A measurement of the diffuse astrophysical neutrino spectrum is presented using IceCube data collected from 2011-2022 (10.3 years). We developed novel detection techniques to search for events with a contained vertex and exiting track induced by muon neutrinos undergoing a charged-current interaction. Searching for these starting track events allows us to not only more effectively reject atmospheric muons but also atmospheric neutrino backgrounds in the southern sky, opening a new window to the sub-100 TeV astrophysical neutrino sky. The event selection is constructed using a dynamic starting track veto and machine learning algorithms. We use this data to measure the astrophysical diffuse flux as a single power law flux (SPL) with a best-fit spectral index of $\gamma = 2.58 ^{+0.10}_{-0.09}$ and per-flavor normalization of $\phi^{\mathrm{Astro}}_{\mathrm{per-flavor}} = 1.68 ^{+0.19}_{-0.22} \times 10^{-18} \times \mathrm{GeV}^{-1} \mathrm{cm}^{-2} \mathrm{s}^{-1} \mathrm{sr}^{-1}$ (at 100 TeV). The sensitive energy range for this dataset is 3 - 550 TeV under the SPL assumption. This data was also used to measure the flux under a broken power law, however we did not find any evidence of a low energy cutoff.

Recent observations of GeV gamma-rays from novae have led to a paradigm shift in the understanding of these objects. While it is now believed that shocks contribute significantly to the energy budget of novae, it is still unknown if the emission is hadronic or leptonic in origin. Neutrinos could hold the key to definitively differentiating between these two scenarios, though the energies of such particles would be much lower than are typically targeted with neutrino telescopes. IceCube's densely instrumented DeepCore sub-array provides the ability to reduce the threshold for observation from 1 TeV down to approximately 10 GeV. We will discuss recent measurements in this low energy regime, details of a new sub-TeV selection, and prospects for future searches for transient neutrino emission.

Measurements of neutrinos at and below 10 GeV provide unique constraints of neutrino oscillation parameters as well as probes of potential Non-Standard Interactions (NSI). The IceCube Neutrino Observatory's DeepCore array is designed to detect neutrinos down to GeV energies. IceCube has built the world's largest data set of neutrinos >10 GeV, making searches for NSI a computational challenge. This work describes the use of convolutional neural networks (CNNs) to improve the energy reconstruction resolution and speed of reconstructing O(10 GeV) neutrino events in IceCube. Compared to current likelihood-based methods which take seconds to minutes, the CNN is expected to provide approximately a factor of 2 improvement in energy resolution while reducing the reconstruction time per event to milliseconds, which is essential for processing large datasets.

New optical sensors called the "D-Egg" have been developed for cost-effective instrumentation for the IceCube Upgrade. With two 8-inch high quantum efficient photomultiplier tubes (PMTs), they offer increased effective photocathode area while retaining as much of the successful IceCube Digital Optical Module design as possible. Mass production of D-Eggs has started in 2020. By the end of 2021, there will be 310 D-Eggs produced with 288 deployed in the IceCube Upgrade. The D-Egg readout system uses advanced technologies in electronics and computing power. Each of the two PMT signals is digitised using ultra-low-power 14-bit ADCs with a sampling frequency of 240 MSPS, enabling seamless and lossless event recording from single-photon signals to signals exceeding 200 PE within 10 ns, as well as flexible event triggering. In this paper, we report the single photon detection performance as well as the multiple photon recording capability of D-Eggs from the mass production line which have been evaluated with the built-in data acquisition system.

The IceCube neutrino observatory--installed in the Antarctic ice--is the largest neutrino telescope to date. It consists of 5,160 photomultiplier-tubes spread among 86 vertical strings making a total detector volume of more than a cubic kilometer. IceCube detects neutrinos via Cherenkov light emitted by charged relativistic particles produced when a neutrino interacts in or near the detector. The detector is particularly sensitive to high-energy neutrinos of due to its size and photosensor spacing. In this analysis we search for dark matter that annihilates into a metastable mediator that subsequently decays into Standard Model particles. These models yield an enhanced high-energy neutrino flux from dark matter annihilation inside the Sun compared to models without a mediator. Neutrino signals that are produced directly inside the Sun are strongly attenuated at higher energies due to interactions with the solar plasma. In the models considered here, the mediator can escape the Sun before producing any neutrinos, thereby avoiding attenuation. We present the results of an analysis of six years of IceCube data looking for dark matter in the Sun. We consider mediator lifetimes between 1 ms to 10 s and dark matter masses between 200 GeV and 75 TeV.

For the in-ice component of the next generation neutrino observatory at the South Pole, IceCube-Gen2, a new sensor module is being developed, which is an evolution of the D-Egg and mDOM sensors developed for the IceCube Upgrade. The sensor design features up to 18 4-inch PMTs distributed homogeneously in a borosilicate glass pressure vessel. Challenges arise for the mechanical design from the tight constraints on the bore hole diameter (which will be 2 inches smaller than for IceCube Upgrade) and from the close packing of the PMTs. The electronics design must meet the space constraints posed by the mechanical design as well as the power consumption and cost considerations from over 10,000 optical modules being deployed. This contribution presents forward-looking solutions to these design considerations. Prototype modules will be installed and integrated in the IceCube Upgrade.

The tau lepton’s supersymmetric partner, the stau, appears in some models as the next-to-lightest supersymmetric particle. Their deacy process into the lightest superpartner is usually suppressed by supersymmetry breaking, which makes it a long-lived particle. In this scenario, its signature is a long, minimally ionizing track when traveling through the IceCube detector. Independent of their primary energy, the stau tracks appear like low-energy muons in the detector. A potential signal of staus would thus be an excess over muon tracks induced by atmospheric muon neutrinos. Our analysis focuses on the region around the horizon as here the ratio between stau signal and atmospheric background is largest. We will present the first sensitivity to constrain the stau mass using IceCube and demonstrate the potential of this analysis with future improvements.

Gamma-ray bursts (GRBs) are among the most powerful events observed in our universe and have long been considered as possible sources of ultra-high-energy cosmic rays, which makes them promising neutrino source candidates. Previous IceCube searches for neutrino correlations with GRBs focused on the prompt (main emission) phase of the GRB and found no significant correlation between neutrino events and the observed GRBs. This motivates us to extend our search beyond the prompt phase. We perform analyses looking for evidence of neutrino emission up to 14 days before and after the prompt phase of GRBs. These analyses rely on a sample of candidate muon-neutrino events observed by IceCube from May 2011 to October 2018. The analyses are model-independent. Two of them scan different time-windows for possible neutrino emission, while a third analysis targets precursor emission based on GRB precursor observations by Fermi-GBM. We discuss the results and implications of these searches including limits on the contribution of GRBs to the diffuse neutrino flux.

Recent results from IceCube regarding TXS 0506+056 suggest the presence of neutrino flares that are not temporally coincident with a significant corresponding gamma ray flare. Such flares are particularly difficult to identify, as their presence must be inferred from the temporal distribution of neutrino data alone. Here we present the results of using a novel method to search for all such flares across the entire neutrino sky in 10 years of IceCube data, using both Gaussian and box-shaped flare hypotheses. Unlike for past searches, that looked for only the most significant neutrino flare in the data at a given direction, here we implement an algorithm to combine information from multiple flares associated with a single source candidate. This represents the most detailed description of the neutrino sky to date, providing the location and intensity of all neutrino cluster candidates in both space and time. These results can be used to further constrain potential populations of transient neutrino sources, serving as a complement to existing time-integrated and time-dependent methods.

The IceCube Neutrino Observatory at the South Pole detects Cherenkov light emitted by charged secondary particles created by primary neutrino interactions. Double pulse waveforms can arise from charged current interactions of astrophysical tau neutrinos with nucleons in the ice and the subsequent decay of tau leptons. The previous 8-year tau double pulse analysis found three tau neutrino candidate events. Among them, the most promising one observed in 2014 is located very near the dust layer in the middle of the detector. A posterior analysis on this event will be presented in this paper, using a new ice model treatment with continuously varying nuisance parameters to do the targeted Monte Carlo re-simulation for tau and other background neutrino ensembles. The impact of different ice models on the expected signal and background statistics will also be discussed.

Clusters of galaxies -- with their turbulent magnetic fields and abundant matter content -- are a promising class of potential neutrino sources. Cosmic rays accelerated within the large-scale shocks,Active GalacticNuclei (AGN), or both can be confined in galaxy clusters over cosmological timescales and produce a steady flux of neutrinos in secondary interactions. The IceCube Neutrino Observatory has detected a diffuse flux of high-energy astrophysical neutrinos. After ten years of operations, however, the origin of this flux remains largely unconstrained. In this work, we perform a stacked search for neutrinos, using a population of over one thousand galaxy clusters detected by the Planck Satellite via the Sunyaev-Zeldovich (SZ) effect up to a redshift $z = 1$. We present the first results on the contribution of galaxy clusters to the diffuse neutrino flux and discuss the implications for various models of cosmic-ray acceleration in large-scale structures.

We present a search for an unstable sterile neutrino by looking for a resonant signal in eight years of atmospheric ν_{μ} data collected from 2011 to 2019 at the IceCube Neutrino Observatory. Both the (stable) three-neutrino and the 3+1 sterile neutrino models are disfavored relative to the unstable sterile neutrino model, though with p values of 2.8% and 0.81%, respectively, we do not observe evidence for 3+1 neutrinos with neutrino decay. The best-fit parameters for the sterile neutrino with decay model from this study are Δm_{41}^{2}=6.7_{-2.5}^{+3.9}  eV^{2}, sin^{2}2θ_{24}=0.33_{-0.17}^{+0.20}, and g^{2}=2.5π±1.5π, where g is the decay-mediating coupling. The preferred regions of the 3+1+decay model from short-baseline oscillation searches are excluded at 90% C.L.

An upgrade to the IceCube Neutrino Telescope is currently under construction. For this IceCube Upgrade, seven new strings will be deployed in the central region of the 86 string IceCube detector to enhance the capability to detect neutrinos in the GeV range. One of the main science objectives of the IceCube Upgrade is an improved calibration of the IceCube detector to reduce systematic uncertainties related to the optical properties of the ice. We have developed a novel optical camera and illumination system that will be part of 700 newly developed optical modules to be deployed with the IceCube Upgrade. A combination of transmission and reflection photographic measurements will be used to measure the optical properties of bulk ice between strings and refrozen ice in the drill hole, to determine module positions, and to survey the local ice environments surrounding the sensor module. In this contribution we present the production design, acceptance testing, and plan for post-deployment calibration measurements with the camera system.

We present performance studies of a segmented optical module for the IceCube-Gen2 detector. Based on the experience gained in sensor development for the IceCube Upgrade, the new sensor will consist of up to eighteen 4 inch PMTs housed in a transparent pressure vessel, providing homogeneous angular coverage. The use of custom molded optical `gel pads' around the PMTs enhances the photon capture rate via total internal reflection at the gel-air interface. This contribution presents simulation studies of various sensor, PMT, and gel pad geometries aimed at optimizing the sensitivity of the optical module in the face of confined space and harsh environmental conditions at the South Pole.

A supermassive black hole, obscured by cosmic dust, powers the nearby active galaxy NGC 1068. Neutrinos, which rarely interact with matter, could provide information on the galaxy's active core. We searched for neutrino emission from astrophysical objects using data recorded with the IceCube neutrino detector between 2011 and 2020. The positions of 110 known gamma-ray sources were individually searched for neutrino detections above atmospheric and cosmic backgrounds. We found that NGC 1068 has an excess of [Formula: see text] neutrinos at tera-electron volt energies, with a global significance of 4.2σ, which we interpret as associated with the active galaxy. The flux of high-energy neutrinos that we measured from NGC 1068 is more than an order of magnitude higher than the upper limit on emissions of tera-electron volt gamma rays from this source.

With infrared luminosities $L_{\mathrm{IR}} \geq 10^{12} L_{\odot}$, Ultra-Luminous Infrared Galaxies (ULIRGs) are the most luminous objects in the infrared sky. They are predominantly powered by starburst regions with star-formation rates $\gtrsim 100~ M_{\odot}~ \mathrm{yr^{-1}}$. ULIRGs can also host an active galactic nucleus (AGN). Both the starburst and AGN environments contain plausible hadronic accelerators, making ULIRGs candidate neutrino sources. We present the results of an IceCube stacking analysis searching for high-energy neutrinos from a representative sample of 75 ULIRGs with redshift $z \leq 0.13$. While no significant excess of ULIRG neutrinos is found in 7.5 years of IceCube data, upper limits are reported on the neutrino flux from these 75 ULIRGs as well as an extrapolation for the full ULIRG source population. In addition, constraints are provided on models predicting neutrino emission from ULIRGs.

The IceCube Upgrade is an extension of the IceCube detector at the geographic South Pole. It consists of seven new strings with novel instrumentation. More than 430 multi-PMT optical modules called "mDOMs", housing 24 3-inch PMTs each, will be produced for the Upgrade. This will require testing and pre-calibration on a short timescale of more than 10,000 PMTs prior to assembly and deployment. We present the design of a PMT testing facility that enables simultaneous testing of roughly 100 PMTs per day at temperatures down to -20{\deg}C. The design is implemented at RWTH Aachen University and TU Dortmund University in parallel to achieve a throughput of up to 1,000 PMTs per week. This will enable a steady supply of tested PMTs to the production sites, which is critical for the Upgrade, as well as the future IceCube-Gen2 project.

After scattering off nuclei in the Sun, dark matter particles can be gravitationally captured by the Sun, accumulate in the Sun's core and annihilate into Standard Model particles. Neutrinos originating from these annihilations can be detected by the IceCube Neutrino Observatory, located at the South Pole. Due to the non-observation of these neutrinos, constraints on the standard spin-dependent and spin-independent dark matter-nucleon scattering cross sections have been placed. Based on these constraints, we present upper limits on the coupling constants of the non-relativistic effective theory of dark matter-nucleon interactions, including velocity and momentum dependent interactions.

The IceCube Neutrino Observatory is a cubic-kilometer scale neutrino detector embedded in the Antarctic ice of the South Pole. In the near future, the detector will be augmented by extensions, such as the IceCube Upgrade and the planned Gen2 detector. The sparseness of observed light in the detector for low-energy events, and the irregular detector geometry, have always been a challenge to the reconstruction of the detected neutrinos' parameters of interest. This challenge remains with the IceCube Upgrade, currently under construction, which introduces seven new detector strings with novel detector modules. The Upgrade modules will increase the detection rate of low-energy events and allow us to further constrain neutrino oscillation physics. However, the geometry of these modules render existing traditional reconstruction algorithms more difficult to use. We introduce a new reconstruction algorithm based on Graph Neural Networks, which we use to reconstruct neutrino events at much faster processing times than the traditional algorithms, while providing comparable resolution. We show that our algorithm is applicable not only to reconstructing data of the current IceCube detector, but also simulated events for next-generation extensions, such as the IceCube Upgrade.

The field of deep learning has become increasingly important for particle physics experiments, yielding a multitude of advances, predominantly in event classification and reconstruction tasks. Many of these applications have been adopted from other domains. However, data in the field of physics are unique in the context of machine learning, insofar as their generation process and the laws and symmetries they abide by are usually well understood. Most commonly used deep learning architectures fail at utilizing this available information. In contrast, more traditional likelihood-based methods are capable of exploiting domain knowledge, but they are often limited by computational complexity. In this contribution, a hybrid approach is presented that utilizes generative neural networks to approximate the likelihood, which may then be used in a traditional maximum-likelihood setting. Domain knowledge, such as invariances and detector characteristics, can easily be incorporated in this approach. The hybrid approach is illustrated by the example of event reconstruction in IceCube.