Abstract

At the LHC, a TeV-scale leptoquark (LQ) that decays dominantly to a top quark (t) and a light charged lepton (` = e, µ) would form a resonance system of boosted-t + high-pT-`. We consider all possible vector LQ models within the Buchmüller-Rückl-Wyler classifications with the desired decay. We propose simple phenomenological Lagrangians that are suitable for bottom-up/experimental studies and, at the same time, can cover the relevant parameter spaces of these models. In this simplified framework, we study the pair and single production channels of vector LQs at the LHC. Interestingly, we find that, like the pair production, the cross sections of some single production processes also depend on the parameter κ that appears in the gluon-vector LQ coupling. We adopt a search strategy of selecting events with at least one boosted hadronic top quark and exactly two high-pT leptons of the same flavor and opposite sign. This combines events from the pair and single production processes and, therefore, can enhance the discovery potential beyond that of the pair-production-only searches. For 5σ discovery we find that vector LQs can be probed up to 2.55 TeV for 100% branching ratio in the t` decay mode and O(1) new couplings at the 14 TeV LHC with 3 ab−1 of integrated luminosity.

Abstract

The optical activity of a metal nanocluster (NC) is induced either by an asymmetric arrangement of constituents or by a dissymmetric field of a chiral ligand layer. Herein, we unveil the origin of chirality in Ag29 NCs, which is attributed to the intrinsically chiral atomic arrangement. The X-ray crystal structure of a Ag29(BDT)12(TPP)4 NC (BDT: 1,3-benzenedithiol; TPP: triphenylphosphine) manifested the presence of intrinsic chirality in the outer shell capping the icosahedral achiral Ag13 core. The enantiomers of the Ag29(BDT)12(TPP)4 NC are separated by high-performance liquid chromatography (HPLC) using a chiral column for the first time, showing mirror-image circular dichroism (CD) spectra. The CD spectra are reproduced by time-dependent density functional theory (TDDFT) calculations based on enantiomeric Ag29 models with achiral 1,3-propanedithiolate ligands. The mechanism of chiral induction in the synthesis of Ag29(DHLA)12 (DHLA: a-dihydrolipoic acid) NCs with a chiral ligand system is further discussed with the aid of DFT calculations. The use of the enantiomeric DHLA ligand preferentially leads to a one-handed atomic arrangement which is more stable than the opposite one, inducing the enantiomeric excess in the population of intrinsically chiral Ag29 NCs with CD activity

Abstract

The fifty–year proposal of nondissociative racemization reaction of a tetracoordinated tetrahedral center from one enantiomer to another via a planar transition state by Hoffmann and coworkers has been explored by many research groups during the past five decades. A number of stable molecules with planar tetracoordinate and higher-coordinate centers have been designed and experimentally realized; however, there has not been a single example of molecular system that can possibly undergo such racemization. Here we show examples of molecular species that undergo inversion of stereochemistry around tetrahedral centers (Si, Al− and P+) either via a planar transition state or an intermediate state using quantum mechanical, ab initio quasi-classical dynamics calculations, and Born-Oppenheimer molecular dynamics (BOMD) simulations. This work is expected to provide potential leads for future studies on this fundamental phenomenon in chemistry.

Abstract

Recent years have witnessed utilization of modern machine learning approaches for predicting properties of material using available datasets. However, to identify potential candidates for material discovery, one has to systematically scan through a large chemical space and subsequently calculate the properties of all such samples. On the other hand, generative methods are capable of efficiently sampling the chemical space and can generate molecules/materials with desired properties. In this study, we report a deep learning based inorganic material generator (DING) framework consisting of a generator module and a predictor module. The generator module is developed based upon conditional variational autoencoders (CVAE) and the predictor module consists of three deep neural networks trained for predicting enthalpy of formation, volume per atom and energy per atom chosen to demonstrate the proposed method. The predictor and generator modules have been developed using a one hot key representation of the material composition. A series of tests were done to examine the robustness of the predictor models, to demonstrate the continuity of the latent material space, and its ability to generate materials exhibiting target property values. The DING architecture proposed in this paper can be extended to other properties based on which the chemical space can be efficiently explored for interesting materials/molecules.

Abstract

Unlike CPUs and GPUs, it is possible to use custom fixed-point data types, specified as a tuple (α, β), on FPGAs. The parameters α and β denote the number of integral and fractional bitwidths respectively. The power and area savings while performing arithmetic operations on fixed-point data types are well known to be significant over using floating-point data types. In this paper, we propose a hybrid approach involving interval analysis and SMT solvers, for estimating integral bitwidths at different compute stages, in an image processing pipeline, specified using a domain-specific language (DSL) such as PolyMage. The DSL specification facilitates the compiler analysis to infer the underlying computational structure with ease. We also propose a simple and practical profile-driven greedy heuristic search technique for fractional bitwidth analysis. Using the Horn-Schunck Optical Flow benchmark program, we demonstrate where the conventional range analysis approaches fail, and how we overcome them using the hybrid technique proposed in this paper. The integral bitwidth estimates provided by the hybrid technique on the optical flow benchmark are up to 3x times better when compared with interval analysis.

Abstract

Proteresis, a complementary effect to well-known hysteresis, is an interesting phenomenon to be explored. As we know, the hysteric device is a bistable switch whose states depend on the system's history whereas the proteretic device states' depend on the future. Though an all-optical implementation of the hysteric device has been demonstrated but its complementary behavior has yet to be contrived. Therefore, this work presents the design and development of an all-optical proteretic system using semiconductor ring lasers. The design was achieved by providing a constraint feedforward path to a hysteric feedback system. Additionally, the role of various parameters was studied in order to achieve proteresis. It is observed that the proteretic effect can be achieved only for specific conditions otherwise the system behaves as a traditional hysteric device. The experimental results match well with the theoretical Simulink results.

Abstract

Pre-detection of hypertension mostly considers the measurement of Brachial Artery Blood Pressure (BABP). Although being a standard vital, it is still considered a poor alternative for Central Blood Pressure (CBP). However, CBP is measured invasively during the process of cardiac catheterization (Cath). Though cuff-less techniques to estimate BABP are widely employed, CBP estimation has not been explored yet. Moreover, to best of our knowledge intermittent CBP estimation has not been proposed earlier. Therefore, we present a cuff-less and beat-by-beat CBP estimation technique using linear regression analysis on features extracted from continuous Electrocardiogram (ECG) and Photoplethysmograph (PPG) signals. Unlike for BABP estimation, 30 supplementary features to conventional pulse transit time such as ST-interval, P-systolic peak interval, etc., were extracted to enhance CBP accuracy. This extraction was done using Haar wavelet along with modulus maxima. Feature selection has been done using the wrapper technique and reduced using principal component analysis. Segregation of each beat was achieved with the help of constraints developed based on iteration and backtracing. This model estimates Systolic CBP with a validation error of 0.109±2.37 mmHg and Diastolic CBP with an error of 0.031±2.102 mmHg for 33 Cath lab patients.

Abstract

Since the eminent work of J. S. Bell, spatial correlations in quantum mechanics have gained much progress. Nevertheless, up to now, there is no agreement on the nature of temporal correlations. In this paper, based on the entangled-history theory, we prove that temporal correlations are just quantum channels. Moreover, by using the state tomography technology, the quantum channel can be uniquely determined. What is more, through the entanglement of formation, temporal correlations can be quantified. Cases when the temporal correlation is strongest and weakest are investigated, too.

Abstract

Quantum states that possess negative conditional von Neumann entropy provide quantum advantage in several protocols including superdense coding, state merging, distributed private randomness distillation and one-way entanglement distillation. While entanglement is an important resource, only a subset of entangled states have negative conditional von Neumann entropy. Despite this utility, a proper resource theory for conditional von Neumann entropy has not been developed, unlike that of entanglement. We pave the way for such a resource theory by characterizing the class of density matrices having non-negative conditional von Neumann entropy as convex and compact. This allows us to prove the existence of a Hermitian operator (a witness) for the detection of states having negative conditional entropy for bipartite systems in arbitrary dimensions. We show constructions of this witness and explicate its utility in the detection of useful states in the above-mentioned protocols. We provide a local decomposition of the witness and probe its implications in the context of the uncertainty principle.

Abstract

Windows whose transmittance can be modified by an applied voltage have previously been fabricated from soft, transparent elastomers sandwiched between ITO coated glass and a compliant, silver nanowire top electrode.1 In this contribution we extend the capabilities of the tunable window so that the optical transmittance can be varied spatially over the window according to voltage signals applied to different segments of the back electrode of the window, defined by patterning of individually addressable electrodes. The actuation signals are controlled using TTL-level input signals applied to high voltage switches. We also show that the spatially tunable window can be fabricated on a flexible substrate, such as PET, and the optical transmittance is not affected by bending of the substrate. The use of a polymer substrate not only increases possible applications of this class of voltage controlled light modulation device but also has the potential of reducing cost at an industrial scale by replacing more costly ITO coated glass substrate.