There are three main points summarized:
1. There are many interesting slow radio transients that could be detected through imaging surveys like accretion flares, orphan gamma-ray bursts, and flare stars.
2. Radio surveys are increasing in sensitivity and field of view by orders of magnitude with instruments like LOFAR, enabling the detection of more rare transient events.
3. TraP is a transient detection pipeline that works by extracting sources from radio images, matching to known sources, identifying new bright sources, analyzing light curves, and making the results accessible through a user-friendly web interface.
The document provides an overview of design thinking basics. It defines design using keywords like general concept, action, and plan/intention. Design is described as creating products, systems, or services that satisfy human needs and improve lives while respecting the environment. Designers are paid to envision better futures and make them happen. Design involves imagining what does not yet exist and making it real. It is about making decisions with uncertainty. The document also discusses what design processes are, how they involve steps to achieve goals, and how they are not always linear. It explores the positions of design between art and science.
How to avoid the latency trap and lessons about software designTom Croucher
The document discusses strategies for avoiding the latency trap when designing mobile applications and web services. It recommends reducing the number of requests made to servers by bundling requests and gzipping responses. It also suggests shaping data into packets in a way that minimizes the number of packets, such as ensuring static assets fit into discrete packet boundaries. The document then introduces Yahoo Query Language (YQL) as a way to unify access to web services and bundle requests from mobile devices without needing a dedicated backend. It provides an example of using YQL to search Flickr photos.
Real time extension for 3D-PTV Lagrangian measurements of turbulent canopy fl...Alex Liberzon
Three-dimensional Particle Tracking Velocimetry is the state-of-the-art fluid flow measurement method, providing a unique view into Lagrangian statistics of a turbulent flow in the urban canopy wind tunnel model.
From gamma-ray to radio: Multi-wavelength follow-up in the first five minutesTim Staley
This document summarizes recent work on fast radio follow-up of transient sources and multi-wavelength classification. It discusses three key areas: 1) examples of fast radio follow-up of gamma-ray bursts and stellar flares, 2) using radio and optical measurements to classify transients, and 3) the need to automate "transient triage" to efficiently prioritize follow-up observations across different facilities. The presenter argues that distributing information about new transients via VOEvents can help the community automate real-time classification and prioritization of targets.
Microservices and Teraflops: Effortlessly Scaling Data Science with PyWren wi...Databricks
PyWren is a serverless framework that allows data scientists to easily scale Python code across AWS Lambda. It uses Lambda to parallelize work by mapping Python functions to a large dataset. The functions and data are serialized and uploaded to S3, which then triggers Lambda. Results are stored in S3. This allows data science problems that take minutes or hours to be solved to complete in seconds by parallelizing across thousands of Lambda instances. PyWren aims to abstract away the complexity of serverless infrastructure so data scientists can focus on their code instead of operations.
The document provides an overview of design thinking basics. It defines design using keywords like general concept, action, and plan/intention. Design is described as creating products, systems, or services that satisfy human needs and improve lives while respecting the environment. Designers are paid to envision better futures and make them happen. Design involves imagining what does not yet exist and making it real. It is about making decisions with uncertainty. The document also discusses what design processes are, how they involve steps to achieve goals, and how they are not always linear. It explores the positions of design between art and science.
How to avoid the latency trap and lessons about software designTom Croucher
The document discusses strategies for avoiding the latency trap when designing mobile applications and web services. It recommends reducing the number of requests made to servers by bundling requests and gzipping responses. It also suggests shaping data into packets in a way that minimizes the number of packets, such as ensuring static assets fit into discrete packet boundaries. The document then introduces Yahoo Query Language (YQL) as a way to unify access to web services and bundle requests from mobile devices without needing a dedicated backend. It provides an example of using YQL to search Flickr photos.
Real time extension for 3D-PTV Lagrangian measurements of turbulent canopy fl...Alex Liberzon
Three-dimensional Particle Tracking Velocimetry is the state-of-the-art fluid flow measurement method, providing a unique view into Lagrangian statistics of a turbulent flow in the urban canopy wind tunnel model.
From gamma-ray to radio: Multi-wavelength follow-up in the first five minutesTim Staley
This document summarizes recent work on fast radio follow-up of transient sources and multi-wavelength classification. It discusses three key areas: 1) examples of fast radio follow-up of gamma-ray bursts and stellar flares, 2) using radio and optical measurements to classify transients, and 3) the need to automate "transient triage" to efficiently prioritize follow-up observations across different facilities. The presenter argues that distributing information about new transients via VOEvents can help the community automate real-time classification and prioritization of targets.
Microservices and Teraflops: Effortlessly Scaling Data Science with PyWren wi...Databricks
PyWren is a serverless framework that allows data scientists to easily scale Python code across AWS Lambda. It uses Lambda to parallelize work by mapping Python functions to a large dataset. The functions and data are serialized and uploaded to S3, which then triggers Lambda. Results are stored in S3. This allows data science problems that take minutes or hours to be solved to complete in seconds by parallelizing across thousands of Lambda instances. PyWren aims to abstract away the complexity of serverless infrastructure so data scientists can focus on their code instead of operations.
An Introduction to Reactive Application, Reactive Streams, and options for JVMSteve Pember
The term “reactive” has lately become a buzzword, with a variety of definitions around the Web. When you hear reactive, what do you think of? Reactive Streams? The Reactive Manifesto? ReactJS? These terms may seem unrelated, but they share a common core concept.
Reactive applications and reactive programming result in flexible, concise, performant code and are a superior alternative to the old standard thread-based imperative programming model. The reactive approach has gained popularity recently for one simple reason: we need alternative designs and architectures to meet today’s demands. However, it can be difficult to shift one’s mind to think in reactive terms due to how accustomed we’ve become to the imperative style.
Stephen Pember explores the various definitions of reactive and reactive programming with the goal of providing techniques for building efficient, scalable applications. Steve dives into the key concepts of Reactive Streams and examines some sample implementations—including how ThirdChannel is currently using reactive libraries in production code. Steve looks at some of the open source options available in the JVM—including Reactor, RxJava, and Ratpack—giving attendees an idea of where to begin with the reactive ecosystem. If reactive is new to you, this should be an excellent introduction.
We walk through the steps of building an application with Grakn. We will begin with how to construct a model of the scenario, moving on to talk about how to use reasoning to reach concrete insights, and go further to use Analytics for a deeper understanding of the dataset.
Finally, we will show the specific usefulness of Grakn for applications in planning, logistics and operations, as we create a journey planner to get us from A to B across the London Underground.
Blog post: https://blog.grakn.ai/planning-logistics-and-operations-modelling-the-london-tube-network-in-grakn-7c03baff65c6
Github code: https://github.com/graknlabs/grakn_examples/tree/master/tube_network_example
Reactive Streams and the Wide World of GroovySteve Pember
The concept of Reactive Streams (aka Reactive Extensions, Reactive Functional Programming, or simply Rx) has become increasingly popular recently, and with good reason. The Reactive Streams specification provides a universal abstraction for asynchronously processing data received across multiple sources (e.g. database, user input, third-party services), and includes mechanisms for controlling the rate at which data is received. This makes it a powerful tool within a Microservice platform. And did we mention that the Groovy lang community is quite involved?
In this talk we’ll explore the various features and concepts of Reactive Streams. We’ll talk about some typical use cases for Rx and more importantly, how to implement them. We’ll focus primarily on RxGroovy and Ratpack, then provide example implementations that show you how to get started with this powerful technique.
Simultaneous Localization and Mapping (SLAM) is a technique used by robots and autonomous vehicles to build a map of an unknown environment while simultaneously keeping track of its current location. The SLAM problem involves two key steps - mapping and localization - which are paradoxical, as mapping requires knowing the location and determining the location requires having a map. The SLAM process uses features extracted from sensor data like laser scans to repeatedly update estimates of landmark positions and the robot's location via an Extended Kalman Filter as the robot moves through the environment.
Sante presents ideas they will work on in their new position conducting multidisciplinary studies connecting general relativity and other fields. They discuss IDSS RPS, a generalization of GPS that accounts for relativistic effects without needing continuous broadcasting, prior knowledge of trajectories, or geodesic tracing. They also discuss using metamaterials and analogue transformations to design acoustic devices by mapping acoustic waves in media to relativistic systems, as well as potential applications in other fields like chemistry and aerodynamics. Sante invites those interested to contact them to discuss other related ideas.
Tunable algorithms for transient follow-upTim Staley
This document discusses an approach for optimizing follow-up observations of astronomical transients using Bayesian decision theory. The approach uses transient lightcurve models, telescope noise models, and prior information to calculate the information content of potential future observations. Observations are prioritized based on their expected information content to efficiently classify transients. The presenter outlines the necessary components for a software system to implement this approach, including lightcurve generation, data fitting, calculating confusion matrices, and an observation scheduler. Future work involves integrating these components and testing the system in realistic simulations.
This document describes a project to improve the processing and visualization of weather satellite telemetry data from the Ocean Surface Topography Mission (OSTM) satellites. The current tool (Cyclone) is slow, taking a long time to perform queries and generate graphs from the large dataset. The authors developed a new tool that ingests the data into Elasticsearch using Logstash, then allows users to quickly query and visualize the data in an interactive graph through a custom interface. Benchmarking showed their tool was over 5 times faster than Cyclone. While ingestion is still slow, the visualization component provides a quicker and easier experience to replace Cyclone. Future work could implement Apache Spark to improve the speed of data ingestion.
The document discusses streams and functional programming in JavaScript. It provides three examples of using streams:
1. Playing MP3 files by piping a read stream through a decoder and speaker.
2. Creating a "sound soup" that randomly plays MP3 files from a directory every half second by piping read streams through a decoder and speaker.
3. A brief history of streams in Node.js, from the original Util.pump method to the current Streams API in versions 1-3, highlighting improvements in error handling and backpressure support.
This document summarizes the work done on evaluating pitch trackers for use in machine learning algorithms. The author developed a simple evaluation method that compares the pitch tracker's output to the true pitch at each time sample, and reports the percentage of correct samples. This single performance score is necessary for machine learning. The author implemented this evaluator in MATLAB and could display the pitch tracker output graphically compared to the true pitch. For their composition, the author used a pitch tracker to add harmony by thirds or fourths to live vocal input in the key of C. Completing the evaluator and using it to train a pitch tracker on guitar recordings is proposed for future work.
This document summarizes the work done on developing an evaluator for machine learning of pitch trackers. The evaluator aims to provide a single quantitative measure of a pitch tracker's performance on a sound file by simply tallying the number of correct pitches identified compared to the total number. While not fully completed, the work included reading pitch tracker output into MATLAB and displaying its performance graphically compared to the true pitches. A composition was also created using a pitch tracker to add harmony based on the detected pitch. Future work includes automating the evaluation to train pitch trackers with machine learning.
This document presents a method for detecting hotspots (services responsible for suboptimal performance) in a service-oriented architecture. The method reconstructs service call graphs from logged metrics to identify the top-k services whose optimization would most reduce latency or cost. It proposes quantifying each service's impact and using a greedy algorithm to select services in descending order of impact. Evaluation on a large-scale production dataset found the approach more effective than a baseline and produced consistent results over time, helping engineering teams optimize performance.
The experiment measured the firing rate of neurons in the ventral nerve cord of an anesthetized cockroach when exposed to different sound frequencies, including 200Hz, 400Hz, 600Hz, and an ultrasonic pest repellent of 25,000Hz. Eight trials were conducted for each frequency, and the average firing rate was calculated and statistically analyzed to determine the effect of different sound frequencies on neural activity. Electrodes were used to record extracellular action potentials from neurons and an oscilloscope and statistical tests analyzed the results.
Shen Lu worked on analyzing next generation sequencing data over 14 weeks. The first few weeks were spent adding background knowledge, converting SRA files to FASTQ format using fastq-dump, and performing quality control checks on the raw data using FASTX toolkit and Trimmomatic. Later weeks involved mapping reads to the reference genome using TopHat, Bowtie and Samtools, estimating transcription levels with Cufflinks, using supercomputers to facilitate analysis, and configuring databases to store and visualize the results.
Robust Visual Tracking Based on Sparse PCA-L1csandit
Recently, visual tracking based on sparse principle component analysis has drawn much
research attention. As we all know, principle component analysis (PCA) is widely used in data
processing and dimensionality reduction. But PCA is difficult to interpret in practical
application and all those principal components are linear combinations of all variables. In our
paper, a novel visual tracking method based on sparse principal component analysis and L1
tracking is introduced, which we named the method SPCA-L1 tracking. We firstly introduce
trivial templates of L1 tracking method, which are used to describe noise, into PCA appearance
model. Then we use lasso model to achieve sparse coefficients. Then we update the eigenbasis
and mean incrementally to make the method robust when solving different kinds of changes of
the target. Numerous experiments, where the targets undergo large changes in pose, scale and
illumination, demonstrate the effectiveness and robustness of the proposed method.
Open Annotation in the CHARMe Project for the I Annotate Conference Raquel Alegre
- The document discusses the CHARMe project, which uses open annotation to share knowledge about climate datasets and help users assess their fitness for purpose.
- Open annotation is a natural fit for CHARMe as it allows recording of motivations, tags, and multiple annotation targets.
- CHARMe will create connected repositories of commentary information stored as triples in "CHARMe nodes" that can be accessed through websites or services.
- Some advanced use cases for annotating climate data include discussing the timing of events, tracing plankton blooms, and identifying features in subsets of multidimensional climate datasets.
PDFs at the LHC: Lessons from Run I and preparation for Run IIjuanrojochacon
This document summarizes parton distribution functions (PDFs) at the start of LHC Run II. It discusses the status of recent PDF sets from NNPDF, MMHT, CT, ABM, and HERAPDF. It notes some differences between these sets and the importance of PDF uncertainties for LHC measurements. The document also discusses benchmarks between PDF sets, comparisons using the APFEL online tool, and the prospects for including more ATLAS data in global PDF fits to further constrain PDFs.
This document provides an overview of particle accelerators. It notes that there are over 30,000 accelerators worldwide used for research, medicine, and industry. Accelerators are used to produce beams of particles like electrons and ions that act as probes for scientific research. Examples of applications mentioned include medical isotopes and radiation therapy, material modification and analysis using synchrotron light sources, and particle physics research using large facilities like CERN. The document aims to give the reader a broad introduction to the field of accelerators and their diverse applications.
This document discusses using Lisp for practical natural language processing (NLP). It begins with an overview of NLP practice, including research work like setting goals, devising algorithms, training models, and testing accuracy. It then discusses some pros and cons of using Lisp for NLP, including its support for interactivity, mathematical foundations, and tree structures. Examples are given of interactive Lisp programs and APIs. The document emphasizes that data is key for NLP and discusses sources for collecting data. It concludes that Lisp is well-suited for NLP research and development due to its interactive and flexible nature.
Which transient when? - A utility function for transient follow-up schedulingTim Staley
Next-generation astronomical facilities such as the LSST and the SKA will be game-changers, allowing us to observe the entire southern sky and track changing sources in near real-time. Keeping up with their alert-streams represents a significant challenge - how do we make the most of our limited telescope resources to follow up 100000 sources per night?
The biggest problem here is classification - we want to find the really interesting transients and spend our time watching those. However, classification based on the initial survey data can only get you so far - we'll need to use robotic follow-up telescopes for rapid-response observations, to give us more information on the most promising targets. To get the most science done, we need to be smart about scheduling that follow-up.
We're exploring use of active learning algorithms (AKA Bayesian Decision Theory) to solve this problem, building a framework that allows for iterative refinement of a probabilistic classification state. Because there are no algorithms that fit this problem 'out-of-the-box', we've built our own analysis framework using the emcee and PyMultiNest packages to power the underlying Bayesian inference. I'll give an overview of how our proposed system fits into the wider context of an automated astronomy ecosystem, then give a gentle introduction to Bayesian Decision Theory and how it can be applied to this problem.
A brief introduction to version control systemsTim Staley
This is a lunchtime talk I gave to the Southampton astronomy department. The aim was to make them aware of version control systems and when they might need to use them.
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An Introduction to Reactive Application, Reactive Streams, and options for JVMSteve Pember
The term “reactive” has lately become a buzzword, with a variety of definitions around the Web. When you hear reactive, what do you think of? Reactive Streams? The Reactive Manifesto? ReactJS? These terms may seem unrelated, but they share a common core concept.
Reactive applications and reactive programming result in flexible, concise, performant code and are a superior alternative to the old standard thread-based imperative programming model. The reactive approach has gained popularity recently for one simple reason: we need alternative designs and architectures to meet today’s demands. However, it can be difficult to shift one’s mind to think in reactive terms due to how accustomed we’ve become to the imperative style.
Stephen Pember explores the various definitions of reactive and reactive programming with the goal of providing techniques for building efficient, scalable applications. Steve dives into the key concepts of Reactive Streams and examines some sample implementations—including how ThirdChannel is currently using reactive libraries in production code. Steve looks at some of the open source options available in the JVM—including Reactor, RxJava, and Ratpack—giving attendees an idea of where to begin with the reactive ecosystem. If reactive is new to you, this should be an excellent introduction.
We walk through the steps of building an application with Grakn. We will begin with how to construct a model of the scenario, moving on to talk about how to use reasoning to reach concrete insights, and go further to use Analytics for a deeper understanding of the dataset.
Finally, we will show the specific usefulness of Grakn for applications in planning, logistics and operations, as we create a journey planner to get us from A to B across the London Underground.
Blog post: https://blog.grakn.ai/planning-logistics-and-operations-modelling-the-london-tube-network-in-grakn-7c03baff65c6
Github code: https://github.com/graknlabs/grakn_examples/tree/master/tube_network_example
Reactive Streams and the Wide World of GroovySteve Pember
The concept of Reactive Streams (aka Reactive Extensions, Reactive Functional Programming, or simply Rx) has become increasingly popular recently, and with good reason. The Reactive Streams specification provides a universal abstraction for asynchronously processing data received across multiple sources (e.g. database, user input, third-party services), and includes mechanisms for controlling the rate at which data is received. This makes it a powerful tool within a Microservice platform. And did we mention that the Groovy lang community is quite involved?
In this talk we’ll explore the various features and concepts of Reactive Streams. We’ll talk about some typical use cases for Rx and more importantly, how to implement them. We’ll focus primarily on RxGroovy and Ratpack, then provide example implementations that show you how to get started with this powerful technique.
Simultaneous Localization and Mapping (SLAM) is a technique used by robots and autonomous vehicles to build a map of an unknown environment while simultaneously keeping track of its current location. The SLAM problem involves two key steps - mapping and localization - which are paradoxical, as mapping requires knowing the location and determining the location requires having a map. The SLAM process uses features extracted from sensor data like laser scans to repeatedly update estimates of landmark positions and the robot's location via an Extended Kalman Filter as the robot moves through the environment.
Sante presents ideas they will work on in their new position conducting multidisciplinary studies connecting general relativity and other fields. They discuss IDSS RPS, a generalization of GPS that accounts for relativistic effects without needing continuous broadcasting, prior knowledge of trajectories, or geodesic tracing. They also discuss using metamaterials and analogue transformations to design acoustic devices by mapping acoustic waves in media to relativistic systems, as well as potential applications in other fields like chemistry and aerodynamics. Sante invites those interested to contact them to discuss other related ideas.
Tunable algorithms for transient follow-upTim Staley
This document discusses an approach for optimizing follow-up observations of astronomical transients using Bayesian decision theory. The approach uses transient lightcurve models, telescope noise models, and prior information to calculate the information content of potential future observations. Observations are prioritized based on their expected information content to efficiently classify transients. The presenter outlines the necessary components for a software system to implement this approach, including lightcurve generation, data fitting, calculating confusion matrices, and an observation scheduler. Future work involves integrating these components and testing the system in realistic simulations.
This document describes a project to improve the processing and visualization of weather satellite telemetry data from the Ocean Surface Topography Mission (OSTM) satellites. The current tool (Cyclone) is slow, taking a long time to perform queries and generate graphs from the large dataset. The authors developed a new tool that ingests the data into Elasticsearch using Logstash, then allows users to quickly query and visualize the data in an interactive graph through a custom interface. Benchmarking showed their tool was over 5 times faster than Cyclone. While ingestion is still slow, the visualization component provides a quicker and easier experience to replace Cyclone. Future work could implement Apache Spark to improve the speed of data ingestion.
The document discusses streams and functional programming in JavaScript. It provides three examples of using streams:
1. Playing MP3 files by piping a read stream through a decoder and speaker.
2. Creating a "sound soup" that randomly plays MP3 files from a directory every half second by piping read streams through a decoder and speaker.
3. A brief history of streams in Node.js, from the original Util.pump method to the current Streams API in versions 1-3, highlighting improvements in error handling and backpressure support.
This document summarizes the work done on evaluating pitch trackers for use in machine learning algorithms. The author developed a simple evaluation method that compares the pitch tracker's output to the true pitch at each time sample, and reports the percentage of correct samples. This single performance score is necessary for machine learning. The author implemented this evaluator in MATLAB and could display the pitch tracker output graphically compared to the true pitch. For their composition, the author used a pitch tracker to add harmony by thirds or fourths to live vocal input in the key of C. Completing the evaluator and using it to train a pitch tracker on guitar recordings is proposed for future work.
This document summarizes the work done on developing an evaluator for machine learning of pitch trackers. The evaluator aims to provide a single quantitative measure of a pitch tracker's performance on a sound file by simply tallying the number of correct pitches identified compared to the total number. While not fully completed, the work included reading pitch tracker output into MATLAB and displaying its performance graphically compared to the true pitches. A composition was also created using a pitch tracker to add harmony based on the detected pitch. Future work includes automating the evaluation to train pitch trackers with machine learning.
This document presents a method for detecting hotspots (services responsible for suboptimal performance) in a service-oriented architecture. The method reconstructs service call graphs from logged metrics to identify the top-k services whose optimization would most reduce latency or cost. It proposes quantifying each service's impact and using a greedy algorithm to select services in descending order of impact. Evaluation on a large-scale production dataset found the approach more effective than a baseline and produced consistent results over time, helping engineering teams optimize performance.
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Robust Visual Tracking Based on Sparse PCA-L1csandit
Recently, visual tracking based on sparse principle component analysis has drawn much
research attention. As we all know, principle component analysis (PCA) is widely used in data
processing and dimensionality reduction. But PCA is difficult to interpret in practical
application and all those principal components are linear combinations of all variables. In our
paper, a novel visual tracking method based on sparse principal component analysis and L1
tracking is introduced, which we named the method SPCA-L1 tracking. We firstly introduce
trivial templates of L1 tracking method, which are used to describe noise, into PCA appearance
model. Then we use lasso model to achieve sparse coefficients. Then we update the eigenbasis
and mean incrementally to make the method robust when solving different kinds of changes of
the target. Numerous experiments, where the targets undergo large changes in pose, scale and
illumination, demonstrate the effectiveness and robustness of the proposed method.
Open Annotation in the CHARMe Project for the I Annotate Conference Raquel Alegre
- The document discusses the CHARMe project, which uses open annotation to share knowledge about climate datasets and help users assess their fitness for purpose.
- Open annotation is a natural fit for CHARMe as it allows recording of motivations, tags, and multiple annotation targets.
- CHARMe will create connected repositories of commentary information stored as triples in "CHARMe nodes" that can be accessed through websites or services.
- Some advanced use cases for annotating climate data include discussing the timing of events, tracing plankton blooms, and identifying features in subsets of multidimensional climate datasets.
PDFs at the LHC: Lessons from Run I and preparation for Run IIjuanrojochacon
This document summarizes parton distribution functions (PDFs) at the start of LHC Run II. It discusses the status of recent PDF sets from NNPDF, MMHT, CT, ABM, and HERAPDF. It notes some differences between these sets and the importance of PDF uncertainties for LHC measurements. The document also discusses benchmarks between PDF sets, comparisons using the APFEL online tool, and the prospects for including more ATLAS data in global PDF fits to further constrain PDFs.
This document provides an overview of particle accelerators. It notes that there are over 30,000 accelerators worldwide used for research, medicine, and industry. Accelerators are used to produce beams of particles like electrons and ions that act as probes for scientific research. Examples of applications mentioned include medical isotopes and radiation therapy, material modification and analysis using synchrotron light sources, and particle physics research using large facilities like CERN. The document aims to give the reader a broad introduction to the field of accelerators and their diverse applications.
This document discusses using Lisp for practical natural language processing (NLP). It begins with an overview of NLP practice, including research work like setting goals, devising algorithms, training models, and testing accuracy. It then discusses some pros and cons of using Lisp for NLP, including its support for interactivity, mathematical foundations, and tree structures. Examples are given of interactive Lisp programs and APIs. The document emphasizes that data is key for NLP and discusses sources for collecting data. It concludes that Lisp is well-suited for NLP research and development due to its interactive and flexible nature.
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Which transient when? - A utility function for transient follow-up schedulingTim Staley
Next-generation astronomical facilities such as the LSST and the SKA will be game-changers, allowing us to observe the entire southern sky and track changing sources in near real-time. Keeping up with their alert-streams represents a significant challenge - how do we make the most of our limited telescope resources to follow up 100000 sources per night?
The biggest problem here is classification - we want to find the really interesting transients and spend our time watching those. However, classification based on the initial survey data can only get you so far - we'll need to use robotic follow-up telescopes for rapid-response observations, to give us more information on the most promising targets. To get the most science done, we need to be smart about scheduling that follow-up.
We're exploring use of active learning algorithms (AKA Bayesian Decision Theory) to solve this problem, building a framework that allows for iterative refinement of a probabilistic classification state. Because there are no algorithms that fit this problem 'out-of-the-box', we've built our own analysis framework using the emcee and PyMultiNest packages to power the underlying Bayesian inference. I'll give an overview of how our proposed system fits into the wider context of an automated astronomy ecosystem, then give a gentle introduction to Bayesian Decision Theory and how it can be applied to this problem.
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This is a lunchtime talk I gave to the Southampton astronomy department. The aim was to make them aware of version control systems and when they might need to use them.
Training your astronomy robots to work as a teamTim Staley
I present a case that the astronomy community is missing a part of the puzzle for the next era of automated big-survey astronomy: we currently have very little published work on target prioritization and optimized observation scheduling. I discuss the sociological issues surrounding the sort of open collaboration needed to make optimal use of globally distributed observatories, and show some preliminary work on generally-applicable classification methods.
An invited talk given to an audience interested in using lucky imaging for microlensing studies. I tried to give an overview of where the challenges lie in getting good science data using lucky imaging techniques.
Lucky imaging - Life in the visible after HSTTim Staley
This document discusses using lucky imaging techniques to improve spatial resolution in astronomy. Standard lucky imaging can select the best frames from thousands taken at high speed to achieve near-diffraction limited resolution on ground-based telescopes. When combined with adaptive optics, lucky imaging can further improve resolution and help expand the sky coverage of AO. Potential applications include exoplanet imaging, resolving close binary stars, and probing binarity in globular cluster cores.
PPT on Direct Seeded Rice presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Authoring a personal GPT for your research and practice: How we created the Q...Leonel Morgado
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
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Slides from talk:
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https://www.etran.rs/2024/en/home-english/
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The cost of acquiring information by natural selectionCarl Bergstrom
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...Advanced-Concepts-Team
Presentation in the Science Coffee of the Advanced Concepts Team of the European Space Agency on the 07.06.2024.
Speaker: Diego Blas (IFAE/ICREA)
Title: Gravitational wave detection with orbital motion of Moon and artificial
Abstract:
In this talk I will describe some recent ideas to find gravitational waves from supermassive black holes or of primordial origin by studying their secular effect on the orbital motion of the Moon or satellites that are laser ranged.
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...AbdullaAlAsif1
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
How to build a TraP: An image-plane transient-discovery tool
1. How to build a TraP
An image-plane transient-finding pipeline
Tim Staley
& TraP contributors.
Lunchtime talk, Southampton, Jan 2015
WWW: 4pisky.org , timstaley.co.uk/talks
2. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Outline
’Slow’ radio transients
How TraP works
How do I use it?
Future work
Summary
3. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
What are we missing?
Image surveys are best for finding
‘slow’ transients
i.e. > 1 second timescale —
excludes regular pulsars, etc.
Such as. . .
4. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
What are we missing?
Accretion flares
Artist’s impression of the microquasar GRO J1655-40. Image credit: NASA/STScI
5. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
What are we missing?
‘Orphan’ gamma-ray burst afterglows
Image credit: NASA’s Goddard Space Flight Center
e.g. Ghirlanda 2014, http://adsabs.harvard.edu/abs/2014PASA...31...22G
6. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
What are we missing?
Flare-star events
Image credit: Casey Reed/NASA
e.g. Osten 2010, http://ukads.nottingham.ac.uk/abs/2010ApJ...721..785O
7. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
What are we missing?
Image surveys are best for finding ’slow’, i.e. > 1
second timescale transients (excludes regular pulsars,
etc).
AGN tidal disruption events
Compact-object binary flares
Orphan gamma-ray bursts
Flare stars
Nulling and eclipsing pulsars (e.g. J. Broderick et al,
in press)
(The unknown?)
8. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Proof of concept: ALARRM
AMI-LA Rapid Response Mode
Staley 2013, http://ukads.nottingham.ac.uk/abs/2013MNRAS.428.3114S
9. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
GRB140327A
Anderson 2014, http://adsabs.harvard.edu/abs/2014MNRAS.440.2059A
van der Horst 2014, http://adsabs.harvard.edu/abs/2014MNRAS.444.3151V
10. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
DG CVn M-dwarf superflare
Fender 2014, http://adsabs.harvard.edu/abs/2014arXiv1410.1545F
Osten et al (in prep)
11. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
So:
Radio transients are out there.
How do we find them directly?
12. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Bigger fields of view
(Green = AMI-LA FoV)
13. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Bigger fields of view
14. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Bigger fields of view
LOFAR-RSM footprint
15. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
The LOFAR ‘Radio Sky Monitor’
Eight 7-beam tiles in LBAs tiles out entire zenith strip
(∼ 1800deg2
/ ∼ 1
4
hemisphere)
Sixteen 7-beam tiles in HBAs for a narrower strip
(∼ 1000deg2
)
16. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Mini-summary
There are interesting radio-transients
waiting.
Radio sensitivity / field of view is
increasing by orders of magnitude.
17. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Mini-summary
There are interesting radio-transients
waiting.
Radio sensitivity / field of view is
increasing by orders of magnitude.
=⇒ Many uninteresting pixels, and a
few exciting rare events.
=⇒ We need tools to search this data.
18. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Outline
’Slow’ radio transients
How TraP works
How do I use it?
Future work
Summary
19. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 1: PySE
Python Source Extractor - Loosely based around
S-Extractor algorithms, but tuned for radio data.
Written solely in Python (extensive use of Numpy).
20. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Sourcefinding algorithms
An illustration of the island deblending method pioneered by
S-Extractor (Bertin et al 1996).
21. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 2: Load ‘extractedsources’ into SQL
database
NB: Store extractions without cross-matching initially.
22. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Brief aside on SQL
23. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Brief aside on SQL
SQL is almost always the most efficient tool for
searching large, well-parsed datasets.
Are astronomers missing out?
24. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 3: Cross-match with known sources
a.k.a. ‘association’
First calculate DeRuiter radius for candidate
associations:
i
j
αij
ij
α,i
,i
rj =
(Δαj)2
σ2
α, + σ2
α,j
+
(Δδj)2
σ2
δ, + σ2
δ,j
25. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 3: Cross-match with known sources
a.k.a. ‘association’
First calculate DeRuiter radius for candidate
associations:
i
j
αij
ij
α,i
,i
rj =
(Δαj)2
σ2
α, + σ2
α,j
+
(Δδj)2
σ2
δ, + σ2
δ,j
Handling meridian-wrap, celestial poles, left as exercise
to reader.
26. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 3: Cross-match with known sources
a.k.a. ‘association’
Mostly we just pick the closest match, and everything
works out fine. But we also try to deal with some
variable-PSF issues:
27. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify bright new transients
The problem:
One of the neat features of TraP is that we can tell
immediately when a bright new source appears. This
may sound trivial initially, but...
28. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify bright new transients
The problem:
One of the neat features of TraP is that we can tell
immediately when a bright new source appears. This
may sound trivial initially, but...
29. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify new sources
Tracking fields of view
30. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify new sources
Tracking detection limits
0 1 2 3 4 5 6
Epoch
3
4
5
6
7
8
Flux
31. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify new sources
Tracking detection limits
0 1 2 3 4 5 6
Epoch
3
4
5
6
7
8
Flux
32. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify new sources
Tracking detection limits
0 1 2 3 4 5
Epoch
3
4
5
6
7
8
Flux
33. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify new sources
Tracking detection limits
0 1 2 3 4 5
Epoch
3
4
5
6
7
8
Flux
34. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify new sources
Tracking detection limits
0 1 2 3 4 5
Epoch
3
4
5
6
7
8
Flux
35. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 4: Identify new sources
Tracking detection limits
0 1 2 3 4 5
Epoch
3
4
5
6
7
8
Flux
36. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 5: Force measurement of any
missing known sources
0 1 2 3 4 5 6
Epoch
3
4
5
6
7
8
Flux
37. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 5: Force measurement of any
missing known sources
0 1 2 3 4 5 6
Epoch
3
4
5
6
7
8
Flux
38. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 6: Analyse lightcurves
We keep a running aggregate (i.e. only need to include
additional data, no recalculation of previous timesteps)
for:
Regular and weighted mean fluxes, μ & ξ
ξN+1 =
WN ξN + N+1 N+1
WN + N+1
(1)
(2)
39. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Step 6: Analyse lightcurves
We keep a running aggregate (i.e. only need to include
additional data, no recalculation of previous timesteps)
for:
Regular and weighted mean fluxes, μ & ξ
ξN+1 =
WN ξN + N+1 N+1
WN + N+1
(1)
(2)
‘Coefficient of variation’, V = σ/μ
Calculate reduced χ-squared value (η), against fit
to straight line at level of weighted-mean ξ.
40. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Outline
’Slow’ radio transients
How TraP works
How do I use it?
Future work
Summary
41. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Installation
TraP can be run on a laptop. But . . .
Makes heavy use of SQL database (most
astronomers not familiar)
Expected to be run on large datasets
42. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Installation
TraP can be run on a laptop. But . . .
Makes heavy use of SQL database (most
astronomers not familiar)
Expected to be run on large datasets
Solution: Web-interface. Displays data in
user-friendly fashion, works extremely well in
server-client model.
44. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Development
Facts
∼20,000 lines of code, ∼350 unit tests, 26K lines of
docs
4 core developers, plus ∼4 testers, 3 continents
Remote, collaborative, development model
Issue tracking
Open (going forward)
45. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Development
Implications
( / Ruminations)
Astronomy –> More software intensive
Getting anything done requires better code re-use
Core software efforts are larger, require ongoing
effort from many contributors.
(cf http://astropy.org!)
46. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Development
Implications
( / Ruminations)
Astronomy –> More software intensive
Getting anything done requires better code re-use
Core software efforts are larger, require ongoing
effort from many contributors.
(cf http://astropy.org!)
You don’t have to be part of it, but, you should be
aware of it
Get to know the latest tools, maybe submit a bugfix
here and there if you can
Do better science, faster (hopefully!)
47. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Outline
’Slow’ radio transients
How TraP works
How do I use it?
Future work
Summary
48. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Different approaches
Two main approaches to image-based transient
surveys:
Cataloguing: Extract source representations, store
in database, analyze lightcurve catalogue.
Difference image analysis a.k.a. image subtraction
49. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Lightcurve cataloguing
Basic concept easily understood - ‘just’ glue
together source extraction and lightcurve analysis.
However, blind source extraction typically requires
good signal to noise - will miss marginal sources.
Crowded fields are also a problem.
50. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Difference image analysis
Better at picking out faint sources in clean data,
much better in crowded fields.
Alard & Lupton 1997, http://adsabs.harvard.edu/abs/1998ApJ...503..325A
Wyrzykowski et al, 2014, http://adsabs.harvard.edu/abs/2014AcA....64..197W
51. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Optical survey characteristics
Which technique should we employ?
Most transient surveys to date are optical:
Fields often crowded or even confusion limited
(best places to look for stellar flares, microlensing)
PSF usually quite well behaved (smooth)
Pixel noise usually uncorrelated / varies on a
different scale to the PSF (dependent on sampling)
=⇒ DIA is usually best approach.
52. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Radio survey characteristics:
(Contrast with optical)
Fields usually quite sparsely populated, at least
with current generation of instruments.
Noise is correlated on beam-width scale.
Dirty beam / PSF may vary significantly from image
to image. May be well modelled, but this depends
on system characterisation.
(Phased arrays e.g. LOFAR) May see artifacts due to
side lobes from out-of-field bright sources.
=⇒ DIA would cause many false positives, better
to stick to high SNR cataloguing.
53. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Outline
’Slow’ radio transients
How TraP works
How do I use it?
Future work
Summary
54. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Summary
TraP:
Good for (wide-field) sparsely populated surveys.
Can be used for real-time transient detection.
Produces catalogue of all sources.
55. ’Slow’ radio transients How TraP works How do I use it? Future work Summary
Summary
TraP:
Good for (wide-field) sparsely populated surveys.
Can be used for real-time transient detection.
Produces catalogue of all sources.
Server-based / web-interface reduction model well
suited to large, challenging datasets.
Open-source Python / SQL, with comprehensive
test-suite and documentation.
http://ascl.net/1412.011