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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23

Method and system for identifying and authenticating an object

An object has a taggant placed in a first portion thereof and has a visible symbol placed on a second portion thereof. When the object is to be identified and authenticated, the taggant is made to radiate with a specific energy signature. The energy signature and at least one image of the symbol are recorded along with a relative location that identifies the first portion of the object. The combination of the energy signature, symbol image and relative location are used to repeatedly identify and authenticate the object.

Schramm, Jr., Harry F.↗

Error Rates and Channel Capacities in Multipulse PPM

A method of computing channel capacities and error rates in multipulse pulse-position modulation (multipulse PPM) has been developed. The method makes it possible, when designing an optical PPM communication system, to determine whether and under what conditions a given multipulse PPM scheme would be more or less advantageous, relative to other candidate modulation schemes. In conventional M-ary PPM, each symbol is transmitted in a time frame that is divided into M time slots (where M is an integer >1), defining an M-symbol alphabet. A symbol is represented by transmitting a pulse (representing 1) during one of the time slots and no pulse (representing 0 ) during the other M 1 time slots. Multipulse PPM is a generalization of PPM in which pulses are transmitted during two or more of the M time slots.

Hamkins, Jon↗

Optimizing Parameters for Deep-Space Optical Communication

A paper discusses the optimization of the parameters of a high-rate, deep-space optical communication link that utilizes pulse-position modulation (PPM) and an error-correcting code (ECC). The parameters in question include the PPM order (number of pulse time slots in one symbol period), the ECC rate, and the uncoded symbol error rate. In simple terms, the optimization problem is to choose the combination of these parameters that maximizes the throughput data rate at a given bit-error-rate (BER), subject to several constraints, including limits on the average and peak power and possibly a limit on the uncoded symbol error rate. This is a complex, multidimensional optimization problem, the solution of which involves computation of channel capacities for various combinations of the parameters. The paper presents extensive theoretical analyses and numerical predictions that elucidate the many facets of the optimization problem. It shows how a nearly optimum solution can be obtained by choosing the optimum PPM order for the desired number of bits per slot and concatenating the PPM mapping with an error-correction code so that the decoded bits satisfy some BER threshold.

Moison, Bruce↗

AutoChem

AutoChem is a suite of Fortran 90 computer programs for the modeling of kinetic reaction systems. AutoChem performs automatic code generation, symbolic differentiation, analysis, and documentation. It produces a documented stand-alone system for the modeling and assimilation of atmospheric chemistry. Given databases of chemical reactions and a list of constituents defined by the user, AutoChem automatically does the following: 1. Selects the subset of reactions that involve a user-defined list of constituents and automatically prepares a document listing the reactions; 2. Constructs the ordinary differential equations (ODEs) that describe the reactions as functions of time and prepares a document containing the ODEs; 3. Symbolically differentiates the time derivatives to obtain the Jacobian and prepares a document containing the Jacobian; 4. Symbolically differentiates the Jacobian to obtain the Hessian and prepares a document containing the Hessian; and 5. Writes all the required Fortran 90 code and datafiles for a stand-alone chemical modeling and assimilation system (implementation of steps 1 through 5). Typically, the time taken for steps 1 through 5 is about 3 seconds. The modeling system includes diagnostic components that automatically analyze each ODE at run time, the relative importance of each term, time scales, and other attributes of the model.

Lary, David John↗

Parallel-Processing Equalizers for Multi-Gbps Communications

Architectures have been proposed for the design of frequency-domain least-mean-square complex equalizers that would be integral parts of parallel- processing digital receivers of multi-gigahertz radio signals and other quadrature-phase-shift-keying (QPSK) or 16-quadrature-amplitude-modulation (16-QAM) of data signals at rates of multiple gigabits per second. Equalizers as used here denotes receiver subsystems that compensate for distortions in the phase and frequency responses of the broad-band radio-frequency channels typically used to convey such signals. The proposed architectures are suitable for realization in very-large-scale integrated (VLSI) circuitry and, in particular, complementary metal oxide semiconductor (CMOS) application- specific integrated circuits (ASICs) operating at frequencies lower than modulation symbol rates. A digital receiver of the type to which the proposed architecture applies (see Figure 1) would include an analog-to-digital converter (A/D) operating at a rate, fs, of 4 samples per symbol period. To obtain the high speed necessary for sampling, the A/D and a 1:16 demultiplexer immediately following it would be constructed as GaAs integrated circuits. The parallel-processing circuitry downstream of the demultiplexer, including a demodulator followed by an equalizer, would operate at a rate of only fs/16 (in other words, at 1/4 of the symbol rate). The output from the equalizer would be four parallel streams of in-phase (I) and quadrature (Q) samples.

Gray, Andrew↗

Improved Measurement of Dispersion in an Optical Fiber

An improved method of measuring chromatic dispersion in an optical fiber or other device affords a lower (relative to prior such methods) limit of measurable dispersion. This method is a modified version of the amplitude-modulation (AM) method, which is one of the prior methods. In comparison with the other prior methods, the AM method is less complex. However, the AM method is limited to dispersion levels . 160 ps/nm and cannot be used to measure the symbol of the dispersion. In contrast, the present modified version of the AM method can be used to measure the symbol of the symbol of the dispersion and affords a measurement range from about 2 ps/nm to several thousand ps/nm with a resolution of 0.27 ps/nm or finer. The figure schematically depicts the measurement apparatus. The source of light for the measurement is a laser, the wavelength of which is monitored by an optical spectrum analyzer. A light-component analyzer amplitude-modulates the light with a scanning radio-frequency signal. The modulated light is passed through a buffer (described below) and through the device under test (e.g., an optical fiber, the dispersion of which one seeks to measure), then back to the light-component analyzer for spectrum analysis. Dispersion in the device under test gives rise to phase shifts among the carrier and the upper and lower sideband components of the modulated signal. These phase shifts affect the modulation-frequency component of the output of a photodetector exposed to the signal that emerges from the device under test. One of the effects is that this component goes to zero periodically as the modulation frequency is varied.

Huang, Shouhua↗

Jitter Controller Software

Sinusoidal jitter is produced by simply modulating a clock frequency sinusoidally with a given frequency and amplitude. But this can be expressed as phase jitter, frequency jitter, or cycle-to-cycle jitter, rms or peak, absolute units, or normalized to the base clock frequency. Jitter using other waveforms requires calculating and downloading these waveforms to an arbitrary waveform generator, and helping the user manage relationships among phase jitter crest factor, frequency jitter crest factor, and cycle-to-cycle jitter (CCJ) crest factor. Software was developed for managing these relationships, automatically configuring the generator, and saving test results documentation. Tighter management of clock jitter and jitter sensitivity is required by new codes that further extend the already high performance of space communication links, completely correcting symbol error rates higher than 10 percent, and therefore typically requiring demodulation and symbol synchronization hardware to operating at signal-to-noise ratios of less than one. To accomplish this, greater demands are also made on transmitter performance, and measurement techniques are needed to confirm performance. It was discovered early that sinusoidal jitter can be stepped on a grid such that one can connect points by constant phase jitter, constant frequency jitter, or constant cycle-cycle jitter. The tool automates adherence to a grid while also allowing adjustments off-grid. Also, the jitter can be set by the user on any dimension and the others are calculated. The calculations are all recorded, allowing the data to be rapidly plotted or re-plotted against different interpretations just by changing pointers to columns. A key advantage is taking data on a carefully controlled grid, which allowed a single data set to be post-analyzed many different ways. Another innovation was building a software tool to provide very tight coupling between the generator and the recorded data product, and the operator's worksheet. Together, these allowed the operator to sweep the jitter stimulus quickly along any of three dimensions and focus on the response of the system under test (response was jitter transfer ratio, or performance degradation to the symbol or codeword error rate). Additionally, managing multi-tone and noise waveforms automated a tedious manual process, and provided almost instantaneous decision- making control over test flow. The code was written in LabVIEW, and calls Agilent instrument drivers to write to the generator hardware.

Lansdowne, Chatwin↗

Blocking Losses With a Photon Counter

It was not known how to assess accurately losses in a communications link due to photodetector blocking, a phenomenon wherein a detector is rendered inactive for a short time after the detection of a photon. When used to detect a communications signal, blocking leads to losses relative to an ideal detector, which may be measured as a reduction in the communications rate for a given received signal power, or an increase in the signal power required to support the same communications rate. This work involved characterizing blocking losses for single detectors and arrays of detectors. Blocking may be mitigated by spreading the signal intensity over an array of detectors, reducing the count rate on any one detector. A simple approximation was made to the blocking loss as a function of the probability that a detector is unblocked at a given time, essentially treating the blocking probability as a scaling of the detection efficiency. An exact statistical characterization was derived for a single detector, and an approximation for multiple detectors. This allowed derivation of several accurate approximations to the loss. Methods were also derived to account for a rise time in recovery, and non-uniform illumination due to diffraction and atmospheric distortion of the phase front. It was assumed that the communications signal is intensity modulated and received by an array of photon-counting photodetectors. For the purpose of this analysis, it was assumed that the detectors are ideal, in that they produce a signal that allows one to reproduce the arrival times of electrons, produced either as photoelectrons or from dark noise, exactly. For single detectors, the performance of the maximum-likelihood (ML) receiver in blocking is illustrated, as well as a maximum-count (MC) receiver, that, when receiving a pulse-position-modulated (PPM) signal, selects the symbol corresponding to the slot with the largest electron count. Whereas the MC receiver saturates at high count rates, the ML receiver may not. The loss in capacity, symbol-error-rate (SER), and count-rate were numerically computed. It was shown that the capacity and symbol-error-rate losses track, whereas the count-rate loss does not generally reflect the SER or capacity loss, as the slot-statistics at the detector output are no longer Poisson. It is also shown that the MC receiver loss may be accurately predicted for dead times on the order of a slot.

Moision, Burce E.↗

Characterization of Operational Performance of Ka-Band Links in Deep Space Network

This paper presents a characterization of performance of 32-GHz Ka-band link in an operational environment. The data come from tracking of Kepler spacecraft by the NASA Deep Space Network (DSN) in the past few years. Ka-band link offers a significant signal-to-noise advantage compared to the more common X- or S-band; however, it is subject to more signal fluctuation caused by the weather. Kepler is the first mission supported by the DSN that solely rely on the higher deep space Ka-band communications link to return its high-rate science data. A well characterization of the operational performance of Kepler would benefit future Ka-band missions, especially for those operating with smaller link margin. The study examines how weather conditions at the DSN facilities (e.g., winds, clouds, rains) affect the received signal, particularly on telemetry data. It addresses questions such as how often the weather affects the link and how much degradation the link could suffer. Among the 22 Ka-band passes in 2012, heavy clouds affected one pass and two passes were impacted by high winds. The adverse weather caused at time as much as 3-dB instantaneous change in the signal to noise ratio (SNR). Estimates of degradation to the SNR as a function of wind speeds are captured based on observations. This study also quantifies the probability distribution of the variation of received signal power. With such information, future missions can better plan their link design. An optimal link design aims for just having enough margin to realize the data return with a targeted probability, with neither having too much margin that it reduces the downlink data rate nor insufficient reserve that causes frequent data outages. The study tries to provide some answers to the questions such as how much does SNR vary from one tracking pass to the next, and what is the cumulative distribution of signal fluctuation. Regarding the signal variation over many tracking passes, we found that the averaged symbol SNR (SSNR) for each pass changed by as much as 4 dB. Some variations were due to geometry such as the changing distance between spacecraft and Earth and different antenna pointing elevations. Other variations seem to be random in nature, reflecting the randomness of operational environments. Some passes were found to be quite stable, with a standard deviation of symbol SNR around 0.25 dB while others had greater variation, up to 1.4 dB. Overall, the cumulative distribution of the symbol SNR reflects that 50% of the fluctuations was less than 0.6 dB, 90% of fluctuation was within 1.6 dB and 95% within 2.2 dB. Some of the challenges in data processing, validation and modeling were captured in this paper. We observed some inconsistent measurements where operational data significantly deviate from a normal expectation. These inconsistent measurements made it hard to develop an accurate and consistent performance model, such as the degradation of signal SNR as a function of high wind. The difficulty was compounded by the fact that there were only a few Ka-band passes observed in high winds.

Pham, Timothy↗

Bit-Wise Arithmetic Coding for Data Compression

Consider the problem of compressing a uniformly quantized source. A traditional approach is to assign variable length codewords to the quantizer output symbols or groups of symbols. Here an alternate solution is proposed: assign a fixed length binary codeword to each output symbol in such a way that a zero is more likely than a one in every codeword bit position. The encoding procedure is described.

Arithmetic↗

A 5.8 GHz 1.77mW AFSK-OFDM CMOS Backscatter Transmitter for Low Power Internet of Things Applications

This paper presents an AFSK-OFDM (amplitude frequency shift keying-orthogonal frequency division multiplexing) based backscatter transmitter for Internet-of-Things (IoT) applications. The transmitter uses an array of 4 low-power direct digital frequency synthesizers (DDFSs) and DACs to transmit data using both frequency and amplitude symbols on 4 different OFDM subcarriers. The backscatter modulator is demonstrated within a 5.8 GHz wireless link using an 8-symbol OFDM library at a range of 2.7m and shown to consume 1.77 mW when operated at a symbol rate of 4MS/s (corresponds to 12 Mb/s). The modulator chip occupies 0.45mm² of silicon area.

Chang, M-C. Frank↗

A Systematic Methodology for Modeling and Attitude Control of Multi-body Space Telescopes

This paper derives a symbolic multi-body rigid nonlinear model for a space telescope using Stoneking’s implementation of Kane’s method. This symbolic nonlinear model is linearized using Matlab symbolic functions diff and inv because the analytic linearization is intractable for manual derivation. The linearized system model is then used to design the controllers using both linear quadratic regulator (LQR) and robust pole assignment methods. The closed-loop systems for the two designs are simulated using both the rigid model as well as a second model containing flexible modes. The performances of the two designs are compared based on the simulation testing results. Our conclusion is that the robust pole assignment design offers better performance than that of the LQR system in terms of actuator usage and pointing accuracy. However, the LQR approach remains an effective first design step that can inform the selection of real eigenvalues for robust pole assignment. The proposed method may be used for the modeling and controller designs for various multi-body systems.

Modeling↗

Identifying stochastic dynamics via finite expression methods

Modeling stochastic differential equations (SDEs) is crucial for understanding complex dynamical systems in various scientific fields. Recent methods often employ neural network-based models, which typically represent SDEs through a combination of deterministic and stochastic terms. However, these models usually lack interpretability and have difficulty in generalizing beyond their training domain. Here, this paper introduces the Finite Expression Method (FEX), a symbolic learning approach designed to derive interpretable mathematical representations of the deterministic component of SDEs. For the stochastic component, we integrate FEX with advanced generative modeling techniques to provide a comprehensive representation of SDEs. The numerical experiments on linear, nonlinear, and multidimensional SDEs demonstrate that FEX generalizes well beyond the training domain and delivers more accurate long-term predictions compared to neural network-based methods. The symbolic expressions identified by FEX not only improve prediction accuracy but also offer valuable scientific insights into the underlying dynamics of the systems.

Complex dynamical systems↗

Recurrent features of amplitudes in planar $\mathcal{N}$ = 4 super Yang-Mills theory

The planar three-gluon form factor for the chiral stress tensor operator in planar maximally supersymmetric Yang-Mills theory is an analog of the Higgs-to-three-gluon scattering amplitude in QCD. The amplitude (symbol) bootstrap program has provided a wealth of high-loop perturbative data about this form factor, with results up to eight loops available. The symbol of the form factor at L loops is given by words of length 2L in six letters with associated integer coefficients. In this paper, we analyze this data, describing patterns of zero coefficients and relations between coefficients. We find many sequences of words whose coefficients are given by closed-form expressions which we expect to be valid at any loop order. Moreover, motivated by our previous machine-learning analysis, we identify simple recursion relations that relate the coefficient of a word to the coefficients of particular lower-loop words. These results open an exciting door for understanding scattering amplitudes at all loop orders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

More about the lattice Hamiltonian for Adjoint QCD 2

In our earlier work [1], we introduced a lattice Hamiltonian for Adjoint QCD 2 using staggered Majorana fermions. We found the gauge invariant space of states explicitly for the gauge group SU(2) and used them for numerical calculations of observables, such as the spectrum and the expectation value of the fermion bilinear. In this paper, we carry out a more in-depth study of our lattice model, extending it to any compact and simply-connected gauge group G. We show how to find the gauge invariant space of states and use it to study various observables. We also use the lattice model to calculate the mixed ’t Hooft anomalies of Adjoint QCD 2 for arbitrary G. We show that the matrix elements of the lattice Hamiltonian can be expressed in terms of the Wigner 6j-symbols of G. For G = SU(3), we perform exact diagonalization for lattices of up to six sites and study the low-lying spectrum, the fermion bilinear condensate, and the string tension. We also show how to write the lattice strong coupling expansion for ground state energies and operator expectation values in terms of the Wigner 6j-symbols. For SU(3) we carry this out explicitly and find good agreement with the exact diagonalizations, and for SU(4) we give expansions that can be compared with future numerical studies.

confinement↗

Landau singularities of the 7-point ziggurat. Part I

We compute the leading (first-type Landau) singularities of a certain four-loop 7-point graph that is related to the 7-point “ziggurat” graph by the graphical moves familiar from equivalent circuit theory. We find perfect agreement with a subset of the “heptagon symbol alphabet” that has appeared in the context of planar Ν = 4 super-Yang-Mills theory. The remaining heptagon symbol letters are found in its subleading Landau singularities, which we address in a companion paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Cluster bootstrap for cosmological correlators

We show that cosmological wavefunction coefficients associated with n-site chain and loop graphs for a cubic scalar theory in de Sitter spacetime have symbol alphabets given by subsets of A 2n−2 and B 2n−1 cluster variables, respectively, and satisfy the associated cluster adjacency properties. The key step in proving this is identifying a precise connection between graph “tubings” that appear in the kinematic flow equation and polygon “triangulations” that encode the combinatorics of cluster compatibility. Our results imply that cosmological wavefunction coefficients in a general power-law FRW cosmology satisfy cluster adjacency to all orders in the ϵ expansion around the de Sitter limit. We use this information as bootstrap input to show that de Sitter symbols for n ≤ 4 are uniquely determined by simple physical constraints.

differential and algebraic geometry↗

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗