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  • 1.
    Balatsky, Alexander V.
    et al.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Institute for Materials Science, Los Alamos National Laboratory, Los Alamos, NM, United States .
    Balatsky, Galina I.
    Borysov, Stanislav S.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics.
    Resource Demand Growth and Sustainability Due to Increased World Consumption2015In: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 7, no 3, p. 3430-3440Article in journal (Refereed)
    Abstract [en]

    The paper aims at continuing the discussion on sustainability and attempts to forecast the impossibility of the expanding consumption worldwide due to the planet's limited resources. As the population of China, India and other developing countries continue to increase, they would also require more natural and financial resources to sustain their growth. We coarsely estimate the volumes of these resources (energy, food, freshwater) and the gross domestic product (GDP) that would need to be achieved to bring the population of India and China to the current levels of consumption in the United States. We also provide estimations for potentially needed immediate growth of the world resource consumption to meet this equality requirement. Given the tight historical correlation between GDP and energy consumption, the needed increase of GDP per capita in the developing world to the levels of the U.S. would deplete explored fossil fuel reserves in less than two decades. These estimates predict that the world economy would need to find a development model where growth would be achieved without heavy dependence on fossil fuels.

  • 2.
    Borysov, Stanislav
    et al.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Singapore Massachusetts Inst Technol MIT Alliance, Singapore.
    Lourenco, Mariana
    Rodrigues, Filipe
    Balatsky, Alexander
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Los Alamos Natl Lab, NM USA.
    Pereira, Francisco
    Using Internet Search Queries to Predict Human Mobility in Social Events2016In: 2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2016, p. 1342-1347Conference paper (Refereed)
    Abstract [en]

    While our transport systems are generally designed for habitual behavior, the dynamics of large and mega cities systematically push it to its limits. Particularly, transport planning and operations in large events are well known to be a challenge. Not only they imply stress to the system on an irregular basis, their associated mobility behavior is also difficult to predict. Previous studies have shown a strong correlation between number of public transport arrivals with the semi-structured data mined from online announcement websites. However, these models tend to be complex in form and demand substantial information retrieval, extraction and data cleaning work, and so they are difficult to generalize from city to city. In contrast, this paper focuses on enriching previously mined information about special events using automated web search queries. Since this context data comes in unstructured natural language form, we employ supervised topic model to correlate it with real measurements of transport usage. In this way, the proposed approach is more generic and a transit agency can start planning ahead as early as the event is announced on the web. The results show that using information mined from the web search not only shows high prediction accuracy of public transport demand, but also potentially provides interesting insights about popular event categories based on extracted topics.

  • 3.
    Borysov, Stanislav
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics. KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Roudi, Yasser
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. The Kavli Institute for Systems Neuroscience, NTNU, Trondheim, Norway.
    Balatsky, Alexander V.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Institute for Materials Science, Los Alamos National Laboratory, Los Alamos, NM, United States.
    U.S. stock market interaction network as learned by the Boltzmann machine2015In: European Physical Journal B: Condensed Matter Physics, ISSN 1434-6028, E-ISSN 1434-6036, Vol. 88, no 12, p. 1-14Article in journal (Refereed)
    Abstract [en]

    We study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented results show that binarization preserves the correlation structure of the market. Properties of distributions of external fields and couplings as well as the market interaction network and industry sector clustering structure are studied for different historical dates and moving window sizes. We demonstrate that the observed positive heavy tail in distribution of couplings is related to the sparse clustering structure of the market. We also show that discrepancies between the model’s parameters might be used as a precursor of financial instabilities.

  • 4.
    Borysov, Stanislav S.
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics. KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Stockholm University, Sweden.
    Balatsky, Alexander V.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Stockholm University, Sweden.
    Cross-Correlation Asymmetries and Causal Relationships between Stock and Market Risk2014In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 8, p. e105874-Article in journal (Refereed)
    Abstract [en]

    We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard & Poor's 500 index for 1994-2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa.

  • 5.
    Borysov, Stanislav S.
    et al.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Forchheimer, Daniel
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics.
    Haviland, David B.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics.
    Dynamic calibration of higher eigenmode parameters of a cantilever in atomic force microscopy by using tip-surface interactions2014In: Beilstein Journal of Nanotechnology, ISSN 2190-4286, Vol. 5, p. 1899-1904Article in journal (Refereed)
    Abstract [en]

    We present a theoretical framework for the dynamic calibration of the higher eigenmode parameters (stiffness and optical lever inverse responsivity) of a cantilever. The method is based on the tip-surface force reconstruction technique and does not require any prior knowledge of the eigenmode shape or the particular form of the tip-surface interaction. The calibration method proposed requires a single-point force measurement by using a multimodal drive and its accuracy is independent of the unknown physical amplitude of a higher eigenmode.

  • 6.
    Borysov, Stanislav S.
    et al.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Geilhufe, R. Matthias
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Balatsky, Alexander V.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Organic materials database: An open-access online database for data mining2017In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 2, article id e0171501Article in journal (Refereed)
    Abstract [en]

    We present an organic materials database (OMDB) hosting thousands of Kohn-Sham electronic band structures, which is freely accessible online at http://omdb.diracmaterials.org. The OMDB focus lies on electronic structure, density of states and other properties for purely organic and organometallic compounds that are known to date. The electronic band structures are calculated using density functional theory for the crystal structures contained in the Crystallography Open Database. The OMDB web interface allows users to retrieve materials with specified target properties using non-trivial queries about their electronic structure. We illustrate the use of the OMDB and how it can become an organic part of search and prediction of novel functional materials via data mining techniques. As a specific example, we provide data mining results for metals and semiconductors, which are known to be rare in the class of organic materials.

  • 7.
    Borysov, Stanislav S.
    et al.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Olsthoorn, Bart
    Stockholm Univ, Roslagstullsbacken 23, SE-10691 Stockholm, Sweden.;Stockholm Univ, Dept Phys, SE-10691 Stockholm, Sweden..
    Gedik, M. Berk
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Geilhufe, R. Matthias
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Balatsky, Alexander V.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Univ Connecticut, Dept Phys, Storrs, CT 06269 USA..
    Online search tool for graphical patterns in electronic band structures2018In: NPJ COMPUTATIONAL MATERIALS, ISSN 2057-3960, Vol. 4, article id UNSP 46Article in journal (Refereed)
    Abstract [en]

    Many functional materials can be characterized by a specific pattern in their electronic band structure, for example, Dirac materials, characterized by a linear crossing of bands; topological insulators, characterized by a "Mexican hat" pattern or an effectively free electron gas, characterized by a parabolic dispersion. To find material realizations of these features, manual inspection of electronic band structures represents a relatively easy task for a small number of materials. However, the growing amount of data contained within modern electronic band structure databases makes this approach impracticable. To address this problem, we present an automatic graphical pattern search tool implemented for the electronic band structures contained within the Organic Materials Database. The tool is capable of finding user-specified graphical patterns in the collection of thousands of band structures from high-throughput calculations in the online regime. Using this tool, it only takes a few seconds to find an arbitrary graphical pattern within the ten electronic bands near the Fermi level for 26,739 organic crystals. The source code of the developed tool is freely available and can be adapted to any other electronic band structure database.

  • 8.
    Borysov, Stanislav S.
    et al.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Platz, Daniel
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics.
    de Wijn, Astrid S.
    Forchheimer, Daniel
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics.
    Tolén, Eric A.
    Balatsky, Alexander V.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Haviland, David B.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics.
    Reconstruction of tip-surface interactions with multimodal intermodulation atomic force microscopy2013In: Physical Review B. Condensed Matter and Materials Physics, ISSN 1098-0121, E-ISSN 1550-235X, Vol. 88, no 11, p. 115405-Article in journal (Refereed)
    Abstract [en]

    We propose a theoretical framework for reconstructing tip-surface interactions using the intermodulation technique when more than one eigenmode is required to describe the cantilever motion. Two particular cases of bimodal motion are studied numerically: one bending and one torsional mode, and two bending modes. We demonstrate the possibility of accurate reconstruction of a two-dimensional conservative force field for the former case, while dissipative forces are studied for the latter.

  • 9.
    Forchheimer, Daniel
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics.
    Borysov, Stanislav S.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Platz, Daniel
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics. Max-Planck-Institute for the Physics of Complex Systems, Germany.
    Haviland, David B.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics.
    Determining surface properties with bimodal and multimodal AFM2014In: Nanotechnology, ISSN 0957-4484, E-ISSN 1361-6528, Vol. 25, no 48, p. 485708-Article in journal (Refereed)
    Abstract [en]

    Conventional dynamic atomic force microscopy (AFM) can be extended to bimodal and multimodal AFM in which the cantilever is simultaneously excited at two or more resonance frequencies. Such excitation schemes result in one additional amplitude and phase images for each driven resonance, and potentially convey more information about the surface under investigation. Here we present a theoretical basis for using this information to approximate the parameters of a tip-surface interaction model. The theory is verified by simulations with added noise corresponding to room-temperature measurements.

  • 10.
    Geilhufe, Matthias
    et al.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Borysov, Stanislav
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Bouhon, A.
    Balatsky, Alexander V.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Data Mining for Three-Dimensional Organic Dirac Materials: Focus on Space Group2017In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, no 1, article id 7298Article in journal (Refereed)
    Abstract [en]

    We combined the group theory and data mining approach within the Organic Materials Database that leads to the prediction of stable Dirac-point nodes within the electronic band structure of three-dimensional organic crystals. We find a particular space group P212121 (#19) that is conducive to the Dirac nodes formation. We prove that nodes are a consequence of the orthorhombic crystal structure. Within the electronic band structure, two different kinds of nodes can be distinguished: 8-fold degenerate Dirac nodes protected by the crystalline symmetry and 4-fold degenerate Dirac nodes protected by band topology. Mining the Organic Materials Database, we present band structure calculations and symmetry analysis for 6 previously synthesized organic materials. In all these materials, the Dirac nodes are well separated within the energy and located near the Fermi surface, which opens up a possibility for their direct experimental observation.

  • 11. Geilhufe, R. Matthias
    et al.
    Borysov, Stanislav S.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Kalpakchi, Dmytro
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Balatsky, Alexander V.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Towards novel organic high-T-c superconductors: Data mining using density of states similarity search2018In: Physical Review Materials, ISSN 2475-9953, Vol. 2, no 2, article id 024802Article in journal (Refereed)
    Abstract [en]

    Identifying novel functional materials with desired key properties is an important part of bridging the gap between fundamental research and technological advancement. In this context, high-throughput calculations combinedwith data-mining techniques highly accelerated this process in different areas of research during the past years. The strength of a data-driven approach for materials prediction lies in narrowing down the search space of thousands of materials to a subset of prospective candidates. Recently, the open-access organic materials database OMDBwas released providing electronic structure data for thousands of previously synthesized three-dimensional organic crystals. Based on the OMDB, we report about the implementation of a novel density of states similarity search tool which is capable of retrieving materials with similar density of states to a reference material. The tool is based on the approximate nearest neighbor algorithm as implemented in the ANNOY library and can be applied via the OMDB web interface. The approach presented here is wide ranging and can be applied to various problems where the density of states is responsible for certain key properties of a material. As the first application, we report about materials exhibiting electronic structure similarities to the aromatic hydrocarbon p-terphenyl which was recently discussed as a potential organic high-temperature superconductor exhibiting a transition temperature in the order of 120 K under strong potassium doping. Although the mechanism driving the remarkable transition temperature remains under debate, we argue that the density of states, reflecting the electronic structure of a material, might serve as a crucial ingredient for the observed high T-c. To provide candidates which might exhibit comparable properties, we present 15 purely organic materials with similar features to p-terphenyl within the electronic structure, which also tend to have structural similarities with p-terphenyl such as space group symmetries, chemical composition, and molecular structure. The experimental verification of these candidates might lead to a better understanding of the underlying mechanism in case similar superconducting properties are revealed.

  • 12.
    Geilhufe, R. Matthias
    et al.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Bouhon, Adrien
    Borysov, Stanislav S.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Balatsky, Alexander V.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
    Three-dimensional organic Dirac-line materials due to nonsymmorphic symmetry: A data mining approach2017In: Physical Review B, ISSN 2469-9950, E-ISSN 2469-9969, Vol. 95, no 4, article id 041103Article in journal (Refereed)
    Abstract [en]

    A datamining study of electronic Kohn-Sham band structures was performed to identify Dirac materials within the Organic Materials Database. Out of that, the three-dimensional organic crystal 5,6-bis(trifluoromethyl)-2-methoxy-1H-1,3-diazepine was found to host different Dirac-line nodes within the band structure. From a group theoretical analysis, it is possible to distinguish between Dirac-line nodes occurring due to twofold degenerate energy levels protected by the monoclinic crystalline symmetry and twofold degenerate accidental crossings protected by the topology of the electronic band structure. The obtained results can be generalized to all materials having the space group P2(1)/c (No. 14, C-2h(5)) by introducing three distinct topological classes.

  • 13. Rodrigues, Filipe
    et al.
    Borysov, Stanislav S.
    KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Singapore-MIT Alliance for Research and Technology, Singapore; Stockholm Univ, Roslagstullsbacken 23, SE-10691 Stockholm, Sweden.
    Ribeiro, Bernardete
    Pereira, Francisco C.
    A Bayesian Additive Model for Understanding Public Transport Usage in Special Events2017In: IEEE Transaction on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, E-ISSN 1939-3539, Vol. 39, no 11, p. 2113-2126Article in journal (Refereed)
    Abstract [en]

    Public special events, like sports games, concerts and festivals are well known to create disruptions in transportation systems, often catching the operators by surprise. Although these are usually planned well in advance, their impact is difficult to predict, even when organisers and transportation operators coordinate. The problem highly increases when several events happen concurrently. To solve these problems, costly processes, heavily reliant on manual search and personal experience, are usual practice in large cities like Singapore, London or Tokyo. This paper presents a Bayesian additive model with Gaussian process components that combines smart card records from public transport with context information about events that is continuously mined from the Web. We develop an efficient approximate inference algorithm using expectation propagation, which allows us to predict the total number of public transportation trips to the special event areas, thereby contributing to a more adaptive transportation system. Furthermore, for multiple concurrent event scenarios, the proposed algorithm is able to disaggregate gross trip counts into their most likely components related to specific events and routine behavior. Using real data from Singapore, we show that the presented model outperforms the best baseline model by up to 26 percent in R-2 and also has explanatory power for its individual components.

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