J. Ho - University Victoria

J. Ho
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Name
J. Ho
Affiliation
University Victoria
City
Victoria
Country
Canada

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High Energy Physics - Experiment (10)
 
High Energy Physics - Theory (9)
 
Physics - Instrumentation and Detectors (8)
 
High Energy Physics - Phenomenology (7)
 
Computer Science - Learning (6)
 
Computer Science - Artificial Intelligence (5)
 
Physics - Materials Science (4)
 
Quantum Physics (4)
 
General Relativity and Quantum Cosmology (4)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (3)
 
Physics - Optics (3)
 
Physics - Other (2)
 
Computer Science - Computer Vision and Pattern Recognition (2)
 
Statistics - Applications (2)
 
Computer Science - Neural and Evolutionary Computing (2)
 
Statistics - Machine Learning (2)
 
Physics - Soft Condensed Matter (2)
 
Physics - Superconductivity (1)
 
Quantitative Biology - Quantitative Methods (1)
 
Astrophysics (1)
 
Quantitative Biology - Subcellular Processes (1)
 
Computer Science - Robotics (1)
 
Computer Science - Distributed; Parallel; and Cluster Computing (1)
 
Physics - Biological Physics (1)
 
Quantitative Biology - Neurons and Cognition (1)
 
Computer Science - Information Theory (1)
 
Mathematics - Information Theory (1)

Publications Authored By J. Ho

2017May
Authors: MicroBooNE collaboration, R. Acciarri, C. Adams, R. An, J. Anthony, J. Asaadi, M. Auger, L. Bagby, S. Balasubramanian, B. Baller, C. Barnes, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, B. Bullard, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. Chen, E. Church, D. Cianci, E. Cohen, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadon, G. De Geronimo, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, A. A. Fadeeva, B. T. Fleming, W. Foreman, A. P. Furmanski, D. Garcia-Gamez, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, A. Hourlier, E. -C. Huang, C. James, J. Jan de Vries, C. -M. Jen, L. Jiang, R. A. Johnson, J. Joshi, H. Jostlein, D. Kaleko, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, S. Li, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A. Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, E. Piasetzky, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, V. Radeka, A. Rafique, S. Rescia, L. Rochester, C. Rudolf von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, A. Smith, E. L. Snider, M. Soderberg, S. Soldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, C. Thorn, M. Toups, Y. -T. Tsai, S. Tufanli, T. Usher, W. Van De Pontseele, R. G. Van de Water, B. Viren, M. Weber, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, L. Yates, B. Yu, G. P. Zeller, J. Zennamo, C. Zhang

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Read More

Suffix Array (SA) is a cardinal data structure in many pattern matching applications, including data compression, plagiarism detection and sequence alignment. However, as the volumes of data increase abruptly, the construction of SA is not amenable to the current large-scale data processing frameworks anymore due to its intrinsic proliferation of suffixes during the construction. That is, ameliorating the performance by just adding the resources to the frameworks becomes less cost- effective, even having the severe diminishing returns. Read More

This paper aims to bridge the affective gap between image content and the emotional response of the viewer it elicits by using High-Level Concepts (HLCs). In contrast to previous work that relied solely on low-level features or used convolutional neural network (CNN) as a black-box, we use HLCs generated by pretrained CNNs in an explicit way to investigate the relations/associations between these HLCs and a (small) set of Ekman's emotional classes. As a proof-of-concept, we first propose a linear admixture model for modeling these relations, and the resulting computational framework allows us to determine the associations between each emotion class and certain HLCs (objects and places). Read More

2017Apr
Authors: MicroBooNE collaboration, R. Acciarri, C. Adams, R. An, J. Anthony, J. Asaadi, M. Auger, L. Bagby, S. Balasubramanian, B. Baller, C. Barnes, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, L. Bugel, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. Chen, E. Church, D. Cianci, E. Cohen, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadon, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, B. T. Fleming, W. Foreman, A. P. Furmanski, D. Garcia-Gamez, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, E. -C. Huang, C. James, J. Jan de Vries, C. -M. Jen, L. Jiang, R. A. Johnson, J. Joshi, H. Jostlein, D. Kaleko, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A. Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, E. Piasetzky, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, A. Rafique, L. Rochester, C. Rudolf von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, E. L. Snider, M. Soderberg, S. Soldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, K. A. Sutton, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, M. Toups, Y. -T. Tsai, S. Tufanli, T. Usher, R. G. Van de Water, B. Viren, M. Weber, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, L. Yates, G. P. Zeller, J. Zennamo, C. Zhang

The MicroBooNE liquid argon time projection chamber (LArTPC) has been taking data at Fermilab since 2015 collecting, in addition to neutrino beam, cosmic-ray muons. Results are presented on the reconstruction of Michel electrons produced by the decay at rest of cosmic-ray muons. Michel electrons are abundantly produced in the TPC, and given their well known energy spectrum can be used to study MicroBooNE's detector response to low-energy electrons (electrons with energies up to ~50 MeV). Read More

Imitation learning has been commonly applied to solve different tasks in isolation. This usually requires either careful feature engineering, or a significant number of samples. This is far from what we desire: ideally, robots should be able to learn from very few demonstrations of any given task, and instantly generalize to new situations of the same task, without requiring task-specific engineering. Read More

2017Mar
Authors: MicroBooNE collaboration, P. Abratenko, R. Acciarri, C. Adams, R. An, J. Asaadi, M. Auger, L. Bagby, S. Balasubramanian, B. Baller, C. Barnes, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, L. Bugel, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. Chen, E. Church, D. Cianci, E. Cohen, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadon, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, B. T. Fleming, W. Foreman, A. P. Furmanski, D. Garcia-Gamez, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, E. -C. Huang, C. James, J. Jan de Vries, C. -M. Jen, L. Jiang, R. A. Johnson, B. J. P. Jones, J. Joshi, H. Jostlein, D. Kaleko, L. N. Kalousis, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A. Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, E. Piasetzky, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, A. Rafique, L. Rochester, C. Rudolf von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, E. L. Snider, M. Soderberg, S. Soldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, M. Toups, Y. -T. Tsai, S. Tufanli, T. Usher, R. G. Van de Water, B. Viren, M. Weber, J. Weston, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, L. Yates, G. P. Zeller, J. Zennamo, C. Zhang

We discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Read More

We explore the use of Evolution Strategies, a class of black box optimization algorithms, as an alternative to popular RL techniques such as Q-learning and Policy Gradients. Experiments on MuJoCo and Atari show that ES is a viable solution strategy that scales extremely well with the number of CPUs available: By using hundreds to thousands of parallel workers, ES can solve 3D humanoid walking in 10 minutes and obtain competitive results on most Atari games after one hour of training time. In addition, we highlight several advantages of ES as a black box optimization technique: it is invariant to action frequency and delayed rewards, tolerant of extremely long horizons, and does not need temporal discounting or value function approximation. Read More

2016Dec
Authors: MicroBooNE Collaboration, R. Acciarri, C. Adams, R. An, A. Aparicio, S. Aponte, J. Asaadi, M. Auger, N. Ayoub, L. Bagby, B. Baller, R. Barger, G. Barr, M. Bass, F. Bay, K. Biery, M. Bishai, A. Blake, V. Bocean, D. Boehnlein, V. D. Bogert, T. Bolton, L. Bugel, C. Callahan, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, S. Chappa, H. Chen, K. Chen, C. Y. Chi, C. S. Chiu, E. Church, D. Cianci, G. H. Collin, J. M. Conrad, M. Convery, J. Cornele, P. Cowan, J. I. Crespo-Anadon, G. Crutcher, C. Darve, R. Davis, M. Del Tutto, D. Devitt, S. Duffin, S. Dytman, B. Eberly, A. Ereditato, D. Erickson, L. Escudero Sanchez, J. Esquivel, S. Farooq, J. Farrell, D. Featherston, B. T. Fleming, W. Foreman, A. P. Furmanski, V. Genty, M. Geynisman, D. Goeldi, B. Goff, S. Gollapinni, N. Graf, E. Gramellini, J. Green, A. Greene, H. Greenlee, T. Griffin, R. Grosso, R. Guenette, A. Hackenburg, R. Haenni, P. Hamilton, P. Healey, O. Hen, E. Henderson, J. Hewes, C. Hill, K. Hill, L. Himes, J. Ho, G. Horton-Smith, D. Huffman, C. M. Ignarra, C. James, E. James, J. Jan de Vries, W. Jaskierny, C. M. Jen, L. Jiang, B. Johnson, M. Johnson, R. A. Johnson, B. J. P. Jones, J. Joshi, H. Jostlein, D. Kaleko, L. N. Kalousis, G. Karagiorgi, T. Katori, P. Kellogg, W. Ketchum, J. Kilmer, B. King, B. Kirby, M. Kirby, E. Klein, T. Kobilarcik, I. Kreslo, R. Krull, R. Kubinski, G. Lange, F. Lanni, A. Lathrop, A. Laube, W. M. Lee, Y. Li, D. Lissauer, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, G. Lukhanin, M. Luethi, B. Lundberg, X. Luo, G. Mahler, I. Majoros, D. Makowiecki, A. Marchionni, C. Mariani, D. Markley, J. Marshall, D. A. Martinez Caicedo, K. T. McDonald, D. McKee, A. McLean, J. Mead, V. Meddage, T. Miceli, G. B. Mills, W. Miner, J. Moon, M. Mooney, C. D. Moore, Z. Moss, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, B. Norris, N. Norton, J. Nowak, M. OBoyle, T. Olszanowski, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, R. Pelkey, M. Phipps, S. Pordes, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, V. Radeka, A. Rafique, R. A Rameika, B. Rebel, R. Rechenmacher, S. Rescia, L. Rochester, C. Rudolf von Rohr, A. Ruga, B. Russell, R. Sanders, W. R. Sands III, M. Sarychev, D. W. Schmitz, A. Schukraft, R. Scott, W. Seligman, M. H. Shaevitz, M. Shoun, J. Sinclair, W. Sippach, T. Smidt, A. Smith, E. L. Snider, M. Soderberg, M. Solano-Gonzalez, S. Soldner-Rembold, S. R. Soleti, J. Sondericker, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, K. Sutton, A. M. Szelc, K. Taheri, N. Tagg, K. Tatum, J. Teng, K. Terao, M. Thomson, C. Thorn, J. Tillman, M. Toups, Y. T. Tsai, S. Tufanli, T. Usher, M. Utes, R. G. Van de Water, C. Vendetta, S. Vergani, E. Voirin, J. Voirin, B. Viren, P. Watkins, M. Weber, T. Wester, J. Weston, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, K. C. Wu, T. Yang, B. Yu, G. P. Zeller, J. Zennamo, C. Zhang, M. Zuckerbrot

This paper describes the design and construction of the MicroBooNE liquid argon time projection chamber and associated systems. MicroBooNE is the first phase of the Short Baseline Neutrino program, located at Fermilab, and will utilize the capabilities of liquid argon detectors to examine a rich assortment of physics topics. In this document details of design specifications, assembly procedures, and acceptance tests are reported. Read More

2016Nov
Authors: MicroBooNE collaboration, R. Acciarri, C. Adams, R. An, J. Asaadi, M. Auger, L. Bagby, B. Baller, G. Barr, M. Bass, F. Bay, M. Bishai, A. Blake, T. Bolton, L. Bugel, L. Camilleri, D. Caratelli, B. Carls, R. Castillo Fernandez, F. Cavanna, H. Chen, E. Church, D. Cianci, G. H. Collin, J. M. Conrad, M. Convery, J. I. Crespo-Anadón, M. Del Tutto, D. Devitt, S. Dytman, B. Eberly, A. Ereditato, L. Escudero Sanchez, J. Esquivel, B. T. Fleming, W. Foreman, A. P. Furmanski, G. T. Garvey, V. Genty, D. Goeldi, S. Gollapinni, N. Graf, E. Gramellini, H. Greenlee, R. Grosso, R. Guenette, A. Hackenburg, P. Hamilton, O. Hen, J. Hewes, C. Hill, J. Ho, G. Horton-Smith, C. James, J. Jan de Vries, C. -M. Jen, L. Jiang, R. A. Johnson, B. J. P. Jones, J. Joshi, H. Jostlein, D. Kaleko, G. Karagiorgi, W. Ketchum, B. Kirby, M. Kirby, T. Kobilarcik, I. Kreslo, A. Laube, Y. Li, A. Lister, B. R. Littlejohn, S. Lockwitz, D. Lorca, W. C. Louis, M. Luethi, B. Lundberg, X. Luo, A. Marchionni, C. Mariani, J. Marshall, D. A. Martinez Caicedo, V. Meddage, T. Miceli, G. B. Mills, J. Moon, M. Mooney, C. D. Moore, J. Mousseau, R. Murrells, D. Naples, P. Nienaber, J. Nowak, O. Palamara, V. Paolone, V. Papavassiliou, S. F. Pate, Z. Pavlovic, D. Porzio, G. Pulliam, X. Qian, J. L. Raaf, A. Rafique, L. Rochester, C. Rudolf von Rohr, B. Russell, D. W. Schmitz, A. Schukraft, W. Seligman, M. H. Shaevitz, J. Sinclair, E. L. Snider, M. Soderberg, S. Söldner-Rembold, S. R. Soleti, P. Spentzouris, J. Spitz, J. St. John, T. Strauss, A. M. Szelc, N. Tagg, K. Terao, M. Thomson, M. Toups, Y. -T. Tsai, S. Tufanli, T. Usher, R. G. Van de Water, B. Viren, M. Weber, J. Weston, D. A. Wickremasinghe, S. Wolbers, T. Wongjirad, K. Woodruff, T. Yang, G. P. Zeller, J. Zennamo, C. Zhang

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. Read More

This article provides the calculation of an effective vertex function between a nucleon and a $Z^\prime$ boson that couples preferentially to either the top quark or the third generation of fermions, for the purpose of calculating vector-portal dark matter nuclear recoil cross sections. Mixing effects between the new gauge group $U(1)^\prime$ and the Standard Model hypercharge group $U(1)_Y$ are taken into account. Contributions to the $U(1)^\prime$ nucleon current from heavy quarks are quantified using the heavy quark expansion. Read More

Within QCD, colourless states may be constructed corresponding to exotic matter outside of the traditional quark model. Experiments have recently observed tetraquark and pentaquark states, but no definitive hybrid meson signals have been observed. With the construction of the PANDA experiment at FAIR, and with full commissioning of the GlueX experiment at JLab expected to be completed this year, the opportunity for the observation of hybrid mesons has greatly increased. Read More

We use QCD Laplace sum-rules to predict masses of open-flavour heavy-light hybrids where one of the hybrid's constituent quarks is a charm or bottom and the other is an up, down, or strange. We compute leading-order, diagonal correlation functions of several hybrid interpolating currents, taking into account QCD condensates up to dimension-six, and extract mass predictions for all $J^P\in\{0^{\pm},\,1^{\pm}\}$. Within theoretical uncertainties, we find degeneracy between the heavy-nonstrange and heavy-strange hybrids in all $J^P$ channels. Read More

The increased availability of electronic health records (EHRs) have spearheaded the initiative for precision medicine using data driven approaches. Essential to this effort is the ability to identify patients with certain medical conditions of interest from simple queries on EHRs, or EHR-based phenotypes. Existing rule--based phenotyping approaches are extremely labor intensive. Read More

The response of lipid bilayers to osmotic stress is an important part of cellular function. Previously, in [Oglecka et al. 2014], we reported that cell-sized giant unilamellar vesicles (GUVs) exposed to hypotonic media, respond to the osmotic assault by undergoing a cyclical sequence of swelling and bursting events, coupled to the membrane's compositional degrees of freedom. Read More

The viability of quantum communication schemes rely on sending quantum states of light over long distances. However, transmission loss can degrade the signal strength, adding noise. Heralded noiseless amplification of a quantum signal can provide a solution by enabling longer direct transmission distances and by enabling entanglement distillation. Read More

In many healthcare settings, intuitive decision rules for risk stratification can help effective hospital resource allocation. This paper introduces a novel variant of decision tree algorithms that produces a chain of decisions, not a general tree. Our algorithm, $\alpha$-Carving Decision Chain (ACDC), sequentially carves out "pure" subsets of the majority class examples. Read More

Consider learning a policy from example expert behavior, without interaction with the expert or access to reinforcement signal. One approach is to recover the expert's cost function with inverse reinforcement learning, then extract a policy from that cost function with reinforcement learning. This approach is indirect and can be slow. Read More

In imitation learning, an agent learns how to behave in an environment with an unknown cost function by mimicking expert demonstrations. Existing imitation learning algorithms typically involve solving a sequence of planning or reinforcement learning problems. Such algorithms are therefore not directly applicable to large, high-dimensional environments, and their performance can significantly degrade if the planning problems are not solved to optimality. Read More

Key to realising quantum computers is minimising the resources required to build logic gates into useful processing circuits. While the salient features of a quantum computer have been shown in proof-of-principle experiments, difficulties in scaling quantum systems have made more complex operations intractable. This is exemplified in the classical Fredkin (controlled-SWAP) gate for which, despite theoretical proposals, no quantum analogue has been realised. Read More

We present a source of polarization entangled photon pairs based on spontaneous parametric downconversion engineered for frequency uncorrelated telecom photon generation. Our source provides photon pairs that display, simultaneously, the key properties for high-performance quantum information and fundamental quantum science tasks. Specifically, the source provides for high heralding efficiency, high quantum state purity and high entangled state fidelity at the same time. Read More

Computer simulation of observable phenomena is an indispensable tool for engineering new technology, understanding the natural world, and studying human society. Yet the most interesting systems are often complex, such that simulating their future behaviour demands storing immense amounts of information regarding how they have behaved in the past. For increasingly complex systems, simulation becomes increasingly difficult and is ultimately constrained by resources such as computer memory. Read More

Electric-magnetic dualities are equivalence between strong and weak coupling constants. A standard example is the exchange of electric and magnetic fields in an abelian gauge theory. We show three methods to perform electric-magnetic dualities in the case of the non-commutative $U(1)$ gauge theory. Read More

The solid immersion lens is a powerful optical tool that allows light entering material from air or vacuum to focus to a spot much smaller than the free-space wavelength. Conventionally, however, they rely on semispherical topographies and are non-planar and bulky, which limits their integration in many applications. Recently, there has been considerable interest in using planar structures, referred to as metasurfaces, to construct flat optical components for manipulating light in unusual ways. Read More

Optical or electrical stimulation of neural circuits in mice during natural behavior is an important paradigm for studying brain function. Conventional systems for optogenetics and electrical microstimulation require tethers or large head-mounted devices that disrupt animal behavior. We report a method for wireless powering of small-scale implanted devices based on the strong localization of energy that occurs during resonant interaction between a radio-frequency cavity and intrinsic modes in mice. Read More

2015Mar
Authors: R. Acciarri1, C. Adams2, R. An3, C. Andreopoulos4, A. M. Ankowski5, M. Antonello6, J. Asaadi7, W. Badgett8, L. Bagby9, B. Baibussinov10, B. Baller11, G. Barr12, N. Barros13, M. Bass14, V. Bellini15, P. Benetti16, S. Bertolucci17, K. Biery18, H. Bilokon19, M. Bishai20, A. Bitadze21, A. Blake22, F. Boffelli23, T. Bolton24, M. Bonesini25, J. Bremer26, S. J. Brice27, C. Bromberg28, L. Bugel29, E. Calligarich30, L. Camilleri31, D. Caratelli32, B. Carls33, F. Cavanna34, S. Centro35, H. Chen36, C. Chi37, E. Church38, D. Cianci39, A. G. Cocco40, G. H. Collin41, J. M. Conrad42, M. Convery43, G. De Geronimo44, A. Dermenev45, R. Dharmapalan46, S. Dixon47, Z. Djurcic48, S. Dytmam49, B. Eberly50, A. Ereditato51, J. Esquivel52, J. Evans53, A. Falcone54, C. Farnese55, A. Fava56, A. Ferrari57, B. T. Fleming58, W. M. Foreman59, J. Freestone60, T. Gamble61, G. Garvey62, V. Genty63, M. Geynisman64, D. Gibin65, S. Gninenko66, D. Göldi67, S. Gollapinni68, N. Golubev69, M. Graham70, E. Gramellini71, H. Greenlee72, R. Grosso73, R. Guenette74, A. Guglielmi75, A. Hackenburg76, R. Hänni77, O. Hen78, J. Hewes79, J. Ho80, G. Horton-Smith81, J. Howell82, A. Ivashkin83, C. James84, C. M. Jen85, R. A. Johnson86, B. J. P. Jones87, J. Joshi88, H. Jostlein89, D. Kaleko90, L. N. Kalousis91, G. Karagiorgi92, W. Ketchum93, B. Kirby94, M. Kirby95, M. Kirsanov96, J. Kisiel97, J. Klein98, J. Klinger99, T. Kobilarcik100, U. Kose101, I. Kreslo102, V. A. Kudryavtsev103, Y. Li104, B. Littlejohn105, D. Lissauer106, P. Livesly107, S. Lockwitz108, W. C. Louis109, M. Lüthi110, B. Lundberg111, F. Mammoliti112, G. Mannocchi113, A. Marchionni114, C. Mariani115, J. Marshall116, K. Mavrokoridis117, N. McCauley118, N. McConkey119, K. McDonald120, V. Meddage121, A. Menegolli122, G. Meng123, I. Mercer124, T. Miao125, T. Miceli126, G. B. Mills127, D. Mladenov128, C. Montanari129, D. Montanari130, J. Moon131, M. Mooney132, C. Moore133, Z. Moss134, M. H. Moulai135, S. Mufson136, R. Murrells137, D. Naples138, M. Nessi139, M. Nicoletto140, P. Nienaber141, B. Norris142, F. Noto143, J. Nowak144, S. Pal145, O. Palamara146, V. Paolone147, V. Papavassiliou148, S. Pate149, J. Pater150, Z. Pavlovic151, J. Perkin152, P. Picchi153, F. Pietropaolo154, P. Płoński155, S. Pordes156, R. Potenza157, G. Pulliam158, X. Qian159, L. Qiuguang160, J. L. Raaf161, V. Radeka162, R. Rameika163, A. Rappoldi164, G. L. Raselli165, P. N. Ratoff166, B. Rebel167, M. Richardson168, L. Rochester169, M. Rossella170, C. Rubbia171, C. Rudolf von Rohr172, B. Russell173, P. Sala174, A. Scaramelli175, D. W. Schmitz176, A. Schukraft177, W. Seligman178, M. H. Shaevitz179, B. Sippach180, E. Snider181, J. Sobczyk182, M. Soderberg183, S. Söldner-Rembold184, M. Spanu185, J. Spitz186, N. Spooner187, D. Stefan188, J. St. John189, T. Strauss190, R. Sulej191, C. M. Sutera192, A. M. Szelc193, N. Tagg194, C. E. Taylor195, K. Terao196, M. Thiesse197, L. Thompson198, M. Thomson199, C. Thorn200, M. Torti201, F. Tortorici202, M. Toups203, C. Touramanis204, Y. Tsai205, T. Usher206, R. Van de Water207, F. Varanini208, S. Ventura209, C. Vignoli210, T. Wachala211, M. Weber212, D. Whittington213, P. Wilson214, S. Wolbers215, T. Wongjirad216, K. Woodruff217, M. Xu218, T. Yang219, B. Yu220, A. Zani221, G. P. Zeller222, J. Zennamo223, C. Zhang224
Affiliations: 1MicroBooNE Collaboration, 2LAr1-ND Collaboration, 3MicroBooNE Collaboration, 4LAr1-ND Collaboration, 5LAr1-ND Collaboration, 6ICARUS-WA104 Collaboration, 7LAr1-ND Collaboration, 8LAr1-ND Collaboration, 9LAr1-ND Collaboration, 10ICARUS-WA104 Collaboration, 11LAr1-ND Collaboration, 12MicroBooNE Collaboration, 13LAr1-ND Collaboration, 14LAr1-ND Collaboration, 15ICARUS-WA104 Collaboration, 16ICARUS-WA104 Collaboration, 17ICARUS-WA104 Collaboration, 18ICARUS-WA104 Collaboration, 19ICARUS-WA104 Collaboration, 20LAr1-ND Collaboration, 21LAr1-ND Collaboration, 22MicroBooNE Collaboration, 23ICARUS-WA104 Collaboration, 24MicroBooNE Collaboration, 25ICARUS-WA104 Collaboration, 26ICARUS-WA104 Collaboration, 27MicroBooNE Collaboration, 28MicroBooNE Collaboration, 29LAr1-ND Collaboration, 30ICARUS-WA104 Collaboration, 31LAr1-ND Collaboration, 32MicroBooNE Collaboration, 33MicroBooNE Collaboration, 34LAr1-ND Collaboration, 35ICARUS-WA104 Collaboration, 36LAr1-ND Collaboration, 37LAr1-ND Collaboration, 38LAr1-ND Collaboration, 39LAr1-ND Collaboration, 40ICARUS-WA104 Collaboration, 41LAr1-ND Collaboration, 42LAr1-ND Collaboration, 43MicroBooNE Collaboration, 44LAr1-ND Collaboration, 45ICARUS-WA104 Collaboration, 46LAr1-ND Collaboration, 47LAr1-ND Collaboration, 48LAr1-ND Collaboration, 49MicroBooNE Collaboration, 50MicroBooNE Collaboration, 51LAr1-ND Collaboration, 52LAr1-ND Collaboration, 53LAr1-ND Collaboration, 54ICARUS-WA104 Collaboration, 55ICARUS-WA104 Collaboration, 56ICARUS-WA104 Collaboration, 57ICARUS-WA104 Collaboration, 58LAr1-ND Collaboration, 59LAr1-ND Collaboration, 60LAr1-ND Collaboration, 61LAr1-ND Collaboration, 62LAr1-ND Collaboration, 63LAr1-ND Collaboration, 64ICARUS-WA104 Collaboration, 65ICARUS-WA104 Collaboration, 66ICARUS-WA104 Collaboration, 67LAr1-ND Collaboration, 68MicroBooNE Collaboration, 69ICARUS-WA104 Collaboration, 70MicroBooNE Collaboration, 71LAr1-ND Collaboration, 72LAr1-ND Collaboration, 73MicroBooNE Collaboration, 74LAr1-ND Collaboration, 75ICARUS-WA104 Collaboration, 76LAr1-ND Collaboration, 77LAr1-ND Collaboration, 78MicroBooNE Collaboration, 79MicroBooNE Collaboration, 80LAr1-ND Collaboration, 81MicroBooNE Collaboration, 82LAr1-ND Collaboration, 83ICARUS-WA104 Collaboration, 84LAr1-ND Collaboration, 85LAr1-ND Collaboration, 86MicroBooNE Collaboration, 87LAr1-ND Collaboration, 88MicroBooNE Collaboration, 89MicroBooNE Collaboration, 90MicroBooNE Collaboration, 91LAr1-ND Collaboration, 92LAr1-ND Collaboration, 93LAr1-ND Collaboration, 94MicroBooNE Collaboration, 95MicroBooNE Collaboration, 96ICARUS-WA104 Collaboration, 97ICARUS-WA104 Collaboration, 98LAr1-ND Collaboration, 99LAr1-ND Collaboration, 100MicroBooNE Collaboration, 101ICARUS-WA104 Collaboration, 102LAr1-ND Collaboration, 103LAr1-ND Collaboration, 104MicroBooNE Collaboration, 105MicroBooNE Collaboration, 106LAr1-ND Collaboration, 107LAr1-ND Collaboration, 108MicroBooNE Collaboration, 109LAr1-ND Collaboration, 110LAr1-ND Collaboration, 111MicroBooNE Collaboration, 112ICARUS-WA104 Collaboration, 113ICARUS-WA104 Collaboration, 114MicroBooNE Collaboration, 115LAr1-ND Collaboration, 116MicroBooNE Collaboration, 117LAr1-ND Collaboration, 118LAr1-ND Collaboration, 119LAr1-ND Collaboration, 120MicroBooNE Collaboration, 121MicroBooNE Collaboration, 122ICARUS-WA104 Collaboration, 123ICARUS-WA104 Collaboration, 124LAr1-ND Collaboration, 125LAr1-ND Collaboration, 126MicroBooNE Collaboration, 127LAr1-ND Collaboration, 128ICARUS-WA104 Collaboration, 129ICARUS-WA104 Collaboration, 130LAr1-ND Collaboration, 131LAr1-ND Collaboration, 132MicroBooNE Collaboration, 133LAr1-ND Collaboration, 134LAr1-ND Collaboration, 135MicroBooNE Collaboration, 136LAr1-ND Collaboration, 137MicroBooNE Collaboration, 138MicroBooNE Collaboration, 139ICARUS-WA104 Collaboration, 140ICARUS-WA104 Collaboration, 141MicroBooNE Collaboration, 142LAr1-ND Collaboration, 143ICARUS-WA104 Collaboration, 144LAr1-ND Collaboration, 145LAr1-ND Collaboration, 146LAr1-ND Collaboration, 147MicroBooNE Collaboration, 148MicroBooNE Collaboration, 149MicroBooNE Collaboration, 150LAr1-ND Collaboration, 151LAr1-ND Collaboration, 152LAr1-ND Collaboration, 153ICARUS-WA104 Collaboration, 154ICARUS-WA104 Collaboration, 155ICARUS-WA104 Collaboration, 156MicroBooNE Collaboration, 157MicroBooNE Collaboration, 158LAr1-ND Collaboration, 159LAr1-ND Collaboration, 160LAr1-ND Collaboration, 161MicroBooNE Collaboration, 162LAr1-ND Collaboration, 163LAr1-ND Collaboration, 164ICARUS-WA104 Collaboration, 165ICARUS-WA104 Collaboration, 166LAr1-ND Collaboration, 167MicroBooNE Collaboration, 168LAr1-ND Collaboration, 169MicroBooNE Collaboration, 170ICARUS-WA104 Collaboration, 171ICARUS-WA104 Collaboration, 172LAr1-ND Collaboration, 173LAr1-ND Collaboration, 174ICARUS-WA104 Collaboration, 175ICARUS-WA104 Collaboration, 176LAr1-ND Collaboration, 177MicroBooNE Collaboration, 178MicroBooNE Collaboration, 179LAr1-ND Collaboration, 180LAr1-ND Collaboration, 181ICARUS-WA104 Collaboration, 182ICARUS-WA104 Collaboration, 183LAr1-ND Collaboration, 184LAr1-ND Collaboration, 185ICARUS-WA104 Collaboration, 186LAr1-ND Collaboration, 187LAr1-ND Collaboration, 188ICARUS-WA104 Collaboration, 189MicroBooNE Collaboration, 190LAr1-ND Collaboration, 191ICARUS-WA104 Collaboration, 192ICARUS-WA104 Collaboration, 193LAr1-ND Collaboration, 194MicroBooNE Collaboration, 195LAr1-ND Collaboration, 196LAr1-ND Collaboration, 197LAr1-ND Collaboration, 198LAr1-ND Collaboration, 199LAr1-ND Collaboration, 200LAr1-ND Collaboration, 201ICARUS-WA104 Collaboration, 202ICARUS-WA104 Collaboration, 203LAr1-ND Collaboration, 204LAr1-ND Collaboration, 205MicroBooNE Collaboration, 206MicroBooNE Collaboration, 207LAr1-ND Collaboration, 208ICARUS-WA104 Collaboration, 209ICARUS-WA104 Collaboration, 210ICARUS-WA104 Collaboration, 211ICARUS-WA104 Collaboration, 212LAr1-ND Collaboration, 213LAr1-ND Collaboration, 214MicroBooNE Collaboration, 215MicroBooNE Collaboration, 216LAr1-ND Collaboration, 217MicroBooNE Collaboration, 218MicroBooNE Collaboration, 219MicroBooNE Collaboration, 220LAr1-ND Collaboration, 221ICARUS-WA104 Collaboration, 222LAr1-ND Collaboration, 223LAr1-ND Collaboration, 224MicroBooNE Collaboration

A Short-Baseline Neutrino (SBN) physics program of three LAr-TPC detectors located along the Booster Neutrino Beam (BNB) at Fermilab is presented. This new SBN Program will deliver a rich and compelling physics opportunity, including the ability to resolve a class of experimental anomalies in neutrino physics and to perform the most sensitive search to date for sterile neutrinos at the eV mass-scale through both appearance and disappearance oscillation channels. Using data sets of 6. Read More

We study a tandem of agents who make decisions about an underlying binary hypothesis, where the distribution of the agent observations under each hypothesis comes from an uncertainty class. We investigate both decentralized detection rules, where agents collaborate to minimize the error probability of the final agent, and social learning rules, where each agent minimizes its own local minimax error probability. We then extend our results to the infinite tandem network, and derive necessary and sufficient conditions on the uncertainty classes for the minimax error probability to converge to zero when agents know their positions in the tandem. Read More

Many charmonium-like and bottomonium-like $XYZ$ resonances have been observed by the Belle, Babar, CLEO and BESIII collaborations in the past decade. They are difficult to fit in the conventional quark model and thus are considered as candidates of exotic hadrons, such as multi-quark states, meson molecules, and hybrids. In this talk, we first briefly introduce the method of QCD sum rules and then provide a short review of the mass spectra of the quarkonium-like tetraquark states and the heavy quarkonium hybrids in the QCD sum rules approach. Read More

QCD Laplace sum rules are used to calculate heavy quarkonium (charmonium and bottomonium) hybrid masses in several distinct $J^{PC}$ channels. Previous studies of heavy quarkonium hybrids did not include the effects of dimension-six condensates, leading to unstable sum rules and unreliable mass predictions in some channels. We have updated these sum rules to include dimension-six condensates, providing new mass predictions for the spectra of heavy quarkonium hybrids. Read More

We study the generalized Dirac-Born-Infeld (DBI) action, which describes a $q$-brane ending on a $p$-brane with a ($q$+1)-form background. This action has the equivalent descriptions in commutative and non-commutative settings, which can be shown from the generalized metric and Nambu-Sigma model. We mainly discuss the dimensional reduction of the generalized DBI at the massless level on the flat spacetime and constant antisymmetric background in the case of flat spacetime, constant antisymmetric background and the gauge potential vanishes for all time-like components. Read More

Liquid Argon Time Projection Chambers (LArTPCs) are ideal detectors for precision neutrino physics. These detectors, when located deep underground, can also be used for measurements of proton decay, and astrophysical neutrinos. The technology must be completely developed, up to very large mass scales, and fully mastered to construct and operate these detectors for this physics program. Read More

We explicitly apply localization results to study the interpolation between three and two dimensional mirror symmetry for Abelian gauge theories with four supercharges. We first use the ellipsoid S_b^3 partition functions to verify the mirror symmetry between a pair of general three dimensional N=2 Abelian Chern-Simons quiver gauge theories. These expressions readily factorize into holomorphic blocks and their anti-holomorphic copies, so we can also obtain the partition functions on S^1 x S^2 via fusion procedure. Read More

We have studied the charmonium and bottomonium hybrid states with various $J^{PC}$ quantum numbers in QCD sum rules. At leading order in $\alpha_s$, the two-point correlation functions have been calculated up to dimension six including the tri-gluon condensate and four-quark condensate. After performing the QCD sum rule analysis, we have confirmed that the dimension six condensates can stabilize the hybrid sum rules and allow the reliable mass predictions. Read More

We have extended the calculation of the correlation functions of heavy quarkonium hybrid operators with various $J^{PC}$ quantum numbers to include QCD condensates up to dimension six. In contrast to previous analyses which were unable to optimize the QCD sum-rules for certain $J^{PC}$, recent work has shown that inclusion of dimension six condensates stabilizes the hybrid sum-rules and permits reliable mass predictions. In this work we have investigated the effects of the dimension six condensates on the remaining channels. Read More

Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. The progression and severity of MS varies by individual, but it is generally a disabling disease. Although medications have been developed to slow the disease progression and help manage symptoms, MS research has yet to result in a cure. Read More

This paper introduces an elemental building block which combines Dictionary Learning and Dimension Reduction (DRDL). We show how this foundational element can be used to iteratively construct a Hierarchical Sparse Representation (HSR) of a sensory stream. We compare our approach to existing models showing the generality of our simple prescription. Read More

We report the formation of sub-5 nm ultrashallow junctions in 4 inch Si wafers enabled by the molecular monolayer doping of phosphorous and boron atoms and the use of conventional spike annealing. The junctions are characterized by secondary ion mass spectrometry and non-contact sheet resistance measurements. It is found that the majority (~70%) of the incorporated dopants are electrically active, therefore, enabling a low sheet resistance for a given dopant areal dose. Read More

Temperature-dependent I-V and C-V spectroscopy of single InAs nanowire field-effect transistors were utilized to directly shed light on the intrinsic electron transport properties as a function of nanowire radius. From C-V characterizations, the densities of thermally-activated fixed charges and trap states on the surface of untreated (i.e. Read More

The $\pi$-electronic structure of graphene in the presence of a modulated electric potential is investigated by the tight-binding model. The low-energy electronic properties are strongly affected by the period and field strength. Such a field could modify the energy dispersions, destroy state degeneracy, and induce band-edge states. Read More

InAs nanowires have been actively explored as the channel material for high performance transistors owing to their high electron mobility and ease of ohmic metal contact formation. The catalytic growth of non-epitaxial InAs nanowires, however, has often relied on the use of Au colloids which is non-CMOS compatible. Here, we demonstrate the successful synthesis of high yield of crystalline InAs nanowires with high yield and tunable diameters by using Ni nanoparticles as the catalyst material on amorphous SiO2 substrates. Read More

Controlled and uniform assembly of "bottom-up" nanowire (NW) materials with high scalability has been one of the significant bottleneck challenges facing the potential integration of nanowires for both nano and macro electronic circuit applications. Many efforts have focused on tackling this challenge, and while significant progress has been made, still most presented approaches lack either the desired controllability in the positioning of nanowires or the needed uniformity over large scales. Here, we demonstrate wafer-scale assembly of highly ordered, dense, and regular arrays of NWs with high uniformity and reproducibility through a simple contact printing process. Read More

A monolayer graphene exists in an environment where a uniform magnetic field interacts a spatially modulated magnetic field. The spatially modulated magnetic field could affect Landau levels due to a uniform magnetic field. The modulation effects on Landau levels are investigated through the Peierl's tight-binding model. Read More

The Peierl's tight-binding model, with the band Hamiltonian matrix, is used to calculate the magnetoelectronic structure of a monolayergraphite. There are many flat Landau levels and some oscillatory Landau levels. The low Landau-level energies are characterized by a simple relation, not for others. Read More

Similar to the optimal-doped, weak-ferromagnetic (WFM induced by canted antiferromagnetism, T$_{Curie}$ = 131 K) and superconducting (T$_{c}$ = 56 K) RuSr$_{2}$GdCu$_{2}$O$_{8}$, the underdoped RuSr$_{2}$EuCu$_{2}$O$_{8}$ (T$_{Curie}$ = 133 K, T$_{c}$ = 36 K) also exhibited a spontaneous vortex state (SVS) between 16 K and 36 K. The low field ($\pm$20 G) superconducting hysteresis loop indicates a weak and narrow Meissner state region of average lower critical field B$_{c1}^{ave}$(T) = B$_{c1}^{ave}$(0)[1 - (T/T$_{SVS}$)$^{2}$], with B$_{c1}^{ave}$(0) = 7 G and T$_{SVS}$ = 16 K. The vortex melting transition (T$_{melting}$ = 21 K) below T$_{c}$ obtained from the broad resistivity drop and the onset of diamagnetic signal indicates a vortex liquid region due to the coexistence and interplay between superconductivity and WFM order. Read More

2004May
Affiliations: 1U. Victoria, 2U. Victoria, 3Kunsan Nat'l Univ., 4Kunsan Nat'l Univ.
Category: Physics - Other

Using the invariant operator method for an effective Hamiltonian including the radiation-spin interaction, we describe the quantum theory for magnetization dynamics when the spin system evolves nonadiabatically and out of equilibrium, $d \hat{\rho}/dt \neq 0$. It is shown that the vector parameter of the invariant operator and the magnetization defined with respect to the density operator, both satisfying the quantum Liouville equation, still obey the Landau-Lifshitz-Gilbert equation. Read More

The Klein-Gordon-Einstein equations of classical real scalar fields have time-dependent solutions (periodic in time). We show that quantum real scalar fields can form non-oscillating (static) solitonic objects, which are quite similar to the solutions describing boson stars formed with classical and quantum complex scalar fields (the latter will be studied in this paper). We numerically analyze the difference between them concerning the mass of boson stars. Read More

Brief comments on a plausible holographic relationship between the opposite rotational dragging effect of a (2+1)-dimensional rotating de Sitter space and the non-unitarity of a boundary conformal field theory are given. In addition to the comments, we study how the opposite rotational dragging effect affects the statistical-mechanical quantities in the rotating de Sitter space in comparison with a BTZ black hole. Read More

We investigate the generalized second law for two-dimensional black holes in equilibrium (Hartle-Hawking) and nonequilibrium (Unruh) with the heat bath surrounding the black holes. We obtain a simple expression for the change of total entropy in terms of covariant thermodynamic variables, which is valid not only for the Hartle-Hawking state but also for the Unruh state up to leading order, without assuming a quasi-stationary evolution of the black holes. Using this expression, it is shown that the rate of local entropy production is non-negative in the two-dimensional black hole systems. Read More

We show that in general holographic stress tensor may contain a new term of divergence of a spacelike unit normal acceleration. Then, it is shown that in contrast to previous descriptions, a new stress tensor for Kerr-AdS solutions can be a traceless one. Interestingly, this prescription entails a local failure on the IR-UV connection. Read More

In a recent letter, Carlip proposed a generalization of the Brown-Henneaux-Strominger construction to any dimension. We present two criticisms about his formulation. Read More

Counterterm actions are constructed along the ADM formalism. It is shown that the counterterm action can be intrinsically written in terms of intrinsic boundary geometry. Using the expression of counterterm action, we obtain a general form of the counterterm action available for any $d$-dimensional spherical boundary. Read More