10 Solving chemistry problems with quantum computers

 

This chapter covers

  • Solving chemistry simulations with quantum computers
  • Implementing the Exp operation and the Trotter–Suzuki method
  • Creating programs for phase estimation, decomposition, and so on

In chapter 9, we used a number of new Q# features like user-defined types (UDTs) and running programs from Python hosts to help us write a quantum program that could estimate phases. As we will see in this chapter, phase estimation is commonly used in quantum algorithms to build up larger and more complex programs. In this chapter, we’ll look at our first practical application area: chemistry.

10.1 Real chemistry applications for quantum computing

So far in this book, we’ve learned how to use quantum devices to do everything from chat with our friend Eve to help decide the fate of kings. In this chapter, though, we’ll get the chance to do something a bit more practical.

Note

Now that we have what we need to solve harder problems with quantum computers, this chapter’s scenario is a little more complicated than most of our earlier games and scenarios. Don’t worry if things don’t make sense off the bat. Take your time and read things more slowly; we promise it will be worth your while!

10.2 Many paths lead to quantum mechanics

 
 
 

10.3 Using Hamiltonians to describe how quantum systems evolve in time

 
 
 

10.4 Rotating around arbitrary axes with Pauli operations

 
 
 
 

10.5 Making the change we want to see in the system

 
 
 

10.6 Going through (very small) changes

 

10.7 Putting it all together

 
 

Summary

 
 
 
 
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