Singular values of the Dirac operator in dense QCD-like theories

We study the singular values of the Dirac operator in dense QCD-like theories at zero temperature. The Dirac singular values are real and nonnegative at any nonzero quark density. The scale of their spectrum is set by the diquark condensate, in contrast to the complex Dirac eigenvalues whose scale is set by the chiral condensate at low density and by the BCS gap at high density. We identify three different low-energy effective theories with diquark sources applicable at low, intermediate, and high density, together with their overlapping domains of validity. We derive a number of exact formulas for the Dirac singular values, including Banks-Casher-type relations for the diquark condensate, Smilga-Stern-type relations for the slope of the singular value density, and Leutwyler-Smilga-type sum rules for the inverse singular values. We construct random matrix theories and determine the form of the microscopic spectral correlation functions of the singular values for all nonzero quark densities. We also derive a rigorous index theorem for non-Hermitian Dirac operators. Our results can in principle be tested in lattice simulations.Comment: 3 references added, version published in JHE

Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows.

MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a machine learning algorithm. We then provide optimized techniques to validate the identified miRNAs through over-expression/loss-of-function studies. Overall, these protocols apply to any field in biology where high-dimensional data are produced. For complete details on the use and execution of this protocol, please refer to Wong et al. (2021a)

Application of headspace solid-phase microextraction and gas chromatography for the analysis of furfural in crude palm oil

Processing of vegetative material containing pentoses has been shown to result in the formation of furfural. Furfural exhibits a spectrophotometric absorption peak at 518 nm when complexed with aniline acetate. Headspace solid-phase microextraction (HS-SPME) method has been successfully used to confirm the presence of furfural in crude palm oil (CPO). Solid phase microextraction (SPME) fiber composed of divinylbenzene/Carboxen/polydimethylsiloxane (DVB/PDMS/CAR) was used to absorb the volatiles in the headspace of the oil. The isolated compounds from the fiber was desorbed and separated on a capillary polar column of a gas chromatograph. Response surface methodology (RSM) was used to optimize the SPME fiber condition for maximum absorption of furfural from CPO. The optimized temperature and time for furfural extraction onto the SPME fiber are 70 °C for 40 min. Oils obtained from the mill were found to contain between 2 and 13% furfural

Neocentromeres Form Efficiently at Multiple Possible Loci in Candida albicans

Centromeres are critically important for chromosome stability and integrity. Most eukaryotes have regional centromeres that include long tracts of repetitive DNA packaged into pericentric heterochromatin. Neocentromeres, new sites of functional kinetochore assembly, can form at ectopic loci because no DNA sequence is strictly required for assembly of a functional kinetochore. In humans, neocentromeres often arise in cells with gross chromosome rearrangements that rescue an acentric chromosome. Here, we studied the properties of centromeres in Candida albicans, the most prevalent fungal pathogen of humans, which has small regional centromeres that lack pericentric heterochromatin. We functionally delimited centromere DNA on Chromosome 5 (CEN5) and then replaced the entire region with the counter-selectable URA3 gene or other marker genes. All of the resulting cen5Δ::URA3 transformants stably retained both copies of Chr5, indicating that a functional neocentromere had assembled efficiently on the homolog lacking CEN5 DNA. Strains selected to maintain only the cen5Δ::URA3 homolog and no wild-type Chr5 homolog also grew well, indicating that neocentromere function is independent of the presence of any wild-type CEN5 DNA. Two classes of neocentromere (neoCEN) strains were distinguishable: “proximal neoCEN” and “distal neoCEN” strains. Neocentromeres in the distal neoCEN strains formed at loci about 200–450 kb from cen5Δ::URA3 on either chromosome arm, as detected by massively parallel sequencing of DNA isolated by CENP-ACse4p chromatin immunoprecipitation (ChIP). In the proximal neoCEN strains, the neocentromeres formed directly adjacent to cen5Δ::URA3 and moved onto the URA3 DNA, resulting in silencing of its expression. Functional neocentromeres form efficiently at several possible loci that share properties of low gene density and flanking repeated DNA sequences. Subsequently, neocentromeres can move locally, which can be detected by silencing of an adjacent URA3 gene, or can relocate to entirely different regions of the chromosome. The ability to select for neocentromere formation and movement in C. albicans permits mechanistic analysis of the assembly and maintenance of a regional centromere

Quantitative Microscopy Reveals Centromeric Chromatin Stability, Size, and Cell Cycle Mechanisms to Maintain Centromere Homeostasis

The deposited item is a book chapter and is part of the series "Centromeres and Kinetochores" published by the publisher Springer Verlag. The deposited book chapter is a post-print version and has been submitted to peer reviewing. There is no public supplementary material available for this publication. This publication hasn't any creative commons license associated.Centromeres are chromatin domains specified by nucleosomes containing the histone H3 variant, CENP-A. This unique centromeric structure is at the heart of a strong self-templating epigenetic mechanism that renders centromeres heritable. We review how specific quantitative microscopy approaches have contributed to the determination of the copy number, architecture, size, and dynamics of centromeric chromatin and its associated centromere complex and kinetochore. These efforts revealed that the key to long-term centromere maintenance is the slow turnover of CENP-A nucleosomes, a critical size of the chromatin domain and its cell cycle-coupled replication. These features come together to maintain homeostasis of a chromatin locus that directs its own epigenetic inheritance and facilitates the assembly of the mitotic kinetochore.There are no funders and sponsors indicated explicitly in the document.info:eu-repo/semantics/publishedVersio

A Cross-Species Analysis of MicroRNAs in the Developing Avian Face

Higher vertebrates use similar genetic tools to derive very different facial features. This diversity is believed to occur through temporal, spatial and species-specific changes in gene expression within cranial neural crest (NC) cells. These contribute to the facial skeleton and contain species-specific information that drives morphological variation. A few signaling molecules and transcription factors are known to play important roles in these processes, but little is known regarding the role of micro-RNAs (miRNAs). We have identified and compared all miRNAs expressed in cranial NC cells from three avian species (chicken, duck, and quail) before and after species-specific facial distinctions occur. We identified 170 differentially expressed miRNAs. These include thirty-five novel chicken orthologs of previously described miRNAs, and six avian-specific miRNAs. Five of these avian-specific miRNAs are conserved over 120 million years of avian evolution, from ratites to galliforms, and their predicted target mRNAs include many components of Wnt signaling. Previous work indicates that mRNA gene expression in NC cells is relatively static during stages when the beak acquires species-specific morphologies. However, miRNA expression is remarkably dynamic within this timeframe, suggesting that the timing of specific developmental transitions is altered in birds with different beak shapes. We evaluated one miRNA:mRNA target pair and found that the cell cycle regulator p27KIP1 is a likely target of miR-222 in frontonasal NC cells, and that the timing of this interaction correlates with the onset of phenotypic variation. Our comparative genomic approach is the first comprehensive analysis of miRNAs in the developing facial primordial, and in species-specific facial development

Volume III. DUNE far detector technical coordination

open966siAcknowledgments This document was prepared by the DUNE collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. The DUNE collaboration also acknowledges the international, national, and regional funding agencies supporting the institutions who have contributed to completing this Technical Design Report.The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay-these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- A nd dual-phase DUNE liquid argon TPC far detector modules. Volume III of this TDR describes how the activities required to design, construct, fabricate, install, and commission the DUNE far detector modules are organized and managed. This volume details the organizational structures that will carry out and/or oversee the planned far detector activities safely, successfully, on time, and on budget. It presents overviews of the facilities, supporting infrastructure, and detectors for context, and it outlines the project-related functions and methodologies used by the DUNE technical coordination organization, focusing on the areas of integration engineering, technical reviews, quality assurance and control, and safety oversight. Because of its more advanced stage of development, functional examples presented in this volume focus primarily on the single-phase (SP) detector module.openAbi B.; Acciarri R.; Acero M.A.; Adamov G.; Adams D.; Adinolfi M.; Ahmad Z.; Ahmed J.; Alion T.; Monsalve S.A.; Alt C.; Anderson J.; Andreopoulos C.; Andrews M.; Andrianala F.; Andringa S.; Ankowski A.; Antonova M.; Antusch S.; Aranda-Fernandez A.; Ariga A.; Arnold L.O.; Arroyave M.A.; Asaadi J.; Aurisano A.; Aushev V.; Autiero D.; Azfar F.; Back H.; Back J.J.; Backhouse C.; Baesso P.; Bagby L.; Bajou R.; Balasubramanian S.; Baldi P.; Bambah B.; Barao F.; Barenboim G.; Barker G.; Barkhouse W.; Barnes C.; Barr G.; Monarca J.B.; Barros N.; Barrow J.L.; Bashyal A.; Basque V.; Bay F.; Alba J.B.; Beacom J.F.; Bechetoille E.; Behera B.; Bellantoni L.; Bellettini G.; Bellini V.; Beltramello O.; Belver D.; Benekos N.; Neves F.B.; Berger J.; Berkman S.; Bernardini P.; Berner R.M.; Berns H.; Bertolucci S.; Betancourt M.; Bezawada Y.; Bhattacharjee M.; Bhuyan B.; Biagi S.; Bian J.; Biassoni M.; Biery K.; Bilki B.; Bishai M.; Bitadze A.; Blake A.; Siffert B.B.; Blaszczyk F.; Blazey G.; Blucher E.; Boissevain J.; Bolognesi S.; Bolton T.; Bonesini M.; Bongrand M.; Bonini F.; Booth A.; Booth C.; Bordoni S.; Borkum A.; Boschi T.; Bostan N.; Bour P.; Boyd S.; Boyden D.; Bracinik J.; Braga D.; Brailsford D.; Brandt A.; Bremer J.; Brew C.; Brianne E.; Brice S.J.; Brizzolari C.; Bromberg C.; Brooijmans G.; Brooke J.; Bross A.; Brunetti G.; Buchanan N.; Budd H.; Caiulo D.; Calafiura P.; Calcutt J.; Calin M.; Calvez S.; Calvo E.; Camilleri L.; Caminata A.; Campanelli M.; Caratelli D.; Carini G.; Carlus B.; Carniti P.; Terrazas I.C.; Carranza H.; Castillo A.; Castromonte C.; Cattadori C.; Cavalier F.; Cavanna F.; Centro S.; Cerati G.; Cervelli A.; Villanueva A.C.; Chalifour M.; Chang C.; Chardonnet E.; Chatterjee A.; Chattopadhyay S.; Chaves J.; Chen H.; Chen M.; Chen Y.; Cherdack D.; Chi C.; Childress S.; Chiriacescu A.; Cho K.; Choubey S.; Christensen A.; Christian D.; Christodoulou G.; Church E.; Clarke P.; Coan T.E.; Cocco A.G.; Coelho J.; Conley E.; Conrad J.; Convery M.; Corwin L.; Cotte P.; Cremaldi L.; Cremonesi L.; Crespo-Anadon J.I.; Cristaldo E.; Cross R.; Cuesta C.; Cui Y.; Cussans D.; Dabrowski M.; Motta H.D.; Peres L.D.S.; David Q.; Davies G.S.; Davini S.; Dawson J.; De K.; Almeida R.M.D.; Debbins P.; Bonis I.D.; Decowski M.; Gouvea A.D.; Holanda P.C.D.; Astiz I.L.D.I.; Deisting A.; Jong P.D.; Delbart A.; Delepine D.; Delgado M.; Dell'acqua A.; Lurgio P.D.; Neto J.R.D.M.; Demuth D.M.; Dennis S.; Densham C.; Deptuch G.; Roeck A.D.; Romeri V.D.; Vries J.D.; Dharmapalan R.; Dias M.; Diaz F.; Diaz J.; Domizio S.D.; Giulio L.D.; Ding P.; Noto L.D.; Distefano C.; Diurba R.; Diwan M.; Djurcic Z.; Dokania N.; Dolinski M.; Domine L.; Douglas D.; Drielsma F.; Duchesneau D.; Duffy K.; Dunne P.; Durkin T.; Duyang H.; Dvornikov O.; Dwyer D.; Dyshkant A.; Eads M.; Edmunds D.; Eisch J.; Emery S.; Ereditato A.; Escobar C.; Sanchez L.E.; Evans J.J.; Ewart E.; Ezeribe A.C.; Fahey K.; Falcone A.; Farnese C.; Farzan Y.; Felix J.; Fernandez-Martinez E.; Menendez P.F.; Ferraro F.; Fields L.; Filkins A.; Filthaut F.; Fitzpatrick R.S.; Flanagan W.; Fleming B.; Flight R.; Fowler J.; Fox W.; Franc J.; Francis K.; Franco D.; Freeman J.; Freestone J.; Fried J.; Friedland A.; Fuess S.; Furic I.; Furmanski A.P.; Gago A.; Gallagher H.; Gallego-Ros A.; Gallice N.; Galymov V.; Gamberini E.; Gamble T.; Gandhi R.; Gandrajula R.; Gao S.; Garcia-Gamez D.; Garcia-Peris M.A.; Gardiner S.; Gastler D.; Ge G.; Gelli B.; Gendotti A.; Gent S.; Ghorbani-Moghaddam Z.; Gibin D.; Gil-Botella I.; Girerd C.; Giri A.; Gnani D.; Gogota O.; Gold M.; Gollapinni S.; Gollwitzer K.; Gomes R.A.; Bermeo L.G.; Fajardo L.S.G.; Gonnella F.; Gonzalez-Cuevas J.; Goodman M.C.; Goodwin O.; Goswami S.; Gotti C.; Goudzovski E.; Grace C.; Graham M.; Gramellini E.; Gran R.; Granados E.; Grant A.; Grant C.; Gratieri D.; Green P.; Green S.; Greenler L.; Greenwood M.; Greer J.; Griffith C.; Groh M.; Grudzinski J.; Grzelak K.; Gu W.; Guarino V.; Guenette R.; Guglielmi A.; Guo B.; Guthikonda K.; Gutierrez R.; Guzowski P.; Guzzo M.M.; Gwon S.; Habig A.; Hackenburg A.; Hadavand H.; Haenni R.; Hahn A.; Haigh J.; Haiston J.; Hamernik T.; Hamilton P.; Han J.; Harder K.; Harris D.A.; Hartnell J.; Hasegawa T.; Hatcher R.; Hazen E.; Heavey A.; Heeger K.M.; Hennessy K.; Henry S.; Morquecho M.H.; Herner K.; Hertel L.; Hesam A.S.; Hewes J.; Pichardo A.H.; Hill T.; Hillier S.J.; Himmel A.; Hoff J.; Hohl C.; Holin A.; Hoppe E.; Horton-Smith G.A.; Hostert M.; Hourlier A.; Howard B.; Howell R.; Huang J.; Huang J.; Hugon J.; Iles G.; Iliescu A.M.; Illingworth R.; Ioannisian A.; Itay R.; Izmaylov A.; James E.; Jargowsky B.; Jediny F.; Jesus-Valls C.; Ji X.; Jiang L.; Jimenez S.; Jipa A.; Joglekar A.; Johnson C.; Johnson R.; Jones B.; Jones S.; Jung C.; Junk T.; Jwa Y.; Kabirnezhad M.; Kaboth A.; Kadenko I.; Kamiya F.; Karagiorgi G.; Karcher A.; Karolak M.; Karyotakis Y.; Kasai S.; Kasetti S.P.; Kashur L.; Kazaryan N.; Kearns E.; Keener P.; Kelly K.J.; Kemp E.; Ketchum W.; Kettell S.; Khabibullin M.; Khotjantsev A.; Khvedelidze A.; Kim D.; King B.; Kirby B.; Kirby M.; Klein J.; Koehler K.; Koerner L.W.; Kohn S.; Koller P.P.; Kordosky M.; Kosc T.; Kose U.; Kostelecky V.; Kothekar K.; Krennrich F.; Kreslo I.; Kudenko Y.; Kudryavtsev V.; Kulagin S.; Kumar J.; Kumar R.; Kuruppu C.; Kus V.; Kutter T.; Lambert A.; Lande K.; Lane C.E.; Lang K.; Langford T.; Lasorak P.; Last D.; Lastoria C.; Laundrie A.; Lawrence A.; Lazanu I.; Lazur R.; Le T.; Learned J.; Lebrun P.; Miotto G.L.; Lehnert R.; De Oliveira M.L.; Leitner M.; Leyton M.; Li L.; Li S.; Li S.; Li T.; Li Y.; Liao H.; Lin C.; Lin S.; Lister A.; Littlejohn B.R.; Liu J.; Lockwitz S.; Loew T.; Lokajicek M.; Lomidze I.; Long K.; Loo K.; Lorca D.; Lord T.; Losecco J.; Louis W.C.; Luk K.; Luo X.; Lurkin N.; Lux T.; Luzio V.P.; MacFarland D.; MacHado A.; MacHado P.; MacIas C.; MacIer J.; Maddalena A.; Madigan P.; Magill S.; Mahn K.; Maio A.; Maloney J.A.; Mandrioli G.; Maneira J.C.; Manenti L.; Manly S.; Mann A.; Manolopoulos K.; Plata M.M.; Marchionni A.; Marciano W.; Marfatia D.; Mariani C.; Maricic J.; Marinho F.; Marino A.D.; Marshak M.; Marshall C.; Marshall J.; Marteau J.; Martin-Albo J.; Martinez N.; Caicedo D.A.M.; Martynenko S.; Mason K.; Mastbaum A.; Masud M.; Matsuno S.; Matthews J.; Mauger C.; Mauri N.; Mavrokoridis K.; Mazza R.; Mazzacane A.; Mazzucato E.; McCluskey E.; McConkey N.; McFarland K.S.; McGrew C.; McNab A.; Mefodiev A.; Mehta P.; Melas P.; Mellinato M.; Mena O.; Menary S.; Mendez H.; Menegolli A.; Meng G.; Messier M.; Metcalf W.; Mewes M.; Meyer H.; Miao T.; Michna G.; Miedema T.; Migenda J.; Milincic R.; Miller W.; Mills J.; Milne C.; Mineev O.; Miranda O.G.; Miryala S.; Mishra C.; Mishra S.; Mislivec A.; Mladenov D.; Mocioiu I.; Moffat K.; Moggi N.; Mohanta R.; Mohayai T.A.; Mokhov N.; Molina J.A.; Bueno L.M.; Montanari A.; Montanari C.; Montanari D.; Zetina L.M.M.; Moon J.; Mooney M.; Moor A.; Moreno D.; Morgan B.; Morris C.; Mossey C.; Motuk E.; Moura C.A.; Mousseau J.; Mu W.; Mualem L.; Mueller J.; Muether M.; Mufson S.; Muheim F.; Muir A.; Mulhearn M.; Muramatsu H.; Murphy S.; Musser J.; Nachtman J.; Nagu S.; Nalbandyan M.; Nandakumar R.; Naples D.; Narita S.; Navas-Nicolas D.; Nayak N.; Nebot-Guinot M.; Necib L.; Negishi K.; Nelson J.K.; Nesbit J.; Nessi M.; Newbold D.; Newcomer M.; Newhart D.; Nichol R.; Niner E.; Nishimura K.; Norman A.; Northrop R.; Novella P.; Nowak J.A.; Oberling M.; Campo A.O.D.; Olivier A.; Onel Y.; Onishchuk Y.; Ott J.; Pagani L.; Pakvasa S.; Palamara O.; Palestini S.; Paley J.M.; Pallavicini M.; Palomares C.; Pantic E.; Paolone V.; Papadimitriou V.; Papaleo R.; Papanestis A.; Paramesvaran S.; Parke S.; Parsa Z.; Parvu M.; Pascoli S.; Pasqualini L.; Pasternak J.; Pater J.; Patrick C.; Patrizii L.; Patterson R.B.; Patton S.; Patzak T.; Paudel A.; Paulos B.; Paulucci L.; Pavlovic Z.; Pawloski G.; Payne D.; Pec V.; Peeters S.J.; Penichot Y.; Pennacchio E.; Penzo A.; Peres O.L.; Perry J.; Pershey D.; Pessina G.; Petrillo G.; Petta C.; Petti R.; Piastra F.; Pickering L.; Pietropaolo F.; Pillow J.; Plunkett R.; Poling R.; Pons X.; Poonthottathil N.; Pordes S.; Potekhin M.; Potenza R.; Potukuchi B.V.; Pozimski J.; Pozzato M.; Prakash S.; Prakash T.; Prince S.; Prior G.; Pugnere D.; Qi K.; Qian X.; Raaf J.; Raboanary R.; Radeka V.; Rademacker J.; Radics B.; Rafique A.; Raguzin E.; Rai M.; Rajaoalisoa M.; Rakhno I.; Rakotondramanana H.; Rakotondravohitra L.; Ramachers Y.; Rameika R.; Delgado M.R.; Ramson B.; Rappoldi A.; Raselli G.; Ratoff P.; Ravat S.; Razafinime H.; Real J.; Rebel B.; Redondo D.; Reggiani-Guzzo M.; Rehak T.; Reichenbacher J.; Reitzner S.D.; Renshaw A.; Rescia S.; Resnati F.; Reynolds A.; Riccobene G.; Rice L.C.; Rielage K.; Rigaut Y.; Rivera D.; Rochester L.; Roda M.; Rodrigues P.; Alonso M.R.; Rondon J.R.; Roeth A.; Rogers H.; Rosauro-Alcaraz S.; Rossella M.; Rout J.; Roy S.; Rubbia A.; Rubbia C.; Russell B.; Russell J.; Ruterbories D.; Saakyan R.; Sacerdoti S.; Safford T.; Sahu N.; Sala P.; Samios N.; Sanchez M.; Sanders D.A.; Sankey D.; Santana S.; Santos-Maldonado M.; Saoulidou N.; Sapienza P.; Sarasty C.; Sarcevic I.; Savage G.; Savinov V.; Scaramelli A.; Scarff A.; Scarpelli A.; Schaffer T.; Schellman H.; Schlabach P.; Schmitz D.; Scholberg K.; Schukraft A.; Segreto E.; Sensenig J.; Seong I.; Sergi A.; Sergiampietri F.; Sgalaberna D.; Shaevitz M.; Shafaq S.; Shamma M.; Sharma H.R.; Sharma R.; Shaw T.; Shepherd-Themistocleous C.; Shin S.; Shooltz D.; Shrock R.; Simard L.; Simos N.; Sinclair J.; Sinev G.; Singh J.; Singh V.; Sipos R.; Sippach F.; Sirri G.; Sitraka A.; Siyeon K.; Smargianaki D.; Smith A.; Smith A.; Smith E.; Smith P.; Smolik J.; Smy M.; Snopok P.; Nunes M.S.; Sobel H.; Soderberg M.; Salinas C.J.S.; Soldner-Rembold S.; Solomey N.; Solovov V.; Sondheim W.E.; Sorel M.; Soto-Oton J.; Sousa A.; Soustruznik K.; Spagliardi F.; Spanu M.; Spitz J.; Spooner N.J.; Spurgeon K.; Staley R.; Stancari M.; Stanco L.; Steiner H.; Stewart J.; Stillwell B.; Stock J.; Stocker F.; Stokes T.; Strait M.; Strauss T.; Striganov S.; Stuart A.; Summers D.; Surdo A.; Susic V.; Suter L.; Sutera C.; Svoboda R.; Szczerbinska B.; Szelc A.; Talaga R.; Tanaka H.; Oregui B.T.; Tapper A.; Tariq S.; Tatar E.; Tayloe R.; Teklu A.; Tenti M.; Terao K.; Ternes C.A.; Terranova F.; Testera G.; Thea A.; Thompson J.L.; Thorn C.; Timm S.; Tonazzo A.; Torti M.; Tortola M.; Tortorici F.; Totani D.; Toups M.; Touramanis C.; Trevor J.; Trzaska W.H.; Tsai Y.T.; Tsamalaidze Z.; Tsang K.; Tsverava N.; Tufanli S.; Tull C.; Tyley E.; Tzanov M.; Uchida M.A.; Urheim J.; Usher T.; Vagins M.; Vahle P.; Valdiviesso G.; Valencia E.; Vallari Z.; Valle J.W.; Vallecorsa S.; Berg R.V.; De Water R.G.V.; Forero D.V.; Varanini F.; Vargas D.; Varner G.; Vasel J.; Vasseur G.; Vaziri K.; Ventura S.; Verdugo A.; Vergani S.; Vermeulen M.A.; Verzocchi M.; De Souza H.V.; Vignoli C.; Vilela C.; Viren B.; Vrba T.; Wachala T.; Waldron A.V.; Wallbank M.; Wang H.; Wang J.; Wang Y.; Wang Y.; Warburton K.; Warner D.; Wascko M.; Waters D.; Watson A.; Weatherly P.; Weber A.; Weber M.; Wei H.; Weinstein A.; Wenman D.; Wetstein M.; While M.R.; White A.; Whitehead L.H.; Whittington D.; Wilking M.J.; Wilkinson C.; Williams Z.; Wilson F.; Wilson R.J.; Wolcott J.; Wongjirad T.; Wood K.; Wood L.; Worcester E.; Worcester M.; Wret C.; Wu W.; Wu W.; Xiao Y.; Yang G.; Yang T.; Yershov N.; Yonehara K.; Young T.; Yu B.; Yu J.; Zalesak J.; Zambelli L.; Zamorano B.; Zani A.; Zazueta L.; Zeller G.; Zennamo J.; Zeug K.; Zhang C.; Zhao M.; Zhivun E.; Zhu G.; Zimmerman E.D.; Zito M.; Zucchelli S.; Zuklin J.; Zutshi V.; Zwaska R.Abi B.; Acciarri R.; Acero M.A.; Adamov G.; Adams D.; Adinolfi M.; Ahmad Z.; Ahmed J.; Alion T.; Monsalve S.A.; Alt C.; Anderson J.; Andreopoulos C.; Andrews M.; Andrianala F.; Andringa S.; Ankowski A.; Antonova M.; Antusch S.; Aranda-Fernandez A.; Ariga A.; Arnold L.O.; Arroyave M.A.; Asaadi J.; Aurisano A.; Aushev V.; Autiero D.; Azfar F.; Back H.; Back J.J.; Backhouse C.; Baesso P.; Bagby L.; Bajou R.; Balasubramanian S.; Baldi P.; Bambah B.; Barao F.; Barenboim G.; Barker G.; Barkhouse W.; Barnes C.; Barr G.; Monarca J.B.; Barros N.; Barrow J.L.; Bashyal A.; Basque V.; Bay F.; Alba J.B.; Beacom J.F.; Bechetoille E.; Behera B.; Bellantoni L.; Bellettini G.; Bellini V.; Beltramello O.; Belver D.; Benekos N.; Neves F.B.; Berger J.; Berkman S.; Bernardini P.; Berner R.M.; Berns H.; Bertolucci S.; Betancourt M.; Bezawada Y.; Bhattacharjee M.; Bhuyan B.; Biagi S.; Bian J.; Biassoni M.; Biery K.; Bilki B.; Bishai M.; Bitadze A.; Blake A.; Siffert B.B.; Blaszczyk F.; Blazey G.; Blucher E.; Boissevain J.; Bolognesi S.; Bolton T.; Bonesini M.; Bongrand M.; Bonini F.; Booth A.; Booth C.; Bordoni S.; Borkum A.; Boschi T.; Bostan N.; Bour P.; Boyd S.; Boyden D.; Bracinik J.; Braga D.; Brailsford D.; Brandt A.; Bremer J.; Brew C.; Brianne E.; Brice S.J.; Brizzolari C.; Bromberg C.; Brooijmans G.; Brooke J.; Bross A.; Brunetti G.; Buchanan N.; Budd H.; Caiulo D.; Calafiura P.; Calcutt J.; Calin M.; Calvez S.; Calvo E.; Camilleri L.; Caminata A.; Campanelli M.; Caratelli D.; Carini G.; Carlus B.; Carniti P.; Terrazas I.C.; Carranza H.; Castillo A.; Castromonte C.; Cattadori C.; Cavalier F.; Cavanna F.; Centro S.; Cerati G.; Cervelli A.; Villanueva A.C.; Chalifour M.; Chang C.; Chardonnet E.; Chatterjee A.; Chattopadhyay S.; Chaves J.; Chen H.; Chen M.; Chen Y.; Cherdack D.; Chi C.; Childress S.; Chiriacescu A.; Cho K.; Choubey S.; Christensen A.; Christian D.; Christodoulou G.; Church E.; Clarke P.; Coan T.E.; Cocco A.G.; Coelho J.; Conley E.; Conrad J.; Convery M.; Corwin L.; Cotte P.; Cremaldi L.; Cremonesi L.; Crespo-Anadon J.I.; Cristaldo E.; Cross R.; Cuesta C.; Cui Y.; Cussans D.; Dabrowski M.; Motta H.D.; Peres L.D.S.; David Q.; Davies G.S.; Davini S.; Dawson J.; De K.; Almeida R.M.D.; Debbins P.; Bonis I.D.; Decowski M.; Gouvea A.D.; Holanda P.C.D.; Astiz I.L.D.I.; Deisting A.; Jong P.D.; Delbart A.; Delepine D.; Delgado M.; Dell'acqua A.; Lurgio P.D.; Neto J.R.D.M.; Demuth D.M.; Dennis S.; Densham C.; Deptuch G.; Roeck A.D.; Romeri V.D.; Vries J.D.; Dharmapalan R.; Dias M.; Diaz F.; Diaz J.; Domizio S.D.; Giulio L.D.; Ding P.; Noto L.D.; Distefano C.; Diurba R.; Diwan M.; Djurcic Z.; Dokania N.; Dolinski M.; Domine L.; Douglas D.; Drielsma F.; Duchesneau D.; Duffy K.; Dunne P.; Durkin T.; Duyang H.; Dvornikov O.; Dwyer D.; Dyshkant A.; Eads M.; Edmunds D.; Eisch J.; Emery S.; Ereditato A.; Escobar C.; Sanchez L.E.; Evans J.J.; Ewart E.; Ezeribe A.C.; Fahey K.; Falcone A.; Farnese C.; Farzan Y.; Felix J.; Fernandez-Martinez E.; Menendez P.F.; Ferraro F.; Fields L.; Filkins A.; Filthaut F.; Fitzpatrick R.S.; Flanagan W.; Fleming B.; Flight R.; Fowler J.; Fox W.; Franc J.; Francis K.; Franco D.; Freeman J.; Freestone J.; Fried J.; Friedland A.; Fuess S.; Furic I.; Furmanski A.P.; Gago A.; Gallagher H.; Gallego-Ros A.; Gallice N.; Galymov V.; Gamberini E.; Gamble T.; Gandhi R.; Gandrajula R.; Gao S.; Garcia-Gamez D.; 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Supernova neutrino burst detection with the Deep Underground Neutrino Experiment

The Deep Underground Neutrino Experiment (DUNE), a 40-kton underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The general capabilities of DUNE for neutrino detection in the relevant few- to few-tens-of-MeV neutrino energy range will be described. As an example, DUNE's ability to constrain the νe spectral parameters of the neutrino burst will be considered

Experiment Simulation Configurations Approximating DUNE TDR

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment consisting of a high-power, broadband neutrino beam, a highly capable near detector located on site at Fermilab, in Batavia, Illinois, and a massive liquid argon time projection chamber (LArTPC) far detector located at the 4850L of Sanford Underground Research Facility in Lead, South Dakota. The long-baseline physics sensitivity calculations presented in the DUNE Physics TDR, and in a related physics paper, rely upon simulation of the neutrino beam line, simulation of neutrino interactions in the near and far detectors, fully automated event reconstruction and neutrino classification, and detailed implementation of systematic uncertainties. The purpose of this posting is to provide a simplified summary of the simulations that went into this analysis to the community, in order to facilitate phenomenological studies of long-baseline oscillation at DUNE. Simulated neutrino flux files and a GLoBES configuration describing the far detector reconstruction and selection performance are included as ancillary files to this posting. A simple analysis using these configurations in GLoBES produces sensitivity that is similar, but not identical, to the official DUNE sensitivity. DUNE welcomes those interested in performing phenomenological work as members of the collaboration, but also recognizes the benefit of making these configurations readily available to the wider community

Neutrino interaction classification with a convolutional neural network in the DUNE far detector

The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2–5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino energies above 2 GeV. When considering all electron neutrino and antineutrino interactions as signal, a selection purity of 90% is achieved. These event selections are critical to maximize the sensitivity of the experiment to CP-violating effects