- Email: [email protected]
Development of pixellated Ir-TESs
ARTICLE IN PRESS
Nuclear Instruments and Methods in Physics Research A 559 (2006) 494–496 www.elsevier.com/locate/nima
Development of pixellated Ir-TESs Nobuyuki Zena,, Hiroyuki Takahashia, Yuichi Kuniedaa, Rathnayaka M.T. Damayanthia, Fumiakira Moria, Kaoru Fujitaa, Masaharu Nakazawaa, Daiji Fukudab, Masataka Ohkubob a
Department of Quantum Engineering and Systems Science, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo 113-8656, Japan b National Institute of Advanced Industrial Science and Technology, 1-1-1 Umezono Tsukuba, Ibaraki 305-8563, Japan Available online 4 January 2006
Abstract We have been developing Ir-based pixellated superconducting transition edge sensors (TESs). In the area of material or astronomical applications, the sensor with few eV energy resolution and over 1000 pixels imaging property is desired. In order to achieve this goal, we have been analyzing signals from pixellated TESs. In the case of a 20 pixel array of Ir-TESs, with 45 mm 45 mm pixel sizes, the incident X-ray signals have been classified into 16 groups. We have applied numerical signal analysis. On the one hand, the energy resolution of our pixellated TES is strongly degraded. However, using pulse shape analysis, we can dramatically improve the resolution. Thus, we consider that the pulse signal analysis will lead this device to be used as a practical photon incident position identifying TES. r 2005 Elsevier B.V. All rights reserved. PACS: 29.30.Kv; 29.40.Gx; 29.40.Vj; 29.85.+c Keywords: TES; Pixel; Array; Signal analysis; Clustering algorithm
1. Introduction X-ray imaging spectroscopy with high energy resolution is strongly desired for astronomical observations or fluorescence analyses. Superconducting transition edge sensors (TESs) are, ultimately, sensitive calorimeters which use their own phase transition edges, and can provide a few eV energy resolution [1]. However, in terms of imaging, the complicated read out system makes work with arrays challenging. Usually, a series array of superconducting quantum interference devices (SQUIDs) is used for amplifying the signals from the TES, and multiple SQUIDs are necessary to read out the pixel arrayed TES [2]. In order to realize a large format TES array which has over 1000 pixels, a simple operation is preferable. On this point, we have fabricated some pixellated TESs whose pixels are all parallel-biased, and read out together by only one SQUID [3]. In this system, the pulse shape analysis becomes important to identify event position. We have adopted the clustering method as a Corresponding author. Tel.: +81 3 5841 6974; fax: +81 3 5841 2928.
E-mail address: [email protected] (N. Zen). 0168-9002/$ - see front matter r 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.nima.2005.12.083
way to classify pulse signals and applied it to a 20 pixel IrTES array.
2. Geometry of 20 pixel Ir-TES We have fabricated a 20 pixel Ir-TES on a 400-nm-thick Si3N4 membrane. Iridium was deposited by magnetron sputtering, and two Ir-TES arrays with 50 and 100 nm thickness are shown in this paper. Their I–V curves indicate that both arrays work properly, though their effective bias ranges are different. A micrograph of a 20 pixel Ir-TES is shown in Fig. 1a. Every pixel is parallel-biased through Nb electrodes and its size is 45 mm 45 mm. This TES has a two-dimensional structure, and ten pixels of each row are defined by nine 45 mm 5 mm sized slits. These slits thermally isolate the pixels from each other. A schematic image of a cross-section view is shown in Fig. 1b. The bridge style membrane structure causes pixels near the edges to cool more effectively than central pixels. This causes a temperature distribution throughout the TES array and also results in different equilibrium bias points for the various pixels, despite their parallel voltage bias.
ARTICLE IN PRESS N. Zen et al. / Nuclear Instruments and Methods in Physics Research A 559 (2006) 494–496
495
Fig. 1. (a) Micrograph of a 20 pixel Ir-TES. (b) A schematic image of a cross-section view of a 20 pixel Ir-TES. Fig. 2. (a) Three-dimensional cluster profile. (b) Averaged pulse shapes in different clusters.
Hence, this structure leads to distinct differences in pixel signal rise and fall times and also pulse height. 3. Irradiation experiment on the 20 pixel Ir-TES Previously, we had applied the low temperature scanning synchrotron microscopy (LTSSM) measurement to a 1D 10 pixel Ir-TES and scanned along each pixel with a 3 keV collimated X-ray source [3]. This 10 pixel Ir-TES has the same configuration as the 20 pixel Ir-TES, which is a membrane structure, parallel voltage-biased and 100 nm thick. By analyzing pulse signals with two parameters, pulse height and rise time, the scanning result showed ten distinct pulse shape groups. Encouraged by this result, we irradiated a dispersive X-ray from an 55Fe source on the 50-nm-thick 20 pixel Ir-TES array which is biased at 7.5 V (94% of Rn ). The pulse shape profile which was analyzed for pulse height, rise time and fall time shows some waveform groups; however, the profile reflects the symmetric arrangement of the device and prevents us from identifying each pixel. Below, we describe further pulse shape analysis. We performed on this data set to improve event position identification.
degree of non-similarity is smaller than some limit, pulse signals are combined into a cluster. The degree of nonsimilarity is calculated again for this new data set and the cluster binding gets repeated. These procedures are continued until the minimum of non-similarity becomes bigger than another configured value. Details are mentioned in Ref. [4]. 4.2. Clustering results The clustering method has been applied to all pulse signals from the 20 pixel Ir-TES. From 12311 pulse signals, 3542 clusters emerged. Among them, about 3400 clusters include only one or two pulse signals, and the number of clusters which include over 100 pulse signals is less than 50. In these 50 clusters, we have found 20 distinguishable pulse shape groups as shown in Fig. 2a. Fig. 2b shows the averaged pulse signals of different clusters. These averaged pulse signals are characteristic in their shapes, and it can be concluded that the clustering method has successfully classified pulse signals from a 20 pixel Ir-TES. 5. Energy resolution
4. Pulse shape analysis The pulse shape profile from the 20 pixel Ir-TES makes it challenging to identify each event in the pixel due to the symmetric array geometry. Because the pulse shape should be different for different pixels, it should be possible to gather similar pulses in order to identify ‘‘hit’’ pixels. We have adopted such a clustering signal processing algorithm which can classify signals by their shapes into some groups, called ‘‘clusters’’ [4]. 4.1. Clustering method Before executing the clustering algorithm, it is necessary to convert the pulse shape information to a waveform vector. A waveform vector consists of nine elements, each of which is a time span between pairs of equal voltage points on a signal pulse. The waveform vector includes detailed information about pulse height, rise time and fall time. The clustering algorithm evaluates the degree of nonsimilarity by the distances among waveform vectors. If the
A dispersive 5.9 keV X-ray was irradiated on the entire area of a 50-nm-thick, 20 pixel Ir-TES which was voltage biased at 88% of Rn . The base line noise was around 14 eV FWHM for every pixel. However, the energy resolution was far worse than the baseline noise, and even the best value among all pixels was 111 eV. The appearance of the Ka line was not sharp, even though the Ka and Kb lines were barely distinguishable. On the other hand, the energy resolution of our 100-nm-thick, 20 pixel Ir-TES which was biased at 80% of Rn was 38.7 eV, and its baseline noise was 13.8 eV. These results may indicate the necessity of controlling the film thickness. Also, even in the case of the 100-nm-thick TES, the energy resolution was three times worse than the baseline noise. This was due to the incomplete separation of each pixel. According to our previous experiments on the 10 pixel Ir-TES, where we irradiated the center of each pixel with a collimated 3 keV X-ray beam, we had achieved 13.1 eV energy resolution, and the value was close to the baseline noise of 10.7 eV [3]. Thus, in order to improve the
ARTICLE IN PRESS 496
N. Zen et al. / Nuclear Instruments and Methods in Physics Research A 559 (2006) 494–496
energy resolution of pixellated TESs, it is necessary to improve the separation between pixels. One possible way might be to use wider slits to define each pixel.
pixel-arrayed TES with increased isolation between pixels may provide a practical position resolving, photon sensitive TES.
6. Conclusion
Acknowledgments
We have been developing Ir-based pixellated TESs with a simple read out system for future large format TES arrays. Pulse signals from 20 pixel Ir-TES whose shapes are characteristic for each pixel are automatically classified into 20 groups by the numerical signal analysis, clustering method. The energy resolution of the 100-nm-thick, 20 pixel Ir-TES is 38.7 eV FWHM for 5.9 keV X-rays of uniform illumination, in spite of the low baseline noise of 13.8 eV. Along with the clustering method, the
The device was fabricated at the VLSI Design and Education Center, The University of Tokyo. References [1] [2] [3] [4]
K.D. Irwin, Appl. Phys. Lett. 69 (1996) 1945. M.F. Cunningham, et al., Appl. Phys. Lett. 81 (2002) 159. M. Ohno, et al., Nucl. Instr. and Meth. A 520 (2004) 267. A. Nakamura, et al, IEEE Trans. Nucl. Sci. 49 (2002) 3295.
Nuclear Instruments and Methods in Physics Research A 559 (2006) 494–496 www.elsevier.com/locate/nima
Development of pixellated Ir-TESs Nobuyuki Zena,, Hiroyuki Takahashia, Yuichi Kuniedaa, Rathnayaka M.T. Damayanthia, Fumiakira Moria, Kaoru Fujitaa, Masaharu Nakazawaa, Daiji Fukudab, Masataka Ohkubob a
Department of Quantum Engineering and Systems Science, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo 113-8656, Japan b National Institute of Advanced Industrial Science and Technology, 1-1-1 Umezono Tsukuba, Ibaraki 305-8563, Japan Available online 4 January 2006
Abstract We have been developing Ir-based pixellated superconducting transition edge sensors (TESs). In the area of material or astronomical applications, the sensor with few eV energy resolution and over 1000 pixels imaging property is desired. In order to achieve this goal, we have been analyzing signals from pixellated TESs. In the case of a 20 pixel array of Ir-TESs, with 45 mm 45 mm pixel sizes, the incident X-ray signals have been classified into 16 groups. We have applied numerical signal analysis. On the one hand, the energy resolution of our pixellated TES is strongly degraded. However, using pulse shape analysis, we can dramatically improve the resolution. Thus, we consider that the pulse signal analysis will lead this device to be used as a practical photon incident position identifying TES. r 2005 Elsevier B.V. All rights reserved. PACS: 29.30.Kv; 29.40.Gx; 29.40.Vj; 29.85.+c Keywords: TES; Pixel; Array; Signal analysis; Clustering algorithm
1. Introduction X-ray imaging spectroscopy with high energy resolution is strongly desired for astronomical observations or fluorescence analyses. Superconducting transition edge sensors (TESs) are, ultimately, sensitive calorimeters which use their own phase transition edges, and can provide a few eV energy resolution [1]. However, in terms of imaging, the complicated read out system makes work with arrays challenging. Usually, a series array of superconducting quantum interference devices (SQUIDs) is used for amplifying the signals from the TES, and multiple SQUIDs are necessary to read out the pixel arrayed TES [2]. In order to realize a large format TES array which has over 1000 pixels, a simple operation is preferable. On this point, we have fabricated some pixellated TESs whose pixels are all parallel-biased, and read out together by only one SQUID [3]. In this system, the pulse shape analysis becomes important to identify event position. We have adopted the clustering method as a Corresponding author. Tel.: +81 3 5841 6974; fax: +81 3 5841 2928.
E-mail address: [email protected] (N. Zen). 0168-9002/$ - see front matter r 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.nima.2005.12.083
way to classify pulse signals and applied it to a 20 pixel IrTES array.
2. Geometry of 20 pixel Ir-TES We have fabricated a 20 pixel Ir-TES on a 400-nm-thick Si3N4 membrane. Iridium was deposited by magnetron sputtering, and two Ir-TES arrays with 50 and 100 nm thickness are shown in this paper. Their I–V curves indicate that both arrays work properly, though their effective bias ranges are different. A micrograph of a 20 pixel Ir-TES is shown in Fig. 1a. Every pixel is parallel-biased through Nb electrodes and its size is 45 mm 45 mm. This TES has a two-dimensional structure, and ten pixels of each row are defined by nine 45 mm 5 mm sized slits. These slits thermally isolate the pixels from each other. A schematic image of a cross-section view is shown in Fig. 1b. The bridge style membrane structure causes pixels near the edges to cool more effectively than central pixels. This causes a temperature distribution throughout the TES array and also results in different equilibrium bias points for the various pixels, despite their parallel voltage bias.
ARTICLE IN PRESS N. Zen et al. / Nuclear Instruments and Methods in Physics Research A 559 (2006) 494–496
495
Fig. 1. (a) Micrograph of a 20 pixel Ir-TES. (b) A schematic image of a cross-section view of a 20 pixel Ir-TES. Fig. 2. (a) Three-dimensional cluster profile. (b) Averaged pulse shapes in different clusters.
Hence, this structure leads to distinct differences in pixel signal rise and fall times and also pulse height. 3. Irradiation experiment on the 20 pixel Ir-TES Previously, we had applied the low temperature scanning synchrotron microscopy (LTSSM) measurement to a 1D 10 pixel Ir-TES and scanned along each pixel with a 3 keV collimated X-ray source [3]. This 10 pixel Ir-TES has the same configuration as the 20 pixel Ir-TES, which is a membrane structure, parallel voltage-biased and 100 nm thick. By analyzing pulse signals with two parameters, pulse height and rise time, the scanning result showed ten distinct pulse shape groups. Encouraged by this result, we irradiated a dispersive X-ray from an 55Fe source on the 50-nm-thick 20 pixel Ir-TES array which is biased at 7.5 V (94% of Rn ). The pulse shape profile which was analyzed for pulse height, rise time and fall time shows some waveform groups; however, the profile reflects the symmetric arrangement of the device and prevents us from identifying each pixel. Below, we describe further pulse shape analysis. We performed on this data set to improve event position identification.
degree of non-similarity is smaller than some limit, pulse signals are combined into a cluster. The degree of nonsimilarity is calculated again for this new data set and the cluster binding gets repeated. These procedures are continued until the minimum of non-similarity becomes bigger than another configured value. Details are mentioned in Ref. [4]. 4.2. Clustering results The clustering method has been applied to all pulse signals from the 20 pixel Ir-TES. From 12311 pulse signals, 3542 clusters emerged. Among them, about 3400 clusters include only one or two pulse signals, and the number of clusters which include over 100 pulse signals is less than 50. In these 50 clusters, we have found 20 distinguishable pulse shape groups as shown in Fig. 2a. Fig. 2b shows the averaged pulse signals of different clusters. These averaged pulse signals are characteristic in their shapes, and it can be concluded that the clustering method has successfully classified pulse signals from a 20 pixel Ir-TES. 5. Energy resolution
4. Pulse shape analysis The pulse shape profile from the 20 pixel Ir-TES makes it challenging to identify each event in the pixel due to the symmetric array geometry. Because the pulse shape should be different for different pixels, it should be possible to gather similar pulses in order to identify ‘‘hit’’ pixels. We have adopted such a clustering signal processing algorithm which can classify signals by their shapes into some groups, called ‘‘clusters’’ [4]. 4.1. Clustering method Before executing the clustering algorithm, it is necessary to convert the pulse shape information to a waveform vector. A waveform vector consists of nine elements, each of which is a time span between pairs of equal voltage points on a signal pulse. The waveform vector includes detailed information about pulse height, rise time and fall time. The clustering algorithm evaluates the degree of nonsimilarity by the distances among waveform vectors. If the
A dispersive 5.9 keV X-ray was irradiated on the entire area of a 50-nm-thick, 20 pixel Ir-TES which was voltage biased at 88% of Rn . The base line noise was around 14 eV FWHM for every pixel. However, the energy resolution was far worse than the baseline noise, and even the best value among all pixels was 111 eV. The appearance of the Ka line was not sharp, even though the Ka and Kb lines were barely distinguishable. On the other hand, the energy resolution of our 100-nm-thick, 20 pixel Ir-TES which was biased at 80% of Rn was 38.7 eV, and its baseline noise was 13.8 eV. These results may indicate the necessity of controlling the film thickness. Also, even in the case of the 100-nm-thick TES, the energy resolution was three times worse than the baseline noise. This was due to the incomplete separation of each pixel. According to our previous experiments on the 10 pixel Ir-TES, where we irradiated the center of each pixel with a collimated 3 keV X-ray beam, we had achieved 13.1 eV energy resolution, and the value was close to the baseline noise of 10.7 eV [3]. Thus, in order to improve the
ARTICLE IN PRESS 496
N. Zen et al. / Nuclear Instruments and Methods in Physics Research A 559 (2006) 494–496
energy resolution of pixellated TESs, it is necessary to improve the separation between pixels. One possible way might be to use wider slits to define each pixel.
pixel-arrayed TES with increased isolation between pixels may provide a practical position resolving, photon sensitive TES.
6. Conclusion
Acknowledgments
We have been developing Ir-based pixellated TESs with a simple read out system for future large format TES arrays. Pulse signals from 20 pixel Ir-TES whose shapes are characteristic for each pixel are automatically classified into 20 groups by the numerical signal analysis, clustering method. The energy resolution of the 100-nm-thick, 20 pixel Ir-TES is 38.7 eV FWHM for 5.9 keV X-rays of uniform illumination, in spite of the low baseline noise of 13.8 eV. Along with the clustering method, the
The device was fabricated at the VLSI Design and Education Center, The University of Tokyo. References [1] [2] [3] [4]
K.D. Irwin, Appl. Phys. Lett. 69 (1996) 1945. M.F. Cunningham, et al., Appl. Phys. Lett. 81 (2002) 159. M. Ohno, et al., Nucl. Instr. and Meth. A 520 (2004) 267. A. Nakamura, et al, IEEE Trans. Nucl. Sci. 49 (2002) 3295.