IA Scholar Query: Uniform Normalisation beyond Orthogonality.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgFri, 30 Sep 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Using Defect Prediction to Improve the Bug Detection Capability of Search-Based Software Testing
https://scholar.archive.org/work/rky5vhwpebglxnnvodfp3vraza
Software systems have a direct and indirect impact on the lives of humans, animals and other living things. They need to be tested thoroughly to minimise software failures. Automated test generators, like search-based software testing (SBST) techniques, replace the tedious and expensive task of manually writing tests. Despite achieving high code coverage, current SBST techniques perform rather poorly in terms of detecting bugs. This thesis proposes novel SBST approaches guided by defect prediction and demonstrates that to effectively and efficiently detect bugs SBST needs to focus test generation more on likely buggy areas in programs guided by defect prediction.BALASURIYAGE ANJANA VISULA PERERAwork_rky5vhwpebglxnnvodfp3vrazaFri, 30 Sep 2022 00:00:00 GMTState-dependent Trotter Limits and their approximations
https://scholar.archive.org/work/m6bcrav6ard4xmpjetr5c3urmu
The Trotter product formula is a key instrument in numerical simulations of quantum systems. However, computers cannot deal with continuous degrees of freedom, such as the position of particles in molecules, or the amplitude of electromagnetic fields. It is therefore necessary to discretize these variables to make them amenable to digital simulations. Here, we give sufficient conditions to conclude the validity of this approximate discretized physics. Essentially, it depends on the state-dependent Trotter error, for which we establish explicit bounds that are also of independent interest.Daniel Burgarth, Niklas Galke, Alexander Hahn, Lauritz van Luijkwork_m6bcrav6ard4xmpjetr5c3urmuThu, 29 Sep 2022 00:00:00 GMTThe Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument
https://scholar.archive.org/work/5tsesdige5h2rpwftsyeyoo64e
We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4-m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the Universe with the Baryon Acoustic Oscillation technique and the growth rate of structure with Redshift Space Distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near UV to near infrared (3600 to 9800 Angstrom) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline's algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project's requirements for redshift performance, with high efficiency and a purity greater than 99 percent for all target classes.J. Guy, S. Bailey, A. Kremin, Shadab Alam, C. Allende Prieto, S. BenZvi, A. S. Bolton, D. Brooks, E. Chaussidon, A. P. Cooper, K. Dawson, A. de la Macorra, A. Dey, Biprateep Dey, G. Dhungana, D. J. Eisenstein, A. Font-Ribera, J. E. Forero-Romero, E. Gaztañaga, S. Gontcho A Gontcho, D. Green, K. Honscheid, M. Ishak, R. Kehoe, D. Kirkby, T. Kisner, Sergey E. Koposov, Ting-Wen Lan, M. Landriau, L. Le Guillou, Michael E. Levi, C. Magneville, Christopher J. Manser, P. Martini, Aaron M. Meisner, R. Miquel, J. Moustakas, Adam D. Myers, Jeffrey A. Newman, Jundan Nie, N. Palanque-Delabrouille, W. J. Percival, C. Poppett, F. Prada, A. Raichoor, C. Ravoux, A. J. Ross, E. F. Schlafly, D. Schlegel, M. Schubnell, Ray M. Sharples, Gregory Tarlé, B. A. Weaver, Christophe Yèche, Rongpu Zhou, Zhimin Zhou, H. Zouwork_5tsesdige5h2rpwftsyeyoo64eThu, 29 Sep 2022 00:00:00 GMTStudies of quantum chromodynamics with jets at the CMS experiment at the LHC
https://scholar.archive.org/work/tl6cqxvdijhwbnd4wxd3l6sbii
Several people played a decisive role in accomplishing this thesis and helped me in dierent aspects. In Hamburg, I would like to extend my deepest gratitude to Patrick L.S. Connor for his invaluable contribution to this work and for training me to consider scientic research as a "share, help, learn, cross-check, enjoy" cycle. Besides developing the overall analysis framework, he was always reachable for help and support, making the work with him a continuous upskilling process. I am also extremely grateful to Paolo Gunnellini for his contributions to the analysis, but mainly for his crucial guidance during my rst steps in high energy physics and his availability to help whenever I needed to. At DESY, I am deeply indebted to Hannes Jung for all his hospitality and support. Apart from that, he also gave me the opportunity to work with his wonderful team, to whom I am also grateful. In particular, many thanks toParaskevas Gianneios, University Of Ioanninawork_tl6cqxvdijhwbnd4wxd3l6sbiiWed, 28 Sep 2022 00:00:00 GMTSpecial representatives of complexified Kähler classes
https://scholar.archive.org/work/4wha77qm6rc3fgkcvc4g7fvsgi
Motivated by constructions appearing in mirror symmetry, we study special representatives of complexified K\"ahler classes, which extend the notions of constant scalar curvature and extremal representatives for usual K\"ahler classes. In particular, we provide a moment map interpretation, discuss a possible correspondence with compactified Landau-Ginzburg models, and prove existence results for such special complexified K\"ahler forms and their large volume limits in certain toric cases.Carlo Scarpa, Jacopo Stoppawork_4wha77qm6rc3fgkcvc4g7fvsgiWed, 28 Sep 2022 00:00:00 GMTFlavour-universal search for heavy neutral leptons with a deep neural network-based displaced jet tagger with the CMS experiment
https://scholar.archive.org/work/gb63ulsuuzhixe7bhaqbgb7a5q
This thesis describes a search for long-lived heavy neutral leptons using a dataset of 137/fb collected during the 2016-2018 proton-proton runs with the CMS detector. The search uses a final state containing two leptons and at least one hadronic jet. This is the first analysis at the Large Hadron Collider which considers universal mixing between the Standard Model and heavy neutral lepton species. The search makes heavy use of a deep neural network-based displaced jet tagging algorithm, originally developed to target heavy long-lived gluino decays. The tagger was trained on both simulation and proton-proton collision data using the domain adaptation technique, which significantly improved the modelling of its output in simulation. The tagger has excellent performance for a range of long-lived particle lifetimes and generalises well to various flavours of displaced jets. In this analysis, the backgrounds are estimated in an entirely data-driven manner. No evidence for heavy neutral leptons is observed, and upper limits are set for a wide range of heavy neutral lepton mass, lifetime, and mixing scenarios. This is the most sensitive search for heavy neutral leptons in the 1–12 GeV mass range to date.Vilius Cepaitis, Alexander Tapper, Science And Technology Facilities Councilwork_gb63ulsuuzhixe7bhaqbgb7a5qWed, 28 Sep 2022 00:00:00 GMTThe JWST Early Release Science Program for Direct Observations of Exoplanetary Systems I: High Contrast Imaging of the Exoplanet HIP 65426 b from 2-16 μm
https://scholar.archive.org/work/xeswkognzfhdxngzsdsclhhhku
We present JWST Early Release Science (ERS) coronagraphic observations of the super-Jupiter exoplanet, HIP 65426 b, with the Near-Infrared Camera (NIRCam) from 2-5 μm, and with the Mid-Infrared Instrument (MIRI) from 11-16 μm. At a separation of ∼0.82" (87^+108_-31 au), HIP 65426 b is clearly detected in all seven of our observational filters, representing the first images of an exoplanet to be obtained by JWST, and the first ever direct detection of an exoplanet beyond 5 μm. These observations demonstrate that JWST is exceeding its nominal predicted performance by up to a factor of 10, with measured 5σ contrast limits of ∼4×10^-6 (∼2.4 μJy) and ∼2×10^-4 (∼10 μJy) at 1" for NIRCam at 3.6 μm and MIRI at 11.3 μm, respectively. These contrast limits provide sensitivity to sub-Jupiter companions with masses as low as 0.3 M_Jup beyond separations of ∼100 au. Together with existing ground-based near-infrared data, the JWST photometry are well fit by a BT-SETTL atmospheric model from 1-16 μm, and span ∼97 luminous range. Independent of the choice of forward model atmosphere we measure an empirical bolometric luminosity that is tightly constrained between log(L_bol/L_⊙)=-4.35 to -4.21, which in turn provides a robust mass constraint of 7.1±1.1 M_Jup. In totality, these observations confirm that JWST presents a powerful and exciting opportunity to characterise the population of exoplanets amenable to direct imaging in greater detail.Aarynn L. Carter, Sasha Hinkley, Jens Kammerer, Andrew Skemer, Beth A. Biller, Jarron M. Leisenring, Maxwell A. Millar-Blanchaer, Simon Petrus, Jordan M. Stone, Kimberly Ward-Duong, Jason J. Wang, Julien H. Girard, Dean C. Hines, Marshall D. Perrin, Laurent Pueyo, William O. Balmer, Mariangela Bonavita, Mickael Bonnefoy, Gael Chauvin, Elodie Choquet, Valentin Christiaens, Camilla Danielski, Grant M. Kennedy, Elisabeth C. Matthews, Brittany E. Miles, Polychronis Patapis, Shrishmoy Ray, Emily Rickman, Steph Sallum, Karl R. Stapelfeldt, Niall Whiteford, Yifan Zhou, Olivier Absil, Anthony Boccaletti, Mark Booth, Brendan P. Bowler, Christine H. Chen, Thayne Currie, Jonathan J. Fortney, Carol A. Grady, Alexandra Z. Greenbaum, Thomas Henning, Kielan K. W. Hoch, Markus Janson, Paul Kalas, Matthew A. Kenworthy, Pierre Kervella, Adam L. Kraus, Pierre-Olivier Lagage, Michael C. Liu, Bruce Macintosh, Sebastian Marino, Mark S. Marley, Christian Marois, Brenda C. Matthews, Dimitri Mawet, Michael W. McElwain, Stanimir Metchev, Michael R. Meyer, Paul Molliere, Sarah E. Moran, Caroline V. Morley, Sagnick Mukherjee, Eric Pantin, Andreas Quirrenbach, Isabel Rebollido, Bin B. Ren, Glenn Schneider, Malavika Vasist, Kadin Worthen, Mark C. Wyatt, Zackery W. Briesemeister, Marta L. Bryan, Per Calissendorff, Faustine Cantalloube, Gabriele Cugno, Matthew De Furio, Trent J. Dupuy, Samuel M. Factor, Jacqueline K. Faherty, Michael P. Fitzgerald, Kyle Franson, Eileen C. Gonzales, Callie E. Hood, Alex R. Howe, Masayuki Kuzuhara, Anne-Marie Lagrange, Kellen Lawson, Cecilia Lazzoni, Ben W. P. Lew, Pengyu Liu, Jorge Llop-Sayson, James P. Lloyd, Raquel A. Martinez, Johan Mazoyer, Sascha P. Quanz, Jea Adams Redai, Matthias Samland, Joshua E. Schlieder, Motohide Tamura, Xianyu Tan, Taichi Uyama, Arthur Vigan, Johanna M. Vos, Kevin Wagner, Schuyler G. Wolff, Marie Ygouf, Xi Zhang, Keming Zhang, Zhoujian Zhangwork_xeswkognzfhdxngzsdsclhhhkuWed, 28 Sep 2022 00:00:00 GMTQuantum state tomography, entanglement detection and Bell violation prospects in weak decays of massive particles
https://scholar.archive.org/work/5qx7xknyhrekxmfynar4t7wy74
A rather general method for determining the spin density matrix of a multi-particle system from angular decay data in presented. The method is based on a Bloch parameterisation of the d-dimensional generalised Gell-Mann representation of ρ and exploits the associated Wigner- and Weyl-transforms on the sphere. Each parameter of a (possibly multipartite) spin density matrix can can be measured from a simple average over an appropriate set of experimental angular decay distributions. The general procedures for both projective and non-projective decays are described, and the Wigner P and Q symbols calculated for the cases of spin-half, spin-one, and spin-3/2 systems. The methods are used to examine Monte Carlo simulations of pp collisions for bipartite systems: pp→ W^+W^-, pp→ ZZ, pp→ ZW^+, pp→ W^-t, and those from the Higgs boson decays H→ WW^* and H→ ZZ^*. Measurements are proposed for entanglement detection, exchange symmetry detection and Bell inequality violation in bipartite systems.Rachel Ashby-Pickering, Alan J. Barr, Agnieszka Wierzchuckawork_5qx7xknyhrekxmfynar4t7wy74Wed, 28 Sep 2022 00:00:00 GMTQuantifying Quantum Advantage in Topological Data Analysis
https://scholar.archive.org/work/w3tuawesfnhahpxmkcn4fuy3ua
Lloyd et al. were first to demonstrate the promise of quantum algorithms for computing Betti numbers in persistent homology (a way of characterizing topological features of data sets). Here, we propose, analyze, and optimize an improved quantum algorithm for topological data analysis (TDA) with reduced scaling, including a method for preparing Dicke states based on inequality testing, a more efficient amplitude estimation algorithm using Kaiser windows, and an optimal implementation of eigenvalue projectors based on Chebyshev polynomials. We compile our approach to a fault-tolerant gate set and estimate constant factors in the Toffoli complexity. Relative to the best classical heuristic algorithms, our analysis reveals that super-quadratic quantum speedups are only possible for this problem when targeting a multiplicative error approximation and the Betti number grows asymptotically. Further, we propose a dequantization of the quantum TDA algorithm that shows that having exponentially large dimension and Betti number are necessary, but insufficient conditions, for super-polynomial advantage. We then introduce and analyze specific problem examples for which super-polynomial advantages may be achieved, and argue that quantum circuits with tens of billions of Toffoli gates can solve some seemingly classically intractable instances.Dominic W. Berry, Yuan Su, Casper Gyurik, Robbie King, Joao Basso, Alexander Del Toro Barba, Abhishek Rajput, Nathan Wiebe, Vedran Dunjko, Ryan Babbushwork_w3tuawesfnhahpxmkcn4fuy3uaTue, 27 Sep 2022 00:00:00 GMTProbing black-hole accretion through time variability
https://scholar.archive.org/work/g5kogdxwxjhsbdimjkvaeia7f4
Flux variability is a remarkable property of black hole (BH) accreting systems, and a powerful tool to investigate the multi-scale structure of the accretion flow. The X-ray band is where some of the most rapid variations occur, pointing to an origin in the innermost regions close to the BH. The study of fast time variability provides us with means to explore the accretion flow around compact objects in ways which are inaccessible via spectral analysis alone, and to peek at regions which cannot be imaged with the currently available instrumentation. In this chapter we will discuss fast X-ray variability in stellar-mass BH systems, namely binary systems containing a star and a BH, occasionally contrasting it with observations of supermassive BHs in active galactic nuclei. We will explore how rapid variations of the X-ray flux have been used in multiple studies as a diagnostic of the innermost regions of the accretion flow in these systems. To this aim we will provide an overview of the currently most used analysis approaches for the study of X-ray variability, describe observations of both aperiodic and quasi-periodic phenomena, and discuss some of the proposed models.Barbara De Marco, Sara E. Motta, Tomaso M. Belloniwork_g5kogdxwxjhsbdimjkvaeia7f4Tue, 27 Sep 2022 00:00:00 GMTIt's a Wrap! Visualisations that Wrap Around Cylindrical, Toroidal, or Spherical Topologies
https://scholar.archive.org/work/akpvfdnu2fhgdjsfxa25kjeu2a
Traditional visualisations are designed to be shown on a flat surface (screen or page) but most data is not "flat". For example, the surface of the earth exists on a sphere, however, when that surface is presented on a flat map, key information is hidden, such as geographic paths on the spherical surface being wrapped across the boundaries of the flat map. Similarly, cyclical time-series data has no beginning or end. When such cyclical data is presented on a traditional linear chart, the viewer needs to perceive continuity of the visualisation across the chart's boundaries. Mentally reconnecting the chart across such a boundary may induce additional cognitive load. More complex data such as a network diagram with hundreds or thousands of links between data points leads to a densely connected structure that is even less "flat" and needs to wrap around in multiple dimensions. To improve the usability of these visualisations, this thesis explores a novel class of interactive wrapped data visualisations, i.e., visualisations that wrap around continuously when interactively panned on a two-dimensional projection of surfaces of 3D shapes, specifically, cylinder, torus, or sphere. We start with a systematic exploration of the design space of interactive wrapped visualisations, characterising the visualisations that help people understand the relationship within the data. Subsequently, we investigate a series of wrappable visualisations for cyclical time series, network, and geographic data. We show that these interactive visualisations better preserve the spatial relations in the case of geospatial data, and better reveal the data's underlying structure in the case of abstract data such as networks and cyclical time series. Furthermore, to assist future research and development, we contribute layout algorithms and toolkits to help create pannable wrapped visualisations.Kun-Ting Chenwork_akpvfdnu2fhgdjsfxa25kjeu2aTue, 27 Sep 2022 00:00:00 GMTThe Development of Energy-Recovery Linacs
https://scholar.archive.org/work/dlfbcw3oynbprcxiawscte6s5i
Energy-recovery linacs (ERLs) have been emphasised by the recent (2020) update of the European Strategy for Particle Physics as one of the most promising technologies for the accelerator base of future high-energy physics. The current paper has been written as a base document to support and specify details of the recently published European roadmap for the development of energy-recovery linacs. The paper summarises the previous achievements on ERLs and the status of the field and its basic technology items. The main possible future contributions and applications of ERLs to particle and nuclear physics as well as industrial developments are presented. The paper includes a vision for the further future, beyond 2030, as well as a comparative data base for the main existing and forthcoming ERL facilities. A series of continuous innovations, such as on intense electron sources or high-quality superconducting cavity technology, will massively contribute to the development of accelerator physics at large. Industrial applications are potentially revolutionary and may carry the development of ERLs much further, establishing another shining example of the impact of particle physics on society and its technical foundation with a special view on sustaining nature.Chris Adolphsenwork_dlfbcw3oynbprcxiawscte6s5iTue, 27 Sep 2022 00:00:00 GMTThe atmospheric entry of micrometeorites on Mars: Implications for their mineralogy, texture and organic constituents
https://scholar.archive.org/work/aw7wajmnanaupkdrvt3fcc4srq
The nature of martian micrometeorites (MMs) was investigated in this thesis through micro-analysis of terrestrial MMs and computational and experimental simulations of atmospheric entry heating. The biases in the Larkman Nunatak micrometeorite collection revealed in this study (Chapter 3) are attributed to the strong winnowing effects associated with sediment transport by aeolian processes. The weathering features observed in these micrometeorites are related to interaction with transient water. Sediment transport on Mars is dominated by aeolian processes, thus accumulations are likely to be similar to wind driven collections on Earth. However, their weathering state is expected to differ from terrestrial micrometeorites owing to the lack of water and much longer accumulation periods and is instead thought to be dominated by perchlorate induced oxidation. Computational simulations of atmospheric entry (Chapter 4) suggest much greater quantities of large, low temperature micrometeorites reaching the martian surface. The lower temperatures and larger particles surviving on Mars are likely to aid in the preservation of micrometeorite derived organic material with large portions of the micrometeorite flux expected to remain below the sublimation temperature of some organic compounds and larger particles allowing thermal gradients to form within particles. Experimental simulations (Chapter 5) indicate several differences between terrestrial and martian particles. Iron oxide phases were lacking in the martian particles including a magnetite rim, which is observed in the severely heated terrestrial particles. Additionally, sulphur and phosphorus are preserved in much greater quantities and in reduced forms in the martian particles. Raman spectroscopy also revealed that micrometeorite derived organic material on Earth experience greater evolution through the expansion of sp2 cluster diameter and growth of aromatic ring structures. Most of these features can be attributed to oxidative processes. Thus, atmospheric composit [...]Aaron Peter Wilson, Matthew Genge, UKSA, Science And Technology Facilities Council (Great Britain)work_aw7wajmnanaupkdrvt3fcc4srqTue, 27 Sep 2022 00:00:00 GMTA streamlined quantum algorithm for topological data analysis with exponentially fewer qubits
https://scholar.archive.org/work/bfpxeg4apvglzfhkomsu4xnphe
Topological invariants of a dataset, such as the number of holes that survive from one length scale to another (persistent Betti numbers) can be used to analyse and classify data in machine learning applications. We present an improved quantum algorithm for computing persistent Betti numbers, and provide an end-to-end complexity analysis. Our approach provides large polynomial time improvements, and an exponential space saving, over existing quantum algorithms. Subject to gap dependencies, our algorithm obtains an almost quintic speedup in the number of datapoints over rigorous state-of-the-art classical algorithms for calculating the persistent Betti numbers to constant additive error - the salient task for applications. However, this may be reduced to closer to quadratic when compared against heuristic classical methods and observed scalings. We discuss whether quantum algorithms can achieve an exponential speedup for tasks of practical interest, as claimed previously. We conclude that there is currently no evidence that this is the case.Sam McArdle, András Gilyén, Mario Bertawork_bfpxeg4apvglzfhkomsu4xnpheMon, 26 Sep 2022 00:00:00 GMTSPYGLASS-II: The Multi-Generational and Multi-Origin Star Formation History of Cepheus Far North
https://scholar.archive.org/work/cyoxonga3fg4xkwzjnl7mzhxtm
Young stellar populations provide a record of past star formation, and by establishing their members' dynamics and ages, it is possible to reconstruct the full history of star formation events. Gaia has greatly expanded the number of accessible stellar populations, with one of the most notable recently-discovered associations being Cepheus Far North (CFN), a population containing hundreds of members spanning over 100 pc. With its proximity (d ≲ 200 pc), apparent substructure, and relatively small population, CFN represents a manageable population to study in depth, with enough evidence of internal complexity to produce a compelling star formation story. Using Gaia astrometry and photometry combined with additional spectroscopic observations, we identify over 500 candidate CFN members spread across 7 subgroups. Combining ages from isochrones, asteroseismology, dynamics, and lithium depletion, we produce well-constrained ages for all seven subgroups, revealing a largely continuous 10 Myr star formation history in the association. By tracing back the present-day populations to the time of their formation, we identify two spatially and dynamically distinct nodes in which stars form, one associated with β Cephei which shows mostly co-spatial formation, and one associated with EE Draconis with a more dispersed star formation history. This detailed view of star formation demonstrates the complexity of the star formation process, even in the smallest of regions.Ronan Kerr, Adam L. Kraus, Simon J. Murphy, Daniel M. Krolikowski, Stella S. R. Offner, Benjamin M. Tofflemire, Aaron C. Rizzutowork_cyoxonga3fg4xkwzjnl7mzhxtmMon, 26 Sep 2022 00:00:00 GMTReconstruction of electron radiation spectra and beam parameters from photon spectrometer data in accelerator experiments using machine learning
https://scholar.archive.org/work/4tyynp4cmne77awyamoedcgh2i
Recovering key aspects of an incoming photon stream during projected FACET-II experiments, such as their energy distributions and the original electron beam's parameters, remains an unsolved computational problem. This paper utilized data from simulated plasma wakefield acceleration betatron radiation experiments and electron-positron pair production to determine which methods could most reliably reconstruct these key properties. The data from these two cases provided a large range of photon energies to help increase confidence in each of the tested methods. In both cases, we compared the performance of maximum likelihood estimation (MLE), a statistical technique used to determine unknown parameters from the distribution of observed data, neural networks, which detect patterns between datasets through repeated training, and a hybrid approach combining the two. Furthermore, in the electron-positron production case, the paper also compared QR decomposition, a matrix decomposition method. The betatron radiation case demonstrated the effectiveness of a hybrid ML-MLE approach, while the electron-positron pair production case illustrated the effectiveness of the ML model in the face of noise. As such, the ML-MLE hybrid approach proved to be the most generalizable of the methods.M. Yadav, S. Zhang, M. Oruganti, B. Naranjo, Y. Zhuang, Ö. Apsimon, C. P. Welsch, J. B. Rosenzweigwork_4tyynp4cmne77awyamoedcgh2iSun, 25 Sep 2022 00:00:00 GMTThe Physics of Learning
https://scholar.archive.org/work/ai3x5a65tndktnosend7gehapq
A learning machine, like all machines, is an open system driven far from thermal equilibrium by access to a low entropy source of free energy. We discuss the connection between machines that learn, with low probability of error, and the optimal use of thermodynamic resources for both classical and quantum machines. Both fixed point and spiking perceptrons are discussed in the context of possible physical implementations. An example of a single photon quantum kernel evaluation illustrates the important role for quantum coherence in data representation. Machine learning algorithms, implemented on conventional complementary metal oxide semiconductor (CMOS) devices, currently consume large amounts of energy. By focusing on the physical constraints of learning machines rather than algorithms, we suggest that a more efficient means of implementing learning may be possible based on quantum switches operating at very low power. Single photon kernel evaluation is an example of the energy efficiency that might be possible.G. J. Milburn, Sahar-Basiri-Esfahaniwork_ai3x5a65tndktnosend7gehapqSat, 24 Sep 2022 00:00:00 GMTSupplementary document for Full Poincaré polarimetry enabled through physical inference - 6025529.pdf
https://scholar.archive.org/work/qj3vdrbt5raahiogsiv7soldv4
Supplementary informationChao He, Jianyu Lin, Jintao Chang, Jacopo Antonello, Ben Dai, Jingyu Wang, Jiahe Cui, ji qi, Min Wu, Daniel Elsonwork_qj3vdrbt5raahiogsiv7soldv4Fri, 23 Sep 2022 00:00:00 GMTReplica approach to the generalized Rosenzweig-Porter model
https://scholar.archive.org/work/xwoiobvl7vfebauxtr44ppfqd4
The generalized Rosenzweig–Porter model arguably constitutes the simplest random matrix ensemble displaying a non-ergodic delocalized phase, which we characterize here by using replica methods. We first derive analytical expressions for the average spectral density in the limit in which the size N of the matrix is large but finite. We then focus on the number of eigenvalues in a finite interval and compute its cumulant generating function as well as the level compressibility, i.e., the ratio of the first two cumulants: these are useful tools to describe the local level statistics. In particular, the level compressibility is shown to be described by a universal scaling function, which we compute explicitly, when the system is probed over scales of the order of the Thouless energy. We confirm our results with numerical tests.Davide Venturelli and Leticia F. Cugliandolo and Grégory Schehr and Marco Tarziawork_xwoiobvl7vfebauxtr44ppfqd4Fri, 23 Sep 2022 00:00:00 GMTThe path to 5G-Advanced and 6G Non-Terrestrial Network systems
https://scholar.archive.org/work/zt6mg2utkngglgfvm4cvud7ggu
Today, 5G networks are being worldwide rolled out, with significant benefits in our economy and society. However, 5G systems alone are not expected to be sufficient for the challenges that 2030 networks will experience, including, e.g., always-on networks, 1 Tbps peak data rate, <10 cm positioning, etc. Thus, the definition of evolutions of the 5G systems and their (r)evolutions are already being addressed by the scientific and industrial communities, targeting 5G-Advanced (5G-A) and 6G. In this framework, Non-Terrestrial Networks (NTN) have successfully been integrated in 3GPP Rel. 17 and it is expected that they will play an even more pivotal role for 5G-A (up to Rel. 20) and 6G systems (beyond Rel. 20). In this paper, we explore the path that will lead to 5G-A and 6G NTN communications, providing a clear perspective in terms of system architecture, services, technologies, and standardisation roadmap.Alessandro Guidotti, Alessandro Vanelli-Coralli, Vincenzo Schena, Nicolas Chuberre, Mohamed El Jaafari, Jani Puttonen, Stefano Cioniwork_zt6mg2utkngglgfvm4cvud7gguFri, 23 Sep 2022 00:00:00 GMT