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D. Derkach

Publications and source records attributed to D. Derkach.

11 recordsLinked to original sources

RatanSunPy: A robust preprocessing pipeline for RATAN-600 solar radio observations data

The advancement of observational technologies and software for processing and visualizing spectro-polarimetric microwave data obtained with the RATAN-600 radio telescope opens new opportunities for studying the physical characteristics of solar plasma at the levels of the chromosphere and corona. These levels remain some difficult to detect in the ultraviolet and X-ray ranges. The development of such methods allows for more precise investigation of the fine structure and dynamics of the solar atmosphere, thereby deepening our understanding of the processes occurring in these layers. The obtained data also can be utilized for diagnosing solar plasma and forecasting solar activity. However, using RATAN-600 data requires extensive data processing and familiarity with the RATAN-600. This paper introduces RatanSunPy, an open-source Python package developed for accessing, visualizing, and analyzing multi-band radio observations of the Sun from the RATAN-600 solar complex. The package offers comprehensive data processing functionalities, including direct access to raw data, essential processing steps such as calibration and quiet Sun normalization, and tools for analyzing solar activity. This includes automatic detection of local sources, identifying them with NOAA (National Oceanic and Atmospheric Administration) active regions, and further determining parameters for local sources and active regions. By streamlining data processing workflows, RatanSunPy enables researchers to investigate the fine structure and dynamics of the solar atmosphere more efficiently, contributing to advancements in solar physics and space weather forecasting.

astro-ph.SR

Global analysis of charm mixing parameters and determination of the CKM angle $\gamma$

We present an updated global analysis of beauty decays sensitive to the angle $\gamma$ of the Cabibbo-Kobayashi-Maskawa matrix and of $D$-meson mixing data in the framework of approximate universality, in which CP violation in $D-\overline{D}$ mixing is described in terms of two universal weak phases corresponding to dispersive and absorptive contributions. We extract the fundamental theoretical parameters determining absorptive and dispersive contributions to $D$ meson mixing and CP violation, together with the angle $\gamma$. The results for the charm mixing parameters are $x_{12} \simeq x = (0.401 \pm 0.043)\%$ and $y_{12} \simeq y = (0.610 \pm 0.017)\%$, while the two CP-violating phases are given by $\phi_2^M = (0.13 \pm 0.70)^{\circ}$ and ${\phi}_2^{\Gamma} = (2.1 \pm 1.6)^{\circ}$. The angle $\gamma$ is found to be $\gamma = (65.7 \pm 2.5)^{\circ}$, in excellent agreement with the indirect determination from the Unitarity Triangle analysis.

hep-ph

Technical Design Report of the Spin Physics Detector at NICA

The Spin Physics Detector collaboration proposes to install a universal detector in the second interaction point of the NICA collider under construction (JINR, Dubna) to study the spin structure of the proton and deuteron and other spin-related phenomena using a unique possibility to operate with polarized proton and deuteron beams at a collision energy up to 27 GeV and a luminosity up to $10^{32}$ cm$^{-2}$ s$^{-1}$. As the main goal, the experiment aims to provide access to the gluon TMD PDFs in the proton and deuteron, as well as the gluon transversity distribution and tensor PDFs in the deuteron, via the measurement of specific single and double spin asymmetries using different complementary probes such as charmonia, open charm, and prompt photon production processes. Other polarized and unpolarized physics is possible, especially at the first stage of NICA operation with reduced luminosity and collision energy of the proton and ion beams. This document is dedicated exclusively to technical issues of the SPD setup construction.

hep-ex

A Comparison of CPU and GPU implementations for the LHCb Experiment Run 3 Trigger

The LHCb experiment at CERN is undergoing an upgrade in preparation for the Run 3 data taking period of the LHC. As part of this upgrade the trigger is moving to a fully software implementation operating at the LHC bunch crossing rate. We present an evaluation of a CPU-based and a GPU-based implementation of the first stage of the High Level Trigger. After a detailed comparison both options are found to be viable. This document summarizes the performance and implementation details of these options, the outcome of which has led to the choice of the GPU-based implementation as the baseline.

physics.ins-det

Using machine learning to speed up new and upgrade detector studies: a calorimeter case

In this paper, we discuss the way advanced machine learning techniques allow physicists to perform in-depth studies of the realistic operating modes of the detectors during the stage of their design. Proposed approach can be applied to both design concept (CDR) and technical design (TDR) phases of future detectors and existing detectors if upgraded. The machine learning approaches may speed up the verification of the possible detector configurations and will automate the entire detector R\&D, which is often accompanied by a large number of scattered studies. We present the approach of using machine learning for detector R\&D and its optimisation cycle with an emphasis on the project of the electromagnetic calorimeter upgrade for the LHCb detector\cite{lhcls3}. The spatial reconstruction and time of arrival properties for the electromagnetic calorimeter were demonstrated.

physics.ins-det

Opportunities in Flavour Physics at the HL-LHC and HE-LHC

Motivated by the success of the flavour physics programme carried out over the last decade at the Large Hadron Collider (LHC), we characterize in detail the physics potential of its High-Luminosity and High-Energy upgrades in this domain of physics. We document the extraordinary breadth of the HL/HE-LHC programme enabled by a putative Upgrade II of the dedicated flavour physics experiment LHCb and the evolution of the established flavour physics role of the ATLAS and CMS general purpose experiments. We connect the dedicated flavour physics programme to studies of the top quark, Higgs boson, and direct high-$p_T$ searches for new particles and force carriers. We discuss the complementarity of their discovery potential for physics beyond the Standard Model, affirming the necessity to fully exploit the LHC's flavour physics potential throughout its upgrade eras.

hep-ph

Deep learning for inferring cause of data anomalies

Daily operation of a large-scale experiment is a resource consuming task, particularly from perspectives of routine data quality monitoring. Typically, data comes from different sub-detectors and the global quality of data depends on the combinatorial performance of each of them. In this paper, the problem of identifying channels in which anomalies occurred is considered. We introduce a generic deep learning model and prove that, under reasonable assumptions, the model learns to identify 'channels' which are affected by an anomaly. Such model could be used for data quality manager cross-check and assistance and identifying good channels in anomalous data samples. The main novelty of the method is that the model does not require ground truth labels for each channel, only global flag is used. This effectively distinguishes the model from classical classification methods. Being applied to CMS data collected in the year 2010, this approach proves its ability to decompose anomaly by separate channels.

physics.data-an

LHCb trigger streams optimization

The LHCb experiment stores around $10^{11}$ collision events per year. A typical physics analysis deals with a final sample of up to $10^7$ events. Event preselection algorithms (lines) are used for data reduction. Since the data are stored in a format that requires sequential access, the lines are grouped into several output file streams, in order to increase the efficiency of user analysis jobs that read these data. The scheme efficiency heavily depends on the stream composition. By putting similar lines together and balancing the stream sizes it is possible to reduce the overhead. We present a method for finding an optimal stream composition. The method is applied to a part of the LHCb data (Turbo stream) on the stage where it is prepared for user physics analysis. This results in an expected improvement of 15% in the speed of user analysis jobs, and will be applied on data to be recorded in 2017.

cs.DC

The UTfit Collaboration Average of $D$ meson mixing data: Winter 2014

We update the analysis of $D$ meson mixing including the latest experimental results as of January 2014. We derive constraints on the parameters $M_{12}$, $Γ_{12}$ and $Φ_{12}$ that describe $D$ meson mixing using all available data, allowing for CP violation. We also provide posterior distributions for observable parameters appearing in $D$ physics.

hep-ph

The UTfit Collaboration Average of D meson mixing data: Spring 2012

We derive constraints on the parameters $M_{12}$, $Γ_{12}$ and $Φ_{12}$ that describe $D$ meson mixing using all available data, allowing for CP violation. We also provide posterior distributions and predictions for observable parameters appearing in $D$ physics.

hep-ph

Update of the Unitarity Triangle Analysis

We present the status of the Unitarity Triangle Analysis (UTA), within the Standard Model (SM) and beyond, with experimental and theoretical inputs updated for the ICHEP 2010 conference. Within the SM, we find that the general consistency among all the constraints leaves space only to some tension (between the UTA prediction and the experimental measurement) in BR(B -> tau nu), sin(2 beta) and epsilon_K. In the UTA beyond the SM, we allow for New Physics (NP) effects in (Delta F)=2 processes. The hint of NP at the 2.9 sigma level in the B_s-\bar B_s mixing turns out to be confirmed by the present update, which includes the new D0 result on the dimuon charge asymmetry but not the new CDF measurement of phi_s, being the likelihood not yet released.

hep-ph