Showing 1–16 of 16 results for author: Wunsch, S

Software Training in HEP

Authors: Sudhir Malik, Samuel Meehan, Kilian Lieret, Meirin Oan Evans, Michel H. Villanueva, Daniel S. Katz, Graeme A. Stewart, Peter Elmer, Sizar Aziz, Matthew Bellis, Riccardo Maria Bianchi, Gianluca Bianco, Johan Sebastian Bonilla, Angela Burger, Jackson Burzynski, David Chamont, Matthew Feickert, Philipp Gadow, Bernhard Manfred Gruber, Daniel Guest, Stephan Hageboeck, Lukas Heinrich, Maximilian M. Horzela, Marc Huwiler, Clemens Lange , et al. (22 additional authors not shown)

Abstract: Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade. Meeting this sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required softw… ▽ More Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade. Meeting this sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g. Unix, version control,C++, continuous integration). The second is knowledge of domain specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving more specialized techniques. These include parallel programming, machine learning and data science tools, and techniques to preserve software projects at all scales. This paper dis-cusses the collective software training program in HEP and its activities led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients from which solutions to the computing challenges of HEP can be formed. Beyond serving the community by ensuring that members are able to pursue research goals, this program serves individuals by providing intellectual capital and transferable skills that are becoming increasingly important to careers in the realm of software and computing, whether inside or outside HEP △ Less

Submitted 6 August, 2021; v1 submitted 28 February, 2021; originally announced March 2021.

Comments: For CHEP 2021 conference,sent for publication to CSBS Springer

MSC Class: HEP; software; training

Software Challenges For HL-LHC Data Analysis

Authors: ROOT Team, Kim Albertsson Brann, Guilherme Amadio, Sitong An, Bertrand Bellenot, Jakob Blomer, Philippe Canal, Olivier Couet, Massimiliano Galli, Enrico Guiraud, Stephan Hageboeck, Sergey Linev, Pere Mato Vila, Lorenzo Moneta, Axel Naumann, Alja Mrak Tadel, Vincenzo Eduardo Padulano, Fons Rademakers, Oksana Shadura, Matevz Tadel, Enric Tejedor Saavedra, Xavier Valls Pla, Vassil Vassilev, Stefan Wunsch

Abstract: The high energy physics community is discussing where investment is needed to prepare software for the HL-LHC and its unprecedented challenges. The ROOT project is one of the central software players in high energy physics since decades. From its experience and expectations, the ROOT team has distilled a comprehensive set of areas that should see research and development in the context of data ana… ▽ More The high energy physics community is discussing where investment is needed to prepare software for the HL-LHC and its unprecedented challenges. The ROOT project is one of the central software players in high energy physics since decades. From its experience and expectations, the ROOT team has distilled a comprehensive set of areas that should see research and development in the context of data analysis software, for making best use of HL-LHC's physics potential. This work shows what these areas could be, why the ROOT team believes investing in them is needed, which gains are expected, and where related work is ongoing. It can serve as an indication for future research proposals and cooperations. △ Less

Submitted 4 May, 2020; v1 submitted 16 April, 2020; originally announced April 2020.

Synchronous single-photon detection with self-resetting GHz-gated superconducting NbN nanowires

Authors: Emanuel Knehr, Artem Kuzmin, Steffen Doerner, Stefan Wuensch, Konstantin Ilin, Heidemarie Schmidt, Michael Siegel

Abstract: We demonstrate a GHz-gated operation of resonator-coupled superconducting nanowire single-photon detectors suitable for synchronous applications. In comparison with conventional dc-biased nanowire detectors, this method prevents the detector from latching and can suppress dark counts and background noise. Using a gating frequency of 3.8 GHz and a fast, synchronized laser diode, we show that the de… ▽ More We demonstrate a GHz-gated operation of resonator-coupled superconducting nanowire single-photon detectors suitable for synchronous applications. In comparison with conventional dc-biased nanowire detectors, this method prevents the detector from latching and can suppress dark counts and background noise. Using a gating frequency of 3.8 GHz and a fast, synchronized laser diode, we show that the detector's operation point follows the oscillating current and its detection efficiency depends on the relative frequency and phase of the bias and modulated optical signal. The obtained experimental results are in good agreement with simulations, showing that the duty cycle of a gated detector can be adjusted in a wide range in case of a pronounced saturation of the current-dependent detection efficiency. This operation mode could be suitable for applications such as quantum key distribution and time-of-flight laser ranging. △ Less

Submitted 16 September, 2020; v1 submitted 30 March, 2020; originally announced March 2020.

Comments: 5 pages, 4 figures

Journal ref: Appl. Phys. Lett. 117, 132602 (2020)

Optimal statistical inference in the presence of systematic uncertainties using neural network optimization based on binned Poisson likelihoods with nuisance parameters

Authors: Stefan Wunsch, Simon Jörger, Roger Wolf, Günter Quast

Abstract: Data analysis in science, e.g., high-energy particle physics, is often subject to an intractable likelihood if the observables and observations span a high-dimensional input space. Typically the problem is solved by reducing the dimensionality using feature engineering and histograms, whereby the latter technique allows to build the likelihood using Poisson statistics. However, in the presence of… ▽ More Data analysis in science, e.g., high-energy particle physics, is often subject to an intractable likelihood if the observables and observations span a high-dimensional input space. Typically the problem is solved by reducing the dimensionality using feature engineering and histograms, whereby the latter technique allows to build the likelihood using Poisson statistics. However, in the presence of systematic uncertainties represented by nuisance parameters in the likelihood, the optimal dimensionality reduction with a minimal loss of information about the parameters of interest is not known. This work presents a novel strategy to construct the dimensionality reduction with neural networks for feature engineering and a differential formulation of histograms so that the full workflow can be optimized with the result of the statistical inference, e.g., the variance of a parameter of interest, as objective. We discuss how this approach results in an estimate of the parameters of interest that is close to optimal and the applicability of the technique is demonstrated with a simple example based on pseudo-experiments and a more complex example from high-energy particle physics. △ Less

Submitted 13 January, 2021; v1 submitted 16 March, 2020; originally announced March 2020.

Journal ref: Comput Softw Big Sci 5, 4 (2021)

Reducing the dependence of the neural network function to systematic uncertainties in the input space

Authors: Stefan Wunsch, Simon Jörger, Roger Wolf, Günter Quast

Abstract: Applications of neural networks to data analyses in natural sciences are complicated by the fact that many inputs are subject to systematic uncertainties. To control the dependence of the neural network function to variations of the input space within these systematic uncertainties, several methods have been proposed. In this work, we propose a new approach of training the neural network by introd… ▽ More Applications of neural networks to data analyses in natural sciences are complicated by the fact that many inputs are subject to systematic uncertainties. To control the dependence of the neural network function to variations of the input space within these systematic uncertainties, several methods have been proposed. In this work, we propose a new approach of training the neural network by introducing penalties on the variation of the neural network output directly in the loss function. This is achieved at the cost of only a small number of additional hyperparameters. It can also be pursued by treating all systematic variations in the form of statistical weights. The proposed method is demonstrated with a simple example, based on pseudo-experiments, and by a more complex example from high-energy particle physics. △ Less

Submitted 23 February, 2020; v1 submitted 26 July, 2019; originally announced July 2019.

Journal ref: Comput Softw Big Sci 4, 5 (2020)

Comparison of SNSPDs biased with microwave and direct currents

Authors: Steffen Doerner, Artem Kuzmin, Stefan Wuensch, Michael Siegel

Abstract: This paper presents a detailed investigation of superconducting nanowire single-photon detectors (SNSPDs) biased with microwave and direct currents. We developed a hybrid detector, which allows the operation in the rf and dc operation mode. With this hybrid detector, we are able to compare the count rates of the same nanowire biased with dc and rf currents. Furthermore, we demonstrate the use of t… ▽ More This paper presents a detailed investigation of superconducting nanowire single-photon detectors (SNSPDs) biased with microwave and direct currents. We developed a hybrid detector, which allows the operation in the rf and dc operation mode. With this hybrid detector, we are able to compare the count rates of the same nanowire biased with dc and rf currents. Furthermore, we demonstrate the use of the oscillating current in the rf operation mode as a reference signal in a synchronous single-photon detection mode. △ Less

Submitted 17 January, 2019; originally announced January 2019.

Geometrical jitter and bolometric regime in photon detection by straight superconducting nanowire

Authors: Artem Kuzmin, Steffen Doerner, Stefan Wuensch, Konstantin Ilin, Michael Siegel, Mariia Sidorova, Alexey Semenov

Abstract: We present a direct observation of the geometrical jitter in single photon detection by a straight superconducting nanowire. Differential measurement technique was applied to the 180-μm long nanowire similar to those commonly used in the technology of superconducting nanowire single photon detectors (SNSPD). A non-gaussian geometrical jitter appears as a wide almost uniform probability distributio… ▽ More We present a direct observation of the geometrical jitter in single photon detection by a straight superconducting nanowire. Differential measurement technique was applied to the 180-μm long nanowire similar to those commonly used in the technology of superconducting nanowire single photon detectors (SNSPD). A non-gaussian geometrical jitter appears as a wide almost uniform probability distribution (histogram) of the delay time (latency) of the nanowire response to detected photon. White electrical noise of the readout electronics causes broadened, Gaussian shaped edges of the histogram. Subtracting noise contribution, we found for the geometrical jitter a standard deviation of 8.5 ps and the full width at half maximum (FWHM) of the distribution of 29 ps. FWHM corresponds to the propagation speed of the electrical signal along the nanowire of $6.2\times10^{6}$ m/s or 0.02 of the speed of light. Alternatively the propagation speed was estimated from the central frequency of the measured first order self-resonance of the nanowire. Both values agree well with each other and with previously reported values. As the intensity of the incident photon flux increases, the wide probability distribution collapses into a much narrower Gaussian distribution with a standard deviation dominated by the noise of electronics. We associate the collapse of the histogram with the transition from the discrete, single photon detection to the uniform bolometric regime △ Less

Submitted 20 February, 2019; v1 submitted 14 December, 2018; originally announced December 2018.

Machine Learning in High Energy Physics Community White Paper

Authors: Kim Albertsson, Piero Altoe, Dustin Anderson, John Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Bjorn Burkle, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Yi-fan Chen, Taylor Childers, Yann Coadou, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Andrea De Simone , et al. (103 additional authors not shown)

Abstract: Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas for machine learning in particle physics. We d… ▽ More Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas for machine learning in particle physics. We detail a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit. △ Less

Submitted 16 May, 2019; v1 submitted 8 July, 2018; originally announced July 2018.

Comments: Editors: Sergei Gleyzer, Paul Seyfert and Steven Schramm

Terahertz Transition-Edge Sensor with Kinetic-Inductance Amplifier at 4.2 K

Authors: Artem Kuzmin, Steffen Doerner, Stefan Singer, Ilya Charaev, Konstantin Ilin, Stefan Wuensch, Michael Siegel

Abstract: Different terrestrial terahertz applications would benefit from large-format arrays, operating in compact and inexpensive cryocoolers at liquid helium temperature with sensitivity, limited by the 300-K background radiation only. A voltage-biased Transition-Edge Sensor (TES) as a THz detector can have sufficient sensitivity and has a number of advantages important for real applications as linearity… ▽ More Different terrestrial terahertz applications would benefit from large-format arrays, operating in compact and inexpensive cryocoolers at liquid helium temperature with sensitivity, limited by the 300-K background radiation only. A voltage-biased Transition-Edge Sensor (TES) as a THz detector can have sufficient sensitivity and has a number of advantages important for real applications as linearity of response, high dynamic range and a simple calibration, however it requires a low-noise current readout. Usually, a current amplifier based on Superconducting Quantum-Interference Device (SQUID) is used for readout, but the scalability of this approach is limited due to complexity of the operation and fabrication. Recently, it has been shown that instead of SQUID it is possible to use a current sensor, which is based on the nonlinearity of the kinetic inductance of a current-carrying superconducting stripe. Embedding the stripe into a microwave high-Q superconducting resonator allows for reaching sufficient current sensitivity. More important, it is possible with the resonator approach to scale up to large arrays using Frequency-Division Multiplexing (FDM) in GHz range. Here, we demonstrate the operation of a voltage-biased TES with a microwave kinetic-inductance current amplifier at 4.2 K. We measured the expected intrinsic Noise-Equivalent Power NEP ~$5\times 10^{-14} \; \rm W/Hz^{1/2}$ and confirmed that a sufficient sensitivity of the readout can be reached in conjunction with a real TES operation. The construction of an array with the improved sensitivity ~ $10^{-15}\; \rm W/Hz^{1/2}$ at 4.2 K could be realized using a combination of the new current amplifier and already existing TES detectors with improved thermal isolation. △ Less

Submitted 2 July, 2018; originally announced July 2018.

Identifying the relevant dependencies of the neural network response on characteristics of the input space

Authors: Stefan Wunsch, Raphael Friese, Roger Wolf, Günter Quast

Abstract: The relation between the input and output spaces of neural networks (NNs) is investigated to identify those characteristics of the input space that have a large influence on the output for a given task. For this purpose, the NN function is decomposed into a Taylor expansion in each element of the input space. The Taylor coefficients contain information about the sensitivity of the NN response to t… ▽ More The relation between the input and output spaces of neural networks (NNs) is investigated to identify those characteristics of the input space that have a large influence on the output for a given task. For this purpose, the NN function is decomposed into a Taylor expansion in each element of the input space. The Taylor coefficients contain information about the sensitivity of the NN response to the inputs. A metric is introduced that allows for the identification of the characteristics that mostly determine the performance of the NN in solving a given task. Finally, the capability of this metric to analyze the performance of the NN is evaluated based on a task common to data analyses in high-energy particle physics experiments. △ Less

Submitted 15 October, 2018; v1 submitted 23 March, 2018; originally announced March 2018.

Journal ref: Comput Softw Big Sci (2018) 2: 5

Superconducting noise bolometer with microwave bias and readout for array applications

Authors: A. A. Kuzmin, A. D. Semenov, S. V. Shitov, M. Merker, S. H. Wuensch, A. V. Ustinov, M. Siegel

Abstract: We present a superconducting noise bolometer for terahertz radiation, which is suitable for large-format arrays. It is based on an antenna-coupled superconducting micro-bridge embedded in a high-quality factor superconducting resonator for a microwave bias and readout with frequency-division multiplexing in the GHz range. The micro-bridge is kept below its critical temperature and biased with a mi… ▽ More We present a superconducting noise bolometer for terahertz radiation, which is suitable for large-format arrays. It is based on an antenna-coupled superconducting micro-bridge embedded in a high-quality factor superconducting resonator for a microwave bias and readout with frequency-division multiplexing in the GHz range. The micro-bridge is kept below its critical temperature and biased with a microwave current of slightly lower amplitude than the critical current of the micro-bridge. The response of the detector is the rate of superconducting fluctuations, which depends exponentially on the concentration of quasiparticles in the micro-bridge. Excess quasiparticles are generated by an incident THz signal. Since the quasiparticle lifetime increases exponentially at lower operation temperature, the noise equivalent power rapidly decreases. This approach allows for large arrays of noise bolometers operating above 1 K with sensitivity, limited by 300-K background noise. Moreover, the response of the bolometer always dominates the noise of the readout due to relatively large amplitude of the bias current. We performed a feasibility study on a proof-of-concept device with a ${1.0\times 0.5 \rm μm^{2}}$ micro-bridge from a 9-nm thin Nb film on a sapphire substrate. Having a critical temperature of 5.8 K, it operates at 4.2 K and is biased at the frequency 5.6 GHz. For the quasioptical input at 0.65 THz, we measured the noise equivalent power ${\approx 3\times 10^{-12}\rm W/\sqrt Hz}$ , which is close to expectations for this particular device in the noise-response regime. △ Less

Submitted 9 September, 2017; originally announced September 2017.

Journal ref: Appl. Phys. Lett. 111, 042601 (2017)

Compact microwave kinetic inductance nanowire galvanometer for cryogenic detectors at 4.2 K

Authors: S. Doerner, A. Kuzmin, K. Graf, S. Wuensch, I. Charaev, M. Siegel

Abstract: We present a compact current sensor based on a superconducting microwave lumped-element resonator with a nanowire kinetic inductor, operating at 4.2 K. The sensor is suitable for multiplexed readout in GHz range of large-format arrays of cryogenic detectors. The device consists of a lumped-element resonant circuit, fabricated from a single 4-nm-thick superconducting layer of niobium nitride. Thus,… ▽ More We present a compact current sensor based on a superconducting microwave lumped-element resonator with a nanowire kinetic inductor, operating at 4.2 K. The sensor is suitable for multiplexed readout in GHz range of large-format arrays of cryogenic detectors. The device consists of a lumped-element resonant circuit, fabricated from a single 4-nm-thick superconducting layer of niobium nitride. Thus, the fabrication and operation is significantly simplified in comparison to state-of-the-art approaches. Because the resonant circuit is inductively coupled to the feed line the current to be measured can directly be injected without having the need of an impedance matching circuit, reducing the system complexity. With the proof-of-concept device we measured a current noise floor δImin of 10 pA/Hz1/2 at 10 kHz. Furthermore, we demonstrate the ability of our sensor to amplify a pulsed response of a superconducting nanowire single-photon detector using a GHz-range carrier for effective frequency-division multiplexing. △ Less

Submitted 8 September, 2017; originally announced September 2017.

Frequency-Multiplexed bias and readout of a 16-pixel Superconducting Nanowire Single-Photon Detector Array

Authors: Steffen Doerner, Artem Kuzmin, Stefan Wuensch, Ilya Charaev, Florian Boes, Thomas Zwick, Michael Siegel

Abstract: We demonstrate a 16-pixel array of radio-frequency superconducting nanowire single-photon detectors with an integrated and scalable frequency-division multiplexing architecture, reducing the required bias and readout lines to a single microwave feed line. The electrical behavior of the photon-sensitive nanowires, embedded in a resonant circuit, as well as the optical performance and timing jitter… ▽ More We demonstrate a 16-pixel array of radio-frequency superconducting nanowire single-photon detectors with an integrated and scalable frequency-division multiplexing architecture, reducing the required bias and readout lines to a single microwave feed line. The electrical behavior of the photon-sensitive nanowires, embedded in a resonant circuit, as well as the optical performance and timing jitter of the single detectors is discussed. Besides the single pixel measurements we also demonstrate the operation of the 16-pixel array with a temporal, spatial and photon-number resolution. △ Less

Submitted 28 April, 2017; originally announced May 2017.

Operation of Multi-Pixel Radio-Frequency Superconducting Nanowire Single-Photon Detector Arrays

Authors: Steffen Doerner, Artem Kuzmin, Stefan Wuensch, Ilya Charaev, Michael Siegel

Abstract: The concept of the radio-frequency superconducting nanowire single-photon detector (RF-SNSPD) allows frequency-division multiplexing (FDM) of the bias and readout lines of several SNSPDs. Using this method, a multi-pixel array can be operated by only one feed line. Consequently, the system complexity as well as the heat load is significantly reduced. To allocate many pixels into a small bandwidth… ▽ More The concept of the radio-frequency superconducting nanowire single-photon detector (RF-SNSPD) allows frequency-division multiplexing (FDM) of the bias and readout lines of several SNSPDs. Using this method, a multi-pixel array can be operated by only one feed line. Consequently, the system complexity as well as the heat load is significantly reduced. To allocate many pixels into a small bandwidth the quality factor of each device is crucial. In this paper, we present an improved RF-SNSPD design. This new design enables a simple tuning of the quality factor as well as the resonant frequency. With a two-pixel device we have demonstrated the operation without crosstalk between the detectors and showed the time, spatial and photon number resolution. Thereby a single pixel requires only a bandwidth of 14 MHz. △ Less

Submitted 7 December, 2016; originally announced December 2016.

Wide-Range Bolometer with RF Readout TES

Authors: S. V. Shitov, N. N. Abramov, A. A. Kuzmin, M. Merker, M. Arndt, S. H. Wuensch, K. S. Ilin, E. Erhan, A. Ustinov, M. Siegel

Abstract: To improve both scalability and noise-filtering capability of a Transition-Edge Sensor (TES), a new concept of a thin-film detector is suggested, which is based on embedding a microbridge TES into a high-Q planar GHz range resonator weakly coupled to a 50 Ohm-readout transmission line. Such a TES element is designed as a hot-electron microbolometer coupled to a THz range antenna and as a load of t… ▽ More To improve both scalability and noise-filtering capability of a Transition-Edge Sensor (TES), a new concept of a thin-film detector is suggested, which is based on embedding a microbridge TES into a high-Q planar GHz range resonator weakly coupled to a 50 Ohm-readout transmission line. Such a TES element is designed as a hot-electron microbolometer coupled to a THz range antenna and as a load of the resonator at the same time. A weak THz signal coupled to the antenna heats the microbridge TES, thus reducing the quality factor of the resonator and leading to a power increment in the readout line. The power-to-power conversion gain, an essential figure of merit, is estimated to be above 10. To demonstrate the basic concept, we fabricated and tested a few submicron sized devices from Nb thin films for operation temperature about 5 K. The dc and rf characterization of the new device is made at a resonator frequency about 5.8 GHz. A low-noise HEMT amplifier is used in our TES experiments without the need for a SQUID readout. The optical sensitivity to blackbody radiation within the frequency band 600-700 GHz is measured as $\sim3\times 10^{-14} \textrm W/\sqrt{\textrm Hz}$ at Tc {\approx} 5 K at bath temperature ~ 1.5 K. △ Less

Submitted 17 December, 2014; originally announced December 2014.

Superconducting hot-electron nanobolometer with microwave bias and readout

Authors: A. A. Kuzmin, M. Merker, S. V. Shitov, N. N. Abramov, A. B. Ermakov, M. Arndt, S. H. Wuensch, K. S. Ilin, A. V. Ustinov, M Siegel

Abstract: We propose a new detection technique based on radio-frequency (RF) bias and readout of an antenna-coupled superconducting nanobolometer. This approach is suitable for Frequency-Division-Multiplexing (FDM) readout of large arrays using broadband low-noise RF amplifier. We call this new detector RFTES. This feasibility study was made on demonstrator devices which are made in all-Nb technology and op… ▽ More We propose a new detection technique based on radio-frequency (RF) bias and readout of an antenna-coupled superconducting nanobolometer. This approach is suitable for Frequency-Division-Multiplexing (FDM) readout of large arrays using broadband low-noise RF amplifier. We call this new detector RFTES. This feasibility study was made on demonstrator devices which are made in all-Nb technology and operate at 4.2 K. The studied RFTES devices consist of an antenna-coupled superconducting nanobolometer made of ultrathin niobium films with transition temperature Tc = 5.2 K. The 0.65-THz antenna and nanobolometer are embedded as a load into a GHz-range coplanar niobium resonator (Tc = 8.9 K, Q = 4000). To heat the superconducting Nb nanobolometer close to the Tc, the RF power at resonator frequency f = 5.8 GHz is applied via a transmission line which is weakly coupled (-11 dB) to the loaded resonator. The THz-antenna of RFTES was placed in the focus of a sapphire immersion lens inside a He4-cryostat equipped with an optical window and a semiconductor RF amplifier. We have demonstrated optical response of the RFTES to THz radiation. The demonstrator receiver system employing the RFTES device showed an optical Noise-Equivalent Power (NEP) 1e-14 W/sqrt(Hz) at 4.2 K. △ Less

Submitted 15 December, 2014; originally announced December 2014.