Large Deviation and Statistical Physics
نویسندگان
چکیده
منابع مشابه
A Statistical Mechanics Approach to Large Deviation Theorems
Chernoo bounds and related large deviation bounds have a wide variety of applications in statistics and learning theory. This paper proves that for any real-valued random variable X the probability of a deviation to value x is bounded by e S(x) where S(x) is the entropy at energy x of a physical system corresponding to the variable X. It is a well known fact of statistical mechanics that entrop...
متن کاملEconomic Fluctuations and Statistical Physics: The Puzzle of Large Fluctuations
We present an overview of recent research applying ideas of statistical physics to try to better understand puzzles regarding economic fluctuations. One of these puzzles is how to describe outliers, phenomena that lie outside of patterns of statistical regularity. We review evidence consistent with the possibility that such outliers may not exist. This possibility is supported by recent analysi...
متن کاملLarge deviation theory and applications
Large deviation theory deals with the decay of the probability of increasingly unlikely events. It is one of the key techniques of modern probability, a role which is emphasised by the recent award of the Abel prize to S.R.S. Varadhan, one of the pioneers of the subject. The subject is intimately related to combinatorial theory and the calculus of variations. Applications of large deviation the...
متن کاملFunctional Large Deviation
We establish functional large deviation principles (FLDPs) for waiting and departure processes in single-server queues with unlimited waiting space and the rst-in rst-out service discipline. We apply the extended contraction principle to show that these processes obey FLDPs in the function space D with one of the non-uniform Skorohod topologies whenever the arrival and service processes obey FL...
متن کاملLarge Deviation Theory
If we draw a random variable n times from Q, the probability distribution of the sum of the random variables is given by Q. This is the convolution of Q with itself n times. As n → ∞, Q tends to a normal distribution by the central limit theorem. This is shown in Figure 1. The top line is a computed normal distribution with the same mean as Q. However, as shown in Figure 3, when plotted on a lo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Progress of Theoretical Physics Supplement
سال: 1989
ISSN: 0375-9687
DOI: 10.1143/ptps.99.165