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At least 379 records · Page 21

Quantum Computing for Neutrino-Nucleus Scattering

Neutrino-nucleus cross section uncertainties are expected to be a dominant systematic in future accelerator neutrino experiments. The cross sections are determined by the linear response of the nucleus to the weak interactions of the neutrino, and are dominated by energy and distance scales of the order of the separation between nucleons in the nucleus. These response functions are potentially an important early physics application of quantum computers. Here we present an analysis of the resources required and their expected scaling for scattering cross section calculations. The current estimates of Trotter steps needed to achieve an energy resolution of 10 MeV and the number of CNOT gates for analyzing Ar40 highlights the need for significant improvements in algorithms. We also examine simple small-scale neutrino-nucleus models on modern quantum hardware. In this paper, we use variational methods to obtain the ground state of a three nucleon system (the triton) and then implement the relevant time evolution. To tame the errors in present-day NISQ devices, we explore the use of different error-mitigation techniques to increase the fidelity of the calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Estimating the energy threshold of phonon-mediated superconducting qubit detectors operated in an energy-relaxation sensing scheme

In recent years, the lack of a conclusive detection of weakly interacting massive particle dark matter at the 10 GeV/c 2 mass scale and above has encouraged development of low-threshold detector technology aimed at probing lighter dark matter candidates. Detectors based on Cooper-pair-breaking sensors have emerged as a promising avenue for this detection due to the low (meV-scale) energy required for breaking a Cooper pair in most superconductors. Among them, devices based on superconducting qubits are interesting candidates for sensing due to their observed sensitivity to broken Cooper pairs. Here, we have developed an end-to-end G 4 CMP -based simulation framework and have used it to evaluate performance metrics of qubit-based devices operating in a gate-based “energy relaxation” readout scheme, akin to those used in recent studies of qubit sensitivity to ionizing radiation. We find that for this readout scheme, the qubit acts as a phonon sensor with an energy threshold ranging down to ≃ 0.4 eV for near-term performance parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

On the Jet–Ejecta Interaction in 3D GRMHD Simulations of a Binary Neutron Star Merger Aftermath

Short γ-ray burst (sGRB) jets form in the aftermath of a neutron star merger, drill through disk winds and dynamical ejecta, and extend over four to five orders of magnitude in distance before breaking out of the ejecta. We present the first 3D general-relativistic magnetohydrodynamic sGRB simulations to span this enormous scale separation. They feature three possible outcomes: jet+cocoon, cocoon, and neither. Typical sGRB jets break out of the dynamical ejecta if (i) the bound ejecta's isotropic equivalent mass along the pole at the time of the BH formation is ≲10 -4 M ⊙ , setting a limit on the delay time between the merger and BH formation, otherwise, the jets perish inside the ejecta and leave the jet-inflated cocoon to power a low-luminosity sGRB; (ii) the postmerger remnant disk contains a strong large-scale vertical magnetic field, ≳1015 G; and (iii) if the jets are weak (≲10 50 erg), the ejecta's isotropic equivalent mass along the pole must be small (≲10 -2 M ⊙ ). Generally, the jet structure is shaped by the early interaction with disk winds rather than the dynamical ejecta. As long as our jets break out of the ejecta, they retain a significant magnetization (≲1), suggesting that magnetic reconnection is a fundamental property of sGRB emission. The angular structure of the outflow isotropic equivalent energy after breakout consistently features a flat core followed by a steep power-law distribution (slope ≳3), similar to hydrodynamic jets. In the cocoon-only outcome, the dynamical ejecta broadens the outflow angular distribution and flattens it (slope ~1.5).

Jets↗

Qualitative properties of mathematical model for data flow

In this paper, properties of a recently proposed mathematical model for data flow in large-scale asynchronous computer systems are analyzed. In particular, the existence of special weak solutions based on propagating fronts is established. Qualitative properties of these solutions are investigated, both theoretically and numerically.

97 MATHEMATICS AND COMPUTING↗

Liquid-free covalent reinforcement of carbon nanotube dry-spun yarns and free-standing sheets

Carbon nanotubes (CNTs) possess exceptional mechanical properties, surpassing stiffness and strength metrics of common materials such as steel alloys by 100× at the nanoscale. However, when myriads of individual CNTs are bundled together into macroscopic ensembles like fibers or sheets, the result is a 100-fold drop in strength compared to its individual components. Here we present a general strategy aimed to close this gap in property scaling. By using vapor-phase polymerization of a crosslinkable polymer, we reinforced the weak interlinkages among individual CNTs within both yarns and sheets to promote a better transference of mechanical load across the structure. Furthermore, after the treatment, dry-spun, low-density 2.3 μm thin yarns increased their elastic moduli by at least 300%, and free-standing CNT sheets exhibited a 10× boost. In-situ synchrotron small-angle X-ray scattering revealed that polymer-reinforced yarns undergo limited CNT bundle rearrangement when subjected to tensile loads compared to pristine yarns. This evidence supports the hypothesis that the polymer hinders CNTs slippage, the root cause of the poor scaling of mechanical properties in these materials. While we demonstrated this reinforcement method for CNT structures, it is not specific to CNTs and could be used in a wide variety of other hierarchical nanostructured ensembles.

36 MATERIALS SCIENCE↗

Transitioning from Stage-III to Stage-IV: Cosmology from galaxy×CMB lensing and shear×CMB lensing (Final Report for Grant SC0021429 "Cosomology with Galaxy and CMB Surveys: Mitigating Systematic Effects Through Combining Datasets")

We examine the cosmological constraining power from two cross-correlation probes between galaxy and cosmic microwave background (CMB) surveys: the cross-correlation of lens galaxy density with CMB lensing convergence $\langle δ_g$$^κ\text{CMB}\rangle$, and source galaxy weak lensing shear with CMB lensing convergence $\langle^{γκ}$$_{\text{CMB}}\rangle$. These two cross-correlation probes provide an independent cross-check of other large-scale structure constraints and are insensitive to galaxy-only or CMB-only systematic effects. In addition, when combined with other large-scale structure probes, the cross-correlations can break degeneracies in cosmological and nuisance parameters, improving both the precision and robustness of the analysis. In this work, we study how the constraining power of $\langle δ_g$$^κ\text{CMB}\rangle + \langle^{γκ}$$_{\text{CMB}}\rangle$ changes from Stage-III (ongoing) to Stage-IV (future) surveys. Given the flexibility in selecting the lens galaxy sample, we also explore systematically the impact on cosmological constraints when we vary the redshift range and magnitude limit of the lens galaxies using mock galaxy catalogs. We find that in our setup, the contribution to cosmological constraints from $\langle δ_g$$^κ\text{CMB}\rangle$ and $\langle^{γκ}$$_{\text{CMB}}\rangle$ are comparable in the Stage-III data sets; but in Stage-IV surveys, the noise in$\langle δ_g$$^κ\text{CMB}\rangle$ becomes subdominant to cosmic variance, preventing $\langle δ_g$$^κ\text{CMB}\rangle$ to further improve the constraints. This implies that to maximize the cosmological constraints from future $\langle δ_g$$^κ\text{CMB}\rangle$ + $\langle^{γκ}$$_{\text{CMB}}\rangle$ analyses, we should focus more on the requirements on$^{γκ}$$_{\text{CMB}}\rangle$ instead of$\langle δ_g$$^κ\text{CMB}\rangle$. Furthermore, the selection of the lens sample should be optimized in terms of our ability to characterize its redshift or galaxy bias instead of its number density.

79 ASTRONOMY AND ASTROPHYSICS↗

Superclustering with the Atacama Cosmology Telescope and Dark Energy Survey. II. Anisotropic Large-scale Coherence in Hot Gas, Galaxies, and Dark Matter

Statistics that capture the directional dependence of the baryon distribution in the cosmic web enable unique tests of cosmology and astrophysical feedback. We use constrained oriented stacking of thermal Sunyaev–Zel’dovich (tSZ) maps to measure the anisotropic distribution of hot gas 2.5–40 Mpc away from galaxy clusters embedded in massive filaments and superclusters. The cluster selection and orientation (at a scale of ∼15 Mpc) use Dark Energy Survey (DES) Year 3 data, while expanded tSZ maps from the Atacama Cosmology Telescope Data Release 6 enable a ∼3× more significant measurement of the extended gas compared to the technique’s proof-of-concept. Decomposing stacks into cosine multipoles of order m , we detect a dipole ( m = 1) and quadrupole ( m = 2) at 8σ–10σ, as well as evidence for m = 4 signal at up to 6σ, indicating sensitivity to late-time non-Gaussianity. We compare to Cardinal simulations with spherical gas models pasted onto dark matter halos. The fiducial tSZ data can discriminate between two models that deplete pressure differently in low-mass halos (mimicking astrophysical feedback), preferring higher average pressure in extended structures. However, uncertainty in the amount of cosmic infrared background contamination reduces the constraining power. Additionally, we apply the technique to DES galaxy density and weak lensing to study for the first time their oriented relationships with tSZ. In the tSZ-to-lensing relation, averaged on 7.5 Mpc (transverse) scales, we observe dependence on redshift but not shape or radial distance. Thus, on large scales, the superclustering of gas pressure, galaxies, and total matter is coherent in shape and extent.

79 ASTRONOMY AND ASTROPHYSICS↗

Beyond fragmented dopant dynamics in quantum spin lattices: Robust localization and non-Gaussian diffusion

The motion of dopants in magnetic spin lattices has received tremendous attention for at least four decades due to its connection to high-temperature superconductivity. Despite these efforts, we lack a complete understanding of their behavior, especially out of the equilibrium and at nonzero temperatures. In this paper, we take a significant step towards a much deeper understanding based on state-of-the-art matrix-product-state calculations. In particular, we investigate the nonequilibrium dynamics of a dopant in two-leg 𝑡−𝐽 ladders with antiferromagnetic XXZ spin interactions. In the Ising limit, we find that the dopant is localized for all investigated nonzero temperatures due to an emergent disordered potential, with a localization length controlled by the underlying correlation length of the spin lattice, which increases exponentially with decreasing temperature. The dopant, hereby, only delocalizes asymptotically in the zero temperature limit. This greatly generalizes the localization effect discovered recently in Hilbert space fragmented models [Phys. Rev. Res. 6, 023325 (2024), SciPost Phys. Core 7, 054 (2024)]. In the presence of spin-exchange processes at rate 𝛼, the dopant diffuses with a diffusion coefficient, 𝐷 ℎ , depending nonmonotonically on 𝛼. It initially increases linearly as 𝐷 ℎ ∝ 𝛼 for 𝛼 ≪ 1 before dropping off as 𝛼 −1 for 𝛼 > 1. Moreover, we show that the underlying spin dynamics at infinite temperature behaves qualitatively the same, albeit with important quantitative differences. We substantiate these findings by showing that the dynamics features self-similar scaling behavior, which strongly deviates from the Gaussian behavior of regular diffusion, especially for weak spin exchange. Finally, we show that the diffusion coefficient 𝐷 ℎ follows an Arrhenius relation at high temperatures, whereby it is exponentially suppressed upon cooling.

Anomalous diffusion↗

Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method

Abstract An interface-modified reproducing kernel particle method (IM-RKPM) is introduced in this work to allow for a direct model construction from image pixels of heterogeneous polycrystalline Li-ion battery microstructures. The interface-modified reproducing kernel (IM-RK) approximation is constructed through scaling of a kernel function by a regularized distance function in conjunction with strategic placement of interface node locations. This leads to RK shape functions with either weak or strong discontinuities across material interfaces, suitable for modeling various interface mechanics. With the placement of a triple junction node and distance-based scaling of kernel functions, the resulting IM-RK shape function also possesses proper discontinuities at the triple junctions. This IM-RK approximation effectively remedies the well-known Gibb’s oscillation in the smooth approximation of discontinuities. Different from the conventional meshfree approaches for interface discontinuities, this IM-RK approach is done without additional degrees of freedom associated with the enrichment functions, and it is formulated with the standard procedures in the RK shape function construction. This work focuses on identifying the accuracy and convergence properties of IM-RKPM for modeling the coupled electro-chemo-mechanical system. A linear patch test is formulated and numerically tested for the electro-chemo-mechanical coupled problem with a Butler–Volmer boundary condition representing the physical conditions in Li-ion battery microstructures. This is followed by verification of the optimal rates of convergence of IM-RKPM for solving the coupled problem with higher order solutions. The image-based modeling of Li-ion battery microstructures in the numerical examples demonstrates the applicability of the proposed method to realistic Li-ion battery materials modeling.

25 ENERGY STORAGE↗

Non-linear enhancement of ultrafast X-ray diffraction through transient resonances

Diffraction-before-destruction imaging with ultrashort X-ray pulses can visualize non-equilibrium processes, such as chemical reactions, with sub-femtosecond precision in the native environment. Here, a nanospecimen diffracts a single X-ray flash before it disintegrates. The sample structure can be reconstructed from the coherent diffraction image (CDI). State-of-the-art X-ray snapshots lack high spatial resolution because of weak diffraction signal. Bleaching effects from photo-ionization significantly restrain image brightness scaling. We find that non-linear transient ion resonances can overcome this barrier if X-ray laser pulses are shorter than in most experiments. We compared snapshots from individual ≈ 100 nm Xe nanoparticles as a function of pulse duration and incoming X-ray fluence. Our experimental results and Monte Carlo simulations suggest that transient resonances can increase ionic scattering cross sections significantly beyond literature values. This provides a novel avenue towards substantial improvement of the spatial resolution in CDI in combination with sub-femtosecond temporal precision at the nanoscale.

47 OTHER INSTRUMENTATION↗

Anomalous Hall effect in the weak-itinerant ferrimagnet FeCr 2 Te 4

In this study, we carried out a comprehensive study of electronic transport, thermal, and thermodynamic properties in Fe Cr 2 Te 4 single crystals. It exhibits bad-metallic behavior and anomalous Hall effect (AHE) below a weak-itinerant paramagnetic-to-ferrimagnetic transition T c ~ 123 K. The linear scaling between the anomalous Hall resistivity ρ x y and the longitudinal resistivity ρ x x implies that the AHE in Fe Cr 2 Te 4 is most likely dominated by an extrinsic skew-scattering mechanism rather than an intrinsic KL or an extrinsic side-jump mechanism, which is supported by our Berry phase calculations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Disruption of Dark Matter Minihalos in the Milky Way Environment: Implications for Axion Miniclusters and Early Matter Domination

Many theories of dark matter beyond the weakly interacting massive particles paradigm feature an enhanced matter power spectrum on subparsec scales, leading to the formation of dense dark matter minihalos. Future local observations are promising to search for and constrain such substructures. The survival probability of these dense minihalos in the Milky Way environment is crucial for interpreting local observations. In this work, we investigate two environmental effects: stellar disruption and (smooth) tidal disruption. These two mechanisms are studied using semianalytic models and idealized N-body simulations. For stellar disruption, we perform a series of N-body simulations of isolated minihalo–star encounters to test and calibrate analytic models of stellar encounters before applying the model to the realistic Milky Way disk environment. For tidal disruption, we perform N-body simulations to confirm the effectiveness of the analytic treatment. Finally, we propose a framework to combine the hierarchical assembly and infall of minihalos to the Milky Way with the late-time disruption mechanisms. We make predictions for the mass functions of minihalos in the Milky Way. The mass survival fraction (at M$_{mh}$ ≥ 10$^{−12}$M$_{⊙}$) of dense dark matter minihalos, e.g., for axion miniclusters and minihalos from early matter domination, is ∼60% with the relatively low-mass, compact population surviving. The survival fraction is insensitive to the detailed model parameters. We discuss various implications of the framework and future direct detection prospects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

54 ENVIRONMENTAL SCIENCES↗

Multi-component Dark Matter and small scale structure formation

We consider the evolution of non-thermal dark matter perturbations in models which contain both Weakly Interacting Massive Particles (WIMPs) and axions. Using constraints from existing observations we examine the percentage of WIMPs and axions that may comprise the cosmological dark matter budget in models with an Early Matter Dominated Epoch (EMDE) — where entropy production is important. After carefully tracking the thermal evolution of the various species by solving the Boltzmann equations, we consider the enhancement of perturbations that may have led to early structure formation for axions and WIMPs. We investigate the impact of enhanced perturbations on the parameter space of both species, after imposing existing constraints from indirect detection experiments. Given these constraints we establish the feasibility of axions to form miniclusters in the early universe in EMDEs for a given percentage of allowed WIMPs. We find that EMDEs with low reheat temperatures near the BBN limit are preferred for axion minicluster formation. When the EMDE is caused by string moduli, the WIMP contribution to the relic density is set by the moduli branching to dark matter at the level of ≲ $\mathcal{O}$ (10 −4 ).

79 ASTRONOMY AND ASTROPHYSICS↗

Optimizing Simulation Parameters for Weak Lensing Analyses Involving Non-Gaussian Observables

We performed a series of numerical experiments to quantify the sensitivity of the predictions for weak lensing statistics obtained in ray-tracing dark matter (DM)-only simulations, to two hyper-parameters that influence the accuracy as well as the computational cost of the predictions: the thickness of the lens planes used to build past light cones and the mass resolution of the underlying DM simulation. The statistics considered are the power spectrum (PS) and a series of non-Gaussian observables, including the one-point probability density function, lensing peaks, and Minkowski functionals. Counterintuitively, we find that using thin lens planes (< 60 h {sup −1} Mpc on a 240 h {sup −1} Mpc simulation box) suppresses the PS over a broad range of scales beyond what would be acceptable for a survey comparable to the Large Synoptic Survey Telescope (LSST). A mass resolution of 7.2 × 10{sup 11} h {sup −1} M {sub ⊙} per DM particle (or 256{sup 3} particles in a (240 h {sup −1} Mpc){sup 3} box) is sufficient to extract information using the PS and non-Gaussian statistics from weak lensing data at angular scales down to 1′ with LSST-like levels of shape noise.

79 ASTRONOMY AND ASTROPHYSICS↗

Near-cryogenic direct air capture using adsorbents

Direct air capture (DAC) of CO 2 is a key component in the portfolio of negative emissions technologies for mitigating global warming. However, even with the most potent amine sorbents, large-scale DAC deployment remains limited by high energy and capital costs. Recently, adsorbents relying on weak interactions with CO 2 have emerged as a potential alternative, thanks to their rapid adsorption kinetics and superior long-term stability, particularly under sub-ambient conditions (∼253 K). Despite these advantages, their use is hindered by the need for a water-removal process, location-specific constraints, and insufficient working capacity even in cold climates. In this study, we hypothesized that further reducing the adsorption temperature to a near-cryogenic range (160–220 K) could enable cost-effective DAC by utilizing the full potential of physisorbents. We primarily consider integrating DAC with a relatively untapped source of cold energy—liquified natural gas (LNG) regasification—to perform near-cryogenic DAC. From large-scale molecular simulations, Zeolite 13X and CALF-20 were identified as promising candidates. These materials were subsequently examined through experiments, including breakthrough analyses at 195 K. Their high CO 2 sorption capacity (4.5–5.5 mmol g −1 ), combined with a low desorption enthalpy and robust long-term stability, led to a threefold reduction in the levelized cost of capture (down to 68.2 USD per tonne CO 2 ). Estimates of the global LNG regasification resource suggest that LNG–DAC coupling could potentially enable the capture of 103–142 megatonnes of CO 2 annually as of 2050.

Kim, Seo-Yul [Georgia Institute of Technology, Atl↗

Neural network acceleration of large-scale structure theory calculations

Here, we make use of neural networks to accelerate the calculation of power spectra required for the analysis of galaxy clustering and weak gravitational lensing data. For modern perturbation theory codes, evaluation time for a single cosmology and redshift can take on the order of two seconds. In combination with the comparable time required to compute linear predictions using a Boltzmann solver, these calculations are the bottleneck for many contemporary large-scale structure analyses. Here, we construct neural network-based surrogate models for Lagrangian perturbation theory (LPT) predictions of matter power spectra, real and redshift space galaxy power spectra, and galaxy-matter cross power spectra that attain ~ 0.1% (at one sigma) accuracy over a broad range of scales in a ωCDM parameter space. The neural network surrogates can be evaluated in approximately one millisecond, a factor of 1000 times faster than the full Boltzmann code and LPT computations. In a simulated full-shape redshift space galaxy power spectrum analysis, we demonstrate that the posteriors obtained using our surrogates are accurate compared to those obtained using the full LPT model. We make our surrogate models public at https://github.com/sfschen/EmulateLSS, so that others may take advantage of the speed gains they provide to enable rapid iteration on analysis settings, something that is essential in complex contemporary large-scale structure analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

Finding evidence for inflation and the origin of galactic magnetic fields with CMB surveys

The origin of the μG magnetic fields observed in galaxies is unknown. One promising scenario is that magnetic fields generated during inflation, larger than 0.1 nG on Mpc scales, were adiabatically compressed to μG strengths in galaxies during structure formation. Thus, detecting a scale-invariant primordial magnetic field (PMF) above 0.1 nG on Mpc scales just after recombination would indicate an inflationary origin of galactic magnetic fields. Furthermore, this would also provide compelling evidence that inflation occurred since only an inflationary mechanism could generate such a strong, scale-invariant magnetic field on Mpc scales. In contrast, constraining the scale-invariant PMF strength to be below 0.1 nG would imply an inflationary scenario is not the primary origin, since such weak PMFs cannot be amplified enough via adiabatic compression to produce the strength of the galactic fields we observe today. We find that measurements of anisotropic birefringence by future CMB surveys will be able to improve the sensitivity to Mpc-scale inflationary PMFs by an order of magnitude, and, in particular, that CMB-HD would lower the upper bound to 0.072 nG at the 95% C.L., which is below the critical 0.1 nG threshold for ruling out a purely inflationary origin. If inflationary PMFs exist, we find that a CMB-HD survey would be able to detect them with about 3σ significance or higher, providing evidence for inflation itself.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗