This chapter covers quantum subsystems and their properties. Single and multiple quantum bit systems are discussed in detail. Quantum states, protocols, operations, and transformations are also presented in this chapter.
We have seen how information can be encoded onto a quantum system by selecting the state in which it is prepared. Retrieving the information is achieved by performing a measurement, and the optimal measurement in any given situation is usually a generalized measurement. In between preparation and measurement, the information resides in the quantum state of the system, which evolves in a manner determined by the Hamiltonian. The associated unitary transformation may usefully be viewed as quantum information processing; if we can engineer an appropriate Hamiltonian then we can use the quantum evolution to assist in performing computational tasks. Our objective in quantum information processing is to implement a desired unitary transformation. Typically this will mean coupling together a number, perhaps a large number, of qubits and thereby generating highly entangled states. It is fortunate, although by no means obvious, that we can realize any desired multiqubit unitary transformation as a product of a small selection of simple transformations and, moreover, that each of these need only act on a single qubit or on a pair of qubits. The situation is reminiscent of digital electronics, in which logic operations are decomposed into actions on a small number of bits. If we can realize and control a very large number of such operations in a single device then we have a computer. Similar control of a large number of qubits will constitute a quantum computer. It is the revolutionary potential of quantum computers, more than any other single factor, that has fuelled the recent explosion of interest in our subject. We shall examine the remarkable properties of quantum computers in the next chapter. In digital electronics, we represent bit values by voltages: the logical value 1 is a high voltage (typically +5 V) and 0 is the ground voltage (0 V). The voltage bits are coupled and manipulated by transistor-based devices, or gates. The simplest gates act on only one bit or combine two bits to generate a single new bit, the value of which is determined by the two input bits. For a single bit, with value 0 or 1, the only possible operations are the identity (which does not require a gate) and the bit flip.
From the outset statistical mechanics will be framed in the language of quantum theory. The typical macroscopic system is composed of multiple constituents, and hence described in some many-particle Hilbert space. In general, not much is known about such a system, certainly not the precise preparation of all its microscopic details. Thus, its description requires a more general notion of a quantum state, a so-called mixed state. This chapter begins with a brief review of the basic axioms of quantum theory regarding observables, pure states, measurements, and time evolution. Particular attention is paid to the use of projection operators and to the most elementary quantum system, a two-level system. The chapter then motivates the introduction of mixed states and examines in detail their mathematical representation and properties. It also dwells on the description of composite systems, introducing, in particular, the notions of statistical independence and correlations.
In this chapter we build on the basic model developed in Chapter 1 by extending the notation to handle quantum systems with multiple qubits. With that terminology in place, we can illustrate the ideas which are basic to quantum algorithms and can confirm theoretically that the unitary transformations we need can be implemented as a sequence of operations involving only one or two qubits. Quantum algorithms can be constructed using a small number of quantum gates, and we discuss those gates next. We then use quantum gates to construct an addition subroutine and complete the chapter with a teleportation subroutine, which is the first illustration of the potential importance of entanglement for communication.
This presentation provides a comprehensive overview of the foundational principles of quantum computation. It begins by contrasting classical and quantum information, highlighting how quantum bits (qubits) leverage superposition, entanglement, and interference to process information in ways that surpass classical limits. The document explains the four postulates of quantum mechanics: state space (qubits as unit vectors in a Hilbert space), time evolution (via unitary operators), measurement (probabilistic collapse of the state), and composite systems (tensor products of subsystems). Key concepts such as the Bloch sphere representation, quantum gates (e.g., Hadamard, CNOT, Pauli gates), and quantum circuits are discussed, illustrating how quantum operations manipulate qubit states. The presentation also covers quantum evolution, the gate model for computation, and the universality of certain gate sets, emphasizing the potential for quantum parallelism and the transformative impact of quantum computing on fields like cryptography and optimization.
In this chapter, we study the properties of quantum entanglement, and more generally the way correlations can appear in quantum mechanics. Quantum entanglement is an important notion that we have already discussed, for instance in the context of the Von Neumann chain or of the Schrödinger cat, but here we give more details on its properties. In classical physics, the notion of correlation is well known. It hinges on the calculation of probabilities and on linear averages over a number of possibilities. A distribution gives the probability of having the first system in a some given state and the second in another state. If this distribution is not a product, the two systems are correlated. If it is a product, they are uncorrelated; measuring the properties of one system does not bring any information on the other. This is in particular the case if the state of each of the two systems is perfectly defined (which also defines the state of the whole system perfectly well). The notion of correlation between sub-systems therefore stems from the multiplicity of possible states of the whole system; fluctuations of this state are necessary to give its full meaning to the classical notion of correlation. In quantum mechanics, the situation is different: as we have seen (in particular in Chapter 4), even a physical system that is perfectly defined by a given state vector already contains fluctuations.
Quantum machines, grounded in the principles of quantum mechanics, harness the extraordinary computational power derived from quantum bits (qubits), contrasting with classical machines reliant on classical bits. Qubits, distinguished by properties like superposition and entanglement, empower quantum algorithms to solve intricate problems with exponential speedup. Quantum states, fundamental to quantum mechanics, serve as descriptors for quantum systems, laying the foundation for subsequent calculations. Quantum gates, unitary operators manipulating qubits, are pivotal in quantum computing, extending beyond single-particle systems to encompass multi-particle scenarios. This flexibility finds applications in quantum simulation, optimization, cryptography, machine learning, and more. Quantum computing’s potential to revolutionize fields arises from its ability to tackle computationally intractable problems. Applications span quantum simulation, optimization, cryptography, machine learning, chemistry, materials science, financial modeling, and transportation. quantum protocols, including communication and cryptography, leverage unique quantum properties. Prominent quantum algorithms, such as Deutsch-Jozsa, Bernstein-Vazirani, Grover’s, and Shor’s, exploit qubit features for efficient problem-solving. These algorithms harness superposition and entanglement, allowing parallel calculations across multiple possibilities. In the landscape of quantum computing, the interplay of quantum bits, gates, states, and algorithms showcases the potential for transformative advances in computation.