High-performance functional renormalization group calculations for interacting fermions

We derive a novel computational scheme for functional Renormalization Group (fRG) calculations for interacting fermions on 2D lattices. The scheme is based on the exchange parametrization fRG for the two-fermion interaction, with additional insertions of truncated partitions of unity. These insertions decouple the fermionic propagators from the exchange propagators and lead to a separation of the underlying equations. We demonstrate that this separation is numerically advantageous and may pave the way for refined, large-scale computational investigations even in the case of complex multiband systems. Furthermore, on the basis of speedup data gained from our implementation, it is shown that this new variant facilitates efficient calculations on a large number of multi-core CPUs. We apply the scheme to the $t$,$t'$ Hubbard model on a square lattice to analyze the convergence of the results with the bond length of the truncation of the partition of unity. In most parameter areas, a fast convergence can be observed. Finally, we compare to previous results in order to relate our approach to other fRG studies.Comment: 26 pages, 9 figure

The Distance of the Gamma-ray Binary 1FGL J1018.6-5856

The recently discovered gamma-ray binary 1FGL J1018.6-5856 has a proposed optical/near-infrared (OIR) counterpart 2MASS 10185560-5856459. We present Stromgren photometry of this star to investigate its photometric variability and measure the reddening and distance to the system. We find that the gamma-ray binary has E(B-V) = 1.34 +/- 0.04 and d = 5.4^+4.6_-2.1 kpc. While E(B-V) is consistent with X-ray observations of the neutral hydrogen column density, the distance is somewhat closer than some previous authors have suggested.Comment: Accepted to PAS

Visual odometry with depth-wise separable convolution and quaternion neural networks

Monocular visual odometry is a fundamental problem in computer vision and it was extensively studied in literature. The vast majority of visual odometry algorithms are based on a standard pipeline consisting in feature detection, feature matching, motion estimation and local optimization. Only recently, deep learning approaches have shown cutting-edge performance, replacing the standard pipeline with an end-to-end solution. One of the main advantages of deep learning approaches over the standard methods is the reduced inference time, that is an important requirement for the application of visual odometry in real-time. Less emphasis, however, has been placed on memory requirements and training efficiency. The memory footprint, in particular, is important for real world applications such as robot navigation or autonomous driving, where the devices have limited memory resources. In this paper we tackle both aspects introducing novel architectures based on Depth-Wise Separable Convolutional Neural Network and deep Quaternion Recurrent Convolutional Neural Network. In particular, we obtain equal or better accuracy with respect to the other state-of-the-art methods on the KITTI VO dataset with a reduction of the number of parameters and a speed-up in the inference time

Exploring Cognitive States: Methods for Detecting Physiological Temporal Fingerprints

Cognitive state detection and its relationship to observable physiologically telemetry has been utilized for many human-machine and human-cybernetic applications. This paper aims at understanding and addressing if there are unique psychophysiological patterns over time, a physiological temporal fingerprint, that is associated with specific cognitive states. This preliminary work involves commercial airline pilots completing experimental benchmark task inductions of three cognitive states: 1) Channelized Attention (CA); 2) High Workload (HW); and 3) Low Workload (LW). We approach this objective by modeling these "fingerprints" through the use of Hidden Markov Models and Entropy analysis to evaluate if the transitions over time are complex or rhythmic/predictable by nature. Our results indicate that cognitive states do have unique complexity of physiological sequences that are statistically different from other cognitive states. More specifically, CA has a significantly higher temporal psychophysiological complexity than HW and LW in EEG and ECG telemetry signals. With regards to respiration telemetry, CA has a lower temporal psychophysiological complexity than HW and LW. Through our preliminary work, addressing this unique underpinning can inform whether these underlying dynamics can be utilized to understand how humans transition between cognitive states and for improved detection of cognitive states

SAR data and field surveys combination to update rainfall-induced shallow landslide inventory

The Campania region has been recurrently hit by severe landslides in volcanoclastic deposits. The city of Naples, and in particular the Camaldoli and Agnano hills (Phlegraean Fields), also suffered several landslide crises in weathered volcanoclastic rocks as a consequence of intense rainfalls or wildfires. To identify slope failures phenomena occurred in the winter season 2019–2020 an innovative procedure has been proposed. The purpose of this procedure is to highlight areas where major land cover changes occurred within our area of study, which can be potentially related to mass movements. The amplitude of spaceborne SAR images has been exploited for the change detection analysis and the output derived from the segmentation procedure has been compared with field observations. The amplitude-based method has been already applied in the detection of landslides, but never on the event with limited extensions, such as for this application. The achieved outcomes allowed the mapping of 62 new landslides that have been used to update the current landslide inventory database. This type of information is expected to help decision-makers with land planning and risk assessment

Nonlocal properties of entangled two-photon generalized binomial states in two separate cavities

We consider entangled two-photon generalized binomial states of the electromagnetic field in two separate cavities. The nonlocal properties of this entangled field state are analyzed by studying the electric field correlations between the two cavities. A Bell's inequality violation is obtained using an appropriate dichotomic cavity operator, that is in principle measurable.Comment: 5 pages, 1 figur

Solution of the Lindblad Equation in the Kraus Representation

The so-called Lindblad equation, a typical master equation describing the dissipative quantum dynamics, is shown to be solvable for finite-level systems in a compact form without resort to writing it down as a set of equations among matrix elements. The solution is then naturally given in an operator form, known as the Kraus representation. Following a few simple examples, the general applicability of the method is clarified.Comment: 9 page

Absence of increased genomic variants in the cyanobacterium Chroococcidiopsis exposed to Mars‐like conditions outside the space station

Despite the increasing interest in using microbial‐based technologies to support human space exploration, many unknowns remain not only on bioprocesses but also on microbial survivability and genetic stability under non‐Earth conditions. Here the desert cyanobacterium Chroococcidiopsis sp. CCMEE 029 was investigated for robustness of the repair capability of DNA lesions accumulated under Mars‐like conditions (UV radiation and atmosphere) simulated in low Earth orbit using the EXPOSE‐R2 facility installed outside the International Space Station. Genomic alterations were determined in a space‐derivate of Chroococcidiopsis sp. CCMEE 029 obtained upon reactivation on Earth of the space‐exposed cells. Comparative analysis of whole‐genome sequences showed no increased variant numbers in the space‐derivate compared to triplicates of the reference strain maintained on the ground. This result advanced cyanobacteria‐based technologies to support human space exploration

Coinductive subtyping for abstract compilation of object-oriented languages into Horn formulas

In recent work we have shown how it is possible to define very precise type systems for object-oriented languages by abstractly compiling a program into a Horn formula f. Then type inference amounts to resolving a certain goal w.r.t. the coinductive (that is, the greatest) Herbrand model of f. Type systems defined in this way are idealized, since in the most interesting instantiations both the terms of the coinductive Herbrand universe and goal derivations cannot be finitely represented. However, sound and quite expressive approximations can be implemented by considering only regular terms and derivations. In doing so, it is essential to introduce a proper subtyping relation formalizing the notion of approximation between types. In this paper we study a subtyping relation on coinductive terms built on union and object type constructors. We define an interpretation of types as set of values induced by a quite intuitive relation of membership of values to types, and prove that the definition of subtyping is sound w.r.t. subset inclusion between type interpretations. The proof of soundness has allowed us to simplify the notion of contractive derivation and to discover that the previously given definition of subtyping did not cover all possible representations of the empty type

Decoherence and robustness of parity-dependent entanglement in the dynamics of a trapped ion

We study the entanglement between the 2D vibrational motion and two ground state hyperfine levels of a trapped ion, Under particular conditions this entanglement depends on the parity of the total initial vibrational quanta. We study the robustness of this quantum coherence effect with respect to the presence of non-dissipative sources of decoherence, and of an imperfect initial state preparation.Comment: 13 pages, 5 figure