scispace - formally typeset
Search or ask a question

Showing papers on "Randomness published in 2021"


Journal ArticleDOI
TL;DR: In this paper, a generalized probability density evolution method (GPDEM) was proposed to investigate the system reliability of complex slopes with consideration to uncertainty in multiple slope parameters and in ground motions.

72 citations


Posted Content
TL;DR: In this article, the authors numerically study both the avalanche instability and many-body resonances in strongly-disordered spin chains exhibiting MBL and identify some landmarks within the MBL regime.
Abstract: We numerically study both the avalanche instability and many-body resonances in strongly-disordered spin chains exhibiting many-body localization (MBL). We distinguish between a finite-size/time MBL regime, and the asymptotic MBL phase, and identify some "landmarks" within the MBL regime. Our first landmark is an estimate of where the MBL phase becomes unstable to avalanches, obtained by measuring the slowest relaxation rate of a finite chain coupled to an infinite bath at one end. Our estimates indicate that the actual MBL-to-thermal phase transition, in infinite-length systems, occurs much deeper in the MBL regime than has been suggested by most previous studies. Our other landmarks involve system-wide resonances. We find that the effective matrix elements producing eigenstates with system-wide resonances are enormously broadly distributed. This means that the onset of such resonances in typical samples occurs quite deep in the MBL regime, and the first such resonances typically involve rare pairs of eigenstates that are farther apart in energy than the minimum gap. Thus we find that the resonance properties define two landmarks that divide the MBL regime in to three subregimes: (i) at strongest disorder, typical samples do not have any eigenstates that are involved in system-wide many-body resonances; (ii) there is a substantial intermediate regime where typical samples do have such resonances, but the pair of eigenstates with the minimum spectral gap does not; and (iii) in the weaker randomness regime, the minimum gap is involved in a many-body resonance and thus subject to level repulsion. Nevertheless, even in this third subregime, all but a vanishing fraction of eigenstates remain non-resonant and the system thus still appears MBL in many respects. Based on our estimates of the location of the avalanche instability, it might be that the MBL phase is only part of subregime (i).

56 citations


Journal ArticleDOI
TL;DR: An overview of this exciting new line of research, including brief introductions to RandNLA and DPPs, as well as applications of D PPs to classical linear algebra tasks such as least squares regression, low-rank approximation and the Nystrom method are provided.
Abstract: Randomized Numerical Linear Algebra (RandNLA) uses randomness to develop improved algorithms for matrix problems that arise in scientific computing, data science, machine learning, etc. Determinantal Point Processes (DPPs), a seemingly unrelated topic in pure and applied mathematics, is a class of stochastic point processes with probability distribution characterized by sub-determinants of a kernel matrix. Recent work has uncovered deep and fruitful connections between DPPs and RandNLA which lead to new guarantees and improved algorithms that are of interest to both areas. We provide an overview of this exciting new line of research, including brief introductions to RandNLA and DPPs, as well as applications of DPPs to classical linear algebra tasks such as least squares regression, low-rank approximation and the Nystrom method. For example, random sampling with a DPP leads to new kinds of unbiased estimators for least squares, enabling more refined statistical and inferential understanding of these algorithms; a DPP is, in some sense, an optimal randomized algorithm for the Nystrom method; and a RandNLA technique called leverage score sampling can be derived as the marginal distribution of a DPP. We also discuss recent algorithmic developments, illustrating that, while not quite as efficient as standard RandNLA techniques, DPP-based algorithms are only moderately more expensive.

51 citations


Journal ArticleDOI
TL;DR: Diagonalizing the transform matrix of the map is given, giving the explicit formulation of any iteration of the generalized Cat map and its real graph (cycle) structure in any binary arithmetic domain is disclosed.
Abstract: Chaotic dynamics is an important source for generating pseudorandom binary sequences (PRBS) Much efforts have been devoted to obtaining period distribution of the generalized discrete Arnold's Cat map in various domains using all kinds of theoretical methods, including Hensel's lifting approach Diagonalizing the transform matrix of the map, this paper gives the explicit formulation of any iteration of the generalized Cat map Then, its real graph (cycle) structure in any binary arithmetic domain is disclosed The subtle rules on how the cycles (itself and its distribution) change with the arithmetic precision e are elaborately investigated and proved The regular and beautiful patterns of Cat map demonstrated in a computer adopting fixed-point arithmetics are rigorously proved and experimentally verified The results can serve as a benchmark for studying the dynamics of the variants of the Cat map in any domain In addition, the used methodology can be used to evaluate randomness of PRBS generated by iterating any other maps

49 citations


Journal ArticleDOI
TL;DR: In this paper, a Pseudo-random number generator (PRNG) with this architecture is devised to generate random bit sequences from secret keys, which are tested with NIST SP 800-22 statistical test suite and were shown to have good randomness.
Abstract: Transmission of the information in any form requires security. Security protocols used for communication rely on the use of random numbers. Pseudo-random numbers are required with good statistical properties and efficiency. The use of a single chaotic map may not produce enough randomness. The turbulence is padded into the existing map to improve its chaotic behaviour and increase the periodicity. A Pseudo-random number generator (PRNG) with this architecture is devised to generate random bit sequences from secret keys. The statistical properties of newly constructed PRNG are tested with NIST SP 800–22 statistical test suite and were shown to have good randomness. To ensure its usability in cryptographic applications, we analysed the size of its key space, key sensitivity, and performance speed. The test results show that the newly designed PRNG has a 3.6% increase in key space and a 5% increase in its performance speed compared to existing chaotic PRNGs. The novel PRNG with faster performance is found suitable for lightweight cryptographic applications.

46 citations


Journal ArticleDOI
TL;DR: A device-independent spot-checking protocol which uses only uniform bits as input that will allow for greater trust in public sources of randomness, such as randomness beacons, and the protocols may one day enable high-quality sources of private randomness as the device footprint shrinks.
Abstract: With the growing availability of experimental loophole-free Bell tests1–5, it has become possible to implement a new class of device-independent random number generators whose output can be certified6,7 to be uniformly random without requiring a detailed model of the quantum devices used8–10. However, all these experiments require many input bits to certify a small number of output bits, and it is an outstanding challenge to develop a system that generates more randomness than is consumed. Here we devise a device-independent spot-checking protocol that consumes only uniform bits without requiring any additional bits with a specific bias. Implemented with a photonic loophole-free Bell test, we can produce 24% more certified output bits (1,181,264,237) than consumed input bits (953,301,640). The experiment ran for 91.0 h, creating randomness at an average rate of 3,606 bits s–1 with a soundness error bounded by 5.7 × 10−7 in the presence of classical side information. Our system allows for greater trust in public sources of randomness, such as randomness beacons11, and may one day enable high-quality private sources of randomness as the device footprint shrinks. Device-independent randomness expansion is demonstrated in an experiment that is secure in the presence of a classical eavesdropper who does not share any entanglement with the setup.

45 citations


Journal ArticleDOI
TL;DR: In this article, the authors proposed an algorithm to generate the unified dataset for the general and some specific applications system models in WSNs, and the results produced by their algorithm reflect the pseudo-randomness and can efficiently regenerate through seed value for validation.

44 citations


Journal ArticleDOI
TL;DR: In this paper, a general three-dimensional discrete memristor-based (3D-DM) map model was presented, which can enhance the chaos complexity of existing discrete maps and display hyperchaos.
Abstract: With the nonlinearity and plasticity, memristors are widely used as nonlinear devices for chaotic oscillations or as biological synapses for neuromorphic computations. But discrete memristors and their coupling maps have not received much attention, yet. Using a discrete memristor model, this paper presents a general three-dimensional discrete memristor-based (3D-DM) map model. By coupling the discrete memristor with four two-dimensional discrete maps, four examples of 3D-DM maps with no or infinitely many fixed points are generated. We simulate the coupling coefficient-depended and memristor initial-boosted bifurcation behaviors of these 3D-DM maps using numerical measures. The results demonstrate that the memristor can enhance the chaos complexity of existing discrete maps and its coupling maps can display hyperchaos. Furthermore, a hardware platform is developed to implement the 3D-DM maps and the acquired hyperchaotic sequences have high randomness. Particularly, these hyperchaotic sequences can be applied to the auxiliary classifier generative adversarial nets (AC-GANs) for greatly improving the discriminator accuracy.

41 citations


Journal ArticleDOI
TL;DR: In this paper, a two-dimensional parametric polynomial chaotic system (2D-PPCS) is proposed, which can yield many 2D chaotic maps with different exponent coefficient settings.
Abstract: When used in engineering applications, most existing chaotic systems may have many disadvantages, including discontinuous chaotic parameter ranges, lack of robust chaos, and easy occurrence of chaos degradation. In this article, we propose a two-dimensional (2-D) parametric polynomial chaotic system (2D-PPCS) as a general system that can yield many 2-D chaotic maps with different exponent coefficient settings. The 2D-PPCS initializes two parametric polynomials and then applies modular chaotification to the polynomials. Setting different control parameters allows the 2D-PPCS to customize its Lyapunov exponents in order to obtain robust chaos and behaviors with desired complexity. Our theoretical analysis demonstrates the robust chaotic behavior of the 2D-PPCS. Two illustrative examples are provided and tested based on numeral experiments to verify the effectiveness of the 2D-PPCS. A chaos-based pseudorandom number generator is also developed to illustrate the applications of the 2D-PPCS. The experimental results demonstrate that these examples of the 2D-PPCS can achieve robust and desired chaos, have better performance, and generate higher randomness pseudorandom numbers than some representative 2-D chaotic maps.

34 citations


Journal ArticleDOI
TL;DR: A TRNG whose randomness is generated by the oscillation of self-timed rings (STRs) and accurately extracted by a jitter-latch structure is designed and shows excellent performance in randomness, robustness, and portability, and the throughput reaches 100 Mbps.
Abstract: Under the requirement of highly reliable encryption, the design of true random number generators (TRNGs) based on field-programmable gate arrays (FPGAs) is receiving increased attention. Although TRNGs based on ring oscillators (ROs) and phase-locked loops (PLLs) have the advantages of small resource overhead and high throughput, there are problems such as instability of randomness and poor portability. To improve the randomness, portability, and throughput of a random number generator, we design a TRNG whose randomness is generated by the oscillation of self-timed rings (STRs) and accurately extracted by a jitter-latch structure. The portability of the structure is verified by electronic design automation (EDA) tools. Under the condition of 0°C–80°C ambient temperature and 1.0 ± 0.1 V output voltage, the proposed structure is tested many times on Xilinx Spartan-6 and Virtex-6 FPGAs with an automatic routing mode. Theoretical analysis shows that this method can effectively improve the coverage of jitter and reduce the migration phenomenon. Experimental results show excellent performance in randomness, robustness, and portability, and the throughput reaches 100 Mbps.

33 citations


Journal ArticleDOI
TL;DR: In this paper, the authors present a review of the existing online methods for testing the two hypotheses of randomness and exchangeability, focusing on the online mode of testing, when the observations arrive sequentially.
Abstract: The hypothesis of randomness is fundamental in statistical machine learning and in many areas of nonparametric statistics; it says that the observations are assumed to be independent and coming from the same unknown probability distribution. This hypothesis is close, in certain respects, to the hypothesis of exchangeability, which postulates that the distribution of the observations is invariant with respect to their permutations. This paper reviews known methods of testing the two hypotheses concentrating on the online mode of testing, when the observations arrive sequentially. All known online methods for testing these hypotheses are based on conformal martingales, which are defined and studied in detail. An important variety of online testing is change detection, where the use of conformal martingales leads to conformal versions of the CUSUM and Shiryaev–Roberts procedures; these versions work in the nonparametric setting where the data is assumed IID according to a completely unknown distribution before the change. The paper emphasizes conceptual and practical aspects and states two kinds of results. Validity results limit the probability of a false alarm or, in the case of change detection, the frequency of false alarms for various procedures based on conformal martingales. Efficiency results establish connections between randomness, exchangeability, and conformal martingales.

Journal ArticleDOI
TL;DR: This work presents an experiment that demonstrates device-independent randomness expansion (DIRNE), i.e., where the generated randomness surpasses that consumed and established security against quantum adversaries.
Abstract: The ability to produce random numbers that are unknown to any outside party is crucial for many applications. Device-independent randomness generation1–4 does not require trusted devices and therefore provides strong guarantees of the security of the output, but it comes at the price of requiring the violation of a Bell inequality for implementation. A further challenge is to make the bounds in the security proofs tight enough to allow randomness expansion with contemporary technology. Although randomness has been generated in recent experiments5–9, the amount of randomness consumed in doing so has been too high to certify expansion based on existing theory. Here we present an experiment that demonstrates device-independent randomness expansion1–3,10–15. By developing a Bell test setup with a single-photon detection efficiency of around 84% and by using a spot-checking protocol, we achieve a net gain of 2.57 × 108 certified bits with a soundness error of 3.09 × 10−12. The experiment ran for 19.2 h, which corresponds to an average rate of randomness generation of 13,527 bits per second. By developing the entropy accumulation theorem4,16,17, we establish security against quantum adversaries. We anticipate that this work will lead to further improvements that push device-independence towards commercial viability. Device-independent randomness expansion is demonstrated in an experiment that is secure against quantum adversaries as established by the entropy accumulation theorem.

Journal ArticleDOI
TL;DR: The highly chaotic nature of hybrid chaos maps and neural network is combined to build a random number generator for cryptographic applications and a custom neural network with a user-defined layer transfer function is built to increase the generator’s randomness.
Abstract: Cryptography is a method for secure communication by hiding information with secret keys so that only authorised users can read and process it. Efficient random sequence generators provide robust cipher design for cryptographic applications; further, these sequences are used for data encryption. In this paper, the highly chaotic nature of hybrid chaos maps and neural network is combined to build a random number generator for cryptographic applications. A custom neural network with a user-defined layer transfer function is built to increase the generator’s randomness. In this work, the two-hybrid chaotic map’s control parameters and iteration value are designed as a layer transfer function to obtain high randomness. Colour image encryption is performed with the extracted sequences and deoxyribonucleic acid encoding technique. Various tests like NIST, attractor test and correlation are applied to the generator to show the degree of randomness. Simulation analysis such as keyspace, key sensitivity, statistical, differential analysis, and chosen-plaintext attack shows the encryption algorithm’s strength.

Journal ArticleDOI
TL;DR: In this article, an explicit mixture random field (MRF) model is proposed to characterize and reconstruct multi-phase stochastic material property and microstructure simultaneously, which is shown to have ultra-high computational efficiency and only requires minimal imaging and property input data.

Journal ArticleDOI
TL;DR: Recent literature examples of stochastic processes in single-entity electrochemistry are reviewed, highlighting strategies for interpreting Stochasticity, contrasting them with macroscale measurements, and describing the insights generated.

Journal ArticleDOI
TL;DR: This paper considers contrasts between stochastic seeding strategies and analyze nonparametric estimators adapted from policy evaluation and importance sampling, and uses simulations on real networks to show that the proposed estimators and designs can substantially increase precision while yielding valid inference.
Abstract: When trying to maximize the adoption of a behavior in a population connected by a social network, it is common to strategize about where in the network to seed the behavior, often with an element o...

Journal ArticleDOI
TL;DR: This paper investigates the application of an ensemble approach based on deep belief networks for short-term traffic flow forecasting and indicates that the proposed approach achieves significant performance improvement over the single DBN and other selected methods.
Abstract: Transportation services play an increasingly significant role for people's daily lives and bring a lot of benefits to individuals and economic development. The randomness and volatility of traffic flows, however, constrains the effective provision of transportation services to a certain extent. Precise traffic flow forecasting becomes the key and primary task to realize the stability of intelligent transport systems and ensure efficient scheduling of traffic. This paper investigates the application of an ensemble approach based on deep belief networks for short-term traffic flow forecasting. Traffic flow data, collected from the real world, is decomposed into several Intrinsic Mode Functions (IMFs) and a residue with EEMD (Ensemble Empirical Mode Decomposition). Then, for each component, the essential feature subset is extracted by the mRMR (minimum Redundancy Maximum Relevance Feature Selection) method considering weather conditions and day properties. Furthermore, each component is trained by DBN (Deep belief networks) and their forecasting results are summed up as the output of the ensemble model at last. Results indicate that the proposed approach achieves significant performance improvement over the single DBN and other selected methods.

Journal ArticleDOI
TL;DR: In this paper, a method to approximate the conditional entropy minimized over a certain set of quantum states is proposed. But this method is only applied to the setting of device-independent randomness generation and quantum key distribution.
Abstract: The rates of quantum cryptographic protocols are usually expressed in terms of a conditional entropy minimized over a certain set of quantum states. In particular, in the device-independent setting, the minimization is over all the quantum states jointly held by the adversary and the parties that are consistent with the statistics that are seen by the parties. Here, we introduce a method to approximate such entropic quantities. Applied to the setting of device-independent randomness generation and quantum key distribution, we obtain improvements on protocol rates in various settings. In particular, we find new upper bounds on the minimal global detection efficiency required to perform device-independent quantum key distribution without additional preprocessing. Furthermore, we show that our construction can be readily combined with the entropy accumulation theorem in order to establish full finite-key security proofs for these protocols. Simple lower bounds on the rates of device-independent quantum information protocols can often overestimate the power of the eavesdropping party. Here, the authors use new entropic quantities defined as semidefinite programs to improve bounds in several regimes without expensive computational resources

Journal ArticleDOI
Xujia Zhu1, Bruno Sudret1
TL;DR: This paper proposes to use the generalized lambda model to emulate the response distribution of stochastic simulators and confirms the convergence of the approach for estimating the sensitivity indices even with the presence of strong heteroscedasticity and small signal-to-noise ratio.

Journal ArticleDOI
TL;DR: In this article, a class of gapless topological phases, protected by symmetry and robust to strong randomness, are uncovered. And they can be realized in nonequilibrium states stabilized by many-body localization.
Abstract: Topological phases represent a pillar of modern condensed matter physics. While gapped topological systems have been studied extensively, gapless topological materials represent an exciting, largely unexplored area. Here, the authors show that symmetry can enrich random quantum critical points and phases. They uncover a class of gapless topological phases, protected by symmetry and robust to strong randomness. Some of these phases can be realized in nonequilibrium states stabilized by many-body localization. They also appear naturally in periodically driven (Floquet) systems.

Journal ArticleDOI
TL;DR: This article considers a point-to-point anti-eavesdropping system in which a reconfigurable intelligent surface is used to enable the secure transmission from a multi-antenna transmitter to a multi"-antenna legitimate receiver", and proposes a security approach by using the reflection at the RIS as multiplicative randomness against the wiretapper.
Abstract: The reconfigurable intelligent surface (RIS) is envisioned to create ultra-secure wireless networks. Previous works on the RIS-assisted security provisioning techniques assumed wiretap channel information at the transmitter, which is practically unavailable in a passive eavesdropping scenario. In this article, we consider a point-to-point anti-eavesdropping system in which a RIS is used to enable the secure transmission from a multi-antenna transmitter to a multi-antenna legitimate receiver. A passive eavesdropper, whose channel state information is completely unknown, attempts to decode the secret messages. We propose a security approach by using the reflection at the RIS as multiplicative randomness against the wiretapper. Specifically, the reflection coefficients in terms of amplitude and phase are updated in each transmission and kept private at the RIS. Through the reflection designs, the effective channel matrix is diagonalized at the legitimate receiver. In contrast, the eavesdropper receives coupled signals with the weights of the randomness at RIS. The main contributions of this article are three reflection designs and correspondingly three secure transmission schemes, which fulfills diverse requirements of the balance amongst performance metrics including the degrees of randomness, spectral efficiency, and reliability. The main benefits of the proposed secure transmission schemes are four-fold. First, the transmitter does not need to know the eavesdropper’s channel states. Second, closed-form solutions for the reflection coefficients are provided. Third, the legitimate receiver has a linear decoding complexity. Fourth, the unauthorized wiretapper is unable to cancel out the multiplicative randomness and thus cannot extract much useful information. Numerical results show that exploiting the RIS as a source of multiplicative randomness provides a new perspective to improve the security of the wireless networks.

Journal ArticleDOI
TL;DR: In this article, the authors show that some tripartite quantum correlations are inexplicable by any causal theory involving bipartite nonclassical common causes and unlimited shared randomness, which constitutes a device-independent proof that nature's nonlocality is fundamentally at least tri-partite in every conceivable physical theory.
Abstract: We show that some tripartite quantum correlations are inexplicable by any causal theory involving bipartite nonclassical common causes and unlimited shared randomness. This constitutes a device-independent proof that nature's nonlocality is fundamentally at least tripartite in every conceivable physical theory---no matter how exotic. To formalize this claim, we are compelled to substitute Svetlichny's historical definition of genuine tripartite nonlocality with a novel theory-agnostic definition tied to the framework of local operations and shared randomness. A companion article by Coiteux-Roy et al. generalizes these concepts to any $N\ensuremath{\ge}3$ number of parties, providing experimentally amenable device-independent inequality constraints along with quantum correlations violating them, thereby certifying that nature's nonlocality must be boundlessly multipartite.

Journal ArticleDOI
Dongheon Yoo1, Youngjin Jo1, Seung-Woo Nam1, Chun Chen1, Byoungho Lee1 
TL;DR: In this article, a computer-generated hologram (CGH) optimization technique that can control the randomness of the reconstructed phase was introduced, which significantly affects the eyebox size and depth of field in holographic near-eye displays.
Abstract: In this Letter, we introduce a computer-generated hologram (CGH) optimization technique that can control the randomness of the reconstructed phase. The phase randomness significantly affects the eyebox size and depth of field in holographic near-eye displays. Our proposal is to synthesize the CGH through the sum of two terms computed from the target scene with a random phase. We set a weighting pattern for summation as the optimization variable, which enables the CGH to reflect the random phase during optimization. We evaluate the proposed algorithm on single-depth and multi-depth contents, and the performance is validated via simulations and experiments.

Journal ArticleDOI
20 Jan 2021
TL;DR: In this paper, the authors studied the problem of goodness-of-fit and independence testing of discrete distributions in a setting where samples are distributed across multiple users, and proposed simple, sample-optimal, and communication-efficient protocols for these two questions in the noninteractive setting, where users may or may not share a common random seed.
Abstract: We study goodness-of-fit and independence testing of discrete distributions in a setting where samples are distributed across multiple users. The users wish to preserve the privacy of their data while enabling a central server to perform the tests. Under the notion of local differential privacy, we propose simple, sample-optimal, and communication-efficient protocols for these two questions in the noninteractive setting, where in addition users may or may not share a common random seed. In particular, we show that the availability of shared (public) randomness greatly reduces the sample complexity. Underlying our public-coin protocols are privacy-preserving mappings which, when applied to the samples, minimally contract the distance between their respective probability distributions.

Proceedings ArticleDOI
01 Jan 2021
TL;DR: This design allows RandRunner to tolerate adversarial or failed leaders while guaranteeing safety and liveness of the protocol despite possible periods of asynchrony, and avoids the necessity of a BFT consensus protocol and its accompanying high complexity and communication overhead.

Journal ArticleDOI
TL;DR: The analysis reveals important differences between the optimal sizing of standard queueing systems and that of systems where servers, upon service completion, randomly join any one of the queues in the system.
Abstract: We consider the problem of optimal fleet sizing in a vehicle sharing system. Vehicles are available for short-term rental and are accessible from multiple locations. A vehicle rented at one locatio...

Journal ArticleDOI
TL;DR: In this paper, the synchronization of a class of nonlinear singularly perturbed complex networks (SPCNs) with semi-Markov jump topologies and impulsive effects is studied.
Abstract: Synchronization of a class of nonlinear singularly perturbed complex networks (SPCNs) with semi-Markov jump topologies and impulsive effects is studied in this article. A complex network with a kind of random switching topologies is considered, where the randomness is depicted by a semi-Markov chain. A method is put forward to obtain the upper bound of singularly perturbed parameter (SPP) with different coupling strengths, and the concept of average impulsive interval is introduced to regulate the frequency of impulses. By utilizing the SPP-dependent semi-Markovian Lyapunov function, some sufficient conditions are derived for achieving synchronization of an SPCN. The effectiveness and validity of the proposed synchronization strategy are verified by two numerical examples.

Journal ArticleDOI
TL;DR: In this article, the authors consider fuzzy stochastic differential equations (FSDEs) driven by fractional Brownian motion (fBm), which can be applied in hybrid real-world systems, including randomness, fuzziness and long-range dependence.
Abstract: In this paper, we consider fuzzy stochastic differential equations (FSDEs) driven by fractional Brownian motion (fBm). These equations can be applied in hybrid real-world systems, including randomness, fuzziness and long-range dependence. Under some assumptions on the coefficients, we follow an approximation method to the fractional stochastic integral to study the existence and uniqueness of the solutions. As an example, in financial models, we obtain the solution for an equation with linear coefficients.

Journal ArticleDOI
TL;DR: The article proposes the imitation learning framework for training such an agent, where the agent will interact with an expert built based on the mixed-integer program to learn its optimal policy, and therefore significantly improve the training efficiency compared with exploration-dominant reinforcement learning (RL) methods.
Abstract: Self-healing capability is a critical factor for a resilient distribution system, which requires intelligent agents to automatically perform service restoration online, including network reconfiguration and reactive power dispatch. The paper proposes the imitation learning framework for training such an agent, where the agent will interact with an expert built based on the mixed-integer program to learn its optimal policy, and therefore significantly improve the training efficiency compared with exploration-dominant reinforcement learning methods. This significantly improved training efficiency makes the training problem under $N-k$ scenarios tractable. A hybrid policy network is proposed to handle tie-line operations and reactive power dispatch simultaneously to further improve the restoration performance. The 33-bus and 119-bus systems with N-k disturbances are employed to conduct the training. The results indicate that the proposed method outperforms traditional reinforcement learning algorithms such as the deep-Q network.

Journal ArticleDOI
TL;DR: The work presented herein describes the design and the validation of a digital True Random Number Generator for cryptographically secure applications on Field Programmable Gate Array, derived from the Fibonacci-Galois Ring Oscillator, supporting throughput up to 400 Mbps.
Abstract: Random numbers are widely employed in cryptography and security applications. If the generation process is weak, the whole chain of security can be compromised: these weaknesses could be exploited by an attacker to retrieve the information, breaking even the most robust implementation of a cipher. Due to their intrinsic close relationship with analogue parameters of the circuit, True Random Number Generators are usually tailored on specific silicon technology and are not easily scalable on programmable hardware, without affecting their entropy. On the other hand, programmable hardware and programmable System on Chip are gaining large adoption rate, also in security critical application, where high quality random number generation is mandatory. The work presented herein describes the design and the validation of a digital True Random Number Generator for cryptographically secure applications on Field Programmable Gate Array. After a preliminary study of literature and standards specifying requirements for random number generation, the design flow is illustrated, from specifications definition to the synthesis phase. Several solutions have been studied to assess their performances on a Field Programmable Gate Array device, with the aim to select the highest performance architecture. The proposed designs have been tested and validated, employing official test suites released by NIST standardization body, assessing the independence from the place and route and the randomness degree of the generated output. An architecture derived from the Fibonacci-Galois Ring Oscillator has been selected and synthesized on Intel Stratix IV, supporting throughput up to 400 Mbps. The achieved entropy in the best configuration is greater than 0.995.