Quantum information effects

We study the two dual quantum information effects to manipulate the amount of information in quantum computation: hiding and allocation. The resulting type-and-effect system is fully expressive for irreversible quantum computing, including measurement. We provide universal categorical constructions that semantically interpret this arrow metalanguage with choice, starting with any rig groupoid interpreting the reversible base language. Several properties of quantum measurement follow in general, and we translate (noniterative) quantum flow charts into our language. The semantic constructions turn the category of unitaries between Hilbert spaces into the category of completely positive trace-preserving maps, and they turn the category of bijections between finite sets into the category of functions with chosen garbage. Thus they capture the fundamental theorems of classical and quantum reversible computing of Toffoli and Stinespring.

Comparative Review on Efficient Design of Reversible Sequential Circuits based on Optimization Parameters

Reversible computing, a well known research area in the field of computer science. One of the aims of reversible computing is to design low power digital circuits that dissipates no energy to heat. The main challenge of designing reversible circuits is to optimize the parameters which make the design costly. In this paper, we review different designs of efficient reversible sequential circuits and prepare a comparative statement based on eight optimization parameters such as Quantum Cost (QC), Delay (del), Garbage Output (GO), Constant Input (CI), Gate Level (GL), Number of Gate (NoG), Type of Gate (ToG), Hardware Complexity (HC) of Circuit.

A Synthetic Genetic Reversible Feynman Gate in a Single E.coli Cell and its Application in Bacterial to Mammalian Cell Information Transfer

Reversible computing is a nonconventional form of computing where the inputs and outputs are mapped in a unique one-to-one fashion. Reversible logic gates in single living cells have not been demonstrated. Here, we created a synthetic genetic reversible Feynman gate in a single E.coli cell. The inputs were extracellular chemicals, IPTG and aTc and the outputs were two fluorescence proteins EGFP and E2-Crimson. We developed a simple mathematical model and simulation to capture the essential features of the genetic Feynman gate and experimentally demonstrated that the behavior of the circuit was ultrasensitive and predictive. We showed an application by creating an intercellular Feynman gate, where input information from bacteria was computed and transferred to HeLa cells through shRNAs delivery and the output signals were observed as silencing of native AKT1 and CTNNB1 genes in HeLa cells. Given that one-to-one input-output mapping, such reversible genetic systems might have applications in diagnostics and sensing, where compositions of multiple input chemicals could be estimated from the outputs.

Post-Synthesis Optimization of Reversible Circuits

One of the main motivations for reversible computing is that quantum computing has as one of its foundations the reversibility of all gates, that is, quantum computing circuit models are reversible. An important problem in reversible computing that has been intensively studied for the last decades is the synthesis of reversible circuits. The extended abstract considers optimization rules aiming to a new algorithm for post-synthesis optimization of reversible circuits composed of generalized Toffoli gates.

A Review on Reversible Computing and it’s applications on combinational circuits

In this era of nanometer semiconductor nodes, the transistor scaling and voltage scaling are not any longer in line with each other, leading to the failure of the Dennard scaling. Thus, it poses a severe design challenge. Reversible computing plays a vital role in applications like low power CMOS, nanotechnology, quantum computing, optical computing, digital signal processing, cryptography, computer graphics andmany more. The primary reasons for designing reversible logic are diminishing the quantum cost, profundity of the circuits and the garbage outputs. It is impossible to determine the quantum computing without implementing the reversible computation. This paper will represent the literature survey based on several papers on combinational circuits using reversible computing and also the future scope is to be discussed.

Quantum Foundations of Classical Reversible Computing

The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible digital paradigm. However, to date, the essential rationale for, and analysis of, classical reversible computing (RC) has not yet been expressed in terms that leverage the modern formal methods of non-equilibrium quantum thermodynamics (NEQT). In this paper, we begin developing an NEQT-based foundation for the physics of reversible computing. We use the framework of Gorini-Kossakowski-Sudarshan-Lindblad dynamics (a.k.a. Lindbladians) with multiple asymptotic states, incorporating recent results from resource theory, full counting statistics and stochastic thermodynamics. Important conclusions include that, as expected: (1) Landauer’s Principle indeed sets a strict lower bound on entropy generation in traditional non-reversible architectures for deterministic computing machines when we account for the loss of correlations; and (2) implementations of the alternative reversible computation paradigm can potentially avoid such losses, and thereby circumvent the Landauer limit, potentially allowing the efficiency of future digital computing technologies to continue improving indefinitely. We also outline a research plan for identifying the fundamental minimum energy dissipation of reversible computing machines as a function of speed.

Quantum Foundations of Classical Reversible Computing

The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible paradigm. However, to date, the essential rationale for and analysis of classical reversible computing (RC) has not yet been expressed in terms that leverage the modern formal methods of non-equilibrium quantum thermodynamics (NEQT). In this paper, we begin developing an NEQT-based foundation for the physics of reversible computing. We use the framework of Gorini-Kossakowski-Sudarshan-Lindblad dynamics (a.k.a. Lindbladians) with multiple asymptotic states, incorporating recent results from resource theory, full counting statistics, and stochastic thermodynamics. Important conclusions include that, as expected: (1) Landauer's Principle indeed sets a strict lower bound on entropy generation in traditional non-reversible architectures for deterministic computing machines when we account for the loss of correlations; and (2) implementations of the alternative reversible computation paradigm can potentially avoid such losses, and thereby circumvent the Landauer limit, potentially allowing the efficiency of future digital computing technologies to continue improving indefinitely. We also outline a research plan for identifying the fundamental minimum energy dissipation of reversible computing machines as a function of speed.

Quantum Foundations of Classical Reversible Computing

The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible paradigm. However, to date, the essential rationale for and analysis of classical reversible computing (RC) has not yet been expressed in terms that leverage the modern formal methods of non-equilibrium quantum thermodynamics (NEQT). In this paper, we begin developing an NEQT-based foundation for the physics of reversible computing. We use the framework of Gorini-Kossakowski-Sudarshan-Lindblad dynamics (a.k.a. Lindbladians) with multiple asymptotic states, incorporating recent results from resource theory, full counting statistics, and stochastic thermodynamics. Important conclusions include that, as expected: (1) Landauer's Principle indeed sets a strict lower bound on entropy generation in traditional non-reversible architectures for deterministic computing machines when we account for the loss of correlations; and (2) implementations of the alternative reversible computation paradigm can potentially avoid such losses, and thereby circumvent the Landauer limit, potentially allowing the efficiency of future digital computing technologies to continue improving indefinitely. We also outline a research plan for identifying the fundamental minimum energy dissipation of reversible computing machines as a function of speed.