Consider a protein with 4 microstates (configurations) at energy eground = 0, 11 microstates at energyEmiddle = €o and 21 microstates at energy eexcited = 2 €0. Assume €o = 1.987 cal mol1. Let p(€ground) correspond to the probability of finding configurations at the lowest energy. VWhat is thisprobability at T = 300 K?%3D

Name: Consider a protein with 4 microstates (configurations) at energy egro
Uploaded: 2024-03-05T11:52:21.000Z
Channel: Bartleby
Description: Consider a protein with 4 microstates (configurations) at energy eground = 0, 11 microstates at energyEmiddle = €o and 21 microstates at energy eexcited = 2 €0. Assume €o = 1.987 cal mol1. Let p(€ground) correspond to the probability of finding conf

Answered: Image /qna-images/answer/392ebd73-2bb9-4789-9e67-007fb2e9e6a7.jpg

Math

Probability

Consider a protein with 4 microstates (configurations) at energy eground = 0, 11 microstates at energy €o and 21 microstates at energy Eexcited = 2 €o. Assume eo = 1.987 cal mol. Let p(€ground ) correspond to the probability of finding configurations at the lowest energy. What is this Emiddle probability at T = 300 K?

Consider a protein with 4 microstates (configurations) at energy eground = 0, 11 microstates at energy €o and 21 microstates at energy Eexcited = 2 €o. Assume eo = 1.987 cal mol. Let p(€ground ) correspond to the probability of finding configurations at the lowest energy. What is this Emiddle probability at T = 300 K?

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

See similar textbooks

Similar questions

The Beer-Lambert law relates the absorbance A of a solution to the concentration C of a species in solution by A = MLC, where L is the path length and M is the molar absorption coefficient. Assume that C = 1.25 ± 0.03 mol/cm3, L = 1.2 ± 0.1 cm, and A = 1.30 ± 0.05.a) Estimate M and find the uncertainty in the estimate.b) Which would provide a greater reduction in the uncertainty in M: reducing the uncertainty in C to 0.01 mol/cm³, reducing the uncertainty in L to 0.05 cm, or reducing the uncertainty in A to 0.01?
Let X1, . . . , Xn be iid with pdf f(x) = 1 x √ 2πθ2 e − (log(x)−θ1) 2 2θ2 , −∞ < x < ∞, and unknown parameters θ1 and θ2. Find the maximum likelihood estimators for θ1 and θ2, respectively
Given a discrete RV X that takes on the values {-2, -1, 3, 4} and whose pmf (probability mass function) is: p-2 = 0.1 , p-1 = 0.2 , p3 = 0.6 , p 4 = 0.1 . Calculate the mean μ X of RV X.
If we let RX(t) = ln MX(t), show that R X(0) = μ and RX(0) = σ2. Also, use these results to find the mean and the variance of a random variable X having the moment-generating function MX(t) = e4(et−1)
The probability that the protective building is between 15- and 20-microns dense is 0.417, which is obtained below: P(15<X<20)==20−15/24−12=0.417 Question-what formula was it used?
Consider a random variable X with E[X] = 10, and X being positive. Estimate E[ln√X] using Jensen’s inequality.
This is a poisson mass function for the future lifetime of a newborn: f0(k) = λk e- λ/k! for all k>= 0,where k is a discrete random variable.For λ= 3 estimate F4(16)
The number of trams X arriving at the St. Peter's Square tram stop every t minutes has the following probability mass function: p(x) =(0.25t)^x/x! * exp(-0.25t) for x=0,1,2,... the probability that 3 to 5 trams arrive in a 6 minute period is
a. What value of c will make f(x) a valid probability mass function ?b. Compute P (1 < X < 6).
The probability mass function of X = the number of major defects in an electrical appliance of a randomly selected type is: Calculate the following:a) E (X)b) V (X) directly from the definition
Find the net change in ve]locity over [1, 4] of an object with a(t) = 8t − t2 m/s2.
Suppose the proportion X of surface area in a randomly selected quadrat that is covered by a certain plant has a standard beta distribution with ? = 4 and ? = 2. (a) Compute E(X) and V(X). (Round your answers to four decimal places.) E(X) = V(X) = (b) Compute P(X ≤ 0.3). (Round your answer to four decimal places.)(c) Compute P(0.3 ≤ X ≤ 0.7). (Round your answer to four decimal places.)