Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience. Existing approaches for fMRI analysis utilize hand-crafted features, but the process of feature extraction risks losing essential information in fMRI scans. To address this challenge, we present SwiFT (Swin 4D fMRI Transformer), a Swin Transformer architecture that can learn brain dynamics directly from fMRI volumes in a memory and computation-efficient manner. SwiFT achieves this by implementing a 4D window multi-head self-attention mechanism and absolute positional embeddings. We evaluate SwiFT using multiple large-scale resting-state fMRI datasets, including the Human Connectome Project (HCP), Adolescent Brain Cognitive Development (ABCD), and UK Biobank (UKB) datasets, to predict sex, age, and cognitive intelligence. Our experimental outcomes reveal that SwiFT consistently outperforms recent state-of-the-art models. Furthermore, by leveraging its end-to-end learning capability, we show that contrastive loss-based self-supervised pre-training of SwiFT can enhance performance on downstream tasks. Additionally, we employ an explainable AI method to identify the brain regions associated with sex classification. To our knowledge, SwiFT is the first Swin Transformer architecture to process dimensional spatiotemporal brain functional data in an end-to-end fashion. Our work holds substantial potential in facilitating scalable learning of functional brain imaging in neuroscience research by reducing the hurdles associated with applying Transformer models to high-dimensional fMRI.

In very clean solid-state systems, where carrier-carrier interactions dominate over any other scattering mechanisms, the flow of electrons can be described within a hydrodynamic framework. In these cases, analogues of viscous fluid phenomena have been experimentally observed. However, experimental studies of electron hydrodynamics have so far been limited to the low velocity, linear response regime. At velocities approaching the speed of sound, the electronic fluid is expected to exhibit compressible behaviour where nonlinear effects and discontinuities such as shocks and choked flow have long been predicted. This compressible regime remains unexplored in electronic systems, despite its promise of strongly nonlinear flow phenomena. Here, we demonstrate compressible electron flow in bilayer graphene through an electronic de Laval nozzle, a structure that accelerates charge carriers past the electronic speed of sound, until they slow down suddenly in a shock. Discontinuities in transport measurements and local flattening of potential in Kelvin probe measurements are consistent with a viscous electron shock front and the presence of supersonic electron flow, and are not consistent with Ohmic or ballistic flow. Breaking the sound barrier in electron liquids opens the door for novel, intrinsically nonlinear electronic devices beyond the paradigm of incompressible flow.

The LBNF/DUNE CDR describes the proposed physics program and experimental design at the conceptual design phase. Volume 2, entitled The Physics Program for DUNE at LBNF, outlines the scientific objectives and describes the physics studies that the DUNE collaboration will perform to address these objectives. The long-baseline physics sensitivity calculations presented in the DUNE CDR rely upon simulation of the neutrino beam line, simulation of neutrino interactions in the far detector, and a parameterized analysis of detector performance and systematic uncertainty. The purpose of this posting is to provide the results of these simulations to the community to facilitate phenomenological studies of long-baseline oscillation at LBNF/DUNE. Additionally, this posting includes GDML of the DUNE single-phase far detector for use in simulations. DUNE welcomes those interested in performing this work as members of the collaboration, but also recognizes the benefit of making these configurations readily available to the wider community.

We discuss two methods that, through a combination of cyclically gluing copies of a given $n$-party boundary state in AdS/CFT and a canonical purification, creates a bulk geometry that contains a boundary homologous minimal surface with area equal to 2 or 4 times the $n$-party entanglement wedge cross-section, depending on the parity of the party number and choice of method. The areas of the minimal surfaces are each dual to entanglement entropies that we define to be candidates for the $n$-party reflected entropy. In the context of AdS$_3$/CFT$_2$, we provide a boundary interpretation of our construction as a multiboundary wormhole, and conjecture that this interpretation generalizes to higher dimensions.

Spanning multiple scales-from macroscopic anatomy down to intricate microscopic architecture-the human brain exemplifies a complex system that demands integrated approaches to fully understand its complexity. Yet, mapping nonlinear relationships between these scales remains challenging due to technical limitations and the high cost of multimodal Magnetic Resonance Imaging (MRI) acquisition. Here, we introduce Macro2Micro, a deep learning framework that predicts brain microstructure from macrostructure using a Generative Adversarial Network (GAN). Grounded in the scale-free, self-similar nature of brain organization-where microscale information can be inferred from macroscale patterns-Macro2Micro explicitly encodes multiscale brain representations into distinct processing branches. To further enhance image fidelity and suppress artifacts, we propose a simple yet effective auxiliary discriminator and learning objective. Our results show that Macro2Micro faithfully translates T1-weighted MRIs into corresponding Fractional Anisotropy (FA) images, achieving a 6.8% improvement in the Structural Similarity Index Measure (SSIM) compared to previous methods, while preserving the individual neurobiological characteristics.

We investigate the relationship between superselection rules and quantum error correcting codes. We demonstrate that the existence of a superselection rule implies the Knill-Laflamme condition in quantum error correction. As an example, we examine quantum chromodynamics through the lens of quantum error correction, where the proton and neutron states in the model are explored as different superselection sectors that protect logical information. Finally we comment on topological quantum error correcting codes and supersymmetric quantum field theory within this framework.

We establish an equivalence between non-isometry of quantum codes and state-dependence of operator reconstruction, and discuss implications of this equivalence for holographic duality. Specifically, we define quantitative measures of non-isometry and state-dependence and describe bounds relating these quantities. In the context of holography we show that, assuming known gravitational path integral results for overlaps between semiclassical states, non-isometric bulk-to-boundary maps with a trivial kernel are approximately isometric and bulk reconstruction approximately state-independent. In contrast, non-isometric maps with a non-empty kernel always lead to state-dependent reconstruction. We also show that if a global bulk-to-boundary map is non-isometric, then there exists a region in the bulk which is causally disconnected from the boundary. Finally, we conjecture that, under certain physical assumptions for the definition of the Hilbert space of effective field theory in AdS space, the presence of a global horizon implies a non-isometric global bulk-to-boundary map.

The three-flavor neutrino oscillation model describes the well-studied phenomenon of neutrinos produced in association with one charged lepton: electron, muon, or tau, and then later detected in association with a possibly different charged lepton. While somewhat surprising, the firm experimental discovery of the phenomenon in the late 1990s and early 2000s has lead to a revolution in particle physics as the nature of neutrinos has been explored with heightened vigor ever since. At the core of the phenomenon are the six neutrino oscillation parameters. These parameters are fundamental and not predicted from anything else in our model of particle physics. At the time of writing this chapter, many of them have been measured, but several key questions remain that are to be answered by neutrino oscillations themselves. These questions have motivated some of the largest and most involved particle physics experiments built to date. This chapter will develop the basics of neutrino oscillation theory and build intuition for the role of the oscillation parameters and how they are measured, as well as the important role of the matter effect in neutrino oscillations.

Proximity-induced superconductivity in a 3D topological insulator represents a new avenue for observing zero-energy Majorana fermions inside vortex cores. Relatively small gaps and low transition temperatures of conventional s-wave superconductors put the hard constraints on these experiments. Significantly larger gaps and higher transition temperatures in cuprate superconductors might be an attractive alternative to considerably relax these constraints, but it is not clear whether the proximity effect would be effective in heterostructures involving cuprates and topological insulators. Here, we present angle-resolved photoemission studies of thin Bi2Se3 films grown in-situ on optimally doped Bi2Sr2CaCu2O8 substrates that show the absence of proximity-induced gaps on the surfaces of Bi2Se3 films as thin as a 1.5 quintuple layer. These results suggest that the superconducting proximity effect between a cuprate superconductor and a topological insulator is strongly suppressed, likely due to a very short coherence length along the c-axis, incompatible crystal and pairing symmetries at the interface, small size of the topological surface state Fermi surface and adverse effects of a strong spin-orbit coupling in the topological material.

We apply the bit thread formulation of holographic entanglement entropy to reduced states describing only the geometry contained within an entanglement wedge. We argue that a certain optimized bit thread configuration, which we construct, gives a purification of the reduced state to a full holographic state obeying a precise set of conditional mutual information relations. When this purification exists, we establish, under certain assumptions, the conjectured $E_P = E_W$ relation equating the entanglement of purification with the area of the minimal cross section partitioning the bulk entanglement wedge. Along the way, we comment on minimal purifications of holographic states, geometric purifications, and black hole geometries.

Kramers degeneracy is one fundamental embodiment of the quantum mechanical nature of particles with half-integer spin under time reversal symmetry. Under the chiral and noncentrosymmetric achiral crystalline symmetries, Kramers degeneracy emerges respectively as topological quasiparticles of Weyl fermions and Kramers nodal lines (KNLs), anchoring the Berry phase-related physics of electrons. However, an experimental demonstration for ideal KNLs well isolated at the Fermi level is lacking. Here, we establish a class of noncentrosymmetric achiral intercalated transition metal dichalcogenide superconductors with large Ising-type spin-orbit coupling, represented by In$_x$TaS$_2$, to host an ideal KNL phase. We provide evidence from angle-resolved photoemission spectroscopy with spin resolution, angle-dependent quantum oscillation measurements, and ab-initio calculations. Our work not only provides a realistic platform for realizing and tuning KNLs in layered materials, but also paves the way for exploring the interplay between KNLs and superconductivity, as well as applications pertaining to spintronics, valleytronics, and nonlinear transport.

Recently, the first ever lattice computation of the $\gamma W$-box radiative correction to the rate of the semileptonic pion decay allowed for a reduction of the theory uncertainty of that rate by a factor of $\sim3$. A recent dispersion evaluation of the $\gamma W$-box correction on the neutron also led to a significant reduction of the theory uncertainty, but shifted the value of $V_{ud}$ extracted from the neutron and superallowed nuclear $\beta$ decay, resulting in a deficit of the CKM unitarity in the top row. A direct lattice computation of the $\gamma W$-box correction for the neutron decay would provide an independent cross-check for this result but is very challenging. Before those challenges are overcome, we propose a hybrid analysis, converting the lattice calculation on the pion to that on the neutron by a combination of dispersion theory and phenomenological input. The new prediction for the universal radiative correction to free and bound neutron $\beta$-decay reads $\Delta_R^V=0.02477(24)$, in excellent agreement with the dispersion theory result $\Delta_R^V=0.02467(22)$. Combining with other relevant information, the top-row CKM unitarity deficit persists.

We present a magneto-infrared spectroscopy study on a newly identified three-dimensional (3D) Dirac semimetal ZrTe$_5$. We observe clear transitions between Landau levels and their further splitting under magnetic field. Both the sequence of transitions and their field dependence follow quantitatively the relation expected for 3D \emph{massless} Dirac fermions. The measurement also reveals an exceptionally low magnetic field needed to drive the compound into its quantum limit, demonstrating that ZrTe$_5$ is an extremely clean system and ideal platform for studying 3D Dirac fermions. The splitting of the Landau levels provides a direct and bulk spectroscopic evidence that a relatively weak magnetic field can produce a sizeable Zeeman effect on the 3D Dirac fermions, which lifts the spin degeneracy of Landau levels. Our analysis indicates that the compound evolves from a Dirac semimetal into a topological line-node semimetal under current magnetic field configuration.

Detector counting rate nonlinearity, though a known problem, is commonly ignored in the analysis of angle resolved photoemission spectroscopy where modern multichannel electron detection schemes using analog intensity scales are used. We focus on a nearly ubiquitous "inverse saturation" nonlinearity that makes the spectra falsely sharp and beautiful. These artificially enhanced spectra limit accurate quantitative analysis of the data, leading to mistaken spectral weights, Fermi energies, and peak widths. We present a method to rapidly detect and correct for this nonlinearity. This algorithm could be applicable for a wide range of nonlinear systems, beyond photoemission spectroscopy.

We report on the development of the HEC2 (High Energy Compression and Current) charge breeder, a possible high performance successor to REXEBIS at ISOLDE. The new breeder would match the performance of the HIE-ISOLDE linac upgrade and make full use of the possible installation of a storage ring at ISOLDE (the TSR@ISOLDE initiative [1]). Dictated by ion beam acceptance and capacity requirements, the breeder features a 2-3.5 A electron beam. In many cases very high charge states, including bare ions up to Z=70 and Li/Na-like up to Z=92 could be requested for experiments in the storage ring, therefore, electron beam energies up to 150 keV are required. The electron-beam current density needed for producing ions with such high charge states at an injection rate into TSR of 0.5-1 Hz is between 10 and 20 kA/cm2, which agrees with the current density needed to produce A/q<4.5 ions for the HIE-ISOLDE linac with a maximum repetition rate of 100 Hz. The first operation of a prototype electron gun with a pulsed electron beam of 1.5 A and 30 keV was demonstrated in a joint experiment with BNL [2]. In addition, we report on further development aiming to achieve CW operation of an electron beam having a geometrical transverse ion-acceptance matching the injection of 1+ ions (11.5 {\mu}m), and an emittance/energy spread of the extracted ion beam matching the downstream mass separator and RFQ (0.08 {\mu}m normalized / +/- 1% ).

Magnetic kagome materials provide a fascinating playground for exploring the interplay of magnetism, correlation and topology. Many magnetic kagome systems have been reported including the binary FemXn (X=Sn, Ge; m:n = 3:1, 3:2, 1:1) family and the rare earth RMn6Sn6 (R = rare earth) family, where their kagome flat bands are calculated to be near the Fermi level in the paramagnetic phase. While partially filling a kagome flat band is predicted to give rise to a Stoner-type ferromagnetism, experimental visualization of the magnetic splitting across the ordering temperature has not been reported for any of these systems due to the high ordering temperatures, hence leaving the nature of magnetism in kagome magnets an open question. Here, we probe the electronic structure with angle-resolved photoemission spectroscopy in a kagome magnet thin film FeSn synthesized using molecular beam epitaxy. We identify the exchange-split kagome flat bands, whose splitting persists above the magnetic ordering temperature, indicative of a local moment picture. Such local moments in the presence of the topological flat band are consistent with the compact molecular orbitals predicted in theory. We further observe a large spin-orbital selective band renormalization in the Fe d_xy+d_(x^2-y^2 ) spin majority channel reminiscent of the orbital selective correlation effects in the iron-based superconductors. Our discovery of the coexistence of local moments with topological flat bands in a kagome system echoes similar findings in magic-angle twisted bilayer graphene, and provides a basis for theoretical effort towards modeling correlation effects in magnetic flat band systems.

Quantum computing promises potential for science and industry by solving certain computationally complex problems faster than classical computers. Quantum computing systems evolved from monolithic systems towards modular architectures comprising multiple quantum processing units (QPUs) coupled to classical computing nodes (HPC). With the increasing scale, middleware systems that facilitate the efficient coupling of quantum-classical computing are becoming critical. Through an in-depth analysis of quantum applications, integration patterns and systems, we identified a gap in understanding Quantum-HPC middleware systems. We present a conceptual middleware to facilitate reasoning about quantum-classical integration and serve as the basis for a future middleware system. An essential contribution of this paper lies in leveraging well-established high-performance computing abstractions for managing workloads, tasks, and resources to integrate quantum computing into HPC systems seamlessly.

The effects of radiation damage in silicon photomultipliers (SiPMs) from gamma rays have been measured and compared with the damage produced by neutrons. Several types of MPPCs from Hamamatsu were exposed to gamma rays and neutrons at the Solid State Gamma Ray Irradiation Facility (SSGRIF) at Brookhaven National Lab and the Institute for Nuclear Research (Atomki) in Debrecen, Hungary. The gamma ray exposures ranged from 1 krad to 1 Mrad and the neutron exposures ranged from 10$^8$ n/cm$^2$ to 10$^{12}$ n/cm$^2$. The main effect of gamma ray damage is an increase in the noise and leakage current in the irradiated devices, similar to what is seen from neutron damage, but the level of damage is considerably less at comparable high levels of exposure. In addition, the damage from gamma rays saturates after a few hundred krad, while the damage from neutrons shows no sign of saturation, suggestive of different damage mechanisms in the two cases. The change in optical absorption in the window material of the SiPMs due to radiation was also measured. This study was carried out in order to evaluate the use of SiPMs for particle physics applications with moderate levels of radiation exposures.

Detecting abrupt changes in real-time data streams from scientific simulations presents a challenging task, demanding the deployment of accurate and efficient algorithms. Identifying change points in live data stream involves continuous scrutiny of incoming observations for deviations in their statistical characteristics, particularly in high-volume data scenarios. Maintaining a balance between sudden change detection and minimizing false alarms is vital. Many existing algorithms for this purpose rely on known probability distributions, limiting their feasibility. In this study, we introduce the Kernel-based Cumulative Sum (KCUSUM) algorithm, a non-parametric extension of the traditional Cumulative Sum (CUSUM) method, which has gained prominence for its efficacy in online change point detection under less restrictive conditions. KCUSUM splits itself by comparing incoming samples directly with reference samples and computes a statistic grounded in the Maximum Mean Discrepancy (MMD) non-parametric framework. This approach extends KCUSUM's pertinence to scenarios where only reference samples are available, such as atomic trajectories of proteins in vacuum, facilitating the detection of deviations from the reference sample without prior knowledge of the data's underlying distribution. Furthermore, by harnessing MMD's inherent random-walk structure, we can theoretically analyze KCUSUM's performance across various use cases, including metrics like expected delay and mean runtime to false alarms. Finally, we discuss real-world use cases from scientific simulations such as NWChem CODAR and protein folding data, demonstrating KCUSUM's practical effectiveness in online change point detection.

The ability to reversibly toggle between two distinct states in a non-volatile method is important for information storage applications. Such devices have been realized for phase-change materials, which utilizes local heating methods to toggle between a crystalline and an amorphous state with distinct electrical properties. To expand such kind of switching between two topologically distinct phases requires non-volatile switching between two crystalline phases with distinct symmetries. Here we report the observation of reversible and non-volatile switching between two stable and closely-related crystal structures with remarkably distinct electronic structures in the near room temperature van der Waals ferromagnet Fe$_{5-\delta}$GeTe$_2$. From a combination of characterization techniques we show that the switching is enabled by the ordering and disordering of an Fe site vacancy that results in distinct crystalline symmetries of the two phases that can be controlled by a thermal annealing and quenching method. Furthermore, from symmetry analysis as well as first principle calculations, we provide understanding of the key distinction in the observed electronic structures of the two phases: topological nodal lines compatible with the preserved global inversion symmetry in the site-disordered phase, and flat bands resulting from quantum destructive interference on a bipartite crystaline lattice formed by the presence of the site order as well as the lifting of the topological degeneracy due to the broken inversion symmetry in the site-ordered phase. Our work not only reveals a rich variety of quantum phases emergent in the metallic van der Waals ferromagnets due to the presence of site ordering, but also demonstrates the potential of these highly tunable two-dimensional magnets for memory and spintronics applications.