M. Petrovici - FOPI Collaboration

M. Petrovici
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M. Petrovici
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FOPI Collaboration
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Computer Science - Neural and Evolutionary Computing (5)
 
Quantitative Biology - Neurons and Cognition (4)
 
Statistics - Machine Learning (4)
 
Nuclear Experiment (3)
 
Physics - Biological Physics (2)
 
High Energy Physics - Phenomenology (2)
 
Physics - Disordered Systems and Neural Networks (2)
 
Nuclear Theory (2)
 
High Energy Physics - Experiment (1)
 
Physics - Instrumentation and Detectors (1)

Publications Authored By M. Petrovici

Despite being originally inspired by the central nervous system, artificial neural networks have diverged from their biological archetypes as they have been remodeled to fit particular tasks. In this paper, we review several possibilites to reverse map these architectures to biologically more realistic spiking networks with the aim of emulating them on fast, low-power neuromorphic hardware. Since many of these devices employ analog components, which cannot be perfectly controlled, finding ways to compensate for the resulting effects represents a key challenge. Read More

A simple approach based on the separation of wounded nucleons in an A-A collision in two categories, those suffering single collisions - corona and the rest - core, estimated within a Glauber Monte-Carlo approach, explains the centrality dependence of the light flavor hadrons production in Pb-Pb collisions at $\sqrt{s_{NN}}$=2.76 TeV. The core contribution does not include any dependence of any process on the fireball shape as a function of the impact parameter. Read More

How spiking networks are able to perform probabilistic inference is an intriguing question, not only for understanding information processing in the brain, but also for transferring these computational principles to neuromorphic silicon circuits. A number of computationally powerful spiking network models have been proposed, but most of them have only been tested, under ideal conditions, in software simulations. Any implementation in an analog, physical system, be it in vivo or in silico, will generally lead to distorted dynamics due to the physical properties of the underlying substrate. Read More

Emulating spiking neural networks on analog neuromorphic hardware offers several advantages over simulating them on conventional computers, particularly in terms of speed and energy consumption. However, this usually comes at the cost of reduced control over the dynamics of the emulated networks. In this paper, we demonstrate how iterative training of a hardware-emulated network can compensate for anomalies induced by the analog substrate. Read More

The highly variable dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference but stand in apparent contrast to the deterministic response of neurons measured in vitro. Based on a propagation of the membrane autocorrelation across spike bursts, we provide an analytical derivation of the neural activation function that holds for a large parameter space, including the high-conductance state. On this basis, we show how an ensemble of leaky integrate-and-fire neurons with conductance-based synapses embedded in a spiking environment can attain the correct firing statistics for sampling from a well-defined target distribution. Read More

2016Jul
Authors: CBM Collaboration, T. Ablyazimov, A. Abuhoza, R. P. Adak, M. Adamczyk, K. Agarwal, M. M. Aggarwal, Z. Ahammed, F. Ahmad, N. Ahmad, S. Ahmad, A. Akindinov, P. Akishin, E. Akishina, T. Akishina, V. Akishina, A. Akram, M. Al-Turany, I. Alekseev, E. Alexandrov, I. Alexandrov, S. Amar-Youcef, M. Anđelić, O. Andreeva, C. Andrei, A. Andronic, Yu. Anisimov, H. Appelshäuser, D. Argintaru, E. Atkin, S. Avdeev, R. Averbeck, M. D. Azmi, V. Baban, M. Bach, E. Badura, S. Bähr, T. Balog, M. Balzer, E. Bao, N. Baranova, T. Barczyk, D. Bartoş, S. Bashir, M. Baszczyk, O. Batenkov, V. Baublis, M. Baznat, J. Becker, K. -H. Becker, S. Belogurov, D. Belyakov, J. Bendarouach, I. Berceanu, A. Bercuci, A. Berdnikov, Y. Berdnikov, R. Berendes, G. Berezin, C. Bergmann, D. Bertini, O. Bertini, C. Beşliu, O. Bezshyyko, P. P. Bhaduri, A. Bhasin, A. K. Bhati, B. Bhattacharjee, A. Bhattacharyya, T. K. Bhattacharyya, S. Biswas, T. Blank, D. Blau, V. Blinov, C. Blume, Yu. Bocharov, J. Book, T. Breitner, U. Brüning, J. Brzychczyk, A. Bubak, H. Büsching, T. Bus, V. Butuzov, A. Bychkov, A. Byszuk, Xu Cai, M. Cálin, Ping Cao, G. Caragheorgheopol, I. Carević, V. Cătănescu, A. Chakrabarti, S. Chattopadhyay, A. Chaus, Hongfang Chen, LuYao Chen, Jianping Cheng, V. Chepurnov, H. Cherif, A. Chernogorov, M. I. Ciobanu, G. Claus, F. Constantin, M. Csanád, N. D'Ascenzo, Supriya Das, Susovan Das, J. de Cuveland, B. Debnath, D. Dementiev, Wendi Deng, Zhi Deng, H. Deppe, I. Deppner, O. Derenovskaya, C. A. Deveaux, M. Deveaux, K. Dey, M. Dey, P. Dillenseger, V. Dobyrn, D. Doering, Sheng Dong, A. Dorokhov, M. Dreschmann, A. Drozd, A. K. Dubey, S. Dubnichka, Z. Dubnichkova, M. Dürr, L. Dutka, M. Dželalija, V. V. Elsha, D. Emschermann, H. Engel, V. Eremin, T. Eşanu, J. Eschke, D. Eschweiler, Huanhuan Fan, Xingming Fan, M. Farooq, O. Fateev, Shengqin Feng, S. P. D. Figuli, I. Filozova, D. Finogeev, P. Fischer, H. Flemming, J. Förtsch, U. Frankenfeld, V. Friese, E. Friske, I. Fröhlich, J. Frühauf, J. Gajda, T. Galatyuk, G. Gangopadhyay, C. García Chávez, J. Gebelein, P. Ghosh, S. K. Ghosh, S. Gläßel, M. Goffe, L. Golinka-Bezshyyko, V. Golovatyuk, S. Golovnya, V. Golovtsov, M. Golubeva, D. Golubkov, A. Gómez Ramírez, S. Gorbunov, S. Gorokhov, D. Gottschalk, P. Gryboś, A. Grzeszczuk, F. Guber, K. Gudima, M. Gumiński, A. Gupta, Yu. Gusakov, Dong Han, H. Hartmann, Shue He, J. Hehner, N. Heine, A. Herghelegiu, N. Herrmann, B. Heß, J. M. Heuser, A. Himmi, C. Höhne, R. Holzmann, Dongdong Hu, Guangming Huang, Xinjie Huang, D. Hutter, A. Ierusalimov, E. -M. Ilgenfritz, M. Irfan, D. Ivanischev, M. Ivanov, P. Ivanov, Valery Ivanov, Victor Ivanov, Vladimir Ivanov, A. Ivashkin, K. Jaaskelainen, H. Jahan, V. Jain, V. Jakovlev, T. Janson, Di Jiang, A. Jipa, I. Kadenko, P. Kähler, B. Kämpfer, V. Kalinin, J. Kallunkathariyil, K. -H. Kampert, E. Kaptur, R. Karabowicz, O. Karavichev, T. Karavicheva, D. Karmanov, V. Karnaukhov, E. Karpechev, K. Kasiński, G. Kasprowicz, M. Kaur, A. Kazantsev, U. Kebschull, G. Kekelidze, M. M. Khan, S. A. Khan, A. Khanzadeev, F. Khasanov, A. Khvorostukhin, V. Kirakosyan, M. Kirejczyk, A. Kiryakov, M. Kiš, I. Kisel, P. Kisel, S. Kiselev, T. Kiss, P. Klaus, R. Kłeczek, Ch. Klein-Bösing, V. Kleipa, V. Klochkov, P. Kmon, K. Koch, L. Kochenda, P. Koczoń, W. Koenig, M. Kohn, B. W. Kolb, A. Kolosova, B. Komkov, M. Korolev, I. Korolko, R. Kotte, A. Kovalchuk, S. Kowalski, M. Koziel, G. Kozlov, V. Kozlov, V. Kramarenko, P. Kravtsov, E. Krebs, C. Kreidl, I. Kres, D. Kresan, G. Kretschmar, M. Krieger, A. V. Kryanev, E. Kryshen, M. Kuc, W. Kucewicz, V. Kucher, L. Kudin, A. Kugler, Ajit Kumar, Ashwini Kumar, L. Kumar, J. Kunkel, A. Kurepin, N. Kurepin, A. Kurilkin, P. Kurilkin, V. Kushpil, S. Kuznetsov, V. Kyva, V. Ladygin, C. Lara, P. Larionov, A. Laso García, E. Lavrik, I. Lazanu, A. Lebedev, S. Lebedev, E. Lebedeva, J. Lehnert, J. Lehrbach, Y. Leifels, F. Lemke, Cheng Li, Qiyan Li, Xin Li, Yuanjing Li, V. Lindenstruth, B. Linnik, Feng Liu, I. Lobanov, E. Lobanova, S. Löchner, P. -A. Loizeau, S. A. Lone, J. A. Lucio Martínez, Xiaofeng Luo, A. Lymanets, Pengfei Lyu, A. Maevskaya, S. Mahajan, D. P. Mahapatra, T. Mahmoud, P. Maj, Z. Majka, A. Malakhov, E. Malankin, D. Malkevich, O. Malyatina, H. Malygina, M. M. Mandal, S. Mandal, V. Manko, S. Manz, A. M. Marin Garcia, J. Markert, S. Masciocchi, T. Matulewicz, L. Meder, M. Merkin, V. Mialkovski, J. Michel, N. Miftakhov, L. Mik, K. Mikhailov, V. Mikhaylov, B. Milanović, V. Militsija, D. Miskowiec, I. Momot, T. Morhardt, S. Morozov, W. F. J. Müller, C. Müntz, S. Mukherjee, C. E. Muńoz Castillo, Yu. Murin, R. Najman, C. Nandi, E. Nandy, L. Naumann, T. Nayak, A. Nedosekin, V. S. Negi, W. Niebur, V. Nikulin, D. Normanov, A. Oancea, Kunsu Oh, Yu. Onishchuk, G. Ososkov, P. Otfinowski, E. Ovcharenko, S. Pal, I. Panasenko, N. R. Panda, S. Parzhitskiy, V. Patel, C. Pauly, M. Penschuck, D. Peshekhonov, V. Peshekhonov, V. Petráček, M. Petri, M. Petriş, A. Petrovici, M. Petrovici, A. Petrovskiy, O. Petukhov, D. Pfeifer, K. Piasecki, J. Pieper, J. Pietraszko, R. Płaneta, V. Plotnikov, V. Plujko, J. Pluta, A. Pop, V. Pospisil, K. Poźniak, A. Prakash, S. K. Prasad, M. Prokudin, I. Pshenichnov, M. Pugach, V. Pugatch, S. Querchfeld, S. Rabtsun, L. Radulescu, S. Raha, F. Rami, R. Raniwala, S. Raniwala, A. Raportirenko, J. Rautenberg, J. Rauza, R. Ray, S. Razin, P. Reichelt, S. Reinecke, A. Reinefeld, A. Reshetin, C. Ristea, O. Ristea, A. Rodriguez Rodriguez, F. Roether, R. Romaniuk, A. Rost, E. Rostchin, I. Rostovtseva, Amitava Roy, Ankhi Roy, J. Rożynek, Yu. Ryabov, A. Sadovsky, R. Sahoo, P. K. Sahu, S. K. Sahu, J. Saini, S. Samanta, S. S. Sambyal, V. Samsonov, J. Sánchez Rosado, O. Sander, S. Sarangi, T. Satława, S. Sau, V. Saveliev, S. Schatral, C. Schiaua, F. Schintke, C. J. Schmidt, H. R. Schmidt, K. Schmidt, J. Scholten, K. Schweda, F. Seck, S. Seddiki, I. Selyuzhenkov, A. Semennikov, A. Senger, P. Senger, A. Shabanov, A. Shabunov, Ming Shao, A. D. Sheremetiev, Shusu Shi, N. Shumeiko, V. Shumikhin, I. Sibiryak, B. Sikora, A. Simakov, C. Simon, C. Simons, R. N. Singaraju, A. K. Singh, B. K. Singh, C. P. Singh, V. Singhal, M. Singla, P. Sitzmann, K. Siwek-Wilczyńska, L. Škoda, I. Skwira-Chalot, I. Som, Guofeng Song, Jihye Song, Z. Sosin, D. Soyk, P. Staszel, M. Strikhanov, S. Strohauer, J. Stroth, C. Sturm, R. Sultanov, Yongjie Sun, D. Svirida, O. Svoboda, A. Szabó, R. Szczygieł, R. Talukdar, Zebo Tang, M. Tanha, J. Tarasiuk, O. Tarassenkova, M. -G. Târzilă, M. Teklishyn, T. Tischler, P. Tlustý, T. Tölyhi, A. Toia, N. Topil'skaya, M. Träger, S. Tripathy, I. Tsakov, Yu. Tsyupa, A. Turowiecki, N. G. Tuturas, F. Uhlig, E. Usenko, I. Valin, D. Varga, I. Vassiliev, O. Vasylyev, E. Verbitskaya, W. Verhoeven, A. Veshikov, R. Visinka, Y. P. Viyogi, S. Volkov, A. Volochniuk, A. Vorobiev, Aleksey Voronin, Alexander Voronin, V. Vovchenko, M. Vznuzdaev, Dong Wang, Xi-Wei Wang, Yaping Wang, Yi Wang, M. Weber, C. Wendisch, J. P. Wessels, M. Wiebusch, J. Wiechula, D. Wielanek, A. Wieloch, A. Wilms, N. Winckler, M. Winter, K. Wiśniewski, Gy. Wolf, Sanguk Won, Ke-Jun Wu, J. Wüstenfeld, Changzhou Xiang, Nu Xu, Junfeng Yang, Rongxing Yang, Zhongbao Yin, In-Kwon Yoo, B. Yuldashev, I. Yushmanov, W. Zabołotny, Yu. Zaitsev, N. I. Zamiatin, Yu. Zanevsky, M. Zhalov, Yifei Zhang, Yu Zhang, Lei Zhao, Jiajun Zheng, Sheng Zheng, Daicui Zhou, Jing Zhou, Xianglei Zhu, A. Zinchenko, W. Zipper, M. Żoładź, P. Zrelov, V. Zryuev, P. Zumbruch, M. Zyzak

Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is studied at very high temperatures and nearly vanishing net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was created at experiments at RHIC and LHC. Read More

Predictions made in Albacete {\it et al} prior to the LHC $p+$Pb run at $\sqrt{s_{NN}} = 5$ TeV are compared to currently available data. Some predictions shown here have been updated by including the same experimental cuts as the data. Some additional predictions are also presented, especially for quarkonia, that were provided to the experiments before the data were made public but were too late for the original publication are also shown here. Read More

Multi-gap RPC prototypes with readout on a multi-strip electrode were developed for the small polar angle region of the CBM-TOF subdetector, the most demanding zone in terms of granularity and counting rate. The prototypes are based on low resistivity ($\sim$10$^{10}$ $\Omega$cm) glass electrodes for performing in high counting rate environment. The strip width/pitch size was chosen such to fulfill the impedance matching with the front-end electronics and the granularity requirements of the innermost zone of the CBM-TOF wall. Read More

The apparent stochasticity of in-vivo neural circuits has long been hypothesized to represent a signature of ongoing stochastic inference in the brain. More recently, a theoretical framework for neural sampling has been proposed, which explains how sample-based inference can be performed by networks of spiking neurons. One particular requirement of this approach is that the neural response function closely follows a logistic curve. Read More