Zobrazeno 1 - 10
of 92
pro vyhledávání: '"DI GUGLIELMO, Giuseppe"'
Autor:
Bhat, Madhav Narayan, Russo, Marco, Carloni, Luca P., Di Guglielmo, Giuseppe, Fahim, Farah, Li, Andy C. Y., Perdue, Gabriel N.
Here we present a technique for using machine learning (ML) for single-qubit gate synthesis on field programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first bootstrap
Externí odkaz:
http://arxiv.org/abs/2411.13037
Autor:
Badea, Anthony, Bean, Alice, Berry, Doug, Dickinson, Jennet, DiPetrillo, Karri, Fahim, Farah, Gray, Lindsey, Di Guglielmo, Giuseppe, Jiang, David, Kovach-Fuentes, Rachel, Maksimovic, Petar, Mills, Corrinne, Neubauer, Mark S., Parpillon, Benjamin, Shekar, Danush, Swartz, Morris, Syal, Chinar, Tran, Nhan, Yoo, Jieun
Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly granular silicon pixel detectors with billions of readout channels. Wit
Externí odkaz:
http://arxiv.org/abs/2410.02945
Autor:
Parpillon, Benjamin, Syal, Chinar, Yoo, Jieun, Dickinson, Jennet, Swartz, Morris, Di Guglielmo, Giuseppe, Bean, Alice, Berry, Douglas, Valentin, Manuel Blanco, DiPetrillo, Karri, Badea, Anthony, Gray, Lindsey, Maksimovic, Petar, Mills, Corrinne, Neubauer, Mark S., Pradhan, Gauri, Tran, Nhan, Wen, Dahai, Fahim, Farah
We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-prin
Externí odkaz:
http://arxiv.org/abs/2406.14860
Autor:
Dickinson, Jennet, Kovach-Fuentes, Rachel, Gray, Lindsey, Swartz, Morris, Di Guglielmo, Giuseppe, Bean, Alice, Berry, Doug, Valentin, Manuel Blanco, DiPetrillo, Karri, Fahim, Farah, Hirschauer, James, Kulkarni, Shruti R., Lipton, Ron, Maksimovic, Petar, Mills, Corrinne, Neubauer, Mark S., Parpillon, Benjamin, Pradhan, Gauri, Syal, Chinar, Tran, Nhan, Wen, Dahai, Yoo, Jieun, Young, Aaron
The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine
Externí odkaz:
http://arxiv.org/abs/2312.11676
Autor:
Wei, Yumou, Forelli, Ryan F., Hansen, Chris, Levesque, Jeffrey P., Tran, Nhan, Agar, Joshua C., Di Guglielmo, Giuseppe, Mauel, Michael E., Navratil, Gerald A.
Publikováno v:
Rev. Sci. Instrum. 95, 073509 (2024)
Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these application
Externí odkaz:
http://arxiv.org/abs/2312.00128
Autor:
Yoo, Jieun, Dickinson, Jennet, Swartz, Morris, Di Guglielmo, Giuseppe, Bean, Alice, Berry, Douglas, Valentin, Manuel Blanco, DiPetrillo, Karri, Fahim, Farah, Gray, Lindsey, Hirschauer, James, Kulkarni, Shruti R., Lipton, Ron, Maksimovic, Petar, Mills, Corrinne, Neubauer, Mark S., Parpillon, Benjamin, Pradhan, Gauri, Syal, Chinar, Tran, Nhan, Wen, Dahai, Young, Aaron
Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the Hi
Externí odkaz:
http://arxiv.org/abs/2310.02474
Autor:
Xu, David, Özgüler, A. Barış, Di Guglielmo, Giuseppe, Tran, Nhan, Perdue, Gabriel N., Carloni, Luca, Fahim, Farah
Publikováno v:
2022 IEEE/ACM Third International Workshop on Quantum Computing Software (QCS), Dallas, TX, USA, 2022, pp. 43-49
Efficient quantum control is necessary for practical quantum computing implementations with current technologies. Conventional algorithms for determining optimal control parameters are computationally expensive, largely excluding them from use outsid
Externí odkaz:
http://arxiv.org/abs/2208.02645
Autor:
Borras, Hendrik, Di Guglielmo, Giuseppe, Duarte, Javier, Ghielmetti, Nicolò, Hawks, Ben, Hauck, Scott, Hsu, Shih-Chieh, Kastner, Ryan, Liang, Jason, Meza, Andres, Muhizi, Jules, Nguyen, Tai, Roy, Rushil, Tran, Nhan, Umuroglu, Yaman, Weng, Olivia, Yokuda, Aidan, Blott, Michaela
We present our development experience and recent results for the MLPerf Tiny Inference Benchmark on field-programmable gate array (FPGA) platforms. We use the open-source hls4ml and FINN workflows, which aim to democratize AI-hardware codesign of opt
Externí odkaz:
http://arxiv.org/abs/2206.11791
We present a custom implementation of a 2D Convolutional Neural Network (CNN) as a viable application for real-time data selection in high-resolution and high-rate particle imaging detectors, making use of hardware acceleration in high-end Field Prog
Externí odkaz:
http://arxiv.org/abs/2201.05638
Publikováno v:
Published in 2019 New York Scientific Data Summit (NYSDS); Publisher: IEEE; Date Added to IEEE Xplore: 25 November 2019
This paper presents the custom implementation, optimization, and performance evaluation of convolutional neural networks on field programmable gate arrays, for the purposes of accelerating deep neural network inference on large, two-dimensional image
Externí odkaz:
http://arxiv.org/abs/2201.04740