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Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13  TeV with the ATLAS Detector.

Publication ,  Journal Article
Aad, G; Abbott, B; Abeling, K; Abicht, NJ; Abidi, SH; Aboulhorma, A; Abramowicz, H; Abreu, H; Abulaiti, Y; Abusleme Hoffman, AC; Acharya, BS ...
Published in: Physical review letters
February 2024

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140  fb^{-1} of pp collisions at sqrt[s]=13  TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e,μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

Duke Scholars

Published In

Physical review letters

DOI

EISSN

1079-7114

ISSN

0031-9007

Publication Date

February 2024

Volume

132

Issue

8

Start / End Page

081801

Related Subject Headings

  • General Physics
  • 51 Physical sciences
  • 49 Mathematical sciences
  • 40 Engineering
  • 09 Engineering
  • 02 Physical Sciences
  • 01 Mathematical Sciences
 

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Aad, G., Abbott, B., Abeling, K., Abicht, N. J., Abidi, S. H., Aboulhorma, A., … Ciungu, B. M. (2024). Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13  TeV with the ATLAS Detector. Physical Review Letters, 132(8), 081801. https://doi.org/10.1103/physrevlett.132.081801
Aad, G., B. Abbott, K. Abeling, N. J. Abicht, S. H. Abidi, A. Aboulhorma, H. Abramowicz, et al. “Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13  TeV with the ATLAS Detector.Physical Review Letters 132, no. 8 (February 2024): 081801. https://doi.org/10.1103/physrevlett.132.081801.
Aad G, Abbott B, Abeling K, Abicht NJ, Abidi SH, Aboulhorma A, et al. Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13  TeV with the ATLAS Detector. Physical review letters. 2024 Feb;132(8):081801.
Aad, G., et al. “Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13  TeV with the ATLAS Detector.Physical Review Letters, vol. 132, no. 8, Feb. 2024, p. 081801. Epmc, doi:10.1103/physrevlett.132.081801.
Aad G, Abbott B, Abeling K, Abicht NJ, Abidi SH, Aboulhorma A, Abramowicz H, Abreu H, Abulaiti Y, Abusleme Hoffman AC, Acharya BS, Adam Bourdarios C, Adamczyk L, Adamek L, Addepalli SV, Addison MJ, Adelman J, Adiguzel A, Adye T, Affolder AA, Afik Y, Agaras MN, Agarwala J, Aggarwal A, Agheorghiesei C, Ahmad A, Ahmadov F, Ahmed WS, Ahuja S, Ai X, Aielli G, Aikot A, Ait Tamlihat M, Aitbenchikh B, Aizenberg I, Akbiyik M, Åkesson TPA, Akimov AV, Akiyama D, Akolkar NN, Al Khoury K, Alberghi GL, Albert J, Albicocco P, Albouy GL, Alderweireldt S, Aleksa M, Aleksandrov IN, Alexa C, Alexopoulos T, Alfonsi F, Algren M, Alhroob M, Ali B, Ali HMJ, Ali S, Alibocus SW, Aliev M, Alimonti G, Alkakhi W, Allaire C, Allbrooke BMM, Allen JF, Allendes Flores CA, Allport PP, Aloisio A, Alonso F, Alpigiani C, Alvarez Estevez M, Alvarez Fernandez A, Alves Cardoso M, Alviggi MG, Aly M, Amaral Coutinho Y, Ambler A, Amelung C, Amerl M, Ames CG, Amidei D, Amor Dos Santos SP, Amos KR, Ananiev V, Anastopoulos C, Andeen T, Anders JK, Andrean SY, Andreazza A, Angelidakis S, Angerami A, Anisenkov AV, Annovi A, Antel C, Anthony MT, Antipov E, Antonelli M, Anulli F, Aoki M, Aoki T, Aparisi Pozo JA, Aparo MA, Aperio Bella L, Appelt C, Apyan A, Aranzabal N, Arcangeletti C, Arce ATH, Arena E, Arguin J-F, Argyropoulos S, Arling J-H, Arnaez O, Arnold H, Artoni G, Asada H, Asai K, Asai S, Asbah NA, Assahsah J, Assamagan K, Astalos R, Atashi S, Atkin RJ, Atkinson M, Atmani H, Atmasiddha PA, Augsten K, Auricchio S, Auriol AD, Austrup VA, Avolio G, Axiotis K, Azuelos G, Babal D, Bachacou H, Bachas K, Bachiu A, Backman F, Badea A, Bagnaia P, Bahmani M, Bailey AJ, Bailey VR, Baines JT, Baines L, Bakalis C, Baker OK, Bakos E, Bakshi Gupta D, Balakrishnan V, Balasubramanian R, Baldin EM, Balek P, Ballabene E, Balli F, Baltes LM, Balunas WK, Balz J, Banas E, Bandieramonte M, Bandyopadhyay A, Bansal S, Barak L, Barakat M, Barberio EL, Barberis D, Barbero M, Barends KN, Barillari T, Barisits M-S, Barklow T, Baron P, Baron Moreno DA, Baroncelli A, Barone G, Barr AJ, Barr JD, Barranco Navarro L, Barreiro F, Barreiro Guimarães da Costa J, Barron U, Barros Teixeira MG, Barsov S, Bartels F, Bartoldus R, Barton AE, Bartos P, Basan A, Baselga M, Bassalat A, Basso MJ, Basson CR, Bates RL, Batlamous S, Batley JR, Batool B, Battaglia M, Battulga D, Bauce M, Bauer M, Bauer P, Bazzano Hurrell LT, Beacham JB, Beau T, Beauchemin PH, Becherer F, Bechtle P, Beck HP, Becker K, Beddall AJ, Bednyakov VA, Bee CP, Beemster LJ, Beermann TA, Begalli M, Begel M, Behera A, Behr JK, Beirer JF, Beisiegel F, Belfkir M, Bella G, Bellagamba L, Bellerive A, Bellos P, Beloborodov K, Belyaev NL, Benchekroun D, Bendebba F, Benhammou Y, Benoit M, Bensinger JR, Bentvelsen S, Beresford L, Beretta M, Bergeaas Kuutmann E, Berger N, Bergmann B, Beringer J, Bernardi G, Bernius C, Bernlochner FU, Bernon F, Berry T, Berta P, Berthold A, Bertram IA, Bethke S, Betti A, Bevan AJ, Bhamjee M, Bhatta S, Bhattacharya DS, Bhattarai P, Bhopatkar VS, Bi R, Bianchi RM, Bianco G, Biebel O, Bielski R, Biglietti M, Billoud TRV, Bindi M, Bingul A, Bini C, Biondini A, Birch-Sykes CJ, Bird GA, Birman M, Biros M, Biryukov S, Bisanz T, Bisceglie E, Biswal JP, Biswas D, Bitadze A, Bjørke K, Bloch I, Blocker C, Blue A, Blumenschein U, Blumenthal J, Bobbink GJ, Bobrovnikov VS, Boehler M, Boehm B, Bogavac D, Bogdanchikov AG, Bohm C, Boisvert V, Bokan P, Bold T, Bomben M, Bona M, Boonekamp M, Booth CD, Borbély AG, Bordulev IS, Borecka-Bielska HM, Borgna LS, Borissov G, Bortoletto D, Boscherini D, Bosman M, Bossio Sola JD, Bouaouda K, Bouchhar N, Boudreau J, Bouhova-Thacker EV, Boumediene D, Bouquet R, Boveia A, Boyd J, Boye D, Boyko IR, Bracinik J, Brahimi N, Brandt G, Brandt O, Braren F, Brau B, Brau JE, Brener R, Brenner L, Brenner R, Bressler S, Britton D, Britzger D, Brock I, Brooijmans G, Brooks WK, Brost E, Brown LM, Bruce LE, Bruckler TL, Bruckman de Renstrom PA, Brüers B, Bruni A, Bruni G, Bruschi M, Bruscino N, Buanes T, Buat Q, Buchin D, Buckley AG, Bulekov O, Bullard BA, Burdin S, Burgard CD, Burger AM, Burghgrave B, Burlayenko O, Burr JTP, Burton CD, Burzynski JC, Busch EL, Büscher V, Bussey PJ, Butler JM, Buttar CM, Butterworth JM, Buttinger W, Buxo Vazquez CJ, Buzykaev AR, Cabrera Urbán S, Cadamuro L, Caforio D, Cai H, Cai Y, Cairo VMM, Cakir O, Calace N, Calafiura P, Calderini G, Calfayan P, Callea G, Caloba LP, Calvet D, Calvet S, Calvet TP, Calvetti M, Camacho Toro R, Camarda S, Camarero Munoz D, Camarri P, Camerlingo MT, Cameron D, Camincher C, Campanelli M, Camplani A, Canale V, Canesse A, Cantero J, Cao Y, Capocasa F, Capua M, Carbone A, Cardarelli R, Cardenas JCJ, Cardillo F, Carli T, Carlino G, Carlotto JI, Carlson BT, Carlson EM, Carminati L, Carnelli A, Carnesale M, Caron S, Carquin E, Carrá S, Carratta G, Carrio Argos F, Carter JWS, Carter TM, Casado MP, Caspar M, Castiglia EG, Castillo FL, Castillo Garcia L, Castillo Gimenez V, Castro NF, Catinaccio A, Catmore JR, Cavaliere V, Cavalli N, Cavasinni V, Cekmecelioglu YC, Celebi E, Celli F, Centonze MS, Cepaitis V, Cerny K, Cerqueira AS, Cerri A, Cerrito L, Cerutti F, Cervato B, Cervelli A, Cesarini G, Cetin SA, Chadi Z, Chakraborty D, Chan J, Chan WY, Chapman JD, Chapon E, Chargeishvili B, Charlton DG, Charman TP, Chatterjee M, Chauhan C, Chekanov S, Chekulaev SV, Chelkov GA, Chen A, Chen B, Chen H, Chen J, Chen M, Chen S, Chen SJ, Chen X, Chen Y, Cheng CL, Cheng HC, Cheong S, Cheplakov A, Cheremushkina E, Cherepanova E, Cherkaoui El Moursli R, Cheu E, Cheung K, Chevalier L, Chiarella V, Chiarelli G, Chiedde N, Chiodini G, Chisholm AS, Chitan A, Chitishvili M, Chizhov MV, Choi K, Chomont AR, Chou Y, Chow EYS, Chowdhury T, Chu KL, Chu MC, Chu X, Chudoba J, Chwastowski JJ, Cieri D, Ciesla KM, Cindro V, Ciocio A, Cirotto F, Citron ZH, Citterio M, Ciubotaru DA, Ciungu BM. Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13  TeV with the ATLAS Detector. Physical review letters. 2024 Feb;132(8):081801.

Published In

Physical review letters

DOI

EISSN

1079-7114

ISSN

0031-9007

Publication Date

February 2024

Volume

132

Issue

8

Start / End Page

081801

Related Subject Headings

  • General Physics
  • 51 Physical sciences
  • 49 Mathematical sciences
  • 40 Engineering
  • 09 Engineering
  • 02 Physical Sciences
  • 01 Mathematical Sciences