{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Walkthrough 1: Introduction to Oqtant and Oqtant Quantum Matter Services (QMS) #\n", "This notebook runs on Oqtant hardware and uses **1 job** " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction ##" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Welcome to the `Oqtant python API`, aka `OqtAPI`, an object-oriented interface for creating, submitting, and retrieving results from experiments with ultracold quantum matter on Infleqtion's Oqtant Quantum Matter Services (QMS) platform. In this introductory walkthrough, we will explore the basics of how you interact with Oqtant QMS using OqtAPI. The general workflow is as follows:\n", "\n", "1. Create an Oqtant account: [https://oqtant.infleqtion.com](https://oqtant.infleqtion.com)\n", "2. Download and install Oqtant: [https://pypi.org/project/oqtant/](https://pypi.org/project/oqtant/)\n", "3. Run this Jupyter Notebook to get started!\n", "4. Instantiate an instance of the `QuantumMatterFactory`, which facilitates communication with Oqtant QMS. This object handles authentication.\n", "5. Create a user-defined `QuantumMatter`, aka *matter*, object for making and/or manipulating quantum matter. This is accomplished with the help of a `QuantumMatterFactory`. This *factory* will serve as your \"one stop shop\" for creation of abstracted objects that control experiments carried out on the Oqtant hardware.\n", "6. Submit your *matter* object to Oqtant QMS. This submits your job to Oqtant's hardware platform. Each *matter* object represents one job, and is identified by a `job id` (UUID or *id*). \n", "7. Use the *matter* object to check status of your job.\n", "8. When your job is complete, view and analyze results. \n", "\n", "For more information, please refer to our documentation: [https://oqtant-docs.infleqtion.com](https://oqtant-docs.infleqtion.com)\n", "\n", "See our web application https://oqtant.infleqtion.com/ for quick access to job creation, results, and account management.\n", "\n", "\n", "Support, feature requests, and bug reports can be submitted here: [https://oqtant.infleqtion.com/support](https://oqtant.infleqtion.com/support)\n", "\n", "This, along with all our example notebooks are publicly available for download from our [GitLab repository.](https://gitlab.com/infleqtion/albert/oqtant-documentation/-/tree/main/oqtant_documentation/docs/examples?ref_type=heads)\n", "\n", "\n", "This walkthrough focuses on how to use OqtAPI with Oqtant QMS. Follow-on walkthroughs will explore user options, accessible abstractions, and data structures in more detail." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Imports and user authentication ##" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "from oqtant.schemas.quantum_matter import QuantumMatterFactory\n", "\n", "qmf = QuantumMatterFactory()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Authenticate automatically ###\n", "\n", "The easiest way to authenticate as an Oqtant user is to execute the following cell. This will activate a widget that will let you sign in, assuming you already have a verified account at [oqtant.infleqtion.com](https://oqtant.inflection.com). If popups are blocked, or you are on a system that does not support this method, please follow the steps just below to authenticate manually instead. \n", "Note that currently the *automatic authentication method is only compatible with classic jupyter notebooks*, and not jupyter lab, nanohub, binder, colab, etc." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "qmf.get_login()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Authenticate manually ###\n", "\n", "If you cannot use the automatic authentication method above, you can instead authenticate using a slightly more manual process: \n", "\n", "1. Navigate to [oqtant.infleqtion.com](https://oqtant.infleqtion.com) and create an account (if you haven't already)\n", "2. Log in, if this is your first time you will need to activate your account with the verification email\n", "2. On the left-hand menu selector, click on \"Oqtant API\" (or go to [oqtant.infleqtion.com/oqtantAPI](https://oqtant.infleqtion.com/oqtantAPI))\n", "3. At the bottom of that page, click the box that copies your API access token to the clipboard\n", "4. Paste that token just below and execute the cell (the if statement keeps the code from executing if you already authenticated above)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "if qmf.login.access_token == \"\":\n", " qmf.login.access_token = \"Paste your token here between the quotes!\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Get client ###\n", "\n", "At this point you should have a valid access token and be able to establish a *client* for communicating with the Oqtant REST service. Executing the cell just below should show your current job quota limits." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "qmf.get_client()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Your first *QuantumMatter* object and job ##" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The QuantumMatter object captures the user-defined inputs that control the behavior of Oqtant hardware. We will explore the available options and underlying data structures in detail in following walkthroughs." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Instantiate a *QuantumMatter* object ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create a QuantumMatter object to generate quantum matter at a target temperature (in nanokelvin, nK). We will also give our object a name (optional). Use the imported `QuantumMatterFactory.create_quantum_matter()` method:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "name='my second quantum matter' temperature=100.0 lifetime=10 image= time_of_flight=12 rf_evap=None rf_shield=None barriers=None landscape=None lasers=None note=None client= result=None job_id=None output=None is_sim=False sim=None run=1\n" ] } ], "source": [ "matter = qmf.create_quantum_matter(temperature=100, name=\"my second quantum matter\")\n", "print(matter)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Submit your *QuantumMatter* object to Oqtant QMS to run a job ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Submit our *QuantumMatter* object to Oqtant QMS using the `submit()` method. This will create a job that will enter the QMS job queue. When you submit, the *QuantumMatter* object recieves a unique job *id* (32 character UUID string). Track the status of our job in the queue by passing the *track=True* option. The default value is *False*. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Submitting 1 job(s):\n", "\n", "- Job: my second quantum matter\n", " Job ID: eb7d0bbe-011f-4c14-888c-44508d3fa6b5\n", "\n", "Tracking 1 job(s):\n", "\n", "- Job: my second quantum matter\n", " - RUNNING\n", " - COMPLETE\n", "\n", "All job(s) complete\n" ] } ], "source": [ "matter.submit(track=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Job are submitted to the queue and receive an id (PENDING), executed on the hardware (RUNNING) and then finish (COMPLETE). The elapsed time depends on the current queue and whether your account is deducting from priority (paid) or free quotas. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Retrieve/fetch the COMPLETE job ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once a job is complete, fetch the results with the `get_result()` method. If your job is not yet complete, you can still fetch the job from the server but the output fields will not be populated." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'COMPLETE'" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# get result from server, including results if available\n", "matter.get_result()\n", "matter.status" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Extract, visualize, and analyze job results ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Output data fields ####" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The contents of the output data depend on the initially constructed QuantumMatter object. Review the contents of a completed job:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "- mot_fluorescence_image\n", " - pixels\n", " - rows\n", " - columns\n", " - pixcal\n", "- tof_image\n", " - pixels\n", " - rows\n", " - columns\n", " - pixcal\n", "- tof_fit_image\n", " - pixels\n", " - rows\n", " - columns\n", " - pixcal\n", "- tof_fit\n", " - gaussian_od\n", " - gaussian_sigma_x\n", " - gaussian_sigma_y\n", " - tf_od\n", " - tf_x\n", " - tf_y\n", " - x_0\n", " - y_0\n", " - offset\n", "- tof_x_slice\n", " - points\n", "- tof_y_slice\n", " - points\n", "- total_mot_atom_number\n", "- tof_atom_number\n", "- thermal_atom_number\n", "- condensed_atom_number\n", "- temperature_nk\n" ] } ], "source": [ "matter.output.fields" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This job contains results from a fluorescence image of the magneto-optical trap (MOT): a cooling stage early in the sequence that produces the quantum matter that is useful for diagnosing number drifts etc., \n", "\n", "This job also contains a time-of-flight (TOF) absorption image with pixel data, row/column counts, and a pixel calibration (pixcal, in microns/pixel), a fit version of the TOF image based on the calculated thermal/condensed atom populations and the associated calculated temperature. These fit results are derived from fitting a \"bimodal\" distribution, consisting of a sum of Gaussian (thermal/classical phase) and Thomas-Fermi (condensed phase) distributions, to the resulting (time of flight) image of the atoms. Data corresponding to the bimodal fit are included in the tof_fit field. \n", "\n", "All TOF image results are given in terms of the optical depth (OD). Advanced users may wish to implement their own temperature and atom population calculations using the included raw image data. \n", "\n", "Any of the output data contents can be accessed programmatically:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "temperature (nK): 162\n", "thermal atom population: 37750\n", "condensed atom population: 5917\n" ] } ], "source": [ "print(\"temperature (nK):\", matter.output.temperature_nk)\n", "print(\"thermal atom population:\", matter.output.thermal_atom_number)\n", "print(\"condensed atom population:\", matter.output.condensed_atom_number)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Extract output image data ####" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "OD image data can be accessed programatically as above, or using the `QuantumMatter.output.get_image_data()` helper method for additional processing. Specify the type of image data to be fetched . For this example, the image options are \"MOT\", \"TIME_OF_FLIGHT\", and \"TIME_OF_FLIGHT_FIT\". " ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "tof_image_data = matter.output.get_image_data(image=\"TIME_OF_FLIGHT\")\n", "tof_fit_image_data = matter.output.get_image_data(image=\"TIME_OF_FLIGHT_FIT\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Image data is returned as a 2D numpy array of values for integer-valued pixel positions. Convert pixel positions to position space using the pixel calibration value via the `QuantumMatter.output.get_image_pixcal` helper function, which returns the units of microns/pixel for each image type." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "4.4" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "matter.output.get_image_pixcal(\"TIME_OF_FLIGHT\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Access pre-calculated cuts of the time-of-flight image along the detected center/peak of the atom ensemble:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "x-slice: [-0.03847772935525559, -0.05357118251753738, -0.023739138223523665, -0.0062017975424166595, 0.027222791333841184]\n", "y-slice: [0.058041758365273366, 0.005338624191457333, -0.0250479825129293, 0.0324867731992234, 0.029763281240659713]\n" ] } ], "source": [ "x_slice = matter.output.get_slice(axis=\"x\")\n", "print(\"x-slice: \", x_slice[0:5])\n", "y_slice = matter.output.get_slice(axis=\"y\")\n", "print(\"y-slice: \", y_slice[0:5])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Visualize results ####" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "OqtAPI provides a number of tools/methods for visualizing job outputs. " ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "matter.output.plot_tof(figsize=(6, 6))\n", "matter.output.plot_slice(axis=\"x\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Built-in plots show the image of the atoms taken at the end of the experiment, in units of optical depth, as well as cuts along the x and y axes. The latter two plots include solid curves corresponding to the bimodal fit that includes the contributions from the quantum matter's thermal fraction (red curve) and thermal + condensed combination (blue curve).\n", "\n", "The OD data can be used directly for further customization and analysis:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "TOF_data = matter.output.get_image_data(\"TIME_OF_FLIGHT\")\n", "plt.figure(figsize=(6, 6))\n", "plt.title(\"Customized plot of the same OD results\")\n", "TOF_plot = plt.imshow(TOF_data, origin=\"upper\", cmap=\"nipy_spectral\")\n", "plt.grid(visible=True)\n", "plt.xlabel(\"x position (pixels)\")\n", "plt.ylabel(\"y position (pixels)\")\n", "plt.colorbar(TOF_plot, shrink=0.8)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Job management using the local filesystem ##" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Choose to retrieve jobs from the Oqtant web app, provided they have not been deleted or removed, or save the job data on your local machine. Local operation is convenient when dealing with large sets of jobs, or without network connectivity." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Save a job to file ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Record *QuantumMatter* from the current by saving information to a local file. For this, you can use the `QuantumMatter.write_to_file()` method:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wrote file: \"eb7d0bbe-011f-4c14-888c-44508d3fa6b5.txt\"\n" ] } ], "source": [ "matter.write_to_file()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By default, this method will save the job data in a newly created local file with the name `*job id*.txt` in the same directory as the current walkthrough / jupyter notebook. Alternatively, you can customize the resulting filename:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wrote file: \"my second quantum matter.txt\"\n" ] } ], "source": [ "matter.write_to_file(file_name=matter.name) # use job name as filename instead" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Full control of data saving is made available by providing the *full* path of the desired output file: (example with default Linux path)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wrote file: \"C:\\Users\\username\\path_to_file\\eb7d0bbe-011f-4c14-888c-44508d3fa6b5.txt\"\n" ] } ], "source": [ "import os\n", "\n", "home = os.path.expanduser(\"~\")\n", "\n", "matter.write_to_file(file_path=f\"{home}\\Documents\\\\{matter.job_id}.txt\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We recommend using the default of the job id to reduce possibility of overwriting job data." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Load a job from file ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Retrieve a job from a local file with (local directory) filename or the full file path:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wrote file: \"eb7d0bbe-011f-4c14-888c-44508d3fa6b5.txt\"\n" ] } ], "source": [ "job_from_file = qmf.load_matter_from_file(f\"{matter.job_id}.txt\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Additional details, features, and discussion ##" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Include user notes ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Every *QuantumMatter* object can hold a note up to 500 characters long. This can be used to add context and additional information. A note remains tied to the job and can be referenced later. The note can be added at the point of creating the QuantumMatter object:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "matter_with_note = qmf.create_quantum_matter(\n", " temperature=100,\n", " name=\"matter with a note\",\n", " note=\"This is something special that I would like to remember.\",\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### What is a `JobType`? ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Each QuantumMatter object submitted to Oqtant is assigned a `JobType` that depends on what features and options are specified. This allows Oqtant to enable or disable certain hardware features depending on what the user requires. We will explore the different job types in future walkthroughs. If you are using the web app, jobs will be identified by the associated job type. For our example shown here, our *matter* object is a *BEC* job: " ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "matter.job_type" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Search for previous jobs ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Need to go back in time? See a history of jobs submitted in previous sessions using `QuantumMatterFactory.search_jobs()`. This method provides a way to ask Oqtant for jobs associated to your account that match certain search criteria.\n", "\n", "The supported search values are:\n", "\n", "- job_type\n", "- name\n", "- submit_start\n", "- submit_end\n", "- notes\n", "\n", "*Note: submit_start and submit_end must be in ISO format to properly work (YYYY-MM-DD or YYYY-MM-DDThh:mm:ss)*\n", "\n", "Using these search values Oqtant will return to you any jobs that are associated to your account and match the provided criteria." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "found_jobs = qmf.search_jobs(name=\"my first\", limit=3, show_results=True)" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2024-04-02T19:54:01.189449Z", "start_time": "2024-04-02T19:54:01.186862Z" } }, "source": [ "### Load job by Id ###\n", "\n", "You can also load jobs by External Id. You can find this External ID through the search_ jobs method or from the \"My Jobs\" page of the Oqtant Web Application. We can see below that after loading Quantum Matter object from the last run job i has access to the same output fields as before. " ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Time-of-flight total atom number: 45505\n" ] } ], "source": [ "# this assumes that you created a job with name first job. You can alternatively replace job id with\n", "# a job id from your job list\n", "my_job = qmf.search_jobs(limit=1, show_results=False)\n", "first_job = qmf.load_matter_from_job_id(job_id=my_job[0][\"external_id\"], run=1)\n", "print(\"Time-of-flight total atom number: \", first_job.output.tof_atom_number)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Show the current status of your jobs in the queue ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When executing many jobs on Oqtant QMS, it is useful to be able to check the status of your submitted jobs without fetching each job individually and checking the status field. This can be accomplished using the `QuantumMatterFactory.show_queue_status()` method, which accepts the same filters as `QuantumMatterFactory.search_jobs()`." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0 job(s) queued:\n", "\n", "╒════════╤══════════╤══════════╤══════╕\n", "│ Name │ Status │ Submit │ ID │\n", "╞════════╪══════════╪══════════╪══════╡\n", "╘════════╧══════════╧══════════╧══════╛\n" ] } ], "source": [ "from datetime import datetime, timedelta\n", "\n", "# set a date range to find jobs submitted within, in this case jobs submitted today\n", "today = datetime.today()\n", "submit_start = today.strftime(\"%Y%m%d\")\n", "submit_end = (today + timedelta(days=1)).strftime(\"%Y%m%d\")\n", "\n", "# search for jobs that have yet to complete\n", "qmf.show_queue_status(submit_start=submit_start, submit_end=submit_end)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you would like to also see completed jobs, you can pass the include_complete=True option:" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1 job(s) queued:\n", "\n", "╒══════════════════════════╤══════════╤═══════════════════════╤══════════════════════════════════════╕\n", "│ Name │ Status │ Submit │ ID │\n", "╞══════════════════════════╪══════════╪═══════════════════════╪══════════════════════════════════════╡\n", "│ my second quantum matter │ COMPLETE │ 08 May 2024, 14:29:53 │ eb7d0bbe-011f-4c14-888c-44508d3fa6b5 │\n", "╘══════════════════════════╧══════════╧═══════════════════════╧══════════════════════════════════════╛\n" ] } ], "source": [ "# search for jobs submitted today, including those that have already completed\n", "qmf.show_queue_status(\n", " submit_start=submit_start,\n", " submit_end=submit_end,\n", " include_complete=True,\n", " limit=20, # limit the number of results shown (100 max)\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Query your current job quota ###" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "qmf.show_job_limits()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Units ###" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Oqtant uses units that are natural choices for dealing with the quantum matter produced and manipulated by the Oqtant platform. The table below is a summary of relevant units used throughout this and following walkthroughs. Some of these objects/quantities have not yet been encountered, but will be shortly. \n", "\n", "| Quantity | Units | Notes |\n", "|---------------------|-------------------------------|-------------------------------------|\n", "| time | milliseconds (ms, $10^{-3}$ m)| |\n", "| frequency | megahertz (MHz, $10^6$ Hz) | RF knife frequency, relative to the energetic trap bottom, $\\geq 0$ |\n", "| powers | milliwatts (mW, $10^{-3}$ W) | RF knife loop antenna delivered power, $\\geq 0$ | \n", "| temperature | nanokelvin (nK, $10^{-9}$ K) | Target or derived atom temperature |\n", "| barrier height | kilohertz (kHz, $10^{3}$ Hz) | Energetic height (J) / Planck's constant|\n", "| barrier position | microns ($\\mu m$, $10^{-6}$ m)| Barrier center position |\n", "| barrier width | microns ($\\mu m$, $10^{-6}$ m)| Shape-dependent barrier width |\n", "| landscape potential | kilohertz (kHz, $10^{3}$ Hz) | Energetic height (J) / Planck's constant|" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 4 }