Decoherence-free quantum information in the presence of dynamical evolution

We analyze decoherence-free (DF) quantum information in the presence of an arbitrary non-nearest-neighbor bath-induced system Hamiltonian using a Markovian master equation. We show that the most appropriate encoding for N qubits is probably contained within the ~(2/9) N excitation subspace. We give a timescale over which one would expect to apply other methods to correct for the system Hamiltonian. In order to remain applicable to experiment, we then focus on small systems, and present examples of DF quantum information for three and four qubits. We give an encoding for four qubits that, while quantum information remains in the two-excitation subspace, protects against an arbitrary bath-induced system Hamiltonian. Although our results are general to any system of qubits that satisfies our assumptions, throughout the paper we use dipole-coupled qubits as an example physical system.Comment: 8 pages, 4 figure

Caustics in the sine-Gordon model from quenches in coupled 1D Bose gases

Caustics are singularities that occur naturally in optical, hydrodynamic and quantum waves, giving rise to high amplitude patterns that can be described using catastrophe theory. In this paper we study caustics in a statistical field theory setting in the form of the sine-Gordon model that describes a variety of physical systems including coupled 1D superfluids. Specifically, we use classical field simulations to study the dynamics of two ultracold 1D Bose gases (quasi-condensates) that are suddenly coupled to each other and find that the resulting non-equilibrium dynamics are dominated by caustics. Thermal noise is included by sampling the initial states from a Boltzmann distribution for phononic excitations. We find that caustics pile up over time in both the number and phase difference observables leading to a characteristic non-thermal `circus tent' shaped probability distribution at long times.Comment: 28 pages, 13 figure

Irreversible Electroporation (IRE) in Locally Advanced Pancreatic Cancer: A Review of Current Clinical Outcomes, Mechanism of Action and Opportunities for Synergistic Therapy

Locally advanced pancreatic cancer (LAPC) accounts for 30% of patients with pancreatic cancer. Irreversible electroporation (IRE) is a novel cancer treatment that may improve survival and quality of life in LAPC. This narrative review will provide a perspective on the clinical experience of pancreas IRE therapy, explore the evidence for the mode of action, assess treatment complications, and propose strategies for augmenting IRE response. A systematic search was performed using PubMed regarding the clinical use and safety profile of IRE on pancreatic cancer, post-IRE sequential histological changes, associated immune response, and synergistic therapies. Animal data demonstrate that IRE induces both apoptosis and necrosis followed by fibrosis. Major complications may result from IRE; procedure related mortality is up to 2%, with an average morbidity as high as 36%. Nevertheless, prospective and retrospective studies suggest that IRE treatment may increase median overall survival of LAPC to as much as 30 months and provide preliminary data justifying the well-designed trials currently underway, comparing IRE to the standard of care treatment. The mechanism of action of IRE remains unknown, and there is a lack of data on treatment variables and efficiency in humans. There is emerging data suggesting that IRE can be augmented with synergistic therapies such as immunotherapy

Hamiltonian learning from time dynamics using variational algorithms

The Hamiltonian of a quantum system governs the dynamics of the system via the Schrodinger equation. In this paper, the Hamiltonian is reconstructed in the Pauli basis using measurables on random states forming a time series dataset. The time propagation is implemented through Trotterization and optimized variationally with gradients computed on the quantum circuit. We validate our output by reproducing the dynamics of unseen observables on a randomly chosen state not used for the optimization. Unlike the existing techniques that try and exploit the structure/properties of the Hamiltonian, our scheme is general and provides freedom with regard to what observables or initial states can be used while still remaining efficient with regard to implementation. We extend our protocol to doing quantum state learning where we solve the reverse problem of doing state learning given time series data of observables generated against several Hamiltonian dynamics. We show results on Hamiltonians involving XX, ZZ couplings along with transverse field Ising Hamiltonians and propose an analytical method for the learning of Hamiltonians consisting of generators of the SU(3) group. This paper is likely to pave the way toward using Hamiltonian learning for time series prediction within the context of quantum machine learning algorithms.Comment: 33 pages, 18 figure

Hydrodynamics of cold atomic gases in the limit of weak nonlinearity, dispersion and dissipation

Dynamics of interacting cold atomic gases have recently become a focus of both experimental and theoretical studies. Often cold atom systems show hydrodynamic behavior and support the propagation of nonlinear dispersive waves. Although this propagation depends on many details of the system, a great insight can be obtained in the rather universal limit of weak nonlinearity, dispersion and dissipation (WNDD). In this limit, using a reductive perturbation method we map some of the hydrodynamic models relevant to cold atoms to well known chiral one-dimensional equations such as KdV, Burgers, KdV-Burgers, and Benjamin-Ono equations. These equations have been thoroughly studied in literature. The mapping gives us a simple way to make estimates for original hydrodynamic equations and to study the interplay between nonlinearity, dissipation and dispersion which are the hallmarks of nonlinear hydrodynamics.Comment: 18 pages, 3 figures, 1 tabl

Third-order nonlinear optical properties of stacked bacteriochlorophylls in bacterial photosynthetic light-harvesting proteins

Enhancement of the nonresonant second order molecular hyperpolarizabilities {gamma} were observed in stacked macrocyclic molecular systems, previously in a {micro}-oxo silicon phthalocyanine (SiPcO) monomer, dimer and trimer series, and now in bacteriochlorophyll a (BChla) arrays of light harvesting (LH) proteins. Compared to monomeric BChla in a tetrahydrofuran (THF) solution, the <{gamma}> for each macrocycle was enhanced in naturally occurring stacked macrocyclic molecular systems in the bacterial photosynthetic LH proteins where BChla`s are arranged in tilted face-to-face arrays. In addition, the {gamma} enhancement is more significant in B875 of LH1 than in B850 in LH2. Theoretical modeling of the nonresonant {gamma} enhancement using simplified molecular orbitals for model SiPcO indicated that the energy level of the two photon state is crucial to the {gamma} enhancement when a two photon process is involved, whereas the charge transfer between the monomers is largely responsible when one photon near resonant process is involved. The calculated results can be extended to {gamma} enhancement in B875 and B850 arrays, suggesting that BChla in B875 are more strongly coupled than in B850. In addition, a 50--160 fold increase in <{gamma}> for the S{sub 1} excited state of relative to S{sub 0} of bacteriochlorophyll in vivo was observed which provides an alternative method for probing excited state dynamics and a potential application for molecular switching

High Speed Modified Booth’s Signed 64x64 Bit Multiplier Using Wallace Structure by Radix-32

The Main objective of the implemented work is completely based on enhancing speed performance multiplication process using radix-32 modified Booth algorithm and Wallace Tree Structure. It is designed for fixed length 64x64 bit operands. In Wallace structure, 3:2and 4:2 Compressors are used which accumulate the partial products. The implemented modified Booth multiplier is verified and advantages over the existing multiplier are quantitatively analyzed. This implemented multiplier provides less delay 0.238 ns. Many researchers had been worked and presented the modified booth multiplier with optimized delay. In this paper, it has been shown that the implemented 64 bit multiplier provides better delay in comparison with those existing papers. A VHDL code has been written and successfully synthesized and simulated using Xilinx ISE 13.1 simulator software. Also partial products which are generated are less as compared to conventional multiplier. No. of logic blocks required for fast multiplication process has been reduced in terms of no. of slices in comparison with previous ones. DOI: 10.17762/ijritcc2321-8169.150712

Hydrodynamic reductions of the heavenly equation

We demonstrate that Pleba\'nski's first heavenly equation decouples in infinitely many ways into a triple of commuting (1+1)-dimensional systems of hydrodynamic type which satisfy the Egorov property. Solving these systems by the generalized hodograph method, one can construct exact solutions of the heavenly equation parametrized by arbitrary functions of a single variable. We discuss explicit examples of hydrodynamic reductions associated with the equations of one-dimensional nonlinear elasticity, linearly degenerate systems and the equations of associativity.Comment: 14 page

GYM: A Multiround Distributed Join Algorithm

Multiround algorithms are now commonly used in distributed data processing systems, yet the extent to which algorithms can benefit from running more rounds is not well understood. This paper answers this question for several rounds for the problem of computing the equijoin of n relations. Given any query Q with width w, intersection width iw, input size IN, output size OUT, and a cluster of machines with M=Omega(IN frac{1}{epsilon}) memory available per machine, where epsilon > 1 and w ge 1 are constants, we show that: 1. Q can be computed in O(n) rounds with O(n(INw + OUT)2/M) communication cost with high probability. Q can be computed in O(log(n)) rounds with O(n(INmax(w, 3iw) + OUT)2/M) communication cost with high probability. Intersection width is a new notion we introduce for queries and generalized hypertree decompositions (GHDs) of queries that captures how connected the adjacent components of the GHDs are. We achieve our first result by introducing a distributed and generalized version of Yannakakis\u27s algorithm, called GYM. GYM takes as input any GHD of Q with width w and depth d, and computes Q in O(d + log(n)) rounds and O(n (INw + OUT)2/M) communication cost. We achieve our second result by showing how to construct GHDs of Q with width max(w, 3iw) and depth O(log(n)). We describe another technique to construct GHDs with longer widths and lower depths, demonstrating other tradeoffs one can make between communication and the number of rounds