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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Improved Beam Loss Accounting with Fast Data Acquisition (DAQ) Chassis

Identifying the source of beam loss events in the CE-BAF accelerator can be a challenging task. However, with our new prototype system, this task becomes more effi-cient. The system, developed in the fall of 2022, utilizes a dispersive beam position monitor (BPM) and the exist-ing switched electrode electronics BPM hardware. Previ-ously a commercial off-the-shelf data acquisition (DAQ) system was employed to capture BPM wire signals at a sample rate of 20 kS/s. The fast shutdown signal triggered the system, which disables the beam at the injector. Analysis of beam position and energy variation before a beam loss event was used to determine if the beam loss event was associated with an energy transient. The proto-type system, implemented using National Instruments hardware and LabVIEW® software, relied on a software trigger. Manual post-processing was required to ascertain whether the fault was due to an un-tripped cavity with a gradient or phase transient. This work focuses on deploying a Fast DAQ Chassis to monitor BPM hardware in real time and during beam loss events. This system was originally developed and in-stalled in CEBAF to monitor the time-domain RF control signals in the legacy analog RF systems. This technology was leveraged to also monitor BPM signals. As the new system employs a hardware trigger, developing tools to automatically identify faults linked to energy transients unrelated to cavity faults will be straightforward. This paper will discuss the project's initial updates, underlin-ing the crucial role of each member of our team in this achievement

Tiskumara, J.↗
DOE OSTI2024

MiniDAQ-3: Providing concurrent independent subdetector data-taking on CMS production DAQ resources

The data acquisition (DAQ) of the Compact Muon Solenoid (CMS) experiment at CERN, collects data for events accepted by the Level-1 Trigger from the different detector systems and assembles them in an event builder prior to making them available for further selection in the High Level Trigger, and finally storing the selected events for offline analysis. In addition to the central DAQ providing global acquisition functionality, several separate, so-called “MiniDAQ” setups allow operating independent data acquisition runs using an arbitrary subset of the CMS subdetectors. During Run 2 of the LHC, MiniDAQ setups were running their event builder and High Level Trigger applications on dedicated resources, separate from those used for the central DAQ. This cleanly separated MiniDAQ setups from the central DAQ system, but also meant limited throughput and a fixed number of possible MiniDAQ setups. In Run 3, MiniDAQ-3 setups share production resources with the new central DAQ system, allowing each setup to operate at the maximum Level-1 rate thanks to the reuse of the resources and network bandwidth. Configuration management tools had to be significantly extended to support the synchronization of the DAQ configurations needed for the various setups. We report on the new configuration management features and on the first year of operational experience with the new MiniDAQ-3 system.

Amoiridis, Vassileios↗
DOE OSTI2026

The high level trigger and express data production at STAR

To meet the demands of the Beam Energy Scan phase-II (BES-II) program, the STAR experiment at the Relativistic Heavy Ion Collider (RHIC) developed a dual real-time framework consisting of a High Level Trigger (HLT) and an Express Data Production system (xProduction). The HLT operates online within the Data Acquisition (DAQ) chain on a dedicated multi-core CPU cluster with the option to offload compute-intensive kernels to Xeon Phi coprocessors. It uses parallelized algorithms, such as the Cellular Automaton (CA) Track Finder, to perform rapid tracking, vertexing, and event filtering. This allows it to select events of interest in real time and provide immediate feedback on detector and beam conditions. In contrast, the xProduction workflow runs concurrently and independently of the DAQ loop. It applies near offline-quality calibration and reconstruction within hours of data collection. The xProduction input is the express data stream, whose content can be enriched by HLT trigger/priority selections under DAQ/HLT resource constraints, and it uses the STAR calibration/conditions framework, incorporating online calibration/QA information when available. This enables early preliminary physics analysis, including the reconstruction of rare signals, such as hyperons and hypernuclei. It also provides collaboration-wide access to analysis-ready datasets. Together, the HLT and xProduction systems form a complementary architecture: the HLT performs online event selection while the xProduction chain delivers high-quality results within a short amount of time. This integrated framework has enabled the prompt reconstruction of the $^5_Λ$ He hypernucleus with high statistical significance and the efficient processing of hundreds of millions of heavy-ion collision events. In conclusion, its demonstrated scalability and robustness establish a model for future high-luminosity experiments requiring both online event filtering and rapid access to analysis-quality data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Region of Interest Filter in DUNE DAQ

The Deep Underground Neutrino Experiment (DUNE) is the next generation neutrino experiment currently under construction. It consists of a broadband neutrino beam at Fermilab, a high precision near detector, and the largest liquid argon time projection chamber far detector ever designed at the Sanford Underground Research Facility (SURF). The Region of Interest (ROI) filter is designed for DUNE’s online Data Acquisition (DAQ) system to address data rate constraints and enable low energy physics in the <10 MeV range. The filter employs zero suppression on the detector signal, and by tuning the readout window and threshold the data rates can be reduced by >90%. Performance of the ROI is analyzed in LArsoft on MARLEY generated low energy MC events propagated through the detector simulation. Notably, the optimized ROI filter enables a lower trigger threshold for readout at ~5-10 MeV, allowing DUNE to explore low-energy physics, specifically focusing on solar boron 8 neutrinos which are relevant in this energy range. This advancement enhances DUNE's scientific capabilities, opening avenues for detailed analyses of previously inaccessible low-energy neutrino interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

High-Throughput Data Processing at FRIB Using ESnet

Real-time or nearly real-time (nearline) data processing methods are critical tools as detector technologies and data acquisition (DAQ) systems allow for higher data rates and volumes. The introduction of the energy sciences network (ESnet), a U.S. Department of Energy (DOE) supported high-speed network for scientific research, creates opportunities to leverage the computing power of DOE facilities like the National Energy Research Scientific Computing Center (NERSC). As a first step toward realizing a DOE Office of Science Integrated Research Infrastructure (IRI) pattern, an automated workflow was developed to remotely process data obtained from a nuclear physics experiment at the Facility for Rare Isotope Beams (FRIB) at NERSC with data transferred between FRIB and NERSC over ESnet. The workflow demonstrated the ability to process one week’s worth of experimental data in approximately 90 min and was used successfully for nearline analysis during a recently completed FRIB experiment. Here, a summary of the workflow development and results of recent demonstrations will be presented.

Data processing↗
DOE OSTI2025

Machine Learning-Based Extreme Data Reduction for Prompt Supernova Pointing at DUNE

One of the goals of the Deep Underground Neutrino Experiment (DUNE) is to use the massive underground liquid argon time projection chamber (LArTPC) detectors at its far site for multimessenger astronomy (MMA), in the detection of neutrinos from core-collapse supernovae (SNe). Its current baseline trigger strategy detects activity in the detector that is consistent with supernova (SN) neutrinos and saves the raw data for further offline analysis but provides no prompt pointing information crucial for optical follow-ups by other observatories. This approach is based on the assumption that prompt pointing determination using raw data is computationally prohibitive. In this article, we demonstrate a proof-of-concept based on applying extreme data reduction on the buffered SN data in the DUNE data acquisition (DAQ) system’s front-end computers using a machine learning (ML) workflow. This reduces the data by ~5 orders of magnitude, allowing a full track reconstruction to be carried out quickly on a single server. The total time to perform the ML-based data reduction and the full track reconstruction is less than the time to transfer the SN data back to Fermilab or a high-performance computing (HPC) center. This shows that prompt processing of raw SN data is possible and, in fact, trivial once the data have been reduced to reject radiological backgrounds, paving the way to a high-quality SN pointing trigger that is based on fully reconstructed data instead of trigger primitives (TPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Advancing \textit{otsdaq}: Enhancements for Usability, Accuracy, and Robustness

High-energy physics (HEP) experiments require data acquisition (DAQ) systems that can orchestrate complex detector operations, high data throughput, and responsive, real-time feedback to operators. Traditional DAQ stacks, which are often bespoke, command-line driven and highly specific, impose large learning curves on users. The Off-The-Shelf Data Acquisition (\textit{otsdaq}) framework was created to address these issues by offering a highly customizable and scalable browser-based ’desktop’ environment, in which experiment-specific control and monitoring applications can be easily deployed and integrated. Although the initial development of the \textit{otsdaq} software was aimed at the Fermilab Test Beam Facility, \textit{otsdaq} is now being leveraged for broader deployment, including the upcoming Mu2e experiment, where real-time monitoring of field-programmable gate array (FPGA)-based Data Transfer Controllers (DTCs), Clock and Fanout (CFO) boards, and several other subsystems are critical. We contribute a set of targeted improvements to \textit{otsdaq}: bitmap visualization functionality for configured data, improved and corrected delta-based DTC throughput metrics, version control (VC)-backed source navigation for console messages, custom navigation hooks to eliminate disruptive user interface glitches, and copy-to-clipboard support for macro execution history. These changes improve usability, reduce debugging time, and increase accuracy in performance data as Mu2e moves toward commissioning.

Mohammed, A. [Unlisted, US]↗
DOE OSTI2023

SPLENDAQ: A Detector-Agnostic Data Acquisition System for Small-Scale Physics Experiments

Many scientific applications from rare-event searches to condensed matter system characterization to high-rate nuclear experiments require time-domain triggering on a raw stream of data, where the triggering is generally threshold-based or randomly acquired. When carrying out detector R &D, there is a need for a general data acquisition (DAQ) system to quickly and efficiently process such data. In the SPLENDOR collaboration, we are developing the Python-based SPLENDAQ package for this exact purpose—it offers two main features for offline analysis of continuous data: a threshold triggering algorithm based on the time-domain optimal filter formalism and an algorithm for randomly choosing nonoverlapping segments for noise measurements. Further, combined with the commercially available Moku platform, developed by Liquid Instruments, we have a full pipeline of event building off raw data with minimal setup. Here, we review the underlying principles of this detector-agnostic DAQ package and give concrete examples of its utility in various applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Advancing $otsdaq$ for Optimized Data Acquisition

High-energy physics (HEP) experiments demand data acquisition (DAQ) systems capable of orchestrating complex detector operations, high data throughput, and responsive, real-time feedback. Traditional systems often have steep learning curves, making onboarding difficult for new users. The Off-The-Shelf Data Acquisition $otsdaq$ framework was developed to address these issues by providing a modular and flexible interface that is easier to operate while remaining customizable enough for experimental setups. As the upcoming Mu2e experiment prepares for deployment, improving stability, usability, and performance has become increasingly critical. Our work enhances $otsdaq$ with features that streamline visualization, correct data metrics, improve debugging workflows, and stabilize the user interface.

Mohammed, Ali (ORCID:0009000860386626)↗
DOE OSTI2024

Oscilloscope Data Push Program

Data acquisition (DAQ) is a complex and costly process. Creating DAQ systems for analyzing a system requires expensive electronics and a dedicated team of engineers for support, posing a challenge for users who readily need data. This project is a proof of concept to create a temporary or one-off DAQ system using equipment commonly available to every team. We aim to automate the data acquisition process from the Rohde \& Schwarz RTO 1044 oscilloscope, convert the acquired binary data into floating point values, and store the results in a CSV file format. By developing a Python program to handle these tasks, we seek to reduce the manual effort involved in data collection, significantly increasing efficiency.

Osei-Tutu, Jason↗
DOE OSTI2021

Evaluation of a high-performance storage buffer with 3D XPoint devices for the DUNE data acquisition system

The DUNE detector is a neutrino physics experiment that is expected to take data starting from 2028. The data acquisition (DAQ) system of the experiment is designed to sustain several TB/s of incoming data which will be temporarily buffered while being processed by a software based data selection system. In DUNE, some rare physics processes (e.g. Supernovae Burst events) require storing the full complement of data produced over 1-2 minute window. These are recognised by the data selection system which fires a specific trigger decision. Upon reception of this decision data are moved from the temporary buffers to local, high performance, persistent storage devices. In this paper we characterize the performance of novel 3DXPoint SSD devices under different workloads suitable for high-performance storage applications. We then illustrate how such devices may be applied to the DUNE use-case: to store, upon a specific signal, 100 seconds of incoming data at 1.5 TB/s distributed among 150 identical units each operating at approximately 10GB/s.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Commissioning of the Mu2e tracker DAQ, planning for the Vertical Slice Test and pre-pattern recognition studies

The primary objective of the Mu2e experiment at Fermilab is to search for the neutrino-less coherent $\mu \rightarrow e$ conversion in the field of an aluminum nucleus ($\mu^- \text{Al} \rightarrow e^- \text{Al}$). The signature of this process is a monochromatic Conversion Electron (CE) with an energy of approximately 104.97 MeV \cite{bartoszek2015mu2e}. Within the Standard Model (SM), the branching ratio for this process, including neutrino masses and oscillation, is expected to be less than $\mathcal{O}(10^{-50})$. This value is far beyond current experimental capabilities. However, models of physics beyond the SM predict much higher relative rates, approaching an observable level. The SINDRUM II experiment set an upper limit on muon conversion at $7 \times 10^{-13}$ (90\% CL) on Au target \cite{SINDRUMII:2006dvw}, and the Mu2e collaboration aims to improve this limit by four orders of magnitude. Observing this process would provide a clear evidence of physics beyond the Standard Model. A brief discussion of the theoretical and experimental aspects is provided in Chapter \ref{intr}. Mu2e adopts a sophisticated experimental setup to achieve its goals, further described in Chapter \ref{mu2echapter}. The central part of the Mu2e detector is the tracker, that consists of 18 tracking stations. The tracker must provide excellent momentum resolution, approximately 1 MeV/c, to distinguish the monochromatic CE signal from the background. To minimize the energy losses, a straw tube tracker will be used \cite{bobbb}. Chapter \ref{chaptertrk} provides an overview of the straw tracker design and its working principles. This Thesis presents a comprehensive study of the Mu2e tracker, covering complementary aspects from initial commissioning to optimization and first steps of the calibration processes. My work at Fermilab has been focused on the complete Data Acquisition (DAQ) testing from both hardware and software perspectives. I was involved in the commissioning of the Mu2e DAQ system and the Vertical Slice Test (VST) of the tracker. The VST encompasses the entire testing chain, from the straws to the readout, and to processed data on disk. I was also focused on the offline analysis, especially on pre-pattern recognition studies, to explore the best methods for identifying $\delta$-electrons during the data taking. Chapter \ref{commissioning} details the commissioning of the tracker DAQ system, emphasizing the importance of understanding of the readout process before the data acquisition. This includes validating the readout logic and firmware through Monte Carlo simulations to confirm functionality and buffering, monitoring the quality of the data from the tracker preamplifiers and front-end electronics, and assessing overall DAQ performance to ensure reliability during future calibration and data-taking. Chapter \ref{planning} discusses the initial steps towards the tracker calibration. The ultimate goal is to perform a time calibration of the first assembled station of the tracker using cosmic muons, aiming for a longitudinal hit position resolution better than 4 cm. This involves determining the signal propagation times and channel-to-channel delays. I performed a Monte Carlo study to determine the impact of the station orientation on the quality of the calibration, in particular on the cosmic track reconstruction, focusing on potential biases that could arise. These studies provide essential insights into the operation, optimization, and calibration of the Mu2e tracker system. Given the high data volume expected during Mu2e operations, estimated at approximately 7 PBytes per year, optimizing memory usage and minimizing CPU consumption are critical. A significant challenge lies in effectively flagging $\delta$-electron hits, which are the primary source of hits in the tracker, without compromising the efficiency of CE hit detection and track reconstruction. A detailed study of pre-pattern recognition and a thorough comparison of two $\delta$-electron flagging algorithms is provided in Chapter \ref{delta}. In Chapter \ref{conclusions}, the findings are concisely summarized, offering a comprehensive synthesis of the research and emphasizing the key insights derived from this study.

43 PARTICLE ACCELERATORS↗
NASA NTRS2021

Combined Cycle Engine Large-Scale Inlet for Mode Transition Studies: System Identification Rack Software Design

This report describes the development of the system identification (SysID) rack custom application code. This code is used to automate the system identification experimental processes for the National Aeronautics and Space Administration (NASA) Combined Cycle Engine Large-Scale Inlet for Mode Transition Experiments testbed. This series of experiments took place in the NASA Glenn Research Center (GRC) 10 foot by 10 foot (10x10) Supersonic Wind Tunnel (SWT) test facility. The SysID code was developed to apply command signals to testbed actuators, receive actuator feedback signals, and acquire sensor data which is used to identify the dynamics of the experimental processes. This code development and the process identification experiments were conducted during Phase-2 testing at various operating points. These points were predefined from data collected during the Phase-1 testbed characterization experiments. The developed SysID code was executed on a NASA designed and built real-time data acquisition (DAQ) and controls (SysID) rack. This report focuses on the development of the SysID rack real-time DAQ and control hardware and the custom application code used to automate the system identification process. The implementation of this reliable and efficient data acquisition and controls development tool is demonstrated by presenting an example of experimental data collected to be used for system identification.

R Thomas↗
DOE OSTI2024

Oscilloscope Data Push Program

This paper details the development of a Python program designed to automate the data acquisition and conversion for an oscilloscope for the purposes of a one-off/temporary data acquisition system for users that readily need data, and do not have the option of obtaining a Data Acquisition (DAQ) solution. Creating DAQ systems for analyzing a system requires expensive electronics and a dedicated team of engineers for support. Traditionally, manual data collection and processing are time consuming and prone to error. By automating these processes, the cost, efficiency and accuracy of data handling are improved upon. This project involves the creation of a program that interacts with the oscilloscope. During this interaction, there are various functions being performed such as the acquisition of waveform data via floating points, generating plots with the acquired wave points, and storing of floating points in a CSV file format for future reference and plotting purposes. While the initial aim of the project included continuous logging to a cloud database, this was deferred due to time constraints. The results portrayed an almost-instant rate of data collection with a buffer time, showcasing the potential for further integration and real-time data processing.

Osei-Tutu, Jason↗
DOE OSTI2023

Performance and Commissioning of the BigBite Timing Hodoscope for Nucleon Form Factor Measurements at Jefferson Lab

The BigBite Timing Hodoscope detector is the primary subject of this thesis. The Super BigBite Spectrometer is a Jefferson Lab Hall A Collaboration project that has and will continue to measure nucleon electromagnetic form factors. This spectrometer includes the Timing Hodoscope which provides high resolution particle timing data for scattered electrons in the electron arm of BigBite. The Timing Hodoscope utilizes 90, 25 × 25 × 600 mm3 scintillator bars stacked on top of each other to form a single detector plane, and these bars are connected to 180 photo-multiplier tubes via light guides. Particles collide with the scintillating material creating a shower of optical photons and these particle events in the bars are collected to generate signals that are readout by the data acquisition (DAQ) electronics. NINO ASIC amplifier-discriminator cards output signals from the photo-multiplier tubes into analogue and logic signals, which are sent to analogue-to-digital (ADC) and time-to-digital (TDC) converter data acquisition readout modules. This data is then used for analysis of the detector. The focus of this thesis is the construction, commissioning, calibration, and performance of the BigBite Timing Hodoscope before and during the first of five nucleon electromagnetic form factor experiments at Jefferson Lab Hall A. Before the neutron magnetic form factor, G n M, experiment, cosmic ray data was collected during commissioning to confirm proper operation of the Timing Hodoscope electronics by observing the ADC and TDC data. Commissioning studies for charge normalization, gain matching, and other ADC and TDC detector data variables were performed before moving the detector into Hall A. Following installation in Hall A, several calibration studies were implemented to fine-tune the detector in preparation for use in the experiment. The calibration studies included analysis of timing cuts, TDC alignment, the time-walk effect, time difference offsets, and scintillator velocity corrections. Once the Timing Hodoscope was well-calibrated, data-taking during the experiment commenced and the beam-on-target data was used to characterize the Timing Hodoscope performance during the G n M experiment run-time. The performance analysis included studies observing energy deposit, cluster size, rates, accidentals, pile-up, tracking efficiency, position resolution, and time resolution. After application of physics cuts to ensure a data set comprised of particle tracks corresponding to elastic electrons, which is the main data of interest for measurement of G n M, the Timing Hodoscope is shown on average across all kinematic settings to have a >98% tracking efficiency, a position resolution of 4-6 cm in the non-dispersive plane and 1.5-2 cm in the dispersive plane, and a time resolution of 500-750 ps. These performance results are compared to a GEANT4 based performance simulation of the BigBite Timing Hodoscope for reference, showing to what degree the measured performance values match those taken from the simulation.

Marinaro, Ralph↗
DOE OSTI2020

DAQExpert the service to increase CMS data-taking efficiency

The Data Acquisition (DAQ) system of the Compact Muon Solenoid (CMS) experiment at the LHC is a complex system responsible for the data readout, event building and recording of accepted events. Its proper functioning plays a critical role in the data-taking efficiency of the CMS experiment. In order to ensure high availability and recover promptly in the event of hardware or software failure of the subsystems, an expert system, the DAQ Expert, has been developed. It aims at improving the data taking efficiency, reducing the human error in the operations and minimising the on-call expert demand. Introduced in the beginning of 2017, it assists the shift crew and the system experts in recovering from operational faults, streamlining the post mortem analysis and, at the end of Run 2, triggering fully automatic recovery without human intervention. DAQ Expert analyses the real-time monitoring data originating from the DAQ components and the high-level trigger updated every few seconds. It pinpoints data flow problems, and recovers them automatically or after given operator approval. We analyse the CMS downtime in the 2018 run focusing on what was improved with the introduction of automated recovery; present challenges and design of encoding the expert knowledge into automated recovery jobs. Furthermore, we demonstrate the web-based, ReactJS interfaces that ensure an effective cooperation between the human operators in the control room and the automated recovery system. We report on the operational experience with automated recovery.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Leveraging the Run 3 experience for the evolution of the ATLAS software-based readout towards HL-LHC

The High-Luminosity Large Hadron Collider (HL-LHC), scheduled to start operating in 2030, aims to increase the instantaneous luminosity by a factor of 10 compared to the LHC. To match this increase, the ATLAS experiment has been implementing a major upgrade program divided into two phases. The first phase (Phase-I), completed in 2022, introduced new trigger and detector systems that have been used during the Run 3 data taking period which began in July 2022. These systems have been used in conjunction with the new Data Acquisition (DAQ) Readout system, based on a software application called Software Readout Driver (SW ROD). SW ROD receives and aggregates data from the front-end electronics via the Front-End Link eXchange (FELIX) system and passes aggregated data fragments to the High-Level Trigger (HLT) system. During Run 3, SW ROD operates in parallel with the legacy Readout System (ROS) at an input rate of 100 kHz. For the Phase-II, the legacy ROS will be completely replaced with a new system based on the next generation of FELIX and an evolution of the SW ROD application called Data Handler. Data Handler has the same functional requirements as SW ROD but must be able to operate at an input rate of 1 MHz. To facilitate this evolution the SW ROD has been implemented using plugin architecture. This contribution presents the design and implementation of the SW ROD application for Run 3, along with the strategy for its evolution to the Phase-II Readout system. It discusses the lessons learned during Run 3 and describes the challenges that have been addressed to accomplish the demanding performance requirements of HL-LHC.

Kolos, Serguei [Univ. of California, Irvine, CA (U↗
DOE OSTI2021

Development of a High Throughput PCIe Card for DAQ System in the ATLAS and DUNE Experiments

In the Run 3 upgrade of ATLAS experiment, the FELIX (Front-End LInk eXchange) system has been prepared as the interface between front-end electronics and common Data Acquisition (DAQ) systems. Based on a PCIe card hosted in commodity server, FELIX's flexibilty makes it has also been adopted by other experiments, such as the Single-Phase ProtoDUNE (Prototype for the Deep Underground Neutrino Experiment), sPHENIX and CBM experiments. The same PCIe based architecture is proposed for use in the ATLAS HL-LHC (High Luminosity Large Hadron Collider) upgrade and the DUNE experiment. To this end, the next generation of FELIX I/O card FLX-801 has been developed. It supports 25+ Gbps high speed fiber optical links and 16-lane Gen4 PCIe interface. There is an on-card DDR4 module to buffer event data for DUNE experiment. This paper reports on the test results for the demonstrator of this next generation card, with which main functions have been successfully evaluated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗