Mr. Alejandro Saez Profile

Alejandro Saez

Electronic Engineer at ALMA

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Publications (12)

Proceedings Article | 29 August 2022 Paper

Assembling and integration of the ALMA hardware in the loop simulation environment

Tzu-Chiang Shen, Alejandro Saez, Rodrigo Cabezas, Mark Gallilee, José L. Ortíz, Carlos Boza, Yoshiharu Asaki, Claudio Follert, Martin Tourneboeuf, Soledad Fuica, Johnny Reveco, Ruben Soto, Jorge Ibsen, Norikazu Mizuno, Stuartt Corder

Proceedings Volume 12189, 121891C (2022) https://doi.org/10.1117/12.2629194

KEYWORDS: Antennas, Telescopes, Signal processing, Control systems, Data modeling, Observatories

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Proceedings Article | 9 July 2018 Presentation + Paper

Evaluation of controllers for tuning digitizers in the ALMA interferometer

Daniel Herrera, Alejandro Saez

Proceedings Volume 10708, 107080Y (2018) https://doi.org/10.1117/12.2312958

KEYWORDS: Control systems, Error analysis, Fuzzy logic, Clocks, Interferometers, Antennas, Logic, Signal processing

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Proceedings Article | 6 July 2018 Presentation + Paper

Introducing hardware in the loop and model based simulation concepts in the ALMA observatory for software testing

Tzu-Chiang Shen, Ruben Soto, Alejandro Saez, Jorge Avarias, Norman Saez, Tomas Staig, Jorge Sepulveda, Jorge Castillo, Rodrigo Amestica, Jorge Ibsen, Stuartt Corder

Proceedings Volume 10707, 107070C (2018) https://doi.org/10.1117/12.2313688

KEYWORDS: Antennas, Optical correlators, Observatories, Computing systems, Signal processing, Hardware testing, Current controlled current source, Adaptive optics, Electronics, Control systems

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Proceedings Article | 26 July 2016 Paper

Implementing the concurrent operation of sub-arrays in the ALMA correlator

Rodrigo Amestica, Jesus Perez, Richard Lacasse, Alejandro Saez

Proceedings Volume 9913, 99133K (2016) https://doi.org/10.1117/12.2231245

KEYWORDS: Information technology, Optical correlators, Signal processing, Antennas, Visibility, Interfaces, Current controlled current source, Calibration, Data processing, Observatories

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The ALMA correlator processes the digitized signals from 64 individual antennas to produce a grand total of 2016 correlated base-lines, with runtime selectable lags resolution and integration time. The on-line software system can process a maximum of 125M visibilities per second, producing an archiving data rate close to one sixteenth of the former (7.8M visibilities per second with a network transfer limit of 60 MB/sec). Mechanisms in the correlator hardware design make it possible to split the total number of antennas in the array into smaller subsets, or sub-arrays, such that they can share correlator resources while executing independent observations. The software part of the sub-system is responsible for configuring and scheduling correlator resources in such a way that observations among independent subarrays occur simultaneously while internally sharing correlator resources under a cooperative arrangement. Configuration of correlator modes through its CAN-bus interface and periodic geometric delay updates are the most relevant activities to schedule concurrently while observations happen at the same time among a number of sub-arrays. For that to work correctly, the software interface to sub-arrays schedules shared correlator resources sequentially before observations actually start on each sub-array. Start times for specific observations are optimized and reported back to the higher level observing software. After that initial sequential phase has taken place then simultaneous executions and recording of correlated data across different sub-arrays move forward concurrently, sharing the local network to broadcast results to other software sub-systems. The present paper presents an overview of the different hardware and software actors within the correlator sub-system that implement some degree of concurrency and synchronization needed for seamless and simultaneous operation of multiple sub-arrays, limitations stemming from the resource-sharing nature of the correlator, limitations intrinsic to the digital technology available in the correlator hardware, and milestones so far reached by this new ALMA feature.

Proceedings Article | 26 July 2016 Paper

The evolution of the simulation environment in the ALMA Observatory

Tzu-Chiang Shen, Ruben Soto, Norman Saez, Gaston Velez, Tomas Staig, Jorge Sepulveda, Alejandro Saez, Nicolas Ovando, Jorge Ibsen

Proceedings Volume 9913, 99130D (2016) https://doi.org/10.1117/12.2232366

KEYWORDS: Observatories, Antennas, Software development, Hardware testing, Control systems, Optical correlators, Computer simulations, Current controlled current source, Solar thermal energy, Electronics

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Proceedings Article | 26 July 2016 Paper

Porting the ALMA Correlator Data Processor from hard real-time to plain Linux

Rodrigo Amestica, Jesus Perez, Alejandro Saez

Proceedings Volume 9913, 99133J (2016) https://doi.org/10.1117/12.2230960

KEYWORDS: Optical correlators, Signal processing, Digital signal processing, Data processing, Visibility, Antennas, Computing systems, Operating systems, Current controlled current source, Observatories

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The ALMA correlator back-end consists of a cluster of 16 computing nodes and a master collector/packager node. The mission of the cluster is to process time domain lags into auto-correlations and complex visibilities, integrate them for some configurable amount of time and package them into a workable data product. Computers in the cluster are organized such that individual workloads per node are kept within achievable levels for different observing modes and antennas in the array. Over the course of an observation the master node transmits enough state information to each involved computing node to specify exactly how to process each set of lags received from the correlator. For that distributed mechanism to work, it is necessary to unequivocally identify each individual lag set arriving at each computing node. The original approach was based on a custom hardware interface to each node in the cluster plus a realtime version of the Linux Operating System. A modification recently introduced in the ALMA correlator consists of tagging each lag set with a time stamp before delivering them to the cluster. The time stamp identifies a precise 16- millisecond window during which that specific data set was streamed to the computing cluster. From the time stamp value a node is able to identify a centroid (in absolute time units), base-lines, and correlator mode during that hardware integration. That is, enough information to let the digital signal processing pipeline in each node to process time domain lags into frequency domain auto-correlations per antenna and visibilities per base-line. The scheme also means that a good degree of concurrency can be achieved in each node by having individual CPU cores process individual lag sets at the same time, thus rendering enough processing power to cope with a maximum 1 GiB/sec output from the correlator. The present paper describes how we time stamp lag sets within the correlator hardware, the implications to their on-line processing in software and the benefits that this extension has brought in terms of software maintainability and overall system simplifications.

Proceedings Article | 19 July 2016 Paper

Low-cost Ku band interferometer for educational purposes

Daniel Herrera, Alejandro Saez, Louise Dauvin

Proceedings Volume 9914, 99143I (2016) https://doi.org/10.1117/12.2232138

KEYWORDS: Interferometers, Signal processing, Ku band, Receptors, Sun, Receivers, Ku band, Oscillators, Bandpass filters, Antennas, Crystals

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Proceedings Article | 19 July 2016 Paper

Detecting anomalies in astronomical signals using machine learning algorithms embedded in an FPGA

Alejandro Saez, Daniel Herrera

Proceedings Volume 9914, 99143B (2016) https://doi.org/10.1117/12.2231491

KEYWORDS: Signal detection, Antennas, Machine learning, Optical correlators, Field programmable gate arrays, Field programmable gate arrays, Neurons, Neural networks, Pathology, Polarization, Reflection

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Proceedings Article | 23 July 2014 Paper

Measuring the first two statistics moments using the Correlator resources

A. Saez, D. Herrera, Jorge Sepulveda

Proceedings Volume 9153, 91532K (2014) https://doi.org/10.1117/12.2056392

KEYWORDS: Optical correlators, Antennas, Error analysis, Quantization, Signal attenuation, Field programmable gate arrays, Correlation function, Telescopes, Logic, Statistical analysis

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Proceedings Article | 23 July 2014 Paper

Detecting loss of coherence based on telescope calibration results in ALMA

A. Saez, A. Tejada, D. Herrera, Jorge Sepulveda

Proceedings Volume 9153, 91532I (2014) https://doi.org/10.1117/12.2056298

KEYWORDS: Calibration, Antennas, Telescopes, X band, Signal attenuation, Polarization, Error analysis, Signal detection, Signal processing, Fused deposition modeling

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Proceedings Article | 5 October 2012 Paper

Development of the test interferometer for ALMA

R. Olguin, T. Shen, R. Brito, A. Saez, R. Soto, S. Asayama, C. Follert, L. Knee, A. Quintana, D. Rabanus, E. Reynolds, N. Saez, J. Sepulveda

Proceedings Volume 8452, 84522A (2012) https://doi.org/10.1117/12.925244

KEYWORDS: Optical correlators, Antennas, Adaptive optics, Interferometers, Oscillators, Solar thermal energy, Interferometry, Computing systems, Control systems, Observatories

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Proceedings Article | 24 September 2012 Paper

Performance highlights of the ALMA correlators

Alain Baudry, Richard Lacasse, Ray Escoffier, John Webber, Joseph Greenberg, Laurence Platt, Robert Treacy, Alejandro Saez, Philippe Cais, Giovanni Comoretto, Benjamin Quertier, Sachiko Okumura, Takeshi Kamazaki, Yoshihiro Chikada, Manabu Watanabe, Takeshi Okuda, Yasutake Kurono, Satoru Iguchi

Proceedings Volume 8452, 845217 (2012) https://doi.org/10.1117/12.925700

KEYWORDS: Optical correlators, Antennas, Field programmable gate arrays, Spectral resolution, Fused deposition modeling, Astronomy, Time division multiplexing, Adaptive optics, Receivers, Polarization

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Showing 5 of 12 publications

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