Study of the decay D s + → K S 0 K S 0 π + and observation of an isovector partner to f 0 ( 1710 )
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Using the entire data sample of 980 fb -1 collected at or near the Y(4S) resonance with the Belle detector operating at the KEKB asymmetric-energy e + e - collider, we report the measurement of the mass, width, and the branching ratios of the Λ c (2625) + charmed baryon. The mass difference between Λ c (2625) + and Λ$^{+}_{c}$ is measured to be M(Λ c (2625) + )-M(Λ$^{+}_{c}$)=341.518±0.006±0.049 MeV/c 2 . The upper limit on the width is measured to be Γ(Λ c (2625) + )<0.52 MeV/c 2 at 90% confidence level. Based on a full Dalitz plot fit, branching ratios with respect to the mode Λ c (2625) + →Λ$^{+}_{c}$π + π - are measured to be $\frac{\mathscr{B}(Λ_c(2625)^+ → Σ^{0}_{c}π^+)} {\mathscr{B}(Λ_c(2625)^+ → ^{+}_{c}π^+π^-)}$ = (5.19±0.23±0.40)% and $\frac{\mathscr{B}(Λ_c (2625)^+ → Σ{_c^+}^+ π^-)}{\mathscr{B}(Λ_c (2625)^+ → Λ{_c^+} π^+π^-)}$ = (5.13±0.26±0.32)%, where the first and second uncertainties are statistical and systematic, respectively. These measurements can be used to further constrain the parameters of the underlying theoretical models.
Some extensions of the Standard Model of particle physics allow for Lorentz invariance and charge-parity-time invariance violations. In the neutrino sector strong constraints have been set by neutrino-oscillation and time-of-flight experiments. However, some Lorentz-invariance-violating parameters are not accessible via these probes. In this work, we focus on the parameters (a$^{(3)}_{of}$)00, (a$^{(3)}_{of}$)10, and (a$^{(3)}_{of}$)11 which would manifest themselves in a nonisotropic β-decaying source as a sidereal oscillation and an overall shift of the spectral endpoint. Based on the data of the first scientific run of the KATRIN experiment, we set the first 90% confidence-level limit on (a$^{(3)}_{of}$)11| of < 0.9 × 10 –6 GeV to 3.7 × 10 –6 GeV, depending on the phase. Furthermore, we derive new constraints on (a$^{(3)}_{of}$)00 and (a$^{(3)}_{of}$)10.
We measure the B0 lifetime and flavor-oscillation frequency using B 0 → D(*) – π + decays collected by the Belle II experiment in asymmetric-energy e + e – collisions produced by the SuperKEKB collider operating at the Υ(4S) resonance. We fit the decay-time distribution of signal decays, where the initial flavor is determined by identifying the flavor of the other B meson in the event. The results, based on 33000 signal decays reconstructed in a data sample corresponding to 190 fb –1 , are τ B 0 = (1.499 ± 0.013 ± 0.008) ps, Δm d = (0.516 ± 0.008 ± 0.005) ps –1 , where the first uncertainties are statistical and the second are systematic. These results are consistent with the world-average values.
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Low-level clouds in the Arctic affect the surface energy budget and vertical transport of heat and moisture. The limited availability of cloud-droplet-forming aerosol particles strongly impacts cloud properties and lifetime. Vertical particle distributions are required to study aerosol–cloud interaction over sea ice comprehensively. This article presents vertically resolved measurements of aerosol particle number concentrations and sizes using tethered balloons. The data were collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition in the summer of 2020. Thirty-four profiles of aerosol particle number concentration were observed in 2 particle size ranges: 12–150 nm (N 12−150 ) and above 150 nm (N >150 ). Concurrent balloon-borne meteorological measurements provided context for the continuous profiles through the cloudy atmospheric boundary layer. Radiosoundings, cloud remote sensing data, and 5-day back trajectories supplemented the analysis. The majority of aerosol profiles showed more particles above the lowest temperature inversion, on average, double the number concentration compared to below. Increased N 12−150 up to 3,000 cm −3 were observed in the free troposphere above low-level clouds related to secondary particle formation. Long-range transport of pollution increased N >150 to 310 cm −3 in a warm, moist air mass. Droplet activation inside clouds caused reductions of N >150 by up to 100%, while the decrease in N 12−150 was less than 50%. When low-level clouds were thermodynamically coupled with the surface, profiles showed 5 times higher values of N 12−150 in the free troposphere than below the cloud-capping temperature inversion. Enhanced N 12−150 and N >150 interacting with clouds were advected above the lowest inversion from beyond the sea ice edge when clouds were decoupled from the surface. Vertically discontinuous aerosol profiles below decoupled clouds suggest that particles emitted at the surface are not transported to clouds in these conditions. It is concluded that the cloud-surface coupling state and free tropospheric particle abundance are crucial when assessing the aerosol budget for Arctic low-level clouds over sea ice.
The main objective of this research grant project was to investigate the physical-chemical processes and properties of particles and partitioning gases that influence gas/particle (G/P) partitioning and timescales for equilibration, to directly determine the conditions under which equilibrium G/P partitioning theory can be applied to secondary organic aerosol (SOA). SOA constitutes a major component of submicron particles in the atmosphere, which have important implications for air quality, human and ecosystem health, radiation balance, and climate; however SOA formation, evolution and losses are not well understood. Use of novel on-line measurements of chemically-speciated partitioning measurements of both gas-phase and particle-phase components was a central component to advancing these scientific goals. The key approach was to conduct environmental chamber studies with systems of increasing complexity to determine G/P partitioning rates and equilibrium states for chemically-speciated SOA components. The project builds on our previous work on gas-wall partitioning that must be understood in order to study G/P partitioning in chambers, and to help extrapolate the results to be atmospherically relevant. The goal was to employ measurements and modeling to systematically determine when G/P partitioning theory accurately describes the distribution of oxidized organic compounds in the gas and aerosol phases, and when and why it does not (e.g., aerosol phase-state kinetic limitations, non-ideal mixing, phase separation, oligomer formation,), for chemical and physical conditions typically found throughout the continental boundary layer.
Fluid and plasma turbulence consists of multi-scale interactions where the energy of the large scales is dissipated through a cascade to the smallest scales set by the microphysics. Turbulence and mixing can be detrimental to system performance, such as in inertial confinement fusion (ICF). Our current understanding of turbulence is mostly derived from studies of incompressible flows, where the intermediate-scaled eddies in the “inertial range” bridge the transfer of energy from the large eddies to the dissipative range, and that there is no communication between eddies of disparate scales. Whether a similar cascade process exists for compressible turbulence, however, remains to be seen; experiments have been limited by diagnostics and supersonic flow facilities. This project has focused on the development of techniques to measure the evolution of flows and microphysical transport properties using particle tracking velocimetry. This project has investigated three main areas: (1) particle-tracking experiments with x-ray radiography, (2) shock-particle interactions, (3) quantifying viscous effects on particles in shocked flows.
With the increase on population the world will depend on renewable sources to meet the increasingly energy needs. Use of lignocellulosic biomass as a renewable source has been proven efficient for conversion to cellulosic ethanol and capable of contributing to achieve the threshold on energy demand while reducing greenhouse gases in 90% when compared with fossil fuels (Wang et al., 2007, 2012). However, the processing of biomass encounters limitations in feeding and flow within biorefineries due to the system plugging by compaction and slurry high yield stress, preventing transport of biomass materials and in some cases unexpected plant shutdowns that results in high operational costs (dos Santos et al., 2021; Ximenes et al., 2021). Different solutions for biomass handling and slurry formation from densified materials like pellets have been studied. Cellulosic biomass residues are typically processed in pretreatment reactors to which acid or base is added (Humbird et al., 2002). Other pretreatments such as liquid hot water (LHW) and steam explosion that act without the addition of chemicals use pressures above the saturation vapor of water, to disrupt biomass structure (Ruiz et al., 2021). Although these methods are widely known, the use of pretreatments like acid digestion and LHW present challenges like waste disposal and could be energy inefficient (Mosier et al., 2005). Alternatively other approaches like enzymatic liquefaction have been applied for biomass transformation into slurries with promising results and without the use of pretreatments (dos Santos et al., 2021). Nevertheless, enzymatic liquefaction implementation faces difficulties due to the recalcitrant properties of biomass, its variability, and the release of enzyme inhibitors. While it has been proven that chemical composition properties in biomass have effects on enzyme inhibition (Huang et al., 2022; Kim et al., 2011; Zhai et al., 2018), hindering the efficiency of the liquefaction, not ample research has been conducted in understanding the physical properties as particle size, porosity, water adsorption retention and their effect in the ability to form a slurry at high solids concentration (Yan et al., 2020). In order to improve lignocellulosic biomass handling and formation of biomass slurries, enzyme assisted liquefaction for slurry creation from corn stover at solids loadings up to 30% is reported in this work. Two different kinds of biomass (pelleted corn stover and cobs) were liquefied in a fed-batch process using commercial enzymes Celluclast 1.5L or Ctec-2 at 1FPU or 3 FPU per gram of dry solids in 10 mM sodium citrate buffer solution (pH 4.8). Pellets were fed into a 1 L stirred bioreactor according to a predefined fed-batch protocol over the first 5 hours until reaching 30% of solids loading. After 6, 24 and 96 hours, samples were taken and characterized with respect to their sugar composition, rheology and water absorption. Successful slurry creation with dramatically reduced yield stress was achieved for corn stover for both assessed enzymes. Yield stresses of 178±7 Pa (3 FPU, Celluclast 1.5L) and 79±6 Pa (3 FPU, Ctec-2) were measured for corn stover at 24 hours, compared to 6,000 Pa for samples without enzyme. Yield stress was 155± 29 Pa (3FPU, Ctec-2) and 257 ± 72 Pa (1 FPU, Celluclast 1.5L) for corn cobs at 24 hours. Yield stress decreased when residence time increased with an enhanced fluidity noted for higher enzyme concentrations. A profile for 6, 24 and 96h of yield stress measurements is presented.
Transformers are the state-of-the-art model architectures and widely used in application areas of machine learning. However the performance of such architectures is less well explored in the ultra-low latency domains where deployment on FPGAs or ASICs is required. Such domains include the trigger and data acquisition systems of the LHC experiments. We present a transformer-based algorithm for jet tagging built with the HGQ2 framework, which is able to produce a model with heterogeneous bitwidths for fast inference on FPGAs, as required in the trigger systems at the LHC experiments. The bitwidths are acquired during training by minimizing the total bit operations as an additional parameter. By allowing a bitwidth of zero, the model is pruned in-situ during training. Using this quantization-aware approach, our algorithm achieves state-of-the-art performance while also retaining permutation invariance which is a key property for particle physics applications. Due to the strength of transformers in representation learning, our work also serves as a stepping stone for the development of a larger foundation model for trigger applications.
Absorption, scattering, and extinction characteristics of small solid spherical particles used as seeding agents in gaseous nuclear rocket engines
Phenomenological description of elementary particle reactions in terms of form factors