nils-herrmann/clean_scirepeval huggingface dataset:
A 2D nearest-neighbor quantum architecture for factoring in polylogarithmic depth

We contribute a 2D nearest-neighbor quantum architecture for Shor's algorithm to factor an $n$-bit number in $O(\log^2(n))$ depth. Our implementation uses parallel phase estimation, constant-depth fanout and teleportation, and constant-depth carry-save modular addition. We derive upper bounds on the circuit resources of our architecture under a new 2D nearest-neighbor model which allows a classical controller and parallel, communicating modules. We also contribute a novel constant-depth circuit for unbounded quantum unfanout in our new model. Finally, we provide a comparison to all previous nearest-neighbor factoring implementations. Our circuit results in an exponential improvement in nearest-neighbor circuit depth at the cost of a polynomial increase in circuit size and width.
Box-counting fractal strings, zeta functions, and equivalent forms of Minkowski dimension

We discuss a number of techniques for determining the Minkowski dimension of bounded subsets of some Euclidean space of any dimension, including: the box-counting dimension and equivalent definitions based on various box-counting functions; the similarity dimension via the Moran equation (at least in the case of self-similar sets); the order of the (box-)counting function; the classic result on compact subsets of the real line due to Besicovitch and Taylor, as adapted to the theory of fractal strings; and the abscissae of convergence of new classes of zeta functions. Specifically, we define box-counting zeta functions of infinite bounded subsets of Euclidean space and discuss results pertaining to distance and tube zeta functions. Appealing to an analysis of these zeta functions allows for the development of theories of complex dimensions for bounded sets in Euclidean space, extending techniques and results regarding (ordinary) fractal strings obtained by the first author and van Frankenhuijsen.
Towards a Book Publishers Citation Reports. First approach using the Book Citation Index

The absence of books and book chapters in the Web of Science Citation Indexes (SCI, SSCI and A&HCI) has always been considered an important flaw but the Thomson Reuters ‘Book Citation Index’ database was finally available in October of 2010 indexing 29,618 books and 379,082 book chapters. The Book Citation Index opens a new window of opportunities for analyzing Humanities and Social Sciences from a bibliometric point of view. The main objective of this article is to analyze different impact indicators referred to the scientific publishers included in the Book Citation Index for the Social Sciences and Humanities fields during 2006-2011. This way we construct what we have called the ‘Book Publishers Citation Reports’. For this, we present a total of 19 rankings according to the different disciplines in Humanities & Arts and Social Sciences & Law with six indicators for scientific publishers.
Numerical Relativity as a Tool for Studying the Early Universe

Numerical simulations are becoming a more effective tool for conducting detailed investigations into the evolution of our universe. In this paper, we show how the framework of numerical relativity can be used for studying cosmological models. The author is working to develop a large-scale simulation of the dynamical processes in the early universe. These take into account interactions of dark matter, scalar perturbations, gravitational waves, magnetic fields, and turbulent plasma. The code described in this report is a GRMHD code based on the Cactus framework and is structured to utilize one of several different differencing methods chosen at run-time. It is being developed and tested on the University of Houston’s Maxwell cluster.
Traveling the silk road: a measurement analysis of a large anonymous online marketplace

We perform a comprehensive measurement analysis of Silk Road, an anonymous, international online marketplace that operates as a Tor hidden service and uses Bitcoin as its exchange currency. We gather and analyze data over eight months between the end of 2011 and 2012, including daily crawls of the marketplace for nearly six months in 2012. We obtain a detailed picture of the type of goods sold on Silk Road, and of the revenues made both by sellers and Silk Road operators. Through examining over 24,400 separate items sold on the site, we show that Silk Road is overwhelmingly used as a market for controlled substances and narcotics, and that most items sold are available for less than three weeks. The majority of sellers disappears within roughly three months of their arrival, but a core of 112 sellers has been present throughout our measurement interval. We evaluate the total revenue made by all sellers, from public listings, to slightly over USD 1.2 million per month; this corresponds to about USD 92,000 per month in commissions for the Silk Road operators. We further show that the marketplace has been operating steadily, with daily sales and number of sellers overall increasing over our measurement interval. We discuss economic and policy implications of our analysis and results, including ethical considerations for future research in this area.
Weighted Kolmogorov-Smirnov test: accounting for the tails.

Accurate goodness-of-fit tests for the extreme tails of empirical distributions is a very important issue, relevant in many contexts, including geophysics, insurance, and finance. We have derived exact asymptotic results for a generalization of the large-sample Kolmogorov-Smirnov test, well suited to testing these extreme tails. In passing, we have rederived and made more precise the approximate limit solutions found originally in unrelated fields, first in [L. Turban,  (1992)] and later in [P. L. Krapivsky and S. Redner,  (1996)].
Directed Random Markets: Connectivity determines Money

Boltzmann–Gibbs (BG) distribution arises as the statistical equilibrium probability distribution of money among the agents of a closed economic system where random and undirected exchanges are allowed. When considering a model with uniform savings in the exchanges, the final distribution is close to the gamma family. In this paper, we implement these exchange rules on networks and we find that these stationary probability distributions are robust and they are not affected by the topology of the underlying network. We introduce a new family of interactions: random but directed ones. In this case, it is found the topology to be determinant and the mean money per economic agent is related to the degree of the node representing the agent in the network. The relation between the mean money per economic agent and its degree is shown to be linear.
Existence of an information unit as a postulate of quantum theory

Despite the enormous success of quantum theory, its significance and meaning are still being debated. In particular, the standard postulates of quantum theory are abstract mathematical statements in terms of complex vectors, self-adjoint operators, etc., and as such they lack a clear physical interpretation. For this reason, it is difficult to assess what they say about the structure of the physical world. In this article, we prove that quantum theory can be formulated through four very simple postulates, each having a direct physical and intuitive meaning. Also, our postulates unveil some connections between physics and information that remain hidden in the standard postulates, thus supporting Wheeler’s hypothesis “it from bit.” Does information play a significant role in the foundations of physics? Information is the abstraction that allows us to refer to the states of systems when we choose to ignore the systems themselves. This is only possible in very particular frameworks, like in classical or quantum theory, or more generally, whenever there exists an information unit such that the state of any system can be reversibly encoded in a sufficient number of such units. In this work, we show how the abstract formalism of quantum theory can be deduced solely from the existence of an information unit with suitable properties, together with two further natural assumptions: the continuity and reversibility of dynamics, and the possibility of characterizing the state of a composite system by local measurements. This constitutes a set of postulates for quantum theory with a simple and direct physical meaning, like the ones of special relativity or thermodynamics, and it articulates a strong connection between physics and information.
Dynamics of fashion: The case of given names

We analyze the social mechanisms that shape the popularity rise and fall of the names given to newborn babies. During the initial stage, popularity increases by imitation. As the people with the same name grow in number, however, its usage is inhibited and eventually decays. This process mirrors the dynamics of fashion fads. An activator-inhibitor dynamical model for the interplay of the population bearing a name and the expecting couples wishing to give it to their children provides a satisfactory explanation of historical data from the Canadian province of Quebec during the twentieth century.
Comet P/2010 TO20 LINEAR-Grauer as a Mini-29P/SW1

Discovered in October 2010 by the LINEAR survey, P/2010 TO20 LINEAR-Grauer (LG) was initially classified as an inert Jupiter Trojan. Subsequent observations obtained in October 2011 revealed LG to be a Jupiter-family comet. LG has one of the largest perihelia (q=5.1 AU) and lowest eccentricities (e=0.09) of the known JFCs. We report on observations of LG taken on 29 October 2011 and numerical simulations of its orbital evolution. Analysis of our data reveals that LG has a small nucleus (<3 km in radius) with broadband colours (B-R=0.99+/-0.06 mag, V-R=0.47+/-0.06 mag) typical of JFCs. We find a model dependent mass-loss rate close to 100 kg/s, most likely powered by water-ice sublimation. Our numerical simulation indicate that the orbit of LG is unstable on very short (10 to 100 yr) timescales and suggest this object has recently evolved into its current location from a more distant, Centaur-type orbit. The orbit, dynamics and activity of LG share similarities with the well known case of comet 29P/Schwassmann-Wachmann 1.
Does GDP measure growth in the economy or simply growth in the money supply

Gross Domestic Product(GDP) is a widely used measurement of economic growth representing the market value of all final goods and services produced by a country within a given time. In this paper we question the assumption that GDP measures production, and suggest that in reality it merely captures changes in the rate of expansion of the money supply used to measure the price data it is derived from. We first review the Quantity Theory of Money $MV=PT$, and show that the Velocity of Circulation of Money(V) does not affect the price level as claimed, as it is also a factor of the quantity of transactions(T). It then follows directly that attempts to measure total production from any form of price data as the GDP measurement does, will necessarily be confounded by the inverse relationship between prices and the quantity of production, which requires that as the total quantity of production increases, prices will drop. Finally, in support of this claim we present an empirical analysis of the GDP of nine countries and one currency union, showing that when normalized for money supply growth GDP measures have been uniformly shrinking over the last 20 years, and discuss the possible reasons for this behaviour.
Wisdom of the Crowd: Incorporating Social Influence in Recommendation Models

Recommendation systems have received considerable attention recently. However, most research has been focused on improving the performance of collaborative filtering (CF) techniques. Social networks, indispensably, provide us extra information on people's preferences, and should be considered and deployed to improve the quality of recommendations. In this paper, we propose two recommendation models, for individuals and for groups respectively, based on social contagion and social influence network theory. In the recommendation model for individuals, we improve the result of collaborative filtering prediction with social contagion outcome, which simulates the result of information cascade in the decision-making process. In the recommendation model for groups, we apply social influence network theory to take interpersonal influence into account to form a settled pattern of disagreement, and then aggregate opinions of group members. By introducing the concept of susceptibility and interpersonal influence, the settled rating results are flexible, and inclined to members whose ratings are "essential".
P = NP

The present paper proves that P=NP. The proof, presented in this paper, is a constructive one: The program of a polynomial time deterministic multi-tape Turing machine M〈∃AcceptingPath〉, which determines if there exists an accepting computation path of a polynomial time non-deterministic single-tape Turing machine M〈NP 〉, is constructed explicitly (machine M〈∃AcceptingPath〉 is different for each machine M〈NP 〉). The features of machine M〈∃AcceptingPath〉 are as follows: 1) the input of machine M〈∃AcceptingPath〉 does not contain any encoded program of machine M〈NP 〉, but the program of machine M〈∃AcceptingPath〉 contains implicitly the program of machine M〈NP 〉; 2) machine M〈∃AcceptingPath〉 is based on reduction L ≤m LP (Linear Programming) instead of reductions L ≤m 3-CNF-SAT ≤ P m ILP (Integer Linear Programming) which are commonly used, wherein language L ∈NP, machine M〈NP 〉 decides L, and ≤m is polynomial time many-one reduction; reduction L ≤m 3-CNF-SAT is not used in the present paper; 3) the reduction to problem LP is a set of reductions L ≤m TCPE ≤ P m LP in fact wherein TCPE (Tape-Consistent Path Existence Problem) is a NP-complete problem defined in the present paper; 4) problem TCPE is reducible to a similar problem TCPE〈1〉 that is a special case of problems mixed-DHORN-SAT (dual Horn) and linear-CNF-SAT; problem TCPE〈1〉 is polynomial time reducible to problem ILP; unlike problem TCPE〈1〉, a polynomial time algorithm is constructed for problem TCPE in the present paper; 5) to determine if there exists an accepting computation path, it is sufficient to find a fractional solution of the resulting linear program; 6) the set of the accepting computation paths of machine M〈NP 〉 is considered as a subset of a more general set of all the computation paths in the acyclic control flow graph of polynomial size of a deterministic computer program that writes values to the tape cells and reads values from the tape cells; 7) reduction L ≤m TCPE is based on the results of reaching definitions analysis for the deterministic computer program and on the notion of network flow; 8) the resulting linear program does not express any combinatorial optimization problem polytope (like TSP polytope); 9) both to accept and reject the input of machine M〈NP 〉, polynomial t(n), an upper bound of the time complexity of machineM〈NP 〉, is not used in the program of machineM〈∃AcceptingPath〉; 10) machine M〈∃AcceptingPath〉 is a pure mathematical construction; the proof presented in the paper is not based on physics theories (but it seems it should relate to them in some a way). SergeyV.Yakhontov: Ph.D. in Theoretical Computer Science, Dept. of Computer Science, Faculty of Mathematics and Mechanics, Saint Petersburg State University, Saint Petersburg, Russian Federation; e-mail: SergeyV.Yakhontov@gmail.com, S.Yakhontov@spbu.ru; phone: +7-911-966-84-30; personal Web page: https://sites.google.com/site/sergeyvyakhontov/; current status of the paper: https://sites.google.com/site/sergeyvyakhontov/home/peqnp-paper-status/; 23-Jan-2017
Recklessly Approximate Sparse Coding

It has recently been observed that certain extremely simple feature encoding techniques are able to achieve state of the art performance on several standard image classification benchmarks including deep belief networks, convolutional nets, factored RBMs, mcRBMs, convolutional RBMs, sparse autoencoders and several others. Moreover, these "triangle" or "soft threshold" encodings are ex- tremely efficient to compute. Several intuitive arguments have been put forward to explain this remarkable performance, yet no mathematical justification has been offered. 
The main result of this report is to show that these features are realized as an approximate solution to the a non-negative sparse coding problem. Using this connection we describe several variants of the soft threshold features and demonstrate their effectiveness on two image classification benchmark tasks.
Mathematical definition, mapping, and detection of (anti)fragility

We provide a mathematical definition of fragility and antifragility as negative or positive sensitivity to a semi-measure of dispersion and volatility (a variant of negative or positive "vega") and examine the link to nonlinear effects. We integrate model error (and biases) into the fragile or antifragile context. Unlike risk, which is linked to psychological notions such as subjective preferences (hence cannot apply to a coffee cup) we offer a measure that is universal and concerns any object that has a probability distribution (whether such distribution is known or, critically, unknown). We propose a detection of fragility, robustness, and antifragility using a single "fast-and-frugal", model-free, probability free heuristic that also picks up exposure to model error. The heuristic lends itself to immediate implementation, and uncovers hidden risks related to company size, forecasting problems, and bank tail exposures (it explains the forecasting biases). While simple to implement, it improves on stress testing and bypasses the cillib flaws in Value-at-Risk.
One Permutation Hashing for Efficient Search and Learning

Recently, the method of b-bit minwise hashing has been applied to large-scale linear learning and sublinear time near-neighbor search. The major drawback of minwise hashing is the expensive preprocessing cost, as the method requires applying (e.g.,) k=200 to 500 permutations on the data. The testing time can also be expensive if a new data point (e.g., a new document or image) has not been processed, which might be a significant issue in user-facing applications. 
We develop a very simple solution based on one permutation hashing. Conceptually, given a massive binary data matrix, we permute the columns only once and divide the permuted columns evenly into k bins; and we simply store, for each data vector, the smallest nonzero location in each bin. The interesting probability analysis (which is validated by experiments) reveals that our one permutation scheme should perform very similarly to the original (k-permutation) minwise hashing. In fact, the one permutation scheme can be even slightly more accurate, due to the "sample-without-replacement" effect. 
Our experiments with training linear SVM and logistic regression on the webspam dataset demonstrate that this one permutation hashing scheme can achieve the same (or even slightly better) accuracies compared to the original k-permutation scheme. To test the robustness of our method, we also experiment with the small news20 dataset which is very sparse and has merely on average 500 nonzeros in each data vector. Interestingly, our one permutation scheme noticeably outperforms the k-permutation scheme when k is not too small on the news20 dataset. In summary, our method can achieve at least the same accuracy as the original k-permutation scheme, at merely 1/k of the original preprocessing cost.
General Balance Functions in the Theory of Interest

We develop an axiomatic theory of balance functions (future value functions) in the theory of interest that is derived from financial considerations and which applies to general regulated payment streams, including continuous payment streams. Balance functions exist and are unique up to an initial choice of deposit and investment accumulation functions. In terms of these balance functions we also construct a unique internal rate of return for each regulated payment stream that is an investment project. This theory subsumes and clarifies previous theories of internal rate of return functions for more specialized classes of investment projects.
Comment on "Casimir force and in situ surface potential measurements on nanomembranes".

Recently D. Garcia-Sanches, K. Y. Fong, H. Bhaskaran, S. Lamoreaux, and H. X. Tang [ (2012)] claimed that the frequency shift of an oscillator under the influence of the residual electric and Casimir forces is best described by the Drude model approach to the Casimir force and excludes the plasma model approach. We demonstrate that calculations in support of this claim are performed incorrectly and that the measured data are in strong disagreement with both theoretical approaches to the Casimir force, thus, suggesting the presence of an unaccounted systematic error in the data.
Long range order in gauge theories: Deformed QCD as a toy model

We study a number of different ingredients, related to long range order observed in lattice QCD simulations, using a simple "deformed QCD" model. This model is a weakly coupled gauge theory, which however has all the relevant crucial elements allowing us to study difficult and nontrivial problems which are known to be present in real strongly coupled QCD. In the present study, we want to understand the physics of long range order in form of coherent low dimensional vacuum configurations observed in Monte Carlo lattice simulations. We demonstrate the presence of double-layer domain wall structures in the deformed QCD, and study their interaction with localized topological monopoles. Furthermore, we show that there is in fact an attractive interaction between the two, such that the monopole favors a position within the domain wall.
Risk minimizing of derivatives via dynamic g-expectation and related topics

In this paper, we investigate risk minimization problem of derivatives based on non-tradable underlyings by means of dynamic g-expectations which are slight different from conditional g-expectations. In this framework, inspired by  and [16], we introduce risk indifference price, marginal risk price and derivative hedge and obtain their corresponding explicit expressions. The interesting thing is that their expressions have nothing to do with nonlinear generator g, and one deep reason for this is due to the completeness of financial market. By giving three useful special risk minimization problems, we obtain the explicit optimal strategies with initial wealth involved, demonstrate some qualitative analysis among optimal strategies, risk aversion parameter and market price of risk, together with some economic interpretations.
The Date of Interbreeding between Neandertals and Modern Humans

Comparisons of DNA sequences between Neandertals and present-day humans have shown that Neandertals share more genetic variants with non-Africans than with Africans. This could be due to interbreeding between Neandertals and modern humans when the two groups met subsequent to the emergence of modern humans outside Africa. However, it could also be due to population structure that antedates the origin of Neandertal ancestors in Africa. We measure the extent of linkage disequilibrium (LD) in the genomes of present-day Europeans and find that the last gene flow from Neandertals (or their relatives) into Europeans likely occurred 37,000–86,000 years before the present (BP), and most likely 47,000–65,000 years ago. This supports the recent interbreeding hypothesis and suggests that interbreeding may have occurred when modern humans carrying Upper Paleolithic technologies encountered Neandertals as they expanded out of Africa.