KM3NeT - Research

Blog for highlights during day-to-day KM3NeT research activities such as pitches for new papers, talks and posters during international conferences and (internal) workshops, comments on events in astroparticle physics and particle physics etc.

KM3NeT at ICRC2021

29 July 2021 – The International Cosmic Ray Conference (ICRC) has come to an end after two intense weeks.

The biannual conference organised under auspices of IUPAP, the International Union of Pure and Applied Physics. This year, the 37th edition of the conference was organised as an online version by DESY Zeuthen in Germany. The KM3NeT Collaboration participated in the conference with many contributions accepted by the International Science Committee of the conference.

Paschal Coyle, Spokesperson of the KM3NeT Collaboration, was invited to present a review talk on underwater neutrino telescopes, including obviously KM3NeT, but also its older sister ANTARES, the GVD telescope in Lake Baikal in Siberia, Russia and the new initiative P-ONE offshore the coast of Canada in the Pacific Ocean:

   

Five more talks covered the very first results obtained with ORCA and ARCA, as well as the prospects for neutrino oscillation measurements and mass ordering determination. With only 6 detection units ARCA6 sees candidates for atmospheric neutrinos; with only 6 detection units ORCA6 sees the effect of oscillation:

In addition, more than 20 poster contributions were presented by the members of our Collaboration. Among them, Thijs van Eden and Jordan Seneca, two PhD students at Nikhef, Amsterdam, who were awarded the best poster prize for their contribution discussing reconstruction of single and double cascade in KM3NeT. Congratulations Thijs and Jordan!

  

 

New publication: Neutrino Mass Ordering and Oscillation Parameters

05 May 2021 – The potential of KM3NeT to measure key properties of neutrinos – in March 2021, the KM3NeT Collaboration released a publication showing that  KM3NeT with its ORCA detector will be in an excellent position to study the phenomenon of neutrino oscillations!

Three neutrino flavours and oscillation

Neutrinos come in three species called flavours: the electron neutrino, the muon neutrino, and the tau neutrino. In the 1960’s, the first experiment was started to study the sun by measuring the flux of electron neutrinos that the solar nuclear processes copiously produce. The experiment revealed that the flux was inconsistent with the expectations! Many solutions were put forward to explain the discrepancy until a measurement of the flux of neutrinos of all three flavours was made and found compatible with the expectation. This key measurement meant that the expectations for the neutrino flux produced by the sun were correct and that the electron neutrinos were converted into other flavours while traveling to Earth. This phenomenon is called neutrino oscillation, subsequently detected also in other contexts. This phenomenon is only explained by quantum mechanics and requires that the neutrinos, initially thought massless, are actually massive!

Neutrino admixture

The neutrinos with definite masses happen to be different from the neutrinos with definite flavours. In other words, a neutrino of a given flavour is an admixture of the neutrinos of definite mass as shown in the top part of fig:1. Because of the mass difference between the neutrino mass states, these states do not propagate at the same velocity. As a result, the neutrino admixture evolves during the propagation, as shown in the bottom part of fig:1. In other words, while propagating, the neutrino flavour changes.

 

Figure 1: Top:the mass state admixtures corresponding to the flavour (so-called weak) states for 2 neutrinos. Middle: a muon neutrino is produced at t=0. As time goes, the neutrino mixture varies reaching periodically a pure muon neutrino state. The probability for the neutrino to be detected in each flavour is represented at the bottom. Reproduced from Slansky et al. Los Alamos Sci. 25 (1997) pp. 28-63.

Using atmospheric neutrinos

The KM3NeT Collaboration aims to study this oscillation phenomenon using neutrinos produced in the collisions of cosmic rays onto the atmosphere. Using these neutrinos, the KM3NeT Collaboration will be able to measure one of the key parameters ruling the neutrino admixture: the so-called θ23 mixing angle. We will also be able to measure the squared mass difference between two of the neutrino mass states – δm232 – and to tell which of the three mass states is the heaviest, i.e. determining the neutrino mass ordering as shown in fig:2. Finally, we will check if the standard three neutrino oscillation paradigm is valid by measuring the fraction of cosmic-ray induced neutrinos that have oscillated to the tau neutrino.

Figure 2: Sensitivity to neutrino mass ordering as a function of data taking time for both normal (red upward pointing triangles) and inverted ordering (blue downward pointing triangles). See the paper for more details and the values of the oscillation parameters considered to obtain the result.

Unique potential

The publication relies on precise simulations to determine the sensitivity of the KM3NeT/ORCA detector to these parameters. The prospects show that the experiment has a unique ability to make these measurements and that world best results can be obtained in few years of data taking with the full detector.

The publication has been submitted to EPJ-C and is available as a pre-print as arXiv:2103.09885.

 

New publication:  core-collapse supernova explosions

11 March 2021 – In February 2021, the KM3NeT Collaboration released a publication describing the potential of KM3NeT to detect low-energy neutrinos from a future core-collapse supernova. The publication is submitted to the European Physical Journal  C.

What is a core-collapse supernova?

Core-collapse supernovae  are very energetic explosions that can end the life of massive stars. They have the peculiar feature of releasing about 99% of their energy as a huge flux of low-energy neutrinos. The neutrinos can escape the stellar core carrying information on the physical processes at play in the collapse, when the star is still opaque to light.

How well can KM3NeT observe a core-collapse supernova?

Thanks to the technology of KM3NeT based on the multifaceted modules with light sensors the KM3NeT detectors are particularly sensitive to the low-energy neutrinos from a supernova.  In the publication it is shown that KM3NeT  – when finished building the detectors –  can reach a 5 sigma discovery potential to observe a core-collapse supernova happening in the Milky Way. For the most optimistic theoretical models describing core-collapse supernovae, the detection threshold can extend up to the Large Magellanic Cloud.

The potential sensitivity of the KM3NeT detectors with 230 detection units in the ARCA detector and 115 units in the ORCA detector as a function of distance of the core-collapsed supernova. Curves are shown for three different masses of the progenitors.

Details

Once a core-collapsed supernova is observed, researchers of KM3NeT can study aspects of the neutrino emission such as the detected neutrino light curve and the neutrino spectrum. This will provide the potential for discrimination between different theoretical models of core-collapse supernovae and help to understand the physical processes behind the explosion mechanism. The time of arrival of the neutrino signal can be determined with an accuracy better than 10 ms for a source at the Galactic Center. The oscillating signature of hydrodynamical instabilities and other physical processes impacting the neutrino time profile can also be detected for nearby events: 3 sigma at 3-8 kpc, depending on the model. From the recorded coincidences, KM3NeT will be able to infer the properties of the neutrino spectrum, estimating the mean neutrino energy with a precision of about 2% if the other spectral parameters such as the energy scale and pinching parameter are known with a small uncertainty.

Neutrino light curves expected using the future full ARCA detector of 230 detection units, from a core-collapse supernova at a distance of 5 kpc and a progenitor of 27 solar masses.

What is possible with the current six detection units of the ORCA detector?

Already with the six detection units of the ORCA detector currently taking data, a detection at 5 sigma level of a core-collapse supernova can be achieved for supernovae at distances up to 10 kpc. The online analysis pipeline is in place, sending warning messages to SNEWS  – the worldwide network  for early warning for supernova events. The first MeV neutrino follow-ups of warnings by gravitational-wave detectors were performed using the data of only four ORCA detection detection units  that were active at that time, bringing the first KM3NeT physics results.

 

Exciting times are ahead. KM3NeT is ready for the observation of the next core-collapse supernova event in our Galaxy!

New paper: Deep-sea deployment of the KM3NeT neutrino telescope detection units by self-unrolling

20 November 2020 – The KM3NeT Collaboration has published a new paper, in which we describe in detail the innovative deployment method for KM3NeT detection units.

No standard moorings

A custom design was necessary, because the KM3NeT mooring – the detection unit -is different from moorings typically used for oceanography.

For instance, in KM3NeT moorings the instrumentation is contained in transparent and thus unprotected glass spheres. That makes them vulnerable during deployment. Moreover, we use a long, thin and soft tube with optical fibres and thin copper wires for data transmission and electrical power for the instruments. That makes the units even more vulnerable.

On top of that, because we use thin Dyneema ropes as strength members in stead of a standard steel cable the mooring is not strong enough to carry the weight of the anchor during deployment.

All this makes it more difficult to deploy the unit without breaking it and we needed a customised deployment method.

Different from other telescopes

Compared to other neutrino telescopes such as ANTARES in the Mediterranean Sea and GVD in Lake Baikal, we designed the KM3NeT detection unit even more slender to minimise the amount of material used for support of the sensor modules. An other – economical – difference is that we have to deploy hundreds of units more for KM3NeT in a period of a few years while keeping the costs for sea operations at a minimum. These are even more reasons for innovation of the deployment method.

The LOM

We developed a custom-made, fast deployment method. Despite the length of the detection unit of several hundreds of metres, we managed to compact it into a small, re-usable spherical launching vehicle instead of deploying it weight down from a surface vessel – the standard method in oceanography. We dubbed the vehicle LOM for Launcher of Optical Modules.

The tric

Once the LOM has reached the seafloor, the innovative tric begins. The buoyant LOM rolls upwards along the Dyneema ropes. While doing so, it spits out the glass spheres with instrumentation attached to the ropes. As a result, while floating to the surface, the LOM leaves the detection unit behind at the seabed, unfurled to its full vertical length. Ready for data taking during many years to come.

Cost effective

The LOM has two economical advantages. First, it does not take a lot in space. Therefore, during a sea operation many LOMs can be stored on deck of a ship. Secondly, we can lower the LOM to the seabed at high speed. As a result, we need less expensive ship time for the installation of the KM3NeT telescope.

Cooperation

As far as we know, the method of compact deployment of moorings with a LOM is unique. The method is the result of close cooperation between engineers and scientists in the KM3NeT Collaboration from both oceanographic and astrophysics institutes. We hope it will inspire oceanographic scientists for the design and deployment of their future moorings.

Details

In the paper, we describe the details of the design of the LOM, the loading with a detection unit, and its underwater self-unrolling. You find the reference below.

LOM in pictures

Pictures below reflect the  process from idea to realisation. First an impression of the initial ideas for deployment by @Marijn van der Meer/Quest. Followed by the technical design of the KM3NeT detection units that must be installed and the design of the LOM launcher vehicle. Finally, photos of the first prototype of the LOM and the final version that is now regularly used for the installation of the detection units of the ARCA and ORCA detectors of the KM3NeT telescope.

 


 

Reference

Deep-sea deployment of the KM3NeT neutrino telescope detection units by self-unrolling

The KM3NeT Collaboration: S. Aiello et al 

2020 JINST 15 P11027

https://doi.org/10.1088/1748-0221/15/11/P11027

New paper: Using convolutional neural networks for event reconstruction for ORCA

12 October 2020 – The KM3NeT Collaboration has published a new paper that aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided.

The conclusion is that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.

 

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT Collaboration, S. Aiello et al

2020 JINST 15 P10005 

https://doi.org/10.1088/1748-0221/15/10/P10005

 

New paper: gSeaGen software tool

13 July 2020 – The KM3NeT Collaboration has published the details of gSeaGen, a simulation software package for efficient generation of neutrino events for the analysis of  measured light signals in the KM3NeT telescopes.  Monte Carlo simulations play an important role in the data analysis of neutrino telescopes. They are used to design reconstruction algorithms for neutrino events and to estimate cosmic and atmospheric signals in various physics analyses.

The new gSeaGen  software  tool is based on code of the GENIE Collaboration which aims at developing a global software platform for the Monte Carlo simulation of neutrino interactions with energies up to PeV scales. Currently, the GENIE simulation code focuses mainly on events in the low-energy range (≤5 GeV) and  is valid up to 5 TeV.

As described in the paper,  the gSeaGen tool allows for the generation of electron, muon and tau neutrino.  Its application for the KM3NeT telescopes is described in detail.

KM3NeT Collaboration, S. Aiello, et al.,  Computer Physics Communications 256 (2020) 107477

https://doi.org/10.1016/j.cpc.2020.107477

https://arxiv.org/abs/2003.14040

New paper: The Control Unit of the KM3NeT Data Acquisition System

17 June 2020 – The KM3NeT Collaboration has published a new paper about the control unit of the data acquisition system. The data acquisition control software  of KM3NeT is operating both the off-shore detectors in the deep sea and in the lab the testing and qualification stations for detector components. The software, named Control Unit, is highly modular. It can undergo upgrades and reconfiguration with the acquisition running. Interplay with the central database of the Collaboration is obtained in a way that allows for data taking even if Internet links fail. In order to simplify the management of computing resources in the long term, and to cope with possible hardware failures of one or more computers, the KM3NeT Control Unit software features a custom dynamic resource provisioning and failover technology, which is especially important for ensuring continuity in case of rare transient events in multi-messenger astronomy. The software architecture relies on ubiquitous tools and broadly adopted technologies and has been successfully tested on several operating systems.

KM3NeT Collaboration, S. Aiello, et al., Computer Physics Communications 256 (2020) 107433, https://doi.org/10.1016/j.cpc.2020.107433, arXiv:1910.00112v1

 

KM3NeT Town Hall meeting

17-19 December 2019, KM3NeT Town Hall meeting in Marseille to promote our amazing multi-messenger programmes.

Website with programme.

 

 

 

 

Stay tuned!

First keynote speakers

After the general introduction by the KM3NeT Spokesperson Mauro Taiuti, the Deputy Spokesperson Aart Heijboer will present the expected performances of KM3NeT detectors and Dorothea Samtleben will show the first data from KM3NeT.

 

 

Workshop on simulation and data analysis

23 January 2019 – An internal KM3NeT workshop on ‘Simulation and Data Analysis’ was organised at INFN – Istitutio Nazionale di Fisica Nucleare in Genova, Italy. In the last two years the ARCA and ORCA sites were equipped with the first detection units which allowed for obtaining the first calibration data. The data comprises many measurements of muons created in the atmosphere. These measurements, although background to the neutrino signal, are extremely useful for the understanding of the detector performance and improving detector calibration and simulations of the detector response. The aim of the workshop was to review the currently existing simulation software tools and tuning them to reach agreement with the collected data on a new precision level.

Simulation of background events comprises very computationally intensive tasks, which must be run on the GRID and cloud infrastructures. For this, automatic workflows for the software deployment and running on different computer infrastructures were discussed and tests have been started. The simulation workflows also should keep provenance of the data to allow for repetition  and tracing of each simulated event. Automisation of the quality control of the data and simulation is yet another key task addressed at the workshop.