IA Scholar Query: The Data Compression Theorem for Ergodic Quantum Information Sources.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgTue, 20 Sep 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Recurrence times, waiting times and universal entropy production estimators
https://scholar.archive.org/work/gaboggn4pbgnnhlex7k6zjdfrm
The universal typical-signal estimators of entropy and cross entropy based on the asymptotics of recurrence and waiting times play an important role in information theory. Building on their construction, we introduce and study universal typical-signal estimators of entropy production in the context of nonequilibrium statistical mechanics of one-sided shifts over finite alphabets.Giampaolo Cristadoro, Mirko Degli Esposti, Vojkan Jakšić, Renaud Raquépaswork_gaboggn4pbgnnhlex7k6zjdfrmTue, 20 Sep 2022 00:00:00 GMTProgress on stochastic analytic continuation of quantum Monte Carlo data
https://scholar.archive.org/work/eahyejzztbcajetpcbh2qid6c4
We report multipronged progress on the stochastic averaging approach to numerical analytic continuation of quantum Monte Carlo data. With the sampled spectrum parametrized with delta-functions in continuous frequency space, a calculation of the configurational entropy lends support to a simple goodness-of-fit criterion for the optimal sampling temperature. To further investigate entropic effects, we compare spectra sampled in continuous frequency with results of amplitudes sampled on a fixed frequency grid. We demonstrate equivalences between sampling and optimizing spectral functions with the maximum-entropy approach with different forms of the entropy. These insights revise prevailing notions of the maximum-entropy method and its relationship to stochastic analytic continuation. We further explore various adjustable (optimized) constraints that allow sharp spectral features to be resolved, in particular at the lower frequency edge. The constraints, e.g., the location of the edge or the spectral weight of a quasi-particle peak, are optimized using a statistical criterion. We show that this method can correctly reproduce both narrow and broad quasi-particle peaks. We next introduce a parametrization for more intricate spectral functions with sharp edges, e.g., power-law singularities. Tests with synthetic data as well as with real simulation data for the spin-1/2 Heisenberg chain demonstrate that constrained sampling methods can reproduce spectral functions with sharp edge features at unprecedented fidelity. We present new results for S=1/2 Heisenberg 2-leg and 3-leg ladders to illustrate the ability of the methods to resolve spectral features arising from both elementary and composite excitations. Finally, we also propose how the methods developed here could be used as "pre processors" for analytic continuation by machine learning.Hui Shao, Anders W. Sandvikwork_eahyejzztbcajetpcbh2qid6c4Mon, 19 Sep 2022 00:00:00 GMTDFTB+, a software package for efficient approximate density functional theory based atomistic simulations
https://scholar.archive.org/work/ltj5a2npufdu3lvpru6w3pkdve
DFTB+ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green's functions, and many more. DFTB+ can be used as a user-friendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the DFTB+ code, demonstrating with a few use case examples, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives.B. Hourahine, B. Aradi, V. Blum, F. Bonafé, A. Buccheri, C. Camacho, C. Cevallos, M. Y. Deshaye, T. Dumitrică, Jan Hermann, Universitätsbibliothek Der FU Berlinwork_ltj5a2npufdu3lvpru6w3pkdveMon, 05 Sep 2022 00:00:00 GMTCharacterising and modeling the co-evolution of transportation networks and territories
https://scholar.archive.org/work/6f4roc6xvrcdtb443uuvx7mpk4
The identification of structuring effects of transportation infrastructure on territorial dynamics remains an open research problem. This issue is one of the aspects of approaches on complexity of territorial dynamics, within which territories and networks would be co-evolving. The aim of this thesis is to challenge this view on interactions between networks and territories, both at the conceptual and empirical level, by integrating them in simulation models of territorial systems.Juste Raimbaultwork_6f4roc6xvrcdtb443uuvx7mpk4Fri, 02 Sep 2022 00:00:00 GMTWhat entropy really is
https://scholar.archive.org/work/oir45wd5vbbhndmloojzexcdja
Even today, the concept of entropy is perceived by many as quite obscure. The main difficulty is analyzed as being fundamentally due to the subjectivity and anthropocentrism of the concept that prevent us to have a sufficient distance to embrace it. However, it is pointed out that the lack of coherence of certain presentations or certain preconceived ideas do not help. They are of three kinds : 1) axiomatic thermodynamics; 2) inconsistent solutions of certain paradoxes; 3) reluctance of physicists to the simplification provided by information theory. The purpose of this paper is to examine these points by paying attention to the structure of the theory, what are the foundations, how ideas articulate, with a peculiar focus on their consistency and economy. It is shown how entropy can be introduced in a more consistent and economical manner, finally allowing a more intuitive understanding.Didier Lairezwork_oir45wd5vbbhndmloojzexcdjaThu, 01 Sep 2022 00:00:00 GMTTesting randomness of series generated in Bell's experiment
https://scholar.archive.org/work/3iutqr4mtfcndlrh2r67uxq3xi
The generation of series of random numbers is an important and difficult problem. Even the very definition of random is difficult. Appropriate measurements on entangled states have been proposed as the definitive solution to produce series of certified randomness. However, several reports indicate that quantum based devices show a disappointing rate of series rejected by standard tests of randomness. This problem is usually solved by using algorithms named extractors but, if the extractor were known by an eavesdropper (a situation that cannot be ruled out) the key security in QKD setups may be menaced. We use a toy fiber optic based setup, similar to a QKD one to be used in the field, to generate binary series, and evaluate their level of randomness according to Ville principle. Series are tested with a battery of standard statistical indicators, Hurst exponent, Kolmogorov complexity, minimum entropy, Takens dimension of embedding, and Augmented Dickey Fuller and Kwiatkowski Phillips Schmidt Shin to check stationarity. A theoretically predicted relationship between complexity and minimum entropy is observed. The good performance of a simple method to get useful series from rejected series, reported by Solis et al, is confirmed and supported with additional arguments. Regarding QKD, the level of randomness of series obtained by applying Toeplitz extractor to rejected series is found to be indistinguishable from the level of non-rejected raw ones.Myriam Nonaka, Mónica Agüero, Marcelo Kovalsky, Alejandro Hnilowork_3iutqr4mtfcndlrh2r67uxq3xiWed, 31 Aug 2022 00:00:00 GMTLectures on classical and quantum cosmology
https://scholar.archive.org/work/epmoopw53nczlf4hrrvrhhyhxy
These lecture notes introduce the reader to the hot big bang model, cosmological perturbations, gravitational waves, the cosmic microwave background, inflation, the singularity problem, the cosmological constant problem and the cosmology of quantum gravity.Gianluca Calcagni, Maria Grazia Di Luca, Tomáš Fodranwork_epmoopw53nczlf4hrrvrhhyhxyTue, 16 Aug 2022 00:00:00 GMTInformation dynamics and the arrow of time
https://scholar.archive.org/work/gdslmjl6irgixoglktutzqt4ma
Why does time appear to pass irreversibly? To investigate, we introduce a class of partitioned cellular automata (PCAs) whose cellwise evolution is based on the chaotic baker's map. After imposing a suitable initial condition and restricting to a macroscopic view, we are left with a stochastic PCA (SPCA). When the underlying PCA's dynamics are reversible, the corresponding SPCA serves as a model of emergent time-reversal asymmetry. Specifically, we prove that its transition probabilities are homogeneous in space and time, as well as Markov relative to a Pearlean causal graph with timelike future-directed edges. Consequently, SPCAs satisfy generalizations of the second law of thermodynamics, which we term the Resource and Memory Laws. By subjecting information-processing agents (e.g., human experimenters) to these laws, we clarify issues regarding the Past Hypothesis, Landauer's principle, Boltzmann brains, scientific induction, and the so-called psychological arrow of time. Finally, by describing a theoretical agent powered by data compression, we argue that the algorithmic entropy takes conceptual precedence over both the Shannon-Gibbs and Boltzmann entropies.Aram Ebtekarwork_gdslmjl6irgixoglktutzqt4maFri, 12 Aug 2022 00:00:00 GMTBounded operators and von Neumann algebras
https://scholar.archive.org/work/cikqosndpje7vmolarptt6mjxu
We discuss the algebras of bounded operators A⊂ B(H), in the case where A is weakly closed, and has a trace tr:A→ℂ. In this case we have A=L^∞(X), with X being a quantum space, and the free case, where Z(A)=ℂ, is of particular interest. We explain this material, following von Neumann and Connes, Jones, Voiculescu.Teo Banicawork_cikqosndpje7vmolarptt6mjxuSun, 07 Aug 2022 00:00:00 GMTReview of performance metrics of spin qubits in gated semiconducting nanostructures
https://scholar.archive.org/work/ggjsrzrt3bdiddxxgnwst4x5le
This Technical Review collects values of selected performance characteristics of semiconductor spin qubits defined in electrically controlled nanostructures. The characteristics are envisioned to serve as a community source for the values of figures of merit with agreed-on definitions allowing the comparison of different spin qubit platforms. We include characteristics on the qubit coherence, speed, fidelity, and the qubit-size of multiqubit devices. The focus is on collecting and curating the values of these characteristics as reported in the literature, rather than on their motivation or significance.Peter Stano, Daniel Losswork_ggjsrzrt3bdiddxxgnwst4x5leWed, 03 Aug 2022 00:00:00 GMTPopcorn Drude weights from quantum symmetry
https://scholar.archive.org/work/si7jw2wstbgnnn2sts7b3o5d7q
Integrable models provide emblematic examples of non-ergodic phenomena. One of their most distinguished properties are divergent zero-frequency conductivities signalled by finite Drude weights. Singular conductivities owe to long-lived quasiparticle excitations that propagate ballistically through the system without any diffraction. The case of the celebrated quantum Heisenberg chain, one of the best-studied many-body paradigms, turns out to be particularly mysterious. About a decade ago, it was found that the spin Drude weight in the critical phase of the model assumes an extraordinary, nowhere continuous, dependence on the anisotropy parameter in the shape of a 'popcorn function'. This unprecedented discovery has been afterwards resolved at the level of the underlying deformed quantum symmetry algebra which helps explaining the erratic nature of the quasiparticle spectrum at commensurate values of interaction anisotropy. This work is devoted to the captivating phenomenon of discontinuous Drude weights, with the aim to give a broader perspective on the topic by revisiting and reconciling various perspectives from the previous studies. Moreover, it is argued that such an anomalous non-ergodic feature is not exclusive to the integrable spin chain but can be instead expected in a number of other integrable systems that arise from realizations of the quantum group 𝒰_q(𝔰𝔩(2)), specialized to unimodular values of the quantum deformation parameter q. Our discussion is framed in the context of gapless anisotropic quantum chains of higher spin and the sine-Gordon quantum field theory in two space-time dimensions.Enej Ilievskiwork_si7jw2wstbgnnn2sts7b3o5d7qTue, 02 Aug 2022 00:00:00 GMTQuantum machine learning for chemistry and physics
https://scholar.archive.org/work/ts35ancqmvay5fhyqya6degva4
Machine learning (ML) has emerged as a formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In recent years, it is safe to conclude that ML and its close cousin, deep learning (DL), have ushered in unprecedented developments in all areas of physical sciences, especially chemistry. Not only classical variants of ML, even those trainable on near-term quantum hardwares have been developed with promising outcomes. Such algorithms have revolutionized materials design and performance of photovoltaics, electronic structure calculations of ground and excited states of correlated matter, computation of force-fields and potential energy surfaces informing chemical reaction dynamics, reactivity inspired rational strategies of drug designing and even classification of phases of matter with accurate identification of emergent criticality. In this review we shall explicate a subset of such topics and delineate the contributions made by both classical and quantum computing enhanced machine learning algorithms over the past few years. We shall not only present a brief overview of the well-known techniques but also highlight their learning strategies using statistical physical insight. The objective of the review is not only to foster exposition of the aforesaid techniques but also to empower and promote cross-pollination among future research in all areas of chemistry which can benefit from ML and in turn can potentially accelerate the growth of such algorithms.Manas Sajjan, Junxu Li, Raja Selvarajan, Shree Hari Sureshbabu, Sumit Suresh Kale, Rishabh Gupta, Vinit Singh, Sabre Kaiswork_ts35ancqmvay5fhyqya6degva4Mon, 18 Jul 2022 00:00:00 GMTAn Algorithmic Approach to Emergence
https://scholar.archive.org/work/4p2ouzqxr5crzbph6d4xycjxpu
We suggest a quantitative and objective notion of emergence. Our proposal uses algorithmic information theory as a basis for an objective framework in which a bit string encodes observational data. A plurality of drops in the Kolmogorov structure function of such a string is seen as the hallmark of emergence. Our definition offers some theoretical results, in addition to extending the notions of coarse-graining and boundary conditions. Finally, we confront our proposal with applications to dynamical systems and thermodynamics.Charles Alexandre Bédard, Geoffroy Bergeronwork_4p2ouzqxr5crzbph6d4xycjxpuSat, 16 Jul 2022 00:00:00 GMTHard-disk computer simulations – a historic perspective
https://scholar.archive.org/work/cnfwnxvtk5bjzj4wm6vivqsbbm
We discuss historic pressure computations for the hard-disk model performed since 1953, and compare them to results that we obtain with a powerful event-chain Monte Carlo and a massively parallel Metropolis algorithm. Like other simple models in the sciences, such as the Drosophila model of biology, the hard-disk model has needed monumental effort to be understood. In particular, we argue that the difficulty of estimating the pressure has not been fully realized in the decades-long controversy over the hard-disk phase-transition scenario. We present the physics of the hard-disk model, the definition of the pressure and its unbiased estimators, several of which are new. We further treat different sampling algorithms and crucial criteria for bounding mixing times in the absence of analytical predictions. Our definite results for the pressure, for up to one million disks, may serve as benchmarks for future sampling algorithms. A synopsis of hard-disk pressure data as well as different versions of the sampling algorithms and pressure estimators are made available in an open-source repository.Botao Li, Yoshihiko Nishikawa, Philipp Hoellmer, Louis Carillo, A. C. Maggs, Werner Krauthwork_cnfwnxvtk5bjzj4wm6vivqsbbmFri, 15 Jul 2022 00:00:00 GMTThe Disordered Heterogeneous Universe: Galaxy Distribution and Clustering Across Length Scales
https://scholar.archive.org/work/plsherp2nnbcbmwtqbhcwuggwi
Studies of disordered heterogeneous media and galaxy cosmology share a common goal: analyzing the distribution of particles at 'microscales' to predict physical properties at 'macroscales', whether for a liquid, composite material, or entire Universe. The former theory provides an array of techniques to characterize a wide class of microstructures; in this work, we apply them to the distributions of galaxies. We focus on the lower-order correlation functions, 'void' and 'particle' nearest-neighbor functions, pair-connectedness functions, percolation properties, and a scalar order metric. Compared to homogeneous Poisson and typical disordered systems, the cosmological simulations exhibit enhanced large-scale clustering and longer tails in the nearest-neighbor functions, due to the presence of quasi-long-range correlations. On large scales, the system appears 'hyperuniform', due to primordial density fluctuations, whilst on the smallest scales, the system becomes almost 'antihyperuniform', and, via the order metric, is shown to be a highly correlated disordered system. Via a finite scaling analysis, we show that the percolation threshold of the galaxy catalogs is significantly lower than for Poisson realizations; this is consistent with the observation that the galaxy distribution contains larger voids. However, the two sets of simulations share a fractal dimension, implying that they lie in the same universality class. Finally, we consider the ability of large-scale clustering statistics to constrain cosmological parameters using simulation-based inference. Both the nearest-neighbor distribution and pair-connectedness function considerably tighten bounds on the amplitude of cosmological fluctuations at a level equivalent to observing twenty-five times more galaxies. These are a useful alternative to the three-particle correlation, and are computable in much reduced time. (Abridged)Oliver H. E. Philcox, Salvatore Torquatowork_plsherp2nnbcbmwtqbhcwuggwiWed, 13 Jul 2022 00:00:00 GMTQuantum simulation with an optical kagome lattice
https://scholar.archive.org/work/hxflqab5tvbtlm5qe6tezhxzxm
This thesis reports on the construction and operation of an ultracold atom- based quantum simulator for studying the kagome lattice and the associated flat band. Despite a copious amount of theoretical effort to elucidate the physics of the kagome lattice, experimental kagome physics is still in its infancy. In the case of ultracold atoms, this is mainly due to considerable technical challenges involved in creating an optical kagome lattice, such as the need for active phase stabilization for bichromatic superlattices. We show that we have overcome these challenges and give a thorough account of our machine's technical details. Furthermore, we present calculations and measurements that fully characterise the kagome quantum simulator. Much of the theoretical work on the kagome lattice has focussed on its flat band. Populating flat bands with ultracold atoms has proven to be difficult and it has so far not been possible to prepare flat bands in thermodynamic equilibrium. We show a route towards studying quantum manybody physics in the flat band of the kagome lattice using negative temperatures. In addition we report, for the first time, on the creation of a negative temperature state in a triangular lattice. This thesis additionally serves to collect and consolidate theoretical research that we can directly study with our machine. In particular, we will discuss the properties of bosons in flat bands and their experimental signatures, with the aim of guiding and accelerating the near-term developments and experiments. Finally, we detail our progress towards realizing a quantum gas microscope for the kagome lattice. In this context, we present a new method for super-resolution microscopy of ultracold atoms in optical lattices.Max Melchner Von Dydiowa, Apollo-University Of Cambridge Repository, Ulrich Schneiderwork_hxflqab5tvbtlm5qe6tezhxzxmWed, 13 Jul 2022 00:00:00 GMTDielectric effects in complex fluids
https://scholar.archive.org/work/hag7n4boo5cx5mwursd36vhr4y
Bulk long-range interionic potentials of mean force222 7.2.2 Scaling analysis of asymptotic screening lengths in concentrated electrolyte solutions . . . . . . . 7.2.3 Ionic liquids confined between like-charged surfaces231 7.2.4 Structural decay in confined ionic liquids . . . . 7.3 On the Relation of Underscreening to Other Measurements237 7.Johannes Zeman, Universität Stuttgartwork_hag7n4boo5cx5mwursd36vhr4yMon, 11 Jul 2022 00:00:00 GMTIntroduction to Machine Learning for the Sciences
https://scholar.archive.org/work/75kotoid75gnlkdgwx4fpuvely
This is an introductory machine-learning course specifically developed with STEM students in mind. Our goal is to provide the interested reader with the basics to employ machine learning in their own projects and to familiarize themself with the terminology as a foundation for further reading of the relevant literature. In these lecture notes, we discuss supervised, unsupervised, and reinforcement learning. The notes start with an exposition of machine learning methods without neural networks, such as principle component analysis, t-SNE, clustering, as well as linear regression and linear classifiers. We continue with an introduction to both basic and advanced neural-network structures such as dense feed-forward and conventional neural networks, recurrent neural networks, restricted Boltzmann machines, (variational) autoencoders, generative adversarial networks. Questions of interpretability are discussed for latent-space representations and using the examples of dreaming and adversarial attacks. The final section is dedicated to reinforcement learning, where we introduce basic notions of value functions and policy learning.Titus Neupert, Mark H Fischer, Eliska Greplova, Kenny Choo, M. Michael Dennerwork_75kotoid75gnlkdgwx4fpuvelyWed, 22 Jun 2022 00:00:00 GMTOptimal Cooling of Multiple Levitated Particles: Theory of Far-Field Wavefront-Shaping
https://scholar.archive.org/work/kkj5eyv4pzb7vevjibqhirck34
The opportunity to manipulate small-scale objects pushes us to the limits of our understanding of physics. Particularly promising in this regard is the interdisciplinary field of levitation, in which light fields can be harnessed to isolate nano-particles from their environment by levitating them optically. When cooled down towards their motional quantum ground state, levitated systems offer the tantalizing prospect of displaying mesoscopic quantum properties. Currently restricted to single objects with simple shapes, the interest in levitation is currently moving towards the manipulation of more complex structures, such as those featuring multiple particles or different degrees of freedom. Unfortunately, current cooling techniques are mostly designed for single objects and thus cannot easily be multiplexed to address such coupled many-body systems. Here, we present an approach based on the spatial modulation of light in the far-field to cool down multiple nano-objects in parallel. Our procedure is based on the experimentally measurable scattering matrix and on its changes with time. We demonstrate how to compose from these ingredients a linear energy-shift operator, whose eigenstates are identified as the incoming wavefronts that implement the most efficient cooling of complex moving ensembles of levitated particles. Submitted in parallel with arxiv:2103.12592, this article provides a theoretical and numerical study of the expected cooling performance as well as of the robustness of the method against environmental parameters.Jakob Hüpfl, Nicolas Bachelard, Markus Kaczvinszki, Michael Horodynski, Matthias Kühmayer, Stefan Rotterwork_kkj5eyv4pzb7vevjibqhirck34Thu, 02 Jun 2022 00:00:00 GMTLow-Rank Approximation for Multiscale PDEs
https://scholar.archive.org/work/kvz2xyegkzd3zmi4rnlxc5dsc4
Ke Chen, Shi Chen, Qin Li, Jianfeng Lu, Stephen J Wrightwork_kvz2xyegkzd3zmi4rnlxc5dsc4Wed, 01 Jun 2022 00:00:00 GMT