text:
Cairns, Australia
Average sea temperature
January, like December, in Cairns, Australia, is another warm summer month, with average temperature varying between 29.3°C (84.7°F) and 24.3°C (75.7°F). In January, the average high-temperature is practically the same as in December - a still moderately hot 29.3°C (84.7°F). Weather in January »
The last month of the summer, February, is another warm month in Cairns, Australia, with average temperature varying between 29.4°C (84.9°F) and 24.3°C (75.7°F). With an average high-temperature of 29.4°C (84.9°F) and an average low-temperature of 24.3°C (75.7°F), February is the warmest month. The average heat index is appraised at a torrid 35.6°C (96.1°F). Weather in February »
The first month of the autumn, March, is still a warm month in Cairns, Australia, with average temperature varying between 23.7°C (74.7°F) and 28.3°C (82.9°F). In March, the average high-temperature is essentially the same as in February - a still warm 28.3°C (82.9°F). Weather in March »
April, the same as March, is another warm autumn month in Cairns, Australia, with average temperature ranging between min 22.3°C (72.1°F) and max 27°C (80.6°F). In Cairns, the average high-temperature in April is almost the same as in March - a still warm 27°C (80.6°F). Weather in April »
May, the last month of the autumn, in Cairns, is also a moderately hot month, with average temperature ranging between max 24.9°C (76.8°F) and min 20.7°C (69.3°F). In Cairns, the average high-temperature in May is almost the same as in April - a still warm 24.9°C (76.8°F). Weather in May »
June, the first month of the winter, in Cairns, is also a moderately hot month, with average temperature fluctuating between 23.7°C (74.7°F) and 18.9°C (66°F). In Cairns, the average high-temperature in June is practically the same as in May - a still moderately hot 23.7°C (74.7°F). Weather in June »
July, the same as June, is another warm winter month in Cairns, Australia, with average temperature varying between 18.3°C (64.9°F) and 23.2°C (73.8°F). With an average high-temperature of 23.2°C (73.8°F) and an average low-temperature of 18.3°C (64.9°F), July is the coldest month. Weather in July »
The last month of the winter, August, is another warm month in Cairns, Australia, with average temperature varying between 18°C (64.4°F) and 24°C (75.2°F). In Cairns, the average high-temperature in August is almost the same as in July - a still warm 24°C (75.2°F). Weather in August »
The first month of the spring, September, is still a warm month in Cairns, Australia, with average temperature fluctuating between 25.8°C (78.4°F) and 19.5°C (67.1°F). In September, the average high-temperature is practically the same as in August - a still warm 25.8°C (78.4°F). Weather in September »
October, like September, in Cairns, Australia, is a moderately hot spring month, with average temperature fluctuating between 27.3°C (81.1°F) and 21.1°C (70°F). In Cairns, the average high-temperature in October is practically the same as in September - a still moderately hot 27.3°C (81.1°F). Weather in October »
November, the last month of the spring, in Cairns, is another warm month, with average temperature ranging between min 22.4°C (72.3°F) and max 28.5°C (83.3°F). In November, the average high-temperature is essentially the same as in October - a still moderately hot 28.5°C (83.3°F). Weather in November »
December, the first month of the summer, in Cairns, is still a warm month, with average temperature fluctuating between 23.5°C (74.3°F) and 29.2°C (84.6°F). In Cairns, Australia, the average high-temperature is practically the same as in November - a still moderately hot 29.2°C (84.6°F). Weather in December »
How much does it rain in Cairns?
Throughout the year, there are 167.3 rainfall days, and 652mm (25.67") of precipitation is accumulated.
What is the wettest month in Cairns?
January is the month with the most rainfall in Cairns, Australia. Rain falls for 22.4 days and accumulates 162mm (6.38") of precipitation.
What month is the sea warmest in Cairns?
With an average sea temperature of 29.5°C (85.1°F), January is the month with the warmest seawater.
When is the highest UV index in Cairns?
Months with the highest UV index in Cairns are January, February and November, with an average maximum UV index of 7.
What is the warmest month in Cairns?
With an average high-temperature of 29.4°C (84.9°F) and an average low-temperature of 24.3°C (75.7°F), February is the warmest month in Cairns, Australia.
What is the most humid month in Cairns?
March is the most humid month, with an average relative humidity of 81%.
What is the month with the shortest days in Cairns?
June has the shortest days of the year, with an average of 11.1h of daylight.
What is the month with the least sunshine in Cairns?
With an average of 5.9h of sunshine, June has the least sunshine of the year in Cairns.
What is the coldest month in Cairns?
July is the coldest month in Cairns, with an average high-temperature of 23.2°C (73.8°F) and an average low-temperature of 18.3°C (64.9°F).
What month is the sea coldest in Cairns?
July is the month with the coldest seawater in Cairns, with an average sea temperature of 23.8°C (74.8°F).
What is the month with the lowest UV index in Cairns?
With an average maximum UV index of 5, July is the month with the lowest UV index.
What is the least humid month in Cairns?
Months with the lowest humidity in Cairns are September and October, with an average relative humidity of 74%.
What is the driest month in Cairns?
The month with the least rainfall in Cairns, Australia, is September when the rain falls for 7.2 days and typically collects 9mm (0.35") of precipitation.
What is the month with the most sunshine in Cairns?
October and November, with an average of 10.8h of sunshine, are months with the most sunshine in Cairns.
When are the longest days in Cairns?
The month with the longest days in Cairns, Australia, is December, with an average of 13.1h of daylight.
The warmest month (with the highest average high temperature) is February (29.4°C).
The month with the lowest average high temperature is July (23.2°C).
Months with the highest average low temperature are January and February (24.3°C).
The coldest month (with the lowest average low temperature) is August (18°C).
The month with the highest atmospheric pressure is July (1016.8mbar).
The month with the lowest atmospheric pressure is January (1007.6mbar).
11.7km/h
The windiest month (with the highest average wind speed) is May (17.2km/h).
The calmest month (with the lowest average wind speed) is February (11.2km/h).
The month with the highest relative humidity is March (81%).
Months with the lowest relative humidity are September and October (74%).
The wettest month (with the highest rainfall) is January (162mm).
The driest month (with the least rainfall) is September (9mm).
The month with the least rainy days is September (7.2 days).
Average sea temperature in January:
Average sea temperature in February:
Average sea temperature in March:
Average sea temperature in April:
Average sea temperature in May:
Average sea temperature in June:
Average sea temperature in July:
Average sea temperature in August:
Average sea temperature in September:
Average sea temperature in October:
Average sea temperature in November:
Average sea temperature in December:
The best month for swimming (with the highest average sea temperature) is January (29.5°C).
The coldest month (with the lowest average sea temperature) is July (23.8°C).
The month with the longest days is December (Average daylight: 13.1h).
Months with the most sunshine are October and November (Average sunshine: 10.8h).
The month with the least sunshine is June (Average sunshine: 5.9h).
The month with the most sunshine days is October (18.6 days).
The month with the least sunshine days is January (6.3 days).
Months with the highest UV index are January, February and November (UV index 7).
The month with the lowest UV index is July (UV index 5).
Months with the most cloud cover are January and March (Cloud cover 45).
The month with the least cloud cover is September (Cloud cover 28).
Months with the highest visibility are January, February, March, April, May, June, July, August, September, October, November and December (10km).
Months with the lowest visibility are January, February, March, April, May, June, July, August, September, October, November and December (10km).
The month with the least rainfall in Cairns, Australia, is September when the rain falls for 7.2 days and typically collects 9mm (0.35") of precipitation. [101252]


Desktop Condor (DTCondor) provides an easy-to-use graphical interface which considerably simplifies the processs of submitting jobs to the ARC Condor pool. By using DTCondor, there is no longer any need to remember obscure UNIX commands or to transfer files to and from the Condor server manually. DTCondor is therefore ideal if you are new to Condor, dislike the arcane UNIX command line environment, or are an infrequent and fairly light Condor user.
The DTCondor graphical interface (DTCondor for short) has been tested extensively (but not exhaustively !) on 32 and 64-bit versions of the Windows 7 operating system that forms the basis of CSD's Managed Windows Service (MWS). It may work on other versions of Windows but unfortunately there is no support for Macs or for Linux-based systems.
DTCondor works best when used on the University campus network but off-campus use is possible via the Virtual Private Network (VPN). See the section of Using DTCondor from off-campus for details. If you would like to use DTCondor, please contact the Condor administrator (Dr Ian C. Smith, i.c.smith@liverpool.ac.uk ) in the first instance, as it will be necessary to set up the server side of things first. You will of course also need an account on the Condor service (for details see the Condor registration web page).
This document provides an introduction to DTCondor and describes in detail how to use it for running applications based on MATLAB or R. Although it is not especially complicated, there is a lot of information presented here and it may be best to have a quick read through first and then try the walk-through examples before reading the guide again in depth. The examples should help familiarise yourself with DTCondor and can act as a starting point for your own applications. Hopefully the documentation should cover most things but if anything isn't clear or if you have any suggestions for improvements, please contact the Condor administrator as this will help to improve the documentation.
The DTCondor software is bundled into a Microsoft Installer (MSI) package which can be downloaded by clicking on the button below.
Note that you must have administrator rights on your computer for DTCondor to install correctly and therefore DTCondor cannot be installed on teaching and learning centre machines.
Another DTCondor icon (see left) should also appear as folder on the Desktop which provides easy access to folders used to store DTCondor data files (e.g. templates, input data, executables - more on this below).
After a short while, the DTCondor Login window should appear as shown below.
[NOTE: throughout this guide "condoruser" should appear as your own username when you actually come to use DTCondor].
Your username should already be filled in but if it is this incorrect, enter your correct Condor username (this will usually be the same as your MWS/e-mail username), then enter your normal MWS/e-mail password and click the Continue button. If you are unable to login, please contact the Condor administrator for help.
The Main Menu contains a list of actions which you can perform with DTCondor. Usually either the second or third items are needed i.e. "create or edit a job template" or "submit jobs using an existing template" but if you wish to run MATLAB applications it will be necessary to create a stand-alone executable by selecting the first option, "build a stand-alone MATLAB executable". This is the subject of the next section so if you are not interested in MATLAB just skip to the Introduction to Job Templates section.
It is not possible to run large numbers of MATLAB scripts (i.e. M-files) directly on the Condor pool because of licensing restrictions and so any MATLAB code used will first need to be compiled or "built" into a stand-alone executable which can run without a license. For very simple applications, most users will place all of their code in a single M-file but often, as things become more complicated, it may be necessary to move some of the code into other M-files. By design, DTCondor can be used to build stand-alone executables from either a single M-file or from multiple M-files. The M-file containing the main part of the program (which calls other M-files) is imaginitively referred to here as the "Main M-file" while the other M-files (perhaps containing your own MATLAB functions) go by the equally prosaic description of "Other M-files".
step is to select the "Main M-File" and (if necessary) the "Other M-files". You can type the filenames by hand including their full path or (much easier) use the Browse button to locate the files and select them. By default, all of the files will come from the M:\matlab64 folder since this is also the default folder for the current version of MATLAB on the MWS. A different default folder can be selected by using the "M-file folder" option. Alternatively, the M-files can be selected in a different folder (the "Main M-file" does not need to be in the same folder as the "Other M-files"). Once all of the files needed have been selected, click on the Continue button and the build process will start.
So what happens next ? Behind the scenes, DTCondor will transfer the M-files plus some other bits and pieces to the Condor server and submit a Condor job which will build the executable using one of the pool PCs (this ensures that your executable is created in the same MATLAB environment that it will run under). Once the job has completed, you can then download the executable and use it for running large batches of "real" jobs.
The progress of the build job can be tracked by using the DTCondor Monitor window. A detailed discussion of this will be saved for the section on Monitoring Progress, but suffice it to say here that the Update Messages button can be used to see what the Condor server is up to and the Download Output button can be used to download the stand-alone executable once it has been created.
what application needs to be run (in other words, what is the executable file or script) ?
how many times does the application need to be run (i.e. how many jobs are required) ?
what input data needs to be processed (alternatively, what are the input files) ?
what input data is the same for every job (this will be held in the "common input files") ?
what input data is different for each job (this will be held in the "indexed input files") ?
In a Monte Carlo or other stochastic analysis application, for example, the indexed input files may contain different random number generator seeds. In a pharmaceutical field trial, the indexed input files might contain data from different patients.
what output data should the application produce (i.e. what will the output files be) ?
This turns out to be very useful in catching errors and so it's a good idea to always provide it if possible.
In the past, all of the above information would need to be supplied to Condor by typing it into a text file. This was both cumbersome and error-prone and therefore DTCondor allows users to enter the information via a graphical interface. [If you have used the Condor service previously, then it's worth pointing out that job templates are essentially the same as simplified job submission files but are hidden and do not (and should not) need to be edited "by hand"].
After a job template has been created, it is straightforward to submit large numbers of jobs and make small changes to the analyses/simulations as needed. Going back to the earlier examples; in the Monte Carlo case, a different model could be used just by changing the underlying code and running it again with the same random number seeds (for MATLAB, the code would also need to rebuilt). This would provide a direct comparison between the two sets of results. In the pharmaceutical example, a new set of field trial data could be processed just by replacing the input files.
The Job Type box is used to select which kind of application is to be run. The "MATLAB M-file" option allows you to run a single job based on one or more M-files (rather than a stand-alone executable) and is useful for testing. The "Generic MWS job" option is provided for backwards compatibility and is not really aimed at new users (if you do need to run applications that are not based on MATLAB or R, please contact the Condor Administrator for advice on how to proceed). The "MATLAB stand-alone executable" option, as it suggests, can be used to run MATLAB applications using executables built earler using DTCondor. Finally the "R script" option can be used for jobs employing one or more R scripts.
Type the name of the main M-file in the "Executable, M-file or R script" text box.
Enter the name of the executable that was built previously and downloaded (this should have a .exe extension).
Enter the name of the main R script (i.e. the script that calls any other R scripts) - this will usually have a .R extension.
The executable can be either a DOS batch (.bat) file or a binary executable (.exe file). In each case, only the name of the file is needed - not the complete path to it.
The next step is to fill in the details of the input and output files in the text boxes below the executable option. Filenames can be entered one per line and (if there are several of them) multiple filenames can be entered in the same box separated by one or more spaces. There is no need to put in the actual path to the file - just the filename itself. The actual files to be used will be selected when you come to submit the jobs.
The "Common input files" boxes can be used to specify which files are the same for all of the jobs and may only be needed for a few applications. Common input files can be useful if (for example) you have look-up data which is needed by all of the jobs and which is the same for each. In the case of R applications, all of the other R scripts apart the main one are counted as common input files and need to be given here. For a "MATLAB M-file" job, enter the names of the "Other M-files" in the "Common input files" text boxes as these are counted as input files.
(note that the indices start at 0 not 1). There is no need to specify the actual index value in the text box or in the underlying MATLAB code as all of the index manipulation will be done for you behind the scenes.
Again there is no need to worry about the index value either in the template or in your code - everything will be taken care of automatically in the background. Indexed output files are optional but their use is recommended.
The reason that specifying the output files is so important is that it allows Condor to flag an error if any of the files are missing after the jobs have run. Put another way, Condor can only determine if something has gone wrong if it knows what outputs are expected. For the very simple examples given below, it is quite easy to spot if things have gone wrong but when submitting very large batches of jobs (we've seen 40,000 jobs in a few cases) it can be tedious to say the least to have to sift through all of the output files to confirm that they are all in fact there.
The "Total number of jobs" option should be fairly self explanatory and determines the amount of times the executable will be run by Condor with different input data. The number of jobs must tally with the actual number of indexed input files used.
and by saving templates there, they will be easier to locate in future; however you can select any folder you wish.
and all files with a .dtc extension will be shown (for generic MWS jobs, switch the filter to .mws to see the relevant templates). You can select one of these and the information contained in it will be displayed in the editor window. You can also load templates from another location by navigating to them. After all of the changes have been made, click on the Save Template button to save the file. The template can be saved under a different filename if you want to keep the old template.
Once you have finished using the Job Template Editor, click the Close button to go back to the Main Menu.
but you can browse to other folders if the required template has been saved in a different location. Also, by default, only standard template files (those with a .dtc extension) are shown. If you are using a generic job template file, then the file filter will need to be changed to *.mws in order to see those files.
After a job template has been loaded some additional information should appear in the window; namely the executable or script file, the common input file(s) (if any), the indexed input files and the indexed output files (if any). An example is shown below where the various files have been circled.
The total number of jobs will also be shown in green near the bottom of the window.
Before submitting the jobs, you will first need to select the actual executable or script to be run. To do this, browse to the file by clicking the Browse button under either Executable file, R Script or M-file (depending on the job type), then select the file and click Open (you can also type the full path to it directly into the text box).
If the files are located elsewhere, either change the folder displayed in the text boxes or (much easier) browse to the folders using the Browse button (if there are no common input files then the folder is irrelevant so don't worry about it).
Once the correct folders have been selected, you can submit the jobs by clicking the Submit Jobs button. DTCondor will do a quick check to see that all of the files needed are in fact present before submitting the jobs to the server and will issue an error message if any are missing. It will then bundle the files into a ZIP format file and upload it to the Condor server for submission. To check that the jobs have actually been submitted properly (and to see how they are progressing) we need to move to the previously sidelined DTCondor Monitor window which is the subject of the next section. For now, you can close the DTCondor Job Submission window to get back to the Main Menu.
You can check how your Condor jobs are progressing using the DTCondor Monitor window. This will open once you have successfully logged-in as shown below.
The information is not refreshed continuously (to avoid overloading the server) but by clicking on the Update Messages button, the latest information will be retrieved from the server and displayed.
The DTCondor server is running and is ready to accept jobs.
It's worth trying this now just to check everything is working.
All of the jobs have now been submitted and none have completed so far.
(To see your own jobs, enter your username in the text box and click on the Submit button). DTCondor can also be closed on the PC and started again later without affecting any of the jobs.
As well as giving more in-depth information than DTCondor, the website has the advantage that it can be used anywhere (including off-campus) without the need for DTCondor to be installed. It is therefore ideal for checking quickly how your jobs are faring whilst away from the office.
Once all of the jobs have completed, you should receive this message.
All of the jobs have now completed.
If you would like to save them to a different folder just use the Browse button to select the desired folder or type the full pathname into the text box. The output files will be compressed into a ZIP file which can be extracted later (right-click on the file in Windows Explorer and select Extract All...).
You can also download the partial results at any time whilst jobs are running by clicking the Download Output button. This can be useful as a check that everything is working correctly. In this case, all of the output files will be downloaded including any log files etc.
Removing Condor jobs - this may take a while.
All jobs have been removed.
If the jobs refuse to terminate, please contact the Condor administrator.
You can safely remove jobs at any time without destroying the results obtained so far which can always be downloaded using the Download Output button. In fact the output files from a given batch of jobs will remain on the server until a new batch of jobs is submitted.
It is possible to submit jobs and retrieve their output files from off-campus using DTCondor however, because direct access to the Condor server is blocked to the outside world, it will first be necessary to establish a connection using the Virtual Private Network. You can find details of how to do this on the CSD page on Virtual Private Network (VPN). If you have difficulties using DTCondor it still possible to use the command line interface and retrieve files using secure FTP. Details on this can be found on the remote access to Condor web page. Note that submitting Condor jobs and retrieving the results can require the transfer of large amounts of data so a fast reliable connection will be needed.
Although only a single M-file is used, the extension to applications using multiple M-files is straightforward.
To begin with: download the M-file by right-clicking on this link product.m and selecting Save Link As... You can save it anywhere on your PC but if you save it to the folder M:\matlab64, then that will simplify things later.
and login using your ordinary MWS username and password.
If you have previously saved the M-file to the M:\matlab64 folder you can skip this step. If not, then type the name of the folder in the "Main M-file folder" text box or better still click the Browse button to locate it (this is easier and less error-prone).
The main M-file, product.m, now needs to be selected. The easiest way to do this is to click the Browse button to the far right of the "Main M-file" label and select product.m. Alternatively you can just type in the filename including its full path, for example : M:\matlab64\product.m.
If your application contained multiple M-files then the next step would be to select them. The easiest way to do this is to click the Browse button to the far right of the "Other M-files" label. After the file browser window appears you will need to select all of the remaining M-files. There are two ways to do this: either hold the SHIFT key down and left-click on the first file and then the last file or hold down the Ctrl key and left-click on each file. When all of the required M-files are highlighted click the Open button. You can also type the filenames including the full paths to them. Note that the "Other M-files" do not need to be in the same folder as the "Main M-file".
The MATLAB Stand-alone Builder window can now be closed by clicking the the Close button to return to the Main menu.
meaning that the stand-alone executable has been built successfully and can now be downloaded.
by either typing the path into the text box or, better still, selecting the folder via the Browse button.
This example shows how to submit multiple MATLAB jobs using the stand-alone executable built earlier. Again the application is exactly the same as that described in the web page on MATLAB Applications and the executable just reads two input matrices, multiplies them together and writes the results to an output file.
The input files will have the form input<index>.mat and the corresponding output files output<index>.mat. Note that the index does not need to be specified either in the MATLAB code or any of the templates as all of the index manipulation is done for you in the background. Similarly, there is nothing special about the filenames chosen and any filename of the form <basename>.<extension> will suffice. However, spaces should not be used and it is best to stick to letters and numbers (and possibly hyphens or underscores used to make things more readable).
Only one other file is needed - the stand-alone executable product.exe. This should have already been built earlier and if you have not already done so, copy this to the default executable folder i.e.
If any changes were needed, for example the number of jobs or input files, then this would be the place to make them. You can try this now by changing some of information and you should see that a message warning you that the template has not been saved appears at the bottom of the window. To make the changes permanent, you could then click the Save Template button to save them to a file. In this case, no changes are needed so just click Close to get back to the Main Menu.
Once a template file has been loaded, the next step is to identify the actual files to be used with the jobs. Firstly, you will need to select the stand-alone executable. To do so click the Browse button under the Executable file text and select the previously built executable (product.exe). There are no common input files for this example so skip over that option to the Indexed input files folder option. If you have previously saved the input files (product0.mat ... product9.mat) to the default location i.e.
then there is no need to change anything but if they were saved to a different folder, this should now be selected by browsing to it using the Browse button below the Indexed input files folder: text.
Since the Job Submission window is no longer needed, it can be closed by clicking the Close button to return to Main Menu.
By repeatedly clicking Update Messages, you should see that the jobs eventually start to run and, after a while, complete. For example here five of the ten jobs have completed.
You can shut down DTCondor at anytime and start it again later without it affecting any of the submitted jobs. It is also possible to get detailed information on how your jobs are progressing by visiting to the Condor website (condor.liv.ac.uk) which is accessible from anywhere (even outside of the University network).
The input files will still have to be indexed in form input<index>.mat (and the corresponding output files output<index>.mat) even though for this example there is only one input file input0.mat. Note that the index does not need to be specified either in the MATLAB code or any of the templates as all of the index manipulation is done for you in the background. Similarly, there is nothing special about the filenames chosen and any filename of the form <basename>.<extension> will suffice. However, spaces should not be used and it is best to stick to letters and numbers (and possibly hyphens or underscores used to make things more readable).
If any changes were needed, for example the input file, then this would be the place to make them. You can try this now by changing some of information and you should see that a message warning you that the template has not been saved appears at the bottom of the window. To make the changes permanent you could then click the Save Template button to save them to a file. In this case, no changes are needed so just click Close to get back to the Main Menu.
Once a template file has been loaded, the next step is to identify the actual files to be used with the jobs. Firstly, you will need to select the main M-file. To do so click the Browse button under the M-file text and select the previously downloaded M-file (product.m). There are no common input files for this example so skip over that option to the Indexed input files folder option. If you have previously saved the input file (input0.mat) to the default location i.e.
then there is no need to change anything but it was saved to a different folder, this should now be selected by browsing to it using the Browse button below the Indexed input files folder: text.
By repeatedly clicking Update Messages, you should see that the job eventually starts to run and, after a while, complete.
This example shows how to submit R jobs using DTCondor. Although only a single R script file is employed here, the extension to applications that require multiple R scripts is straightforward. The application is exactly the same as that described in the web page on R Applications and it calculates a frequency distribution for a very large number of observations stored as R data files. The input files will have the form observations<index>.dat and the corresponding output files results<index>.mat. Note that the index does not need to be specified either in the R code or any of the templates as all of the index manipulation is done for you in the background. Similarly, there is nothing special about the filenames chosen and any filename of the form <basename>.<extension> will suffice. However, spaces should not be used and it is best to stick to letters and numbers (and possibly hyphens or underscores used to make things more readable).
If any changes were needed, for example the number of jobs or input files, then this would be the place to make them. You can try this now by changing some of information and you should see that a message warning you that the template has not been saved appears at the bottom of the window. To make the changes permanent you could then click the Save Template button to save them to a file. In this case, no changes are needed so just click Close to get back to the Main Menu.
Once a template file has been loaded, the next step is to identify the actual files to be used with the jobs. Firstly, you will need to select the main R script. To do this click the Browse button under the R script text and select (analyse.R). There are no common input files for this example so skip over that option to the Indexed input files folder option. If you have previously saved the input files (observations0.dat ... observations9.dat) to the default location i.e.


Please provide recommended PC specs. (CPU/RAM/etc...) to support transcoding on the fly.
Thank you for the question. I've been meaning to provide CPU specs on the site and I will do that soon.
For on-the-fly transcoding of 720p and below you can use a dual-core 3Ghz CPU with 2GBs of RAM (provided nothing else is really running on that machine). A quad-core CPU would be better of course. For 1080p, you'd need an i5 or i7 with 4GBs of RAM. A quad-core may also work, but it depends on the specific CPU make and model. Typically Intel-based processors work a little bit better (faster).
The only other requirement is disk space. One high-def (1080p) movie can take up anywhere from 4 to 10 GBs after transcoding. You can limit the temporary transcoding folder size by both disk space used and age of files (see Tools -> Options -> Transcoding in KRR). If you have a NAS drive, I'd recommend not moving the transcoding folder there and to keep it on your local disk - this saves network bandwidth and ensures that files can be written and read at optimum speed.
Please let me know if you'd like to know more or have specific questions about your hardware.


text:
\section{Introduction}
Numerous applications in quantum optics, communications, and computing rely on strong interactions between single atoms and photons \cite{chang2018colloquium,reiserer2015cavity,o2013fiber}. Recently, atom-light interactions using nanophotonic devices \cite{thompson2013coupling,burgers2019clocked} and nanofibers \cite{kato2019observation,schneeweiss2017fiber} have been demonstrated in a number of laboratories. However, these setups require a substantial effort to cool, transport, and eventually trap the atoms near the dielectric surface of the nanophotonic system. Miniaturization and scalability are hindered by these additional requirements. Moreover, there is a mismatch of timescales between the nanoseconds required to strongly couple atoms and photons in microresonators and the milliseconds to seconds required for atomic cooling and trap loading. This limits the duty cycle of quantum devices based on atoms and photons. By contrast, laser slowed, or even in some cases, fast thermal atomic beams possess many of the prerequisites for quantum device fabrication \cite{li2019cascaded,li2020robust}.

In this paper, we experimentally demonstrate a high-performance silicon nitride ($\mathrm{Si_3N_4}$ or in short, SiN) microring resonator and show, through simulations, that it is capable of strongly interacting with slow atomic beams during their microseconds-long transit time above the resonator.  In this feasibility study, we also show that racetrack versions of these resonators can be combined with thermal atomic beams, which substantially reduces the vacuum requirement and laser overhead and paves the way toward highly integrated quantum devices using atoms on chips.

Among different material platforms, stoichiometric low-pressure chemical-vapor-deposited SiN (LPCVD-$\mathrm{SiN}$) has garnered attention for integrated nanophotonics as a CMOS-compatible material with a wide transparency window ranging from short visible wavelengths ($450$ nm) to infrared (IR) \cite{baets2016silicon, munoz2017silicon}. This would allow the co-integration of photonic and microelectronic structures for system-level implementations \cite{rahim2017expanding}. High-quality-factor (high-Q) photonic resonators using SiN are demonstrated in the near-IR regime with Qs on the order of $40\times10^6$ \cite{ji2017ultra}. However, these record Qs are achieved in oxide-clad thick-film SiN resonators with a large radius. In most cases, high-temperature annealing is also used to reflow the etched structure, mitigate plasma damages, and further improve the Q of hitherto not-annealed microresonators \cite{li2013vertical, xuan2016high, brasch2014radiation}. However, such high-temperature annealing would degrade the underneath front-end-of-the-line (FEOL) circuitry, which is required in system-level implementations \cite{el2018annealing}.

In our platform, the microresonator should allow a strong interaction of the atom flying above the resonator with the evanescent tail of the electric field of a resonant mode.  This requires a mode with low field confinement.  Furthermore, the microresonator needs to have a reasonably small radius, for the single atom cooperativity
parameter $C\sim Q/V$ increases with decreasing mode volume $V$.

The requirements for efficient atom-photon interactions impose trade-offs among the degrees of freedom to achieve high Qs in microresonators. High-Q microresonators are usually achieved with a large radius, tight field confinement, oxide-clad. Our requirements along with the increased Rayleigh scattering at typical wavelengths of atomic transition \cite{gorodetsky2000rayleigh} highlight the challenges to achieve high-Q \cite{zhao2020visible}. In this paper, we demonstrate a LPCVD-SiN microring resonator with a loaded Q of $1.55\times10^6$ at near-visible wavelengths
which is the record-high Q for the air-clad thin-film microrings with no chemical -mechanical polishing (CMP) at near-visible wavelengths, to the best of our knowledge.

A strong interaction between the cavity mode and the atom requires a thinner SiN film with air-cladding to expose the cavity mode. For this purpose, a SiN film with a thickness of $287$ nm is chosen. The width of the waveguide bent to form the microring resonator is chosen $w_f=5$ $\mu$m to minimize the surface roughness at the inner wall of the microresonator, while the second-order transverse electric (TE) mode (i.e., the electric field in the plane of resonator) with maximum electric field away from the outer wall would experience lower scattering compared to the fundamental TE mode. The outer radius of the ring is $R_o=35$ $\mu$m to ensure an appropriate quality of the resonant modes, i.e., avoiding significant curvature while increasing the coupling factor g, and having a large-enough spectral distance between different families of transverse resonant modes. The second-order radial TE mode has a higher Q than the first-order one as its peak of the electric field is farther away from the outer ring sidewall, thus lowering the scattering losses. For the $D_2$ atomic transition of $^{87}$Rb at the wavelength $\lambda = 780.24$ nm, fine-tuning of the resonance wavelength through thermal tuning is required.  This is compatible with device operation at an elevated temperature above 100\degree C to avoid atomic deposition.

\begin{figure}[t]
\centering
\includegraphics[trim = 0 50 200 0, width=\linewidth]{figure2.pdf}
\caption{ Optical characterization of the microring. (a) Normalized transmission through the waveguide, and (b) the scanning electron microscope (SEM) image of the fabricated microresonator with an outer radius of $35$ $\mu$m and a width of $5$ $\mu$m formed in a 287 nm-thick SiN on a $\mathrm{SiO_2}$ substrate. The microresonator is coupled to a bus waveguide with a gap distance of $100$ nm. In (a) families of modes spaced by $\sim 1$ nm can be seen.  Within each family, the spacing is large enough to avoid intermode coupling. The TE$_2$ family mode represents high-Q resonances as shown in the zoomed-in plots in (c) and (d). Loaded  Qs at both resonant wavelengths $\lambda = 774$ $(778.2)$ nm are above $1.5\times10^6$. Blue circles are experimental data and the solid red lines are fits to a double Lorentzian curve to account for the splitting of degenerate counter-clockwise resonant modes.}
\label{fig:characterization}
\end{figure}

The fabrication process starts with a planar polished oxidized silicon (Si) wafer, with $5$ $\mu$m thermal oxide that is formed by dry-wet-dry oxidation process, forming a $300$ nm-thick dry silicon dioxide (Si$O_2$) layer on top to ensure the high quality of the oxide region at the interface with the devices. The SiN layer for defining the waveguide and microresonator is deposited by LPCVD at a Tystar nitride furnace, with agent gases of dichlorosilane (DCS) and ammonia at $800 ^\circ C$. The stoichiometric SiN (i.e., $\mathrm{Si_3N_4}$) is deposited by adjusting the agents' ratio, leading to a refractive index around $2$ at $\lambda = 632$ nm. The deposition time is adjusted to reach a SiN thickness about $290$ nm. The sample is cleaned in two steps: first AMI solution (acetone, methanol, isopropanol), nitrogen blow dry, followed by BOE 6:1 (buffered oxide etchant) wet etching, running DI (deionized) water, and nitrogen blow dry. The sample is then baked on a hot plate to remove any moisture and prepare it for electron-beam resist coating. Flowable oxide (DOW corning FOx 16) is then spun on the SiN thin-film, followed by baking the sample on a hot plate. The devices are patterned using electron beam lithography (EBL) with current $I = 2 $ nA. The EBL parameters are optimized to minimize the edge roughness in the mask. After developing the sample in $25 \%$ Tetramethylammonium hydroxide (TMAH electronic grade) and nitrogen blow dry, the sample is etched in inductively coupled plasma (ICP) reactive ion etching (RIE) machine, with an optimized flow of oxygen, argon, and carbon tetrafluoride ($CF_4$) as the etching agents. The selectivity of SiN:FOx has been around one. The process is followed by short wet etching in BOE 6:1 and nitrogen blow dry.

To characterize the Q of the microresonators, the continuous-wave (CW) laser light from a tunable diode laser is passed through a polarization controller and input-coupled to the bus waveguide using a waveguide grating. The transmitted light is then detected at the output of the waveguide, where a multi-mode fiber collects light from an out-coupling grating and followed by a Si amplified detector. The CW laser is swept in the wavelength range $\lambda= 770 - 780.5$ nm with $0.05$ pm resolution.
The collected transmission from the detector is then fitted to two-Lorentzian curves, to take into account the intracavity coupling between counter-propagating modes. This facilitates the characterization of Qs associated with these modes.
Figure \ref{fig:characterization}(a) shows the transmission characteristics of the fabricated microring resonator with outer radius $R=$ 35 $\mu$m (see Fig. \ref{fig:characterization}(b)).

The zoomed linear transmissions for two longitudinal resonant modes at $\lambda=774.2$ nm and $\lambda=778.2$ nm are depicted in Fig. \ref{fig:characterization}(c), and \ref{fig:characterization}(d), respectively, showing Qs larger than 1.5$\times 10^6$ for both modes.
Figure \ref{fig:characterization}(c) indicates the splitting between the counterclockwise and clockwise modes at $\lambda=774.2$ nm.
The splitting is proportional to the coupling between them, so for the resonant mode at $\lambda=778.20745$ nm, the coupling is almost negligible.
This resonator can be temperature tuned to the $D_2$ resonance of the $^{87}$Rb atom at 780.24 nm.  Finite element simulations using COMSOL multiphysics and assuming a uniform temperature at the $\mathrm{SiO_2}$ and SiN layers indicate an $\approx 90 ^\circ C$ increase over the room temperature would be required. This number is roughly consistent with the formula $\frac{\partial \lambda}{\partial T} = \frac{\lambda}{n_g}\frac{\partial n_\text{eff}}{\partial T}$, with $n_g$ and $n_\text{eff}$ being the group index and the effective refractive index of the mode, respectively, T being the temperature in Kelvin (K), and using the thermo-optic coefficients (TOCs) $4\times10^{-5}$ $K^{-1}$ and $1.5\times 10^{-5}$ $K^{-1}$, respectively, for SiN and $\mathrm{SiO_2}$.

\begin{figure}[ht]
\centering
\includegraphics[width=\linewidth]{figure1new.pdf}
\caption{High-Q SiN resonator for strong atom-light interaction. (a) Normalized electric field distribution at the cross-section of the microresonator for the mode $\mathrm{TE_{2,486}}$ with subscripts $2$ and $486$ showing the radial and azimuth mode numbers. The width of the SiN film bent to form the microring is $5$ $\mu$m, with a height of $287$ nm, and an outer radius of $35$ $\mu$m. Red lines show the boundary of the SiN resonator, and the gray line shows the boundary of the $\mathrm{SiO_2}$ substrate. (b) The atom-resonator coupling factor g(z) along the vertical dashed line in (a) at the lateral maximum of the resonator mode intensity at radius $R=33.7$ $\mu$m.}
\label{fig:first}
\end{figure}
The coupling between an atom and an optical mode is governed by the Jaynes–Cummings Hamiltonian \cite{reiserer2015cavity}:
\begin{equation}
        H=\hbar \omega_a\sigma^\dagger\sigma+\hbar \omega_c a^\dagger a+\hbar g(\vec{r})(\sigma a^\dagger+\sigma^\dagger a)
        \label{eq:hamiltonian}
\end{equation}
Here $\sigma = |g\rangle \langle e|$ is the atomic lowering operator, where $|g\rangle$ and $|e \rangle$ are the ground and the excited states of the atom, respectively;  $a$ is the photon annihilation operator; $\omega_a$ and $\omega_c$ are the atomic  and cavity angular resonance frequencies, respectively. The $g(\vec{r})$ factor characterizes the interaction strength between the atom and the cavity mode, which can be calculated as:
\begin{equation}
    g(\vec{r})=g_0\cdot \frac{\sqrt{\epsilon(\vec{r})}|E(\vec{r})|}{\max(\sqrt{\epsilon(\vec{r})}|E(\vec{r})|)}
\end{equation}
with $g_0=-d_{ge}\sqrt{\frac{\omega_c}{2\epsilon_0 \hbar V}}$. Here $d_{ge}$ is the effective dipole matrix element between ground and excited states; $V$ is the mode volume defined as $V=\int dr^3\frac{\epsilon(\vec{r})|E(\vec{r})|^2}{\max(\epsilon(\vec{r})|E(\vec{r})|^2)}$ \cite{englund2005controlling}, and $\epsilon(\vec{r})$ and $E(\vec{r})$ are material permittivity and electric field of the optical mode at location $\vec{r}$.
The electric field distribution of the $\mathrm{TE_{2,486}}$ mode is demonstrated in Figure \ref{fig:first}(a). The subscript numbers $2$ and $486$ indicate the radial and azimuth mode numbers, respectively.
The value of $g(\vec{r})$ at $R_0=33.7$ $\mu$m is shown in Figure \ref{fig:first}(b). It is noticed that $g(R_0,z)$ decreases very fast with $z$,  emphasizing the importance of air-cladding in resonator design.  Our resonator achieves a single-photon vacuum Rabi frequency $2g(R_0,z_0)=2\pi \times 64$ MHz around $z_0=100$ nm above the resonator while achieving a high Q with air-cladding. The single-atom cooperativity parameter is $C(R_0,z_0)=4g(R_0,z_0)^2/\kappa\gamma\approx2.7>1$. $\kappa$ and $\gamma$ here define the cavity and atomic energy decay rates.

Figure \ref{fig:simulation}(a) shows the concept of atom sensing using our high-Q resonator. Atoms from an atomic source, either a slow atomic beam from a 2D$^+$ magneto-optical trap (MOT) \cite{dieckmann1998two} or a beam of fast atoms from a thermal vapor as in Ref \cite{li2019cascaded}, pass through the microchannels, fly above the resonator, and strongly interact with it. Lithographically defined microchannels of 1-3 mm length help with atomic beam collimation and alignment with the resonator and will minimize excess contamination by alkali metals. The coupling waveguide is designed to bring the resonator into the critical coupling condition.

To understand the dynamics of an atom interacting with the resonator we simulate the known Master equation \cite{reiserer2015cavity} for the density operator. We can apply the adiabatic approximation with slow atomic beams because the time scale for atomic transit (microseconds) over the resonator is much slower than the internal state evolution time (tens of nanoseconds) given ($(g,\ \gamma,\ \kappa)/2\pi\approx$ (32, 6, 256) MHz) and confirmed by full time-dependent calculations.  The spatial coordinate of the atom, $\vec{r}(t)$, is computed classically with the surface force, while the Master equation is solved using the instantaneous value of $g(\vec{r}(t))$. We use an approximate formula for the Casimir-Polder potential for Rb atoms (Ref \cite{thompson2013coupling} supplement)
$\mathrm{U}(z)=\frac{-C_{3}\frac{\lambda_{\text{eff}}}{2\pi}}{z^3\cdot(z+\frac{\lambda_{\text{eff}}}{2\pi})}$, where $C_3=2\pi\hbar\times1500$ $\mu$m$^3$, and $\lambda_{\text{eff}}=650$ nm for SiN.

Figure \ref{fig:simulation}(b) shows the transmission of the cavity versus laser detuning for both an empty cavity and a cavity containing one stationary atom 100 nm above the resonator at $R=33.7 \mu$m.  The peak splitting is the well-known vacuum Rabi splitting that is proportional to $g(\vec{r})$ \cite{thompson1992observation}. If we set the excitation laser to zero-detuning and lock the resonator to the atomic transition, the presence of an atom will cause the transmission of the cavity to increase. With a constant excitation power, this will result in an increasing photon flux in the detector. For moving atoms, the change of the photon flux depends on $g(\vec{r}(t))$, and with single-photon counting modules as the detector, we can achieve the real-time monitoring of an atom transit.

Sample transits for atoms with different velocities are shown in Figure \ref{fig:simulation}(c). The signals are displaced in time for a clearer view. The resonator size is the same as that in Figure \ref{fig:characterization} with a Q of $1.5\times10^6$.  The extinction ratio at the critical coupling condition is assumed to be 13 dB. The horizontal and vertical velocities of the atom are set to zero. The number of transmitted photons increases as an atom flies closer to the resonator surface, and the double peak in the signal results from the two nodes in the TE$_2$ field distribution (See Figure \ref{fig:first} (a)). Atoms with a broad range of longitudinal velocities can be detected. The atom's height and longitudinal velocity determine the signal intensity and duration, respectively. The faster the atom, the closer it can be to the resonator without crashing and the more intense (but shorter) signal it creates. With these constraints, we estimate that atoms with 0.2 m/s to 30 m/s longitudinal velocities can be detected without crashing on the resonator. The atom beams with such velocities can be generated from a 2D$^+$ MOT \cite{dieckmann1998two,ramirez2006multistage} and delivered via microchannels as shown schematically in Figure \ref{fig:simulation}(a). Interestingly, the ring configuration allows us to detect the same atom twice, and the time interval can be used to calculate the longitudinal velocity of the atom as well.

While the ratio $g/\kappa \approx0.12$ achieved is not yet in the strong coupling regime, the interaction between single atoms and photons is sufficiently strong that it can  enable quantum device applications.  For example, we envision that our platform could be used for a single-photon switch by single atoms, similar to what has been demonstrated using macroscopic resonators \cite{o2013fiber}. Using a 2D$^+$ MOT with $1.8\times10^{10}$ atoms/mm$^2$/s \cite{dieckmann1998two}, which has an average longitudinal velocity around 8 m/s, we estimate that with an excitation power of 3.4 photons/$\mu$s and a Q of $1.5\times10^6$, we can achieve on average, a 50\% contrast between "ON" and "OFF" states and a single photon routing rate around 10 kHz for each microchannel-resonator pair. The routing rate is much faster than those in the typical cold-atoms-dropping approach \cite{shomroni2014all}, which requires around one second to finish one cycle. If the resonator Q can be improved to $6\times10^6$, the contrast can be 85\%, which is competitive with the cold atom systems but with much higher repetition rates due to the absence of a long dead time. The switch can be activated by the entry of a single atom into the vicinity of the resonator and by using fast electronics to detect the rise of detected photons in the first 100 ns time bin.

\begin{figure}[t]
\centering
\includegraphics[width=\linewidth]{figure3new_3.pdf}
\caption{(a) The schematic of the single-atom sensing platform. (b) Transmission spectra of excitation photons, with $g/2\pi=32$ MHz, loaded $Q=1.5\times10^6$, and 52.9 pW optical excitation power under the ideal critical coupling condition. The cavity is locked on resonance for atom sensing. (c) The detector signal when an atom flies above the resonator. The reference black line is the background signal from the imperfect critical coupling condition. Blue line: $v=3$ m/s, $h_0=150$ nm; Red dash: $v=1.5$ m/s, $h_0=190$ nm; Orange dot: $v=0.8$ m/s, $h_0=230$ nm. The excitation power is  52.9 pW. The vertical and horizontal velocities are set to be zero. $h_0$ is the vertical distance between atoms and the top resonator surface. (d) The detector signal when an atom flies above a racetrack resonator (shown in inset, with extinction ratio of 13 dB in the critical coupling regime), with velocity $v=300$ m/s, $h_0$ = $100$ nm, and excitation power of 231.8 pW. The resonator is locked to $w_0+kv_a$ to compensate the Doppler effect.}
\label{fig:simulation}
\end{figure}

We also studied the potential use of racetrack resonators to detect thermal atomic beams generated by microchannel-collimation of a 100 \degree C Rb vapor \cite{li2019cascaded}. Atomic vapors have recently been proposed for cavity quantum electrodynamics (QED) applications \cite{alaeian2020cavity}.
The advantage of our approach is the ability to place atoms with lithographic precision at a discrete location above the resonator. We designed a racetrack resonator with a R = 20 $\mu$m ring section and 30 $\mu$m straight sections and align its straight sections to our microchannels (see Figure \ref{fig:simulation}(d) inset). In this way, the collimated thermal atoms with an average speed of 300 m/s will fly along the 30 $\mu$m straight section and strongly interact with the resonator for $\sim$ 100 ns. The Master equation simulation of a thermal atom transit without adiabatic approximation is shown in Figure \ref{fig:simulation}(d). The setup is similar to Figure \ref{fig:simulation}(a) and the Q of the racetrack resonator is assumed to be $1.5\times10^6$, with the transverse and vertical velocity set to be zero.  The initial peak is the Rabi oscillation resulting from an atom entering the regime with a strong evanescent field of the racetrack. If we monitor photons transmitted in 100 ns time bins and assume a 50\% detection efficiency, we should find the number of photons jumping from 2.5 to $\sim$ 6, which indicates an atom transit. We have fabricated racetrack resonators  with $\sim 7\times10^5$ loaded Q, and the optimization of the fabrication process for achieving Q $\sim1.5\times10^6$ is currently underway.

Our simulations reveal that miniature atomic beams are a promising candidate to achieve a strong interaction with the microresonator at the single-photon level. With the achieved Q and using multiple channel-resonator pairs together, one can imagine generating multi-photon states on chip in a simple and scalable architecture.  Without the requirement of atom trapping, ultra-high vacuum would not be needed. Thus, we believe that the platform reported here can set the stage for a new class of scalable quantum devices on chip using atoms and photons.

\bigskip
\noindent
{\textbf{Funding:}} This work was supported by the Air Force Office of Scentific Research (AFOSR) Grant no. FA9550-19-1-0228.  This work was performed in part at the Georgia Tech Institute for Electronics and Nanotechnology, a member of the National Nanotechnology Coordinated Infrastructure (NNCI), which is supported by the National Science Foundation (ECCS-1542174).

\section{Introduction}
Numerous applications in quantum optics, communications, and computing rely on strong interactions between single atoms and photons \cite{chang2018colloquium,reiserer2015cavity,o2013fiber}. Recently, atom-light interactions using nanophotonic devices \cite{thompson2013coupling,burgers2019clocked} and nanofibers \cite{kato2019observation,schneeweiss2017fiber} have been demonstrated in a number of laboratories. However, these setups require a substantial effort to cool, transport, and eventually trap the atoms near the dielectric surface of the nanophotonic system. Miniaturization and scalability are hindered by these additional requirements. Moreover, there is a mismatch of timescales between the nanoseconds required to strongly couple atoms and photons in microresonators and the milliseconds to seconds required for atomic cooling and trap loading. This limits the duty cycle of quantum devices based on atoms and photons. By contrast, laser slowed, or even in some cases, fast thermal atomic beams possess many of the prerequisites for quantum device fabrication \cite{li2019cascaded,li2020robust}.

In this paper, we experimentally demonstrate a high-performance silicon nitride ($\mathrm{Si_3N_4}$ or in short, SiN) microring resonator and show, through simulations, that it is capable of strongly interacting with slow atomic beams during their microseconds-long transit time above the resonator.  In this feasibility study, we also show that racetrack versions of these resonators can be combined with thermal atomic beams, which substantially reduces the vacuum requirement and laser overhead and paves the way toward highly integrated quantum devices using atoms on chips.

Among different material platforms, stoichiometric low-pressure chemical-vapor-deposited SiN (LPCVD-$\mathrm{SiN}$) has garnered attention for integrated nanophotonics as a CMOS-compatible material with a wide transparency window ranging from short visible wavelengths ($450$ nm) to infrared (IR) \cite{baets2016silicon, munoz2017silicon}. This would allow the co-integration of photonic and microelectronic structures for system-level implementations \cite{rahim2017expanding}. High-quality-factor (high-Q) photonic resonators using SiN are demonstrated in the near-IR regime with Qs on the order of $40\times10^6$ \cite{ji2017ultra}. However, these record Qs are achieved in oxide-clad thick-film SiN resonators with a large radius. In most cases, high-temperature annealing is also used to reflow the etched structure, mitigate plasma damages, and further improve the Q of hitherto not-annealed microresonators \cite{li2013vertical, xuan2016high, brasch2014radiation}. However, such high-temperature annealing would degrade the underneath front-end-of-the-line (FEOL) circuitry, which is required in system-level implementations \cite{el2018annealing}.

In our platform, the microresonator should allow a strong interaction of the atom flying above the resonator with the evanescent tail of the electric field of a resonant mode.  This requires a mode with low field confinement.  Furthermore, the microresonator needs to have a reasonably small radius, for the single atom cooperativity
parameter $C\sim Q/V$ increases with decreasing mode volume $V$.

The requirements for efficient atom-photon interactions impose trade-offs among the degrees of freedom to achieve high Qs in microresonators. High-Q microresonators are usually achieved with a large radius, tight field confinement, oxide-clad. Our requirements along with the increased Rayleigh scattering at typical wavelengths of atomic transition \cite{gorodetsky2000rayleigh} highlight the challenges to achieve high-Q \cite{zhao2020visible}. In this paper, we demonstrate a LPCVD-SiN microring resonator with a loaded Q of $1.55\times10^6$ at near-visible wavelengths
which is the record-high Q for the air-clad thin-film microrings with no chemical -mechanical polishing (CMP) at near-visible wavelengths, to the best of our knowledge.

A strong interaction between the cavity mode and the atom requires a thinner SiN film with air-cladding to expose the cavity mode. For this purpose, a SiN film with a thickness of $287$ nm is chosen. The width of the waveguide bent to form the microring resonator is chosen $w_f=5$ $\mu$m to minimize the surface roughness at the inner wall of the microresonator, while the second-order transverse electric (TE) mode (i.e., the electric field in the plane of resonator) with maximum electric field away from the outer wall would experience lower scattering compared to the fundamental TE mode. The outer radius of the ring is $R_o=35$ $\mu$m to ensure an appropriate quality of the resonant modes, i.e., avoiding significant curvature while increasing the coupling factor g, and having a large-enough spectral distance between different families of transverse resonant modes. The second-order radial TE mode has a higher Q than the first-order one as its peak of the electric field is farther away from the outer ring sidewall, thus lowering the scattering losses. For the $D_2$ atomic transition of $^{87}$Rb at the wavelength $\lambda = 780.24$ nm, fine-tuning of the resonance wavelength through thermal tuning is required.  This is compatible with device operation at an elevated temperature above 100\degree C to avoid atomic deposition.

\begin{figure}[t]
\centering
\includegraphics[trim = 0 50 200 0, width=\linewidth]{figure2.pdf}
\caption{ Optical characterization of the microring. (a) Normalized transmission through the waveguide, and (b) the scanning electron microscope (SEM) image of the fabricated microresonator with an outer radius of $35$ $\mu$m and a width of $5$ $\mu$m formed in a 287 nm-thick SiN on a $\mathrm{SiO_2}$ substrate. The microresonator is coupled to a bus waveguide with a gap distance of $100$ nm. In (a) families of modes spaced by $\sim 1$ nm can be seen.  Within each family, the spacing is large enough to avoid intermode coupling. The TE$_2$ family mode represents high-Q resonances as shown in the zoomed-in plots in (c) and (d). Loaded  Qs at both resonant wavelengths $\lambda = 774$ $(778.2)$ nm are above $1.5\times10^6$. Blue circles are experimental data and the solid red lines are fits to a double Lorentzian curve to account for the splitting of degenerate counter-clockwise resonant modes.}
\label{fig:characterization}
\end{figure}

The fabrication process starts with a planar polished oxidized silicon (Si) wafer, with $5$ $\mu$m thermal oxide that is formed by dry-wet-dry oxidation process, forming a $300$ nm-thick dry silicon dioxide (Si$O_2$) layer on top to ensure the high quality of the oxide region at the interface with the devices. The SiN layer for defining the waveguide and microresonator is deposited by LPCVD at a Tystar nitride furnace, with agent gases of dichlorosilane (DCS) and ammonia at $800 ^\circ C$. The stoichiometric SiN (i.e., $\mathrm{Si_3N_4}$) is deposited by adjusting the agents' ratio, leading to a refractive index around $2$ at $\lambda = 632$ nm. The deposition time is adjusted to reach a SiN thickness about $290$ nm. The sample is cleaned in two steps: first AMI solution (acetone, methanol, isopropanol), nitrogen blow dry, followed by BOE 6:1 (buffered oxide etchant) wet etching, running DI (deionized) water, and nitrogen blow dry. The sample is then baked on a hot plate to remove any moisture and prepare it for electron-beam resist coating. Flowable oxide (DOW corning FOx 16) is then spun on the SiN thin-film, followed by baking the sample on a hot plate. The devices are patterned using electron beam lithography (EBL) with current $I = 2 $ nA. The EBL parameters are optimized to minimize the edge roughness in the mask. After developing the sample in $25 \%$ Tetramethylammonium hydroxide (TMAH electronic grade) and nitrogen blow dry, the sample is etched in inductively coupled plasma (ICP) reactive ion etching (RIE) machine, with an optimized flow of oxygen, argon, and carbon tetrafluoride ($CF_4$) as the etching agents. The selectivity of SiN:FOx has been around one. The process is followed by short wet etching in BOE 6:1 and nitrogen blow dry.

To characterize the Q of the microresonators, the continuous-wave (CW) laser light from a tunable diode laser is passed through a polarization controller and input-coupled to the bus waveguide using a waveguide grating. The transmitted light is then detected at the output of the waveguide, where a multi-mode fiber collects light from an out-coupling grating and followed by a Si amplified detector. The CW laser is swept in the wavelength range $\lambda= 770 - 780.5$ nm with $0.05$ pm resolution.
The collected transmission from the detector is then fitted to two-Lorentzian curves, to take into account the intracavity coupling between counter-propagating modes. This facilitates the characterization of Qs associated with these modes.
Figure \ref{fig:characterization}(a) shows the transmission characteristics of the fabricated microring resonator with outer radius $R=$ 35 $\mu$m (see Fig. \ref{fig:characterization}(b)).

The zoomed linear transmissions for two longitudinal resonant modes at $\lambda=774.2$ nm and $\lambda=778.2$ nm are depicted in Fig. \ref{fig:characterization}(c), and \ref{fig:characterization}(d), respectively, showing Qs larger than 1.5$\times 10^6$ for both modes.
Figure \ref{fig:characterization}(c) indicates the splitting between the counterclockwise and clockwise modes at $\lambda=774.2$ nm.
The splitting is proportional to the coupling between them, so for the resonant mode at $\lambda=778.20745$ nm, the coupling is almost negligible.
This resonator can be temperature tuned to the $D_2$ resonance of the $^{87}$Rb atom at 780.24 nm.  Finite element simulations using COMSOL multiphysics and assuming a uniform temperature at the $\mathrm{SiO_2}$ and SiN layers indicate an $\approx 90 ^\circ C$ increase over the room temperature would be required. This number is roughly consistent with the formula $\frac{\partial \lambda}{\partial T} = \frac{\lambda}{n_g}\frac{\partial n_\text{eff}}{\partial T}$, with $n_g$ and $n_\text{eff}$ being the group index and the effective refractive index of the mode, respectively, T being the temperature in Kelvin (K), and using the thermo-optic coefficients (TOCs) $4\times10^{-5}$ $K^{-1}$ and $1.5\times 10^{-5}$ $K^{-1}$, respectively, for SiN and $\mathrm{SiO_2}$.

\begin{figure}[ht]
\centering
\includegraphics[width=\linewidth]{figure1new.pdf}
\caption{High-Q SiN resonator for strong atom-light interaction. (a) Normalized electric field distribution at the cross-section of the microresonator for the mode $\mathrm{TE_{2,486}}$ with subscripts $2$ and $486$ showing the radial and azimuth mode numbers. The width of the SiN film bent to form the microring is $5$ $\mu$m, with a height of $287$ nm, and an outer radius of $35$ $\mu$m. Red lines show the boundary of the SiN resonator, and the gray line shows the boundary of the $\mathrm{SiO_2}$ substrate. (b) The atom-resonator coupling factor g(z) along the vertical dashed line in (a) at the lateral maximum of the resonator mode intensity at radius $R=33.7$ $\mu$m.}
\label{fig:first}
\end{figure}
The coupling between an atom and an optical mode is governed by the Jaynes–Cummings Hamiltonian \cite{reiserer2015cavity}:
\begin{equation}
        H=\hbar \omega_a\sigma^\dagger\sigma+\hbar \omega_c a^\dagger a+\hbar g(\vec{r})(\sigma a^\dagger+\sigma^\dagger a)
        \label{eq:hamiltonian}
\end{equation}
Here $\sigma = |g\rangle \langle e|$ is the atomic lowering operator, where $|g\rangle$ and $|e \rangle$ are the ground and the excited states of the atom, respectively;  $a$ is the photon annihilation operator; $\omega_a$ and $\omega_c$ are the atomic  and cavity angular resonance frequencies, respectively. The $g(\vec{r})$ factor characterizes the interaction strength between the atom and the cavity mode, which can be calculated as:
\begin{equation}
    g(\vec{r})=g_0\cdot \frac{\sqrt{\epsilon(\vec{r})}|E(\vec{r})|}{\max(\sqrt{\epsilon(\vec{r})}|E(\vec{r})|)}
\end{equation}
with $g_0=-d_{ge}\sqrt{\frac{\omega_c}{2\epsilon_0 \hbar V}}$. Here $d_{ge}$ is the effective dipole matrix element between ground and excited states; $V$ is the mode volume defined as $V=\int dr^3\frac{\epsilon(\vec{r})|E(\vec{r})|^2}{\max(\epsilon(\vec{r})|E(\vec{r})|^2)}$ \cite{englund2005controlling}, and $\epsilon(\vec{r})$ and $E(\vec{r})$ are material permittivity and electric field of the optical mode at location $\vec{r}$.
The electric field distribution of the $\mathrm{TE_{2,486}}$ mode is demonstrated in Figure \ref{fig:first}(a). The subscript numbers $2$ and $486$ indicate the radial and azimuth mode numbers, respectively.
The value of $g(\vec{r})$ at $R_0=33.7$ $\mu$m is shown in Figure \ref{fig:first}(b). It is noticed that $g(R_0,z)$ decreases very fast with $z$,  emphasizing the importance of air-cladding in resonator design.  Our resonator achieves a single-photon vacuum Rabi frequency $2g(R_0,z_0)=2\pi \times 64$ MHz around $z_0=100$ nm above the resonator while achieving a high Q with air-cladding. The single-atom cooperativity parameter is $C(R_0,z_0)=4g(R_0,z_0)^2/\kappa\gamma\approx2.7>1$. $\kappa$ and $\gamma$ here define the cavity and atomic energy decay rates.

Figure \ref{fig:simulation}(a) shows the concept of atom sensing using our high-Q resonator. Atoms from an atomic source, either a slow atomic beam from a 2D$^+$ magneto-optical trap (MOT) \cite{dieckmann1998two} or a beam of fast atoms from a thermal vapor as in Ref \cite{li2019cascaded}, pass through the microchannels, fly above the resonator, and strongly interact with it. Lithographically defined microchannels of 1-3 mm length help with atomic beam collimation and alignment with the resonator and will minimize excess contamination by alkali metals. The coupling waveguide is designed to bring the resonator into the critical coupling condition.

To understand the dynamics of an atom interacting with the resonator we simulate the known Master equation \cite{reiserer2015cavity} for the density operator. We can apply the adiabatic approximation with slow atomic beams because the time scale for atomic transit (microseconds) over the resonator is much slower than the internal state evolution time (tens of nanoseconds) given ($(g,\ \gamma,\ \kappa)/2\pi\approx$ (32, 6, 256) MHz) and confirmed by full time-dependent calculations.  The spatial coordinate of the atom, $\vec{r}(t)$, is computed classically with the surface force, while the Master equation is solved using the instantaneous value of $g(\vec{r}(t))$. We use an approximate formula for the Casimir-Polder potential for Rb atoms (Ref \cite{thompson2013coupling} supplement)
$\mathrm{U}(z)=\frac{-C_{3}\frac{\lambda_{\text{eff}}}{2\pi}}{z^3\cdot(z+\frac{\lambda_{\text{eff}}}{2\pi})}$, where $C_3=2\pi\hbar\times1500$ $\mu$m$^3$, and $\lambda_{\text{eff}}=650$ nm for SiN.

Figure \ref{fig:simulation}(b) shows the transmission of the cavity versus laser detuning for both an empty cavity and a cavity containing one stationary atom 100 nm above the resonator at $R=33.7 \mu$m.  The peak splitting is the well-known vacuum Rabi splitting that is proportional to $g(\vec{r})$ \cite{thompson1992observation}. If we set the excitation laser to zero-detuning and lock the resonator to the atomic transition, the presence of an atom will cause the transmission of the cavity to increase. With a constant excitation power, this will result in an increasing photon flux in the detector. For moving atoms, the change of the photon flux depends on $g(\vec{r}(t))$, and with single-photon counting modules as the detector, we can achieve the real-time monitoring of an atom transit.

Sample transits for atoms with different velocities are shown in Figure \ref{fig:simulation}(c). The signals are displaced in time for a clearer view. The resonator size is the same as that in Figure \ref{fig:characterization} with a Q of $1.5\times10^6$.  The extinction ratio at the critical coupling condition is assumed to be 13 dB. The horizontal and vertical velocities of the atom are set to zero. The number of transmitted photons increases as an atom flies closer to the resonator surface, and the double peak in the signal results from the two nodes in the TE$_2$ field distribution (See Figure \ref{fig:first} (a)). Atoms with a broad range of longitudinal velocities can be detected. The atom's height and longitudinal velocity determine the signal intensity and duration, respectively. The faster the atom, the closer it can be to the resonator without crashing and the more intense (but shorter) signal it creates. With these constraints, we estimate that atoms with 0.2 m/s to 30 m/s longitudinal velocities can be detected without crashing on the resonator. The atom beams with such velocities can be generated from a 2D$^+$ MOT \cite{dieckmann1998two,ramirez2006multistage} and delivered via microchannels as shown schematically in Figure \ref{fig:simulation}(a). Interestingly, the ring configuration allows us to detect the same atom twice, and the time interval can be used to calculate the longitudinal velocity of the atom as well.

While the ratio $g/\kappa \approx0.12$ achieved is not yet in the strong coupling regime, the interaction between single atoms and photons is sufficiently strong that it can  enable quantum device applications.  For example, we envision that our platform could be used for a single-photon switch by single atoms, similar to what has been demonstrated using macroscopic resonators \cite{o2013fiber}. Using a 2D$^+$ MOT with $1.8\times10^{10}$ atoms/mm$^2$/s \cite{dieckmann1998two}, which has an average longitudinal velocity around 8 m/s, we estimate that with an excitation power of 3.4 photons/$\mu$s and a Q of $1.5\times10^6$, we can achieve on average, a 50\% contrast between "ON" and "OFF" states and a single photon routing rate around 10 kHz for each microchannel-resonator pair. The routing rate is much faster than those in the typical cold-atoms-dropping approach \cite{shomroni2014all}, which requires around one second to finish one cycle. If the resonator Q can be improved to $6\times10^6$, the contrast can be 85\%, which is competitive with the cold atom systems but with much higher repetition rates due to the absence of a long dead time. The switch can be activated by the entry of a single atom into the vicinity of the resonator and by using fast electronics to detect the rise of detected photons in the first 100 ns time bin.

\begin{figure}[t]
\centering
\includegraphics[width=\linewidth]{figure3new_3.pdf}
\caption{(a) The schematic of the single-atom sensing platform. (b) Transmission spectra of excitation photons, with $g/2\pi=32$ MHz, loaded $Q=1.5\times10^6$, and 52.9 pW optical excitation power under the ideal critical coupling condition. The cavity is locked on resonance for atom sensing. (c) The detector signal when an atom flies above the resonator. The reference black line is the background signal from the imperfect critical coupling condition. Blue line: $v=3$ m/s, $h_0=150$ nm; Red dash: $v=1.5$ m/s, $h_0=190$ nm; Orange dot: $v=0.8$ m/s, $h_0=230$ nm. The excitation power is  52.9 pW. The vertical and horizontal velocities are set to be zero. $h_0$ is the vertical distance between atoms and the top resonator surface. (d) The detector signal when an atom flies above a racetrack resonator (shown in inset, with extinction ratio of 13 dB in the critical coupling regime), with velocity $v=300$ m/s, $h_0$ = $100$ nm, and excitation power of 231.8 pW. The resonator is locked to $w_0+kv_a$ to compensate the Doppler effect.}
\label{fig:simulation}
\end{figure}

We also studied the potential use of racetrack resonators to detect thermal atomic beams generated by microchannel-collimation of a 100 \degree C Rb vapor \cite{li2019cascaded}. Atomic vapors have recently been proposed for cavity quantum electrodynamics (QED) applications \cite{alaeian2020cavity}.
The advantage of our approach is the ability to place atoms with lithographic precision at a discrete location above the resonator. We designed a racetrack resonator with a R = 20 $\mu$m ring section and 30 $\mu$m straight sections and align its straight sections to our microchannels (see Figure \ref{fig:simulation}(d) inset). In this way, the collimated thermal atoms with an average speed of 300 m/s will fly along the 30 $\mu$m straight section and strongly interact with the resonator for $\sim$ 100 ns. The Master equation simulation of a thermal atom transit without adiabatic approximation is shown in Figure \ref{fig:simulation}(d). The setup is similar to Figure \ref{fig:simulation}(a) and the Q of the racetrack resonator is assumed to be $1.5\times10^6$, with the transverse and vertical velocity set to be zero.  The initial peak is the Rabi oscillation resulting from an atom entering the regime with a strong evanescent field of the racetrack. If we monitor photons transmitted in 100 ns time bins and assume a 50\% detection efficiency, we should find the number of photons jumping from 2.5 to $\sim$ 6, which indicates an atom transit. We have fabricated racetrack resonators  with $\sim 7\times10^5$ loaded Q, and the optimization of the fabrication process for achieving Q $\sim1.5\times10^6$ is currently underway.

Our simulations reveal that miniature atomic beams are a promising candidate to achieve a strong interaction with the microresonator at the single-photon level. With the achieved Q and using multiple channel-resonator pairs together, one can imagine generating multi-photon states on chip in a simple and scalable architecture.  Without the requirement of atom trapping, ultra-high vacuum would not be needed. Thus, we believe that the platform reported here can set the stage for a new class of scalable quantum devices on chip using atoms and photons.

\bigskip
\noindent
{\textbf{Funding:}} This work was supported by the Air Force Office of Scentific Research (AFOSR) Grant no. FA9550-19-1-0228.  This work was performed in part at the Georgia Tech Institute for Electronics and Nanotechnology, a member of the National Nanotechnology Coordinated Infrastructure (NNCI), which is supported by the National Science Foundation (ECCS-1542174).

redpajama_set_name: RedPajamaArXiv


Susan holds a powerful vision—The Cultivation of World Peace Through Inner Peace—as it is expressed through the Teachings and Practices of the Agape Movement/New Thought Ageless Wisdom. She has been an Agape Minister since 2009 and an Agape Licensed Spiritual Practitioner since 2002, serving the community both individually and collectively.
For over 14 years, Susan has taught numerous classes and developed many workshops at Agape. She helps design and manage the delivery of courses and programs for Agape University. As Staff minister, her role includes Curriculum Development, Faculty/Facilitator Training, Professional Practitioner Studies Program Coordinator and Ministerial Education & Instruction. Susan is currently teaching "Introduction to Transcendent Masters", "Prayer as a Way of Life" and "Introduction to Chaplaincy – for Ministers in Training".
In 2009 Susan began working in hospice care as a certified Chaplain/Spiritual Counselor, supporting families and patients moving through their final transition. She provides bereavement services and facilitates grief workshops to families that have lost loved ones. She also holds a specialized certification in the field of Palliative Care Chaplaincy.
Susan is a single mother of four adult children and currently resides in beautiful Laguna Beach, CA. She loves hiking, cycling, yoga and beach walks. She has a strong practice in meditation, including the Vipaassana technique, Michael Beckwith's Life Visioning Process and prayer.


There is a common phrase I head from pastors, "as we grow larger, we must grow smaller." This is typically around the implementation of home-based groups as a means to facilitate relationships, personal ministry, and try to develop a sense of community within the corporate whole. While I agree this is a great means by which to accomplish the objectives, there is a more important step. Community must start with you and I at the individual level. How can a small group come together if each of us cannot accomplish this in a one-to-one scenario What do I mean by this?
First, we must live intentional lives. Each day we must go about our day, whether at work, at school, or whatever occupies our day, as if God has a purpose for the day. He wants us to be cognizant of people who need a touch by God and we are the conduit for His purposes.
It is really that simple. If we love people then this unique outward-forcused element (in our self-centered society) draws people to you. The door begins to swing open for you to talk about the faith which is at the core of your heart. There is a saying along the lines of "people don't care how much you know until they know how much you care." Be intentional each day, make room in your life for others, and be sensitive to the leadings of the Spirit. You will see great things and Community will be birthed, both in the one-on-one, the small group, and finally the corporate gathering.


text:
Q: Asp.Net MVC Upload a Video File Size Greater than 2MB I has a one API Solution(Target Framework 4.0) and one MVC Solution(Target Framework 4.5.1) of job portal. In profile summery I need to upload a video but the problem I faced , I can not upload a video file which size is greater than 2MB. So, I search on internet and find a solution is that change the web.config on Api Solutions with this as mension below,
Web.config
<system.web>
 <compilation debug="true" targetFramework="4.0" />
 <httpRuntime executionTimeout="108000" maxRequestLength="2147483647"/>
</system.web>
 <system.webServer>
    <!-- maxAllowedContentLength = 2GB (the value is in Bytes) -->
    <security>
      <requestFiltering>
        <requestLimits maxAllowedContentLength="2147483647" />
      </requestFiltering>
    </security>
</system.webServer>

after apply this same problem occurred "Failed!The remote server returned an error: (500) Internal Server Error."
Here my Controller Code on MVC solutions
CandidateController
 #region UPDATE CANDIDATE PROFILE SUMMERY
        [HttpPost]
        public string UpdateProfileSummery(string info)
        {
            string Res = "";
            string Token = "";string FileName="";
            ResultInfo<string> ResultInfo = new Models.ResultInfo<string>();
            CandidateProfileSummery ProfInfo = new CandidateProfileSummery();
            try
            {
                if (info != "" && info != null)
                {
                    ProfInfo = JsonConvert.DeserializeObject<CandidateProfileSummery>(info);

                    //ProfInfo.Gender = ProfInfo.NamePrefix == "Mr." ? "male" : "female";
                    if (Request.Files.Count > 0)
                    {
                        //  Get all files from Request object
                        HttpFileCollectionBase files = Request.Files;
                        if (User.Identity.Name != "" && User.Identity.Name != null)
                        {
                            string[] arr = User.Identity.Name.Split('|');
                            Token = arr[0];
                            ProfInfo.ID = Convert.ToInt64(arr[3]);
                        }
                        for (int i = 0; i < files.Count; i++)
                        {
                            HttpPostedFileBase file = files[i];
                            int fileSizeInBytes = file.ContentLength;
                            FileName = file.FileName;
                            if (file.FileName.ToLower().Contains(".mp4")|| file.FileName.ToLower().Contains(".mov") || file.FileName.ToLower().Contains(".wmv") || file.FileName.ToLower().Contains(".avi") || file.FileName.ToLower().Contains(".flv") || file.FileName.ToLower().Contains(".mkv") || file.FileName.ToLower().Contains(".3gp"))
                            {
                                ProfInfo.VideoType = Path.GetExtension(file.FileName);
                                if (ProfInfo.VideoType != ".mp4" && ProfInfo.VideoType != ".MP4" && ProfInfo.VideoType != ".MOV" && ProfInfo.VideoType != ".mov" && ProfInfo.VideoType != ".WAV" && ProfInfo.VideoType != ".wmv" && ProfInfo.VideoType != ".AVI" && ProfInfo.VideoType != ".avi" && ProfInfo.VideoType != ".FLV" && ProfInfo.VideoType != ".flv" && ProfInfo.VideoType != ".MKV" && ProfInfo.VideoType != ".mkv" && ProfInfo.VideoType != ".3GP" && ProfInfo.VideoType != ".3gp")
                                {
                                    Res = "Failed! File type should be video file.";
                                }

                                else
                                {
                                    MemoryStream target = new MemoryStream();
                                    file.InputStream.CopyTo(target);
                                    byte[] fileData = target.ToArray();
                                    ProfInfo.VD = fileData;
                                }
                            }
                            else
                            {
                                ProfInfo.FileType = Path.GetExtension(file.FileName);
                                if (ProfInfo.FileType != ".png" && ProfInfo.FileType != ".jpeg" && ProfInfo.FileType != ".jpg" && ProfInfo.FileType != ".gif")
                                {
                                    Res = "Failed! File type should be jpeg/jpg or png.";
                                }

                                 else
                                {

                                    MemoryStream target = new MemoryStream();
                                    file.InputStream.CopyTo(target);
                                    byte[] fileData = target.ToArray();
                                    ProfInfo.DP = fileData;
                                }
                            }

                        }

                        string fname;
                        if (Request.Browser.Browser.ToUpper() == "IE" || Request.Browser.Browser.ToUpper() == "INTERNETEXPLORER")
                        {
                            string[] testfiles = FileName.Split(new char[] { '\\' });
                            fname = testfiles[testfiles.Length - 1];
                        }
                        else
                        {
                            //In this section I got error when file size > 2MB
                            string JsonRes = WebService.Postfile(ApiUrl + "Jobseeker/updateJbsProfileSummery?Token=" + Token, JsonConvert.SerializeObject(ProfInfo));
                            ResultInfo = JsonConvert.DeserializeObject<ResultInfo<string>>(JsonRes);
                            if (ResultInfo.ErrorCode == 200)
                            {
                                Res = "Success! " + ResultInfo.Info;
                            }
                            else
                            {
                                Res = ResultInfo.Info;
                            }
                        }
                    }
                    else
                    {
                        if (User.Identity.Name != "" && User.Identity.Name != null)
                        {
                            string[] arr = User.Identity.Name.Split('|');
                            Token = arr[0];
                            ProfInfo.ID = Convert.ToInt64(arr[3]);
                        }

                        string JsonRes = WebService.Postfile(ApiUrl + "Jobseeker/updateJbsProfileSummery?Token=" + Token, JsonConvert.SerializeObject(ProfInfo));
                        ResultInfo = JsonConvert.DeserializeObject<ResultInfo<string>>(JsonRes);
                        if (ResultInfo.ErrorCode == 200)
                        {
                            Res = "Success! " + ResultInfo.Info;
                        }
                    }
                }
                else
                {
                    Res = "Failed! Information is not provided.";
                }

            }
            catch (Exception ex)
            {

                Res = "Failed!" + ex.Message;
            }
            return Res;
        }
        #endregion

Is it any problem on Api solution webconfig file "maxRequestLength" not supported on target framework 4.0
If anyone solve my problem, Thank You In Advanced

A: add this config
public static IWebHostBuilder CreateWebHostBuilder(string[] args) =>
WebHost.CreateDefaultBuilder(args)
.UseStartup<Startup>()
.UseKestrel(options =>
{
    options.Limits.MaxRequestBodySize = 52428800; //50MB
});

for more way visit this link click here

redpajama_set_name: RedPajamaStackExchange


With the release of the NSW Budget for 2018-19, here are our top 10 budget measures.
A record $8.0 billion investment in health infrastructure over four years to continue the major capital program to provide new facilities, upgrades and redevelopments including Liverpool Hospital to get a $740 million world-class health, research and education precinct by 2026; $700 million for a new mental health infrastructure program; $1 billion for 950 more nurses and 300 doctors in state hospitals; $8 billion for capital works across 40 hospitals.
The Government is planning and delivering more than 170 new or upgraded schools to accommodate strong enrollment growth, at an estimated cost of $6.0 billion over four years.
Investing in a landmark $156.5 million Parents Package to improve the well-being of new parents and their babies.
$1.5 billion for bus services throughout New South Wales, including regional and metropolitan services, school services and funding of new and replacement buses.
The Government will invest more than $648.0 million in the More Trains, More Services program to improve the accessibility and capacity of state-wide train services.
From 1 July 2018 the tax-free threshold for payroll tax will increase from $750,000 to $850,000. It will continue to increase by $50,000 every year to reach $1.0 million in 2021-22. The increased thresholds will reduce the number of NSW small businesses subject to payroll tax by around 2,000 in 2018-19. This will grow to around 5,000 in 2021-22.
Funding for the New South Wales transition to the full National Disability Insurance Scheme (NDIS) on 1 July 2018 including $3.2 billion in 2018-19 as the NSW Government contribution to support the transition to the NDIS. This consists of an estimated $2.7 billion cash contribution and $477.5 million in kind contribution through services provided by NSW Government agencies.
$288.2 million over four years to further support the re-engineering of the NSW Police Force and provide the Police Commissioner with the flexibility to deploy resources according to need and effectively address and respond to crime.
An additional $61 million over 4 years for homelessness programs, and $33.1 million over 4 years to support Aboriginal housing.
100,000 fee-free apprenticeships will be created through a $285 million fund.


1 NUMBER: GROUP: Vehicle Performance DATE: November 25, 2015 This bulletin is supplied as technical information only and is not an authorization for repair. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without written permission of FCA US LLC. THIS BULLETIN SUPERSEDES SERVICE BULLETIN REV. B, DATED SEPTEMBER 29, 2015, WHICH SHOULD BE REMOVED FROM YOUR FILES. ALL REVISIONS ARE HIGHLIGHTED WITH **ASTERISKS** AND INCLUDE ADDITIONAL DTCs, REPAIR PROCEDURE AND NEW LOPS. THIS SERVICE BULLETIN IS ALSO BEING RELEASED AS RAPID RESPONSE TRANSMITTAL (RRT) ALL APPLICABLE SOLD AND UN-SOLD RRT VIN's HAVE BEEN LOADED. TO VERIFY THAT THIS RRT SERVICE ACTION IS APPLICABLE TO THE VEHICLE, USE VIP OR PERFORM A VIN SEARCH IN TECHCONNECT. ALL REPAIRS ARE REIMBURSABLE WITHIN THE PROVISIONS OF WARRANTY. HELP USING THE witech DIAGNOSTIC APPLICATION FOR FLASHING AN ECU IS AVAILABLE BY SELECTING HELP THEN HELP CONTENTS AT THE TOP OF THE witech DIAGNOSTIC APPLICATION WINDOW. THE witech SOFTWARE IS REQUIRED TO BE AT THE LATEST RELEASE BEFORE PERFORMING THIS PROCEDURE. SUBJECT: Flash: 3.0L Powertrain Diagnostic And System Enhancements OVERVIEW: This bulletin involves reprogramming the Powertrain Control Module (PCM) with the latest available software. **It also involves the cleaning or replacement of the Exhaust Gas Temperature (EGT) Sensor 1/2 and/or Catalyst Temperature Sensor if necessary depending on Diagnostic Trouble Codes (DTCs) that may have set.** MODELS: 2015 (WK) Jeep Grand Cherokee NOTE: This bulletin applies to vehicles equipped with a 3.0L diesel engine (Sales Code EXF) and 8 speed transmission (Sales Code DFD).
3 NOTE: The parts listed above may be needed to complete the repair, they are not required to be changed.** REPAIR PROCEDURE: 1. **Using witech, check for any codes setting in the PCM and record them on the repair order. If necessary, perform a vehicle scan report and save it for your records. 2. Using witech, Check the PCM calibration and see if it is up to date. Does the PCM software need to be updated? a. Yes>>> Proceed to Step #3. b. No>>> Proceed to Step #7.** NOTE: Install a battery charger to ensure battery voltage does not drop below 13.2 volts. Do not allow the charging voltage to climb above 13.5 volts during the flash process. CAUTION: Do not interrupt the software update process in any way once it has begun. It may cause permanent damage to the PCM which will require replacement. 3. Reprogram the PCM with the latest available software. Detailed instructions for flashing control modules using the witech Diagnostic Application are available by selecting the HELP tab on the upper portion of the witech window, then HELP CONTENTS. This will open the Welcome to witech Help screen where help topics can be selected. NOTE: If the module is up to date and no flashes are available use inspection LOP CW to close the active RRT. 4. Clear all DTCs that may have been set in any module due to reprogramming. The witech application will automatically present all DTCs after the flash and allow them to be cleared. 5. Under the PCM System Tests perform the SCR DEF Tank Fluid Level Reset procedure. 6. Turn the ignition off for 35 seconds to complete the flash. 7. Verify the Transmission Control Module (TCM) is programmed with the latest available software. Refer to all applicable published service bulletins for detailed repair procedures and labor times regarding updating the TCM software. 8. **Refer back to the vehicle scan report recorded in Step #1. Is DTC P Catalyst Efficiency (Bank 1), found setting active or stored in the PCM memory? a. Yes>>> Proceed to Step #9. b. No>>> Proceed to Step # Remove the EGT Sensor 1/2 located in the inlet of the Diesel Particulate Filter (DPF)/Diesel Oxidation Catalyst (DOC) assembly. Refer to detailed removal procedures available in DealerCONNECT> TechCONNECT> Service Info Section 11 - Exhaust System> Sensor, Exhaust Temperature> Removal> Exhaust Gas Temperature Sensor 1/ Remove the Catalyst Temperature Sensor located in the middle of the Diesel Particulate Filter (DPF)/Diesel Oxidation Catalyst (DOC) assembly. Refer to detailed removal procedures available in DealerCONNECT> TechCONNECT> Service Info Section 11 - Exhaust System> Sensor, Exhaust Temperature> Removal> Catalyst Exhaust Temperature Sensor.
4 Inspect the sensor body and probe for any signs of damage or excessive soot. See (Fig. 1). Fig. 1 EGT Sensor Bank 1 Sensor Excessive soot blocking sensor ports 12. Was excessive soot found on the sensor? a. Yes>>> Proceed to Step #13. b. No>>> Proceed to Step # Using shop air set to a maximum of 80 psi, clean all excessive soot from the sensor probe. 14. Using a suitable multi-meter with appropriate test probes, test the resistance between the sensor connector terminals 1 and 2. With the sensor at room temperature, F (18-25 C), the resistance should measure between 200 and 240 ohms. 15. Is the temperature sensor resistance within specifications? a. Yes>>> Install the original EGT sensor 1/2 and/or Catalyst Temperature Sensor. Refer to detailed installation procedures available in DealerCONNECT> TechCONNECT> Service Info Section 11 - Exhaust System> Sensor, Exhaust Temperature> Installation> Exhaust Gas Temperature Sensor 1/2. b. No>>> Install a new EGT sensor 1/2 and/or Catalyst Temperature Sensor. Refer to detailed installation procedures available in DealerCONNECT> TechCONNECT> Service Info Section 11 - Exhaust System> Sensor, Exhaust Temperature> Installation> Exhaust Gas Temperature Sensor 1/ Refer back to the vehicle scan report recorded in Step #1. Were DTCs P System Too Lean (Bank 1), P System Too Rich (Bank 1), P026C-00 Fuel Injection Quantity Lower Than Expected, and/or P026D-00 Fuel Injection Quantity Higher Than Expected, found setting active or stored in the PCM memory? a. Yes>>> Further diagnosis and repair is required. Refer to all applicable published TSBs or service information in DealerCONNECT/TechCONNECT regarding these DTCs. The bulletin is now complete.
OVERVIEW: This bulletin involves installing heated seat heating element repair kits.
NOTE: This bulletin applies to vehicles equipped with tilt steering (sales code SUA) and built on or after January 14, 2002.
OVERVIEW: This bulletin involves installing a new antilock brake control module.
OVERVIEW: This bulletin involves installing a shim package and a tilt head housing assembly in the steering column upper tilt head.