Self-localization of magnon Bose-Einstein condensates in the ground state and on excited levels: from harmonic to box-like trapping potential

Long-lived coherent spin precession of 3He-B at low temperatures around 0.2 Tc is a manifestation of Bose-Einstein condensation of spin-wave excitations or magnons in a magnetic trap which is formed by the order-parameter texture and can be manipulated experimentally. When the number of magnons increases, the orbital texture reorients under the influence of the spin-orbit interaction and the profile of the trap gradually changes from harmonic to a square well, with walls almost impenetrable to magnons. This is the first experimental example of Bose condensation in a box. By selective rf pumping the trap can be populated with a ground-state condensate or one at any of the excited energy levels. In the latter case the ground state is simultaneously populated by relaxation from the exited level, forming a system of two coexisting condensates.Comment: 4 pages, 5 figure

Nanoelectronic thermometers optimised for sub-10 millikelvin operation

We report the cooling of electrons in nanoelectronic Coulomb blockade thermometers below 4 mK. Above 7 mK the devices are in good thermal contact with the environment, well isolated from electrical noise, and not susceptible to self-heating. This is attributed to an optimised design that incorporates cooling fins with a high electron-phonon coupling and on-chip electronic filters, combined with a low-noise electronic measurement setup. Below 7 mK the electron temperature is seen to diverge from the ambient temperature. By immersing a Coulomb Blockade Thermometer in the 3He/4He refrigerant of a dilution refrigerator, we measure a lowest electron temperature of 3.7 mK.Comment: 11 pages, 4 figures. (Fixed fitted saturation T_e on p9

Eight years of sub-micrometre organic aerosol composition data from the boreal forest characterized using a machine-learning approach

The Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, located within the boreal forest of Finland, is a unique station in the world due to the wide range of long-term measurements tracking the Earth-atmosphere interface. In this study, we characterize the composition of organic aerosol (OA) at SMEAR II by quantifying its driving constituents. We utilize a multi-year data set of OA mass spectra measured in situ with an Aerosol Chemical Speciation Monitor (ACSM) at the station. To our knowledge, this mass spectral time series is the longest of its kind published to date. Similarly to other previously reported efforts in OA source apportionment from multi-seasonal or multi-annual data sets, we approached the OA characterization challenge through positive matrix factorization (PMF) using a rolling window approach. However, the existing methods for extracting minor OA components were found to be insufficient for our rather remote site. To overcome this issue, we tested a new statistical analysis framework. This included unsupervised feature extraction and classification stages to explore a large number of unconstrained PMF runs conducted on the measured OA mass spectra. Anchored by these results, we finally constructed a relaxed chemical mass balance (CMB) run that resolved different OA components from our observations. The presented combination of statistical tools provided a data-driven analysis methodology, which in our case achieved robust solutions with minimal subjectivity. Following the extensive statistical analyses, we were able to divide the 2012-2019 SMEAR II OA data (mass concentration interquartile range (IQR): 0.7, 1.3, and 2.6 mu gm(-3)) into three sub-categories - low-volatility oxygenated OA (LV-OOA), semi-volatile oxygenated OA (SV-OOA), and primary OA (POA) - proving that the tested methodology was able to provide results consistent with literature. LV-OOA was the most dominant OA type (organic mass fraction IQR: 49 %, 62 %, and 73 %). The seasonal cycle of LV-OOA was bimodal, with peaks both in summer and in February. We associated the wintertime LV-OOA with anthropogenic sources and assumed biogenic influence in LV-OOA formation in summer. Through a brief trajectory analysis, we estimated summertime natural LV-OOA formation of tens of ngm 3 h 1 over the boreal forest. SV-OOA was the second highest contributor to OA mass (organic mass fraction IQR: 19 %, 31 %, and 43 %). Due to SV-OOA's clear peak in summer, we estimate biogenic processes as the main drivers in its formation. Unlike for LV-OOA, the highest SV-OOA concentrations were detected in stable summertime nocturnal surface layers. Two nearby sawmills also played a significant role in SV-OOA production as also exemplified by previous studies at SMEAR II. POA, taken as a mix of two different OA types reported previously, hydrocarbon-like OA (HOA) and biomass burning OA (BBOA), made up a minimal OA mass fraction (IQR: 2 %, 6 %, and 13 %). Notably, the quantification of POA at SMEAR II using ACSM data was not possible following existing rolling PMF methodologies. Both POA organic mass fraction and mass concentration peaked in winter. Its appearance at SMEAR II was linked to strong southerly winds. Similar wind direction and speed dependence was not observed among other OA types. The high wind speeds probably enabled the POA transport to SMEAR II from faraway sources in a relatively fresh state. In the event of slower wind speeds, POA likely evaporated and/or aged into oxidized organic aerosol before detection. The POA organic mass fraction was significantly lower than reported by aerosol mass spectrometer (AMS) measurements 2 to 4 years prior to the ACSM measurements. While the co-located long-term measurements of black carbon supported the hypothesis of higher POA loadings prior to year 2012, it is also possible that short-term (POA) pollution plumes were averaged out due to the slow time resolution of the ACSM combined with the further 3 h data averaging needed to ensure good signal-to-noise ratios (SNRs). Despite the length of the ACSM data set, we did not focus on quantifying long-term trends of POA (nor other components) due to the high sensitivity of OA composition to meteorological anomalies, the occurrence of which is likely not normally distributed over the 8-year measurement period. Due to the unique and realistic seasonal cycles and meteorology dependences of the independent OA subtypes complemented by the reasonably low degree of unexplained OA variability, we believe that the presented data analysis approach performs well. Therefore, we hope that these results encourage also other researchers possessing several-yearlong time series of similar data to tackle the data analysis via similar semi- or unsupervised machine-learning approaches. This way the presented method could be further optimized and its usability explored and evaluated also in other environments.Peer reviewe

Constructing a data-driven receptor model for organic and inorganic aerosol : a synthesis analysis of eight mass spectrometric data sets from a boreal forest site

The interactions between organic and inorganic aerosol chemical components are integral to understanding and modelling climate and health-relevant aerosol physicochemical properties, such as volatility, hygroscopicity, light scattering and toxicity. This study presents a synthesis analysis for eight data sets, of non-refractory aerosol composition, measured at a boreal forest site. The measurements, performed with an aerosol mass spectrometer, cover in total around 9 months over the course of 3 years. In our statistical analysis, we use the complete organic and inorganic unit-resolution mass spectra, as opposed to the more common approach of only including the organic fraction. The analysis is based on iterative, combined use of (1) data reduction, (2) classification and (3) scaling tools, producing a data-driven chemical mass balance type of model capable of describing site-specific aerosol composition. The receptor model we constructed was able to explain 83 +/- 8% of variation in data, which increased to 96 +/- 3% when signals from low signal-to-noise variables were not considered. The resulting interpretation of an extensive set of aerosol mass spectrometric data infers seven distinct aerosol chemical components for a rural boreal forest site: ammonium sulfate (35 +/- 7% of mass), low and semi-volatile oxidised organic aerosols (27 +/- 8% and 12 +/- 7 %), biomass burning organic aerosol (11 +/- 7 %), a nitrate-containing organic aerosol type (7 +/- 2 %), ammonium nitrate (5 +/- 2 %), and hydrocarbon-like organic aerosol (3 +/- 1 %). Some of the additionally observed, rare outlier aerosol types likely emerge due to surface ionisation effects and likely represent amine compounds from an unknown source and alkaline metals from emissions of a nearby district heating plant. Compared to traditional, ionbalance-based inorganics apportionment schemes for aerosol mass spectrometer data, our statistics-based method provides an improved, more robust approach, yielding readily useful information for the modelling of submicron atmospheric aerosols physical and chemical properties. The results also shed light on the division between organic and inorganic aerosol types and dynamics of salt formation in aerosol. Equally importantly, the combined methodology exemplifies an iterative analysis, using consequent analysis steps by a combination of statistical methods. Such an approach offers new ways to home in on physicochemically sensible solutions with minimal need for a priori information or analyst interference. We therefore suggest that similar statisticsbased approaches offer significant potential for un- or semi-supervised machine-learning applications in future analyses of aerosol mass spectrometric data.Peer reviewe

High Power Test on an x-Band Slotted-Iris Accelerator Structure at NLCTA

The CLIC study group at CERN has built two X-band HDS (Hybrid Damped Structure) accelerating structures for high-power testing in NLCTA at SLAC. These accelerating structures are novel with respect to their rf-design and their fabrication technique. The eleven-cell constant impedance structures, one made out of copper and one out of molybdenum, are assembled from clamped high-speed milled quadrants. They feature the same heavy higher-order-mode damping as nominal CLIC structures achieved by slotted irises and radial damping waveguides for each cell. The X-band accelerators are exactly scaled versions of structures tested at 30 GHz in the CLIC test facility, CTF3. The results of the X-band tests are presented and compared to those at 30 GHz to determine frequency scaling, and are compared to the extensive copper data from the NLC structure development program to determine material dependence and make a basic validation of the HDS design. INTRODUCTIO

Novel Data Acquisition System for Silicon Tracking Detectors

We have developed a novel data acquisition system for measuring tracking parameters of a silicon detector in a particle beam. The system is based on a commercial Analog-to-Digital VME module and a PC Linux based Data Acquisition System. This DAQ is realized with C++ code using object-oriented techniques. Track parameters for the beam particles were reconstructed using off-line analysis code and automatic detector position alignment algorithm. The new DAQ was used to test novel Czochralski type silicon detectors. The important silicon detector parameters, including signal size distributions and signal to noise distributions, were successfully extracted from the detector under study. The efficiency of the detector was measured to be 95 %, the resolution about 10 micrometers, and the signal to noise ratio about 10.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 6 pages, LaTeX, 5 eps figures. PSN TUGP00

High-Gradient Test of a Tungsten-Iris X-Band Accelerator Structure at NLCTA

The CLIC study group at CERN has built two X-band accelerating structures to be tested at SLAC in NLCTA. The structures consist of copper cells with insert irises made out of molybdenum and tungsten, clamped together and installed in a vacuum tank. These structures are exactly scaled versions from structures tested previously at 30 GHz and with short pulses (16 ns) in the CLIC Test Facility at CERN. At 30 GHz these structures reached gradients of 150 MV/m for tungsten and 195 MV/m for molybdenum. These experiments were designed to provide data on the dependence of rf breakdown on pulse length and frequency. This paper reports in particular on the high-gradient test of the tungsten-iris structure. At the shortest possible pulse length of 22 ns a gradient of 125 MV/m was reached at X-band, 20 % lower than the 150 MV/m measured at 30 GHz in the CLIC Test Facility. The pulse length dependence and the dependence of the break down rate as a function of gradient were measured in detail. The results are compared to data obtained from the molybdenum-iris experiment at X-band which took place earlier as well as to 30 GHz data

Chemical transformations in monoterpene-derived organic aerosol enhanced by inorganic composition

Secondary organic aerosol (SOA) is known to impact both climate and air quality, yet molecular-level composition measurements remain challenging, hampering our understanding of SOA formation and evolution. Here, we reveal the importance of underestimated reaction pathways for the (trans) formation of SOA from monoterpenes, one of the largest SOA precursors globally. Utilizing mass spectrometric techniques to achieve a comprehensive characterization of molecular-level changes in the SOA, we were able to link the appearance of high-molecular weight (HMW) organic molecules to the concentration and level of neutralization of particulate sulfate. Interestingly, this oligomerization coincided with a decrease of highly oxygenated molecules (HOMs). Our findings highlight the role of particle-phase processing, and the underestimated importance of sulfate aerosol for monoterpene-SOA formation. The observations of these processes directly in the atmosphere reveal the need to account for the formation of HMW oligomers to fully understand the physicochemical properties of organic aerosol.Peer reviewe

Evaluating the performance of five different chemical ionization techniques for detecting gaseous oxygenated organic species

The impact of aerosols on climate and air quality remains poorly understood due to multiple factors. One of the current limitations is the incomplete understanding of the contribution of oxygenated products, generated from the gas-phase oxidation of volatile organic compounds (VOCs), to aerosol formation. Indeed, atmospheric gaseous chemical processes yield thousands of (highly) oxygenated species, spanning a wide range of chemical formulas, functional groups and, consequently, volatilities. While recent mass spectrometric developments have allowed extensive on-line detection of a myriad of oxygenated organic species, playing a central role in atmospheric chemistry, the detailed quantification and characterization of this diverse group of compounds remains extremely challenging. To address this challenge, we evaluated the capability of current state-of-the-art mass spectrometers equipped with different chemical ionization sources to detect the oxidation products formed from alpha-Pinene ozonolysis under various conditions. Five different mass spectrometers were deployed simultaneously for a chamber study. Two chemical ionization atmospheric pressure interface time-of-flight mass spectrometers (CI-APi-TOF) with nitrate and amine reagent ion chemistries and an iodide chemical ionization time-of-flight mass spectrometer (TOF-CIMS) were used. Additionally, a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF 8000) and a new "vocus" PTR-TOF were also deployed. In the current study, we compared around 1000 different compounds between each of the five instruments, with the aim of determining which oxygenated VOCs (OVOCs) the different methods were sensitive to and identifying regions where two or more instruments were able to detect species with similar molecular formulae. We utilized a large variability in conditions (including different VOCs, ozone, NOx and OH scavenger concentrations) in our newly constructed atmospheric simulation chamber for a comprehensive correlation analysis between all instruments. This analysis, combined with estimated concentrations for identified molecules in each instrument, yielded both expected and surprising results. As anticipated based on earlier studies, the PTR instruments were the only ones able to measure the precursor VOC, the iodide TOF-CIMS efficiently detected many semi-volatile organic compounds (SVOCs) with three to five oxygen atoms, and the nitrate CI-APi-TOF was mainly sensitive to highly oxygenated organic (O > 5) molecules (HOMs). In addition, the vocus showed good agreement with the iodide TOF-CIMS for the SVOC, including a range of organonitrates. The amine CI-APi-TOF agreed well with the nitrate CI-APi-TOF for HOM dimers. However, the loadings in our experiments caused the amine reagent ion to be considerably depleted, causing nonlinear responses for monomers. This study explores and highlights both benefits and limitations of currently available chemical ionization mass spectrometry instrumentation for characterizing the wide variety of OVOCs in the atmosphere. While specifically shown for the case of alpha-Pinene ozonolysis, we expect our general findings to also be valid for a wide range of other VOC-oxidant systems. As discussed in this study, no single instrument configuration can be deemed better or worse than the others, as the optimal instrument for a particular study ultimately depends on the specific target of the study.Peer reviewe