Related papers: Data Streams from the Low Frequency Instrument On-…
We consider a system that is composed of an energy constrained sensor node and a sink node, and devise optimal data compression and transmission policies with an objective to prolong the lifetime of the sensor node. While applying…
Noiseless compressive sensing is a protocol that enables undersampling and later recovery of a signal without loss of information. This compression is possible because the signal is usually sufficiently sparse in a given basis. Currently,…
We estimate the effects of low temporal frequency modes in the time stream on sky maps such as expected from the PLANCK experiment -- a satellite mission designed to image the sky in the microwave band. We perform the computations in a…
The Planck mission will provide full-sky maps of the Cosmic Microwave Background with unprecedented angular resolution (~ 10') and sensitivity (DT / T = 10^-6). This requires cryogenically cooled, high sensitivity detectors as well as an…
The Radiometer Electronics Box Assembly (REBA) is the control and data processing on board computer of the Low Frequency Instrument (LFI) of the Planck mission (ESA). The REBA was designed and built incorporating state of the art…
The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission…
In this paper we present an overview of the Telescope designed for ESA's mission dedicated to map the Cosmic Microwave Background Anisotropies and Polarization. Two instruments, LFI and HFI, operate in an overall frequency range between 25…
Lossless floating-point time series compression is crucial for a wide range of critical scenarios. Nevertheless, it is a big challenge to compress time series losslessly due to the complex underlying layouts of floating-point values. The…
We present a procedure for efficiently compressing astronomical radio data for high performance applications. Integrated, post-correlation data are first passed through a nearly lossless rounding step which compares the precision of the…
In this paper we discuss two main problems associated with the analysis of the data from LISA Pathfinder (LPF): i) Excess noise detection and ii) Noise parameter identification. The mission is focused on the low frequency region ([0.1; 10]…
We investigate the effect of radio-frequency interference (RFI) excision in estimating the cosmological \hi\ 21 cm power spectrum. Flagging of RFI-contaminated channels results in a non-uniform sampling of the instrumental bandpass…
Thanks to the rapid proliferation of connected devices, sensor-generated time series constitute a large and growing portion of the world's data. Often, this data is collected from distributed, resource-constrained devices and centralized at…
The High Frequency Instrument of Planck will map the entire sky in the millimeter and sub-millimeter domain from 100 to 857 GHz with unprecedented sensitivity to polarization ($\Delta P/T_{\tiny cmb} \sim 4\cdot 10^{-6}$) at 100, 143, 217…
Although large language models (LLM) have achieved remarkable performance, their enormous parameter counts hinder deployment on resource-constrained hardware. Low-rank compression can reduce both memory usage and computational demand, but…
LiteBIRD is a space-borne experiment dedicated to detecting large-scale $B$-mode anisotropies in the linear polarization of the Cosmic Microwave Background (CMB) predicted by the theory of inflation. It is planned to be launched in the late…
As the use of neuromorphic, event-based vision sensors expands, the need for compression of their output streams has increased. While their operational principle ensures event streams are spatially sparse, the high temporal resolution of…
We propose a novel lossless and lossy compression scheme for color filter array~(CFA) sampled images based on the wavelet transform of them. Our analysis suggests that the wavelet coefficients of HL and LH subbands are highly correlated.…
Recent learning-based lossless image compression methods encode an image in the unit of subimages and achieve comparable performances to conventional non-learning algorithms. However, these methods do not consider the performance drop in…
Today's HPC applications are producing extremely large amounts of data, such that data storage and analysis are becoming more challenging for scientific research. In this work, we design a new error-controlled lossy compression algorithm…
Compression algorithms reduce the redundancy in data representation to decrease the storage required for that data. Data compression offers an attractive approach to reducing communication costs by using available bandwidth effectively.…