Search

The GRAINE project observes cosmic gamma-rays, using a balloon-borne emulsion-film-based telescope in the sub-GeV/GeV energy band. We reported in our previous balloon experiment in 2018, GRAINE2018, the detection of the known brightest source, Vela pulsar, with the highest angular resolution ever reported in an energy range of $>$80 MeV. However, the emulsion scanning system used in the experiment was designed to achieve a high-speed scanning, and it was not accurate enough to ensure the optimum spacial resolution of the emulsion film and limited the performance. Here, we report a new high-precision scanning system that can be used to greatly improve the observation result of GRAINE2018 and also be employed in future experiments. The system involves a new algorithm that recognizes each silver grain on an emulsion film and is capable of measuring tracks with a positional resolution for the passing points of tracks of almost the same as the intrinsic resolution of nuclear emulsion film ($\sim$70 nm). This resolution is approximately one order of magnitude smaller than that obtained with the high-speed scanning system. With this system, an angular resolution for gamma-rays of 0.1$^\circ$ at 1 GeV is expected to be achieved. Furthermore, we successfully combine the new high-precision system with the existing high-speed system, establishing the system to make a high-speed and high-precision measurement. Employing these systems, we reanalyze the gamma-ray events detected previously by only the high-speed system in GRAINE2018 and obtain an about three times higher angular resolution (0.22$^\circ$) in 500--700 MeV than the original value. The high-resolution observation may bring new insights into the gamma-ray emission from the Galactic center region and may realize polarization measurements of high-energy cosmic gamma-rays., Comment: 20 pages, 11 figures

This paper presents the first results of the study of high-energy electron and muon neutrino charged-current interactions in the FASER$\nu$ emulsion/tungsten detector of the FASER experiment at the LHC. A subset of the FASER$\nu$ volume, which corresponds to a target mass of 128.6~kg, was exposed to neutrinos from the LHC $pp$ collisions with a centre-of-mass energy of 13.6~TeV and an integrated luminosity of 9.5 fb$^{-1}$. Applying stringent selections requiring electrons with reconstructed energy above 200~GeV, four electron neutrino interaction candidate events are observed with an expected background of $0.025^{+0.015}_{-0.010}$, leading to a statistical significance of 5.2$\sigma$. This is the first direct observation of electron neutrino interactions at a particle collider. Eight muon neutrino interaction candidate events are also detected, with an expected background of $0.22^{+0.09}_{-0.07}$, leading to a statistical significance of 5.7$\sigma$. The signal events include neutrinos with energies in the TeV range, the highest-energy electron and muon neutrinos ever detected from an artificial source. The energy-independent part of the interaction cross section per nucleon is measured over an energy range of 560--1740 GeV (520--1760 GeV) for $\nu_e$ ($\nu_{\mu}$) to be $(1.2_{-0.7}^{+0.8}) \times 10^{-38}~\mathrm{cm}^{2}\,\mathrm{GeV}^{-1}$ ($(0.5\pm0.2) \times 10^{-38}~\mathrm{cm}^{2}\,\mathrm{GeV}^{-1}$), consistent with Standard Model predictions. These are the first measurements of neutrino interaction cross sections in those energy ranges.

The Forward Search Experiment (FASER) at CERN's Large Hadron Collider (LHC) has recently directly detected the first collider neutrinos. Neutrinos play an important role in all FASER analyses, either as signal or background, and it is therefore essential to understand the neutrino event rates. In this study, we update previous simulations and present prescriptions for theoretical predictions of neutrino fluxes and cross sections, together with their associated uncertainties. With these results, we discuss the potential for possible measurements that could be carried out in the coming years with the FASER neutrino data to be collected in LHC Run 3 and Run 4., Comment: 19 pages, 10 figures

We report the first direct observation of neutrino interactions at a particle collider experiment. Neutrino candidate events are identified in a 13.6 TeV center-of-mass energy $pp$ collision data set of 35.4 fb${}^{-1}$ using the active electronic components of the FASER detector at the Large Hadron Collider. The candidates are required to have a track propagating through the entire length of the FASER detector and be consistent with a muon neutrino charged-current interaction. We infer $153^{+12}_{-13}$ neutrino interactions with a significance of 16 standard deviations above the background-only hypothesis. These events are consistent with the characteristics expected from neutrino interactions in terms of secondary particle production and spatial distribution, and they imply the observation of both neutrinos and anti-neutrinos with an incident neutrino energy of significantly above 200 GeV., Comment: Submitted to PRL on March 24 2023

Tau neutrino is the least studied lepton of the Standard Model (SM). The NA65/DsTau experiment targets to investigate $D_s$, the parent particle of the $\nu_\tau$, using the nuclear emulsion-based detector and to decrease the systematic uncertainty of $\nu_\tau$ flux prediction from over 50% to 10% for future beam dump experiments. In the experiment, the emulsion detectors are exposed to the CERN SPS 400 GeV proton beam. To provide optimal conditions for the reconstruction of interactions, the protons are required to be uniformly distributed over the detector's surface with an average density of $10^5~\rm{cm^{-2}}$ and the fluctuation of less than 10%. To address this issue, we developed a new proton irradiation system called the target mover. The new target mover provided irradiation with a proton density of $0.98~\rm{cm^{-2}}$ and the density fluctuation of $2.0\pm 0.3$% in the DsTau 2021 run., Comment: 9 pages, 16 figures

Deformable registration of two-dimensional/three-dimensional (2D/3D) images of abdominal organs is a complicated task because the abdominal organs deform significantly and their contours are not detected in two-dimensional X-ray images. We propose a supervised deep learning framework that achieves 2D/3D deformable image registration between 3D volumes and single-viewpoint 2D projected images. The proposed method learns the translation from the target 2D projection images and the initial 3D volume to 3D displacement fields. In experiments, we registered 3D-computed tomography (CT) volumes to digitally reconstructed radiographs generated from abdominal 4D-CT volumes. For validation, we used 4D-CT volumes of 35 cases and confirmed that the 3D-CT volumes reflecting the nonlinear and local respiratory organ displacement were reconstructed. The proposed method demonstrate the compatible performance to the conventional methods with a dice similarity coefficient of 91.6 \% for the liver region and 85.9 \% for the stomach region, while estimating a significantly more accurate CT values.

Unsupervised image translation using adversarial learning has been attracting attention to improve the image quality of medical images. However, adversarial training based on the global evaluation values of discriminators does not provide sufficient translation performance for locally different image features. We propose adversarial learning with a feedback mechanism from a discriminator to improve the quality of CBCT images. This framework employs U-net as the discriminator and outputs a probability map representing the local discrimination results. The probability map is fed back to the generator and used for training to improve the image translation. Our experiments using 76 corresponding CT-CBCT images confirmed that the proposed framework could capture more diverse image features than conventional adversarial learning frameworks and produced synthetic images with pixel values close to the reference image and a correlation coefficient of 0.93.

FASER, the ForwArd Search ExpeRiment, is an experiment dedicated to searching for light, extremely weakly-interacting particles at CERN's Large Hadron Collider (LHC). Such particles may be produced in the very forward direction of the LHC's high-energy collisions and then decay to visible particles inside the FASER detector, which is placed 480 m downstream of the ATLAS interaction point, aligned with the beam collisions axis. FASER also includes a sub-detector, FASER$\nu$, designed to detect neutrinos produced in the LHC collisions and to study their properties. In this paper, each component of the FASER detector is described in detail, as well as the installation of the experiment system and its commissioning using cosmic-rays collected in September 2021 and during the LHC pilot beam test carried out in October 2021. FASER will start taking LHC collision data in 2022, and will run throughout LHC Run 3., Comment: 92 pages, 72 Figures

Hypothetical short-range interactions could be detected by measuring the wavefunctions of ultracold neutrons (UCNs) on a mirror bounded by the Earth's gravitational field. The Searches require detectors with higher spatial resolution. We are developing a UCN detector for the with a high spatial resolution, which consists of a Si substrate, a thin converter layer including $^{10}$B$_{4}$C, and a layer of fine-grained nuclear emulsion. Its resolution was estimated to be less than 100 nm by fitting tracks of either $^{7}$Li nuclei or $\alpha$-particles, which were created when neutrons interacted with the $^{10}$B$_{4}$C layer. For actual measurements of the spatial distributions, the following two improvements were made: The first was to establish a method to align microscopic images with high accuracy within a wide region of 65 mm $\times$ 0.2 mm. We created reference marks of 1 $\mu$m and 5 $\mu$m diameter with an interval of 50 $\mu$m and 500 $\mu$m, respectively, on the Si substrate by electron beam lithography and realized a position accuracy of less than 30 nm. The second was to build a holder that could maintain the atmospheric pressure around the nuclear emulsion to utilize it under vacuum during exposure to UCNs. The intrinsic resolution of the improved detector was estimated by evaluating the blur of a transmission image of a gadolinium grating taken by cold neutrons as better than 0.56 $\pm$ 0.08 $\mu$m, which included the grating accuracy. A test exposure to UCNs was conducted to obtain the spatial distribution of UCNs in the Earth's gravitational field. Although the test was successful, a blurring of 6.9 $\mu$m was found in the measurements, compared with a theoretical curve. We identified the blurring caused by the refraction of UCNs due to the roughness of the upstream surface of the substrate. Polishing of the surface makes the resolution less than 100 nm.

FASER is a new experiment designed to search for new light weakly-interacting long-lived particles (LLPs) and study high-energy neutrino interactions in the very forward region of the LHC collisions at CERN. The experimental apparatus is situated 480 m downstream of the ATLAS interaction-point aligned with the beam collision axis. The FASER detector includes four identical tracker stations constructed from silicon microstrip detectors. Three of the tracker stations form a tracking spectrometer, and enable FASER to detect the decay products of LLPs decaying inside the apparatus, whereas the fourth station is used for the neutrino analysis. The spectrometer has been installed in the LHC complex since March 2021, while the fourth station is not yet installed. FASER will start physics data taking when the LHC resumes operation in early 2022. This paper describes the design, construction and testing of the tracking spectrometer, including the associated components such as the mechanics, readout electronics, power supplies and cooling system.

Organ shape reconstruction based on a single-projection image during treatment has wide clinical scope, e.g., in image-guided radiotherapy and surgical guidance. We propose an image-to-graph convolutional network that achieves deformable registration of a 3D organ mesh for a single-viewpoint 2D projection image. This framework enables simultaneous training of two types of transformation: from the 2D projection image to a displacement map, and from the sampled per-vertex feature to a 3D displacement that satisfies the geometrical constraint of the mesh structure. Assuming application to radiation therapy, the 2D/3D deformable registration performance is verified for multiple abdominal organs that have not been targeted to date, i.e., the liver, stomach, duodenum, and kidney, and for pancreatic cancer. The experimental results show shape prediction considering relationships among multiple organs can be used to predict respiratory motion and deformation from digitally reconstructed radiographs with clinically acceptable accuracy.

The FASER experiment is a new small and inexpensive experiment that is placed 480 meters downstream of the ATLAS experiment at the CERN LHC. FASER is designed to capture decays of new long-lived particles, produced outside of the ATLAS detector acceptance. These rare particles can decay in the FASER detector together with about 500-1000 Hz of other particles originating from the ATLAS interaction point. A very high efficiency trigger and data acquisition system is required to ensure that the physics events of interest will be recorded. This paper describes the trigger and data acquisition system of the FASER experiment and presents performance results of the system acquired during initial commissioning.

FASER$\nu$ at the CERN Large Hadron Collider (LHC) is designed to directly detect collider neutrinos for the first time and study their cross sections at TeV energies, where no such measurements currently exist. In 2018, a pilot detector employing emulsion films was installed in the far-forward region of ATLAS, 480 m from the interaction point, and collected 12.2 fb$^{-1}$ of proton-proton collision data at a center-of-mass energy of 13 TeV. We describe the analysis of this pilot run data and the observation of the first neutrino interaction candidates at the LHC. This milestone paves the way for high-energy neutrino measurements at current and future colliders., Comment: Auxiliary materials are available at https://faser.web.cern.ch/fasernu-first-neutrino-interaction-candidates

FASERnu is a proposed small and inexpensive emulsion detector designed to detect collider neutrinos for the first time and study their properties. FASERnu will be located directly in front of FASER, 480 m from the ATLAS interaction point along the beam collision axis in the unused service tunnel TI12. From 2021-23 during Run 3 of the 14 TeV LHC, roughly 1,300 electron neutrinos, 20,000 muon neutrinos, and 20 tau neutrinos will interact in FASERnu with TeV-scale energies. With the ability to observe these interactions, reconstruct their energies, and distinguish flavors, FASERnu will probe the production, propagation, and interactions of neutrinos at the highest human-made energies ever recorded. The FASERnu detector will be composed of 1000 emulsion layers interleaved with tungsten plates. The total volume of the emulsion and tungsten is 25cm x 25cm x 1.35m, and the tungsten target mass is 1.2 tonnes. From 2021-23, 7 sets of emulsion layers will be installed, with replacement roughly every 20-50 1/fb in planned Technical Stops. In this document, we summarize FASERnu's physics goals and discuss the estimates of neutrino flux and interaction rates. We then describe the FASERnu detector in detail, including plans for assembly, transport, installation, and emulsion replacement, and procedures for emulsion readout and analyzing the data. We close with cost estimates for the detector components and infrastructure work and a timeline for the experiment., Comment: 49 pages, 25 figures; submitted to the CERN LHCC on 28 October 2019

Respiratory motion and the associated deformations of abdominal organs and tumors are essential information in clinical applications. However, inter- and intra-patient multi-organ deformations are complex and have not been statistically formulated, whereas single organ deformations have been widely studied. In this paper, we introduce a multi-organ deformation library and its application to deformation reconstruction based on the shape features of multiple abdominal organs. Statistical multi-organ motion/deformation models of the stomach, liver, left and right kidneys, and duodenum were generated by shape matching their region labels defined on four-dimensional computed tomography images. A total of 250 volumes were measured from 25 pancreatic cancer patients. This paper also proposes a per-region-based deformation learning using the reproducing kernel to predict the displacement of pancreatic cancer for adaptive radiotherapy. The experimental results show that the proposed concept estimates deformations better than general per-patient-based learning models and achieves a clinically acceptable estimation error with a mean distance of 1.2 $\pm$ 0.7 mm and a Hausdorff distance of 4.2 $\pm$ 2.3 mm throughout the respiratory motion.

In the DsTau experiment at the CERN SPS, an independent and direct way to measure tau neutrino production following high energy proton interactions was proposed. As the main source of tau neutrinos is a decay of Ds mesons, produced in proton-nucleus interactions, the project aims at measuring a differential cross section of this reaction. The experimental method is based on a use of high resolution emulsion detectors for effective registration of events with short lived particle decays. Here we present the motivation of the study, details of the experimental technique, and the first results of the analysis of the data collected during test runs, which prove feasibility of the full scale study of the process in future.

We promote the precise gamma-ray observation project Gamma-Ray Astro-Imager with Nuclear Emulsion (GRAINE), which uses balloon-borne emulsion gamma-ray telescopes. The emulsion telescope realizes observations with high angular resolution, polarization sensitivity, and large aperture area in the 0.01--100 GeV energy region. Herein, we report the data analysis of emulsion tracks and the first demonstration of gamma-ray imaging via an emulsion telescope by using the flight data from the balloon experiment performed in 2015 (GRAINE 2015). The emulsion films were scanned by the latest read-out system for a total area of 41 m$^2$ in three months, and then the gamma-ray event selection was automatically processed. Millions of electron-pair events are accumulated in the balloon-borne emulsion telescope. The emulsion telescope detected signals from a calibration source (gamma rays from the interaction of cosmic rays with an aluminum plate) with a high significance during the balloon observation and created a gamma-ray image consistent with the source size and the expected angular resolution in the energy range of 100--300 MeV. The flight performance obtained in the GRAINE 2015 experiment proves that balloon-borne emulsion telescope experiments with larger area are feasible while maintaining expected imaging performance., Comment: 21 pages, 18 figures

Indirect reciprocity based on reputation is a leading mechanism driving human cooperation, where monitoring of behaviour and sharing reputation-related information are crucial. Because collecting information is costly, a tragedy of the commons can arise, with some individuals free-riding on information supplied by others. This can be overcome by organising monitors that aggregate information, supported by fees from their information users. We analyse a co-evolutionary model of individuals playing a social dilemma game and monitors watching them; monitors provide information and players vote for a more beneficial monitor. We find that (1) monitors that simply rate defection badly cannot stabilise cooperation---they have to overlook defection against ill-reputed players; (2) such overlooking monitors can stabilise cooperation if players vote for monitors rather than to change their own strategy; (3) STERN monitors, who rate cooperation with ill-reputed players badly, stabilise cooperation more easily than MILD monitors, who do not do so; (4) a STERN monitor wins if it competes with a MILD monitor; and (5) STERN monitors require a high level of surveillance and achieve only lower levels of cooperation, whereas MILD monitors achieve higher levels of cooperation with loose and thus lower cost monitoring., Comment: 22 pages, 4 figures (supplementary information: 12 pages, 3 figures). Under review in Royal Society Open Science

Topological and kinematical characteristics of hadron interactions have been studied using a lead-emulsion target exposed to 2, 4 and 10 GeV/c hadron beams. A total length of 60 m $\pi^-$ tracks was followed using a high speed automated emulsion scanning system. A total of 318 hadron interaction vertices and their secondary charged particle tracks were reconstructed. Measurement results of interaction lengths, charged particle multiplicity, emission angles and momenta of secondary charged particles are compared with a Monte Carlo simulation and appear to be consistent. Nuclear fragments emitted from interaction vertices were also detected by a newly developed emulsion scanning system with wide-angle acceptance. Their emission angle distributions are in good agreement with the simulated distributions. Probabilities of an event being associated with at least one fragment track are found to be greater than 50% for beam momentum $P > 4$ GeV/c and are well reproduced by the simulation. These experimental results validate estimation of the background due to hadron interactions in the sample of $\tau$ decay candidates in the OPERA $\nu_{\mu} \to \nu_{\tau}$ oscillation experiment., Comment: 14 pages, 11 figures

Indirect reciprocity is a mechanism for cooperation in social dilemma situations, in which an individual is motivated to help another to acquire a good reputation and receive help from others afterwards. Ingroup favoritism is another aspect of human cooperation, whereby individuals help members in their own group more often than those in other groups. Ingroup favoritism is a puzzle for the theory of cooperation because it is not easily evolutionarily stable. In the context of indirect reciprocity, ingroup favoritism has been shown to be a consequence of employing a double standard when assigning reputations to ingroup and outgroup members; e.g., helping an ingroup member is regarded as good, whereas the same action toward an outgroup member is regarded as bad. We analyze a model of indirect reciprocity in which information sharing is conducted groupwise. In our model, individuals play social dilemma games within and across groups, and the information about their reputations is shared within each group. We show that evolutionarily stable ingroup favoritism emerges even if all the players use the same reputation assignment rule regardless of group (i.e., a single standard). Two reputation assignment rules called simple standing and stern judging yield ingroup favoritism. Stern judging induces much stronger ingroup favoritism than does simple standing. Simple standing and stern judging are evolutionarily stable against each other when groups employing different assignment rules compete and the number of groups is sufficiently large. In addition, we analytically show as a limiting case that homogeneous populations of reciprocators that use reputations are unstable when individuals independently infer reputations of individuals, which is consistent with previously reported numerical results., Comment: 25 pages, 7 figures. The Abstract is shortened to fill in arXiv's abstract form

Detecting the first electron pairs with nuclear emulsion allows a precise measurement of the direction of incident gamma-rays as well as their polarization. With recent innovations in emulsion scanning, emulsion analyzing capability is becoming increasingly powerful. Presently, we are developing a balloon-borne gamma-ray telescope using nuclear emulsion. An overview and a status of our telescope is given., Comment: 10 pages, 5 figures, talk given at PSB1-0023-1018 in 38th COSPAR Scientific Assembly, 25 July 2010, Bremen, Germany

Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information theoretic method to the spatiotemporal data of cell-phone locations, [C. Song et al. Science 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one's conversation partners is defined as the degree to which one's next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to some extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual's predictability is correlated with the position in the static social network derived from the data. Individuals confined in a community - in the sense of an abundance of surrounding triangles - tend to have low predictability, and those bridging different communities tend to have high predictability., Comment: 38 pages, 19 figures

Many online marketplaces enjoy great success. Buyers and sellers in successful markets carry out cooperative transactions even if they do not know each other in advance and a moral hazard exists. An indispensable component that enables cooperation in such social dilemma situations is the reputation system. Under the reputation system, a buyer can avoid transacting with a seller with a bad reputation. A transaction in online marketplaces is better modeled by the trust game than other social dilemma games, including the donation game and the prisoner's dilemma. In addition, most individuals participate mostly as buyers or sellers; each individual does not play the two roles with equal probability. Although the reputation mechanism is known to be able to remove the moral hazard in games with asymmetric roles, competition between different strategies and population dynamics of such a game are not sufficiently understood. On the other hand, existing models of reputation-based cooperation, also known as indirect reciprocity, are based on the symmetric donation game. We analyze the trust game with two fixed roles, where trustees (i.e., sellers) but not investors (i.e., buyers) possess reputation scores. We study the equilibria and the replicator dynamics of the game. We show that the reputation mechanism enables cooperation between unacquainted buyers and sellers under fairly generous conditions, even when such a cooperative equilibrium coexists with an asocial equilibrium in which buyers do not buy and sellers cheat. In addition, we show that not many buyers may care about the seller's reputation under cooperative equilibrium. Buyers' trusting behavior and sellers' reputation-driven cooperative behavior coevolve to alleviate the social dilemma., Comment: 5 figures

Humans and other animals can adapt their social behavior in response to environmental cues including the feedback obtained through experience. Nevertheless, the effects of the experience-based learning of players in evolution and maintenance of cooperation in social dilemma games remain relatively unclear. Some previous literature showed that mutual cooperation of learning players is difficult or requires a sophisticated learning model. In the context of the iterated Prisoner's Dilemma, we numerically examine the performance of a reinforcement learning model. Our model modifies those of Karandikar et al. (1998), Posch et al. (1999), and Macy and Flache (2002) in which players satisfice if the obtained payoff is larger than a dynamic threshold. We show that players obeying the modified learning mutually cooperate with high probability if the dynamics of threshold is not too fast and the association between the reinforcement signal and the action in the next round is sufficiently strong. The learning players also perform efficiently against the reactive strategy. In evolutionary dynamics, they can invade a population of players adopting simpler but competitive strategies. Our version of the reinforcement learning model does not complicate the previous model and is sufficiently simple yet flexible. It may serve to explore the relationships between learning and evolution in social dilemma situations., Comment: 7 figures