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We report a demonstration of the scalability of optically transparent xenon in the solid phase for use as a particle detector above a kilogram scale. We employed a cryostat cooled by liquid nitrogen combined with a xenon purification and chiller system. A modified {\it Bridgeman's technique} reproduces a large scale optically transparent solid xenon.
We present a purity monitor for the KEDR liquid krypton calorimeter. A new method is suggested based on the usage of a short pulse of a gas discharge as a source of ultraviolet radiation for the photoproduction of electrons in a drift cell of the monitor. This paper describes the design of the monitor, the results of experiments with gaseous and liquid krypton, as well as the experience of using the developed device in the process of krypton purification for the KEDR liquid krypton calorimeter.
Measurements of the optical properties of highly transparent liquids are necessary for large-scale detectors that seek to detect optical signatures in kiloton-scale or larger volumes. Detailed understanding of the attenuation and scattering properties of fill media is critical to the ability to accurately simulate detector performance, and yet is often unavailable until in-situ measurements can be performed. Moreover, in-situ measurements may rely on effective attenuation lengths or other approximations to characterize performance, rather than absolute measurements of attenuation and scattering. To better understand the optical properties of potential fill media and purification schemes, a system has been developed which provides simultaneous attenuation and differential scattering cross-section measurements for highly transparent liquids. This horizontal, adjustable path-length “long-arm” system provides excellent isolation from the atmosphere, a high degree of vibration insensitivity, and a simple and reliable method of calibration. Further, scattering measurements can be carried out simultaneously at ports along the beamline equipped with optics allowing the selection of scatter angle and polarization. This enables both reliable quantitative scatter measurements and phase-function separation. This system has been extensively tested using deionized (DI) water as a benchmark, and has demonstrated repeatable measurements of attenuation lengths exceeding 100 m and scattering lengths approaching 1 km.
One of the most promising approaches for the next generation of neutrino experiments is the realization of large hybrid Cherenkov/scintillation detectors made possible by recent innovations in photodetection technology and liquid scintillator chemistry. The development of a potentially suitable future detector liquid with particularly slow light emission is discussed in the present publication. This cocktail is compared with respect to its fundamental characteristics (scintillation efficiency, transparency, and time profile of light emission) with liquid scintillators currently used in large-scale neutrino detectors. In addition, the optimization of the admixture of wavelength shifters for a scintillator with particularly high light emission is presented. Furthermore, the pulse-shape discrimination capabilities of the novel medium was studied using a pulsed particle accelerator driven neutron source. Beyond that, purification methods based on column chromatography and fractional vacuum distillation for the co-solvent DIN (Diisopropylnaphthalene) are discussed.
Experiments aimed at direct searches for WIMP dark matter require highly effective reduction of backgrounds and control of any residual radioactive contamination. In particular, neutrons interacting with atomic nuclei represent an important class of backgrounds due to the expected similarity of a WIMP-nucleon interaction, so that such experiments often feature a dedicated neutron detector surrounding the active target volume. In the context of the development of DarkSide-20k detector at INFN Gran Sasso National Laboratory (LNGS), several R&D projects were conceived and developed for the creation of a new hybrid material rich in both hydrogen and gadolinium nuclei to be employed as an essential element of the neutron detector. Thanks to its very high cross-section for neutron capture, gadolinium is one of the most widely used elements in neutron detectors, while the hydrogen-rich material is instrumental in efficiently moderating the neutrons. In this paper results from one of the R&Ds are presented. In this effort the new hybrid material was obtained as a poly(methyl methacrylate) (PMMA) matrix, loaded with gadolinium oxide in the form of nanoparticles. We describe its realization, including all phases of design, purification, construction, characterization, and determination of mechanical properties of the new material.
DarkSide-20k (DS-20k) is a dark matter detection experimentunder construction at the Laboratori Nazionali del Gran Sasso (LNGS)in Italy. It utilises ∼ 100 t of low radioactivity argon from anunderground source (UAr) in its inner detector, with half serving astarget in a dual-phase time projection chamber (TPC). The UArcryogenics system must maintain stable thermodynamic conditionsthroughout the experiment's lifetime of over10 years. Continuous removal ofimpurities and radon from the UAr is essential for maximising signalyield and mitigating background. We are developing an efficient andpowerful cryogenics system with a gas purification loop with atarget circulation rate of1000 slpm. Central to itsdesign is a condenser operated with liquid nitrogen which is pairedwith a gas heat exchanger cascade, delivering a combined coolingpower of more than 8 kW. Here wepresent the design choices in view of the DS-20k requirements, inparticular the condenser's working principle and the coolingcontrol, and we show test results obtained with a dedicatedbenchmarking platform at CERN and LNGS. We find that the thermalefficiency of the recirculation loop, defined in terms of nitrogenconsumption per argon flow rate, is95 % and the pressure in the testcryostat can be maintained within±(0.1–0.2) mbar. Wefurther detail a 5-day cool-down procedure of the test cryostat,maintaining a cooling rate typically within-2 K/h, as required for theDS-20k inner detector. Additionally, we assess the circuit's flowresistance, and the heat transfer capabilities of two heat exchangergeometries for argon phase change, used to provide gas forrecirculation. We conclude by discussing how our findings influencethe finalisation of the system design, including necessarymodifications to meet requirements and ongoing testing activities.
The DarkSide-20k dark matter experiment, currently under construction at LNGS, features a dual-phase time projection chamber (TPC) with a ∼ 50 t argon target from an underground well. At this scale, it is crucial to optimise the argon flow pattern for efficient target purification and for fast distribution of internal gaseous calibration sources with lifetimes of the order of hours. To this end, we have performed computational fluid dynamics simulations and heat transfer calculations. The residence time distribution shows that the detector is well-mixed on time-scales of the turnover time (∼ 40 d). Notably, simulations show that despite a two-order-of-magnitude difference between the turnover time and the half-life of 83m Kr of 1.83 h, source atoms have the highest probability to reach the centre of the TPC 13 min after their injection, allowing for a homogeneous distribution before undergoing radioactive decay. We further analyse the thermal aspects of dual-phase operation and define the requirements for the formation of a stable gas pocket on top of the liquid. We find a best-estimate value for the heat transfer rate at the liquid-gas interface of 62 W with an upper limit of 144 W and a minimum gas pocket inlet temperature of 89 K to avoid condensation on the acrylic anode. This study also informs the placement of liquid inlets and outlets in the TPC. The presented techniques are widely applicable to other large-scale, noble-liquid detectors.
As liquid xenon time projection chambers scale to ever-larger sizes, so too do the engineering challenges they pose. Here, we describe a large, flexible, multipurpose test facility capable of supporting the development of a number of key aspects of liquid xenon detector systems. Example applications of this facility include characterization of large-area light and charge sensor arrays, tests of xenon purification techniques and materials compatibility, and investigations into high-voltage phenomena. This facility uses an automated and remotely monitored cryo-cooling system based on immersion of the test chamber in a liquid bath rather than conductive coupling, leading to advantages in temperature and pressure stability, as well as increasing required response times in the case of cooling-power loss. Design advantages, operational procedures, and performance of the facility are described, as well as five examples of liquid xenon test chambers that use the facility.
Abstract We provide in this paper a concrete method for training a quantum neural network to maximize the relevant information about a property that is transmitted through the network. This is significant because it gives an operationally well founded quantity to optimize when training autoencoders for problems where the inputs and outputs are fully quantum. We provide a rigorous algorithm for computing the value of the quantum information bottleneck quantity within error ε that requires O ( log 2 ( 1 / ϵ ) + 1 / δ 2 ) queries to a purification of the input density operator if its spectrum is supported on { 0 } ⋃ [ δ , 1 − δ ] for δ > 0 and the kernels of the relevant density matrices are disjoint. We further provide algorithms for estimating the derivatives of the QIB function, showing that quantum neural networks can be trained efficiently using the QIB quantity given that the number of gradient steps required is polynomial.
The Sanford Underground Research Facility (SURF) will host the Far Detector of the Deep Underground Neutrino Experiment (DUNE), an international multi-kiloton Long-Baseline neutrino experiment that will be installed about one and a half kilometers underground in Lead, SD. Detectors will be located inside four cryostats filled with almost 70,000 metric tons of ultrapure liquid argon, with a level of impurities lower than 100 parts per trillion of oxygen equivalent contamination. The cryogenics infrastructure supporting this experiment is provided by the Long-Baseline Neutrino Facility (LBNF). This contribution presents modes of operation, layout, and main features of the LBNF Far Site cryogenic system, which is composed of three subsystems: Infrastructure, Proximity, and Internal cryogenics. The Infrastructure cryogenics supports the needs of the cryostat and Proximity cryogenics. It includes the equipment to receive the argon in liquid phase, vaporize it and transfer it underground as a gas, the nitrogen system (composed of the refrigeration system, liquid nitrogen buffer tanks and liquid and gaseous nitrogen distribution), liquid and gaseous argon distribution and process controls. The Proximity cryogenics receives fluids from the Infrastructure cryogenics and delivers them to the Internal cryogenics at the required temperature, pressure, purity and mass flow rate. It includes the argon condensers, liquid and gaseous argon purification and regeneration systems, nitrogen and argon phase separators, piping, valves, and instrumentation. The Internal cryogenics comprises the liquid and gaseous argon distribution inside the cryostats for the commissioning, cool down, fill, and steady state operations of the cryostats and detectors. An international engineering team is designing these systems and will manufacture, install, commission, and qualify them. This contribution describes the main features, performance, functional requirements, and modes of operation of the LBNF Far Site cryogenics system. It also presents the status of the design, along with present and future needs to support the DUNE experiment.
The far Detector of the Deep Underground Neutrino Experiment (DUNE) will be housed in several large volume (about 12.500 m$^{3}$) liquid argon cryostats. The design principle of these large cryostats, and of the cryogenic system belonging to them, are investigated through the design, construction and operation of a series of prototype installations.The Neutrino Platform 02 (NP02) and 04 (NP04) cryostats, placed at CERN, contain DUNE proto-type detectors, each of them housed in an about 600 m$^{3}$ liquid argon bath. These cryostats, based on the membrane cryostat principle, and their cryogenic systems have been designed according to the DUNE principle. Measurements performed in these test stands shall confirm the foreseen heat loads into the cryostat systems entering via its walls, via detector cabling and via the cold electronics, shall confirm the low temperature gradient over the active detector volume and shall certify the liquid argon purification principle.This paper introduces the requirements for the NP02 and NP04 cryostats and their cryogenic systems, describes the design principle applied to these two systems and gives an overview of the different modes in which the two systems have been operating. The experimental results are presented and discussed, and “lessons learned” for future installations are dawn.
In the context of the Neutrino Platform, CERN has designed, constructed, and commissioned the proximity cryogenics systems that serve two CERN based large-scale prototypes of future neutrino detectors. Each of these prototypes features a high voltage time projection chamber placed inside a membrane cryostat being submerged in 600m3 of liquid argon at about 1.0 bar. A copper and molecular sieve based cryogenic purification system has to ensure that the argon in the cryostat has a contamination level below 100 ppt oxygen equivalent. The two proximity cryogenics systems provide the purging, cool-down, filling, normal operation and emptying modes for each cryostat. This paper reports on the design, construction and commissioning of the ProtoDUNE proximity cryogenics facilities.
The task of learning a quantum circuit to prepare a given mixed state is a fundamental quantum subroutine. We present a variational quantum algorithm (VQA) to learn mixed states which is suitable for near-term hardware. Our algorithm represents a generalization of previous VQAs that aimed at learning preparation circuits for pure states. We consider two different ansätze for compiling the target state; the first is based on learning a purification of the state and the second on representing it as a convex combination of pure states. In both cases, the resources required to store and manipulate the compiled state grow with the rank of the approximation. Thus, by learning a lower rank approximation of the target state, our algorithm provides a means of compressing a state for more efficient processing. As a byproduct of our algorithm, one effectively learns the principal components of the target state, and hence our algorithm further provides a new method for principal component analysis. We investigate the efficacy of our algorithm through extensive numerical implementations, showing that typical random states and thermal states of many body systems may be learnt this way. Additionally, we demonstrate on quantum hardware how our algorithm can be used to study hardware noise-induced states.
Negative emissions technologies will be essential for limiting anthropogenic global temperature increases to 2 °C in the later years of the 21st century. Carbonic anhydrase (CA) metalloenzymes catalyze the otherwise slow conversion of CO 2 into carbonic acid (H 2 CO 3 ), suggesting their utility in the rapid hydration and downstream capture of dissolved CO 2 in aqueous media for a variety of CO 2 capture methods, such as thermal and pH swings and mineralization. The possibility of driving the rapid capture of CO 2 by catalyzing the CO 2 hydration bottleneck carries real potential for realizing efficient direct air capture (DAC) and direct ocean capture (DOC) systems. However, scaled application of CAs will be dependent on some way of economically sourcing the enzymes at volumes relevant to scaled DAC/DOC operations. In this perspective, we consider the prospect of catalyzing CO 2 hydration using a CA that is bound to the outer membrane of a cyanobacterial host, engineered constructs we call CyCAMs. Coupling extracellular CA expression to a marine, photosynthetic cyanobacterial host results in a CO 2 hydration catalyst that is continuously refreshed during the bacterial growth cycle, without the need for enzyme purification or harvesting steps. In the case of marine cyanobacteria, sunlight and the solutes native to seawater provide the respective energy, nutrients and sources of inorganic carbon essential to maintaining the bacterial population. We consider the potential impact of CA-mediated CO 2 hydration on a variety of DAC processes, with CO 2 mineralization explored as a primary use case.
Mentha longifolia (L.) Huds., a wild, diploid mint species, has been developed as a model for mint genetic and genomic research to aid breeding efforts that target Verticillium wilt disease resistance and essential oil monoterpene composition. Here, we present a near-complete, chromosome-scale mint genome assembly for M. longifolia USDA accession CMEN 585. This new assembly is an update of a previously published genome draft, with dramatic improvements. A total of 42,107 protein-coding genes were annotated and placed on 12 chromosomal scaffolds. One hundred fifty-three genes contained conserved sequence domains consistent with nucleotide binding site-leucine-rich-repeat (NBS-LRR) plant disease resistance genes. Homologs of genes implicated in Verticillium wilt resistance in other plant species were also identified. Multiple paralogs of genes putatively involved in p-menthane monoterpenoid biosynthesis were identified and several cases of gene clustering documented. Heterologous expression of candidate genes, purification of recombinant target proteins, and subsequent enzyme assays allowed us to identify the genes underlying the pathway that leads to the most abundant monoterpenoid volatiles. Here, the bioinformatic and functional analyses presented here are laying the groundwork for using marker-assisted selection in improving disease resistance and essential oil traits in mints.
Abstract The Structural Classification of Proteins—extended (SCOPe, https://scop.berkeley.edu) knowledgebase aims to provide an accurate, detailed, and comprehensive description of the structural and evolutionary relationships amongst the majority of proteins of known structure, along with resources for analyzing the protein structures and their sequences. Structures from the PDB are divided into domains and classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.08, we have developed search and display tools for analysis of genetic variants we mapped to structures classified in SCOPe. In order to improve the utility of SCOPe to automated methods such as deep learning classifiers that rely on multiple alignment of sequences of homologous proteins, we have introduced new machine-parseable annotations that indicate aberrant structures as well as domains that are distinguished by a smaller repeat unit. We also classified structures from 74 of the largest Pfam families not previously classified in SCOPe, and we improved our algorithm to remove N- and C-terminal cloning, expression and purification sequences from SCOPe domains. SCOPe 2.08-stable classifies 106 976 PDB entries (about 60% of PDB entries).
Using affinity purification and mass spectrometry, we identified the subunits of Arabidopsis thaliana multisubunit RNA Polymerases I and III (abbreviated as Pol I and Pol III), providing the first description of their physical compositions in plants. AC40 and AC19 subunits are typically common to Pol I (a.k.a. Pol A) and Pol III (a.k.a. Pol C) and are encoded by single genes whose mutation, in humans, is a cause of the craniofacial disorder, Treacher-Collins Syndrome. Surprisingly, A. thaliana, and related species, express two distinct AC40 paralogs, one of which assembles into Pol I and the other of which assembles into Pol III. Changes at eight amino acid positions correlate with this functional divergence of Pol I and Pol III-specific AC40 paralogs. Two genes encode homologs of the yeast C53 subunit, and either variant can assemble into Pol III. By contrast, only one of two potential C17 variants, and one of two potential C31 variants were detected in Pol III. We introduce a new nomenclature system for plant Pol I and Pol III subunits in which the twelve subunits that are structurally and functionally homologous among Pols I through V are assigned equivalent numbers.
Non-homologous end joining (NHEJ) repairs DNA double strand breaks in non-cycling eukaryotic cells. NHEJ relies on polynucleotide kinase/phosphatase (PNKP), which generates 5'-phosphate/3'-hydroxyl DNA termini that are critical for ligation by the NHEJ DNA ligase, LigIV. PNKP and LigIV require the NHEJ scaffolding protein, XRCC4. The PNKP FHA domain binds to the CK2-phosphorylated XRCC4 C-terminal tail, while LigIV uses its tandem BRCT repeats to bind the XRCC4 coiled-coil. Yet, the assembled PNKP-XRCC4-LigIV complex remains uncharacterized. Here, we report purification and characterization of a recombinant PNKP-XRCC4-LigIV complex. We show that the stable binding of PNKP in this complex requires XRCC4 phosphorylation and that only one PNKP protomer binds per XRCC4 dimer. Small angle X-ray scattering (SAXS) reveals a flexiblemultistate complex that suggests that both the PNKP FHA and catalytic domains contact the XRCC4 coiled-coil and LigIV BRCT repeats. Hydrogen-deuterium exchange indicates protection of a surface on the PNKP phosphatase domain that may contact XRCC4-LigIV. Amutation on this surface (E326K) causes the hereditary neuro-developmental disorder, MCSZ. This mutation impairs PNKP recruitment to damaged DNA in human cells and provides a possible disease mechanism. Together, this work unveils multipoint contacts between PNKP and XRCC4-LigIV that regulate PNKP recruitment and activity within NHEJ.