For me, symmetry and continuity of prediction are important when dealing with machine learning models. Because even though the position of the ice cube is not symmetrical, the process of generating Cherenkov light will be symmetrical.
\nThe topology of the graph in ICE-Cube will change drastically depending on the scenario in which the neutrinos occur. If the topology changes drastically, the input to the neural network also changes drastically. Then, even if the neural network model is continuous, there is no guarantee that the model's result is continuous. I think that if this continuity is broken, the neural network will overfit in the simulated environment or in the case of one neutrino.
\nOf course, It can be mitigated based on data augmentation (like z-axis rotation) and increase the amount of data. But before that, we need to define the solution space for the model to predict.
\nAs a beginner to this topic, I found it difficult to get a neural network to predict directions. So, I first thought of estimating the particle's position at each moment based on Ice Cube's data. I believe predicting the range of positions is an easier problem than predicting the direction. After predicting the positions of the neutrinos over time, it will be possible to reconstruct the direction of the neutrinos.
\nI.e. I want to approach this problem by estimating the position with uncertainty by combining data from multiple sensors.
I am curious whether the neutrinos' trajectory in an ice cube is a straight line.
", "messages": [ { "id": "2133128", "postDate": "02/07/2023 09:02:23", "content": "For me, symmetry and continuity of prediction are important when dealing with machine learning models. Because even though the position of the ice cube is not symmetrical, the process of generating Cherenkov light will be symmetrical.
\nThe topology of the graph in ICE-Cube will change drastically depending on the scenario in which the neutrinos occur. If the topology changes drastically, the input to the neural network also changes drastically. Then, even if the neural network model is continuous, there is no guarantee that the model's result is continuous. I think that if this continuity is broken, the neural network will overfit in the simulated environment or in the case of one neutrino.
\nOf course, It can be mitigated based on data augmentation (like z-axis rotation) and increase the amount of data. But before that, we need to define the solution space for the model to predict.
\nAs a beginner to this topic, I found it difficult to get a neural network to predict directions. So, I first thought of estimating the particle's position at each moment based on Ice Cube's data. I believe predicting the range of positions is an easier problem than predicting the direction. After predicting the positions of the neutrinos over time, it will be possible to reconstruct the direction of the neutrinos.
\nI.e. I want to approach this problem by estimating the position with uncertainty by combining data from multiple sensors.
I am curious whether the neutrinos' trajectory in an ice cube is a straight line.
", "rawMarkdown": "For me, symmetry and continuity of prediction are important when dealing with machine learning models. Because even though the position of the ice cube is not symmetrical, the process of generating Cherenkov light will be symmetrical.\n\nThe topology of the graph in ICE-Cube will change drastically depending on the scenario in which the neutrinos occur. If the topology changes drastically, the input to the neural network also changes drastically. Then, even if the neural network model is continuous, there is no guarantee that the model's result is continuous. I think that if this continuity is broken, the neural network will overfit in the simulated environment or in the case of one neutrino.\n\nOf course, It can be mitigated based on data augmentation (like z-axis rotation) and increase the amount of data. But before that, we need to define the solution space for the model to predict.\n\nAs a beginner to this topic, I found it difficult to get a neural network to predict directions. So, I first thought of estimating the particle's position at each moment based on Ice Cube's data. I believe predicting the range of positions is an easier problem than predicting the direction. After predicting the positions of the neutrinos over time, it will be possible to reconstruct the direction of the neutrinos.\nI.e. I want to approach this problem by estimating the position with uncertainty by combining data from multiple sensors.\n\nI am curious whether the neutrinos' trajectory in an ice cube is a straight line.", "votes": null }, { "id": "2135118", "postDate": "02/08/2023 13:12:52", "content": "There are two detection methods: neutrino–electron scattering and neutrino reactions on deuterium, in which
\nCherenkov/scintillation light is created by electrons. In the case of scattering, the electron direction is closely correlated with
\nthe direction of the incoming neutrino. But in the case of reactions on deuterium, i have no idea. It depends on energy of neutrino.
\nHope it helps.
If I understand it correctly:
\nA neutrino comes into the observatory and an interaction happens. One of the 2 (or both?) happens:
\nThe trajectory of the neutrino I also believe is a straight line, but, we can't observe that, we can only observe the light generated by the interaction. When a muon is generated, I believe it has the direction of the neutrino.
", "rawMarkdown": "If I understand it correctly:\n\nA neutrino comes into the observatory and an interaction happens. One of the 2 (or both?) happens:\n\n- Cascade-like event: The interaction generates a shower of particles that emits light mostly in the direction that the neutrino was going, but those particles are short-lived, so the light doesn't go far away.\n- Track-like event: The neutrino interacts with an atomic nucleus and this interaction releases a muon. The muon lives long enough, follows a straight line, and emits Cherenkov radiation (that is, it emits light in a cone in the direction that it is going [image](https://en.wikipedia.org/wiki/Cherenkov_radiation#/media/File:Cherenkov.svg)). This light goes directly to the detectors, or it may be scattered.\n\nThe trajectory of the neutrino I also believe is a straight line, but, we can't observe that, we can only observe the light generated by the interaction. When a muon is generated, I believe it has the direction of the neutrino.", "votes": null }, { "id": "2143123", "postDate": "02/14/2023 04:12:48", "content": "We don't see the neutrino but the particles created by the collision. Cylinder, cone or sphere seem to be three shapes of light that can be generated by the particles from the collision.
", "rawMarkdown": "We don't see the neutrino but the particles created by the collision. Cylinder, cone or sphere seem to be three shapes of light that can be generated by the particles from the collision.", "votes": null } ], "comments": [ { "id": 2135118, "author_name": "derkanat", "author_url": "", "post_date": "02/08/2023 13:12:52", "content": "There are two detection methods: neutrino–electron scattering and neutrino reactions on deuterium, in which
\nCherenkov/scintillation light is created by electrons. In the case of scattering, the electron direction is closely correlated with
\nthe direction of the incoming neutrino. But in the case of reactions on deuterium, i have no idea. It depends on energy of neutrino.
\nHope it helps.
If I understand it correctly:
\nA neutrino comes into the observatory and an interaction happens. One of the 2 (or both?) happens:
\nThe trajectory of the neutrino I also believe is a straight line, but, we can't observe that, we can only observe the light generated by the interaction. When a muon is generated, I believe it has the direction of the neutrino.
", "votes": null, "replies": [] }, { "id": 2143123, "author_name": "pcjimmmy", "author_url": "", "post_date": "02/14/2023 04:12:48", "content": "We don't see the neutrino but the particles created by the collision. Cylinder, cone or sphere seem to be three shapes of light that can be generated by the particles from the collision.
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "2133128": "For me, symmetry and continuity of prediction are important when dealing with machine learning models. Because even though the position of the ice cube is not symmetrical, the process of generating Cherenkov light will be symmetrical.\n\nThe topology of the graph in ICE-Cube will change drastically depending on the scenario in which the neutrinos occur. If the topology changes drastically, the input to the neural network also changes drastically. Then, even if the neural network model is continuous, there is no guarantee that the model's result is continuous. I think that if this continuity is broken, the neural network will overfit in the simulated environment or in the case of one neutrino.\n\nOf course, It can be mitigated based on data augmentation (like z-axis rotation) and increase the amount of data. But before that, we need to define the solution space for the model to predict.\n\nAs a beginner to this topic, I found it difficult to get a neural network to predict directions. So, I first thought of estimating the particle's position at each moment based on Ice Cube's data. I believe predicting the range of positions is an easier problem than predicting the direction. After predicting the positions of the neutrinos over time, it will be possible to reconstruct the direction of the neutrinos.\nI.e. I want to approach this problem by estimating the position with uncertainty by combining data from multiple sensors.\n\nI am curious whether the neutrinos' trajectory in an ice cube is a straight line.", "2135118": "There are two detection methods: neutrino–electron scattering and neutrino reactions on deuterium, in which\nCherenkov/scintillation light is created by electrons. In the case of scattering, the electron direction is closely correlated with\nthe direction of the incoming neutrino. But in the case of reactions on deuterium, i have no idea. It depends on energy of neutrino.\nHope it helps.", "2135945": "If I understand it correctly:\n\nA neutrino comes into the observatory and an interaction happens. One of the 2 (or both?) happens:\n\n- Cascade-like event: The interaction generates a shower of particles that emits light mostly in the direction that the neutrino was going, but those particles are short-lived, so the light doesn't go far away.\n- Track-like event: The neutrino interacts with an atomic nucleus and this interaction releases a muon. The muon lives long enough, follows a straight line, and emits Cherenkov radiation (that is, it emits light in a cone in the direction that it is going [image](https://en.wikipedia.org/wiki/Cherenkov_radiation#/media/File:Cherenkov.svg)). This light goes directly to the detectors, or it may be scattered.\n\nThe trajectory of the neutrino I also believe is a straight line, but, we can't observe that, we can only observe the light generated by the interaction. When a muon is generated, I believe it has the direction of the neutrino.", "2143123": "We don't see the neutrino but the particles created by the collision. Cylinder, cone or sphere seem to be three shapes of light that can be generated by the particles from the collision." }, "source": "meta" }