KM3NeT - Blog

KM3NeT blog posts

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!

A collaboration in corona times

18 February 2021 – Like everyone else the KM3NeT Collaboration has to follow the restrictive measures against the COVID-19 pandemic. So, once more, the last two weeks we held our Collaboration meeting on-line. At this virtual meeting we discussed the many details of building the telescopes, analysing the data and developing the simulation programs.  We are very encouraged by the large progress with constructing the many detector components and the installation of the ARCA and ORCA telescope infrastructures. We are excited by the many analyses of data from the installed detector units on which we will  report at the upcoming conferences. Nevertheless, we  tremendously miss our colleagues.  In particular, for the young scientists in our Collaboration these are difficult times, but they are amazing in their efforts for the Collaboration.

During the Collaboration meeting we virtually said goodbye and thank you to Marco Anghinolfi, who will be retiring soon after many years of service to the Collaboration.  We hope you enjoy your retirement. Arrivederci, but no goodbye!

We virtually raised a glass to thank Mauro Taiuti for his four years of leadership as Spokesperson of KM3NeT. Fortunately, he has promised to continue his scientific career in the Collaboration!

We are looking forward to the new leadership of Paschal Coyle and his team. All the best for executing the tremendous task ahead of building the telescopes and executing the scientific program – also in corona times. We will do our best to support you!

We virtually applauded our PhD students who have recently completed their theses and wished our postdocs leaving the Collaboration all the best for their careers!

We virtually welcomed new students and postdocs who will work on the nitty gritty of data analysis and detector calibration. We hope to meet you face-to-face very soon!

Last but not least, we  virtually welcomed LPC Caen, France as a new group in the collaboration who  will participate in both the construction work and the scientific program. Super!

On the bright side of virtual meetings our conference committee reported a more diverse participation of our Collaboration in the international conferences. More people took part and the representation among speakers was better balanced in seniority and gender.

Building and operating a telescope is an attractive, tremendous, collaborative effort relying on  a lot of human interaction, hard to recreate in a virtual environment – but we did our best! We were still able to generate our customary  Collaboration group picture as you can see below: a collaboration in corona times.

 

 

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

 

‘6 strings, 6 months’

On 27 July 2020, the ORCA detector of KM3NeT reached a milestone: its first 6 strings were continuously taking data since 6 months. With two musical productions of the amazing talents in the KM3NeT Collaboration, the milestone  was celebrated.

Enjoy ‘6 strings, 6 months’, the song of the Route 66 of KM3NeT and an instrumental piece on 6 pianos by 6 players.

Both productions were recorded in corona times – at large distances between the performers.

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 against racism and discrimination

10 June 2020 – The KM3NeT  Collaboration is deeply saddened by the recent outbreaks of violence and hatred against people of colour. They once again laid bare the enduring worldwide systemic racism.

The researchers in KM3NeT are strongly against any kind of racism or discrimination. We urge all citizens of the world and their leaders to embrace all actions suited to establish equal opportunities for all, and forever.

As a collaboration, we will increase awareness on the impact of unintended racism and discrimination in our universities and research institutes and in particular in our collaboration.

KM3NeT collaboration meets online

8 June 2020 – Like so many other meetings, also the Spring Collaboration meeting of KM3NeT went online during corona times.  A week full of discussions  started today. An online concert and quiz are planned. Of course the traditional group photo has already been made.

 

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.