Learning a Static Analyzer from Data

To be practically useful, modern static analyzers must precisely model the effect of both, statements in the programming language as well as frameworks used by the program under analysis. While important, manually addressing these challenges is difficult for at least two reasons: (i) the effects on the overall analysis can be non-trivial, and (ii) as the size and complexity of modern libraries increase, so is the number of cases the analysis must handle. In this paper we present a new, automated approach for creating static analyzers: instead of manually providing the various inference rules of the analyzer, the key idea is to learn these rules from a dataset of programs. Our method consists of two ingredients: (i) a synthesis algorithm capable of learning a candidate analyzer from a given dataset, and (ii) a counter-example guided learning procedure which generates new programs beyond those in the initial dataset, critical for discovering corner cases and ensuring the learned analysis generalizes to unseen programs. We implemented and instantiated our approach to the task of learning JavaScript static analysis rules for a subset of points-to analysis and for allocation sites analysis. These are challenging yet important problems that have received significant research attention. We show that our approach is effective: our system automatically discovered practical and useful inference rules for many cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned analyzers

Formal Verification of Neural Network Controlled Autonomous Systems

In this paper, we consider the problem of formally verifying the safety of an autonomous robot equipped with a Neural Network (NN) controller that processes LiDAR images to produce control actions. Given a workspace that is characterized by a set of polytopic obstacles, our objective is to compute the set of safe initial conditions such that a robot trajectory starting from these initial conditions is guaranteed to avoid the obstacles. Our approach is to construct a finite state abstraction of the system and use standard reachability analysis over the finite state abstraction to compute the set of the safe initial states. The first technical problem in computing the finite state abstraction is to mathematically model the imaging function that maps the robot position to the LiDAR image. To that end, we introduce the notion of imaging-adapted sets as partitions of the workspace in which the imaging function is guaranteed to be affine. We develop a polynomial-time algorithm to partition the workspace into imaging-adapted sets along with computing the corresponding affine imaging functions. Given this workspace partitioning, a discrete-time linear dynamics of the robot, and a pre-trained NN controller with Rectified Linear Unit (ReLU) nonlinearity, the second technical challenge is to analyze the behavior of the neural network. To that end, we utilize a Satisfiability Modulo Convex (SMC) encoding to enumerate all the possible segments of different ReLUs. SMC solvers then use a Boolean satisfiability solver and a convex programming solver and decompose the problem into smaller subproblems. To accelerate this process, we develop a pre-processing algorithm that could rapidly prune the space feasible ReLU segments. Finally, we demonstrate the efficiency of the proposed algorithms using numerical simulations with increasing complexity of the neural network controller

On the lease rate, convenience yield and speculative effects in the gold futures market

By examining data on the gold forward offered rate (GOFO) and lease rates over the period 1996- 2009, we conclude that the convenience yield of gold is better approximated by the lease rate than the interest-adjusted spread of Fama & French (1983). Using the latter quantity, we study the relationship between gold leasing and the level of COMEX discretionary inventory and exhibit that lease rates are negatively related to inventories. We also show that Futures prices have increasingly exceeded forward prices over the period, and this effect increases with the speculative pressure and the maturity of the contracts

Strong Interactions of Single Atoms and Photons near a Dielectric Boundary

Modern research in optical physics has achieved quantum control of strong interactions between a single atom and one photon within the setting of cavity quantum electrodynamics (cQED). However, to move beyond current proof-of-principle experiments involving one or two conventional optical cavities to more complex scalable systems that employ N >> 1 microscopic resonators requires the localization of individual atoms on distance scales < 100 nm from a resonator's surface. In this regime an atom can be strongly coupled to a single intracavity photon while at the same time experiencing significant radiative interactions with the dielectric boundaries of the resonator. Here, we report an initial step into this new regime of cQED by way of real-time detection and high-bandwidth feedback to select and monitor single Cesium atoms localized ~100 nm from the surface of a micro-toroidal optical resonator. We employ strong radiative interactions of atom and cavity field to probe atomic motion through the evanescent field of the resonator. Direct temporal and spectral measurements reveal both the significant role of Casimir-Polder attraction and the manifestly quantum nature of the atom-cavity dynamics. Our work sets the stage for trapping atoms near micro- and nano-scopic optical resonators for applications in quantum information science, including the creation of scalable quantum networks composed of many atom-cavity systems that coherently interact via coherent exchanges of single photons.Comment: 8 pages, 5 figures, Supplemental Information included as ancillary fil

Quantum computing implementations with neutral particles

We review quantum information processing with cold neutral particles, that is, atoms or polar molecules. First, we analyze the best suited degrees of freedom of these particles for storing quantum information, and then we discuss both single- and two-qubit gate implementations. We focus our discussion mainly on collisional quantum gates, which are best suited for atom-chip-like devices, as well as on gate proposals conceived for optical lattices. Additionally, we analyze schemes both for cold atoms confined in optical cavities and hybrid approaches to entanglement generation, and we show how optimal control theory might be a powerful tool to enhance the speed up of the gate operations as well as to achieve high fidelities required for fault tolerant quantum computation.Comment: 19 pages, 12 figures; From the issue entitled "Special Issue on Neutral Particles

Prostate cancer in BRCA2 germline mutation carriers is associated with poorer prognosis

BACKGROUND: The germline BRCA2 mutation is associated with increased prostate cancer (PrCa) risk. We have assessed survival in young PrCa cases with a germline mutation in BRCA2 and investigated loss of heterozygosity at BRCA2 in their tumours. METHODS: Two cohorts were compared: one was a group with young-onset PrCa, tested for germline BRCA2 mutations (6 of 263 cases had a germline BRAC2 mutation), and the second was a validation set consisting of a clinical set from Manchester of known BRCA2 mutuation carriers (15 cases) with PrCa. Survival data were compared with a control series of patients in a single clinic as determined by Kaplan-Meier estimates. Loss of heterozygosity was tested for in the DNA of tumour tissue of the young-onset group by typing four microsatellite markers that flanked the BRCA2 gene, followed by sequencing. RESULTS: Median survival of all PrCa cases with a germline BRCA2 mutation was shorter at 4.8 years than was survival in controls at 8.5 years (P = 0.002). Loss of heterozygosity was found in the majority of tumours of BRCA2 mutation carriers. Multivariate analysis confirmed that the poorer survival of PrCa in BRCA2 mutation carriers is associated with the germline BRCA2 mutation per se. CONCLUSION: BRCA2 germline mutation is an independent prognostic factor for survival in PrCa. Such patients should not be managed with active surveillance as they have more aggressive disease. British Journal of Cancer (2010) 103, 918-924. doi:10.1038/sj.bjc.6605822 www.bjcancer.com Published online 24 August 2010 (C) 2010 Cancer Research U

Functional MRI of Auditory Responses in the Zebra Finch Forebrain Reveals a Hierarchical Organisation Based on Signal Strength but Not Selectivity

BACKGROUND: Male songbirds learn their songs from an adult tutor when they are young. A network of brain nuclei known as the 'song system' is the likely neural substrate for sensorimotor learning and production of song, but the neural networks involved in processing the auditory feedback signals necessary for song learning and maintenance remain unknown. Determining which regions show preferential responsiveness to the bird's own song (BOS) is of great importance because neurons sensitive to self-generated vocalisations could mediate this auditory feedback process. Neurons in the song nuclei and in a secondary auditory area, the caudal medial mesopallium (CMM), show selective responses to the BOS. The aim of the present study is to investigate the emergence of BOS selectivity within the network of primary auditory sub-regions in the avian pallium. METHODS AND FINDINGS: Using blood oxygen level-dependent (BOLD) fMRI, we investigated neural responsiveness to natural and manipulated self-generated vocalisations and compared the selectivity for BOS and conspecific song in different sub-regions of the thalamo-recipient area Field L. Zebra finch males were exposed to conspecific song, BOS and to synthetic variations on BOS that differed in spectro-temporal and/or modulation phase structure. We found significant differences in the strength of BOLD responses between regions L2a, L2b and CMM, but no inter-stimuli differences within regions. In particular, we have shown that the overall signal strength to song and synthetic variations thereof was different within two sub-regions of Field L2: zone L2a was significantly more activated compared to the adjacent sub-region L2b. CONCLUSIONS: Based on our results we suggest that unlike nuclei in the song system, sub-regions in the primary auditory pallium do not show selectivity for the BOS, but appear to show different levels of activity with exposure to any sound according to their place in the auditory processing stream

Micromechanical Properties of Injection-Molded Starch–Wood Particle Composites

The micromechanical properties of injection molded starch–wood particle composites were investigated as a function of particle content and humidity conditions. The composite materials were characterized by scanning electron microscopy and X-ray diffraction methods. The microhardness of the composites was shown to increase notably with the concentration of the wood particles. In addition,creep behavior under the indenter and temperature dependence were evaluated in terms of the independent contribution of the starch matrix and the wood microparticles to the hardness value. The influence of drying time on the density and weight uptake of the injection-molded composites was highlighted. The results revealed the role of the mechanism of water evaporation, showing that the dependence of water uptake and temperature was greater for the starch–wood composites than for the pure starch sample. Experiments performed during the drying process at 70°C indicated that the wood in the starch composites did not prevent water loss from the samples.Peer reviewe

Encoding of Temporal Information by Timing, Rate, and Place in Cat Auditory Cortex

A central goal in auditory neuroscience is to understand the neural coding of species-specific communication and human speech sounds. Low-rate repetitive sounds are elemental features of communication sounds, and core auditory cortical regions have been implicated in processing these information-bearing elements. Repetitive sounds could be encoded by at least three neural response properties: 1) the event-locked spike-timing precision, 2) the mean firing rate, and 3) the interspike interval (ISI). To determine how well these response aspects capture information about the repetition rate stimulus, we measured local group responses of cortical neurons in cat anterior auditory field (AAF) to click trains and calculated their mutual information based on these different codes. ISIs of the multiunit responses carried substantially higher information about low repetition rates than either spike-timing precision or firing rate. Combining firing rate and ISI codes was synergistic and captured modestly more repetition information. Spatial distribution analyses showed distinct local clustering properties for each encoding scheme for repetition information indicative of a place code. Diversity in local processing emphasis and distribution of different repetition rate codes across AAF may give rise to concurrent feed-forward processing streams that contribute differently to higher-order sound analysis