The point of building a quantum computer is that it allows to model living things with predictive power and gives the opportunity to control life. Its scaling means not just the improvement of the instrument part, but also, mainly, mathematical and software tools, and our understanding of the QC problem. The first principle of quantum modeling is the reduction of reality to finite-dimensional models similar to QED in optical cavities. The second principle is a strict limitation of the so-called Feynman principle, the number of qubits in the standard formulation of the QC. This means treating decoherence exclusively as a limitation of the memory of a classical modeling computer, and introducing corresponding progressive restrictions on the working area of the Hilbert space of quantum states as the model expands. The third principle is similarity in processes of different nature. The quantum nature of reality is manifested in this principle; its nature is quantum nonlocality, which is the main property that ensures the prospects of quantum physical devices and their radical advantage over classical ones.
The point of building a quantum computer is that it allows to model living things with predictive power and gives the opportunity to control life. Its scaling means not just the improvement of the instrument part, but also, mainly, mathematical and software tools, and our understanding of the QC problem. The first principle of quantum modeling is the reduction of reality to finite-dimensional models similar to QED in optical cavities. The second principle is a strict limitation of the so-called Feynman principle, the number of qubits in the standard formulation of the QC. This means treating decoherence exclusively as a limitation of the memory of a classical modeling computer, and introducing corresponding progressive restrictions on the working area of the Hilbert space of quantum states as the model expands. The third principle is similarity in processes of different nature. The quantum nature of reality is manifested in this principle; its nature is quantum nonlocality, which is the main property that ensures the prospects of quantum physical devices and their radical advantage over classical ones.
Quantum computing is the area of study focused on developing computer technology based on the principles of quantum theory. The quantum computer, following the laws of quantum physics, would gain enormous processing power through the ability to be in multiple states and to perform tasks using all possible permutations simultaneously. Classical computing relies, at its ultimate level, on principles expressed by Boolean algebra. Data must be processed in an exclusive binary state at any point in time or bits. While the time that each transistor or capacitor needs to be either in 0 or 1 before switching states is now measurable in billionths of a second, there is still a limit as to how quickly these devices can be made to switch state. As the authors progress to smaller and faster circuits, they begin to reach the physical limits of materials and the threshold for classical laws of physics to apply. Beyond this, the quantum world takes over.
Quantum computing operates by manipulating the quantum state of a system to solve problems intractable for classical computing. These problems, previously considered limitations of classical algorithms, have solutions through quantum approaches. Therefore, quantum computing suggests that the complexity of such problems lies in the current epistemic state rather than the objective state of the problem. Computational complexity can be classified into objective and epistemic complexity. Some classical problems exhibiting exponential complexity fall into the epistemic category, as their solutions depend on the current state of human knowledge and available tools. Quantum computing suggests that even mathematics isn’t entirely objective, and mathematics, in one sense, is human-made and a kind of technology, which reflects our intention and planning. Computational complexity, therefore, bridges the objective and subjective. Overcoming classical complexity necessitates advancements in scientific theories, algorithms, and quantum technology, all of which rely on the development of human cognitive abilities. Quantum computing is not just a mathematical construct, but also has physical meaning. If it were purely mathematical, classical physics and systems could potentially achieve the same results. What makes the quantum world special is its empirical nature—the physical reality of quantum chips, quantum algorithms, and quantum evolution. Quantum supremacy, or quantum advantage, refers to the potential superiority of quantum computers over classical ones. Controllable quantum systems offer an overwhelming advantage in terms of manipulation and dominance compared to classical systems. Essentially, quantum computing has the potential to significantly outperform classical computing. Many experts, including Shor, have proposed that quantum computing’s power stems from its ability to perform multiple computations simultaneously—a concept often referred to as the Quantum parallelism thesis. Rather, some argue that the true source of quantum computing acceleration lies in the fundamental differences between classical and quantum logic. However, it’s important to note that quantum logic, while providing a new perspective, does not directly address the core principle of quantum parallelism. This dominance stems from quantum physics’ unique properties: Exponential storage capacity, parallel computing inherent to its nature (ontological), and the ability to perform calculations with exponential speedup through quantum algorithms.
Quantum computing stands as a pioneering field within computer science, leveraging the enigmatic principles of quantum mechanics to execute intricate calculations. At its heart lies the qubit, the elemental building block of quantum information, which resides in a state of superposition, representing both 0 and 1 concurrently. Quantum computers, constructed from assemblies of qubits, inhabit an expansive and intricate 2^n-dimensional complex Hilbert space, with their evolution governed by the Schrödinger equation. The process of quantum computation can be distilled into three key stages:1) Initialization of the input state: Initiating the quantum process; 2)Application of unitary transformations: Executing the desired transformations on the input state; 3) Measurement of the output state. Quantum computers serve as universal machines, capable of decomposing any unitary transformation into a sequence of fundamental gates. This chapter will reveal the importance of quantum mechanics, quantum computation and its applications.
Physics has two main ambitions: to predict and to understand. Indeed, physics aims for the prediction of all natural phenomena. Prediction entails modeling the correlation between an action, the input, and what is subsequently observed, the output.Understanding, on the other hand, involves developing insightful principles and models that can explain the widest possible varietyof correlations present in nature. Remarkably, advances in both prediction and understanding foster our physical intuition and, as a consequence, novel and powerful applications are discovered. Quantum mechanics is a very successful physical theory both in terms of its predictive power as well as in its wide applicability. Nonetheless and despite many decades of development, we do not yet have a proper physical intuition of quantum phenomena. I believe that improvements in our understanding of quantum theory will yield better, and more innovative, protocols and vice versa.This dissertation aims at advancing our understanding and developing novel protocols. This is done through four approaches. The first one is to study quantum theory within a broad family of theories. In particular, we study quantum theory within the family of locally quantum theories. We found out that the principle that singles out quantum theory out of this family, thus connecting quantum local and nonlocal structure, is dynamical reversibility. This implies that the viability of large scale quantum computing can be based on concrete physical principles that can be experimentally tested at a local level without needing to test millions of qubits simultaneously. The second approach is to study quantum correlations from a black box perspective thus making as few assumptions as possible. The strategy is to study the completeness of quantum predictions by benchmarking them against alternative models. Three main results and applications come out of our study. Firstly, we prove that performing complete amplification of randomness starting from a source of arbitrarily weak randomness - a task that is impossible with classical resources - is indeed possible via nonlocality. This establishes in our opinion the strongest evidence for a truly random event in nature so far. Secondly, we prove that there exist finite events where quantum theory gives predictions as complete as any no-signaling theory can give, showing that the completeness of quantum theory is not an asymptotic property. Finally, we prove that maximally nonlocal theories can never be maximally random while quantum theory can, showing a trade-off between the nonlocality of a theory and its randomness capabilities. We also prove that quantum theory is not unique in this respect. The third approach we follow is to study quantum correlations in scenarios where some parties have a restriction on the available quantum degrees of freedom. The future progress of semi-device-independent quantum information depends crucially on our ability to bound the strength of these correlations. Here we provide a full characterization via a complete hierarchy of sets that approximate the target set from the outside. Each set can be in turn characterized using standard numerical techniques. One application of our work is certifying multidimensional entanglement device-independently.The fourth approach is to confront quantum theory with computer science principles. In particular, we establish two interesting implications for quantum theory results of raising the Church-Turing thesis to the level of postulate. Firstly, we show how different preparations of the same mixed state, indistinguishable according to the quantum postulates, become distinguishable when prepared computably. Secondly, we identify a new loophole for Bell-like experiments: if some parties in a Bell-like experiment use private pseudorandomness to choose their measurement inputs, the computational resources of an eavesdropper have to be limited to observe a proper violation of non locality.
Quantum computing is a propitious technology which is likely to revolutionize computing.It differs from classical computing, in context of the algorithms it requires for computations and the methods of implementation which correspond to the principles of quantum mechanics.The clock frequency of existing computer processor systems may reach about 40 GHz within the next decade.By then one atom may represent one bit, but electrons under such conditions cannot be described by classical physics, due to this a new model of computing becomes absolutely inevitable.The prospect of quantum computing may have the potential in dealing with the problems faced by classical computing.
The Feynman Festival is a new interdisciplinary conference developed for studying Richard Feynman and his physics. The first meeting of this new conference series was held at the University of Maryland on 23--28 August 2002 ( http://www.physics.umd.edu/robot/feynman.html ) and the second meeting is scheduled for August 2004 at the same venue. According to Feynman, the different aspects of nature are different aspects of the same thing. Therefore, the ultimate purpose of the conference is to find Feynman's same thing from all different theories. For this reason, the first meeting of the Festival did not begin with a fixed formula, but composed its scientific programme based on responses from the entire physics community. The conference drew the most enthusiastic response from the community of quantum computing, the field initiated by Feynman. Encouraged by the response, we decided to edit a special issue of Journal of Optics B: Quantum and Semiclassical Optics on quantum computing in connection with the first Feynman Festival. The authorship is not restricted to the participants of the Feynman Festival, and all interested parties were encouraged to submit their papers on this subject. Needless to say, all the papers were peer reviewed according to the well-established standards of the journal. The subject of quantum computing is not restricted to building and operating computers. It requires a deeper understanding of how quantum mechanics works in materials as well as in our minds. Indeed, it covers the basic foundations of quantum mechanics, measurement theory, information theory, quantum optics, atomic physics and condensed matter physics. It may be necessary to develop new mathematical tools to accommodate the language that nature speaks. It is gratifying to note that this special issue contains papers covering all these aspects of quantum computing. As Feynman noted, we could be discussing these diversified issues to study one problem. In our case, this `one problem' is to build quantum computers.