ZN\mathbb{Z}_N lattice gauge theories with matter fields

Motivated by the exotic phenomenology of certain quantum materials and recent advances in programmable quantum emulators, we here study fermions and bosons in $\mathbb Z_N$ lattice gauge theories. We introduce a family of exactly soluble models, and characterize their orthogonal (semi-)metallic ground states, the excitation spectrum, and the correlation functions. We further study integrability breaking perturbations using an appropriately derived set of Feynman diagrammatic rules and borrowing physics associated to Anderson's orthogonality catastrophe. In the context of the ground states, we revisit Luttinger's theorem following Oshikawa's flux insertion argument and furthermore demonstrate the existence of a Luttinger surface of zeros in the fermionic Green's function. Upon inclusion of perturbations, we address the transition from the orthogonal metal to the normal state by condensation of certain excitations in the gauge sectors, so-called ``$e$-particles''. We furthermore discuss the effect of dynamics in the dual ``$m$-particle'' excitations, which ultimately leads to the formation of charge-neutral hadronic $N$-particle bound states. We present analytical arguments for the most important phases and estimates for phase boundaries of the model. Specifically, and in sharp distinction to quasi-1D $\mathbb Z_N$ lattice gauge theories, renormalization group arguments imply that the phase diagram does not include an emergent deconfining $U(1)$ phase. Therefore, in regards to lattice QED problems, $\mathbb Z_N$ quantum emulators with $N<\infty$ can at best be used for approximate solutions at intermediate length scales

Direct Relationship Between Electrokinetic Surface-charge Measurement of Effluents and Coagulant Type and Dose

AbstractColloidal stability due to rejection between particles with identical charge is a severe problem in water treatment. Pretreatment of industrial effluents such as olive mill or cowshed dairy wastewater includes the addition of “coagulants” aimed at neutralizing the colloids and reducing their rejection. However, the amount and type of coagulant are usually determined by “trial-and-error” jar tests due to the lack of an efficient method to evaluate the effluents' charge. This study presents a method for direct evaluation of the efficiency of type and dose of coagulants based on particle charge detector (PCD) measurements of the colloidal effluents and the coagulant to be used as the neutralizing compound. This presumably trivial procedure is not common, apparently due to the fact that measuring colloidal charge with a PCD is less widely used than ζ potential measurements. A few examples of the effective use of this procedure are presented

Knowledge of previous tasks: task similarity influences bias in task duration predictions

Bias in predictions of task duration has been attributed to misremembering previous task duration and using previous task duration as a basis for predictions. This research sought to further examine how previous task information affects prediction bias by manipulating task similarity and assessing the role of previous task duration feedback. Task similarity was examined through participants performing two tasks 1 week apart that were the same or different. Duration feedback was provided to all participants (Experiment 1), its recall was manipulated (Experiment 2), and its provision was manipulated (Experiment 3). In all experiments, task similarity influenced bias on the second task, with predictions being less biased when the first task was the same task. However, duration feedback did not influence bias. The findings highlight the pivotal role of knowledge about previous tasks in task duration prediction and are discussed in relation to the theoretical accounts of task duration prediction bias

Topological Insulators and Superconductors from D-branes

Realization of topological insulators (TIs) and superconductors (TSCs), such as the quantum spin Hall effect and the Z_2 topological insulator, in terms of D-branes in string theory is proposed. We establish a one-to-one correspondence between the K-theory classification of TIs/TSCs and D-brane charges. The string theory realization of TIs and TSCs comes naturally with gauge interactions, and the Wess-Zumino term of the D-branes gives rise to a gauge field theory of topological nature. This sheds light on TIs and TSCs beyond non-interacting systems, and the underlying topological field theory description thereof. In particular, our string theory realization includes the honeycomb lattice Kitaev model in two spatial dimensions, and its higher-dimensional extensions.Comment: 5 pages, 1 figur

Photonic Structures Optimization Using Highly Data-Efficient Deep Learning: Application To Nanofin And Annular Groove Phase Masks

Metasurfaces offer a flexible framework for the manipulation of light properties in the realm of thin film optics. Specifically, the polarization of light can be effectively controlled through the use of thin phase plates. This study aims to introduce a surrogate optimization framework for these devices. The framework is applied to develop two kinds of vortex phase masks (VPMs) tailored for application in astronomical high-contrast imaging. Computational intelligence techniques are exploited to optimize the geometric features of these devices. The large design space and computational limitations necessitate the use of surrogate models like partial least squares Kriging, radial basis functions, or neural networks. However, we demonstrate the inadequacy of these methods in modeling the performance of VPMs. To address the shortcomings of these methods, a data-efficient evolutionary optimization setup using a deep neural network as a highly accurate and efficient surrogate model is proposed. The optimization process in this study employs a robust particle swarm evolutionary optimization scheme, which operates on explicit geometric parameters of the photonic device. Through this approach, optimal designs are developed for two design candidates. In the most complex case, evolutionary optimization enables optimization of the design that would otherwise be impractical (requiring too much simulations). In both cases, the surrogate model improves the reliability and efficiency of the procedure, effectively reducing the required number of simulations by up to 75% compared to conventional optimization techniques

Equiangular lines, mutually unbiased bases, and spin models

We use difference sets to construct interesting sets of lines in complex space. Using (v,k,1)-difference sets, we obtain k^2-k+1 equiangular lines in C^k when k-1 is a prime power. Using semiregular relative difference sets with parameters (k,n,k,l) we construct sets of n+1 mutually unbiased bases in C^k. We show how to construct these difference sets from commutative semifields and that several known maximal sets of mutually unbiased bases can be obtained in this way, resolving a conjecture about the monomiality of maximal sets. We also relate mutually unbiased bases to spin models.Comment: 23 pages; no figures. Minor correction as pointed out in arxiv.org:1104.337

Supersymmetric QCD flavor changing top quark decay

We present a detailed and complete calculation of the gluino and scalar quarks contribution to the flavour-changing top quark decay into a charm quark and a photon, gluon, or a Z boson within the minimal supersymmetric standard model including flavour changing gluino-quarks-scalar quarks couplings in the right-handed sector. We compare the results with the ones presented in an earlier paper where we considered flavour changing couplings only in the left-handed sector. We show that these new couplings have important consequences leading to a large enhancement when the mixing of the scalar partners of the left- and right-handed top quark is included. Furthermore CP violation in the flavour changing top quark decay will occur when a SUSY phase is taken into account.Comment: 14 pages, latex, 3 figure

Entropically-driven binding of mithramycin in the minor groove of C/G-rich DNA sequences

Final full-text version available at: http://dx.doi.org/10.1093/nar/gkm037.-- Supplementary Data is available.The antitumour antibiotic mithramycin A (MTA) is a DNA minor-groove binding ligand. It binds to C/G-rich tracts as a dimer that forms in the presence of divalent cations such as Mg2+. Differential scanning calorimetry, UV thermal denaturation, isothermal titration calorimetry and competition dialysis were used, together with computations of the hydrophobic free energy of binding, to determine the thermodynamic profile of MTA binding to DNA. The results were compared to those obtained in parallel using the structurally related mithramycin SK (MSK). The binding of MTA to salmon testes DNA determined by UV melting studies (Kobs = 1.2 (±0.3) x 10^5 M–1) is tighter than that of MSK (2.9 (±1.0) x 10^4 M–1) at 25°C. Competition dialysis studies showed a tighter MTA binding to both salmon testes DNA (42% C + G) and Micrococcus lysodeikticus DNA (72% C + G). The thermodynamic analysis of binding data at 25°C shows that the binding of MTA and MSK to DNA is entropically driven, dominated by the hydrophobic transfer of the antibiotics from solution to the DNA-binding site. Direct molecular recognition between MTA or MSK and DNA through hydrogen bonding and van der Waals contacts may also contribute significantly to complex formation.Supported by a grant from the Spanish Ministry of Education and Science (SAF2005-00551) and the FEDER program of the European Community. This work was carried out within the framework of the Centre de Referencia en Biotecnologia of the Generalitat de Catalunya. Funding to pay the Open Access publication charge was provided by the Ministry of Education and Science and CSIC (Spain).Peer reviewe

The Effects of Previous Misestimation of Task Duration on Estimating Future Task Duration

It is a common time management problem that people underestimate the duration of tasks, which has been termed the "planning fallacy." To overcome this, it has been suggested that people should be informed about how long they previously worked on the same task. This study, however, tests whether previous misestimation also affects the duration estimation of a novel task, even if the feedback is only self-generated. To test this, two groups of participants performed two unrelated, laboratory-based tasks in succession. Learning was manipulated by permitting only the experimental group to retrospectively estimate the duration of the first task before predicting the duration of the second task. Results showed that the experimental group underestimated the duration of the second task less than the control group, which indicates a general kind of learning from previous misestimation. The findings imply that people could be trained to carefully observe how much they misestimate task duration in order to stimulate learning. The findings are discussed in relation to the anchoring account of task duration misestimation and the memory-bias account of the planning fallacy. © 2014 Springer Science+Business Media New York