the fundamental questions of the origin and nature of the universe. Any observations of an antihelium nucleus would provide evidence for the existence of antimatter. In 1999, AMS-01 established a new upper limit of 10^-6 for the antihelium/helium flux ratio in the universe. AMS-02 will search with a sensitivity of 10^-9, an improvement of three orders of magnitude, sufficient to reach the edge of the expanding universe and resolve the issue definitively.

The visible matter in the universe (stars) adds up to less than 5 percent of the total mass that is known to exist from many other observations. The other 95 percent is dark, either dark matter (which is estimated at 20 percent of the universe by weight or dark energy, which makes up the balance). The exact nature of both still is unknown. One of the leading candidates for dark matter is the neutralino. If neutralinos exist, they should be colliding with each other and giving off an excess of charged particles that can be detected by AMS-02. Any peaks in the background positron, anti-proton, or gamma flux could signal the presence of neutralinos or other dark matter candidates.

Six types of quark (u, d, s, c, b and t) have been found experimentally, however all matter on Earth is made up of only two types of quarks (u and d). It is a fundamental question whether there is matter made up of three quarks (u, d and s). This matter is known as Strangelets. Strangelets can have extremely large mass and very small charge-to-mass ratios. It would be a totally new form of matter. AMS will provide a definitive answer on the existence of this extraordinary matter. The above three examples indicates that AMS will probe the foundations of modern physics.

Cosmic radiation is a significant obstacle to a manned space flight to Mars. Accurate measurements of the cosmic ray environment are needed to plan appropriate countermeasures. Most cosmic ray studies are done by balloon-borne satellites with flight times that are measured in days; these studies have shown significant variations. AMS-02 will be operative on the ISS for a nominal mission of 3 years, gathering an immense amount of accurate data and allowing measurements of the long term variation of the cosmic ray flux over a wide energy range, for nuclei from protons to iron. After the nominal mission, AMS-02 can continue to provide cosmic ray measurements. In addition to the understanding the radiation protection required for manned interplanetary flight, this data will allow the interstellar propagation and origins of cosmic rays to be pinned down. See: The newly-installed Alpha Magnetic Spectrometer-2 (AMS)

Apex Experiment

APEX is one of several experiments hunting for the carrier of a new force, a hypothetical boson dubbed A’. This graph shows the range of the parameter space covered by these proposed experiments. The solid red is the slice of parameter space covered by APEX’s test run. The full APEX experiment will search the entire area above the red curve. See: PI Science: Hunting for New Forces

***

We present a search at Jefferson Laboratory for new forces mediated by sub-GeV vector bosons with weak coupling $\alpha'$ to electrons. Such a particle $A'$ can be produced in electron-nucleus fixed-target scattering and then decay to an $e^+e^-$ pair, producing a narrow resonance in the QED trident spectrum. Using APEX test run data, we searched in the mass range 175--250 MeV, found no evidence for an $A'\to e^+e^-$ reaction, and set an upper limit of $\alpha'/\alpha \simeq 10^{-6}$. Our findings demonstrate that fixed-target searches can explore a new, wide, and important range of masses and couplings for sub-GeV forces. See: Search for a new gauge boson in the $A'$ Experiment (APEX)

***

Rouven Essig, Search for a New Vector Boson Decaying to e+e- (talk to Hall A Collaboration on APEX Motivation ).

Saturday, December 03, 2011

Magic Cerenkov Telescope

MAGIC (Major Atmospheric Gamma-ray Imaging Cherenkov Telescopes) is a system of two Imaging Atmospheric Cherenkov telescopes situated at the Roque de los Muchachos Observatory on La Palma, one of the Canary Islands, at about 2200 m above sea level. MAGIC detects particle showers released by gamma rays, using the Cherenkov radiation, i.e., faint light radiated by the charged particles in the showers. With a diameter of 17 meters for the reflecting surface, it is the largest in the world.

The first telescope was built on 2004 and operated for five years in standalone mode. A second MAGIC telescope (MAGIC-II), at a distance of 85 m from the first one, started taking data in July 2009. Together they integrate the MAGIC telescope stereoscopic system.^[1]

MAGIC is sensitive to cosmic gamma rays with energies between 50 GeV and 30 TeV due to its large mirror; other ground-based gamma-ray telescopes typically observe gamma energies above 200-300 GeV. Satellite-based detectors detect gamma-rays in the energy range from keV up to several GeV.

See Also: The Magic Telescopes

Bird Man?

Amazing flying for Jetman.

Yves Rossy: That's really the goal, because if you put [in] steering, then you reinvent the airplane. And I wanted to keep this freedom of movement. And it's really like the kid playing the airplane. I want to go down like that. And up I climb, I turn. It's really pure flying. It's not steering, it's flight.

Friday, December 02, 2011

A Synesthetes Talk in the Afterlife :)

Looking up a list of who's who in the Synesthetes world I found it quite interesting. This YouTube Video below was attributed too Maureen Seaberg

When Mayer was seventeen, he was stricken with cardiac dysrhythmia and was hospitalized for a weekend. Reflecting on the incident, Mayer said, “That was the moment the songwriter in me was born,” and he penned his first lyrics the night he got home from the hospital. See: John Mayer (October 16, 1977), musician, sound to color

John Mayer's song about gravity was quite appealing for obvious reasons? Maybe some will understand why but in science it cannot be so.

See: Synesthesia Resource Center

Thursday, December 01, 2011

Intensity Frontier Workshop and Space Exploration

This workshop is an opportunity for the scientific community to identify the physics potential of the Intensity Frontier. Starting in September 2011, six working groups will study and begin to document the full spectrum of opportunities for fundamental physics at the Intensity Frontier and identify the necessary facilities to execute such a program.

The workshop is open to the broader particle and nuclear physics community and the working groups will expect and solicit input from the community. This exercise will continue during October and November 2011, with smaller topical workshops and meetings organized by the working groups. The workshop from Nov 30 to Dec 2, 2011 will be another opportunity for community input and the workshop will conclude with the preliminary findings of the working groups. The final report detailing the workshop results will be completed by the end of January 2012.Fundamental Physics at the Intensity Frontier

***

Exploring the Wonders of the Universe

The newly-installed Alpha Magnetic Spectrometer-2 is visible at center of the International Space Station's starboard truss. The Alpha Magnetic Spectrometer, or AMS, is the largest scientific collaboration to use the orbital laboratory. This investigation is sponsored by the U.S. Department of Energy and made possible by funding from 16 nations. Led by Nobel Laureate Samuel Ting, more than 600 physicists from around the globe will be able to participate in the data generated from this particle physics detector. The mission of the AMS is, in part, to seek answers to the mysteries of antimatter, dark matter and cosmic ray propagation in the universe. Image Credit: NASA

See Also:

Wednesday, November 30, 2011

Superconductivity Dance Flash Mob

What can I say people in science seem to like to dance a lot to explain things?:)

Ranging from slime molds to Alzheimer’s Disease, a new online exhibit, Emergent Universe (http://www.emergentuniverse.org) aims to encourage young people to learn about “emergence,” complex behaviors that arise from the interaction of simple parts. See: Emergent Universe - an online museum of science.

***

Flash Mobs & Floating Trains

Created for the online science museum emergentuniverse.org, this dance flash mob illustrates the behavior of electrons in a superconductor. Superconductors are materials which, at very low temperatures, can conduct electric currents without any resistance. That means that the current can flow forever with no energy loss.

The exhibit on superconductivity at emergentuniverse.org will go live this summer, 2011, in honor of the 100th anniversary of the discovery of the phenomenon of superconductivity. Emergentuniverse.org is sponsored by the Institute for Complex Adaptive Matter (icam-i2cam.org).

***

At emergentuniverse.org "Unlocking the Universe" together with "Hear the Music," it was appealing to me back then as it is now.

***

The weird quantum nature of the atomic world challenges us to revise the way we view the world around us. We learn that our everyday world - built out of the myriad superposition of matter waves, has an unexpected capacity for new kinds of behavior and "self organization" that we are only just beginning to fathom. Music of the Quantum World

***

See Also:

Bee Movie and Science Today

Update:

Music of the Quantum

Tuesday, November 29, 2011

PlatoHagel's Channel

Just some of the YouTubes I have watched.

Would have liked Blogger to design a Youtube index feature according to the blogger YouTubes we have highlighted in our own blogs. Also each time one comes to this blog or others, a different Youtube will will be presented for viewing from our favorites?

Monday, November 28, 2011

Reality Tunnel

Certainly do not know who the fellow is in present image(Gregg Braden).....but for now, that is not important. He is not important and his message.....about life.....I am concerned about the science. As I watch the Tibetan Monk there is a question for me about the boundary and the infinite. These same notions of belief about the multiverse too have hidden in them thoughts from a scientific point of view(think of The Fabric of the Cosmos IV) as well as a spiritual perspective as shown in YouTube video above. Put the spiritual wording aside then. What is it we strive to do then about something then greater then ourselves? Is this what we are doing?

Of course I am seeking responsible questions about the nature of reality as they are are very important to me.

So indeed it would have been much easier for me to see the traced pathways of routes that any of us took could become a pathway for another to experience and understand. This is not about "What the Bleep" and the value of the entry of the video above, is something more then what is ascertain by such description of what could have fueled those local universes. What is to become the motivation of what could have progressed from the Big Bang to become the eternal inflation?

Yet can we not say that each of us has their individual pathway of experience is but to know that "such a tunnel" predates and points toward the idea of expression as a viable option to the life unfolding for us. Is it real? What is your motivation for being then if not to have a "driving force for expression?" Your acceptance to participate?

So such a tunnel for expression then becomes a method by which all undergo the process toward us saying something that is real when and only when....or indeed, is it illusory? So we accept "the tunnel as real?" Such a format becomes a method by which such expression for life is "becoming?"

Feynman: Probability and Uncertainty in Quantum Mechanics

Richard Feynman courtesy of the Cornell Messenger Lecture Archive. Cornell Mathematics Library. Lecture #6 Probability and Uncertainty in quantum mechanics.

See Also: Feynman on QM in 1964

It is nice to see particulate expression from this point of view as well. Thanks Lubos.

History of Supersymmetry to Today

Special Topic of Supersymmetry

by Science Watch

Since the 1980s, if not earlier, supersymmetry has reigned as the best available candidate for physics beyond the standard model. But experimental searches for supersymmetric particles have so far come up empty, only reconfirming the standard model again and again. This leaves supersymmetry a theory of infinite promise and ever more questionable reality. See Link above.

Also: What's Inside ScienceWatch.com This Month - ScienceWatch.com - Thomson Reuters

Update-

See Also :

Nima Arkani-Hamed on Maximally Supersymmetric Theories

An interview with Arkani-Hamed on SUSY

Thursday, November 24, 2011