Measurement of the W gamma Production Cross Section in Proton-Proton Collisions at root s=13 TeV and Constraints on Effective Field Theory Coefficients

A fiducial cross section for W gamma production in proton-proton collisions is measured at a center-of-mass energy of 13 TeV in 137 fb(-1) of data collected using the CMS detector at the LHC. The W -> e nu and mu nu decay modes are used in a maximum-likelihood fit to the lepton-photon invariant mass distribution to extract the combined cross section. The measured cross section is compared with theoretical expectations at next-to-leading order in quantum chromodynamics. In addition, 95% confidence level intervals are reported for anomalous triple-gauge couplings within the framework of effective field theory.Peer reviewe

Search for top squark production in fully hadronic final states in proton-proton collisions at root s=13 TeV

A search for production of the supersymmetric partners of the top quark, top squarks, is presented. The search is based on proton-proton collision events containing multiple jets, no leptons, and large transverse momentum imbalance. The data were collected with the CMS detector at the CERN LHC at a center-of-mass energy of 13 TeV, and correspond to an integrated luminosity of 137 fb(-1). The targeted signal production scenarios are direct and gluino-mediated top squark production, including scenarios in which the top squark and neutralino masses are nearly degenerate. The search utilizes novel algorithms based on deep neural networks that identify hadronically decaying top quarks and W bosons, which are expected in many of the targeted signal models. No statistically significant excess of events is observed relative to the expectation from the standard model, and limits on the top squark production cross section are obtained in the context of simplified supersymmetric models for various production and decay modes. Exclusion limits as high as 1310 GeVare established at the 95% confidence level on the mass of the top squark for direct top squark production models, and as high as 2260 GeV on the mass of the gluino for gluino-mediated top squark production models. These results represent a significant improvement over the results of previous searches for supersymmetry by CMS in the same final state.Peer reviewe

Measurements of Higgs boson production cross sections and couplings in the diphoton decay channel at root s=13 TeV

Measurements of Higgs boson production cross sections and couplings in events where the Higgs boson decays into a pair of photons are reported. Events are selected from a sample of proton-proton collisions at root s = 13TeV collected by the CMS detector at the LHC from 2016 to 2018, corresponding to an integrated luminosity of 137 fb(-1). Analysis categories enriched in Higgs boson events produced via gluon fusion, vector boson fusion, vector boson associated production, and production associated with top quarks are constructed. The total Higgs boson signal strength, relative to the standard model (SM) prediction, is measured to be 1.12 +/- 0.09. Other properties of the Higgs boson are measured, including SM signal strength modifiers, production cross sections, and its couplings to other particles. These include the most precise measurements of gluon fusion and vector boson fusion Higgs boson production in several different kinematic regions, the first measurement of Higgs boson production in association with a top quark pair in five regions of the Higgs boson transverse momentum, and an upper limit on the rate of Higgs boson production in association with a single top quark. All results are found to be in agreement with the SM expectations.Peer reviewe

Measurements of production cross sections of the Higgs boson in the four-lepton final state in proton–proton collisions at √s=13Te

Production cross sections of the Higgs boson are measured in the H → Z Z → 4 ℓ (ℓ=e,μ) decay channel. A data sample of proton–proton collisions at a center-of-mass energy of 13Te, collected by the CMS detector at the LHC and corresponding to an integrated luminosity of 137fb-1 is used. The signal strength modifier μ, defined as the ratio of the Higgs boson production rate in the 4 ℓ channel to the standard model (SM) expectation, is measured to be μ=0.94±0.07(stat)-0.08+0.09(syst) at a fixed value of mH=125.38Ge. The signal strength modifiers for the individual Higgs boson production modes are also reported. The inclusive fiducial cross section for the H → 4 ℓ process is measured to be 2.84-0.22+0.23(stat)-0.21+0.26(syst)fb, which is compatible with the SM prediction of 2.84±0.15fb for the same fiducial region. Differential cross sections as a function of the transverse momentum and rapidity of the Higgs boson, the number of associated jets, and the transverse momentum of the leading associated jet are measured. A new set of cross section measurements in mutually exclusive categories targeted to identify production mechanisms and kinematical features of the events is presented. The results are in agreement with the SM predictions.STFC, Marie-Curie program and the European Research Council and Horizon 2020 Gran

FISHER'S EQUATION

Bachelor'sBACHELOR OF SCIENCE (HONOURS

Nonvolatile Memristive Materials and Physical Modeling for In‐Memory and In‐Sensor Computing

Separate memory and processing units are utilized in conventional von Neumann computational architectures. However, regarding the energy and the time, it is costly to shuffle data between the memory and the processing entity, and for data‐intensive applications associated with artificial intelligence, the demand is ever increasing. A paradigm shift in traditional architectures is required, and in‐memory computing is one of the non‐von‐Neumann computing strategies. By harnessing physical signatures of the memory, computing workloads are administered in the same memory element. For in‐memory computing, a wide range of memristive material (MM) systems have been examined. Moreover, developing computing schemes that perform in the same sensory network and that minimize the data shuffle between the processing unit and the sensing element is a requirement, to process large volumes of data efficiently and decrease the energy consumption. In this review, an overview of the switching character and system signature harnessed in three archetypal MM systems is rendered, along with an integrated application survey for developing in‐sensor and in‐memory computing, viz., brain‐inspired or analogue computing, physical unclonable functions, and random number generators. The recent progress in theoretical studies that reveal the structural origin of the fast‐switching ability of the MM system is further summarized

Nonvolatile Memristive Materials and Physical Modeling for In‐Memory and In‐Sensor Computing

Publication status: PublishedSeparate memory and processing units are utilized in conventional von Neumann computational architectures. However, regarding the energy and the time, it is costly to shuffle data between the memory and the processing entity, and for data‐intensive applications associated with artificial intelligence, the demand is ever increasing. A paradigm shift in traditional architectures is required, and in‐memory computing is one of the non‐von‐Neumann computing strategies. By harnessing physical signatures of the memory, computing workloads are administered in the same memory element. For in‐memory computing, a wide range of memristive material (MM) systems have been examined. Moreover, developing computing schemes that perform in the same sensory network and that minimize the data shuffle between the processing unit and the sensing element is a requirement, to process large volumes of data efficiently and decrease the energy consumption. In this review, an overview of the switching character and system signature harnessed in three archetypal MM systems is rendered, along with an integrated application survey for developing in‐sensor and in‐memory computing, viz., brain‐inspired or analogue computing, physical unclonable functions, and random number generators. The recent progress in theoretical studies that reveal the structural origin of the fast‐switching ability of the MM system is further summarized.</jats:p

Toward Single-Cell Multiple-Strategy Processing Shift Register Powered by Phase-Change Memory Materials

Modern innovations are built on the foundation of computers. Compared to von Neumann architectures having separate storage and processing units, in‐memory operation utilizes the same primary structure for data storage and register operations, therefore promising to decrease the energy cost of computing in data centers significantly. While various studies centered on exploring novel device architectures, designing suitable material platforms is extremely challenging. Herein, all four material (M) states of a phase‐change material (PCM) in data storage and register operations are utilized and a combined M state‐based model framework for developing in‐memory operation is demonstrated, along with nonvolatile, reprogrammable single‐cell shift register operations. A previously unachieved multiple‐level‐per‐volt different‐initial‐state multilevel set process with further computing in the M state‐based platform is realized. The simplest case of a programmable shift register configuration is demonstrated with a serial‐in–serial‐out processing strategy, as well as more complex reprogrammable processing schemes using the M state‐type platform, showing previously unreported nonvolatile shift register types with multiple processing approaches. This paves the way for development of next‐generation low‐power‐electronic systems using two‐terminal‐based semiconductor materials

Ultra-efficient MCF-7 cell ablation and chemotherapy-integrated electrothermal therapy with DOX–WS2–PEG–M13 nanostructures

Abstract Clinical trials have generated encouraging outcomes for the utility of thermal agents (TAs) in cancer thermal therapy (TT). Although the fast breakdown of TAs alleviates safety concerns, it restricts the thermal stability necessary for effective treatment. TAs with excellent thermal stability, on the other hand, deteriorate slowly. Rare are the approaches that address the trade-off between high thermal stability and quick deterioration of TAs. Here we control the thermal signature of WS2-type 2D materials by utilizing previously undescribed DOX–WS2–PEG–M13 nanostructures (we term them D nanostructures) through Joule heating phenomena, and develop an integrated system for TT for enhancing thermal performance, and simultaneously, maintaining rapid degradation, and chemotherapy for efficacious treatment. A relative cell viability of ~ 50% was achieved by the D-based TT (DTT) configuration, as well as a 1 nM drug concentration. The D-driven chemotherapy (DCT) model also attains a relative cell viability of 80% for 1 nM drug concentration, while a 1-week degradation time was revealed by the D nanostructure. Theoretical studies elucidate the drug molecule–nanostructure and drug-on-nanostructure–solution interaction-facilitated enhancement in drug loading and drug release performance in DCT varieties. As a result, this work not only proposes a “ideal TA” that circumvents TA restrictions, but also enables proof-of-concept application of WS2-based materials in chemotherapy-unified combination cancer therapy. Graphical Abstrac

Ultrafast Near-Ideal Phase-Change Memristive Physical Unclonable Functions Driven by Amorphous State Variations.

Funder: SUTD‐MIT International Design CenterThere is an ever-increasing demand for next-generation devices that do not require passwords and are impervious to cloning. For traditional hardware security solutions in edge computing devices, inherent limitations are addressed by physical unclonable functions (PUF). However, realizing efficient roots of trust for resource constrained hardware remains extremely challenging, despite excellent demonstrations with conventional silicon circuits and archetypal oxide memristor-based crossbars. An attractive, down-scalable approach to design efficient cryptographic hardware is to harness memristive materials with a large-degree-of-randomness in materials state variations, but this strategy is still not well understood. Here, the utilization of high-degree-of-randomness amorphous (A) state variations associated with different operating conditions via thermal fluctuation effects is demonstrated, as well as an integrated framework for in memory computing and next generation security primitives, viz., APUF, for achieving secure key generation and device authentication. Near ideal uniformity and uniqueness without additional initial writing overheads in weak memristive A-PUF is achieved. In-memory computing empowers a strong exclusive OR (XOR-) and-repeat A PUF construction to avoid machine learning attacks, while rapid crystallization processes enable large-sized-key reconfigurability. These findings pave the way for achieving a broadly applicable security primitive for enhancing antipiracy of integrated systems and product authentication in supply chains