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NASA NTRS1972

Adaptive line by line encoder for image transmission.

A simple adaptive algorithm is applied to the line by line encoding of images. Among its desirable properties the algorithm includes a control of encoding errors independently of the image statistics. This block transform encoder, because of its adaptive nature gives rise to nonstationary errors and end of block effects. Two methods are proposed to reduce these effects and thus improve the subjective quality of reconstructed images. The performance of the algorithm is image dependent and several illustrative examples are given.

Algazi, V. R.↗

NASA NTRS1994

Convolutional encoding of self-dual block codes (2)

Solomon and van Tilborg have developed convolutional encoding algorithms for quadratic residue (QR) codes of lengths 47 and beyond. For these codes and reasonable constraint lengths, there are sequential decodings that may be simple, as in a convolutional encoding/decoding of the extended Golay Code. In addition, the previously found constraint length K = 9 for the (48, 24; 12) QR code was lower to K = 8 by Solomon. In our search for the smallest possible constraint lengths K for (80, 40; 16) self-dual quadratic residue and nonquadratic residue codes, we have found the constraint lengths K = 14 and K = 13, respectively. We have discovered a K = 21 convolutional encoding for the (104, 52; 20) QR code; there may be a smaller K for a (104, 52; 20) self-dual code that is not a quadratic residue code. The smaller the K, the less complex the sequential or Viterbi decoder.

Solomon, G.↗

DOE OSTI2023

A Novel Spatial-Temporal Variational Quantum Circuit to Enable Deep Learning on NISQ Devices

Quantum computing presents a promising approach for machine learning with its capability for extremely parallel computation in high-dimension through superposition and entanglement. Despite its potential, existing quantum learning algorithms, such as Variational Quantum Circuits (VQCs), face challenges in handling more complex datasets, particularly those that are not linearly separable. What’s more, it encounters the deployability issue, making the learning models suffer a drastic accuracy drop after deploying them to the actual quantum devices. To overcome these limitations, this paper proposes a novel spatial-temporal design, namely “ST-VQC”, to integrate nonlinearity in quantum learning and improve the robustness of the learning model to noise. Specifically, ST-VQC can extract spatial features via a novel block-based encoding quantum sub-circuit coupled with a layer-wise computation quantum sub-circuit to enable temporal-wise deep learning. Additionally, a SWAP-Free physical circuit design is devised to improve robustness. These designs bring a number of hyperparameters. After a systematic analysis of the design space for each design component, an automated optimization framework is proposed to generate the ST-VQC quantum circuit. The proposed ST-VQC has been evaluated on two IBM quantum processors, ibm-cairo with 27 qubits and ibmq-lima with 7 qubits to assess its effectiveness. The results of the evaluation on the standard dataset for binary classification show that ST-VQC can achieve over 30% accuracy improvement compared with existing VQCs on actual quantum computers. Moreover, on a non-linear synthetic dataset, the STVQC outperforms a linear classifier by 27.9%, while the linear classifier using classical computing outperforms the existing VQC by 15.58%.

Li, Jinyang↗

NASA NTRS1971

Image coding by adaptive block quantization.

A new source encoder called the adaptive block quantizer is proposed for coding data sources that emit a sequence of correlated real numbers with known first- and second-order statistics. Blocks of source output symbols are first classified and then block quantized in a manner that depends on their classification. The system is optimized relative to both the mean square error and the subjective quality of the reconstructed data for a certain class of pictorial data, and the resulting system performance demonstrated. Some interesting relationships between mean square error and subjective picture quality are presented.

Tasto, M.↗

DOE OSTI2019

Human V H 1-69 Gene-Encoded Human Monoclonal Antibodies against Staphylococcus aureus IsdB Use at Least Three Distinct Modes of Binding To Inhibit Bacterial Growth and Pathogenesis

Staphylococcus aureus is an important human pathogen that infects nearly every human tissue. Like most organisms, the acquisition of nutrient iron is necessary for its survival. One route by which it obtains this metal is through the iron-regulated surface determinant (Isd) system that scavenges iron from the hemoglobin of the host. We show that the heavy chain variable region IGHV1-69 gene commonly encodes human monoclonal antibodies (mAbs) targeting IsdB-NEAT2. Remarkably, these antibodies bind to multiple antigenic sites. One class of IGHV1-69-encoded mAbs blocks S. aureus heme acquisition by binding to the heme-binding site of NEAT2, while two additional classes reduce the bacterial burden in vivo by an alternative Fc receptor-mediated mechanism. We further identified clonal lineages of IGHV1-69-encoded mAbs using donor samples, showing that each lineage diversifies during infection by somatic hypermutation. These studies reveal that IGHV1-69-encoded antibodies contribute to a protective immune response, furthering our understanding of the correlates of protection against S. aureus infection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Composing effective prediction at five points

Color-kinematics duality in the adjoint has proven key to the relationship between gauge and gravity theory scattering amplitude predictions. In recent work, we demonstrated that at four-point tree-level, a small number of color-dual EFT building blocks could encode all higher-derivative single-trace massless corrections to gauge and gravity theories compatible with adjoint double-copy. One critical aspect was the trivialization of building higher-derivative color-weights — indeed, it is the mixing of kinematics with non-adjoint-type color-weights (like the permutation-invariant d 4 ) which permits description via adjoint double-copy. Here we find that such ideas clarify the predictions of local five-point higher-dimensional operators as well. We demonstrate how a single scalar building block can be combined with color structures to build higher-derivative color factors that generate, through double copy, the amplitudes associated with higher-derivative gauge-theory operators. These may then be suitably mapped, through another double-copy, to higher-derivative corrections in gravity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

Compact video content representation for video coding using low multi-linear tensor rank approximation with dynamic core tensor order

Tensor is a multi-way representation of an entity that is widely used in many applications of mathematics and physics. The wide range of tensor algebra operations attract the researchers of graphical and vision field to identify unique methods for various applications such as segmentation, compression, indexing and so on. In this paper, low multi-linear rank approximation of a tensor is used for decomposition so as to perform compression on a video that is represented as a 4D tensor. Thus, the encoder has blocks for (1) multilinear rank approximation method so as to aid decomposition, (2) sparsity removal of residual data to reduce the required memory storage to a small level, (3) quantization on the sparse less residual data and (4) LZ77 dictionary coding for the video. The decoder uses a tensor reconstruction block along with residual error correction block that reduces loss/error in the reconstructed video. The size of core tensor is an important factor in rank approximation. It is identified at run time depending on the video contents. This size is determined adaptively using Tikhonov’s regularization method. The best value of core tensor size is identified with the corner of L-curve which preserves the video contents from heavy loss/error. Experimental results of the proposed work on comparison with H.264/AVC compression method indicate that the proposed method achieves up to 10% improvement in compression ratio with the least amount of loss and a maximum signal to noise ratio of 0.14. The proposed system gives better compression ratio than H.265 for videos with more number of frames without compromising quality.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1995

Quantization Distortion in Block Transform-Compressed Data

The popular JPEG image compression standard is an example of a block transform-based compression scheme; the image is systematically subdivided into block that are individually transformed, quantized, and encoded. The compression is achieved by quantizing the transformed data, reducing the data entropy and thus facilitating efficient encoding. A generic block transform model is introduced.

block transform-compressed data quantization image↗

NASA NTRS1993

Determining the locations of the various CIRC recording format information blocks (user data blocks, C2 and C1 words and EFM frames) on a recorded compact disc

Just prior to its being EFM modulated (i.e., converted to eight-to-fourteen channel data by the EFM encoder) and written to a Compact Disc (CD), information that passes through the CIRC Block Encoder is grouped into 33-byte blocks referred to as EFM frames. Twenty four of the bytes that make up a given EFM frame are user data that was input into the CIRC encoder at various (different) times, 4 of the bytes of this same EFM frame were created by the C2 ECC encoder (each at a different time), and another 4 were created by the C1 ECC encoder (again, each at a different time). The one remaining byte of the given EFM frame, which is known as the EFM frame C&D (for Control & Display) byte, carries information that identifies which portion of the current disc program track the given EFM frame belongs to and also specifies the location of the given EFM frame on the disc (in terms of a time stamp that has a resolution of l/75th second, or 98 EFM frames). (Note: since the program track and time information is stored as a 98-byte word, a logical group consisting of 98 consecutive EFM frames must be read, and their respective C&D bytes must be catenated and decoded, before the program track identification and time position information that pertains to the entire block of 98 EFM frames can be obtained.) The C&D byte is put at the start (0th byte) of an EFM frame in real time; its placement completes the construction of the EFM frame - it is assigned just before the EFM frame enters the EFM encoder. Four distinct blocks of data are referred to: 24-byte User Input Data Blocks; 28-byte C2 words; 32-byte C1 words; and 33-byte EFM frames.

Howe, Dennis G.↗

DOE OSTI2023

Symmetry-Breaking Dendrimer Synthons in Colloidal Crystal Engineering with DNA

Breaking symmetry in colloidal crystals is challenging due to the inherent chemical and structural isotropy of many nanoscale building blocks. If a non-particle component could be used to anisotropically encode such building blocks with orthogonal recognition properties, one could expand the scope of structural and compositional possibilities of colloidal crystals beyond what is thus far possible with purely particle-based systems. In this work, we report the synthesis and characterization of novel DNA dendrimers that function as symmetry-breaking synthons, capable of programming anisotropic and orthogonal interactions within colloidal crystals. When the DNA dendrimers have identical sticky ends, they hybridize with DNA-functionalized nanoparticles to yield three distinct colloidal crystals, dictated by dendrimer size, including a structure not previously reported in the field of colloidal crystal engineering, Si 2 Sr. When used as symmetry-breaking synthons (when the sticky ends deliberately consist of orthogonal sequences), the synthesis of binary and ternary colloidal alloys with structures that can only be realized through directional interactions is possible. Furthermore, by modulating the extent of shape anisotropy within the DNA dendrimers, the local distribution of the nanoparticles within the crystals can be directed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Quantum Adiabatic Optimization with Rydberg Arrays: Localization Phenomena and Encoding Strategies

Quantum adiabatic optimization seeks to solve combinatorial problems using quantum dynamics, requiring the Hamiltonian of the system to align with the problem of interest. However, these Hamiltonians are often incompatible with the native constraints of quantum hardware, necessitating encoding strategies to map the original problem into a hardware-conformant form. While the classical overhead associated with such mappings is easily quantifiable and typically polynomial in problem size, it is much harder to quantify their overhead on the quantum algorithm, e.g., the transformation of the adiabatic timescale. In this work, we address this challenge on the concrete example of the encoding scheme proposed in [Nguyen , PRX Quantum , 010316 (2023)], which is designed to map optimization problems on arbitrarily connected graphs into Rydberg atom arrays. We consider the fundamental building blocks underlying this encoding scheme and determine the scaling of the minimum gap with system size along adiabatic protocols. Even when the original problem is trivially solvable, we find that the encoded problem can exhibit an exponentially closing minimum gap. We show that this originates from a quantum coherent effect, which gives rise to an unfavorable localization of the ground-state wave function. On the QuEra Aquila neutral atom machine, we observe such localization and its effect on the success probability of finding the correct solution to the encoded optimization problem. Finally, we propose quantum-aware modifications of the encoding scheme that avoid this quantum bottleneck and lead to an exponential improvement in the adiabatic performance. This highlights the crucial importance of accounting for quantum effects when designing strategies to encode classical problems onto quantum platforms. Published by the American Physical Society 2025

Bombieri, Lisa (ORCID:0009000950422897)↗

NASA NTRS1993

A high-speed lossless data compression system for space applications

This paper reports on the integration of a lossless data compression/decompression chipset into a space data system architecture. For its compression engine, the data system incorporates the Universal Source Encoder (USE) designed for the NASA/Goddard Space Flight Center. Currently, the data compression testbed generates video frames consisting of 512 lines of 512 pixels having 8-bit resolution. Each image is passed through the USE where the lines are internally partitioned into 16-word blocks. These blocks are adaptively encoded across widely varying entropy levels using a Rice 12-option set coding algorithm. The current system operates at an Input/Output rate of 10 Msamples/s or 80 Mbits/s for each buffered input line. Frame and line synchronization for each image are maintained through the use of uniquely decodable command words. Length information of each variable length compressed image line is also included in the output stream. The data and command information are passed to the next stage of the system architecture through a serial fiber-optic transmitter. The initial segment of this stage consists of packetizer hardware which adds an appropriate CCSDS header to the received source data. An uncompressed mode is optionally available to pass image lines directly to the packetizer hardware. A data decompression testbed has also been developed to confirm the data compression operation.

Miko, Joe↗

NASA NTRS1995

A seismic data compression system using subband coding

This article presents a study of seismic data compression techniques and a compression algorithm based on subband coding. The algorithm includes three stages: a decorrelation stage, a quantization stage that introduces a controlled amount of distortion to allow for high compression ratios, and a lossless entropy coding stage based on a simple but efficient arithmetic coding method. Subband coding methods are particularly suited to the decorrelation of nonstationary processes such as seismic events. Adaptivity to the nonstationary behavior of the waveform is achieved by dividing the data into separate blocks that are encoded separately with an adaptive arithmetic encoder. This is done with high efficiency due to the low overhead introduced by the arithmetic encoder in specifying its parameters. The technique could be used as a progressive transmission system, where successive refinements of the data can be requested by the user. This allows seismologists to first examine a coarse version of waveforms with minimal usage of the channel and then decide where refinements are required. Rate-distortion performance results are presented and comparisons are made with two block transform methods.

Kiely, A. B.↗

DOE OSTI2026

Quantum Computing for AI-based Design and Optimization of Electric Motors

Knowledge-based artificial intelligence and hierarchical fuzzy logic offer an interpretable framework for electricvehicle motor preliminary design, but their computational burden grows with linguistic granularity and coupled design-space size. This paper presents a reduced quantum reformulation of the hierarchical fuzzy inference of air-gap flux density, a representative level-one motor-design parameter. Starting from the published electric-vehicle motor-design framework, a three-term fuzzy prototype is constructed from the original inference structure. The reduced model is then reformulated as a modular quantum register-oracle system, in which each hierarchical subrelation is encoded as a block oracle and evaluated through superpositionbased candidate-label testing. The proposed modular quantum formulation reproduces the reduced classical prototype after block fusion. A resource analysis shows that the reduced modular system requires seven qubits per block and twenty-two qubits in a straightforward four-block implementation. Finally, a crossovercomplexity model is derived to identify the regime in which quantum candidate search may become favorable relative to hierarchical fuzzy inference. The results show that no quantum advantage should be claimed for the present one-output reduced benchmark, but that a plausible crossover emerges for larger joint candidate spaces and higher linguistic granularity. The work therefore establishes a technically consistent starting point for future quantum-assisted electric-vehicle motor-design optimization.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗

NASA NTRS1973

Note on the error signal of block quantizers.

Demonstration that the error signal incurred by block quantizing stationary data is nonstationary under some conditions. Examples are presented which indicate that the mean square error is largest at the block edges. When block quantizers are used to encode pictures at low bit rates, this effect tends to make the block edges visible in the reconstructed picture.

Tasto, M.↗

DOE OSTI2018

Radiation Hard CMOS Sensors for Detector at High Energy Colliders

In this project we developed a radiation hard CMOS sensor architecture for High Energy Colliders. The key accomplishments were: 1. Developed a sensor architecture to support very high occupancy rate and hit rates 2. Developed, simulated (TCAD), and fabricated 20 different types of pixelated test structures for the quadruple well high resistivity substrate process. Measured performance of these pixel test structures; Dark currents were found to be close to physical limits; and Quantum efficiency were found to be close to ideal as well 3. Defined the scope for the PDK for the quadruple well process on high resistivity silicon Highlights of the new architecture are: Readout of pixel arrays with reconstruction efficiency >99% at hit rates of 500 MHits/cm 2 and array occupancy of 0.2%; Minimization of in-pixel signal storage requirement (data will be read out at frame rates of 1MHz); Low power dissipation through integration of fragmented projection architecture (Minimum analog power dissipation); Pixel array level data reduction (Hit location is encoded through shape of sub-block projections); Programmable resolution and frame rate (Pixels can be binned to increase frame rate); Minimum data overhead, encoded projection results for all sub-blocks are read out without location information

43 PARTICLE ACCELERATORS↗

NASA NTRS1977

Advanced imaging communication system

Key elements of system are imaging and nonimaging sensors, data compressor/decompressor, interleaved Reed-Solomon block coder, convolutional-encoded/Viterbi-decoded telemetry channel, and Reed-Solomon decoding. Data compression provides efficient representation of sensor data, and channel coding improves reliability of data transmission.

Hilbert, E. E.↗

NASA NTRS1989

Data compression experiments with LANDSAT thematic mapper and Nimbus-7 coastal zone color scanner data

A case study is presented where an image segmentation based compression technique is applied to LANDSAT Thematic Mapper (TM) and Nimbus-7 Coastal Zone Color Scanner (CZCS) data. The compression technique, called Spatially Constrained Clustering (SCC), can be regarded as an adaptive vector quantization approach. The SCC can be applied to either single or multiple spectral bands of image data. The segmented image resulting from SCC is encoded in small rectangular blocks, with the codebook varying from block to block. Lossless compression potential (LDP) of sample TM and CZCS images are evaluated. For the TM test image, the LCP is 2.79. For the CZCS test image the LCP is 1.89, even though when only a cloud-free section of the image is considered the LCP increases to 3.48. Examples of compressed images are shown at several compression ratios ranging from 4 to 15. In the case of TM data, the compressed data are classified using the Bayes' classifier. The results show an improvement in the similarity between the classification results and ground truth when compressed data are used, thus showing that compression is, in fact, a useful first step in the analysis.

Tilton, James C.↗