bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spherical collapse of non-top-hat profiles in the presence of dark
energy with arbitrary sound speed
Authors: Batista R.C. , de Oliveira H.P. , Abramo L.R.W. 
Published: February 2023

Abstract
We study the spherical collapse of non-top-hat matter fluctuations in the presence of
dark energy with arbitrary sound speed. The model is described by a system of partial differential
equations solved using a pseudo-spectral method with collocation points. This method can reproduce
the known analytical solutions in the linear regime with an accuracy better than 10-6% and
better than 10-2% for the virialization threshold given by the usual spherical collapse
model. We show the impact of nonlinear dark energy fluctuations on matter profiles, matter
peculiar velocity and gravitational potential. We also show that phantom dark energy models with
low sound speed can develop a pathological behaviour around matter halos, namely negative energy
density. The dependence of the virialization threshold density for collapse on the dark energy
sound speed is also computed, confirming and extending previous results in the limit for
homogeneous and clustering dark energy.
Threshold of primordial black hole formation against
velocity dispersion in matter-dominated era
Authors: Harada Tomohiro , Kohri Kazunori , Sasaki Misao , Terada Takahiro , Yoo Chul-Moon 
Published: February 2023

Abstract
We study the effects of velocity dispersion on the formation of primordial black
holes (PBHs) in a matter-dominated era. The velocity dispersion is generated through the
nonlinear growth of perturbations and has the potential to impede the gravitational collapse and
thereby the formation of PBHs. To make discussions clear, we consider two distinct length
scales. The larger one is where gravitational collapse occurs which could lead to PBH formation,
and the smaller one is where the velocity dispersion develops due to nonlinear interactions. We
estimate the effect of the velocity dispersion on the PBH formation by comparing the free-fall
timescale and the timescale for a particle to cross the collapsing region. As a demonstration, we
consider a log-normal power spectrum for the initial density perturbation with the peak value
σ
0
2 at a scale that corresponds to the larger scale. We find that the threshold value of
the density perturbation δ̃
th at the horizon entry for the PBH formation
scales as δ̃
th ∝ σ
0
2/5 for σ
0 ≪ 1.
Family of CV states of definite parity and their metrological power
Authors: Podoshvedov Mikhail S , Podoshvedov Sergey A 
Published: February 2023

Abstract
We introduce a new family of continuous variable (CV) states of definite parity originating from the single mode squeezed vacuum (SMSV) state by subtracting an arbitrary number of photons from it. A beam splitter with arbitrary transmittance and reflectance parameters redirects input photons in an indistinguishable manner to the output and measuring modes followed by probabilistic measurement, thereby converting the initial SMSV photon distribution into a new one after we know the number of registered photons. The family of the measurement-induced CV states is solely determined by the SMSV parameter which inevitably decreases when generating the CV states. We show that the quantum state engineering of CV states of definite parity by subtraction of multiphoton state from input SMSV state can significantly enhance their nonclassical properties (more squeezing, larger value of quantum Fisher information) compared to the initial state from which they originate, which, combined with a significant gain in brightness, makes them attractive for ultra-precise measurements. The potential of the new family of CV states of a certain parity, to which original SMSV, no doubt, belongs, can become decisive for a new push to implementation of optical quantum metrology protocols.
Investigation of Z-boson decay into

and

baryons within the NRQCD factorization approach*
Authors: Luo Xuan , Fu Hai-Bing , Tian Hai-Jiang 
Published: February 2023

Abstract

Z-boson decay provides a good opportunity to search for the

baryon because a large number of its events can be collected at high energy colliders. In this paper, we perform a complete investigation of the indirect production of the

and

baryons via the Z-boson decay process

with a

quark under the NRQCD factorization approach. After considering the contribution from the diquark states

,

,

, and

, the calculated branching fractions are

and

. Furthermore, the

and

production events are predicted to be of the order of

and

at the LHC collider, and the order of

and

for the CEPC collider. We then estimate the production ratio for

with

in Z-boson decay, that is,

and

, respectively. Finally, we present the differential decay widths of

and

with respect to

and z distributions and analyze the uncertainties.
Open quantum system approach for heavy quark thermalization*
Authors: Xie Zhuoxuan , Chen Baoyi 
Published: February 2023

Abstract
We treat heavy quark as an open quantum system in a hot medium and rederive the stochastic Schrödinger equation (SSE) from the full Schrödinger equation for both heavy quarks and the medium. We apply the SSE to the dynamical evolutions of a heavy quark (as a system) in the static hot medium (as an environment). Heavy quarks interact with the medium via random scatterings, which exchange the momentum and phase factor randomly between two wave functions of the system and the environment. The exchange of momentum and phase factor results in the transition between different eigenstates of the system. These are included via an external stochastic potential in the Hamiltonian of SSE. Stochastic wave functions of a heavy quark are evolved with the stochastic external potential. The mean wave functions and corresponding momentum distributions of heavy quarks are obtained after the ensemble average over a large set of stochastic wave functions. We present the thermalization of heavy quarks in the static medium with different coupling strengths.
Normalizing Flows for LHC Theory
Authors: Butter Anja 
Published: February 2023

Abstract
Over the next years, measurements at the LHC and the HL-LHC will provide us with a wealth of new data. The best hope to answer fundamental questions, like the nature of dark matter, is to adopt big data techniques in simulations and analyses to extract all relevant information. On the theory side, LHC physics crucially relies on our ability to simulate events efficiently from first principles. These simulations will face unprecedented precision requirements to match the experimental accuracy. Innovative ML techniques like generative networks can help us overcome limitations from the high dimensionality of the phase space. Such networks can be employed within established simulation tools or as part of a new framework. Since neural networks can be inverted, they open new avenues in LHC analyses.
The STEM paradox: Factors affecting diversity in STEM fields
Authors: Cherney I D 
Published: February 2023

Abstract
Women obtain more than half of U.S. undergraduate degrees in biology, chemistry, and mathematics, yet they earn less than 20% of computer science, engineering, and physics undergraduate degrees (NSF). Why are women represented in some STEM fields more than others? The STEM Paradox or Gender Equality Paradox show that countries with greater gender equality have a lower percentage of female STEM graduates. This phenomenon as well as other factors explaining gender disparities in STEM participation and some possible solutions are discussed.
Outlook on software framework in low and intermediate energy nuclear physics
Authors: Matta Adrien 
Published: February 2023

Abstract
Over the past decades nuclear physics experiments have seen a drastic increase in complexity. With the arrival of second generation radioactive ion beam facilities all over the world, the run for exploring more and more exotic nuclei is raging. The low intensity of RI-beams requires more complex setup, larger solid angle coverage and detection of a wider variety of charged and neutral particles. Design, construction and operation of a variety of complex instruments used in such experiments require many software developments. The short lifetime of experimental setups and multiple combinations of instruments demand a strong methodology. As the community is shifting to this new paradigm, the quest for the optimum framework is becoming central in the field. In this outlook we will introduce the specificity of the nuclear physics community, technical needs of such frameworks, and give an overview of the existing ones, with an emphasize on the difficult balance between computing performances, versatility and integration with other frameworks.
Anomaly detection of I/O behaviours in HEP computing cluster based on unsupervised machine learning
Authors: Wang Lu , Hu Qingbao , Chen Juan 
Published: February 2023

Abstract
Problematic I/O pattern is the major cause of low efficient HEP jobs. In a cluster with tens of thousands of job slots, locating the source of an anomalous workload is a nontrivial task. Automatic anomaly detection can largely shorten the recovery time of these situations and reduce manpower for problem diagnoses. This paper provides a data-driven approach to solve this problem. We design and implement an anomaly detection system based on Isolation Forest, a very efficient and scalable machine learning algorithm for spatial anomaly detection in high dimension space. Historical monitoring I/O patterns collected from the Lustre file system provides a sufficient statistical basis for model training and updating. Routine model updates and job tagging ensures adaptability and promptness. Web-based visualization and sorting tools facilitate the validation of model prediction. With the detection system, time spent on tracing the source of a problematic workload can be reduced from hours to minutes.
An array-oriented Python interface for FastJet
Authors: Roy Aryan , Pivarski Jim , Freer Chad Wells 
Published: February 2023

Abstract
Analysis on HEP data is an iterative process in which the results of one step often inform the next. In an exploratory analysis, it is common to perform one computation on a collection of events, then view the results (often with histograms) to decide what to try next. Awkward Array is a Scikit-HEP Python package that enables data analysis with array-at-a-time operations to implement cuts as slices, combinatorics as composable functions, etc. However, most C++ HEP libraries, such as FastJet, have an imperative, one-particle-at-a-time interface, which would be inefficient in Python and goes against the grain of the array-at-a-time logic of scientific Python. Therefore, we developed fastjet, a pip-installable Python package that provides FastJet C++ binaries, the classic (particle-at-a-time) Python interface, and the new array-oriented interface for use with Awkward Array. The new interface streamlines interoperability with scientific Python software beyond HEP, such as machine learning. In one case, adopting this library along with other array-oriented tools accelerated HEP analysis code by a factor of 20. It was designed to be easily integrated with libraries in the Scikit-HEP ecosystem, including Uproot (file I/O), hist (histogramming), Vector (Lorentz vectors), and Coffea (high-level glue). We discuss the design of the fastjet Python library, integrating the classic interface with the array oriented interface and with the Vector library for Lorentz vector operations. The new interface was developed as open source.
Clustering in the Heterogeneous Reconstruction Chain of the CMS HGCAL Detector
Authors: Alves Bruno , Pantaleo Felice , Rovere Marco 
Published: February 2023

Abstract
We present an important milestone for the CMS High Granularity Calorimeter (HGCAL) event reconstruction: the deployment of the GPU clustering algorithm (CLUE) to the CMS software. The connection between GPU CLUE and the preceding GPU calibration step is thus made possible, further extending the heterogeneous chain of HGCAL’s reconstruction framework. In addition to improvements brought by CLUE’s deployment, new recursive device kernels are added to efficiently calculate the position and energy of CLUE clusters. Data conversions between GPU and CPU are included to facilitate the validation of the algorithms and increase the flexibility of the reconstruction. For the first time in HGCAL, conditions data are deployed to the GPU and made available on demand at any stage of the heterogeneous reconstruction. This is achieved via a new geometry ordering scheme in which physical and memory locations are connected. This scheme is successfully tested with the GPU CLUE version reported here, and is expected to have a broad range of applicability for future heterogeneous developments in CMS. Finally, the performance of the combined calibration and clustering algorithms on GPU is assessed and compared to its CPU counterpart.
Commissioning LHCb’s GPU high level trigger
Authors: Agapopoulou Christina 
Published: February 2023

Abstract
From 2022 onward, the upgraded LHCb experiment will use a triggerless readout system collecting data at an event rate of 30 MHz. A software-only High Level Trigger will enable unprecedented flexibility for trigger selections. During the first stage (HLT1), a sub-set of the full offline track reconstruction for charged particles is run to select particles of interest based on single or two-track selections. This includes decoding the raw data, clustering of hits, pattern recognition, as well as track fitting, ghost track rejection with machine learning techniques and finally event selections. HLT1 will be processed entirely on O(100) GPUs. We will present the integration of the GPU HLT1 into LHCb’s data acquisition system in preparation for data taking in 2022.
Configuration Information System for online processing and data monitoring in the NICA experiments
Authors: Alexandrov E. , Alexandrov I. , Chebotov A. , Gertsenberger K. , Filozova I. , Priakhina D. , Shestakova G. 
Published: February 2023

Abstract
The collection, storage and processing of experimental data are an integral part of modern high-energy physics experiments. The Configuration Information System (CIS) based on the Configuration Database (ConfigDb) is an essential element of a complex of information systems developed for the NICA experiments. The CIS is used to store and provide data on the configuration of the experiment hardware and software systems when collecting data from the detectors in online mode. The ConfigDb stores both a set of various configuration parameters and descriptions of a sequence of online software tasks to be started and run during experiment sessions. The system allows loading configuration information, activating hardware setups and launching all necessary software applications with the required parameters on the specified distributed nodes. The CIS architecture mainly contains the ConfigDb and Configuration Manager, which uses the Dynamic Deployment System API for managing tasks and providing intercommunication. The manager loads configuration data from the database, starts software tasks in a described sequence and supports task process management. The client-server architecture of the CIS is presented. The client has been implemented as a Web service to manage configuration parameters by users.
Data Handling Optimization in Russian Data Lake Prototype
Authors: Alekseev A , Kiryanov A , Klimentov A , Korchuganova T , Mitsyn V , Oleynik D , Petrosyan A , Smirnov S , Zarochentsev A 
Published: February 2023

Abstract
CERN experiments are preparing for the HL-LHC era, which will bring an unprecedented volume of scientific data. These data will need to be stored and processed by thousands of physicists, but expected resource growth is nowhere near the extrapolated requirements of existing models, in terms of both storage volume and compute power. Opportunistic CPU resources such as HPCs and university clusters can provide extra CPU cycles, but there is no opportunistic storage. In this article, we will present the main architectural ideas, deployment details, and test results, with emphasis on our research to build a prototype of a distributed data processing and storage system with a focus on optimizing the efficiency of resources by reducing overhead costs for accessing the data. The described prototype was built using the geographically distributed WLCG sites and university clusters in Russia.
Detray: a compile time polymorphic tracking geometry description
Authors: Salzburger A , Niermann J , Yeo B , Krasznahorkay A 
Published: February 2023

Abstract
A detailed geometry description is essential to any high quality track reconstruction application. In current C++ based track reconstruction software libraries this is often achieved by an object oriented, polymorphic geometry description that implements different shapes and objects by extending a common base class. Such a design, however, has been shown to be problematic when attempting to adapt these applications to run on heterogeneous computing hardware, particularly on hardware accelerators. We present detray, a compile time polymorphic and yet accurate track reconstruction geometry description which is part of the ACTS parallelization R&D effort. detray is built as an index based geometry description with a shallow memory layout, that uses variadic template programming to allow custom shapes and intersection algorithms rather than inheritance from abstract base classes. It is designed to serve as a potential geometry and navigation backend for ACTS and as such implements the ACTS navigation model of boundary portals and purely surface based geometric entities. detray is designed to work with a dedicated memory management library and thus can be instantiated as a geometry model in host and device code.
Development of the automatic procedures for spinor matrix element calculation with massive particles
Authors: Dydyshka Y 
Published: February 2023

Abstract
We present a new version the procedure for calculation helicity amplitudes with massive particles. First, we introduce a massive 4-momentum into higher dimensional space, where it can be treated as massless. Secondly, we apply the symmetry properties of gauge theories and get quite simple matrix elements in terms of the field strength.
Distributed file systems performance tests on Kubernetes/Docker clusters
Authors: Fornari Federico , Cavalli Alessandro , Cesini Daniele , Falabella Antonio , Fattibene Enrico , Morganti Lucia , Prosperini Andrea , Sapunenko Vladimir 
Published: February 2023

Abstract
Modern data centers need distributed file systems to provide user applications with access to data stored on a large number of nodes. The ability to mount a distributed file system and leverage its native application programming interfaces in a Docker container, combined with the advanced orchestration features provided by Kubernetes, can improve flexibility in installing, monitoring and recovering data management and transfer services. At INFN-CNAF some distributed file systems (i.e. IBM Spectrum Scale, CephFS and Lustre-ZFS) deployment tests with Kubernetes and Docker have been conducted recently with positive results. The purpose of this paper is to show the throughput scores of the previously mentioned file systems when their servers are containerized and run on bare metal machines using a container orchestration framework. This is a preliminary study: for the time being, only sequential read/write tests have been considered.
EOS deployment on Ceph RBD/CephFS with K8s
Authors: Fornari Federico , Costantini Alessandro , Cavalli Alessandro , Cesini Daniele , Duma Doina Cristina , Falabella Antonio , Fattibene Enrico , Mascetti Luca , Morganti Lucia , Peters Andreas-Joachim , Prosperini Andrea , Sapunenko Vladimir 
Published: February 2023

Abstract
The present activity focused on the integration of different storage systems (EOS [1] and Ceph [2]) with the aim to combine the high level scalability and stability of EOS services with the reliability and redundancy features provided by Ceph. The work has been carried out as part of the collaboration between the national center of INFN (Italian Institute for Nuclear Physics) dedicated to Research and Development on Information and Communication Technologies and the Conseil Européen pour la Recherche Nucléaire (CERN), with the goal of evaluating and testing different technologies for next-generation storage challenges. This work leverages the well-known open-source container orchestration system, Kubernetes [3], for managing file system services. The results obtained by measuring the performances of the different combined technologies, comparing for instance block device and file system as backend options provided by a Ceph cluster deployed on physical machines, are shown and discussed in the manuscript.
Evaluation and Implementation of Various Persistent Storage Options for CMSWEB Services in Kubernetes Infrastructure at CERN
Authors: Imran Muhammad , Kuznetsov Valentin , Paparrigopoulos Panos , Trigazis Spyridon , Pfeiffer Andreas 
Published: February 2023

Abstract
This paper summarizes the various storage options that we implemented for the CMSWEB cluster in Kubernetes infrastructure. All CMSWEB services require storage for logs, while some services also require storage for data. We also provide a feasibility analysis of various storage options and describe the pros/cons of each technique from the perspective of the CMSWEB cluster and its users. In the end, we also propose recommendations according to the service needs. The first option is the CephFS which can be mounted multiple times across various clusters and VMs and works very well with k8s. We use it both for data and the logs. The second option is the Cinder volume. It is the block storage that runs the filesystem on top of it. It can only be attached to one instance at a time. We use this option only for the data. The third option is S3 storage. It is object storage that offers a scalable storage service that can be used by applications compatible with the Amazon S3 protocol. It is used for the logs. For S3, we explored two mechanisms. For the first scenario, we consider fluentd that runs as a sidecar container in the service pods and sends logs to S3 bucket. For the second scenario, we considered filebeat that runs as a sidecar container in the service pod and scaps those logs to fluentd which runs as a daemonset in each node and sends those logs to S3 in the end. The fourth option is EOS. We configured EOS inside the pods of the CMSWEB services. The fifth option that we explored is to use dedicated VMs that have Ceph volume attached to them. In EOS and VM, the logs from the service pods are sent to EOS/VM using the rsync approach. The last option is to send service logs to Elasticsearch. It has been implemented using fluentd that runs as a daemonset in each node. In parallel to the sending logs to S3 fluentd also sends those logs to the Elasticsearch infrastructure at CERN.