Science topics: Computational PhysicsMonte Carlo

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# Monte Carlo - Science topic

Explore the latest questions and answers in Monte Carlo, and find Monte Carlo experts.

Questions related to Monte Carlo

Do Monte Carlo or Generalize Linear Model do the same thing?

What are their difference?

Which is best for a count data and why?

Dear scientific researchers,

I am working with SOLTRACE software to simulate the optical performance of a solar parabolic trough collector and I would like to know if there are possibilities to include a DNI file on the simulation of the studied collector instead of a fixed DNI value. Moreover, I calculate the ratio between the rays hitting the tube receiver and the ones reflected by the mirrors. I would like to know if this ratio is corresponding to the optical efficiency or to the intercept factor.

Thank you in advance for your help and collaboration.

Best regards.

I want to do Computational screening of chiral metal–organic frameworks for enantioselective adsorption

Please share a paper/report/thesis how monte carlo simulation can be applied to Multi criteria decision making.

Based on the Mediation model, I have 2 parallel mediators for which I would like to calculate the sample size based on a power of 0.80 and a medium effect size. Is what I had input correct?

Like MPFP, important sampling etc.

Hi,

Imagine that you are going to sample a protein conformation (consists of N atoms) using Monte Carlo and Molecular Dynamics simulations, independently.

For the MD simulation, the phase space has a dimension of 6N dimension (3N position and 3N momentum). I'm assuming that the phase space for MC has a dimension of 3N (just position of atoms). Am I missing something here?

I'm doing a LINAC simulation using the Monte Carlo code TOPAS. I've read somewhere that the NRC LINAC specifications are not propriety and are in the public domain, but I failed to find them.

Can someone point me in the right direction where I should look. I tried google patents, science direct and web of science but came up empty handed.

I've found this paper (https://doi.org/10.1118/1.1290714) with the geometrical specifications but for the same component it was given two different distances form central axes can someone help me understand it.

Any help would be greatly appreciated.

I am trying to determine health risk by Monte Carlo in @Risk software. When I am running my data, the mean, maximum and minimum is the same and the bell-shaped graph is not forming.

Please help!

Thanks in advance!

Dear all,

I am eager to conduct power analysis by employing the Monte Carlo simulation available in Mplus. I have run a Multivariate Latent Growth Curve model (MLGCM) with my three-wave longitudinal data in my study, and thus, I have followed the guideline presented by Muthen & Muthen (2002; ). However, I guess, I am a systematic mistake (see, the attached output of monte carlo simulation for % sig. coefficient for mean score for SNAT = .134) but, unfortunately, I cannot find out what the problem/mistake is. Is there anyone who might help out to find the mistake(s)?

The out of the Monte Carlo simulation is attached. Besides, you can see the output of my MLGCM below. Thanks in advance for any kind of help!

MODEL RESULTS

Two-Tailed

Estimate S.E. Est./S.E. P-Value

INAT |

ID_T1 1.000 0.000 999.000 999.000

ID_T2 1.000 0.000 999.000 999.000

ID_T3 1.000 0.000 999.000 999.000

SNAT |

ID_T1 0.000 0.000 999.000 999.000

ID_T2 1.000 0.000 999.000 999.000

ID_T3 2.000 0.000 999.000 999.000

IET |

ID_G1 1.000 0.000 999.000 999.000

ID_G2 1.000 0.000 999.000 999.000

ID_G3 1.000 0.000 999.000 999.000

SET |

ID_G1 0.000 0.000 999.000 999.000

ID_G2 1.000 0.000 999.000 999.000

ID_G3 2.000 0.000 999.000 999.000

SNAT WITH

INAT -0.083 0.041 -2.037 0.042

IET WITH

INAT -0.208 0.080 -2.582 0.010

SNAT 0.019 0.034 0.556 0.578

SET WITH

INAT 0.063 0.037 1.732 0.083

SNAT 0.017 0.014 1.178 0.239

IET -0.205 0.087 -2.361 0.018

Means

INAT 3.497 0.061 57.275 0.000

SNAT -0.027 0.026 -1.018 0.309

IET 3.479 0.078 44.763 0.000

SET -0.129 0.035 -3.713 0.000

Intercepts

ID_T1 0.000 0.000 999.000 999.000

ID_T2 0.000 0.000 999.000 999.000

ID_T3 0.000 0.000 999.000 999.000

ID_G1 0.000 0.000 999.000 999.000

ID_G2 0.000 0.000 999.000 999.000

ID_G3 0.000 0.000 999.000 999.000

Variances

INAT 0.706 0.092 7.662 0.000

SNAT 0.079 0.031 2.568 0.010

IET 1.141 0.156 7.316 0.000

SET 0.148 0.069 2.135 0.033

Residual Variances

ID_T1 0.131 0.068 1.929 0.054

ID_T2 0.244 0.040 6.055 0.000

ID_T3 0.057 0.063 0.901 0.368

ID_G1 0.115 0.116 0.998 0.318

ID_G2 0.338 0.059 5.696 0.000

ID_G3 0.139 0.105 1.324 0.186

Determining intervals for the common language effect size (CLES), probability of superiority (PS), Area Under the Curve (AUC) or Exceedance Probability (EP) is possible via multiple method Ruscia and Mullen (2012). However, is this also possible via Fishers Z transformation? For simplicity I will call the “effect size” EP.

If we make the following assumptions: we have a (real) value that can range between -1 and 1 and assume the error distribution is (approximately) normally distributed (also invoking CLT), then we would be able to obtain intervals via Fishers z transformation (I think???).

The rationale is: EP does not range from -1 and 1, but from 0 till 1. Hereby 0.5 would represent the NULL. However, it would be possible to transform the EP to a value between -1 and 1 assuming a “directionality”: < 0.5 is negative and >= 0.5 is positive. Then,

EP

_{d}=(EP-0.5)*2EP

_{z}= ln[ (EP_{d}+1)/(EP_{d}-1) ]*0.5 = atanh(EP_{d})SE = √[ 1/(3-n

_{1}) + 1/(3-n_{2}) ]Lower = SE*1.96-EP

_{d}Upper = SE*1.96+EP

_{d}Transformation back to the original scale (EP) would be possible for both positive and negative values.

If positive

EP = [ exp(EP

_{d}*2)-1)/(exp(EP_{d}*2)+1 ]/2+0.5 = tanh(EP_{d})/2+0.5If negative

EP = [ 1 + (exp(EP

_{d}*2)-1)/(exp(EP_{d}*2)+1) ] / 2 = [ 1 + tanh(EP_{d}) ]/2However, when comparing the analytical intervals to Monte Carlo (MC) simulations the intervals are much broader using a smaller samples size. Although the extreme intervals, either upper when EP < 0.5 or lower when EP < 0.5 Below an example of Ruscio and Mullen (2012) where n1 and n2 are both 15 and another example with the same mu and sd when nx and ny are both 150. Also the intervals by Ruscio and Mullen (2012) are much smaller. The question is, why are these intervals broader is the rationale completely wrong, did I make a mistake or is it simply impossible what I am doing? I know there are other ways obtaining the intervals but using fishers Z transformation would make it rather “elegant”.

Thank you in advance for your time!

Dear all,

I am looking for any helpful resources on monte carlo markov chain simulation. Either pdf, book or stata do file or R script would be a great help for me. Any starting point where I can learn mcmc asap.

Would be really happy if someone can share Stata do.file or R scripts for monte carlo markov chain.

Thank you very much

Many Monte Carlo methods to solve a given Partial Differential Equation (PDE) are built by sampling the PDE's Green's function. E.g., for heat diffusion, diffusion-convection-reaction type of equations, and so on, have algorithms that can be derived directly from the PDE (i.e., through Ito calculus or stochastic integral). On the other hand, for the Radiative Transfer Equation (RTE), there is an Integral representation. However, the argument for explaining Monte Carlo Radiative Transfer (MCRT) ALWAYS revolves around the physical interpretation.

I even found a review article [1] that states on page 16: "Unlike traditional approaches to RT problems, MCRT calculations do not attempt to solve the RTE directly."

Is there really NO relation (discovered yet) between MCRT and the RTE? or is it just that no one has ever proven this?. I understand the physical interpretation; it is just that having mathematical foundations would also help teach it in class. Can anyone help me by directing me to a reference that derives this?.

[1] Noebauer, U. M., & Sim, S. A. (2019). Monte Carlo radiative transfer.

*Living Reviews in Computational Astrophysics*,*5*(1), 1-103.i want to know how can i can begin to write the UDF(User Define Function) for monte carlo ray tracing

Hi everyone,

I am currently developing a Gibbs Ensemble Monte Carlo algorithm. I am trying to implement a Widom Insertion Method to calculate the chemical potential of the liquid-phase and gas-phase boxes; however, I haven't been able to successfully do it. My inter-particle potential is that of a hard sphere (i.e. equal to infinity when particles overlap). I suspect the issue with my implementation has to do with how I've been treating the instances where the inserted particles overlap with any of the particles already present in the box I'm trying to determine the chemical potential of. I've been guiding myself by the work of Frenkel & Smit; more specifically, the article attached. Can anyone with experience in this topic help me figure this out?

Thank you beforehand for any assistance anyone may provide!

I am looking for the following article for a student at the University of Burgundy :
- A Monte Carlo Study of Confidence Interval Methods for Generalizability Coefficient / Zhehan Jiang, Mark Raymond, Christine DiStefano, Dexin Shi, Ren Liu, Junhua Sun

Published August 7, 2021 Educational and Psychological Measurement
Our library can pay this interloan library with IFLA Vouchez.
Thank you for your help

The forecast error determined by the probability density function (PDF) of the system forecast error can be used to model uncertainty. Monte Carlo sampling (MCS) and simulation generate a number of solar irradiances and load demand scenarios. The greater the number of generated scenarios, the more complicated the computation and the longer the convergence response time. As a result, this study used a K-means clustering-driven scenario reduction scheme to reduce the generated scenarios in reduced scenarios while preserving a precise estimation of the uncertainty.

Is there a manuscript or book where these concepts can be learned, or any MatLab/python code where they can be understood?

Dear colleagues

I have tried to conduct a Monte Carlo simulation in Mplus for a latent three-factor model with correlations between the factors. I want to test whether n = 500 would be enough to construct the factors properly and to detect correlations as low as r = .3. (I know it propably is, I just wanted to finally explore Monte Carlo simulations).

However, I keep receiving the following error message, no matter what I do:

***** ERROR in MONTECARLO command**

**Probabilities of observations for patterns must sum up to 1.**

Unfortunately, the Mplus website is no help. I have enclosed my syntax. It is a lot to ask, but those of you who are familiar with Monte Carlo simulations for categorical indicators, would you consider pointing my in the right direction? What do I need to change?

Thank you in advance for your insight.

Best

Marcel

P.S. I have attached a more reader friendly PDF of the syntax as well.

**-------------------------------------------------------------------------------------------**

**TITLE:**

Monte Carlo study

three factors: subjective content knowledge (geography, history, civics)

categorical indicators (4-point Likert scale)

**MONTECARLO:**

NAMES =

f18_a f18_b f18_c f18_d f18_e f18_f f18_g

f19_a f19_b f19_c f19_d f19_e

f20_a f20_b f20_c f20_d f20_e f20_f f20_h f20_i;

CATEGORICAL =

f18_a f18_b f18_c f18_d f18_e f18_f f18_g

f19_a f19_b f19_c f19_d f19_e

f20_a f20_b f20_c f20_d f20_e f20_f f20_h f20_i;

NOBSERVATIONS = 500;

NREPS = 1000;

!Items measured on a 4-point Likert scale

GENERATE = f18_a-f20_i (3 p);

!5 % missings on each item assumed

PATMISS = f18_a-f20_i (.05);

!50 % of cases assumed to have missings

PATPROBS = .50;

!The next part is probably where I get it wrong

**MODEL POPULATION:**

SCK_Geo BY f18_a-f18_g*.1

SCK_Geo@1;

SCK_His BY f19_a-f19_e*.1

SCK_His@1;

SCK_Civ BY f20_a-f20_i*.1

SCK_Civ@1;

SCK_Civ WITH SCK_Geo*.3;

SCK_Civ WITH SCK_His* .3;

SCK_His WITH SCK_Geo* .3;

**ANALYSIS:**

TYPE = general;

ESTIMATOR = WLSMV;

PARAMETERIZATION=THETA;

**MODEL:**

SCK_Geo BY f18_a-f18_g*.1

SCK_Geo@1;

SCK_His BY f19_a-f19_e*.1

SCK_His@1;

SCK_Civ BY f20_a-f20_i*.1

SCK_Civ@1;

SCK_Civ WITH SCK_Geo*.3;

SCK_Civ WITH SCK_His* .3;

SCK_His WITH SCK_Geo * .3;

**OUTPUT:**Tech9;

Actually, I am confused with the following problems:

1. Monte Carlo generates data whereas I have primary data.

2. Still I have to use Monte Carlo? should I generate data through monte Carlo first and then should I run the model?

3. Please share with me some sample syntax if anyone has.

4. Following previous studies, my purpose of using Monte Carlo is to find the indirect effect of the independent variable on the dependent variable through double mediation in the multilevel mediation model (2-1-1-2 model).

Actually, I am confused with the following problems:

1. Monte Carlo generates data whereas I have primary data.

2. Still I have you use Monte Carlo, should I generate data through monte Carlo first and then should I run the model?

3. Please share with me some sample syntax if anyone has. thanks

I initially performed an analysis with AMOS of my mediation (4 mediators), using McKinnon.

One reviewer suggested me to use Monte Carlo, and another one suggested me to use bootstrap with Mplus. I have the notion that Monte Carlo is better than bootstrap based on Preacher & Selig (2012), so I was thinking of performing a Monte Carlo analysis of the indirect effects on Mplus, but I don't know how to do it.

Anyone can help me telling me what syntax to introduce in Mplus in order to conduct the mediation and the Monte Carlo indirect effects analysis?

Yes, I am looking for free related software.

Hi everyone. I took a basic course on Markov Chains, and know a little about Monte Carlo Stimulations and Methods. But I never got to the part of spreadsheets.

If anyone can help direct me to a few non-technical, not to hard to read books on Monte Carlo Stimulations I would be grateful.

Suppose a six degree of freedom simulation of an aircraft, which some aerodynamic parameters (e.g: stability derivatives), mass configuration (e.g center of mass) and etc, are randomly choose within known bounds. From the Monte Carlo sample those simulations are split in two groups: with instability (any time during the simulation) and without instability during the flight.

My question is, How could I find the more important combination of random parameters the caused the instability in flight?

I have already done a sensitivity analysis, so I have an idea how each one influence individually. What I really one to find is how the combination of parameter is causing the instability.

I am assessing pros and cons of alternative statistical methods. I would appreciate your advice.

Thanks,

Luis Orlando Duarte

Hi there, I need expert opinion in evaluating the use of Monte Carlo method and its accuracy in predicting the permeability of rock layers in oil exploration.

Does anyone know a geotechnical engineering software which can support subset simulation? I need to do some probabilistic analysis of a geotechnical project. However, due to the small probability, I need to use subset simulation instead of the crude Monte Carlo analysis.

When calculating a budget or a risk reserve, a simulation or estimation is performed.

Sometimes the Monte Carlo simulation is used.

It seems that each administration and each company uses different confidence percentiles when summarising the simulations in order to take a final decision.

Commonly, 70%, 75% or 80% percentiles are used. The American administration uses 60% for civil works projects...

My doubt is, is there any recommendation or usual approach to choose a percentile?

Is there any standard or normalized confidence percentile to use?

I expected to find such an answer in the AACE International or International Cost Estimating and Analysis Association, but I did not.

Thank you for sharing your knowledge.

I am a beginner to probabilistic forecasting. From my research I have a vague idea that monte carlo simulation can be done for injecting uncertainity in the process. Do i need to get multiple point forecasts doing monte carlo and do postprocessing for obtaining a proabibilistic distribution?.Can any one help with the procedure what steps should i follow to do probabilistic forecasting? It would be helpful if someone can share an example

How is Hamiltonian Monte Carlo is better than Markov Chain Monte Carlo method in Bayesian computations?

I am doing research about neutron spectra measurement and interested in response function calculation. Then i want to know the theory in NRESP and NEFF. Please share your literature with me, Thank you !

I would like to conduct Monte Carlo uncertainty analysis for actual and predicted data in R;

Kindly share some effective resources;

However, I have this <<https://rdrr.io/rforge/metRology/man/uncertMC.html>> where understanding the hyperparameters of it is another challenge.

Please share your views/knowledge/ effective stuff/materials

best regard!

I started a new project and I want to simulate co2 adsorption By a molecular simulation Method.

Please recommend some books

regards

I'm doing a Montecarlo Analysis using Abaqus and Matlab.

I have written a Matlab code that is able to run the Abaqus job taken as imput the Abaqus .imp file.

I need to solve n realizations of my Abaqus model each with a different predefined field.

I can assign the predefined field from a .txt file using the Abaqus interface the command for the creation of a mapped field.

My question is if I can do this assignment of the predefined field from a .txt file using Matlab.

I have done the non linear curve fitting for the Birch-Murnaghan eos for the E vs V data that i have. Then calculated the chi squared value, minimsed it using solver but could not get the minimum values of the constants that i need( B0,V0,E0,B0

^{'}). I Wanted to know where i went wrong, the workbook of the data is attached. Any help is appreciated.Several simulation studies show that the MCNP code fails when dealing with detailed physics at nanometric level (e.g., when modeling B4C nanoparticles in neutron shielding materials).

I would like to study properties of transport of some ions, and I found out that DCV-GCMD is a good way of simulating my system. However, in previous papers, I failed to find the simulation package people where using (it might have been an in-house code, but it's not precised).

Does anyone have suggestions on that ?

Does anyone else know how to simulate a source with rectangular cross section without using beam collimation in gate monte carlo code?

Thanks & Regards

I want to simulate MCTS algorithm in MATLAB for travelling salesman problem (TSP), and was wondering if such a source code exists?

How radiative transfer equation with monte carlo technique can be started.

I run MC simulations with MCNP6, of the imaging process in CyberKnife radiosurgery system. I want to score the scattered photon fluence in a region simulating my detector that comes from a tube that produces 120kVp.

My question is how to score in a different bin the scattered fluence that comes from different cells of interest.

I wrote an MC algorithm that simulates bead-spring models and am in need of verifying the results of my code. Is there any resource in the literature that has energy expectation values (or any other metric) for MC simulation of bead-spring models that I can use for result verification?

I have 7 random variables with their distribution functions. I linked the MATLAB and Opensees program to generate a random variable in MATLAB and get the structure response in Opensees. To obtain an explicit function between the variables and the structure response, using the cftool in MATLAB, only two variables can be entered.

while I have 7 random variables.Now, who can help me to get a Polynomial function by using the response surface method to perform Monte Carlo analysis.

Would be grateful so much for a link.

I found some single publications, but topic is quite new for me, so I wanna find some book or big review paper.

Focus should be given on how to correctly model that, so I am eager to look at publications of the end of previous (some classical ones) and of current century.

The interest is also in simulation modelling using Monte Carlo algorythms.

Thank you for attention and possible support.

There is t-depl as a 2D depletion measurement, and t-6depl which is a Monte Carlo KENO . va code, but I am looking to calculate the depletion process that like the t-depl, but in t-depl there is no geometry description like KENO Va

How it is possible to link between them

Best regards

Dear fellow researchers

I would like to run an

**a-posteriori Monte Carlo**study to determine the necessary sample size for my SEM in**Mplus**with categorical/ordinal data but I cannot wrap my head around the systax I need.I have 13 latent factors with 5 indicators (on average) and a total sample size of n = 450.

Any help is greatly appreciated.

Please note that

**I cannot use R**.Many thanks

Marcel

Using ray tracing software to model a luminescent solar concentrator.

We want to study neutron contamination in radiotherapy. Is the GATE monte carlo code capable of tracking the neutron particle separately and measuring the dose deposited by this particular particle? If yes, may you provide some brief information about this?

thanks in advance to your attention or maybe your help.

I would like to simulate energy deposition as a result of the stopping of high energy particles in a dense plasma. For example the energy deposited when 10MeV protons are stopped in a hydrogen plasma of density 300g/cc. I think combining a Particle in Cell code with a monte carlo code would give the appropriate physics. However I have not found a code available to do this kind of simulation. Does anyone know of any appropriate simulation tools for this problem?

Number of environmental variable=5

Species abundance in each sites is used as dependent variables.

Thank you

- In principle, a system perturbation can be taken into account by mean estimated difference, between the Value computed in two independent calculation, one with a nominal system rather the second with the perturbed system.
- Small perturbations, practically, for small perturbations, the computation time necessary to obtain a statistical uncertainty on the difference of these values that is sufficiently low is prohibitive. Also number of perturbations required is often huge, therefore it is difficult to resort to independent calculation.
- Which method can be sufficient to calculate the perturbation dependently (between the two system mentioned before)?!

I want to carry out Monte Carlo simulations by varying certain parameters in an equation. I have to use Monte Carlo simulation as I have understood from literature survey. Can anyone please let me know which softwares have this provision?

I have tested the performance of 9 strategies of asset allocation through a Monte Carlo simulation and I have calculated for each of them 10 risk/return metrics: average annualized return, standard deviation, skewness, kurtosis, downside deviation, Sharpe ratio, Sortino ratio, Value at Risk, Information ratio (with a Buy-and-hold strategy serving as a benchmark) and Total return (5-year investment horizon). The study in its base case is a replication of the work of Cesari and Cremonini (2003), please see link below. So how can I test if the differences in the performance of the 9 strategies (according to the above-mentioned 10 risk metrics) are statistically significant?

Any help would be highly appreciated.

Best regards,

Kaloyan Kazakov

I guess we need the optical part of GATE. But how do I modify / set the physics to simulate this effect (because geant4 seems to have it already)?

I am hoping to do a Monte Carlo in my Life Cycle Assessment. One parameter I need more data on is the regeneration efficiency for ion exchange (how much of a regenerant chemical I need to put in to get out what the ion exchange is capturing), and was hoping to find more data. I am looking for data specifically on a macroporous weak acid cation exchange resin. Does anyone have information on data sources to look at, or even better, if there is another source that has already determined the distribution?

Knowing the kVp and mAs for an x-ray machine, I need to model it as a source in my Monte Carlo input model. I know how to use these inputs to calculate the average energy of the spectrum, but hope someone can help me determine a) how I can calculate the exact spectrum (which parameters would I even use for this?) and b) how to model this in MCNP5?

I have a attached a screenshot of the guide I am using. This function seems ideal but the explanation is too brief for me to understand what inputs it takes.

In MCTS I have searched and found that the mcts itself has not very succesful results but when we combine it with deep reinforcement learning we get perfect results like Google have done in Alpha Go Zero. My question is how to combine mcts with deep reinforcement learning like Alpha Go Zero?

Hello, I am trying to determine how to run a power analysis for a MANCOVA. I typically use G*Power. I did not see MANCOVA option in that program. Any direction/guidance on running a power analysis in SAS, R, or SPSS would be helpful. I do not have a background in bootstrapping or Monte Carlo but I heard that may be a option but I am not sure on the code.

- How effectively are Monte-Carlo methodology and Grid-Computing technology used in Finance for Corporate Performance Measurement?

- How extensively are these used in different business sectors/industries for Corporate Performance purposes?

- In terms of costs and benefits, how can the trade-off between short-term and long-term of operating Monte-Carlo and Grid-Computing be evaluated?

- Grid Computing and Cloud Computing are not the same, although they are mostly used synonymously in all-day life. Grind Computing has the ambitious vision to "connect and share" heterogeneous hardware for specific high-performance computing (e.g. running complex and resource-intensive calculations with distributed CPUs, RAMs, etc.), while Cloud Computing is till now mostly focused on services used as an interconnection of storage space and telecommunication: http://en.wikipedia.org/wiki/Grid_computing.

- There are several scientific Grid Computing platforms, like e.g. BOINC; but for the Finance world this seems to be quite in an initial phase ...

what are other alternative methods to Monte Carlo Sampling?

Hi, I've carried out Canonical Correspondence Analysis to test the correlation of microhabitat variables with herpetofauna species abundance. May I know how do I test the significance of the result? I wanted to try Monte Carlo analysis but I can't find a guide on how to do it. Please help! Thanks in advance.

I want to perform a Monte Carlo simulation in Crystal Ball application, by running the inputs in a matlab script and getting outputs from it to be pasted in forecast analysis cells in crystal ball.

I have data for one year and would like to create a model based on mean wind speed of the wind at a given region and standard deviation.However I am confused where to start anyone with a vivid information on how to go about it IN MATLAB.

Hi all,

I'm trying to simulate the photon decay spectrum of Eu155 in Geant4. I'm not using the decay file provided by Geant4 because the energies and intensities listed are incorrect. I've changed/added values to match trusted literature, ensuring that the syntax is the same and the intensity column sums to 100.

The resulting spectra however is not right. There are too few photons per decay for most energies. I'm confident I'm collecting all the photons. I've attached my decay file and the resulting plot. The picture also has a 2nd plot of what the spectra should approximately look like for comparison.

I want to know what the intensity column is actually doing and how to adjust it such that the photons per decay match the values I've placed in the intensity column (noting that it's as a percentage there).

Any help is greatly appreciated

Thanks,

- Giuseppe

Is there any program or code which employ Monte Carlo simulation to generate the initial adsorption configurations? I know Materials Studio Adsorption Locator can do this, but I do not have Materials Studio, also it is not suitable for my case because I have over hundreds molecules. Can anyone suggest a program or python code to do this? Or a tutorial about how to execute it by python is also welcome.

This one we have been stumped on for the entire day
We're getting "

*fatal error. detector no. 1 of tally 5 is not in any cell.",*What could be causing this? In the manual and all examples we've seen, nobody has parameters specifying cell location for the tally. It is a very simple problem, 3 concentric layered cylinders on the Z axis, with a point Cf-252 source in the center, and a ring detector 1cm outside the outer surface. Below is our simple input file if needed1- c MCNP TEST
2- c CELL CARDS
3- 1 1 -0.96 -100 -400 500 IMP:N=1.0 $ For radius 0-10 (under plane 400, above plane 500)
4- 2 2 -11.34 100 -200 -400 500 IMP:N=1.0 $ For radius 10-20
5- 3 1 -0.96 200 -300 -400 500 IMP:N=1.0 $ For radius 20-95
6- 4 0 600 IMP:N=0 $ Terminate outside of kill-sphere
7-
8- c SURFACE CARDS
9- 100 CZ 10
10- 200 CZ 20
11- 300 CZ 95
12- 400 PZ 500 $
13- 500 PZ -500 $Two planes to cut infinitely tall cylinders
14- 600 SO 700 $Kill sphere around entire problem
15-
16- c DATA CARDS
17- MODE N
18- TOTNU
19- NPS 10000
20- SDEF POS=0 0 0 CEL=1 PAR=1 ERG=D1
21- SP1 -3 1.18000 1.03419
22- c MATERIAL SPECIFICATION
23- M1 NLIB=60c $ pOLYETHEYLENE CH2
24- 1001 2.0 $ Hydrogen
25- 6000 1.0 $ Carbon
26- M2 NLIB=60c $ Lead
27- 82207 1.0
28- c TALLY SPECIFICATIONS
29- F5Z:N 0 96 0
30- E5 1 18
31- DF5 IU=1 IC=10 FAC=6.44e7
--------------------------------------------------------------------------------------------------

And a snip of the output file where the error is looks like this:
28- c TALLY SPECIFICATIONS
29- F5Z:N 0 96 0
30- E5 1 18
31- DF5 IU=1 IC=10 FAC=6.44e7

fatal error. detector no. 1 of tally 5 is not in any cell.

ring detector specifications
detector a0 r axis r0
1 0.00000E+00 9.60000E+01 z 0.00000E+00

We are investigating preferential associations and more precisely whether some pairs of individuals interact more with each other in different behavioural contexts. The interaction dataset does not contain binary data, which then does not allow us to use Monte Carlo test. We are now trying to find an alternative solution, and are thinking of adapting/modifying MC test in order to use the non binary data.

To all those statisticians out there! I'm trying to compare between differential expression of 41 proteins found within organisms (same species) from 5 sites. Each site contains 5 samples. The software I'm working with is PRIMER V.6. Since the transformed protein values I have are analog to abundance of various taxa, I chose to go with the Bray-Curtis similarity matrix. Next I looked at the MDS with the sites as the factor. There were several noticeable differences between sites. PERMANOVA (pairwise bw sites) was my the next step in which I got significant differences between various pairs of sites. Since the number of samples is rather small (5) and only 126 unique permutaions, I also tested with the Monte Carlo, which pointed out that one marginal P-value, which was significant in PERMANOVA, was not significant in the Monte Carlo test. Next I used pairwise PERMDISP to check for dispersion effect. Another analysis I did was the ANOSIM, in order to see the strength of the differences (dissimilarities) between pairs. R statistic range between 0.3 to 1. SIMPER was used to see what proteins contributed most to the observed differences between sites. Here comes one thing (of many) that I'm not sure about: P(perm) of the PERMDISP is 0.011 (global?), but I'm looking at the pairwise tests, where some are significant and some are not. In this case, does it matter that the global p value is <0.05?

Any comments on this procedure would be highly appreciated.

Cheers, Zafrir.

I have read in the literature that secondary electrons (SEs) only escape from the top few nanometres (<10nm) of a sample under SEM. If this is the case, why am I able to see the microstructure of my sample even when I have a 20 nm carbon layer on top? How can the SEs escape from the sample surface and then through the carbon layer?

I want to simulate a hysteresis loop using monte carlo simulation in any program, it can be Matlab, Maple or C ++, which routine should I implement?

I would like to begin studying the adsorption of liquid mixtures (aqueous medium in a first moment) using Monte Carlo simulations on Grand Canonical ensemble.

what are the analytical methods (not simulations like Monte Carlo )for sampling load and generation probability distributions which can be applied to a small scale power system?