Book Image

Quantum Computing Algorithms

By : Barry Burd
5 (1)
Book Image

Quantum Computing Algorithms

5 (1)
By: Barry Burd

Overview of this book

Navigate the quantum computing spectrum with this book, bridging the gap between abstract, math-heavy texts and math-avoidant beginner guides. Unlike intermediate-level books that often leave gaps in comprehension, this all-encompassing guide offers the missing links you need to truly understand the subject. Balancing intuition and rigor, this book empowers you to become a master of quantum algorithms. No longer confined to canned examples, you'll acquire the skills necessary to craft your own quantum code. Quantum Computing Algorithms is organized into four sections to build your expertise progressively. The first section lays the foundation with essential quantum concepts, ensuring that you grasp qubits, their representation, and their transformations. Moving to quantum algorithms, the second section focuses on pivotal algorithms — specifically, quantum key distribution and teleportation. The third section demonstrates the transformative power of algorithms that outpace classical computation and makes way for the fourth section, helping you to expand your horizons by exploring alternative quantum computing models. By the end of this book, quantum algorithms will cease to be mystifying as you make this knowledge your asset and enter a new era of computation, where you have the power to shape the code of reality.
Table of Contents (19 chapters)
Free Chapter
Part 1 Nuts and Bolts
Part 2 Making Qubits Work for You
Part 3 Quantum Computing Algorithms
Part 4 Beyond Gate-Based Quantum Computing


  1. This chapter’s Quantum operations for teleportation section presents the equations that show why teleportation works. What happens in these equations if the initial state of Alice’s qubit is |0? What happens if the initial state is |1?
  2. In Figure 6.10, Alice’s qubit starts in state 0.8228 |0 + 0.5683 |1. Modify this chapter’s generate_amplitudes function as follows:
    def generate_amplitudes():
        alpha = 0.8228
        beta = 0.5683
        return alpha, beta

With this version of generate_amplitudes, what happens when you call the add_gates function? Why?

  1. Write Qiskit code to create a circuit of the following kind:

I’ve blurred out the initial amplitudes of Alice’s qubit because you should generate those values randomly.

Run this circuit several times to convince yourself that Bob’s qubit...