Old isolated neutron stars have been gathering attention as targets to probe Dark Matter (DM) through temperature observations. DM will anomalously heat neutron stars through its gravitational capture and annihilation process, which predicts surface temperature as T_s ~ (1 − 3) × 10^3 K for t > 10^6 years. We may put constraints on DM-nucleon scattering cross section by finding even colder neutron stars.
This story, however, assumed that there is no relevant heating source for old neutron stars. In this talk, we discuss the creep motion of vortex lines in the neutron superfluid of the inner crust as the heating mechanism. This creep mechanism is inherent in the structure of neutron stars. The heating luminosity is proportional to the time derivative of the angular velocity of the pulsar rotation, and the proportional constant J has an approximately universal value for each neutron star. If this vortex creep heating is quantitatively relevant against DM heating, this mechanism may cause a serious background to probe DM.
The J parameter can be determined from the temperature observation of old neutron stars because the heating luminosity is balanced with the photon emission in the late time. We study the latest data of neutron star temperature observation and find that these data indeed give similar values of J, in favor of the assumption that these neutron stars are heated by the frictional motion of vortex lines. Besides, these values turn out to be consistent with the theoretical calculations of the vortex-nuclear interaction. Integarting all the results, we evaluate the vortex creep heating and conclude its significance against DM heating.

This is the fourth event by the Quantum Gravity Gatherings (QGG) Study Group at RIKEN iTHEMS. For this event we have invited Prof. Yuki Sato, National Institute of Technology, Tokuyama College, to give pedagogical lectures on the causal dynamical triangulations approach to quantum gravity. We wish this event to provide insights to researchers in related fields.

The causal dynamical triangulations formalism appears to be one of the most promising constructive approaches to quantum gravity: possessing deep links with the asymptotic safety programme and Hořava-Lifshitz gravity, causal dynamical triangulations appears to avoid many of the well-known pathologies characteristic of its Euclidean analogue. As an example the emergence of spacetime geometry remains possible in various spacetime dimensions. While many of the results in higher dimensions are understood only at the numerical level, the analytical study of the approach in two spacetime dimensions is relatively well developed; Yuki Sato is a leading expert on these latter developments and we are very lucky he has agreed to present the understanding of 2D causal spacetime coming from this approach in a manner consistent with the Quantum Gravity Gatherings philosophy.

This intensive lecture series is intended to be a lively and participatory event, not just a listening experience. For this reason, the number of participants will be limited to about 30 with priority given to graduate students and young post-docs; the intensive talk will be given in a face-to-face blackboard style (in English, no online streaming) to allow for informal and lively Q&A discussions. The program will also include short talk sessions, where interested participants can give a 5 min talk on a topic of their choice (their research, reviews on some works, what they want to study in the future, etc.). Registration is available via the dedicated website.

We introduce the first large-scale dataset, MNISQ, for both the Quantum and the Classical Machine Learning community during the Noisy Intermediate-Scale Quantum era. MNISQ consists of 4,950,000 data points organized in 9 subdatasets. Building our dataset from the quantum encoding of classical information (e.g., MNIST dataset), we deliver a dataset in a dual form: in quantum form, as circuits, and in classical form, as quantum circuit descriptions (quantum programming language, QASM). In fact, also Machine Learning research related to quantum computers undertakes a dual challenge: enhancing machine learning by exploiting the power of quantum computers, while also leveraging state-of-the-art classical machine learning methodologies to help the advancement of quantum computing. Therefore, we perform circuit classification on our dataset, tackling the task with both quantum and classical models. In the quantum endeavor, we test our circuit dataset with Quantum Kernel methods, and we show excellent results with up to 97% accuracy. In the classical world, the underlying quantum mechanical structures within the quantum circuit data are not trivial. Nevertheless, we test our dataset on three classical models: Structured State Space sequence model (S4), Transformer, and LSTM. In particular, the S4 model applied on the tokenized QASM sequences reaches an impressive 77% accuracy. These findings illustrate that quantum circuit-related datasets are likely to be quantum advantageous, but also that state-of-the-art machine learning methodologies can competently classify and recognize quantum circuits. We finally entrust the quantum and classical machine learning community.

Cosmological observations have led to an extremely precise understanding of the large-scale structure of the Universe. A common assumption is to extrapolate large-scale properties to smaller scales; however, whether this is correct or not is unknown and many well-motivated early Universe scenarios predict substantially different structure formation histories. In this seminar I will discuss two scenarios where nonlinear structures form much earlier than is typically assumed. In the first case, the initial fluctuations are enhanced on small scales leading to either primordial black holes clusters or WIMP minihalos right after matter-radiation equality. In the second, I will show that an additional attractive dark force leads to structure formation even in the radiation dominated Universe. I will furthermore discuss possible observations of such early structure formation including changes to the cosmic microwave background, dark matter annihilation, and when the first galaxies form.