diff --git "a/abs_29K_G/test_abstract_long_2405.01359v1.json" "b/abs_29K_G/test_abstract_long_2405.01359v1.json" new file mode 100644--- /dev/null +++ "b/abs_29K_G/test_abstract_long_2405.01359v1.json" @@ -0,0 +1,98 @@ +{ + "url": "http://arxiv.org/abs/2405.01359v1", + "title": "GAIA: A General AI Assistant for Intelligent Accelerator Operations", + "abstract": "Large-scale machines like particle accelerators are usually run by a team of\nexperienced operators. In case of a particle accelerator, these operators\npossess suitable background knowledge on both accelerator physics and the\ntechnology comprising the machine. Due to the complexity of the machine,\nparticular subsystems of the machine are taken care of by experts, who the\noperators can turn to. In this work the reasoning and action (ReAct) prompting\nparadigm is used to couple an open-weights large language model (LLM) with a\nhigh-level machine control system framework and other tools, e.g. the\nelectronic logbook or machine design documentation. By doing so, a multi-expert\nretrieval augmented generation (RAG) system is implemented, which assists\noperators in knowledge retrieval tasks, interacts with the machine directly if\nneeded, or writes high level control system scripts. This consolidation of\nexpert knowledge and machine interaction can simplify and speed up machine\noperation tasks for both new and experienced human operators.", + "authors": "Frank Mayet", + "published": "2024-05-02", + "updated": "2024-05-02", + "primary_cat": "cs.CL", + "cats": [ + "cs.CL", + "physics.acc-ph" + ], + "label": "Original Paper", + "paper_cat": "Retrieval AND Augmented AND Generation AND RAG", + "gt": "Large-scale machines like particle accelerators are usually run by a team of\nexperienced operators. In case of a particle accelerator, these operators\npossess suitable background knowledge on both accelerator physics and the\ntechnology comprising the machine. Due to the complexity of the machine,\nparticular subsystems of the machine are taken care of by experts, who the\noperators can turn to. In this work the reasoning and action (ReAct) prompting\nparadigm is used to couple an open-weights large language model (LLM) with a\nhigh-level machine control system framework and other tools, e.g. the\nelectronic logbook or machine design documentation. By doing so, a multi-expert\nretrieval augmented generation (RAG) system is implemented, which assists\noperators in knowledge retrieval tasks, interacts with the machine directly if\nneeded, or writes high level control system scripts. This consolidation of\nexpert knowledge and machine interaction can simplify and speed up machine\noperation tasks for both new and experienced human operators.", + "main_content": "Introduction Particle accelerators are complex machines that consist of a large number of subsystems. Although many processes are automated and feedback systems are in place, experiments and machine supervision need to be performed by a group of operators. These operators usually have an accelerator physics background and mostly know how the technology works. They especially know how to setup and tune the machine parameters for certain working points and experiments using high-level graphical user interfaces, which are connected to low-level machine control software. Due to the complexity of the machine, some subsystems of the machine are taken care of by experts, who the operators can turn to. This work shows that it is possible to support the day-to-day operation of a complex machine like a particle accelerator using a large language model (LLM), an object-oriented high-level machine control system framework, as well as a number of interfaces to knowledge bases such as the electronic logbook. The system is able to assist the operators on many levels, e.g. by producing Python scripts, which when executed perform a task defined by an input prompt to the LLM. To this end, the reasoning and action prompting paradigm (ReAct) [Yao et al., 2023] is implemented. This way a multi-expert system is realized, mimicking the real world, where the complex machine is operated by many subsystem experts. arXiv:2405.01359v1 [cs.CL] 2 May 2024 \fGAIA TECHNICAL REPORT 2 Background \u2013 Accelerator Controls Modern accelerators are routinely operated using sophisticated low-level control systems, such as EPICS1, TANGO2, TINE3, or DOOCS4. These control systems allow for high frequency machine and beam diagnostics, as well as control, which is an essential requirement for highly available, brilliant beams for the users. In addition, control systems are often paired with high speed data acquisitions systems (DAQ), capable of recording pulse synchronized data at the machine repetition rate. In order to access the machine, or derived data (via middle layer servers), users can usually leverage libraries and wrappers for common programming and scripting languages such as C, C++, Java, or Python. Easy to use toolkits are sometimes provided to create graphical user interfaces (GUIs) for simple interaction with control system servers (e.g. parameter scans), or data visualization. On many machines there is the need to perform experiments, which are more complex than simple oneor twodimensional parameter scans. In this case users and operators have to either perform the tasks manually, or to write measurement scripts using e.g. Python. In this work a Python-based scripting toolkit called doocs_generic_experiment is used, which simplifies the task of writing a measurement script substantially. The toolkit follows an object-oriented approach and is based on a set of so called actions, which resemble real-world sub-tasks an operator would have to perform if the experiment would be conducted manually. These actions can be grouped into procedures, which can reach arbitrary complexity. In addition of performing a set of action in series, procedures can also run multiple actions in parallel to save time. The final experiment can then consit of either one, or many of these procedures. Due to the easy to unterstand concept of stringing together common actions and procedures, the toolkit enables rapid prototyping of complex experiments and enables fulland semi-automation of experimental campaigns, which would otherwise take too long to perform manually. In addition, the concept of encapsulating commonly performed actions adds a safety layer as the room for possible mistakes is reduced. Figure 1 shows a selection of currently available actions and procedures. Action ReadAction WriteAction RichWriteAction RichReadAction IfElseAction LogAction UserInputAction PauseAction WaitForStabilityAction ParallelReadAction WaitForChangeAction SubscriptionAction ProcessingAction AlarmConditionAction NeuralNetAction LaserSwitchAction ScreenAction PulseShotModeAction BeamRecenteringAction LaserApertureAction MagnetDegaussAction MagnetCycleAction PrintToLogbookAction PolariXOnBeamSwitchAction Procedure ParallelProcedure DOOCSManager DOOCSAddress SingleDataProcedure ScanProcedure ImageScanProcedure OutputManager MachineStateProcedure PhaseAdvanceScanProcedure FourDimTomographyProcedure FiveDimTomographyProcedure Figure 1: A selection of procedures and actions available via the doocs_generic_experiment Python module. 1https://epics.anl.gov, last access 2024-04-26 2https://www.tango-controls.org, last access 2024-04-26 3https://tine.desy.de, last access 2024-04-26 4https://doocs.desy.de, last access 2024-04-26 2 \fGAIA TECHNICAL REPORT 3 Multi-Expert System \u2013 GAIA In order to realize the operations assistant, the open-weights LLM Mixtral 8x7B Instruct v0.1 (8 bit quantization) [Jiang et al., 2024] is used as the main model. Mixtral 8x7B supports a context size of 32k tokens. This is ideal for reasoning and chain of thought (CoT) prompting [Wei et al., 2022, 2023, Yao et al., 2023]. The model runs locally on a single Nvidia A100 80GB GPU in the DESY Maxwell cluster and is served by Ollama5 (model tag: mixtral:8x7b-instruct-v0.1-q8_0). Note that the Maxwell node does not need to directly interface with the accelerator control system. All interaction and knowledge retrieval is performed by a client application, which runs on a computer, which is part of the control system network. This client can then interface with control system servers, file servers, the Mattermost messaging system, etc., if needed. The client is called General AI Assistant (GAIA). One of the main concepts of the ReAct prompting scheme is tool use. As the agent engages in its inner monologue, or chain of thought, it will eventually reach a point where it needs to either perform an action, or retrieve information. This is analogous to an operator deciding to either use control system tools to control or diagnose certain parts of the machine, or to turn to an expert to retrieve information. Technically, the agent, which is implemented using LangChain6, interrupts the LLM output stream and injects the result of a particular tool use. The agent might, for example, come to the conclusion that it needs to retrieve the current value of a particular machine parameter. In this case, within its chain of thought, it may suggest using doocs_generic_experiment based tools to perform this particular task. Another example would be the retrieval of information from the electronic logbook. One advantage of the concept of tool use is that it helps to circumvent the LLM token limit. In many cases knowledge retrieval may involve classical retrieval augmented generation (RAG) [Lewis et al., 2021] implementations, which use their own disjunct LLM context. This way, only the result of the knowledge retrieval process is injected into the agents context window. In addition, this allows the use of fine-tuned RAG systems potentially based on other LLMs. If the task is to devise a certain experimental procedure at a particle accelerator, at least two tools/experts may be needed. The first expert may provide knowledge about the layout of the beam line, as well as how to utilize the specific elements for a given task. The second expert may on the other hand be proficient in producing doocs_generic_experiment code and how to interface with the accelerator control system. The agent is able to combine the output of the two tools, yielding a suitable Python program from a prompt, such as \"I want to operate the accelerator at maximum energy gain\". Figure 2 shows a selection of tools used in the current GAIA implementation. In the following section a number of example prompts to GAIA are shown. Note that the chain of thought, which is shown in the examples, is usually not visible to the user. \u21e8 Look up info about the accelerator layout \u21e8 Uses an already existing lattice file parser AcceleratorLatticeTool \u21e8 Helps looking up DOOCS addresses \u21e8 Uses simple sequence matching DOOCSAddressHelperTool \u21e8 Summarizes .pptx files from weekly meetings \u21e8 Uses basic prompting and its own context OperationsMeetingSummarizer \u21e8 Gives access to the electronic logbook \u21e8 Uses an existing CLI interface to the logbook LogbookTool \u21e8 Let\u2019s the agent contact experts \u21e8 Uses Mattermost API MattermostChatBotTool \u21e8 Runs Python code \u21e8 \u2026for example generated by DGEHelperTool PythonCodeRunnerTool \u21e8 ReadActionTool, LogbookActionTool, \u2026 \u21e8 MachineStateProcedureTool, \u2026 Wrappers around Actions and Procedures \u21e8 Explains doocs_generic_experiment \u21e8 Can also generate code DGEHelperTool \u21e8 \u2026in order to get accurate calculations CalculatorTool Figure 2: A selection of tools to be used by GAIA. 5http://www.ollama.com, last access 2024-04-26 6http://www.langchain.com, last access 2024-04-26 3 \fGAIA TECHNICAL REPORT 4 Examples In this section example prompts to GAIA are presented. The results are shown in Figs 3 through 7. Note that some parts of the output are truncated, as indicated by \u2019[...]\u2019. The chain of thought, shown in the examples, is usually not visible to the user. Also, names are redacted if needed. The example cases show the versatility of the system, which includes access to meeting notes (Fig. 3), guidance on how to use doocs_generic_experiment (Fig. 4), information retrieval from the electronic logbook (Fig. 5), machine data access using doocs_generic_experiment and subsequently contacting human experts via Mattermost chat (Fig. 6), and running complex tasks using an ad hoc generated doocs_generic_experiment script (Fig. 7). fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? Can you summarize the last operations meeting? > Entering new AgentExecutor chain\u2026 Thought: To answer this question, I need to use the \"Operation Meeting Summarizer\" tool and provide the date of the meeting as input. I will ask the user for the date if it has not been provided. Action: ``` { \"action\": \"User Input Tool\", \"action_input\": { \"question\": \"What is the date of the operation meeting you want me to summarize?\" } } ``` What is the date of the operation meeting you want me to summarize? 29.01.2024 Observation: 29.01.2024 Thought: Based on the user input, I can now use the \"Operation Meeting Summarizer\" tool to generate a summary of the operations meeting that took place on the given date. Action: ```json { \"action\": \"Operation Meeting Summarizer\", \"action_input\": { \"date\": \"2024-01-29\" } } ``` Observation: The ARES Operation Meeting summary from January 29, 2024 covers [\u2026] > Finished chain. The ARES Operation Meeting summary from January 29, 2024 covers the week 4 achievements, difficulties, and notes. During this week, the team re-established the velocity bunching working point using fewer quads, optimized transmission through the DLA, and worked on various scans and tuning. They also faced a TWS1 modulator fault due to low solenoid water flow rate, which was fixed. On the ARES beamline, the EA.L2 camera had ROI and background subtraction applied, showing likely Cherenkov/Smith-Purcell effects but no coherence yet. PolariX development included switching on the OVC, testing higher water temperatures for BOC detuning, conditioning both vertical and horizontal streaking, and developing measurement and analysis scripts. PolariX measurements consisted of streaking along various angles covering the full range of the phase shifter and emittance measurement using DLQZM1 and the D1 screen. For week 5, [Name 1] will be on shift with [Name 2] on Monday, followed by [Name 1] with Frank on Tuesday, [Name 1] with [Name 3] on Wednesday, [Name 4] on Thursday for AutoAcc beamtime, and [Name 5] on Friday for UKE beamtime preparation. Additionally, there are plans for connecting the kicker magnet, installing in-air stages, laser work, DLA activities, and more during this week. What can I do for you? Figure 3: Example: \"Can you summarize the last operations meeting?\". Names are redacted. 4 \fGAIA TECHNICAL REPORT fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? I want to write values to multiple devices in parallel using doocs_generic_experiment. How do I do this? > Entering new AgentExecutor chain\u2026 Thought: To answer this question, I need to understand how to write values to multiple devices in parallel using the doocs_generic_experiment Python module. I can use the DGE Helper tool for this. Action: ```json { \"action\": \"DGE Helper\", \"action_input\": { \"query\": \"How to write values to multiple devices in parallel using doocs_generic_experiment?\" } } ``` Observation: To write values to multiple devices in parallel using [\u2026] To write values to multiple devices in parallel using `doocs_generic_experiment`, you can use a `ParallelProcedure` with a list of `WriteAction`. Here is an example: ```python from doocs_generic_experiment import DOOCSAddress, WriteAction, ParallelProcedure # Define the addresses and values to write addresses = [DOOCSAddress('dev1', writable=True), DOOCSAddress('dev2', writable=True)] values = [10, 20] # Create a list of WriteAction instances write_actions = [WriteAction(address, value) for address, value in zip(addresses, values)] # Create a ParallelProcedure instance and add the write actions parallel_procedure = ParallelProcedure(actions=write_actions) # Run the procedure parallel_procedure.run() ``` In this example, we first define a list of `DOOCSAddress` instances with the `writable` flag set to `True`. We then create a list of `WriteAction` instances using a list comprehension and the `zip` function to pair the addresses and values. Finally, we create a `ParallelProcedure` instance and add the write actions to it. When we run the procedure, the write actions will be executed in parallel. What can I do for you? Figure 4: Example: \"I want to write values to multiple devices in parallel using doocs_generic_experiment. How do I do this?\". 5 \fGAIA TECHNICAL REPORT fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? Did they manage to define the new hexapod parking position today? > Entering new AgentExecutor chain\u2026 To answer this question, I need to check the logbook entries for today related to the hexapod parking position. I will use the Logbook tool with the 'n_days' parameter set to 0 to get the entries from today. Action: ``` { \"action\": \"Logbook\", \"action_input\": { \"n_days\": 0, \"n_entries\": null } } ``` Observation: Logbook name: SINBAD-ARESelog e-Logbook, Date: Wednesday 14. February 2024 Logbook entries: [\u2026] Date: 14.02.2024 18:14 Authors: [Name 1] Title: New Hexapod Parking Position Content: The grid is spaced in 1mm steps. The new parking position (red dot) is 7mm away from the Vgroove holder [\u2026] Date: 14.02.2024 14:23 Authors: [Name 1], [Name 2] Title: Activated Reference Phase Tracking for the Gun Content: [\u2026] > Finished chain. Based on the logbook entries, they did manage to define a new hexapod parking position today. The new parking position is 7mm away from the V-groove holder, as recorded in the entry at 18:14 by [Name 1]. What can I do for you? Figure 5: Example: \"Did they manage to define the new hexapod parking position today?\". Names are redacted. 6 \fGAIA TECHNICAL REPORT fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? Can you ask an expert whether the current value of the Gun Amplitude (Probe) is correct? > Entering new AgentExecutor chain\u2026 Thought: To answer this question, I need to find out the current value of the Gun Amplitude (Probe). I can use the ReadAction tool for this. After getting the value, I will ask an expert via Mattermost chat whether it is correct. Action: ``` { \"action\": \"ReadAction\", \"action_input\": { \"address\": \"MTest/GUN_AMPLITUDE_PROBE\" } } ``` Observation: nan Thought: It seems there was an issue with the DOOCS address provided. I will use the DOOCS Address Helper tool to ensure the correct address is used. Action: ```json { \"action\": \"DOOCS Address Helper\", \"action_input\": { \"search_query\": \"Gun Amplitude (Probe)\" } } ``` Observation: SINBAD.RF/LLRF.CONTROLLER/VS.AR.LI.RSB.G.1/AMPL.SAMPLE Thought: Now that I have the correct DOOCS address, I can use the ReadAction tool to get the current value of the Gun Amplitude (Probe). After getting the value, I will ask an expert via Mattermost chat whether it is correct. Action: ``` { \"action\": \"ReadAction\", \"action_input\": { \"address\": \"SINBAD.RF/LLRF.CONTROLLER/VS.AR.LI.RSB.G.1/AMPL.SAMPLE\" } } ``` Observation: 74.56 Thought: Now that I have the current value of the Gun Amplitude (Probe), I can ask an expert via Mattermost chat whether it is correct. Action: ```json \"action\": \"Mattermost Chat Bot\", \"action_input\": { \"chat_message\": \"@fmayet The current value of the Gun Amplitude (Probe) is 74.56. Is this value correct?\u201d } } ``` The current value of the Gun Amplitude (Probe) is 74.56. Is this value correct? I would say it is a little low, but they can proceed with the experiment. Observation: Here is a message from fmayet: I would say it is a little low, but they can proceed with the experiment. Thought: I have obtained the current value of the Gun Amplitude (Probe) and consulted an expert. The expert has confirmed that the value is a bi t low, but they can continue with the experiment. > Finished chain. The current value of the Gun Amplitude (Probe) is 74.56, and it is a bit low. However, you can proceed with the experiment. What can I do for you? Figure 6: Example: \"Can you ask an expert whether the current value of the Gun Amplitude (Probe) is correct?\". 7 \fGAIA TECHNICAL REPORT fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? Please cycle the two magnets ARDLMQZM1 and ARDLMQZM2 in parallel and post the result to the logbook afterwards. > Entering new AgentExecutor chain\u2026 To perform this task, I will first ask the DGE Helper for advice. Action: ``` { \"action\": \u201cDGE Helper\", \"action_input\": { \"query\": \"How can I cycle the two magnets ARDLMQZM1 and ARDLMQZM2 in parallel and post the result to the logbook afterwards?\" } } ``` Observation: [\u2026] Thought: I will now run the code using Python Code Runner. Action: ```json { \"action\": \"Python Code Runner\", \"action_input\": { \"code\": \"[\u2026]\" } } ``` This is the code I would like to run for you: from doocs_generic_experiment import ParallelProcedure, MagnetCycleAction, PrintToLogbookAction # Define the ParallelProcedure to cycle both magnets in parallel cycle_magnets_procedure = ParallelProcedure( [ MagnetCycleAction(magnet_name='ARDLMQZM1'), MagnetCycleAction(magnet_name='ARDLMQZM2') ] ) # Define the PrintToLogbookAction to print the result to the logbook print_to_logbook = PrintToLogbookAction(title=\"Magnet Cycling Result\", severity='INFO', author='aresoper (via doocs_generic_experiment)', logbook=\u2018areslog\u2019, message=\u201cARDLMQZM1 and ARDLMQZM2 are now cycled.\u201d) # Define a Procedure that runs both actions in sequence procedure = Procedure([cycle_magnets_procedure, print_to_logbook]) # Run the procedure procedure.run() Do you want to run this code? Figure 7: Example: \"Please cycle the two magnets ARDLMQZM1 and ARDLMQZM2 in parallel and post the result to the logbook afterwards.\". 8 \fGAIA TECHNICAL REPORT 5", + "additional_graph_info": { + "graph": [ + [ + "Frank Mayet", + "Willi Kuropka" + ] + ], + "node_feat": { + "Frank Mayet": [ + { + "url": "http://arxiv.org/abs/2405.01359v1", + "title": "GAIA: A General AI Assistant for Intelligent Accelerator Operations", + "abstract": "Large-scale machines like particle accelerators are usually run by a team of\nexperienced operators. In case of a particle accelerator, these operators\npossess suitable background knowledge on both accelerator physics and the\ntechnology comprising the machine. Due to the complexity of the machine,\nparticular subsystems of the machine are taken care of by experts, who the\noperators can turn to. In this work the reasoning and action (ReAct) prompting\nparadigm is used to couple an open-weights large language model (LLM) with a\nhigh-level machine control system framework and other tools, e.g. the\nelectronic logbook or machine design documentation. By doing so, a multi-expert\nretrieval augmented generation (RAG) system is implemented, which assists\noperators in knowledge retrieval tasks, interacts with the machine directly if\nneeded, or writes high level control system scripts. This consolidation of\nexpert knowledge and machine interaction can simplify and speed up machine\noperation tasks for both new and experienced human operators.", + "authors": "Frank Mayet", + "published": "2024-05-02", + "updated": "2024-05-02", + "primary_cat": "cs.CL", + "cats": [ + "cs.CL", + "physics.acc-ph" + ], + "main_content": "Introduction Particle accelerators are complex machines that consist of a large number of subsystems. Although many processes are automated and feedback systems are in place, experiments and machine supervision need to be performed by a group of operators. These operators usually have an accelerator physics background and mostly know how the technology works. They especially know how to setup and tune the machine parameters for certain working points and experiments using high-level graphical user interfaces, which are connected to low-level machine control software. Due to the complexity of the machine, some subsystems of the machine are taken care of by experts, who the operators can turn to. This work shows that it is possible to support the day-to-day operation of a complex machine like a particle accelerator using a large language model (LLM), an object-oriented high-level machine control system framework, as well as a number of interfaces to knowledge bases such as the electronic logbook. The system is able to assist the operators on many levels, e.g. by producing Python scripts, which when executed perform a task defined by an input prompt to the LLM. To this end, the reasoning and action prompting paradigm (ReAct) [Yao et al., 2023] is implemented. This way a multi-expert system is realized, mimicking the real world, where the complex machine is operated by many subsystem experts. arXiv:2405.01359v1 [cs.CL] 2 May 2024 \fGAIA TECHNICAL REPORT 2 Background \u2013 Accelerator Controls Modern accelerators are routinely operated using sophisticated low-level control systems, such as EPICS1, TANGO2, TINE3, or DOOCS4. These control systems allow for high frequency machine and beam diagnostics, as well as control, which is an essential requirement for highly available, brilliant beams for the users. In addition, control systems are often paired with high speed data acquisitions systems (DAQ), capable of recording pulse synchronized data at the machine repetition rate. In order to access the machine, or derived data (via middle layer servers), users can usually leverage libraries and wrappers for common programming and scripting languages such as C, C++, Java, or Python. Easy to use toolkits are sometimes provided to create graphical user interfaces (GUIs) for simple interaction with control system servers (e.g. parameter scans), or data visualization. On many machines there is the need to perform experiments, which are more complex than simple oneor twodimensional parameter scans. In this case users and operators have to either perform the tasks manually, or to write measurement scripts using e.g. Python. In this work a Python-based scripting toolkit called doocs_generic_experiment is used, which simplifies the task of writing a measurement script substantially. The toolkit follows an object-oriented approach and is based on a set of so called actions, which resemble real-world sub-tasks an operator would have to perform if the experiment would be conducted manually. These actions can be grouped into procedures, which can reach arbitrary complexity. In addition of performing a set of action in series, procedures can also run multiple actions in parallel to save time. The final experiment can then consit of either one, or many of these procedures. Due to the easy to unterstand concept of stringing together common actions and procedures, the toolkit enables rapid prototyping of complex experiments and enables fulland semi-automation of experimental campaigns, which would otherwise take too long to perform manually. In addition, the concept of encapsulating commonly performed actions adds a safety layer as the room for possible mistakes is reduced. Figure 1 shows a selection of currently available actions and procedures. Action ReadAction WriteAction RichWriteAction RichReadAction IfElseAction LogAction UserInputAction PauseAction WaitForStabilityAction ParallelReadAction WaitForChangeAction SubscriptionAction ProcessingAction AlarmConditionAction NeuralNetAction LaserSwitchAction ScreenAction PulseShotModeAction BeamRecenteringAction LaserApertureAction MagnetDegaussAction MagnetCycleAction PrintToLogbookAction PolariXOnBeamSwitchAction Procedure ParallelProcedure DOOCSManager DOOCSAddress SingleDataProcedure ScanProcedure ImageScanProcedure OutputManager MachineStateProcedure PhaseAdvanceScanProcedure FourDimTomographyProcedure FiveDimTomographyProcedure Figure 1: A selection of procedures and actions available via the doocs_generic_experiment Python module. 1https://epics.anl.gov, last access 2024-04-26 2https://www.tango-controls.org, last access 2024-04-26 3https://tine.desy.de, last access 2024-04-26 4https://doocs.desy.de, last access 2024-04-26 2 \fGAIA TECHNICAL REPORT 3 Multi-Expert System \u2013 GAIA In order to realize the operations assistant, the open-weights LLM Mixtral 8x7B Instruct v0.1 (8 bit quantization) [Jiang et al., 2024] is used as the main model. Mixtral 8x7B supports a context size of 32k tokens. This is ideal for reasoning and chain of thought (CoT) prompting [Wei et al., 2022, 2023, Yao et al., 2023]. The model runs locally on a single Nvidia A100 80GB GPU in the DESY Maxwell cluster and is served by Ollama5 (model tag: mixtral:8x7b-instruct-v0.1-q8_0). Note that the Maxwell node does not need to directly interface with the accelerator control system. All interaction and knowledge retrieval is performed by a client application, which runs on a computer, which is part of the control system network. This client can then interface with control system servers, file servers, the Mattermost messaging system, etc., if needed. The client is called General AI Assistant (GAIA). One of the main concepts of the ReAct prompting scheme is tool use. As the agent engages in its inner monologue, or chain of thought, it will eventually reach a point where it needs to either perform an action, or retrieve information. This is analogous to an operator deciding to either use control system tools to control or diagnose certain parts of the machine, or to turn to an expert to retrieve information. Technically, the agent, which is implemented using LangChain6, interrupts the LLM output stream and injects the result of a particular tool use. The agent might, for example, come to the conclusion that it needs to retrieve the current value of a particular machine parameter. In this case, within its chain of thought, it may suggest using doocs_generic_experiment based tools to perform this particular task. Another example would be the retrieval of information from the electronic logbook. One advantage of the concept of tool use is that it helps to circumvent the LLM token limit. In many cases knowledge retrieval may involve classical retrieval augmented generation (RAG) [Lewis et al., 2021] implementations, which use their own disjunct LLM context. This way, only the result of the knowledge retrieval process is injected into the agents context window. In addition, this allows the use of fine-tuned RAG systems potentially based on other LLMs. If the task is to devise a certain experimental procedure at a particle accelerator, at least two tools/experts may be needed. The first expert may provide knowledge about the layout of the beam line, as well as how to utilize the specific elements for a given task. The second expert may on the other hand be proficient in producing doocs_generic_experiment code and how to interface with the accelerator control system. The agent is able to combine the output of the two tools, yielding a suitable Python program from a prompt, such as \"I want to operate the accelerator at maximum energy gain\". Figure 2 shows a selection of tools used in the current GAIA implementation. In the following section a number of example prompts to GAIA are shown. Note that the chain of thought, which is shown in the examples, is usually not visible to the user. \u21e8 Look up info about the accelerator layout \u21e8 Uses an already existing lattice file parser AcceleratorLatticeTool \u21e8 Helps looking up DOOCS addresses \u21e8 Uses simple sequence matching DOOCSAddressHelperTool \u21e8 Summarizes .pptx files from weekly meetings \u21e8 Uses basic prompting and its own context OperationsMeetingSummarizer \u21e8 Gives access to the electronic logbook \u21e8 Uses an existing CLI interface to the logbook LogbookTool \u21e8 Let\u2019s the agent contact experts \u21e8 Uses Mattermost API MattermostChatBotTool \u21e8 Runs Python code \u21e8 \u2026for example generated by DGEHelperTool PythonCodeRunnerTool \u21e8 ReadActionTool, LogbookActionTool, \u2026 \u21e8 MachineStateProcedureTool, \u2026 Wrappers around Actions and Procedures \u21e8 Explains doocs_generic_experiment \u21e8 Can also generate code DGEHelperTool \u21e8 \u2026in order to get accurate calculations CalculatorTool Figure 2: A selection of tools to be used by GAIA. 5http://www.ollama.com, last access 2024-04-26 6http://www.langchain.com, last access 2024-04-26 3 \fGAIA TECHNICAL REPORT 4 Examples In this section example prompts to GAIA are presented. The results are shown in Figs 3 through 7. Note that some parts of the output are truncated, as indicated by \u2019[...]\u2019. The chain of thought, shown in the examples, is usually not visible to the user. Also, names are redacted if needed. The example cases show the versatility of the system, which includes access to meeting notes (Fig. 3), guidance on how to use doocs_generic_experiment (Fig. 4), information retrieval from the electronic logbook (Fig. 5), machine data access using doocs_generic_experiment and subsequently contacting human experts via Mattermost chat (Fig. 6), and running complex tasks using an ad hoc generated doocs_generic_experiment script (Fig. 7). fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? Can you summarize the last operations meeting? > Entering new AgentExecutor chain\u2026 Thought: To answer this question, I need to use the \"Operation Meeting Summarizer\" tool and provide the date of the meeting as input. I will ask the user for the date if it has not been provided. Action: ``` { \"action\": \"User Input Tool\", \"action_input\": { \"question\": \"What is the date of the operation meeting you want me to summarize?\" } } ``` What is the date of the operation meeting you want me to summarize? 29.01.2024 Observation: 29.01.2024 Thought: Based on the user input, I can now use the \"Operation Meeting Summarizer\" tool to generate a summary of the operations meeting that took place on the given date. Action: ```json { \"action\": \"Operation Meeting Summarizer\", \"action_input\": { \"date\": \"2024-01-29\" } } ``` Observation: The ARES Operation Meeting summary from January 29, 2024 covers [\u2026] > Finished chain. The ARES Operation Meeting summary from January 29, 2024 covers the week 4 achievements, difficulties, and notes. During this week, the team re-established the velocity bunching working point using fewer quads, optimized transmission through the DLA, and worked on various scans and tuning. They also faced a TWS1 modulator fault due to low solenoid water flow rate, which was fixed. On the ARES beamline, the EA.L2 camera had ROI and background subtraction applied, showing likely Cherenkov/Smith-Purcell effects but no coherence yet. PolariX development included switching on the OVC, testing higher water temperatures for BOC detuning, conditioning both vertical and horizontal streaking, and developing measurement and analysis scripts. PolariX measurements consisted of streaking along various angles covering the full range of the phase shifter and emittance measurement using DLQZM1 and the D1 screen. For week 5, [Name 1] will be on shift with [Name 2] on Monday, followed by [Name 1] with Frank on Tuesday, [Name 1] with [Name 3] on Wednesday, [Name 4] on Thursday for AutoAcc beamtime, and [Name 5] on Friday for UKE beamtime preparation. Additionally, there are plans for connecting the kicker magnet, installing in-air stages, laser work, DLA activities, and more during this week. What can I do for you? Figure 3: Example: \"Can you summarize the last operations meeting?\". Names are redacted. 4 \fGAIA TECHNICAL REPORT fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? I want to write values to multiple devices in parallel using doocs_generic_experiment. How do I do this? > Entering new AgentExecutor chain\u2026 Thought: To answer this question, I need to understand how to write values to multiple devices in parallel using the doocs_generic_experiment Python module. I can use the DGE Helper tool for this. Action: ```json { \"action\": \"DGE Helper\", \"action_input\": { \"query\": \"How to write values to multiple devices in parallel using doocs_generic_experiment?\" } } ``` Observation: To write values to multiple devices in parallel using [\u2026] To write values to multiple devices in parallel using `doocs_generic_experiment`, you can use a `ParallelProcedure` with a list of `WriteAction`. Here is an example: ```python from doocs_generic_experiment import DOOCSAddress, WriteAction, ParallelProcedure # Define the addresses and values to write addresses = [DOOCSAddress('dev1', writable=True), DOOCSAddress('dev2', writable=True)] values = [10, 20] # Create a list of WriteAction instances write_actions = [WriteAction(address, value) for address, value in zip(addresses, values)] # Create a ParallelProcedure instance and add the write actions parallel_procedure = ParallelProcedure(actions=write_actions) # Run the procedure parallel_procedure.run() ``` In this example, we first define a list of `DOOCSAddress` instances with the `writable` flag set to `True`. We then create a list of `WriteAction` instances using a list comprehension and the `zip` function to pair the addresses and values. Finally, we create a `ParallelProcedure` instance and add the write actions to it. When we run the procedure, the write actions will be executed in parallel. What can I do for you? Figure 4: Example: \"I want to write values to multiple devices in parallel using doocs_generic_experiment. How do I do this?\". 5 \fGAIA TECHNICAL REPORT fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? Did they manage to define the new hexapod parking position today? > Entering new AgentExecutor chain\u2026 To answer this question, I need to check the logbook entries for today related to the hexapod parking position. I will use the Logbook tool with the 'n_days' parameter set to 0 to get the entries from today. Action: ``` { \"action\": \"Logbook\", \"action_input\": { \"n_days\": 0, \"n_entries\": null } } ``` Observation: Logbook name: SINBAD-ARESelog e-Logbook, Date: Wednesday 14. February 2024 Logbook entries: [\u2026] Date: 14.02.2024 18:14 Authors: [Name 1] Title: New Hexapod Parking Position Content: The grid is spaced in 1mm steps. The new parking position (red dot) is 7mm away from the Vgroove holder [\u2026] Date: 14.02.2024 14:23 Authors: [Name 1], [Name 2] Title: Activated Reference Phase Tracking for the Gun Content: [\u2026] > Finished chain. Based on the logbook entries, they did manage to define a new hexapod parking position today. The new parking position is 7mm away from the V-groove holder, as recorded in the entry at 18:14 by [Name 1]. What can I do for you? Figure 5: Example: \"Did they manage to define the new hexapod parking position today?\". Names are redacted. 6 \fGAIA TECHNICAL REPORT fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? Can you ask an expert whether the current value of the Gun Amplitude (Probe) is correct? > Entering new AgentExecutor chain\u2026 Thought: To answer this question, I need to find out the current value of the Gun Amplitude (Probe). I can use the ReadAction tool for this. After getting the value, I will ask an expert via Mattermost chat whether it is correct. Action: ``` { \"action\": \"ReadAction\", \"action_input\": { \"address\": \"MTest/GUN_AMPLITUDE_PROBE\" } } ``` Observation: nan Thought: It seems there was an issue with the DOOCS address provided. I will use the DOOCS Address Helper tool to ensure the correct address is used. Action: ```json { \"action\": \"DOOCS Address Helper\", \"action_input\": { \"search_query\": \"Gun Amplitude (Probe)\" } } ``` Observation: SINBAD.RF/LLRF.CONTROLLER/VS.AR.LI.RSB.G.1/AMPL.SAMPLE Thought: Now that I have the correct DOOCS address, I can use the ReadAction tool to get the current value of the Gun Amplitude (Probe). After getting the value, I will ask an expert via Mattermost chat whether it is correct. Action: ``` { \"action\": \"ReadAction\", \"action_input\": { \"address\": \"SINBAD.RF/LLRF.CONTROLLER/VS.AR.LI.RSB.G.1/AMPL.SAMPLE\" } } ``` Observation: 74.56 Thought: Now that I have the current value of the Gun Amplitude (Probe), I can ask an expert via Mattermost chat whether it is correct. Action: ```json \"action\": \"Mattermost Chat Bot\", \"action_input\": { \"chat_message\": \"@fmayet The current value of the Gun Amplitude (Probe) is 74.56. Is this value correct?\u201d } } ``` The current value of the Gun Amplitude (Probe) is 74.56. Is this value correct? I would say it is a little low, but they can proceed with the experiment. Observation: Here is a message from fmayet: I would say it is a little low, but they can proceed with the experiment. Thought: I have obtained the current value of the Gun Amplitude (Probe) and consulted an expert. The expert has confirmed that the value is a bi t low, but they can continue with the experiment. > Finished chain. The current value of the Gun Amplitude (Probe) is 74.56, and it is a bit low. However, you can proceed with the experiment. What can I do for you? Figure 6: Example: \"Can you ask an expert whether the current value of the Gun Amplitude (Probe) is correct?\". 7 \fGAIA TECHNICAL REPORT fmayet@desymac42 ~ % ./gaia \u2014-verbose True Welcome to GAIA (served on max-wng055) What can I do for you? Please cycle the two magnets ARDLMQZM1 and ARDLMQZM2 in parallel and post the result to the logbook afterwards. > Entering new AgentExecutor chain\u2026 To perform this task, I will first ask the DGE Helper for advice. Action: ``` { \"action\": \u201cDGE Helper\", \"action_input\": { \"query\": \"How can I cycle the two magnets ARDLMQZM1 and ARDLMQZM2 in parallel and post the result to the logbook afterwards?\" } } ``` Observation: [\u2026] Thought: I will now run the code using Python Code Runner. Action: ```json { \"action\": \"Python Code Runner\", \"action_input\": { \"code\": \"[\u2026]\" } } ``` This is the code I would like to run for you: from doocs_generic_experiment import ParallelProcedure, MagnetCycleAction, PrintToLogbookAction # Define the ParallelProcedure to cycle both magnets in parallel cycle_magnets_procedure = ParallelProcedure( [ MagnetCycleAction(magnet_name='ARDLMQZM1'), MagnetCycleAction(magnet_name='ARDLMQZM2') ] ) # Define the PrintToLogbookAction to print the result to the logbook print_to_logbook = PrintToLogbookAction(title=\"Magnet Cycling Result\", severity='INFO', author='aresoper (via doocs_generic_experiment)', logbook=\u2018areslog\u2019, message=\u201cARDLMQZM1 and ARDLMQZM2 are now cycled.\u201d) # Define a Procedure that runs both actions in sequence procedure = Procedure([cycle_magnets_procedure, print_to_logbook]) # Run the procedure procedure.run() Do you want to run this code? Figure 7: Example: \"Please cycle the two magnets ARDLMQZM1 and ARDLMQZM2 in parallel and post the result to the logbook afterwards.\". 8 \fGAIA TECHNICAL REPORT 5" + }, + { + "url": "http://arxiv.org/abs/1801.10373v1", + "title": "Using short drive laser pulses to achieve net focusing forces in tailored dual grating dielectric structures", + "abstract": "Laser-driven grating type DLA (Dielectric Laser Accelerator) structures have\nbeen shown to produce accelerating gradients on the order of GeV/m. In simple\n$\\beta$-matched grating structures due to the nature of the laser induced\nsteady-state in-channel fields the per period forces on the particles are\nmostly in longitudinal direction. Even though strong transverse magnetic and\nelectric fields are present, the net focusing effect over one period at maximum\nenergy gain is negligible in the case of relativistic electrons. Stable\nacceleration of realistic electron beams in a DLA channel however requires the\npresence of significant net transverse forces. In this work we simulate and\nstudy the effect of using the transient temporal shape of short Gaussian drive\nlaser pulses in order to achieve suitable field configurations for potentially\nstable acceleration of relativistic electrons in the horizontal plane. In order\nto achieve this, both the laser pulse and the grating geometry are optimized.\nSimulations conducted with the Particle-In-Cell code VSim 7.2 are shown for\nboth the transient and steady state/long pulse case. Finally we investigate how\nthe drive laser phase dependence of the focusing forces could affect a\npotential DLA-based focusing lattice.", + "authors": "Frank Mayet, Ralph Assmann, Ulrich Dorda, Willi Kuropka", + "published": "2018-01-31", + "updated": "2018-01-31", + "primary_cat": "physics.acc-ph", + "cats": [ + "physics.acc-ph" + ], + "main_content": "Introduction The concept of dielectric laser accelerators (DLA) has gained increasing attention in accelerator research, because of the high achievable acceleration gradients (\u223cGeV/m) [1]. This is due to the high damage threshold of dielectrics at optical frequencies. One of the structure types being studied is the symetrically driven dual grating. A schematic of this type of structure is shown in Fig. 1. If the structure periodicity \u03bbS and the drive laser wavelength \u03bbL are adjusted according to the normalized velocity \u03b2p of the injected electrons, phase-synchronous acceleration can be achieved. In this case the structure is then called \u03b2matched. In simple \u03b2-matched grating structures due to the nature of the laser induced in-channel \ufb01elds the steadystate per period longitudinal force on the particle is \u03c0/2 out of phase with the transverse force (see Sec. 2). Therefore at maximum energy gain phase no transverse forces are exerted on the particle. Stable acceleration and transport of realistic electron beams in a DLA channel however requires the presence of signi\ufb01cant net transverse forces. In this work we simulate and study how a) the magnitude of the transverse force can be enhanced and b) how the phase relation between the longitudinal and transverse force can be altered by tailoring the structure geometry and hence Email address: frank.mayet@desy.de (F. Mayet) x y Laser, lin.-polarized-in-x e2 SiO2 \u03bbS \u03bbL Figure 1: Schematic of a dual grating DLA illuminated from both sides with a linearly polarized laser \ufb01eld with wavelength \u03bbL. \u03bbS is the period length, which is connected to the laser wavelength by the synchronicity condition \u03bbS = \u03b2m\u03bbL, where \u03b2m is the matched normalized particle velocity. The electrons travel along x with normalized velocity \u03b2p. leaving the ideal grating picture as shown in Fig. 1. In the \ufb01nal section (Sec. 5) we investigate how the drive laser phase dependence of the resulting focusing forces could a\ufb00ect a potential future DLA-based focusing lattice. 2. Analytical Description of the Fields For the following calculation an in x-direction linearly polarized plane wave, which is traveling along the yPreprint submitted to Nuclear Instruments and Methods in Physics Research Section A March 23, 2022 arXiv:1801.10373v1 [physics.acc-ph] 31 Jan 2018 \fdirection with a wavelength of \u03bb0 is assumed (cf. Fig. 1). It is incident on a single grating perpendicular to the grating structure, which implies a structure being periodic in x-direction. The problem is assumed to be pseudo-2dimensional in the sense that in z-direction the structure is in\ufb01nite. Using Maxwell\u2019s Equations we see that our plane wave has a non-vanishing magnetic \ufb01eld only in z-direction. The magnetic \ufb01eld after passage of the grating can be described as a composition of an in\ufb01nite number of spatial harmonics, or di\ufb00raction modes (cf. Floquet Theorem \u2192Fourier series) [2]: Bz(x, y, t) = \u221e X n=\u2212\u221e B(n) z,0 \u00b7 ei(nkxx+kyy\u2212\u03c9t+\u03c60), where kx = 2\u03c0/\u03bbx is the wave vector component w.r.t the grating period and B(n) z,0 is the n-th order complex Fourier weight. The term \u03c60 is an arbitrary phase o\ufb00set. Here it describes the particle to laser phase relation. Inserting Bz into the wave equation for vacuum it can be seen that k2 y = k2 0 \u2212n2k2 x. Hence Bz(x, y, t) = \u221e X n=1 B(n) z,0 \u00b7 e i \u0010 y\u221a k2 0\u2212n2k2 x+nkxx\u2212\u03c9t+\u03c60 \u0011 . Using \u2207\u00d7 \u20d7 B = \u2212i\u00b7 k0 c \u20d7 E the x and y components of the electric \ufb01eld can be calculated from Bz. In order to e\ufb03ciently accelerate a moving particle it has to be phase synchronous with the parallel component of the electromagnetic \ufb01eld. From this it follows that \u03c9 nkx = \u03b2mc \u21d4kx = k0 n\u03b2m \u21d4\u03b2m = \u03bbx n\u03bb0 , (1) where k0 is the laser wave number and \u03b2mc is the matched particle velocity. Eq. (1) is the synchronicity condition for grating accelerators for the n-th harmonic. In the following calculations we use n = 1 as the synchronous order and hence kx = k0/\u03b2m. Inserting kx into the expressions for the \ufb01eld components and taking only the real part yields \u211c(B)(x, y, t) = \u221e X n=\u2212\u221e |B(n) z,0 | \u00b7 e\u2212\u03b4(n) m y \u00b7 \uf8eb \uf8ec \uf8ed 0 0 cos \u0010 n k0 \u03b2m x \u2212\u03c9t + \u02dc \u03c6(n) 0 \u0011 \uf8f6 \uf8f7 \uf8f8, \u211c(E)(x, y, t) = \u221e X n=\u2212\u221e |E(n) x,0| \u00b7 e\u2212\u03b4(n) m y \u00b7 \uf8eb \uf8ec \uf8ec \uf8ed sin \u0010 n k0 \u03b2m x \u2212\u03c9t + \u02dc \u03c6(n) 0 \u0011 q n2 n2\u2212\u03b22 m \u00b7 cos \u0010 n k0 \u03b2m x \u2212\u03c9t + \u02dc \u03c6(n) 0 \u0011 0 \uf8f6 \uf8f7 \uf8f7 \uf8f8, (2) where \u03b4(n) m = k0 q n2 \u03b22 m \u22121, \u02dc \u03c6(n) 0 = \u03c60 + \u03c6(n) and |E(n) x,0| = c q n2 \u03b22 m \u22121 \u00b7 |B(n) z,0 |. |B(n) z,0 | and \u03c6(n) are the amplitudes and phases of the complex weights of the spatial harmonics respectively. It can be seen that the \ufb01eld falls o\ufb00exponentially in y. The particles are accelerated in evanescent \ufb01eld components, which is required by the Lawson-Woodward Theorem. From Eq. (2) it can already be seen that in the case of an ideal grating DLA the longitudinal and transverse \ufb01elds are out of phase by \u03c0/2. In order to describe a dual grating DLA two grating \ufb01elds need to be superimposed, while taking both the channel width Lgap and the opposite travel direction of the second drive laser into account. 3. Per-Period Force on the Particle In the previous section the steady state in-channel \ufb01elds of a single and dual grating DLA were described. Using this \ufb01eld description it is now possible to estimate the perperiod e\ufb00ect on a particle traversing the channel along the grating grooves with longitudinal velocity \u03b2pc. For now we consider a zero-emittance single particle. It is also assumed for simplicity that \u03b2p = constant during the traversal of a single grating period. First it is necessary to map the time-dependence of the \ufb01eld to the particle position along the channel. Since x = \u03b2pct and \u03c9 = ck0, we can substitute \u03c9t \u21d2k0x/\u03b2p. It is now helpful to introduce the particle to grating spatial phase \u03a8(n) m (x), which is de\ufb01ned as \u03a8(n) m (x) = k0 \u0012 n \u03b2m \u22121 \u03b2p \u0013 x. (3) In the \u03b2-matched case it reduces to \u03a8(n)(x) = k0 \u03b2m (n \u22121)x. Note that Eq. (3) is zero for n = 1 in the \u03b2-matched case, which eliminates the spatial dependence of the force on the electron during traversal of the period, which is just a re-statement of the phase-synchronicity of the \ufb01rst order. In order to simplify the equations it is furthermore helpful to de\ufb01ne \u2206(n) m,\u00b1(y), the transverse decay factor, which is de\ufb01ned for the dual grating case as \u2206(n) m,\u00b1(y) = e\u2212\u03b4(n) m y \u00b1 e\u2212\u03b4(n) m (Lgap\u2212y) (4) and for the single grating case as \u2206(n) m (y) = e\u2212\u03b4(n) m y. The force on a moving particle caused by the presence of an electromagnetic \ufb01eld is given by the Lorentz Force FL = q(E+v\u00d7B), where q is the particle charge and v its 2 \fvelocity. Therefore the non-zero force components are in our case given by Fx = qEx and Fy = q(Ey \u2212vxBz), where vx = \u03b2pc. Inserting the expressions for Ex and Ey, as well as the newly introduced de\ufb01nitions \u03a8(n) m (x), \u2206(n) m,\u00b1(y) and \u02dc \u03c6(n) 0 yields for n \u0338= 0 F (n) x (x, y) = qc s n2 \u03b22 m \u22121 \u00b7 B(n) z0 \u00b7 sin(\u03a8(n) m x + \u02dc \u03c6(n) 0 ) \u00b7 \u2206(n) m,+(y), F (n) y (x, y) = qc \u0014 n \u03b2m \u2212\u03b2p \u0015 \u00b7 B(n) z0 \u00b7 cos(\u03a8(n) m x + \u02dc \u03c6(n) 0 ) \u00b7 \u2206(n) m,\u2212(y). (5) The average per-period (or net-) force can now be calculated as \u27e8Fx,y\u27e9(n)(y) = 1 \u03bbx Z \u03bbx 0 F (n) x,y (x, y)dx where it is assumed that the transverse motion during one period is negligible and hence ds \u2192dx. It can be shown that in the \u03b2-matched case \u27e8Fx,y\u27e9(n)(y) = 0, \u2200n \u0338= 1. This is not generally true anymore if \u03b2m \u0338= \u03b2p. 3.1. Signi\ufb01cant Per-Period Transverse Force As described above, in the case of an ideal dual grating DLA Eq. (5) can be used to estimate the per-period force on a particle traveling along the DLA channel. Taking a closer look on F (n) y (x, y) it is possible to identify di\ufb00erent ways to enhance the transverse force. Considering the term \u0014 n \u03b2m \u2212\u03b2p \u0015 two options come to mind: \u2022 Signi\ufb01cant mismatch between \u03b2m and \u03b2p \u2022 Virtual mismatch between \u03b2m and \u03b2p by injecting the electrons with an angle in the x \u2212z plane [3] At the same time if the grating is mismatched as has been already stated above higher orders do not cancel out anymore. It has to be noted however that the enhancement of the per-period transverse force via mismatch is not trivial since the spatial phase also changes with the level of mismatch (see Eq. 3). In addition to that, due to the increasingly fast decay of the higher orders (see Eq. 4) the accelerating \ufb01eld is much less homogeneous across the channel, which results in increased correlated energy spread. Then there is a third option, which is based on letting the B(n) z,0 depend on t, or subsequently x. This means B(n) z,0 \u2192B(n) z,0 (x), or in other words: The driving \ufb01eld envelope is not constant, which needs to be taken into account in the integration of the average per-period force and can lead to an enhancement as shown below. 3.2. Using Time-dependent Fourier Weights The following calculations are based on four assumptions: \u2022 The slope of the B(n) z,0 (x) is linear over one period \u2022 There is only negligible transverse motion of the electron over one period \u2022 The electron to laser phase is constant over one period \u2022 The structure is and stays \u03b2-matched It is reasonable to assume that the slope of the \ufb01eld during one single grating period is almost linear and hence B(n) z,0 (x) = B(n) z,0,0 + dxB(n) z,0 \u00b7 x, where dx \u2192d/dx. With this we get for n \u0338= 0 \u27e8Fy\u27e9(n)(y) \u221d Z \u03bbx 0 (B(n) z,0,0 + dxB(n) z,0 \u00b7 x) \u00b7 cos(\u03a8(n)x + \u02dc \u03c6(n) 0 )dx. (6) In case of the synchronous mode n = 1 this integral yields: \u27e8Fy\u27e9(1)(y) \u221d B(1) z,0,0 + dxB(1) z,0 2 \u00b7 \u03bbx ! \u00b7 cos(\u02dc \u03c6(1) 0 ). (7) This means that the \ufb01rst order transverse force depends on both the amplitude and its slope. If the slope is suf\ufb01ciently steep (since it is multiplied with the drive laser wavelength), the transverse force can be enhanced by this term. It is also interesting to note that if the slope term dominates the sign of the slope will cause a \u03c0 phase \ufb02ip. In Fig. 2 the envelope of Eq. 7 is shown for di\ufb00erent time Amplitude (a.u.) Phase (a.u.) a) b) c) d) Figure 2: Illustration of the resulting transverse per-period force envelope according to Eq. 7 using the time dependence as described by Eq. 8. The pulse length is reduced from a) to d). The amplitude scale is kept constant and in a.u., while the phase scale is always given by the interval [\u22125\u03c3, 5\u03c3]. dependent B(1) z,0(t). The time dependence was chosen to be a Gaussian as de\ufb01ned by g(x) = 1 \u03c3 \u221a 2\u03c0 e\u22121 2( x\u2212\u00b5 \u03c3 ) 2 , (8) 3 \fwhere \u00b5 is the center and \u03c3 is the rms width as usual. It can be seen that for long pulses the slope does not play a role yet and the resulting pulse shape is just the initial Gaussian. If however the pulse gets short enough and the slope term large enough, the pulse shape gets modi\ufb01ed substantially as two peaks emerge. Compared to the initial pulse shape the peak amplitude is enhanced. 4. Simulations In order to verify the force enhancement e\ufb00ect shown in the previous section numerical FDTD (Finite-Di\ufb00erenceTime-Domain) simulations were carried out using VSim 7.2 [4]. Simulations were performed for both the steady state case and a short pulse case using Eq. 8 as the envelope, where the rms drive laser pulse length was chosen to be 50 fs and the peak amplitude 0.5 GV/m. The two drive lasers were assumed to be phase-locked and incident on a \u03b2\u2212matched dual grating. \u03b2m was chosen to be close to 1 (\u219250 MeV). As the \ufb01gure of merit the equivalent magnetic focusing gradient as described in [5] was used. It is de\ufb01ned by G = \u2202\u22a5\u27e8F\u22a5\u27e9\u03bb qec , (9) where \u2202\u22a5\u27e8F\u22a5\u27e9\u03bb is the derivative of the per-period average transverse force w.r.t. the transverse coordinate, qe the electron charge and c the speed of light. The unit of G is [T/m] as expected. The simulation was carried out according to the scheme shown in Fig. 3. Fig. 4 shows the results of the simulation and subsequent data processing. The solid line shows G and the scatter plot the accelerating part of the longitudinal force, where the size of the data point symbolizes its magnitude. The decelerating part is omitted for readability. In comparison to the steady state both the two emerging peaks (as already seen for short pulses in Fig. 2), as well as the enhancement of G by a factor of \u223c2.5 at the maximum can be seen. The focusing gradient indeed seems to depend on the slope of the spatial harmonic weights as predicted by the simple calculations shown in the previous sections. It can also be seen that the phase relation between acceleration and focusing \u03a6(t) changes along the pulse. Calculate(the(transient( field(for(one(cell/period Calculate(the(per3period(average(force( on(a(single(beta3matched(particle Calculate(the(equivalent(magnetic( focusing(gradient Repeat(this(for(all(phases(along(the( Gaussian(drive(pulse Figure 3: Simulation scheme for the numerical \ufb01eld simulations using VSim 7.2. 4.1. Acceleration to Focusing Phase In the previous section the possible enhancement of G using short drive pulses was shown. Even though \u03a6(t) \u0338= const. along the pulse it is never \ufb02at 0. If this was the case, the beam would be focused and accelerated at the same time on-crest. \u03bbs dn dc do di Figure 5: The new structure design. Only one cell is shown. In order to achieve this, we investigated a modi\ufb01ed grating structure as shown in Fig. 5. Since this structure \u2013 due to its shape \u2013 adds a certain amount of resonance to the system the analytical description as shown above does not apply completely anymore. Hence we also expect \u03a6(t) to evolve di\ufb00erently along the pulse. Fig. 6 shows G in a section of the pulse around its peak for three di\ufb00erent values of the geometry shape (dn, dc). It can be seen that \u03a6(t) can indeed be altered to a degree that \u03a6(t) \u22480 over several periods of the pulse. Interestingly in this cona) b) c) Normalized Equivalent Magnetic Gradient (a.u.) Figure 6: Normalized equivalent magnetic focusing gradient vs. time. The scatter plot shows the accelerating part of the longitudinal force, where the size of the data points symbolizes its magnitude. From a) to c) both dn and dc are decreased slighty. 4 \fEquiv. Mag. Gradient Acc. Long. Force Equiv. Mag. Gradient Acc. Long. Force Figure 4: Equivalent magnetic focusing gradient G vs. time, calculated from VSim 7.2 \ufb01eld data (solid line). The scatter plot shows the accelerating part of the longitudinal force, visualizing the change of the phase between acceleration and focusing along the pulse. The size of the data points symbolizes the magnitude of the force. Left: 50 fs rms Gaussian drive pulse. Right: Steady state case. \ufb01guration do = 2\u03bbL, di = \u03bbL. It has to be noted that the peak amplitude of G is also altered. Fig. 7 shows the maximum achieved G, normalized to the steady state result, for di\ufb00erent rms drive laser pulse lengths, as well as a \ufb01t to Eq. 9, using Eq. 7 for F\u22a5and a free scaling factor for \u03c3 in Eq. 8. It can be seen that with decreasing pulse length the maximum G is enhanced as discussed in the last section. It can also be seen that the onset of the enhancement e\ufb00ect is in\ufb02uenced by the structure geometry as well. \u25cf \u25cf \u25cf \u25cf \u25cf \u25cf \u25a0 \u25a0 \u25a0 \u25a0 \u25a0 \u25a0 0 100 200 300 400 500 1 2 3 4 5 6 Laser Pulse Length (fs, rms) Normalized Amplitude (a.u.) dn = 0.4 (VSim 7.2) dn = 0.4 (Fit) dn = 0.1 (VSim 7.2) dn = 0.1 (Fit) Figure 7: Normalized maximum achieved G for di\ufb00erent rms drive laser pulse lengths simulated with VSim 7.2, as well as a \ufb01t to Eq. 9. Two exemplary geometries de\ufb01ned by dn are shown. 5. DLA Transport Line If in the future a fully integrated DLA-based accelerator should be able to reach high energies, a need for beam transportation along the miniaturized beamline is implied. In conventional accelerators transport lattices often comprise multiple so called FODO cells, which combine a focusing and a defocusing quadrupole separated by drift sections. This is due to the fact that quadrupoles can only focus in one plane. In the respective other plane the beam is defocused. By alternating the focusing plane the beam can be kept stable. Since a simple grating type DLA only acts on one transverse plane, it will also be necessary to build a kind of FODO lattice out of DLAs, where every second device is rotated by 90 deg. A similar setup has already been studied by Kuropka et al. [6]. Here we focus on the fact that due to the short period length \u03bbp the equivalent quadrupole focusing strength k strongly depends on the longitudinal position of a particle within the channel (or laser-to-electron phase \u03c60). It is worth noting that over a phase range of \u03c0/2 the equivalent k can vary many orders of magnitude, even going down to 0. For a \ufb01nite length beam this phase dependence has a strong e\ufb00ect on the betatron phase advance \u03a8x,y of the individual slices along the beam. 5.1. Phase dependent Transport Matrix The goal of this section is to write down a transfer matrix for the particle phase space coordinate (x, x\u2032) in analogy to a quadrupole transfer matrix, with the inclusion of a phase dependent k. The well known quadrupole transfer matrix is given by MQF = cos(\u2126) 1 \u221a k sin(\u2126) \u2212 \u221a k sin(\u2126) cos(\u2126) ! , MQD = cosh(\u2126) 1 \u221a |k| sinh(\u2126) p |k| sinh(\u2126) cosh(\u2126) ! , (10) where \u2126= p |k|s and s is the quadrupole length. If k > 0 the quadrupole is focusing (MQF), if k < 0 it is defocusing (MQD). Otherwise it is just a drift section. The k value is usually calculated via k = e p \u00b7 dBz dy , where e is the electron charge and p = p E2/c2 \u2212m2 0c2 the total momentum of the particle. In order to incorporate 5 \fthe phase dependence inside the DLA, we re-de\ufb01ne it in accordance with [7] as k(\u03c60) = 2.998 \u00b7 G \u03b2pE[GeV] \u00b7 cos(\u03c60), (11) where G is the equivalent magnetic gradient as de\ufb01ned by Eq. 9. It is now possible to construct the FODO lattice by matrix multiplication of focusing, defocusing and drift matrices respectively. 5.2. Simulation We simulate the transport of an electron bunch through a long DLA-based FODO lattice using the aforementioned transfer matrices. Here only the horizontal plane is taken into account. The parameters of the lattice are summarized in Tab. 1 and satisfy the usual stability criterion f > lcell/4 for FODO cells of length lcell and focal length f = 1/ks. The result of the transport of a uniform electron Table 1: Parameters of the DLA-based FODO Lattice. Parameter Value NFODO 1000 \u03b2m 0.9999 (\u219250 MeV) \u03bbS \u03b2m\u00b7 2 \u00b5m N\u03bbS per F,D 10 N\u03bbS per O 100 G 2.0 MT/m beam with 1 fs length through 1000 FODO cells (\u223c40 cm) is shown in Fig. 8. It can be seen that the phase-dependent phase advance indeed has a subtantial e\ufb00ect on the phase space. Note that some parts of the bunch have crossed the channel boundary (dashed line). The e\ufb00ect of this is not taken into account in this study. Figure 8: The beam after 1000 FODO cells. The scatter plot shows the macro particles and the solid line the betatron phase advance along the beam. 6." + }, + { + "url": "http://arxiv.org/abs/1801.07503v1", + "title": "Simulations and plans for possible DLA experiments at SINBAD", + "abstract": "In this work we present the outlines of possible experiments for dielectric\nlaser acceleration (DLA) of ultra-short relativistic electron bunches produced\nby the ARES linac, currently under construction at the SINBAD facility (DESY\nHamburg). The experiments are to be performed as part of the Accelerator on a\nChip International Program (ACHIP), funded by the Gordon and Betty Moore\nFoundation. At SINBAD we plan to test the acceleration of already\npre-accelerated relativistic electron bunches in laser-illuminated dielectric\ngrating structures. We present outlines of both the acceleration of ultra-short\nsingle bunches, as well as the option to accelerate phase-synchronous sub-fs\nmicrobunch trains. Here the electron bunch is conditioned prior to the\ninjection by interaction with an external laser field in an undulator. This\ngenerates a sinusoidal energy modulation that is transformed into periodic\nmicrobunches in a subsequent chicane. The phase synchronization is achieved by\ndriving both the modulation process and the DLA with the same laser pulse. In\naddition to the conceptual layouts and plans of the experiments we present\nstart-to-end simulation results for different ARES working points.", + "authors": "Frank Mayet, Ralph Assmann, Joern Boedewadt, Reinhard Brinkmann, Ulrich Dorda, Willi Kuropka, Christoph Lechner, Barbara Marchetti, Jun Zhu", + "published": "2018-01-23", + "updated": "2018-01-23", + "primary_cat": "physics.acc-ph", + "cats": [ + "physics.acc-ph" + ], + "main_content": "Introduction The Accelerator on a Chip International Program (ACHIP) funded by the Gordon and Betty Moore Foundation aims to demonstrate a working prototype of a particle accelerator on a chip until 2021. Being part of the ACHIP collaboration DESY will conduct related test experiments at its SINBAD facility [1]. Here we present plans for the \ufb01rst DLA experiments at SINBAD using electrons produced by the ARES linac [2, 3]. In addition to the conceptual layout of the experiment we present possible linac working points and an estimation of the expected results using a \u03b2-matched dual grating type DLA structure [4] illuminated by a 1 or 2 micron laser. At the time of this publication three di\ufb00erent ACHIPrelated experiments are planned to be conducted at ARES. In the \ufb01rst experiment we plan to accelerate already preaccelerated relativistic single electron bunches in a laserilluminated dielectric grating structure. The goal of the experiment is to show net-acceleration with low energy spread growth instead of a broad energy modulation. Since the ACHIP target periodicity of the DLA structure currently is 2 \u00b5m, achieving a DLA drive laser to electron phase spread of \u03c3\u03c6 < \u03c0/4 is challenging. At ARES we aim to produce su\ufb03ciently short bunches using the velocity bunching technique [5, 6, 7, 8]. Email address: frank.mayet@desy.de (F. Mayet) In addition to the short bunch lengths the small scale of the DLA structures consequentely implies the need for ultra-stable drive laser to electron phase. In order to enable stable multi-shot operation we plan to also implement a technique for phase-synchronous acceleration of microbunch trains [9]. The main idea of the scheme is to condition a relatively long bunch in a way that it is transformed into a train of ultra-short microbunches. If done correctly, these microbunches then populate the periodic accelerating buckets in a phase stable manner. The third experiment, which is planned to be conducted at ARES, aims to test the feasibility of using DLA structures as transverse de\ufb02ectors (DLA TDS). To this end either single bunches or trains of microbunches are injected in a suitably designed and driven structure. A detailed study of this topic can be found in these proceedings [10]. Hence it is left out here for brevity. 2. The SINBAD Facility and ARES The dedicated accelerator R&D facility SINBAD (Short INnovative Bunches and Accelerators at Desy) is a new facility at DESY, which is foreseen to host multiple independent experiments. Two experiments are currently under construction: ARES (Accelerator Research Experiment at Sinbad) and AXSIS [11]. The ACHIP experiments are planned to be conducted at the ARES linac Preprint submitted to Nuclear Instruments and Methods in Physics Research Section A June 24, 2021 arXiv:1801.07503v1 [physics.acc-ph] 23 Jan 2018 \fRF(Gun Dual(Pl. Steerer BAM Dipole( Spectrometer BCM Steerers (H/V) Travelling(Wave( Structure(1 Travelling(Wave( Structure(2 Solenoids A B B B A Screen,(TEM(grid((advanced(beam(diagnostics), Collimator,(Faraday(Cup B Screen Screen(+(Faraday(Cup Gun( Solenoids Diagnostic(Stations: Figure 1: The ARES linac. (see Fig. 1). The ARES linac is a conventional 100 MeV S-band linac, which is designed to produce sub-fs electron bunches with charges in the range of 0.5-20 pC. To this end the electrons are \ufb01rst accelerated in a 1.5 cell S-band gun to 5 MeV with a single bunch repetition rate of up to 50 Hz. They are then further accelerated in two S-band traveling wave (TW) structures. In order to compress the bunch the two TW structures can be used for velocity bunching [5]. Transverse focusing is achieved using multiple solenoids (cf. Fig. 1). The accelerator is planned to be available for DLA-related experiments in mid 2019. In the \ufb01rst stage the ACHIP experiments are planned to be conducted within the 4 m space between the two TW structures and a matching region, which is needed for a later energy upgrade of the beamline (see Fig. 2 and Fig. 3). After the interaction point the beam will be transported through the matching region to a dipole spectrometer in order to diagnose the energy gain/modulation. Matching Section + Spectrometer for Commissioning ARES-linac 13.5 m Cathode Laser (Pharos SP-200) Collimator Target Chamber 257 nm 1000 nm Vacuum Valve Screen Steerers (H/V) DLA not to scale to scale 17.5 m DLA Laser Table and Diagnostics Quadrupole DLA Laser System not to scale Figure 2: Sketch of the ARES beam line and the preliminary layout of the \ufb01rst ACHIP experiment. Photo cathode laser Gun Experimental%laser beam%line 13.5%m%ARES%linac 4%m%experimental%area Matching section for chicane,%dipole spectrometer Figure 3: CAD model of the relevant part of the ARES linac beamline and the experimental area, which is foreseen for the ACHIPrelated experiments. 3. External Injection of Single Bunches The \ufb01rst DLA-related experiments at SINBAD are planned to be based on the external injection of single ultra-short electron bunches into a grating-type DLA structure. In the current design both the cathode of the RF-gun and the DLA are driven by the same laser system (see Fig. 2). Since the DLA is foreseen to be operated with a laser wavelength of 2 \u00b5m, the initial 1028 nm beam is split and converted on the one hand to 257 nm (fourth harmonic generation) and on the other to 2 \u00b5m (optical parametric ampli\ufb01er). This setup has the advantage of intrinsic synchronization between the cathode and the DLA laser beams. The relative electron to laser phase jitter is hence mainly given by the RF-induced beam arrival time jitter contribution. 3.1. Working Point Tab. 1 shows the beam parameters at the interaction point for a simulated ARES working point. It is based on a 100 fs rms laser pulse length on the cathode (Gaussian time pro\ufb01le) and optimized for minimal bunch length using the velocity bunching technique. The simulation was performed using ASTRA [12] including space charge. Table 1: Simulated Working Point for External Injection of Single Bunches. Parameter @ IP Value Charge [pC] 0.5 Bunch Length [fs, FWHM] 2.1 E [MeV] 99.1 \u2206E/E [%] 0.12 \u03c3xy [\u00b5m] 7.8 \u03f5n,xy [nm] 105 3.2. Simulation Simulations were performed using a combination of ASTRA and VSim 7.2 [13]. The procedure combines the simulation of the ARES working point up to the DLA (ASTRA-based) and the DLA interaction (VSim-based). Any possible interaction of the electrons with the dielectric material is currently not taken into account. The beam is assumed to be collimated just upstream of the DLA. Figure 4 shows the energy spectrum of the transmitted part before and after the DLA interaction respectively. In the simulation an accelerating gradient of 1 GeV/m over 150 periods was assumed. In reality this will depend a lot on the achievable laser parameters at the DLA, which are not \ufb01xed at the time of this publication. As the electrons are already highly relativistic dephasing is not an issue here. The results show that \u223c80 % of the collimated core of the bunch is accelerated. 2 \fFigure 4: Simulated energy spectrum of the transmitted part of the bunch before (left) and after (right) the DLA interaction (mean energy gain of \u223c300 keV). The bins are chosen according to the expected minimum energy resolution of the spectrometer (\u223c10\u22124). 4. Phase-Synchronous Acceleration In the previous section a \ufb01rst possible experiment involving single bunches was described. As has been stated above achieving an energy spectrum as shown in Fig. 4 over many conscutive shots assumes a very stable bunch arrival time at the DLA. In order to achieve reasonably low energy spread growth due to arrival time jitter, the rms phase stability needs to be < \u03c0/4, which translates to < 1 fs for a DLA period length of 2 \u00b5m. This is a very challenging goal, as the design phase stability of ARES is currently given as < 10 fs rms. In order to tackle this problem, we want to adapt a scheme that has already been successfully used in other contexts [14, 15] to our DLA case. The main idea of the scheme is to condition a relatively long bunch in a way that it is transformed into a train of ultrashort microbunches. If done correctly, these microbunches then populate the periodic accelerating buckets in a phase stable manner. Fig. 5 shows a sketch of how the scheme works. The inBeam splitter Magnetic chicane DLA Modulator Injection Beam from Linac 2 micron laser beam Delay Longitudinal phase space Energy modulation Density modulation Figure 5: Basic representation of the microbunching scheme using a modulator and a chicane. coming long electron bunch is modulated inside an undulator, into which a laser pulse is colinearly injected in a way that it overlaps with the electron bunch in time and space. The external laser \ufb01eld consequently imprints an energy modulation onto the electron distribution, which can in the plane wave approximation be expressed as [16] \u2206\u03b3 = r PL P0 2KLuJ \u03b3w0 cos(kLs), (1) where s is the comoving longitudinal coordinate, PL the laser beam power, P0 \u22488.7 GW, K the undulator parameter, Lu the undulator length, w0 the laser waist, kL the laser wave number and J = J0(\u03be/2) \u2212J1(\u03be/2) with \u03be = K2/(2 + K2). The device is hence called a laser modulator. The imprinted energy modulation can then be transformed into a density modulation, which ultimately (and ideally) results in a train of microbunches. If the energy of the incoming electrons is low enough this transformation can be achieved by a simple drift, but in case of highly relativistic electrons a dispersive section such as a magnetic chicane has to be used. Once the train of microbunches is formed it can be transported and injected into the DLA structure. If both the modulator and the DLA are driven by the same laser and the relative phase jitter between the two arms is negligible, intrinsic phase synchronisation between the microbunches and the DLA \ufb01eld can be achieved. Any laser to electron bunch phase jitter in the DLA caused by the laser system or the electron time of arrival is compensated due to the fact that the intrabunch phase of the microbunch train is also shifted by the same amount. In other words: The modulator acts as a focusing device in the time/phase domain. Any residual laser to electron phase jitter can now be attributed to the mean electron energy (via R56) and the phase jitter between the two laser arms. 4.1. Integration In [9] we have already studied a theoretical extension of the ARES beamline in order to show the feasibility of the concept in the 2 \u00b5m DLA context. A clear enhancement of the accelerated fraction in the modulator on case was con\ufb01rmed in simulation compared to the non-modulated beam. Preliminary start to end simulations based on ASTRA, GENESIS 1.3 [17] and VSim 7.2 showed an achievable microbunch train with microbunches as short as (699 \u00b1 88) attoseconds FWHM with a spacing of (2.00 \u00b1 0.01) \u00b5m in its 6 period core. In order to keep the setup at SINBAD as small and affordable as possible we aim to use a scaled down version of the setup, which \ufb01ts into the planned target chamber. Current plans foresee repurposing components that have already been used at SLAC (NLCTA) [14]. The components comprise a miniature undulator, permanent magnetic chicance and permanent magnetic quadrupole (PMQ) triplet. Tab. 2 shows the relevant parameters of the components. 4.2. Simulation The undulator was originally designed for an 800 nm drive laser and 60 MeV. The wavelength of emitted undu3 \fTable 2: Relevant Parameters of the Microbunching Hardware according to [14]. Note that all Components can be adjusted. Parameter Value Undulator Undulator Period [cm] 1.8 Periods 3 Undulator Parameter 0.46-1.7 Chicane R56 [mm] 0.06-0.22 PMQ Bore Radius [mm] 3 Magnet Length (1) [mm] 7 Magnet Length (2,3) [mm] 13 Spacing (adjustable) [mm] 4-20 Bmax,pole [T] 0.6 lator radiation is given by \u03bbl = \u03bbu 2\u03b32 \u0012 1 + K2 2 \u0013 , (2) where \u03bbu is the undulator period and \u03b3 the normalized energy of the electrons. Since the pulse energy of our cathode laser system is limited and the conversion from 1 \u00b5m to 2 \u00b5m involves substantial losses (e\ufb03ciency \u223c0.2), we currently plan to perform the microbunching at 1 \u00b5m. Using Eq. 2 hence yields a resonant energy between 50.5 and 75.5 MeV depending on the adjustable K of the undulator. In order to achieve as short microbunches as possible the relative energy spread at the modulator needs to be as low as possible [9]. In our case in order to achieve \u2264\u03c0/4 bunch length, \u2206\u03b3/\u03b30 \u22645.7\u00b710\u22124. Also the energy chirp should be as low as possible in order ensure even spacing between the individual microbunches. Tab. 3 shows a possible ARES working point. For this study we use ELEGANT [18] to Table 3: Simulated Working Point for External Injection of Microbunch Trains. Parameter @ Mod Value Charge [pC] 2.5 Bunch Length [fs, rms] 112.3 E [MeV] 75.26 \u03b4 0.76 \u00b7 10\u22124 \u03f5n,xy [nm] 248 simulate the laser modulator and OCELOT [19] for the further beam transport through the chicane and the PMQ triplet. NB: No collective e\ufb00ects are taken into account in the laser modulator. The OCELOT simulation includes both space charge and CSR. Fig 6 shows a slice of the z \u2212x phase space of the simulated beam at the DLA entrance, as well as the obtained microbunch properties. The microbunch length along the whole macro pulse is (186\u00b173) as FWHM with a spacing of (1.0002\u00b10.0091) \u00b5m (N = 118). This is well below our \u03c3\u03c6 < \u03c0/4 requirement at 1 \u00b5m. Prior to the DLA simulation the beam is collimated in order to accomodate the <2 \u00b5m channel width. Fig. 7 Table 4: Simulation parameters used in ELEGANT and OCELOT. Parameter Value Undulator Undulator Parameter 1.7 Dispersive Section R56 [mm] 0.13 Laser Pulse Energy [\u00b5J] 90 Pulse Length [fs, rms] 300 Waist [\u00b5m] 500 Figure 6: Top: z \u2212x phase space of a longitudinal 9 period slice of the simulated beam at the DLA entrance showing 9 consecutive microbunches. Bottom: Projection across the horizontal axis. Microbunch length: (160\u00b113) as FWHM, spacing: (1.0011\u00b10.0068) \u00b5m. shows the achieved energy gain of the slice due to the DLA interaction for the microbunched and unmodulated beam for comparison. As for the single bunch case we simulated a 150 period dual grating DLA with is operated at an accelerating gradient of 1 GeV/m. It can be seen that the acceleration e\ufb03ciency is clearly enhanced as can also be seen in our previous studies [9]. 5." + } + ], + "Willi Kuropka": [ + { + "url": "http://arxiv.org/abs/1802.02874v1", + "title": "Full PIC simulation of a first ACHIP experiment @ SINBAD", + "abstract": "In laser illuminated dielectric accelerators (DLA) high acceleration\ngradients can be achieved due to high damage thresholds of the materials at\noptical frequencies. This is a necessity for developing more compact particle\naccelerator technologies. The Accelerator on a CHip International Program\n(ACHIP) funded by the Gordon and Betty Moore Foundation is researching such\ndevices. DESY Hamburg is part of the collaboration. The dedicated accelerator\nresearch facility SINBAD is particularly well suited for DLA experiments at\nrelativistic electron energies. High quality beams and short bunch lengths are\nanticipated from the ARES linac which is currently under construction at\nSINBAD. The aim of the experiment is the injection of a short electron bunch\nfrom the ARES linac into a DLA. In this study the results of one of the first\npossible experiments at the facility are estimated via a combination of\nparticle-in-cell (PIC) and tracking simulations. ASTRA is used to simulate an\nelectron bunch from the ARES linac at a suitable working point. The dielectric\npart of the setup will be simulated using the PIC code from CST Particle Studio\nincorporating the retrieved bunch from the ASTRA simulation. The energy spectra\nof the electron bunches are calculated as would be measured from a spectrometer\ndipole with and without the laser fields.", + "authors": "Willi Kuropka, Frank Mayet, Ulrich Dorda, Ralph Assmann", + "published": "2018-02-08", + "updated": "2018-02-08", + "primary_cat": "physics.acc-ph", + "cats": [ + "physics.acc-ph" + ], + "main_content": "Introduction The Accelerator on a CHip International Program (ACHIP) is a research project funded by the Gordon and Betty Moore Foundation. It aims at the construction of a compact fully laser driven dielectric electron accelerator for radiation generation and atto-second science. Several Universities in Europe and the USA and the national Laboratories PSI, DESY and SLAC are involved [1]. This research \ufb01eld gains more attention in recent years as the search for compact particle acceleration technologies continues. Fully dielectric laser driven acceleration structures are foreseen to sustain high acceleration gradients in the GV m\u22121 regime. This is mainly due to the high laser damage thresholds of dielectrics at optical frequencies. The advancement in microand nano-fabrication from the semiconductor industry can be leveraged in the manufacturing of these structures limiting production costs. Also the ongoing development in laser technologies promises higher repetition rates and average powers suitable for DLAs [2]. DESY Hamburg contributes to the ACHIP project by granting access to its SINBAD facility and support from the ARD (accelerator research and development) and laser groups. SINBAD is the upcoming dedicated lon term accelerator research and development facility at DESY. At Email address: willi.kuropka@desy.de (W. Kuropka) the moment two projects are foreseen to be implemented. The \ufb01rst is ARES (Accelerator Research Experiment at Sinbad), which is based on a linac consisting of an S-band, normal conducting radio frequency gun and traveling wave accelerator structures. The second project is called AXSIS (Frontiers in Attosecond X-ray Science: Imaging and Spectroscopy [3]) and aims at X-ray radiation generation via inverse compton-scattering with electrons from THzdriven dielectric lined waveguides [4]. The location of the ACHIP related experiments will be at the ARES linac. It is foreseen to inject already relativistic electron bunches at around 100 MeV from the linac into the DLA structures. Its high beam quality and short femtosecond electron bunches are well suited for DLA experiments with small apertures and optical drive laser wavelengths. By driving the DLA with at least 2 \u00b5m wavelength a single bunch net-acceleration experiment is feasible. In this work we present a full PIC (CST Particle Studio [5]) simulation of the DLA interaction with an ASTRA [6] simulated electron bunch from the ARES linac. The energy spectra with and without the laser \ufb01eld are calculated as anticipated from a dipole spectrometer. The results are compared with a simpli\ufb01ed simulation code for DLAs developed in-house in our group [7]. Preprint submitted to Nuclear Instruments and Methods in Physics Research Section A September 20, 2018 arXiv:1802.02874v1 [physics.acc-ph] 8 Feb 2018 \f2. ARES working point and experimental setup The ARES linac consists of an S-band gun and two traveling wave structures (TW). The experimental area will be situated after the second TW shown in \ufb01gure 1. For this working point the \ufb01rst TW is used o\ufb00-crest for velocity bunching yielding a longitudinal focus into the second TW structure where the compressed bunch length is \ufb01xed due to reaching high Lorentz-factor. The TWs are equipped with solenoid magnets to focus the beam transversely. With this setup the working point shown in table 1 is achievable in simulation. Figure 1: Overview of the ARES linac with reserved space for the experimental area. Table 1: Simulated working point at structure center for minimal bunch length using velocity bunching from [8] Parameter @ IP Value Charge [pC] 0.5 Bunch Length [fs, FWHM] 2.1 (0.3 * \u03bb0) E [MeV] 99.1 \u2206E/E [%] 0.12 \u03c3xy [\u00b5m] 7.8 \u03f5n,xy [nm] 105 For the \ufb01rst experiments the drive laser power for the DLA is split from the ARES cathode laser. A small part of the power is converted to UV via a fourth-harmonic generator. An optical parametric ampli\ufb01er is used to convert the remaining laser power from 1 \u00b5m to 2 \u00b5m. This is feasible due to low charge requirements for this kind of experiment. The cathode laser delivers 1 mJ. For this setup the split-o\ufb00and the conversion e\ufb03ciency of an OPA of around 10 % only allow for low two digit \u00b5J pulse energy at the 2 \u00b5m wavelength. Using this wavelength with a period of 6.67 fs a net-gain in particle energy is possible since the bunch only covers a limited phase range of around one third of the accelerating \ufb01eld. Other methods can be implemented to achieve net-gain of a bunch train and to reduce arrival time jitter [9]. The cathode laser pulse has to be short to achieve the short bunch lengths necessary, about 120 fs. The laser pulse duration at the DLA is identical to the duration at the cathode. The temporal and spatial shape of the laser pulse are Gaussian. Table 2 shows the collected laser parameters. The maximum electric \ufb01eld amplitude in the channel for the given pulse energy is around 4 GV m\u22121. These parameters are still well below the anticipated damage threshold of fused silica [10]. To have the maximum possible energy gain the interaction length is elongated by introducing a 45\u25e6pulse front tilt to the DLA drive pulse. The resulting interaction length is 100 \u00b5m. The DLA for the simulation is assumed with this length containing ca. 50 periods. Table 2: laser pulse parameters Parameter @ IP Value Wavelength [\u00b5m] 2 \u03c3t [fs] 120 Energy [\u00b5J] 14 \u03c3x [\u00b5m] 50 \u03c3y [\u00b5m] 10 3. PIC simulation The particle-in-cell code from CST Studio Suite 2017 was used for this simulation. A grating type pillar structure with 50 periods of fused silica illuminated from both sides was simulated (see \ufb01gure 2). The total laser pulse energy is 14 \u00b5J. Spatially a Gaussian intensity pro\ufb01le of the laser is assumed. The electron beam is assumed to be collimated horizontally to the gap size of the DLA and to a full width of 10 \u00b5m in vertical direction allowing only small transmission of around 25 fC. The beam size does not change signi\ufb01cantly along the structure. This should still be detectable with an intensi\ufb01ed CCD camera setup [11]. At \ufb01rst zero emittance test beams comprised of single electrons emitted at each timestep from point sources were simulated. Figure 3 shows the dependency of various particle parameters after the DLA interaction on the injection time. As expected the accelerating electron-to-laser-phase shows transverse defocusing. At the phase of the highest achievable energy gain the bunch from the ARES simulation was injected. The same particle distribution was propagated using the in-house code. 4. Results In \ufb01gure 4 the energy spectra of the bunch after the DLA are shown with laser illumination and without. The 2 \fFigure 2: Schematic of the pillar grating type DLA with parameters \u03bb0 = 2 \u00b5m, A = 0.5 \u2217\u03bb0, C = 0.37 \u2217\u03bb0, H = 0.87 \u2217\u03bb0. Figure 3: Shown is the data of three test particle beams from point sources at the center of the structure gap and at a horizontal o\ufb00sets from the center of 150 nm. The \ufb01rst plot shows the horizontal transverse kick of the particles. The second plot shows the horizontal transverse o\ufb00set from the starting position. And the third shows the particle energy. All show the corresponding di\ufb00erence before and after the structure dependent on the injection time zoomed to the period of maximum achievable energy gain. interaction with the structure due to wake\ufb01elds and beam loading are not visible in the spectrum, which is to be expected due to the symmetry of the beam and the low charge. This is most likely due to the low bunch charge. The spectrum with the laser \ufb01eld shows a mean net-gain in particle energy of 43.2 keV. This corresponds to an acceleration gradient of 432 MeV/m. The third histogram in \ufb01gure 4 shows the result from the in-house code, which is in good agreement with the full PIC simulation. The transverse phase spaces are virtually the same in all three scenarios. The short propagation distance allows for no conclusion about the accuracy of the code with respect to the PIC simulation. It is important to mention the arrival time jitter of the ARES linac, which is expected to be in the order of 10 fs. This means that the actual bunches will be injected at a Figure 4: Shown are the histograms of the particle energy distribution after the DLA. The \ufb01rst histogram is without the laser \ufb01eld. The second one is from the PIC simulation with laser \ufb01eld. And the third one shows the spectrum from the in-house code. random laser to electron phase. With a maximum repetition rate of 50 Hz sorting of the recorded spectra is feasible to look at the single shot spectra. Methods to mitigate the arrival time jitter are under investigation [12]. 5. Outlook The simulations have to be extended to include possible laser system upgrades to show the full potential of the setup. Additional conventional or permanent magnet based focusing of the electron beam into the DLA should be investigated to increase electron beam transmission. Methods to mitigate the arrival time jitter have to be developed to show stable net acceleration and to scan the electron to laser phase to fully characterize DLA structures. Optimization of the DLA structures with respect to acceleration gradients and transverse beam manipulation are underway. 6." + }, + { + "url": "http://arxiv.org/abs/1802.01945v1", + "title": "Simulation of deflecting structures for dielectric laser driven accelerators", + "abstract": "In laser illuminated dielectric accelerators (DLA) high acceleration\ngradients can be achieved, due to high damage thresholds of the materials at\noptical frequencies. This is a necessity in developing more compact particle\naccelerator technologies. The Accelerator on a CHip International Program\nfunded by the Gordon and Betty Moore Foundation is researching such devices.\nMeans to manipulate the beam, i.e. focusing and deflection, are needed for the\nproper operation of such devices. These means should rely on the same\ntechnologies for manufacturing and powering like the accelerating structures.\nIn this study different concepts for dielectric laser driven deflecting\nstructures are investigated via particle-in-cell (PIC) simulations and compared\nafterwards. The comparison is conducted with respect to the suitability for\nbeam manipulation. Another interesting application will be investigated as a\ndiagnostic device for ultra short electron bunches from conventional\naccelerators functioning like a radio frequency transverse deflecting cavity\n(TDS).", + "authors": "Willi Kuropka, Frank Mayet, Ulrich Dorda, Ralph Assmann", + "published": "2018-02-06", + "updated": "2018-02-06", + "primary_cat": "physics.acc-ph", + "cats": [ + "physics.acc-ph" + ], + "main_content": "Introduction The Accelerator on a CHip International Program (ACHIP) is a research project funded by the Gordon and Betty Moore Foundation. It aims at the construction of a compact fully laser driven electron accelerator for radiation generation and atto-second science. Several universities in Europe and the USA and the national laboratories PSI, DESY and SLAC are involved. [1] This research \ufb01eld gains more attention in recent years as the search for compact particle acceleration technologies continues. Fully dielectric laser driven acceleration structures are foreseen to sustain high acceleration gradients in the GV m\u22121 regime. This is mainly due to the high laser damage thresholds of dielectrics at optical frequencies. The advancement in microand nano-fabrication from the semi conductor industry can be leveraged in the manufacturing of these structures limiting production costs. Also the ongoing development in laser technologies is promising.[2] Structures for focusing and de\ufb02ection of the beam are necessary for the eventual implementation of such an accelerator. De\ufb02ecting structures also can be useful diagnostics for short electron bunches. In this paper three candidates for the de\ufb02ection of particles are investigated via PIC simulation. 2. Grating based dielectric laser acceleration The investigated structure consists of two gratings with a gap. They are illuminated form both sides with laser Email address: willi.kuropka@desy.de (W. Kuropka) beams. The laser beams are in phase and have the same amplitude. Electric \ufb01elds of both beams are polarized in the direction the electron beam travels along the gap. Figure 1 is illustrating the structure. The periodic di\ufb00raction \ufb01elds in the gap along the zaxis can be described via spatial harmonics. If the grating period matches the incoming laser wavelength, the \ufb01rst spatial harmonic has a speed of light phase velocity. The acceleration in this harmonic is transversely uniform depending on the gap size. The phase velocity of this \ufb01rst spatial harmonic can be reduced by shortening the grating period with respect to the laser wavelength making it possible to also accelerate non-relativistic particles. Alternatively higher order modes can be chosen to be synchronous with the particle according to this synchronicity condition: \u03bbDLA = n\u03b2\u03bblaser (1) Where n is the order of the spatial harmonic, \u03b2 is the fraction of the vacuum speed of light of the particle, \u03bblaser is the central wavelength of the incoming laser \ufb01eld and \u03bbDLA gives the period of the grating structure. 3. Grating based de\ufb02ecting structures The presented structures are grating based due to the necessary compatibility with the grating type accelerator design. For acceleration the electric \ufb01eld of the incoming laser is linearly polarized in longitudinal direction of the electron beam. In the \ufb01rst investigated scheme (A) the polarization is rotated 90\u25e6into the y-direction transverse to the e-beam. Preprint submitted to Nuclear Instruments and Methods in Physics Research Section A November 8, 2021 arXiv:1802.01945v1 [physics.acc-ph] 6 Feb 2018 \fFigure 1: Schematic of the double illuminated pillar grating type DLA with parameters \u03bbDLA = 1.994 \u00b5m, A = 0.5\u2217\u03bb0, C = 0.37\u2217\u03bb0, H = 0.87 \u2217\u03bb0 for the laser wavelength from 2 with fused silica as dielectric The de\ufb02ection now should occur in the \u201cfree\u201d direction not limited by the grating aperture . For the second scheme (B) the phase of the two incoming beams is set o\ufb00by 180\u25e6canceling out the accelerating \ufb01elds and amplifying the transverse components. Here the de\ufb02ection appears in the direction limited by the grating (See \ufb01gure 1 and table 1). The third scheme (C) is from [3] and a rotation of the whole acceleration structure so that the force has an additional strong transverse component as shown in \ufb01gure 2. The polarization of the electric \ufb01eld of the laser is still perpendicular to the direction of the grating groves. The other component is still in the longitudinal direction and will induce additional energy spread if used as streaking device. Table 1: Laser Parameters for Acceleration and Schemes A and B E-Field Accelerator Scheme A Scheme B Ex,1 0 0 0 Ey,1 0 E(x, y, z, t) 0 Ez,1 E(x, y, z, t) 0 E(x, y, z, t) Ex,2 0 0 0 Ey,2 0 E(x, y, z, t) 0 Ez,2 E(x, y, z, t) 0 E(x, y, z, t) \u03c601 \u2212\u03c601 0 0 180\u25e6 4. PIC simulation The CST PIC [4] simulations were set up with the parameters from table 2 for one grating period with a point source test beam and excited by plane wave. The de\ufb02ection is laser-to-electron phase dependent and the maxiFigure 2: The whole structure is rotated so that the electron beam travels through the gap at an angle relative to the grating grooves. Illustration taken from [3] Scheme C. mum is shown in table 3. The dimensions of the grating used in the simulation are shown in \ufb01gure 1. Additionally the transverse kick from the acceleration structure is investigated as comparison. It is important to note that this kick is position dependent and particles at the center of the gap are not kicked. This is comparable to a focusing or defocusing of an electron beam. Here the o\ufb00set for the test beam is 150 nm from the gap center. Table 2: Simulation Parameters Parameter Value Wavelength 2 \u00b5m Laser Amplitude 2 GV m\u22121 Particle Energy 5 MeV Table 3: Simulation results Scheme A B C Accel. Max. de\ufb02. 4 \u00b5rad 20 \u00b5rad 34 \u00b5rad 0.5 \u00b5rad De\ufb02. plane unlimited limited unlimited focusing 5. Results The results show that the schemes B and C may be feasible candidates for de\ufb02ection or streaking devices. In scheme B the beam size is limited by the aperture of the structure which limits the resolution in a streaking application. For beam manipulation the scheme may still be feasible. Scheme C has the strongest de\ufb02ection forces but inherently has longitudinal forces in the sam order of magnitude, too, which would add to the energy spread of the streaked particles. Both schemes have transverse forces an order of magnitude stronger than the focusing/defocusing forces of the acceleration structure. Scheme A has only limited de\ufb02ection forces. The electric \ufb01eld and the e\ufb00ect of the magnetic \ufb01eld are canceling each other out. In \ufb01gure 3 the relations for the di\ufb00erent schemes are shown. 2 \fFigure 3: The top graph shows the dependecy of the transverse and longitudinal kicks for scheme A and B. There are no signi\ufb01cant longitudinal kicks. The middle graph shows the relation for scheme B where the signi\ufb01cant longitudinal an transverse kicks are in phase. The third graph shows the relation for the grating used as an accelerator. 6. Outlook and" + } + ] + }, + "edge_feat": {} + } +} \ No newline at end of file