Science method

# Monte Carlo Simulation - Science method

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

Questions related to Monte Carlo Simulation

While performing a Monte Carlo simulation I get some "jumps" in the skewness and kurtosis as shown in the picture.

How can you explain this odd behavior and non convergence of the beforementioned moments?

Any advice would do wonders.

Best regards

Edit:

Since the equation I was modelling was hard to analyze for errors or discontinuities, I simulated the random variables of the equation as with random numbers of their corresponding distribution. And, the same thing happened when I simulated a GEV variable and a Lognormal variables (as shown in the attachments)

# Simulations means how many simulations of the same variable are performed using Monte Carlo raw sampling.

I wanna simulate data for an observed continuous variable. The values are supposed range between 10 and 20, with mean of 16 and variance of 2.

I would appreciate if anyone could help me with this.

Thanks!

Hello.

I have some questions about

**CASINO version 3.3.0.4.****Q1**. I know that when the electron beam escapes the sample, the scattering stops and the trajectory ends. However, when I ran the simulation, electrons that escaped the specimen were scattering in the vacuum.

(1st. figure: simulatio by me / 2nd figure: reference )

How do I set up the simulation in order for the electrons exiting the specimen to be emitted in a straight line?

**Q2**. I use a specimen with an area of 100 um X 100 um X 50 nm. However, when I run this sample, I get BSE yield and SE yield of 0.

If the area of this sample is set to 100 nm X 100 nm X 50 nm, the yield is not zero.

Why is the yield different depending on the sample dimension, and why is the yield 0?

**Q3**. What are the criteria for BSE yield and SE yield?

Are you counting the electrons that escaped the sample?

**Q4**. I use samples with multiple layers. Does the beam interacting with the sample scatter again in the process of emission?

**Q5**. How does plasmon energy affect the generation of SE?

**Q6**. Does SE calculated by CASINO include SE2(generated by BSE)?

thanks for all.

I want to determine the temperature dependancy of order to disorder phase transition of cubic perovskite? And I haven’t enough computational resource for that..So, Python or Matlab can be a good option in this case

Hello everyone, I'm modelling some metallic atoms over a carbon surface. I want to try the UFF published by Rappe et al. However I was checking the VdW potential and they have an uncommon definition of the Lennard Jones potential (paper's formula attached as a picture) Can someone help me to understand why it is so and if these parameters are somehow transferable to the typical definition of the LJ potential.

Many thanks

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

I would like to run a Monte Carlo Simulation for stocks. Since stock returns are not normally distributed I am wondering, what is the best distribution function?

What about Weilbull, Frechet, Gumbel, Rossi etc.?

My biggest concern is, to incorporate the difference between median and mean. My Data is:

Mean: 10,67%
Median: 14,77 %
Standarddeviation: 17,41%

Can we use Monte-Carlo simulations to understand the practical impact of process variation on Ambit-AND-OR (which requires triple-row activation) in all the components in the subarray (cell capacitance, transistor length/width/resistance, bitline / wordline capacitance and resistance, and voltage levels). ?

Hello everyone,

I am trying to run a Monte Carlo simulation to estimate the delivered dose of alpha-particles from Ra-223 decay to cancer cells. My system is simple. Just cells and Ra-223 media. Do you have any recommendations?

Thank you.

Best regards,

Mehran

Actually, I did not any idea about the Monte Carlo simulation. I would like to add the Monte Carlo simulation to my adsorption study. How can I learn Monte Carlo simulation? Which program should I use? Thanks in advance.

Good day,

I have a need for carrying out monte-carlo simulation to model the health risk due to heavy metals in groundwater.

I need help figuring it out using Oracle crystal ball.

I also appreciate if you also have an excel template which i can use.

Looking forward to your responses.

Thank you and GOD bless.

To see complete details, please find the attached file. Thanks.

There are several methods to check the statistical significance of an absorption feature in the X-ray spectrum of X-ray pulsar. I am looking for the Monte Carlo simulation method. It would be helpful to discuss the detailed method to use this type of simulation. I also looking for more applications of these simulations. Thanks.

I need some guidance regarding CRLB to compute numerically, and to estimate Doppler frequency, for a synthetic signal, given below.

**X = A*sinc(B*(t-𝜏).*exp(j*2*pi*F*(t-𝜏); whereas θ = [ F, A, 𝜏 ]**

**"A"**is complex and has amplitude and phase. "

**F**" is doppler and "

**𝜏**" is azimuth shift

Hello to All,

Any suggests in writing LAMMPS input file of pcff forcefield? I couldn't find one in the lammps manual, especially for the pair_style and pair_coeff part.

Thanks in advance.

I have around 1000 images from Micro-CT and from those I want to know the angle made by the non-spherical particles with the column's central axis. I have been able to stack the images in Image J but further, I do not have any clue how to analyze the stack and the angle of the particles.

The other way I have seen to find the orientation is by doing the Markov Monte Carlo simulation on which I am totally clueless about how to proceed.

It will be great if someone can help me using the above either method to calculate the orientation of the particles with the bed's central axis in a packed bed.

I am attaching one such figure from which I want to calculate the orientation and the one stacked volume image from the Micro-CT and also the Complete procedure of Markov Monte Carlo simulation.

How to calculate mean square angular displacement ? Do we need any periodic boundary conditions if at each step angle is updated using theta(t+dt) = theta(t) + eta(t) , where eta(t) is a gaussian noise . Please describe the procedure to calculate this quantity.

How can I provide Monte-Carlo simulation for power calcilaton of the second order cfa in mplus (40 observed categorial variables, 20 first order latent variables and 5 second order latent variables).

MATLAB Monte Carlo simulation is very common and important for UWOC. How did you realize the Matlab Monte Carlo simulation of underwater wireless optical communication? Source code sharing?

I would like to use a Monte Carlo simulation to calculate base rates of abnormally low scores in cognitive testing. While this has been shown to be possible using the intercorrelations between the tests (Crawford et al., 2007) more recent research has indicated that factors such as IQ and years of education exert a significant influence base rate estimates (e.g. Karr et al., 2017). Is it possible to run Monte Carlo simulations while also adjusting for covariates of these types?

I am working on probabilistic human health risks on dumpsite pollution in developing countries. Is there anyone who has an example of an excel file of the Monte Carlo simulation? Any paper that detailed about this issue?

Thank you very much.

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;

My lab needs to determine a more robust method of determining uncertainty of our gas analysis using a monte carlo simulation which is determined annually . We sample a QC cylinder of known gas concentration before and after every batch of samples. If i assume a normal distribution of the gas analysis, can i simply enter the mean and standard deviation of all the QC results for the respective gas component for the year and then run a simulation off this and calculate the uncertainty? If i assume a rectangular distribution, can i simply use the lowest and highest QC result for the respective component and use these as my highest and lowest bounds, run the simulation and calculate the uncertainty of this? Any guidance or help would be greatly appreciated. Thank you Lachlan

I want to carry out particle in cell simulation for Electron Cyclotron Resonance (ECR) plasma for the in-house developed reactor at our laboratory. Kindly share any freely available PIC code with instruction guidelines so that I could do the simulation. I am using windows platform. I don't have any information on how to do the simulation. So if there is any tutorial, also share that. Can it be done by MATLAB coding also?

Looking forward for your guidance.

In the attached file, the Persian Curve is proposed as a certain alternative for the famous Monte Carlo Simulation, MCS. The proposal is a revolution in all areas with application of the MCS.

Do you have any logical reason to oppose the proposal?

If Not, your recommendation, approval and presenting case studies is a great service to human knowledge and academic society.

Dear Colleagues ... Greetings

I would like to compare some robust regression methods based on the bootstrap technique. the comparison will be by using Monte-Carlo simulation (the regression coefficients are known) so, I wonder how can I bootstrap the determination coefficient and MSE.

Thanks in advance

Huda

I am using the HOOMD-blue package, and I was advised to use force-shifted Leanard Jones potential, with a tree neighbor list. I do not know which parameters I should write for those charged molecules (hard spheres) "'N, charge'" The system would also have some counterions, and they have an impact on the system.

**class****hoomd.md.pair.ForceShiftedLJ(**

**nlist****,**

**r_cut=None****,**

**r_on=0.0****,**

**mode='none'****)**

**nlist = hoomd.md.nlist.tree(**

**r_buff=0.4, check_period=1, d_max=None, dist_check=True, name=None)**

Thanks in advance!

Hello All,

Please is it possible to use MATLAB in analysing the sharing and compatibility studies between Satellite Communication systems and 5G systems using the Monte Carlo Simulation approach rather than the Minimum Coupling Loss approach?

OR the Monte Carlo Simulation approach in analysing sharing & compatibility studies is only implemented using Spectrum Engineering software (e.g. SEAMCAT) other than MATLAB?

I am studying free space optical recently, but I don’t know how to generate Málaga fading to Monte-Carlo simulation. Who can help me?

I am looking for some quality materials for learning the molecular dynamics theory and the use of LAMMPS. Besides the LAMMPS manual from Sandia National Laboratory, which sources can I use for learning LAMMPS?

Simple geometry was made having concentric cylinders bounded by a square region. The geometry has a reflective boundary. The source was defined at one point in the boundary and when it had been run for criticality calculation, it resulted in an error messaging "the entire source was rejected". I tried to do the simulation by placing the source closer but it still results in an error. Any help will be appreciated.

Hi, i am conducting a Monte Carlo simulation for my new distribution but the MSE values are increasing while the sample size increase, does any experience this issue before and what should i do to fix it? thank u

Dear community,

I want to define a geometry in MCNP with several levels of universes and fills, say:

c cells

10 100 -1 -1 u=1

11 0 1 u=1

c

30 0 -2 fill=1 u=2

31 0 2 u=2

c

40 0 -3 fill=2

41 0 3

Universe 1 consists of cells 10 and 11 and fills cell 30. Cells 30 and 31 make up universe 2 and fill cell 40. (I have not tested the above piece of code for errors but I hope you got the idea.)

Now I want to define an identical geometry where the material in cell 10 is changed from 100 to 200. Is there a way to do this?

"20 like 10 but mat=200 u=3" is possible, of course. However, then the entire remaining code must be copied (with adapted cell and universe numbers) in order to make up new universes. Is there something like "50 like 40 but ***mat of cell 10 within cell 30 within cell 40***=200"?

An alternative solution could be to define the material of 10 as a distribution depending on which higher-level cell cell 10 will be in (like mat=Fcel D1; SI1 L 50 40; SP1 100 200). But I do not see a way to access the cell numbers of higher level either.

I am making a simulation of energy deposited of some radioactive sources in scintillation detector. I have some results, but I don't have the same distribution energy between experimental spectra and simulated spectra. I do not know why.

For instance, the spectra of Cs-137 is shown. However, it does not have the same resolution.

Someone who can help me how to improve the simulation.

The scintillation detector is of NaI:Tl.

Hello,

My area of research is to valuate Exchange option (Margrabe option). I am looking for Monte Carlo simulation technique that can be applied to some real trading data. I have evaluated them using Liu process and wish to compare my results with simulation. In excel I prepare basic model based on Margrabe formula, but results deviate. Thanks in advance.

I am working on molecular simulation of adsorption and I want to design a new molecular simulator software by C++.

The input of this software is some text file. I want to get initial position of each atom in Cartesian coordinate in a text file.

So I want to make this initial position data.

Can I make a structure in Material Studio 2017 and convert/export or extract this data to a text file?

In general and special for energy materials applications.

I want to develop a Markov switching model for "demographic transitions" (discrete time and discrete state) using the estimates (hazard rates or transition rates) from a continuous-time hazard model. The only data I have, is the estimated hazard rates for various age groups e.g. transition rate of marriage for age group 20 to 25 is 0.93, which means the model assumes piecewise linear form of baseline hazard model.

The transition rates have been estimated using following model;

log-hazard rate = log(baselinehazard) + covariate effects

or hazard rate = (baseline hazard)*Exp(covariates)

The first step for developing the Markov switching model is to know the transition probabilities. I have seen in literature that transition probabilities can be calculated using monte carlo simulations. So I will first project the life profiles of a synthetic population and then would randomly let them make transitions. for example, for a single person if there are two possible states in the next period marriage and death with some probability "p", then I generate random numbers and compare them with 'p' and if 'p' is higher than random draw then the individual make the transition otherwise he remains single. (I assume here that 'p' is the transition rate). once simulations are done, i will determine the "transition probabilities", which is the aim of performing this step.

when I run these monte carlo simulations, I also need to keep the track of "durations" like how longer the person remained divorced or married? Now my questions are as follows:

1) Is it appropriate to consider transitions rate as 'p' in the simulations?

2) I am running the simulations on MATLAB, and I do not know how can I keep the track of duration or event history of simulated population.

3) If someone is working in this area, I would be happy to talk in detail about it.

Thank you!

Hey!

I am a psychology student working on a small project for one of my seminars. The goal is to present to fellow students how different sample sizes affect different ways of assessing measurement invariance (Chi-square or Alternate Fit Indices).

Additionally, I would like to show them an example of how to do your own Monte Carlo simulation. Someone could theoretically go the extra mile and estimate sample size for the specific experiment they might plan.

However, we all only use R-studio, and we don´t have access to programs like MPlus. Sadly, I am not advanced enough to write some code for this. Therefore, I am looking for researchers who did a Monte Carlo simulation to assess measurement invariance in R-Studio. That way, I could ask for the code they used and hopefully learn something along the way.

I am grateful for any cue and comment. Thank you very much!

Hello,

I am a newbie in geant4. I'm learning it playing with example. Sometimes, when I go to simulate an example code, it doesn't create an executable file (the green one in my ubuntu terminal). Why does it happen? There is no error while building the file.

Please help.

File lists from terminal,

**there is no executable file.****anamika@anamika-Inspiron-3421:~/Cyclotron/g4work/B5$ ls**

**CMakeCache.txt cmake_install.cmake exampleB5.cc exampleB5.out gui.mac icons.mac init.mac Makefile run1.mac run.png vis.mac**

**CMakeFiles CMakeLists.txt exampleB5.in GNUmakefile History include init_vis.mac README run2.mac src**

**anamika@anamika-Inspiron-3421:~/Cyclotron/g4work/B5$**

For a Monte Carlo simulation involving photon counting detectors, I am running into the problem of creating random numbers that have a given expectation and a given correlation matrix. Due to the statistics of the detector (double counting), the diagonal elements can be larger than 1 so that the statistics is not exactly Poisson. The off-diagonals of the correlation are positive.

Has anyone come across a similar problem?

I created a new test for uniformity, but so far, I've had no luck finding its critical values analytically, I could only obtain them by Monte Carlo simulation. What's worse is that histograms show that the null distribution does not approach normal distribution even at large n, so I cannot approximate it with mean and standard deviation.Is there any sort of "standard procedure" for deriving null distribution of a test statistic? Or at least approximating it with an analytical expression?

I'm currently working on a project where I deal with a protein of size ~50K atoms. I want to do a computer simulation with the protein using Monte Carlo instead of MD, and looking for any software that can do that.

I have so far tried Cassandra and GOMC but both didn't work out well since my system was too big compared to the system size both software targeted to.

Does anyone have an experience in MC software and know which software is suitable to do the simulation with the above size protein?

Thank you!

Hello All,

I am very new to this. I am tasked with simulating clinical data that is large in volume and spans over a period of time. I will have some data provided to start with but what would be the best approach/method/tool/software to do this. I was told monte carlo simulation is too random for the data. Need a more structured approach.

Any feedback would be greatly appreciated.

Thank you.

-Sachin

Variance reduction methods are used in Monte Carlo simulation in order to reduce the simulation time. I would appreciate it if anyone suggests the drawbacks of this method.

Regards,

Hi

I am trying to do a multivariate meta-analysis MC simulation in r and I want to control for the sample sizes (studies sample sizes), Within-study correlation, and between-study correlation.

I am using mvmeta and the main problem is where to plug in the between study-correlation!

Any ideas?

I have below model:

X = A*B

Where A = a list of values with Lognormal distribution (size = 13)

and B = another list of values with Lognormal distribution (size = 13)

How can I perform 1st order, 2nd order and total Sobol sensitivity analysis of this model in R programming?

Please help me with the steps.

Application of Monte-Carlo-Simulation in Structural Reliability, risk analysis or other complicated modeling.

In our current design of linear binary current steering low-noise CMOS slowDAC, we converged in the use of

**long channel NMOS transistors**. Indeed, a low noise, lower than 10pA/√Hz at 100µA, and**good matching of the weights of the binary DAC**leads to the use of long channel NMOS transistor in the design of**binary coded current mirrors**.It seems better to increase L than W to improve the current mirror matching looking at Monte Carlo Simulations.

**NMOS sized with L as long as 20 µm for a W of 8 µm is considered**. Assuming that such long channel NMOS transistors are unusual (?) in VLSI design ... have you experienced the use of long-channel transistors in VLSI DAC design? Any papers, or review about the use, and justifications, of long channel MOS transistors for ASIC design?

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

In solving an optimisation problem with uncertain input parameters, we are using Monte Carlo simulation (MCS) and scenario reduction to arrive at a number of scenarios with their associated probabilities. Optimisation algorithm outputs decision variables for different scenarios. For example, the power of a generator at different scenarios; Assume that in a generation scheduling problem with Ng generators, at scenario 1 with probability 0.3 power of generator 1 is 12, at scenario 2 with probability 0.2 power of generator 1 is 17 and at scenario 3 with probability 0.5 power of generator 1 is 9. Then in practice, how the decision maker must set the power of this generator?

Hi everyone,

I currently use MCS method to analyze effect of some uncertain parameters on electrical power system and run 10,000 simulations to calculate the output which approximately takes around 1 hour.

I recently read some methods which can reduce the MCS scenarios thus, resulting in low computational time.

So, can our fellow researchers elaborate more on this topic or suggest me any other techniques which has the potential to significantly reduce the computational time of MCS (say around 5 minutes for my work) with reasonable accuracy?

Cheers

Sam

Reliability researchers often consider the result of the crude Monte Carlo simulation as an accurate solution for a reliability problem. However, is this approach really a general accurate reliability method?

Regardless of problems with the small probabilities, can anyone present a reliability problem that crude Monte Carlo simulation is not able to solve it?

Dear All,

I want to calculate the proton primary dose and yield in water for 250 Mev proton beam using Fluka Mc Code but I couldn't. I think it's because detector data entered incorrectly.

So what should I do in this situation?

best regards.

NB1: I'm a beginner user

NB2: attached you will find the corresponding input and output files

Dear researchers,

According to the central limit theorem for a large number of random samples as X1, X2, ..., Xn, with expected value mu and standard deviation sigma, the following confidence interval is defined:

[mu - Z*sigma/sqrt(n), mu + Z*sigma/sqrt(n)]

As it can be seen in the interval above, as the number of samples n, increases the interval becomes narrower, and as a result so many samples stay out of the confidence interval, which is not good for our prediction of the problem. I have a question that put it in the following forms:

What is the main definition of a confidence interval? Is it a confidence interval for the average of Xi or Xi itself? In other words, should all Xi(s) lie within the interval with the probability of say 95%? or this is not necessary?

I have already attached a MATLAB code for randn function, one can see that as n increases the CI becomes narrower and so many Xi(s) stay out of the CI, however, for lower value of n, the results seem logical.

thanks for your responses.

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.

Hello I am new to molecular dynamics simulations. I am trying to calculate the chemical potential for iron and phosphorus to do some grand canonical monte carlo simulations. Please help me. Thank you very much in advance.

Fortran code of kinetic monte carlo simulation for study hetero epitaxiale deposition

I want to use a rssa file in a MCNPX code several time , my rssa file scored 1e6 history and i want to use it 8 times(8×1e6) to reach valid variance .

When i ran that , just 1 time it used.

How can i use that 8 times ?

I have the topology file for a polymer, i.e. I know all the bonded and non-bonded interaction parameters, but I am unaware of the well-accepted methodology to generate the initial structure. I can think of three methods, to perform this but I am not sure which is the best, or if there are better methods out there.

Method 1: I generate a random initial structure and I do an energy minimization in vacuum (the polymer will shrink in size) and then energy minimization in water (the polymer will grow in size). (I may get stuck in local minima)

Method 2: Use Method 1, then perform Monte-Carlo simulations to find global minima.

Method 3: Use Method 1, then increase the temperature and the reduce to temperature so that I can sample the global minima.

What algorithms does a software like Schrodinger use to find the 3-d structure of the molecule from the chemical formula?

My intention is to develop a python script to do the same work that Schrodinger does, but I can't seem to find a book/paper to do which discusses the available algorithms.

PS: I use GROMACS simulation package.

When dealing with an uncertainty characterization problem, we do not know what the true value of an uncertain variable is. So, how can we evaluate which method (e.g. Monte Carlo simulation, Chance-constrained programming, etc.) could better estimate the true value of an uncertain variable?

Matlab codes for Kinetic monte carlo simulation

What is Monte Carlo simulation and how it is useful for condensed matter research?

I presently use Materials studios for MD simulations involving MOFs and nearly all output results from from Geometry optimization to Energy calculation have this query: "Energy contributors with missing parameters" What does it mean? Does it signify that there's a problem in the simulation or what?

I'm a very much beginner in using RASPA. I want to simulate a crystal phase, for which I have .xyz file. Can RASPA read .xyz files?