Cavity Induced Interfacing of Atoms and Light

This chapter introduces cavity-based light-matter quantum interfaces, with a single atom or ion in strong coupling to a high-finesse optical cavity. We discuss the deterministic generation of indistinguishable single photons from these systems; the atom-photon entanglement intractably linked to this process; and the information encoding using spatio-temporal modes within these photons. Furthermore, we show how to establish a time-reversal of the aforementioned emission process to use a coupled atom-cavity system as a quantum memory. Along the line, we also discuss the performance and characterisation of cavity photons in elementary linear-optics arrangements with single beam splitters for quantum-homodyne measurements.Comment: to appear as a book chapter in a compilation "Engineering the Atom-Photon Interaction" published by Springer in 2015, edited by A. Predojevic and M. W. Mitchel

Explorations for Efficient Reversible Barrel Shifters and Their Mappings in QCA Nanocomputing

This thesis is based on promising computing paradigm of reversible logic which generates unique outputs out of the inputs and. Reversible logic circuits maintain one-to-one mapping inside of the inputs and the outputs. Compared to the traditional irreversible computation, reversible logic circuit has the advantage that it successfully avoids the information loss during computations. Also, reversible logic is useful to design ultra-low-power nanocomputing circuits, circuits for quantum computing, and the nanocircuits that are testable in nature. Reversible computing circuits require the ancilla inputs and the garbage outputs. Ancilla input is the constant input in reversible circuits. Garbage output is the output for maintaining the reversibility of the reversible logic but is not any of the primary inputs nor a useful bit. An efficient reversible circuit will have the minimal number of garbage and ancilla bits. Barrel shifter is one of main computing systems having applications in high speed digital signal processing, oating-point arithmetic, FPGA, and Center Processing Unit (CPU). It can operate the function of shifting or rotation for multiple bits in only one clock cycle. The goal of this thesis is to design barrel shifters based on the reversible computing that are optimized in terms of the number of ancilla and garbage bits. In order to achieve this goal, a new Super Conservative Reversible Logic Gate (SCRL gate) has been used. The SCRL gate has 1 control input depending on the value of which it can swap any two n-1 data inputs. We proved that the SCRL gate is superior to the existing conservative reversible Fredkin gate. This thesis develops 5 design methodologies for reversible barrel shifters using SCRL gates that are primarily optimized with the criteria of the number of ancilla and garbage bits. The five proposed methodologies consist of reversible right rotator, reversible logical right shifter, reversible arithmetic right shifter, reversible universal right shifter and reversible universal bidirectional shifter. The proposed reversible barrel shifter design is compared with the existing works in literature and have shown improvement ranging from 8.5% to 92% by the number of garbage and ancilla bits. The SCRL gate and design methodologies of reversible barrel shifter are mapped in Quantum Dot Cellular Automata (QCA) computing. It is illustrated that the SCRL-based designs of reversible barrel shifters have less QCA cost (cost in terms of number of inverters and majority voters) compared to the Fredkin gate- based designs of reversible barrel shifters

Thermodynamic Computing

The hardware and software foundations laid in the first half of the 20th Century enabled the computing technologies that have transformed the world, but these foundations are now under siege. The current computing paradigm, which is the foundation of much of the current standards of living that we now enjoy, faces fundamental limitations that are evident from several perspectives. In terms of hardware, devices have become so small that we are struggling to eliminate the effects of thermodynamic fluctuations, which are unavoidable at the nanometer scale. In terms of software, our ability to imagine and program effective computational abstractions and implementations are clearly challenged in complex domains. In terms of systems, currently five percent of the power generated in the US is used to run computing systems - this astonishing figure is neither ecologically sustainable nor economically scalable. Economically, the cost of building next-generation semiconductor fabrication plants has soared past $10 billion. All of these difficulties - device scaling, software complexity, adaptability, energy consumption, and fabrication economics - indicate that the current computing paradigm has matured and that continued improvements along this path will be limited. If technological progress is to continue and corresponding social and economic benefits are to continue to accrue, computing must become much more capable, energy efficient, and affordable. We propose that progress in computing can continue under a united, physically grounded, computational paradigm centered on thermodynamics. Herein we propose a research agenda to extend these thermodynamic foundations into complex, non-equilibrium, self-organizing systems and apply them holistically to future computing systems that will harness nature's innate computational capacity. We call this type of computing "Thermodynamic Computing" or TC.Comment: A Computing Community Consortium (CCC) workshop report, 36 page

A Uniform Mathematical Representation of Logic and Computation.

The current models of computation share varying levels of correspondence with actual implementation schemes. They can be arranged in a hierarchical structure depending upon their level of abstraction. In classical computing, the circuit model shares closest correspondence with physical implementation, followed by finite automata techniques. The highest level in the abstraction hierarchy is that of the theory of computation.Likewise, there exist computing paradigms based upon a different set of defining principles. The classical paradigm involves computing as has been applied traditionally, and is characterized by Boolean circuits that are irreversible in nature. The reversible paradigm requires invertible primitives in order to perform computation. The paradigm of quantum computing applies the theory of quantum mechanics to perform computational tasks.Our analysis concludes that descriptions at lowest level in the abstraction hierarchy should be uniform across the three paradigms, but the same is not true in case of current descriptions. We propose a mathematical representation of logic and computation that successfully explains computing models in all three paradigms, while making a seamless transition to higher levels of the abstraction hierarchy. This representation is based upon the theory of linear spaces and, hence, is referred to as the linear representation. The representation is first developed in the classical context, followed by an extension to the reversible paradigm by exploiting the well-developed theory on invertible mappings. The quantum paradigm is reconciled with this representation through correspondence that unitary operators share with the proposed linear representation. In this manner, the representation is shown to account for all three paradigms. The correspondence shared with finite automata models is also shown to hold implicitly during the development of this representation. Most importantly, the linear representation accounts for the Hamiltonians that define the dynamics of a computational process, thereby resolving the correspondence shared with underlying physical principles.The consistency of the linear representation is checked against a current existing application in VLSI CAD that exploits the linearity of logic functions for symbolic representation of circuits. Some possible applications and applicability of the linear representation to some open problems are also discussed