A simple, lock-free object-pool


Recently, I was using Apache Thrift for a distributed high performance C++ application. Apache Thrift is an RPC for calling functions on other ends of networks and across different languages. On a single thread, using an RPC is a bad idea, if performance is the goal. So the way to get high performance from such a system is by putting multiple clients in many threads. However, the problem is that Apache Thrift’s clients are not thread-safe! What do we do?

The solution is an object pool of clients, and since the application is a high-performance, I chose it to be a lock-free object pool. Lock-free means that no mutexes are involved in the design, but only atomic variables. I couldn’t find anything out there, so I implemented my own, which I hope will be useful to others, too. While this design is lock-free, it’s not “wait-free”. Meaning that, obviously, if all objects in the pool are used, the system will block/wait until an object is available, or the programmer has to setup an asynchronous waiting mechanism. It’s possible to “try” to get an object in this design.

In the following I’ll discuss my design of this object pool.

The design

The design of this object pool is simple.

  • There’s a vector of size N that holds N initialized objects. The initialization of the objects is done in the constructor, by passing a functor/lambda that intializes every object and puts them in the vector (hence, the objects must be at least move-constructible).
  • I used a lock-free queue from boost. The queue has integers ranging from 0 to N-1. In order to check whether an object is available, its index in the vector has to be in this queue.
  • If borrowing is successful, a new object “BorrowedObject” will be returned, which contains a pointer to the borrows object. This is a safe mechanism, where returning to the pool is done automatically when this object is destroyed.

Shall we look at some code?

template <typename T>
class ObjectPool
    AvailableObjectsQueueType availableObjectsQueue;
    std::size_t               objectCount;
    std::vector<T>            objects;
    std::atomic_uint64_t      availableObjectsCount;
    std::atomic_bool          shutdownFlag;

    friend BorrowedObject<T>;
    ObjectPool(std::size_t Size, std::function<T(std::size_t)> objectInitializers);
    ObjectPool()                  = delete;
    ObjectPool(const ObjectPool&) = delete;
    ObjectPool(ObjectPool&&)      = delete;
    ObjectPool& operator=(const ObjectPool&) = delete;
    ObjectPool& operator=(ObjectPool&&) = delete;

    BorrowedObject<T> borrowObj(uint64_t sleepTime_ms = 0);
    BorrowedObject<T> try_borrowObj(bool& success);
    std::size_t       size() const;
    uint64_t    getAvailableObjectsCount() const;
    std::vector<T>&   getInternalObjects_unsafe();
    void              shutdown();

As you can see, the class is not copyable or movable, for simplicity. Besdies that, the following methods can be seen:

  • The constructor: Takes the size of the pool, and a functor/lambda to initialize the objects. The parameter in this functor/lambda is of type std::size_t. The purpose of this is to be able to have the initialization done as a function of the number of the object in the pool.
  • borrowObj(): A blocking method for borrowing an object from the pool.
  • try_borrowObj(): A non-blocking method for borrowing an object from a the pool, returns a null object on failure.
  • shutdown(): Shutdown the object pool, which calls the destructor of all objects and prevents borrowing further.

You can find the full implementation here.


Here’s a simple design of a lock-free object pool. No more than 200 lines. The feature I find cool in this object pool is that the objects themselves are not being passed around, but only their indices, which can be done quite efficiently on most modern CPUs.

Safe resource allocation and deallocation in C++ (C++11 and C++03)


Back then before 2010, one always used Valgrind to make sure that their C++ program isn't leaking memory. There's a whole modern way of using C++ that doesn't even make you need that. If you're using a C++11 program (and even if you're not), and you still require to keep checking whether your code is leaking memory, then you're most likely doing it all wrong. Keep reading if you wanna know the right way that saves you the trouble having to memory check all the time, and uses true object-oriented programming.

Basically this artice is about the concept named RAII, Resource Allocation Is Initialization, and why it's important from my perspective.

The golden rules of why you should do this

My Golden Rules in C++ development:

  1. Humans do mistakes, and just an arrogant would claim that he doesn't (why else do we have something called "error handling"?)
  2. Things can go wrong, no matter how robust your program is, and how careful you are, and you can't plan every possible outcome
  3. A problem-prone program is no better than a program with a problem; so why bother writing a program with problems?

Once you embrace these 3 rules, you'll never write bad code, because your code will be ready for worst case scenario.

In the last few years, I never found a single lost byte in my Valgrind-analysed programs; and I'm talking about big projects, not in the single class level. The difference will be clear soon.

I'm going to start from simple cases, up to more complicated scenarios.

Scenario 1: If you're creating and deleting objects under pointers

Consider the following example:

void DoSomethingElse(int* var)
    std::cout << *x << std::endl;
    //... do stuff with x
void DoSomething()
    int* x = new int;
    delete x;

Let me make this as clear as possible: If you ever, ever use a new followed by delete… you're breaking all the 3 rules we made up there. Why? Here are the rules and how you're breaking them:

1. You may do the mistake of forgetting to write that delete
2. DoSomethingElse() might throw an exception, and hence that delete may not be called.
3. This is a problem prone design, so it's a program with a problem.

The right way to do this: Smart pointers!

What are smart pointers?

I'm sure you've heard of them before, but if you haven't, the idea is very simple. If you define, for example, an integer like this:

void SomeFunction()
    int i = 0;
    // do stuff with i
} //here you're going out of the scope of the function

You never worry about deleting i. The reason is that once i goes out of scope, it's deleted automatically (through a destructor). Smart pointers are just the same. They wrap your pointer, such that they are deleted once they are out of scope. Let's look at our function DoSomething() again with smart pointers:

void DoSomething()
    std::unique_ptr<int> x(new int); //line 1
    DoSomethingElse(x.get());        //line 2
} //once gone out of scope, x will be deleted automatically, 
  //the destructor of unique_ptr will delete the integer

That's all the change you have to do, and you're done! In line 1, you're creating a unique_ptr, which will encapsulate your pointer. The reason why it's "unique" will become soon clear. Once the a unique_ptr goes out of scope, it'll delete the object under it. So you don't have to worry! This way, the 3 Golden Rules are served. In line 2, we're using x.get() instead of x, because the get() method will return the raw pointer stored inside the unique_ptr. If you'd like to delete the object manually, use the method x.reset(). The method reset() can take a parameter to another pointer, or can be empty to become nullptr.

PS: unique_ptr is C++11. If you're using C++03, you could use unique_ptr from the boost library

Why is it called "unique"?

Generally, multiple pointers can point to the same object. So, going back to the initial example, the following is a possible scenario:

void DoSomething()
    int* x = new int(1);
    int* y = x; //now x and y, both, point to the same integer
    std::cout << *x << "\t" << *y << std::endl; //both will print 1
    *x = *x + 1; //add 1 to the object under x
    std::cout << *x << "\t" << *y << std::endl; //both will print 2
    delete x; //you delete only 1 object, not 2!

But can you do this with unique_ptr? The answer is *no*! That's why it's called unique, because it's a pointer that holds complete *ownership* of the object under it (the integer, in our case), and it's unique in that. If you try to do this:

void DoSomething()
    std::unique_ptr<int> x(new int);
    std::unique_ptr<int> y = x; //compile error!

your program won't compile! Think about it… if this were to compile, who should delete the pointer when the function ends, x or y? It's ambiguous and dangerous. In fact, this is exactly why auto_ptr was deprecated in C++11. It allowed the operation mentioned before, which effectively *moved* the object under it. This was dangerous and unclear semantically, which is why it's deprecated.

On the other hand, you can move an object from one unique_ptr to another! Here's how:

void DoSomething()
    std::unique_ptr<int> x(new int);
    std::unique_ptr<int> y = std::move(x);
    //now x is empty, and y has the integer, 
    //and y is responsible for deleting the integer

with std::move(x), you convert x to an rvalue reference, indicating that it can be safely moved/modified.

Shared pointers

Since we established that unique pointers are "unique", let's introduce the solution to the case where multiple smart pointers can point to the same object. The answer is: shared_ptr. Here's the same example:

void DoSomething()
    std::shared_ptr<int> x(new int(2)); //the value of *x is 2
    std::shared_ptr<int> y = x; //this is valid!
    //now both x and y point to the integer

Who is responsible for deleting the object now? x or y? Generally, any of them! The way shared pointers work is that they have a common reference counter. They count how many shared_ptrs point to the same object, and once the counter goes to zero (i.e., the last object goes out of scope), the last object is responsible for deleting.

In fact, using the new operator manually is highly discouraged. The alternative is use make_shared, which covers some corner cases of possible memory leaks. For example, if the constructor of the class use in shared_ptr has a multi-parameter constructor that may throw an exception. Here's how make_shared is used:

void DoSomething()
    std::shared_ptr<int> x = std::make_shared<int>(2); //the value of *x is 2
    std::shared_ptr<int> y = x; //this is valid!
    //now both x and y point to the integer


Note: Shared pointers change a fundamental aspect of C++, which is "ownership". When using shared pointers, it may be easy to lose track of the object. This is a common problem in asynchronous applications. This is a story for another day though.

Note 2: The reference counter of shared_ptr is thread-safe. You can pass it among threads with no problems. However, the thread-safety of the underlying object it points to is your responsibility.

Scenario 2: I don't have C++11 and I can't use boost

This is a common scenario in organizations that maintain very old software. The solution to this is very easy. Write your own smart pointer class. How hard can it be? Here's a simple quick-and-dirty example that works:

template <typename T>
class SmartPtr
    T* ptr;
    // disable copying by making assignment and copy-construction private
    SmartPtr(const SmartPtr& other) {} 
    SmartPtr& operator=(const SmartPtr& other) {return SmartPtr();}
    SmartPtr(T* the_ptr = NULL)
        ptr = NULL;
    void reset(T* the_ptr = NULL)
        if(ptr != NULL)
            delete ptr;
        ptr = the_ptr;
    T* get() const //get the pointer
        return ptr;
    T& operator*()
        return *ptr;
    T* release() //release ownership of the pointer
        T* ptr_to_return = ptr;
        ptr = NULL;
        return ptr_to_return;


and that's it! The method release(), I haven't explained. It simply releases the pointer without deleting it. So it's a way to tell the unique_ptr: "Give me the pointer, and forget about deleting it; I'll take care of that myself".

You can now use this class exactly like you use unique_ptr. Creating your own shared_ptr is a little more complicated though, and depends on your needs. Here's the questions you need to ask yourself on how to design this:

  1. Do you need multithreading support? shared_ptr supports thread-safe reference counting.
  2. Do you need to just count references, or also track them? For some cases, one might need to track all references with something like a vector of references or a map.
  3. Do you need to support release()? Releasing is not supported in shared_ptr, since it depends on reference counting, there's no way to tell other instances to release.

More requirements will require more work, especially that prior to C++11, multithreading was not in the C++ standard, meaning that you're gonna have to use system-specific C++.

For a strictly single-threaded application with C++03, I created a shared pointer implementation that supports releasing. Here's the source code.

Scenario 3: Enable a flag, do something, then disable it again

Consider the following code, which is common in GUI applications:

void GUIClass::addTheFiles(const std::vector<FileType>& files)
    for(unsigned i = 0; i < files.size(); i++)

While this looks legitimate way to do things, it's not. This is absolutely no different that the pointer situation. What if adding fails? Either because of a memory problem, or because of some exception? The function will exit without reenabling that button, and your program will become unusable and the user will probably have to restart it.

Solution? Just like before. Don't do it yourself, and get the destructor of some class to do it for you. Let's do this. What do we need? We need a class that will call a function with a reference to some variable on exit. Consider the following class:

class AutoHandle
    std::function<void()> func;
    bool done = false; //used to make sure the call is done only once
    // disable copying and moving
    AutoHandle(const AutoHandle& other) = delete;
    AutoHandle& operator=(const AutoHandle& other) = delete;
    AutoHandle(AutoHandle&& other) = delete;
    AutoHandle& operator=(AutoHandle&& other) = delete;
    AutoHandle(const std::function<void()>& the_func)
        func = the_func;
    void doCall()
            done = true;


Let's use it!

void GUIClass::addTheFiles(const std::vector<FileType>& files)
    AutoHandle ah([this](){this->enableButton();}); //lambda function that contains the function to be called on exit
    for(unsigned i = 0; i < files.size(); i++)
} //Now, the function enableButton() will definitely be called definitely on exit.


This way, you guarantee that enableButton() will be called when the function exits. This whole thing here is C++11, but doing it in C++03 is not impossible, though I completely sympathize with you if you feel it's too much work for such a simple task, because:

  1. Since there's no std::function in C++03, we're gonna have to make that class template that accepts functors (function objects)
  2. Since there's no lambda functions in C++03, we're gonna have to make the call a new functor for every case (depending on how much you would like to toy with templates, also another big topic)

Just for completeness, here's how you could use AutoHandle in C++03 with a Functor:

template <typename CallFunctor, typename T>
class AutoHandle
    bool done; //used to make sure the call is done only once
    CallFunctor func;
    // disable copying by making assignment and copy-construction private
    AutoHandle(const AutoHandle& other) {}
    AutoHandle& operator=(const AutoHandle& other) {return *this;}
    AutoHandle(T* caller) : func(CallFunctor(caller))
        done = false;
    void doCall()
            done = true;

struct DoEnableButtonFunctor
    GUIClass* this_ptr;
    DoEnableButtonFunctor(GUIClass* thisPtr)
        this_ptr = thisPtr;
    void operator()()


Here's how you can use this:

void GUIClass::addTheFiles(const std::vector<FileType>& files)
    AutoHandle<DoEnableButtonFunctor,GUIClass> ah(this); //functor will be called on exit
    for(unsigned i = 0; i < files.size(); i++)
} //Now, the function enableButton() will definitely be called definitely on exit.

Again, writing a functor for every case is a little painful, but depending on the specific case, you may decide. However, in C++11 projects, there's no excuse. You can easily make your code way more reliable with lambdas.

Remember, you're not bound to the destructor to do the calls. You can also call doCall() yourself anywhere (equivalent to reset() in unique_ptr). But the destructor will *guarantee* that the worst case scenario is covered if something went wrong.

Scenario 4: Opening and closing resources

This could even be more dangerous than the previous cases. Consider the following:

void ReadData()
    int handle = OpenSerialPort("COM3");


This form is quite common in old libraries. I faced such a format with the HDF5 library. If you read the previous sections, you'll get the problem with such usage and the idea on how to fix it. It's all the same. You *should never* close resources manually. For my HDF5 problem, I wrote a SmartHandle class that guarantees that HDF5 resources are correctly closed. Find it here. Of course, the formal right way to do this is to write a whole wrapper for the library. This may be an over-kill depending on your project constraints.

Notes on Valgrind

If you follow these rules, you'll be 100% safe with the resources you use. You rarely will ever need to use Valgrind. However, when you write the classes that we talked about (such as AutoHandle, SmartPtr, etc), it's very, very important not only to test it with Valgrind, but also to write good tests that will cover every corner case. Because once you do these classes right, you never have to worry about them. If you do them wrong, the consequences could be catastrophic. Surprising? Welcome to object-orient programming! This is exactly what "separation of concerns" mean.


Whenever you have to do, then undo something, then keep in mind that you shouldn't have this manually done. Sometimes it's safe and trivial, but many times it may lead to simply bad and error-prone design. I covered a few cases and different ways to tackle the issue. By following these examples, I guarantee that your code will become more compact (given that you're using C++11) and way more reliable.

Just a side-note on standards and rules

Sometimes when I discuss such issues related to modern designs, people claim that they have old code, and they don't want to change the style of the old code for consistency. Other times they claim that this would be violating some standard issued by some authority. All these reasons don't show that doing or not doing this is right or wrong. It just shows that someone doesn't want to do them because they're "following the rules". To me (and I can't emphasize enough that this is my opinion), it just is like asking someone "Why do you do this twice a day, how does it help you?", and get the answer "Because my religion tells me I have to do it". While I respect all ideologies, such an answer is not a rational answer that justifies the pros and cons of doing something. That answer doesn't tell why doing that twice a day helps that guy's health, physically or mentally or otherwise. He just is following a rule *that shouldn't be discussed*. I'm a rational person and I like discussing things by putting them on the table, which helps in achieving the best outcome. If someone's answer is "I have a standard I need to follow it", then that effectively and immediately closes the discussion. There's nothing else to add. Please note that I'm not encouraging breaking the rules here. If your superior tells you how to do it, and you couldn't convince them otherwise, then just do what he tells you, because most likely your superior has a broader picture of other aspects of a project that don't depend on code only.


Can I use Qt Creator without Qt?

Qt Creator… the best IDE for developing C and C++ I’ve ever seen in my life. Since I like it that much, I’m sharing some of what I know about it.

DISCLAIMER: I’m not a lawyer, so don’t hold me liable for anything I say here about licensing. Anything you do is your own responsibility. 

What does using Qt Creator without Qt mean?

It simply means that you don’t have to install or use the Qt libraries, including qmake. There are many reasons why that may be the case:

  • You may have an issue with licensing since qmake is LGPL licensed
  • You may not have the possibility to install qmake alone without its whole gear, as is the case in Windows
  • You may not want to compile the whole Qt libraries if the pre-compiled versions that work with your compiler is not available

While I love Qt and use it all the time, I follow the principle of decoupling my projects from libraries if I don’t use them. But since I love Qt Creator, I still want to use it! Reasons will become clear below.

What are the ingredients of this recipe?

  1. Qt Creator
  2. CMake
  3. A compiler (gcc, MinGW or Visual Studio, or anything else)

You don’t need to download the whole Qt SDK. Just Qt Creator. It’s about 90 MB.

Basic steps

After installing the 3 ingredients, make sure that Qt Creator recognized that CMake exists on the computer. The next picture (click on it to magnify it) is how it looks like if CMake was found. If it doesn’t find CMake, on Windows, most likely the reason is that you chose in the installation not to add CMake to the system’s PATH. Eventually, you can just add it manually if it can’t be found automatically.

Next, make sure that Qt recognizes the compiler and the debugger as you see in the next pictures. Again, you can add them manually.

For Visual Studio to be found automatically, I guess the environment variable VS140COMNTOOLS has to be defined. “140” is version 14 of Visual Studio, which is the version number of Visual Studio 2015. It’s defined by default when Visual Studio is installed. For MinGW to be detected automatically, the bin of MinGW has to be in PATH.

Adding the complete tool-chain/kit

Go to the “Kits” tab. If you have Qt libraries installed and configured, you’ll see them there. I don’t like Qt SDK, and I usually compile my own versions of Qt. You’ll see that in the next screenshot.

What you see in the next screenshot are 3 kits that use Qt libraries, and another that do not. The free version of Visual Studio (2012 and later) comes with both 32-bit and 64-bit compilers. You can choose any one of them, or both (like I do). I don’t use MinGW often on Windows, so I install only 1 version of it (I use MinGW on Windows primarily because it offers the “-pedantic" flag, which gives the chance to experiment with C++ standard-approved features).

Now click “Add”, and choose the fields as shown below (most importantly, configure CMake correctly, it’s a little tricky, and the error on Qt Creator doesn’t tell you what you did wrong)

If you’re getting unexplained errors when running CMake, follow the following instructions carefully

Visual Studio

The following is a screenshot of how Visual Studio configuration should look like (screenshot is for 64-bit)

Set the following

  • For the 32-bit compiler: Choose the compiler with (x86)
  • For the 64-bit compiler: Choose the compiler with (x86_am64) or (amd64)
  • Choose “None” for Qt version
  • Choose the correct debugger
  • Most importantly: After choosing CMake from the drop-down list, make sure that CMake generator is chosen to be “NMake Makefiles”, and the Extra generator to be CodeBlocks

The last piece of information is the invitation to all kinds of problems. If running CMake doesn’t work, you most likely configured that part incorrectly.


The following is a screenshot of how MinGW configuration should look like:

  • Choose “None” for Qt version
  • Choose the correct debugger
  • Most importantly: After choosing CMake from the drop-down list, make sure that CMake generator is chosen to be “MinGW Makefiles”, and the Extra generator to be CodeBlocks

The last piece of information is the invitation to all kinds of problems. If running CMake doesn’t work, you most likely configured that part incorrectly.

I have to say that from my experience, Qt Creator some times fails to run CMake with MinGW with no good reason. I fix this by switching the “Extra generator” to “CodeLite”, and back to “CodeBlocks”. I’m currently using Qt Creator 4.2.0. It might be a bug?


It’s very easy to get gcc/g++ to work. The following is a screenshot:

  • Choose “None” for Qt version
  • Most importantly: After choosing CMake from the drop-down list, make sure that CMake generator is chosen to be “CodeBlocks – Unix Makefiles”.  It’s chosen by default, so nothing to worry about.

And you’re done!

What can I do with CMake + Qt Creator?

No ultimate dependence on Qt Creator!

Visual Studio solutions don’t work without Visual Studio. Netbeans configuration is stored in “netbeans project directory”. it’s very annoying that every IDE has its own weird format! I never stop hearing people complaining about porting their programs to other systems and having problems because of this.

One of the things I like most about Qt Creator is the fact that it doesn’t have any special project files for itself. The Makefile itself (CMake file, in this case, or qmake otherwise) is the project file. This ensures not only 100% portability (since both make systems are cross-platform) but also independence of Qt Creator itself. In the future, if the whole Qt Creator project goes down, your project won’t be affected at all.

What if I want to use Qt Creator just as an IDE without having to build a project through it?

I had the “luxury” of getting a project from a space agency to add some features to it, where they had their own build system. I wasn’t able to use Qt Creator to build the project, but…

But why use Qt Creator? Simply because you’ll get

  • Syntax highlighting
  • target functions and classes following
  • advanced refactoring options (like renaming classes, functions, etc)
  • Search capabilities in source files.
  • Repository updates checking
  • Type hierarchy navigation with a click
  • And lots more!

With all these, yet, while the project contains a few thousand source files, I was able to add *all* files and parse them with Qt using a few CMake lines. And it was fast enough to handle all that!

How to do it? How to add all these files in one step?

CMake supports recursive adding of source files. Consider the following CMake file (always called CMakeLists.txt):

cmake_minimum_required(VERSION 3.0)

file(GLOB_RECURSE MySrcFiles


add_executable(MyExecutable main.cpp)

target_link_libraries(MyExecutable MySrcFilesLib)

The first two lines are obvious. The “file" part recursively finds all the files under the directory mentioned and saves them in the variable ${MySrcFiles}. The variable ${CMAKE_SOURCE_DIR} is basically the directory where you cmake file “CMakeLists.txt" is located. Feel free to set any directory you find fit.

The “add_library” part creates a library from the source (and header) files saved in ${MySrcFiles}.

The “add_executable” part  “creates” the executable, which is then linked to the libraries you added.

That last linking part is not necessary if you don’t want to build in Qt Creator.

With such a simple CMake file, Qt Creator was smart enough to add all the source files, parse them, and give me all the functionality I needed to edit that project successfully.

SSH proxy with Putty that reconnects automatically


Putty can be used to tunnel your connection through your SSH server. It creates a SOCKS proxy that you can use anywhere. The annoying part there is that if Putty disconnects for any reason, you’ll have to reestablish the connection manually. If you’re happy reconnecting putty manually all the time, then this article is not for you. Otherwise, keep reading to see how I managed to find a fair solution to this problem.


For this recipe, you need the following

  1. Putty, of course. You could use “Putty Tray”, which supports being minimized to taskbar.
  2. Python 3

I understand that you may not have or use Python, but the solution I used depends on it, unfortunately. You could download Miniconda 3,  which is a smaller version of Anaconda 3. Anaconda is my recommended Python release.

How does this work in a nutshell?

The idea is very simple.

  1. Create a Putty session configuration that suites you
  2. Configure the session to close on disconnect
  3. Create a script that will relaunch your putty session on exit
  4. Make sure that the launcher you’re gonna use doesn’t keep a command prompt window open (which is why I’m using Python; pythonw.exe solves this issue).

Configuring Putty

To create a putty tunnel proxy, load your favorite session configuration, and then go to the tunnels configuration, and use the following settings, assuming you want the SOCKS proxy port to be 5150. Choose any port you like.


After connecting with this configuration, this creates a SOCKS that you can connect to with the loopback IP-Address, at port 5150.

One more important thing to configure in putty, is to set putty to exit on failure. This is important because we’re gonna set putty to reconnect through a program that detects that it exited to start it again.


Configuring Python and the launch script

Assuming you installed Python 3 and included in your PATH, now you have to install a package called tendo. This package is used to prevent running multiple instances of the program.

To install it, first, run the command prompt of Windows (in case Python is installed directly on the system drive, C:\, you have to run it as administrator). In the command prompt, to ensure that Python is working fine, run:

python -V

If this responds with no error and gives a message like:

Python 3.5.1 :: Anaconda 4.1.0 (32-bit)

Then you’re good to go! Otherwise, make sure that Python is added to PATH, and try again.

To install tendo, simply run in command prompt

pip install tendo

After that, in the directory of putty, write this script to a file:

import subprocess
from tendo import singleton
import time

me = singleton.SingleInstance() #exits if another instance exists

while True:
 print("Starting putty session...")
 subprocess.call('"putty.exe" -load "mysession"')
 print("Putty session closed... restarting...")
 time.sleep(5)   #sleep to avoid infinitely fast restarting if no connection is present

The name “mysession” is the name of your session in putty. Replace it with your session name.

This script simply checks first that the current instance is the only instance, and then runs an infinite loop that keeps running the program every time it exits. So we made putty exit on disconnect, and this program will just run infinitely

Save this script to some file like “MyLoop.pyw”.

Testing the loop

Python has two executables. First is “python.exe”, and the other one is “pythonw.exe”. The difference is quite simple. The first one, “python.exe”, runs your script as a terminal program. The second one, “pythonw.exe”, runs your script without a terminal. It’s designed for GUI applications. Now “python.exe” is not what we need, but it still is useful for debugging the script. So whenever you have a problem or when you want to run this for the first time, switch to/use “python.exe”. Once you’re done and everything looks fine, switch to “pythonw.exe”.

Final step: The execution shortcut

This is not necessary, but it makes things easy. It makes it easy to control whether you want to use “python.exe” or “pythonw”. It makes it also possible to make your script handy. Simple create a shortcut to “python.exe” or “pythonw.exe”, and the first command line parameter should be your script. Remember that “Start in” has to be the directory, where Putty is located. Following picture is an example of how that shortcut should look like.


And you’re good to go! Start with “python.exe”, and once it works, and you find that every time you exit putty or a disconnection happens it relaunches it, switch to “pythone.exe”, and you’re done.

Final notes

This is not a super-fancy solution. This is a solution that’ll get you through and get the job done. If you want to exit the looping script, you’ll have to kill Python from your task-manager.

You may create a fancy taskbar app that’ll do the looping and exits, which I would’ve done if I had the time. So please share it if you do! You can use PyQt or PySide for that.


With this, you’ll keep reconnecting on disconnect, and you can get all your software to use your ssh server as a SOCKS proxy. Cheers!

Tunnel through https to your ssh server, and bypass all firewalls – The perfect tunnel! (HAProxy + socat)


Perhaps there’s no way to emphasize this more, but I don’t encourage violation of corporate policy. I do this stuff for fun, as I love programming and I love automating my life and gaining more convenience and control with technology. I’m not responsible for any problem you might get with your boss in your job for using this against your company’s firewall, or any similar problem for that matter.


I was in a hotel in Hannover, when I tried to access my server’s ssh. My ssh client, Putty, gave this disappointing message


At first I got scared as I thought my server is down, but then I visited the websites of that server, and they were fine. After some investigation, I found that my hotel blocks any access to many ports, including port 22, i.e., ssh. Did this mean that I won’t have access to my server during my trip? Not really!

I assume you’re using a Windows client, but in case you’re using linux, the changes you have to do are minimal, and I provide side-by-side how to do the same on a linux client. Let me know if you have a problem with any of this.

Tunneling mechanism, and problems with other methods that are already available

There are software that does something similar for you automatically, like sslh, but there’s a problem there.

What does sslh do?

When you install sslh on your server, you choose, for example, port 443 for it. Port 443 is normally for http-ssl (https), that’s normally taken by your webserver. So you change also your webserver’s port to some arbitrary port, say 22443. Then, say you want to connect to that server: sslh analyzes and detects whether the incoming network packets are ssh or http. If the packets are ssh, it forwards them to port 22. If the packets looks like https, it forwards them to the dummy port you chose, which is 22443 as we assumed.

What’s the problem with sslh, and similar programs?

It all depends on how sophisticated the firewall you’re fighting is. Some firewalls are mediocre, and they just blindly open port 443, and you can do your sslh trick there and everything will work fine. But smart firewalls are not that dull; they analyze your packets and then judge whether you’re allowed to be connected. Hence, a smart firewall will detect that you’re trying to tunnel ssh, and will stop you!

How do we solve this problem?

The solution is: Masquerade the ssh packets inside an https connection, hence, the firewall will have to do a man-in-the-middle attack in order to know what you’re trying to do. This will never happen! Hence, I call this solution: “The perfect solution“.

How to create the tunnel?

I use HAProxy for this purpose. You need that on your server. It’s available in standard linux systems. In Debian and Ubuntu, you can install it using

sudo apt-get install haproxy

You will need “socat” on your client to connect to this tunnel. This comes later after setting up HAProxy.

How does HAProxy work?

I don’t have a PhD in HAProxy, it’s fairly a complicated program that can be used for many purposes, including load balancing and simple internal proxying between different ports, and I use it only for this purpose. Let me give a brief explanation on how it works. HAProxy uses the model of frontends and backends. A frontend is what a client sees. You set a port there, and a communication mode (tcp, for example). You tell also a frontend “where these packets should go”, based on some conditions (called ACL, Access Control Lists). You choose to which backend the packets have to go. The backend contains information about the target local port. So in short words, you tell HAProxy where to forward these packets from the frontend to the backend based on some conditions.

A little complication if you use https websites on the same server

If you use https webserver on the same machine, you’ll have a problem. The problem is that you’ll need to check whether the packets are ssh before decrypting them, because once you decrypt them, you can’t use them as non-encrypted again (hence haproxy doesn’t support forking encrypted and decrypted packets side-by-side). This is because you choose to decrypt in your frontend. That’s why we use SNI (Server Name Indication) and do a trick:

  • If there’s no SNI (no server name, just IP address), then forward to ssh
  • If server name used is ssh.example.com (some subdomain you choose), then forward to ssh (optional)
  • If anything else is the case, forward to the https web server port

We also use 2-frontends. The first one is the main one, and the second is a dummy frontend, and is only used to decrypt the ssh connection’s https masquerade. HAProxy decrypts only in frontends.

Let’s do it!

The configuration file of HAProxy in Debian/Ubuntu is


You could use nano, vi or vim to edit it (you definitely have to be root or use sudo). For example:

sudo nano /etc/haproxy/haproxy.cfg
  1. Your main https port is 443
  2. Your main ssh port is 22
  3. Your https webserver is now on 22443
  4. The dummy ssh port is 22222 (used just for decryption, it doesn’t matter what you put it)
Main frontend

This is the frontend that will take care of the main port (supposedly 443). Everything after a sharp sign (#) on a line is a comment.

#here's a definition of a frontend. You always give frontends and backends a name
frontend TheMainSSLPort
 mode tcp
 option tcplog
 bind #listen to port 443 under all ip-addresses

 timeout client 5h #timeout is quite important, so that you don't get disconnected on idle
 option clitcpka

 tcp-request inspect-delay 5s
 tcp-request content accept if { req_ssl_hello_type 1 }

 #here you define the backend you wanna use. The second parameter is the backend name
 use_backend sshDecrypt if !{ req_ssl_sni -m found } #if no SNI is given, then go to SSH
 use_backend sshDecrypt if { req_ssl_sni -i ssh.exmple.com } #if SNI is ssh.example.com, also go to ssh

default_backend sslWebServerPort #if none of the above apply, then this is https

In the previous configuration, we have two paths for the packets, i.e., two backends:

  1. If the connection is ssh, the backend named “sshDecrypt” will be used.
  2. If the connection is https, the backend named “sslWebServerPort” will be used.
The https backend

I put this here first because it’s easier. All you have to do here is forward the packets to your webserver’s port, which we assumed to be port 22433. The following is the relevant configuration:

backend sslWebServerPort
 mode tcp
 option tcplog
 server local_https_server #forward to this server, port 22443

Now the https part is done. Let’s work on the ssh part.

The ssh front- and backends

We’ll have to use a trick, as mentioned before, to get this to work. Once a judgment is done for packets to go to ssh (using SNI), the packets have to be decrypted. This is not possible in a backend, thus we use a backend to forward the packets to a dummy frontend that decrypts the packets, and then send these to another backend to send the packets to the ssh server.

backend sshToDecryptor
 mode tcp
 option tcplog
 server sshDecFrontend
 timeout server 5h

This forwards the packets to port 22222. Now we build a frontend at that port that decrypts the packets.

frontend sshDecyprtionPort
 timeout client 5h
 option clitcpka

 bind ssl crt /path/to/combined/certs.pem no-sslv3
 mode tcp
 option tcplog

 tcp-request inspect-delay 5s
 tcp-request content accept if HTTP

default_backend sshServ #forward to the ssh server backend

The file /path/to/combined/certs.pem has to contain your private key, certificate and certificate chain in one file of your SSL. Concatenate them all in one file.

Finally, the back end to the ssh server:

backend sshServ
 mode tcp
 option tcplog
 server sshServer1
 timeout server 5h

That’s all you need to create the tunnel.

Test your haproxy configuration on the server

To test your configuration, stop HAProxy using

sudo service haproxy stop

and run the following command to start HAProxy in debug mode:

sudo haproxy -d -f /etc/haproxy/haproxy.cfg

The “-d” flag is debug mode, and the “-f” flag is used to choose the config file. The typical output looks like:

Available polling systems :
 epoll : pref=300, test result OK
 poll : pref=200, test result OK
 select : pref=150, test result FAILED
Total: 3 (2 usable), will use epoll.
Using epoll() as the polling mechanism.

If you don’t get any errors, then your configuration is OK. Press ctrl+c to close this foreground version of HAProxy, and start the HAProxy service:

sudo service haproxy start
Test your tunnel from your client

To test your client, you can use OpenSSL. The following command will connect to the server.

openssl s_client -connect ssh.example.com:443

You can also use your IP address. This will connect to HAProxy, and will be interpreted as ssh, if your configuration is correct. Once it reaches the ssh server, you’re good! You’ll see lots of stuff from OpenSSL, and finally a few seconds later the following message will appear if you’re using a Debian server:

SSH-2.0-OpenSSH_6.7p1 Debian-5+deb8u2

The message will change depending on your server’s linux distribution and OpenSSH server version. Once you see this message, this shows that you reached your ssh server successfully. You now have to setup a connection to your server’s tunnel.

Connecting to the ssh server using the tunnel

You need socat to connect to the https tunnel, and then you ssh to that tunnel. The program, socat, can be downloaded either as a zip package (please google it and try it, if it works, great. I had problem with OpenSSL dlls back then when I first tried this). Or you can use Cygwin to get it. Cygwin is a set of linux programs compiled for Windows. Don’t get too confident in the installer and just download all its components or you’ll easily consume 30 GB of diskspace and consume 10 hours installing these components. Just download what you need.

In case you’re using a linux client, socat is a standard program in linux. Just install it with your default package manager, e.g. in Debian/Ubuntu

sudo apt-get install socat
Running the socat tunnel

Open your Windows command prompt as administrator (or linux terminal), and use the following command to connect to your server using socat

socat -d TCP-LISTEN:8888,fork,range= OPENSSL-CONNECT:ssh.example.com:443,verify=0

Here we use port 8888 as an intermediate local port on your client. Once this works with no errors, you’re good to use an ssh client.

Warning: A “-v” flag is verbose for socat. Don’t do this for serious connections, but only for tests, as it writes everything on the terminal where socat is running, and since Windows Command Prompt prints messages synchronously, it’ll slow down everything for you.

Connect with your ssh client

Assuming you’re using putty, this is how your client should look like


Or if you’re using a linux client, simply use this in your terminal

ssh -p 443

And you should connect, and you’re done! Congratulations! You’re connected to your ssh server through https.

What about the other ports, other than ssh?

Once you got ssh working, everything else is easy. You can use an ssh SOCKS proxy tunnel. Putty does this easily for you. All you have to do is configure your connection as in the picture:


This creates a SOCKS proxy. To use it, I provide the following example that I do on Thunderbird to secure my e-mail connections. You can do the same on any program you like, even on your web browser:


You can do the same on linux. Please google how to create an ssh tunnel on linux for SOCKS proxy.


You’re connected! You can bypass any firewall you want just by being given access port 443. The only way to stop you is by cutting off your internet completely 🙂

Share this if you like it! I welcome your questions and any other thoughts in the comments.

Start your computer remotely using Raspberry Pi

Why do that?

I have my server at home, which contains multiple hard-drives with all my data on them in RAID configuration. I have my way to access this server remotely from any where in the world, but in order to access the server, it has to be turned on! So the problem is: How do I turn my server when I need it?

This whole thing took me like 4 hours of work. It turns out it’s much easier than it looks like.

Why is keeping the server turned on all the time a bad idea?

Of course, a web-server can be left turned on all the time to be accessed from everywhere at any time, but a server that is used to store data… I don’t see why one would turn it on unless one needs something from it. In fact, I see the following disadvantages in keeping the server on all the time and benefits for being able to turn it on remotely:

  1. High power consumption… although the server I use is low-power, but why use 150 W all the time with no real benefit?
  2. Reduction of the server life-span, components like the processor has a mean life-time that will be consumed by continuous operation.
  3. Fans wear out and become noisier when used for longer times.
  4. What if the server froze? I should be able to restart it remotely.

What do you need to pull this off?

  • Raspberry Pi (1 or 2, doesn’t matter, but I’ll be discussing 2)


  • 5 Volts Relay. I use a 4 Channel relay module. It costs like $7 on eBay or Amazon depending on how many channels you need.


  • Jumper cables (female-female specifically if you’re using Raspberry Pi + a similar Relay Module) to connect the Raspberry Pi to the Relay Module



  • More wires and connectors to connect the server to the Raspberry Pi cleanly, without having a permanent long cord permanently connected to the server. I used scrap Molex 4-pin connectors:


I cut a similar connector in half and used one part as a permanent connector to the server, and the other part went to the wire that goes to the Relay Module.

  • Finally, you need some expertise in Linux and SSH access as the operating system I use on my Raspberry Pi is Raspbian. This I can’t teach here, unfortunately, as it’s an extensive topic. Please learn how to access Raspberry Pi using SSH and how to install Raspbian. There are tons of tutorials for that online on the Raspbian and Raspberry websites that teach it extensively. If you’re using Windows on your laptop/desktop to SSH to the Raspberry Pi, you can use Putty as an SSH client.

Once you’re in the terminal of your Raspberry Pi, you’re ready to go!

How control is done using Raspberry Pi:

If you already know how to control Raspberry Pi 2 GPIO pins, you can skip this section.

On Raspberry Pi 2, there is a set of 40 pins that contain 26 pins that are called GPIO (General Purpose Input/Output) pins. GPIO pins can be controlled from the operating system of Raspberry Pi. I use Raspbian as an operating system of my Raspberry Pi 2 and the Python scripting language. In Raspbian, python is pre-equipped with what’s necessary to start controlling GPIO pins very easily.

Why Python? Because it’s super-easy and is very popular (it took me a few days to become very familiar with everything in that language… yes, it’s that simple). Feel free to use anything else you find convenient for you. However, I provide here only Python scripts.

The following is a map of these pins:



And the following is a video where I used them to control my 4-channel Relay Module:

And following is the Python script I used to do that. Lines that start with a sharp (#) are comments:

Note 1: Be aware that indentation matters in Python for each line (that’s how you identify scopes in Python). If you get an indent error when you run the script, that only means that the indentation of your script is not consistent. Read a little bit about indentation in Python if my wording for the issue isn’t clear.

Note 2: You MUST run this as super-user.


import RPi.GPIO as GPIO
import time


#The following is a function that inverts the current pin value and saves the new state
def switchPortState(portMapElement):
    GPIO.output(portMapElement[0],not portMapElement[1])
    pe = [portMapElement[0],not portMapElement[1]]
    return pe

#There's no easy way to know the current binary state of a pin (on/off, or 1/0, or True/False), so I use this structure, which is a dictionary array that goes from up to the number of channels one wants to control (I used GPIO channels 2,3,5,6). The first element of each element is the GPIO port number, and the second element is the assumed initial condition. The latter will invert in each step as in the video
portMap = {}
portMap[0] = [2,False]
portMap[1] = [3,False]
portMap[2] = [5,False]
portMap[3] = [6,False]

for i in range(len(portMap)):
    GPIO.setup(portMap[i][0], GPIO.OUT)

while True:
    for i in range(len(portMap)):
    portMap[i] = switchPortState(portMap[i])

If you access your Raspberry Pi using SSH, then you can use “nano” as an easy text editor to paste this script. Say if you wanna call the script file “script.py”, then:

nano script.py

will open a text editor where you can paste this script. After you’re done, press Ctrl+X to exit and choose to save your script. Then make this script executable (linux thing), using:

chmod +x script.py

then run the script using

sudo ./script.py

This will start the script and the leds will flash every half a second.

Again, we’re using “sudo” because we can only control Raspberry Pi’s GPIO pins as super user. There are ways to avoid putting your password each time you wanna run this, which will be explained later.

Get a grasp on the concept of turning the computer on/off:

There are two ways to turn your computer on/off electronically without using the switch and without depending on the bios (LAN wake-up, etc…):

  1. If you’re lucky, the power button’s wires will be exposed and you can immediately make a new connection branch in the middle and lead it outside the computer. Shorting the wires is equivalent to pressing the power button.
  2. Use the power supply’s motherboard green wire. Shorting this wire to ground (to any black wire) will jump the computer and start it.

The following is a random picture for a computer power supply. A clip is used to short green with ground.

ATX-Power-Supply-ConnectorI used the first way of the two ways I mentioned. Here’s a video showing how it looks like:

So shorting these two wires that come from the power button for some time (half a second) is what I did and that works as being equivalent to pressing the power button. After you manage how to connect these, then you can go to the next step.

Connecting the power-wires to the Relay Module:

After learning how to control the Relay Module, and learning how to take a branch from the computer case that if you would short the computer starts, the remaining part is to connect the power-wires, that you got from your computer power button or green+black power supply cords, and connect them to the Relay Module. The following video shows the concept and the result.

Now you have the two terminals that if you short together the computer starts, let’s get into a little more details.

Important: One important thing to keep in mind when doing the wire connection to the Relay Module, is that we need to connect them in a way that does not trigger the power switch if the Raspberry Pi is restarted. Therefore, choose the terminal connections to be disconnected by default, as the following picture shows:



Connect your power-wires two terminals to any of the marked two in the picture. The way the Relay Module works is that when it’s turned off, it switches whether the middle terminal is connected to left or right. By default it’s connected to right, and that’s what we can see in the small schematic under the terminals.

After doing the connections properly, now you can use the following script turn your computer on:


import RPi.GPIO as GPIO
import time
import argparse

#initialize GPIO pins

#use command line arguments parser to decide whether switching should be long or short
#The default port I use here is 6. You can change it to whatever you're using to control your computer.
parser = argparse.ArgumentParser()
parser.add_argument("-port", "--portnumber", dest = "port", default = "6", help="Port number on GPIO of Raspberry Pi")
#This option can be either long or short. Short is for normal computer turning on and off, and long is for if the computer froze.
parser.add_argument("-len","--len", dest = "length", default = "short" , help = "Length of the switching, long or short")

args = parser.parse_args()

#initialize the port that you'll use
GPIO.setup(int(args.port), GPIO.OUT)

#switch relay state, wait some time (long or short) then switch it back. This acts like pressing the switch button.
if args.length == "long":
elif args.length == "short":
    print("Error: parameter -len can be only long or short")

Save this script as, say, “switch.py”, and make it executable as we did before:

chmod +x switch.py

Now you can test running this script, and this is supposed to start your computer!

sudo ./switch.py

Running the program from a web browser

You could be already satisfied by accessing switching the computer remotely using ssh, but I made the process a little bit fancier using a php webpage.


Here, I explain how you could get the job done to have a webpage that turns on/off your computer. I don’t focus on security. Be careful not to make your home/work network’s components accessible to the public. Please consult some expert to verify that what you’re doing is acceptable and does not create a security threat for others’ data.

Using superuser’s sudo without having to put the password everytime

In order to access this from the web, you have to change pins states without having to enter the password.

To do this, run the command

sudo visudo

This will open a text editor. If your username for Raspberry Pi’s linux is myuser, then add the following lines there in that file:

www-data ALL=(myuser) NOPASSWD: ALL

This will allow the Apache user to execute the sudo command as you, and you have absolute super-user power. Now notice that this is not the best solution from a security point of view, but it just works. The best solution is to allow the user www-data to run a specific command as root. Just replace the last “ALL” of www-data with a comma separated list of the commands you wanna allow www-data to run, and replace “myuser” between the parenthesis with “root”. I recommend you do that after having succeeded, to minimize the possible mistakes you could do. This is a legitimate development technique, we start with something less perfect, test it, then perfect it one piece at a time.

Installing Apache web-server

First, install the web-server on your Raspberry Pi. Do this by running this set of commands in your terminal:

sudo apt-get install apache2
sudo apt-get install php5
sudo apt-get install libapache2-mod-php5
sudo a2enmod php5
sudo a2enmod alias
sudo service apache2 restart

I hope I haven’t forgotten any more necessary components, but there are, too, many tutorials out there and forums discussing how to start an apache webserver.

If the apache installation is a success, then you could go to your web-browser and see whether it’s working. First, get the hostname of your Raspberry Pi by running this command in Raspberry Pi’s terminal


Let’s say your hostname is “myhostname”. Now go to your browser, and enter this address:


If this gives you a webpage, then the web-server is working fine and you can proceed. Otherwise, if the browser gives an error, you have to debug your web-server and get it working. Please consult some tutorial online to help you run the apache server.

Creating the webpage:

The default directory where the main webpage is stored in apache is either “/var/www/” or “/var/www/html/”. Check where the index.html that you saw is, and place the new php file there. Say that php file has the name “control.php”, and say the default directory is “/var/www/”. Then, go to that directory using

cd /var/www/

Now create the new php page using the command

sudo nano control.php

And use the script

<!DOCTYPE html>
<title>Control page</title>
<form action="#" method="post">
 <select name="switchlen">
 <option value="short">Short</option>
 <option value="long">Long</option>
 <input type="submit" value="Switch server" name="submit">

 if($_POST['switchlen'] == "long")
 echo("This is long");
 $command = "sudo -u myuser sudo /usr/bin/python3 /home/myuser/switch.py -len long > debug.log 2>&1";
 else if($_POST['switchlen'] == "short")
 echo("This is short");
 $command = "sudo -u myuser sudo /usr/bin/python3 /home/myuser/switch.py -len short > debug.log 2>&1";
 $output = shell_exec($command);
 echo("Script return: ");

Don’t forget to change the path of the script to the correct path of your script “switch.py”, and change “myuser” to the username you’re using in your Raspberry Pi. After you’re done, press Ctrl+X to save and exit.

To use this page and have it successfully run the script, you have to do one more thing, which is making apache’s user own this file. The username for the apache web-server is called “www-data”, so assuming you called the file “control.php”, you have to run this command:

sudo chown www-data:www-data control.php

After you run this command, you should use “sudo nano” to edit this file instead of only nano, since your linux user doesn’t own the file anymore.

Also, don’t save the file in any place other than the original folder of apache (like /var/www), at least not before you make sure it works. Adding new folders that apache recognizes is something that requires additional steps that I don’t discuss here. Please consult an apache tutorial for that.

To test the new php page, go to the link:


If the website doesn’t work, check the the file “debug.log” in the same path of control.php. It will tell you what was wrong in the script.

Controlling your computer from outside your home

If you’re in a home network, then you can only access that webpage from within the network. If you would like to access it from outside the network, you have to have VPN access to your home network. Consider achieving this using OpenVPN. That’s how I do it. I may write an article about it some time in the future.


I hope this article has given you an idea on how to control your appliances using Raspberry Pi. We have shown how to turn a computer on/off remotely.

I do this for fun, but also more professional tasks can be achieved using similar scripts, such as controlling scientific experiments.

Designing high magnetic field coils efficiently

It sounds simple, I agree. But the problem is like designing a car. You could simply put some wheels together with simple set of chains and create a “car” that moves in your front lawn. But then if you want to design a professional car, you’ll spend much more time and professionalism to do it. And if you wanna build a sports car, you’ll have to fine tune every single parameter of your components to push the edge of what you can achieve.

This story doesn’t apply only to coils, but everything you design (actually I learned it from a book called “Professional C++” in a chapter discussing efficiency of algorithm writing, it’s not far from this case).

Concerning coils, if you just want to generate a few micro Tesla with no concerns about the homogeneity for the coil you’re designing, then it doesn’t matter how you do it. You could just wind a bunch of wires on your hand and your done. Today I’m not talking about such a thing. Today I’m gonna talk about coils that you want to use to generate relatively huge fields, with reasonable homogeneity.

For such specifications, if you’re careless about the details, you may end up wasting lots of time for experimental experience and money for cooling and power supplies. If you plan it carefully, you’ll save lots of money.

Parameters of the system

Any coils you design to generate magnetic fields will have a set of parameters that you have to tune. From those parameters I mention:

• Dimensions and geometry of the coils

• Magnetic field to be generated

• Thickness of the wires to be used

Where to start

The first thing one should determine for a coil system is the geometry of the coils. This is because the purpose of the coils is not just to generate a field, period. But it’s to generate a field over some region that is well defined for a specific experiment. One should know in advance what sample will be exposed to the magnetic field. If you don’t know that, you could spend days working on your coils, and eventually find out that your coils don’t fit your sample, or that your coils are so huge that you’re wasting so much power to generate fields you don’t need (math will show how important the size of your coils vs power is).

Therefore, start by defining the geometry of your coils. Once you know some characteristic radius or length of your coils, you have one step done. One more thing to pre-define, is how much wiring volume you want to use.

Optimum coil thickness

Any person starting with designing coils will have this question in mind: What’s the optimum wire thickness that should be used to have the optimum magnetic field. Guess what? If you know how much wire-volume you will use, then it doesn’t matter at all. Let’s do the math to verify this.

Suppose you have a slot to wind your wires that have a diameter $d$, and the slot has width $w$ and height $h$, as the figure shows. How can we optimally fill your wires in it? The optimal way is what the figure shows; it’s called “hexagonal packing”. This is in case we ignore third dimension’s problems, such as diagonal wires in the slots. This is a good approximation if the wires are wound carefully.

Cross section of packed wires (or packed cylinders)
Cross section of packed wires (or packed cylinders)

Notice that it’s very important to have a high number of circles per direction. This is to make sure that the flow of the current will be homogeneous in the volume. Imagine the opposite case, if you have one circle with diameter $d=h$. This will modify the magnetic field you expect from the wire as all the calculations of the magnetic field from a wire assume an infinitesimally thin wire.

With that said, let’s calculate the magnetic field from such a configuration. Any magnetic field generated from a current has the following form using the Biot-Savart law or Ampere’s law:

$$B=U\left(r\right)\cdot n\cdot I,$$

where $U\left(r\right)$ is a coefficient that depends on the dimensions of the coils with radius $r$, and $I$ is the electrical current, and $n$ is the number of total turns of the coil. We assumed that we know the geometry of your coil, meaning that $U\left(r\right)$ is fixed before starting this calculation. Let’s see how the wire diameter will modify your magnetic field.

From the definition of resistivity of a wire, we have

$$R=\rho\frac{\ell}{A}=\rho\frac{4\ell}{\pi d^{2}},$$

where R
is the resistance of the wire, $\ell$ is its length, $A=\pi\left(\frac{d} {2}\right)^{2}$ is its cross sectional area and $\rho$ is its resistivity. On the other hand, the power to be exerted on the coil is given by the formula

$$P=I^{2}R\quad\rightrightarrows \quad I=\sqrt{\frac{P}{R}},$$

and from the resistivity formula

$$I=\sqrt{\frac{P}{R}}=\frac{d}{2}\sqrt{\frac{\pi P}{\rho\ell}},$$

and we can put this in a form proportional to the magnetic field

$$B\propto n\cdot I=n\frac{d}{2}\sqrt{\frac{\pi P}{\rho\ell}}$$

There’s still one more question remaining to settle this; what’s the length of the wire required? The length of the wire depends on the diameter of the wire that will be used, since a thicker wire will occupy the area of the slot faster. Whether you wind your wire on a circle or a square, the length of the wire used will depend linearly on the side length or diameter of that geometry. If we call that $r$, then the length of the wire going to be $\ell=n\cdot k\cdot r$, where $k$ is $2\pi$ for a coil on the shape of a circle, and $4$ for a square coil, and $n$ is the number of turns. The formula of current then becomes:

$$n\cdot I=n\frac{d}{2}\sqrt{\frac{\pi P}{\rho\ell}}=n\frac{d}{2}\sqrt{\frac{\pi P}{\rho n\cdot k\cdot r}}=\frac{d}{2}\sqrt{\frac{\pi nP}{\rho\cdot k\cdot r}}.$$

Finally, the number of turns can be seen as the number of circles stacked in a hexagonal packing (as shown in the figure of the hexagonal packing). The number of circles (or cylindrical wires) with diameter $d$ packed in a slot of width $w$ and height $h$ can be approximated assuming a high number of circles (cylinders) per direction


where the factor $\cos30^{\circ}$ is simply due to the space saved with the hexagonal packing. In fact it doesn’t matter what packing you choose, since all packings will depend inversely on $d^{2}$, which is the important part. With this, the current formula becomes:

$$n\cdot I=\frac{d}{2}\sqrt{\frac{\pi nP}{\rho\cdot k\cdot r}}=\frac{1}{2}\sqrt{\frac{2\pi}{\sqrt{3}}}\sqrt{\frac{ whP}{\rho k r}}.$$

This result shows that the field doesn’t depend on the wire that we choose or the current we use. The magnetic field depends only on the power if the geometry of the coil is fixed.

One more important result here is that the power required is linearly proportional to $r$, which means that if your coils would have half the radius, half the power will be required. Thus it’s considerably important to make the coils as small as possible.

How to choose the wire diameter?

Having the magnetic field not depend on the wire thickness doesn’t mean we can choose it arbitrarily. In fact, the wire determines a very important characteristic, which is the voltage and amperage that we will need to generate. It doesn’t make sense to make a coil that will require 150 amperes and 0.1 volts, and that’s what the wire diameter determines for you. The thinner the wire is, the more resistance the coil will have, and thus more voltage will be required.

Thus, to fine-tune the production of your coil, decide the diameter of the wire after choosing the power supply that has the appropriate voltage and amperage.


It’s intuitive to think that the amount of current will tell how much field you’ll get, this is from simple, classical electromagnetism. However, in reality, it doesn’t really depend on the current. This is because the choice of the current depends on other parameters that are prioritized, such as the geometry of the coils. If the geometry of the coils is fixed, then it doesn’t matter how much current you put, but what matters is practically how much power one will put in.

This result is important for high field generators, since higher fields will entail higher power requirement, leading to heating problems. If your coils generate more heat that your system can dissipate, then it makes sense to think beforehand whether to whether the geometry should be made smaller or different, since smaller geometry means less power requirement.

What is a neutron Electric Dipole Moment (EDM)? How is it realized?


It’s funny how some times scientists could have conflicts over equivalent concepts without realizing the equivalence in what they’re saying. Recently, a conflict happened between a PhD student, in his PhD defense, and an examining professor. The conflict’s topic was: How is CP violation realized in permanent EDMs?

The funny thing is that both their pictures were correct. It’s just that one picture has an assumption on how an EDM should be quantum mechanically defined, and the other measures the existence of a neutron EDM through a CP violating energy.

Introduction to permanent EDM and CP violation

You could skip this part if you’re familar with CP violation and EDMs.

The concept of CP violation is a modern topic. It’s been out there for about 50 years, since the Nobel Prize discovery of CP violating Kaon dacays (Christenson et al. 1964). It also gained intresest because Sakharov (Sakharov 1991) postulated that the existence of matter in the universe instead of annihilating with anti-matter can be explained with interactions that should be CP violating (not only that, but this is one important condition).

What is CP violation?

CP is a combination of two quantum mechanical operators, $C$ and $P$. The $C$ operator is called the Charge Conjugation Operator; it simply converts each particle to an anti-particle. The $P$ operator is called the Parity Operator; it flips the coordinate system as a mirror would do, so that every right is left and every left is right. In other words, one could mathematically say that a coordinate $\vec{r}$ becomes $-\vec{r}$ after a parity operation. One more important operator that comes into play in the same game is $T$, the Time Reversal Operator. It simply reverses time progression. From this, CP violation is defined to be that systems in our world will have different physical laws when applying the $CP$ operators.

In 2002, an article was published (Greenberg 2002) that states that violating CPT symmetry implies breaking Lorentz Invariance, which is like the most fundamental symmetry we understand in our universe. The Lorentz symmetry simply means that Einsteins special relativity holds. This means that if CPT is violated, then relativity is broken, thus we would be in big trouble in our path in understanding the universe. Since all experiments agree with Lorentz invarinace, it is widely accepted that CPT symmetry is a fundamental symmetry in the universe.

The implication of CPT symmetry is that if CP is violated, then T is violated as well, to compensate for the former’s violation and result in CPT symmetry.

What is an EDM?

An Electric Dipole Moment (EDM) is defined in classical electromagnetism in its simplest form to be two charges with opposite signs and a fixed distance between them. Such a system is interesting in classical physics because applying an electric field on it will create a torque that gets it to rotate. Besides that it’s a part of an expansion called the Multipole Expansion that simplifies the treatment of many complex systems with complicated charge distribution.

For a group of particles, an EDM can be defined as:

$$\vec{d}=\sum_{i} \vec{r}_i q_i,$$

where $r_i$ is the position of particle number $i$, and $q_i$ is the charge of particle number $i$.

What is the reason for the conflict?

It’s well known that a neutron possesses a magnetic moment. The magnetic moment is associated with the spin of the neutron. In quantum mechanics, measurements can be done along one axis only. Measurements using multiple axes can have many problems, in which the quantum mechanical observables (quantum numbers) become time dependant, or in other words we could say: Measurements on multiple axes would lead to not having Good Quantum Numbers. A good quantum number is a mark of a good measurement and is reproducible. Measurements that change over time (except for approximations and eigenvalues that we understand) are useless, because they’re not reproducible. Some people like to pretend to be smarter than nature, and try to find ways to trick quantum measurements on multiple axes, but such people are either mistaken or haven’t yet realized that they’re doing a mistake. Humanity spent decades trying to trick the quantum world, but failed, and a good experimental example of this is in the following paragraph.

To illustrate good measurements, I’ll refer to the well-known Double Slit Experiment. See the picture for an illustration of the experiment. In this experiment, there’s a light source, which shines light on two open slits. You would think that you’ll have two spots on the screen, but this doesn’t happen due to quantum mechanical intereference effects.


In the double slit experiment, if only one slit is open, then the position of photons can be determined (by tolerating the spread due to diffraction, which is a good approximation). Thus we can say that the position of a photon in that case is a good measurement and is well defined along the path of the photon, from the light source to the detection screen.

If we open both slits, phase interference will show up. This leads to having an interference pattern (multiple maxima and minima in intensity), in which the position of the photon is not defined and the precision is worse than before! You can never, ever define a position of a photon after the slits with the same precision that you had in one slit. In this case, a measurement of a position is considered a bad measurement. There has been many tries to trick the system, but it never works. This is due to the wave-nature of the system that puts the phases of the constituent waves into account. This can be mathematically realized by the so called Uncertainty Principle. A position ($x$) and velocity (or momentum, $p_x$) of a particle can never be determined with infinite precision. This can be mathematically written with the commutator

$$\left[ x,p_x \right]=x p_x – p_x x = i\hbar$$

If the commutator would have been zero, then a simultaneous measurement with infinite precision (up to experimental constraints) is possible. A similar commutator exists between angular momentum $\vec{L}$ that is measured on different axes.

$$\left[ L_x,L_y \right]=i\hbar L_z$$

Therefore, the angular momentum can never be measured on multiple axes together. Actually, it’s not only the angular momentum. Any vector quantity cannot be measured on multiple axes. This follows from a famous mathematical theorem called the Wigner-Eckart theorem. This theorem shows that all vectors in quantum mechanics are the same up to a scaling factor. That’s why, tricking the system to measure on multiple axes is just pointless! Hence, in every quantum measurement, a single axis is defined to measure all vector quantities. It’s called the quantization axis.

Quantization axis of a neutron… is the problem!

Trouble starts now! We already know that there’s an axis for the neutron that is defined with its spin (or its magnetic moment). What if an EDM exists? An EDM is a vector quantity! Can it have another axis?

The conflict is exactly here. There are two schools of thought for this:

1- An EDM can physically exist in any direction, but we can only measure it along the spin, the well known quantization axis. If a measurement is done along a different axis, it cannot be distinguished.

2- An EDM must only exist along the spin, without caring what the nature of that EDM is, whether it’s a separation of charges or not.

This is exactly the source of conflict between the professor and the student. In fact, there’s no difference between those pictures. The reason of this is that no matter how you look at it, what matters is what we can measure, which is the same for both cases.

First picture:

For the first picture, we say that if a neutron EDM is measured, it has to be measured along the spin. If the neutron wave-function is $\left| J,m_J \right>$, where $J$ is the angular momentum eigenvalue and $m_J$ is the magnetic quantum number, then

$$\left<J, m_J \left| \hat{\vec{d}}_\mathrm{n} \right| J, m_J \right>= k\left<J, m_J \left| \hat{\vec{J}} \right| J, m_J \right>$$

or in short

$$\left< \hat{\vec{d}}_\mathrm{n}  \right>= k\left< \hat{\vec{J}}  \right>,\quad (*)$$

where $\hat{\vec{d}}_\mathrm{n}$ is nothing but an quantum mechanical operator that is constructed from the classical dipole moment defined above. This operator can be written as from before

$$\hat{\vec{d}}_\mathrm{n} = \sum_{i} \hat{\vec{r}}_i q_i, $$

where $\hat{\vec{r}}_i$ is the position of constituent number $i$. Let’s test $\hat P$ (parity) operator on this system

$$\left<\hat{P}^\dagger \hat{\vec{d}}_\mathrm{n}  \hat{P} \right>=-\left< \hat{\vec{d}}_\mathrm{n} \right>$$

$$\left<\hat{P}^\dagger \hat{\vec{J}} \hat{P} \right>=\left< \hat{J} \right>$$

Parity operator changes the sign of the EDM because it changes $r$ to $-r$. The spin doesn’t flip under parity because it’s an axial vector (opposite of polar vector); thus it’s a product of two other vectors. Notice that Eq. $(*)$ doesn’t hold anymore when parity is applied and $k \rightarrow -k$. Therefore, a permanent EDM violates parity!

Let’s test time reversal, $\hat{T}$

$$\left<\hat{T}^\dagger \hat{\vec{d}}_\mathrm{n}  \hat{T} \right>=\left< \hat{\vec{d}}_\mathrm{n} \right>$$

$$\left<\hat{T}^\dagger \hat{\vec{J}}  \hat{T} \right>=-\left< \hat{J} \right>$$

Time reversal doesn’t affect the EDM because such an EDM doesn’t depend on time. Spin or magnetic moments, however, reverse sign by time reversal, since magnetic moments are generated by the motion of charges, and a backwards motion will reverse the magnetic moment. Thus, a permanent EDM violates time reversal symmetry.

This means that CP is violated when a permanent EDM exists.

Second picture:

In the second picture, it’s claimed that we don’t know what’s going on inside, but there’s strictly an EDM that is proportional to spin. The game can be played in a different way. We define a Hamiltonian of the system

$$\hat{H}=-\hat{\vec{\mu}}_\mathrm{n}\cdot \vec{B}-\hat{\vec{d}}_\mathrm{n}\cdot \vec{E}.$$

By calculating the expectation value of this Hamiltonian and relating it to the numerical magnetic moment of the neutron, $\mu_\mathrm{n}$, and a hypothetical numerical value of the EDM, $d_\mathrm{n}$, and by considering that the magnetic moment and the EDM are along a single axis, the precession energy of the neutron becomes

$$E=\hbar \omega_\mathrm{L}=2\mu_\mathrm{n} B+ 2 d_\mathrm{n} E .$$

The factor 2 comes from the convention of $\mu_n$ being meaured from the eigen-energy of the system with no electric and magnetic fields up to the maximum magnetic moment (which is 1/2), leading to energy spacing of twice that for a spin-1/2 particle. And $\omega_\mathrm{L}$ is the Larmor frequency, which is the transition frequency from the two possible eigenstates of the spin.

By applying the parity operator, $\hat P$, to the energy term, we get

$$E=\hbar \omega_\mathrm{L}=2\mu_\mathrm{n} B- 2 d_\mathrm{n} E .$$

This is because $E$ is a polar vector, and $B$ is an axial vector. This shows that the existence of an EDM modifies the energy of the system under parity! This is another way to look at the effect of an EDM on the energy of the system upon applying $P$ operator. The same can be tested for $T$ operator which will flip only the magnetic field, since it’s an axial vector.


It doesn’t really matter how we look at it. The reason for this is that what matters in the experiment is what we measure! The picture of an intrinsic EDM that consists of separation of charges is violated through $P$ and $T$ operators. The other picture with electric and magnetic fields is violated because the system’s energy is different when appying those operators.

How to organize scientific literature?


A huge burden for a scientist is the organiation of their literature. I, as a physicist, have over 1000 articles that I used in my work along the history of my career in physics. Besides many, many books that I also would need at any second while working.

How can I organize all those books and all those articles?
How can I reach any piece of information I need whenever I need it without wasting an hour digging in my collection of articles by filename?

This question has been going in my head for a long time, and I started a few months ago to dig for an answer. I was thinking of writing a php program that organizes my literature with copies of literature inside it and with bibtex support, but guess what… a solution with those features is already there! I just found that there are many, many organizations that have written such programs. Examples are Mendeley and Zotero.

There are more, but I only tested these.

Both are great, but…

Both programs Mendeley and Zotero are great when considered locally on your computer! They’re so good that they can take your PDF, read it, index it, and automatically find reference details for you such as Author list, DOI, ISBN, title, and many others and make this data available when you search for something and simply display the article when you click on its information. You can even add a note to some article, attach it to the article and make it reachable when needed through the note. This is extremely helpful when you want to mark a specific piece of information in some literature, making it not necessary to dig in all your literature.

I started with Mendeley, I was happy with it, until I realized that I also need a synchronization mechanism among my computers at home and at work. Mendeley is a commercial software, it offers very limited diskspace (about 2 GB), and stuff are stored on their server, making it a problem for some people due to corporate policy, which prevents them from storing work information on 3rd party servers. Besides, even if that’s allowed, 2 GB is not really good enough. That’s why, I left Mendeley.

Then I found Zotero, which is technically a program derived from Firefox. Zotero creates a local database folder on your computer with local copies of your literature inside it. You can copy the database wherever you want and even move it between computers. Then you can easily choose what directory you want to use to store your data. This is SUPER CONVENIENT! It’s very practical for making backups of everything, and not losing anything on long term use. There’s even an option for synchronization with the web. They offer also little diskspace (about 1 GB), but then if you pay 10\$, they give you infinite diskspace, which is convient, and gives you the option to synchronize your literature among multiple computers.

What if corporate policy prevents me from storing literature on a 3rd party server?

Actually it’s not only corporate policy that prevents me from doing that. What prevents me, too, is that I’m not convinced that such a service is worth 10\$ per month, especially that I own a linux server, for which I pay 30\$ per month with 1 TB diskspace. Does it make sense to pay 30\$ for a full-featured linux server and 10\$ just for literature? Not at all!

Proposing a solution to avoid 3rd party cloud intervention

The solution is very simple, and I could implement this solution due to the nice way Zotero stores data. Since Zotero stores data in a single, defined folder, all you have to do is synchronize this folder among the computers you have to use! A method to do this is by using a repository system, like GIT, which I find not convenient, since I manually have to commit, push and pull every change. So the better method I found is a synchronization system driven from my 30\$ server, called Seafile.

Seafile is an opensource cloud system (similar to Dropbox) that can be run from your own server! It uses client-side encryption and is the safest I know and most recommended, so far. I have been using it for all my work and data, and I find it very convenient. So, all you have to do is synchronize your Zotero data folder among the PCs you want to use.

If you don’t have a server for yourself, simply use some 3rd party cloud, like Dropbox, which will anyway give you more diskspace than the standard Zotero cloud offers. However, you’re, again, limited by diskspace eventually. In case you need more diskspace, I really recommend that you rent (or probably buy for your home) your own linux server. You learn a lot, and you save a lot of money and you can use it for multiple purposes for yourself and your family.

Or… you could use servers from your own institution, which are normally offered at good universities (normally universities offer free diskspace for employees and students which is globally accessible or at least through a VPN service).


There’s some risk when doing this, but it’s not that bad for a reason. The main risk when using this method is that you could open the same Zotero database from different computers. I’m not sure whether just opening from different computers would create a problem, but I could almost be certain that if you make changes on different computers simultaneously you’ll induce a problem if your cloud tries to merge databases. However, it’s not that bad, because cloud systems usually create full history of your files with a revision for every change you make, meaning that if your database files (files with extention *.sqlite in Zotero) get corrupted, you can always roll back to a previous version and have zero losses.


You can create a very good and reliable scientific literature database system using Zotero, and a cloud. This is a perfect solution for personal literature. However, I still don’t have a solution for groups that won’t involve storing data on a 3rd party server.

PS: It could be possible to use your own server to synchronize Zotero database as if you would be synchronizing with the official Zotero server. However, this would involve recompiling the source code of Zotero with your server address, which, I think, is a huge burden. This depends on whether your group wants to be commited to such a solution.

What is exactly non-deterministic in our universe?

What is determinism?

Determinism is the concept that the physical world that we live in is wound like a clock. The concept says that if we would know every law that governs the universe, and we have the computational power to compute those laws; then, we may know the future with 100% certainty.

Bad news is…

This universe is non-deterministic. We know this, now, with great certainty, and with many experiments and many successful models that have shown, so far, that this is true. In fact, Einstein had fought his last 20 years, before his death, to disprove this fact, and he failed.

Will someone else disprove it? A Nobel prize awaits this Genius, if he could do it!

Main question of the article

What if an observer lives outside our universe and monitors the universe from the outside, and knows the internal parameters that control our universe. Will he be able to determine the future infinitely precisely?

It’s a very complicated question in fact to think about. However, in order to answer the question, we have to understand what is non-deterministic in our universe.

How can we tackle this question?

In order to understand the answer to this question, we have to understand what it is that we have to predict. And understand why uncertainty shows up in the first place.

Where does uncertainty come from?

Uncertainty comes mainly from the fact that we deal with a world governed by some classical parameters. For example, we deal with energy and position. Those parameters, if known very well, describe our systems very accurately.

In other words, in the simplest form, if we know the positions and energies of a set of particles; we may, as well, predict the future and dynamics of the system very accurately.

What is it that we’re uncertain about in our universe?

Here comes the problem. When we go to the microscopic level of particles, we find that the macroscopic (large scale) description of systems is very different. In quantum mechanics (QM), systems are defined by the so called “wave packets”. They’re not anymore “objects” like we thought of them before.

The above picture shows that a particle in its microscopic description is not a particle, as we had learned about it before. It’s a wave packet. If we try to look at this wave packet from our classical view, the transition from the wave description to the macroscopic, classical description, will suffer uncertainties. Look at the particle at the bottom. While the wave on the top is very clear and well defined with no uncertainties whatsoever, the bottom, classical, picture of the particle suffers uncertainties.

The problem is the transition

Our particles are described by wave packets in the microscopic level. But in our world, we don’t deal with wave packets. We deal with particles. We deal with well defined energies and well defined positions. Therefore, we need a transformation that will take our wave packet from its wavy picture, to a picture that is compatible with our classical observations. This transformation is called in QM the expectation value. When performing this transition, there is no way we can do it without uncertainty. For example, in the particle seen in the picture, we can never, ever, define a single point that characterizes the position of the particle. There’s no position! The particle is smeared over a volume of space. Therefore, the transformation from the QM picture, with wavy properties, to the classical picture, is the cause of uncertainties.


The reason of non-determinism in this world is not that we don’t know the characteristics of a particle in its wave nature. The main problem causing uncertainty to appear is that the description of particles in their microscopic form is always coherent with uncertainties, due to the incompatibility of the world views when taking the step from the microscopic world to the classical world.

Answering the main question: Will someone outside the universe, who knows the parameters of those wave packets, be able to predict the future with 100% certainty? The answer is NO. Because the fact that a transformation from the wavy form to the classical form contains uncertainties is not related to our physical world. It’s rather related to the mathematical nature of this transformation, which inherently will cause uncertainties to appear, independent of the knowledge of the entity performing this transformation.