Search

On-chip emitters that generate single and entangled photons are essential for photonic quantum information processing technologies. Semiconductor quantum dots (QDs) are attractive candidates that emit high-quality quantum states of light, however at a rate limited by their spontaneous radiative lifetime. In this study, we utilize the Purcell effect to demonstrate up to a 38-fold enhancement in the emission rate of InAs QDs by coupling them to metal-clad GaAs nanopillars. These cavities, featuring a sub-wavelength mode volume of 4.5x10-4 ({\lambda}/n)3 and quality factor of 62, enable Purcell-enhanced single-photon emission across a large bandwidth of 15 nm with a multi-photon emission probability as low as 0.5 %. The broadband nature of the cavity eliminates the need for implementing tuning mechanisms typically required to achieve QD-cavity resonance, thus relaxing fabrication constraints. Ultimately, this QD-cavity architecture represents a significant stride towards developing solid-state quantum emitters generating near-ideal single-photon states at GHz-level repetition rates., Comment: Minor changes have been made to the manuscript after v1: Title has been modified. Reference number 42 and 62 updated. The manuscript has been edited to improve the general readability of the text

The problem of quickest change detection is studied in the context of detecting an arbitrary unknown mean-shift in multiple independent Gaussian data streams. The James-Stein estimator is used in constructing detection schemes that exhibit strong detection performance both asymptotically and non-asymptotically. First, a James-Stein-based extension of the recently developed windowed CuSum test is introduced. Our results indicate that the proposed scheme constitutes a uniform improvement over its typical maximum likelihood variant. That is, the proposed James-Stein version achieves a smaller detection delay simultaneously for all possible post-change parameter values and every false alarm rate constraint, as long as the number of parallel data streams is greater than three. Additionally, an alternative detection procedure that utilizes the James-Stein estimator is shown to have asymptotic detection delay properties that compare favorably to existing tests. The second-order term of the asymptotic average detection delay is reduced in a predefined low-dimensional subspace of the parameter space, while second-order asymptotic minimaxity is preserved. The results are verified in simulations, where the proposed schemes are shown to achieve smaller detection delays compared to existing alternatives, especially when the number of data streams is large., Comment: 27 pages, 5 figures

We present the first study of coherent exclusive quarkonium ($J/\psi$, $\Upsilon$) photoproduction in ultraperipheral nucleus-nucleus collisions (UPCs) at the LHC in the framework of collinear factorization and next-to-leading order (NLO) perturbative QCD (pQCD). We make NLO predictions for the $J/\psi$ and $\Upsilon$ rapidity distributions for lead (Pb) and oxygen (O) beams, and quantify their dependence on the factorization/renormalization scale, nuclear parton distribution functions (PDFs) and their uncertainties, and on differences between nuclear PDFs and generalized parton distribution functions (GPDs). We show that within the PDF-originating uncertainties our approach provides a good description of the available $J/\psi$ photoproduction data in Pb+Pb UPCs at the LHC but that the scale uncertainty is significant. We demonstrate that at NLO pQCD the quark contributions are important in the $J/\psi$ case but that gluons clearly dominate the $\Upsilon$ cross sections. We also study how the scale dependence could be tamed by considering O+O/Pb+Pb ratios of the exclusive $J/\psi$ UPC cross sections, and how HERA and p+p/Pb LHC data can help in obtaining better-controlled NLO predictions in the $\Upsilon$ case., Comment: 6 pages, 5 figures, contributed talk by K.J.E. at the 11th International Conference on Hard and Electromagnetic Probes of High-Energy Nuclear Collisions, Hard Probes 2023, 26-31 March 2023, Aschaffenburg, Germany

This paper studies the relationship between basketball teams' four factors and efficiency ratings as defined by Oliver (2004). The paper introduces an equation showing how a team's four factors in conjunction with its field goal and free throw percentages can be used to calculate its offensive rating. Moreover, the substitution of defensive four factors into the equation allows for the calculation of defensive and net ratings. To incorporate recent trends in the NBA, the paper updates the estimation for the relative frequency of possession-ending free throws which are needed to estimate the number of possessions from box score data. Sensitivity analysis of the offensive rating is performed in order to better understand the relative importance of the four factors. By examining partial derivatives of the offensive rating, the paper quantifies the marginal impact of small changes in the offensive and defensive four factors on offensive, defensive, and net ratings. Most importantly it is observed that the relationship between the four factors and efficiency ratings is non-linear and the individual factors' effect on the ratings depends on the values of the other factors. The paper also includes examples from NBA seasons spanning 1996-97 through 2022-23., Comment: 30 pages, 10 figures, to be submitted

We present predictions for the rapidity-differential cross sections of exclusive $\Upsilon$ photoproduction in ultraperipheral collisions (UPCs) of lead ions at the Large Hadron Collider (LHC). We work in the framework of collinear factorization at next-to-leading order (NLO) in perturbative QCD, modeling the generalized parton distributions (GPDs) through the Shuvaev transform of nuclear parton distribution functions (nPDFs). While the effects due to the GPD modeling turn out to be small, the direct NLO predictions still carry significant nPDF-originating uncertainties and depend strongly on the choices of the factorization and renormalization scales. To tame the scale dependence and to account for the fact that the NLO calculations generally underpredict the photoproduction measurements on protons, we also present alternative, data-driven predictions. In this approach the underlying photoproduction cross sections on lead are found by combining their nuclear modifications calculated at NLO with the measured photoproduction cross sections on protons. The data-driven strategy reduces the uncertainties associated with the scale choices, and essentially eliminates the effects of GPD modeling thereby leaving the cross sections sensitive mainly to the input nPDFs. Our estimates indicate that the process is measurable in ${\rm Pb}+{\rm Pb}$ collisions at the LHC., Comment: 14 pages

We present predictions for the cross sections of coherent $J/\psi$ photoproduction in lead-lead and oxygen-oxygen ultraperipheral collisions (UPCs) as a function of the $J/\psi$ rapidity at the LHC in the framework of collinear factorization at next-to-leading order (NLO) in perturbative QCD. Taking generalized parton distribution functions in their forward limit and using the EPPS21, nNNPDF3.0, and nCTEQ15WZSIH nuclear parton distribution functions, we update our recent results for Pb-Pb collisions, make detailed predictions for O-O collisions for several beam energy configurations, and examine the ratio of O-O and Pb-Pb UPC cross sections. We show that the latter observable allows one to significantly reduce the scale uncertainty of NLO predictions for this process., Comment: 21 pages, 18 figures. Revised version with corrected error bands for nNNPDF3.0 results in Figs. 4 and 15-18. Matches the published Erratum, Phys. Rev. C 108, 069901 (2023)

This work extends the results of [Garde and Hyv\"onen, Math. Comp. 91:1925-1953] on series reversion for Calder\'on's problem to the case of realistic electrode measurements, with both the internal admittivity of the investigated body and the contact admittivity at the electrode-object interfaces treated as unknowns. The forward operator, sending the internal and contact admittivities to the linear electrode current-to-potential map, is first proven to be analytic. A reversion of the corresponding Taylor series yields a family of numerical methods of different orders for solving the inverse problem of electrical impedance tomography, with the possibility to employ different parametrizations for the unknown internal and boundary admittivities. The functionality and convergence of the methods is established only if the employed finite-dimensional parametrization of the unknowns allows the Fr\'echet derivative of the forward map to be injective, but we also heuristically extend the methods to more general settings by resorting to regularization motivated by Bayesian inversion. The performance of this regularized approach is tested via three-dimensional numerical examples based on simulated data. The effect of modeling errors related to electrode shapes and contact admittances is a focal point of the numerical studies., Comment: 26 pages, 4 figures

We present the first study of rapidity-differential cross sections of coherent exclusive $J/\psi$ photoproduction in heavy-ion ultraperipheral collisions (UPCs) at the LHC, $\text{d}\sigma(\text{Pb}+\text{Pb}\rightarrow \text{Pb}+J/\psi+\text{Pb})/\text{d}y$, to NLO in collinear factorisation. Taking the generalised parton distributions as their forward limit counterparts, the NLO contributions in the cross sections are quantified and we show that the real part of the amplitude and quark-PDF contributions must not be neglected. We further evaluate the uncertainties arising from the scale-choice at both LO and NLO, and compare our results with exclusive $J/\psi$ photoproduction data in Pb+Pb UPCs from LHC. The scale dependence in $\text{d}\sigma(\text{Pb}+\text{Pb}\rightarrow \text{Pb}+J/\psi+\text{Pb})/\text{d}y$ is sizable, but we can find a scale-choice at NLO that reproduces the Pb+Pb UPC data at both Run 1 and Run 2 collision energies. This process has traditionally been suggested to be a direct probe of nuclear gluon distributions. We show that the situation changes rather dramatically from LO to NLO, where the interplay of both gluon and quark contributions, and in particular their relative signs, play a significant role. We end with some concluding remarks about the outlook of this observable within a tamed collinear factorisation., Comment: 5 pages, 4 figures. Proceedings of the XXIX International Workshop on Deep-Inelastic Scattering and Related Subjects (DIS2022)

We present the first next-to-leading-order (NLO) perturbative QCD (pQCD) study of rapidity-differential cross sections of coherent exclusive photoproduction of $J/\psi$ mesons in heavy-ion ultraperipheral collisions (UPCs) at the LHC, $d\sigma/dy(\text{Pb} + \text{Pb} \rightarrow \text{Pb} + J/\psi + \text{Pb})$. For this, we account for the photon-nucleon NLO cross sections at the forward limit, the $t$ dependence using a standard nuclear form factor, and the photon fluxes of the colliding nuclei. Approximating the generalized parton distributions with their forward-limit parton distribution functions (PDFs), we quantify the NLO contributions in the cross sections, show that the real part of the amplitude and quark-PDF contributions must not be neglected, quantify the uncertainties arising from the scale-choice and PDFs, and compare our results with ALICE, CMS and LHCb $J/\psi$ photoproduction data in Pb+Pb UPCs, exclusive $J/\psi$ photoproduction data from HERA, and LHCb data in p+p. The scale dependence in $d\sigma/dy(\text{Pb} + \text{Pb} \rightarrow \text{Pb} + J/\psi + \text{Pb})$ is significant, but we can find a scale-choice that reproduces the Pb+Pb UPC data both at 2.76 and 5.02 TeV collision energies. This process has traditionally been suggested to be a direct probe of nuclear gluon distributions. We show that the situation changes rather dramatically from LO to NLO: the NLO cross sections reflect the nuclear effects of both gluons and quarks in a complicated manner where the relative signs of the LO and NLO terms in the amplitude play a significant role., Comment: 22 pages, 13 figures

Determining the sensitivity of the posterior to perturbations of the prior and likelihood is an important part of the Bayesian workflow. We introduce a practical and computationally efficient sensitivity analysis approach using importance sampling to estimate properties of posteriors resulting from power-scaling the prior or likelihood. On this basis, we suggest a diagnostic that can indicate the presence of prior-data conflict or likelihood noninformativity and discuss limitations to this power-scaling approach. The approach can be easily included in Bayesian workflows with minimal effort by the model builder and we present an implementation in our new R package priorsense. We further demonstrate the workflow on case studies of real data using models varying in complexity from simple linear models to Gaussian process models., Comment: 31 pages, 15 (+5 suppl) figures

Rapid detection of spatial events that propagate across a sensor network is of wide interest in many modern applications. In particular, in communications, radar, IoT, environmental monitoring, and biosurveillance, we may observe propagating fields or particles. In this paper, we propose Bayesian sequential single and multiple change-point detection procedures for the rapid detection of such phenomena. Using a dynamic programming framework we derive the structure of the optimal single-event quickest detection procedure, which minimizes the average detection delay (ADD) subject to a false alarm probability upper bound. The multi-sensor system configuration is arbitrary and sensors may be mobile. In the rare event regime, the optimal procedure converges to a more practical threshold test on the posterior probability of the change point. A convenient recursive computation of this posterior probability is derived by using the propagation characteristics of the spatial event. The ADD of the posterior probability threshold test is analyzed in the asymptotic regime, and specific analysis is conducted in the setting of detecting random Gaussian signals affected by path loss. Then, we show how the proposed procedure is easy to extend for detecting multiple propagating spatial events in parallel in a multiple hypothesis testing setting. A method that provides strict false discovery rate (FDR) control is proposed. In the simulation section, it is demonstrated that exploiting the spatial properties of the event decreases the ADD compared to procedures that do not utilize this information, even under model mismatch., Comment: 13 pages, 5 figures

Two-dimensional materials and their mechanical properties are known to be profoundly affected by rippling deformations. However, although ripples are fairly well understood, less is known about their origin and controlled modification. Here, motivated by recent reports of laser-controlled creation of line defects in graphene, we investigate how line defects could be used to control rippling in graphene and other two-dimensional materials. By sequential multi-scale coupling of density-functional tight-binding and continuum elasticity simulations, we quantify the amount of rippling when the number and the cumulative length of the line defects increase. Simulations show that elastic sheets with networks of line defects create rippling that induces considerable out-of-plane rigidification and in-plane softening with non-linear elastic behavior. We hope that these insights help to guide experimental attempts to modify the mechanical properties of graphene and other two-dimensional materials., Comment: 8 pages, 4 figures

Many data sets contain an inherent multilevel structure, for example, because of repeated measurements of the same observational units. Taking this structure into account is critical for the accuracy and calibration of any statistical analysis performed on such data. However, the large number of possible model configurations hinders the use of multilevel models in practice. In this work, we propose a flexible framework for efficiently assessing differences between the levels of given grouping variables in the data. The assessed group heterogeneity is valuable in choosing the relevant group coefficients to consider in a multilevel model. Our empirical evaluations demonstrate that the framework can reliably identify relevant multilevel components in both simulated and real data sets.

In many modern applications, large-scale sensor networks are used to perform statistical inference tasks. In this paper, we propose Bayesian methods for multiple change-point detection using a sensor network in which a fusion center (FC) can receive a data stream from each sensor. Due to communication limitations, the FC monitors only a subset of the sensors at each time slot. Since the number of change points can be high, we adopt the false discovery rate (FDR) criterion for controlling the rate of false alarms, while minimizing the average detection delay (ADD). We propose two Bayesian detection procedures that handle the communication limitations by monitoring the subset of the sensors with the highest posterior probabilities of change points having occurred. This monitoring policy aims to minimize the delay between the occurrence of each change point and its declaration using the corresponding posterior probabilities. One of the proposed procedures is more conservative than the second one in terms of having lower FDR at the expense of higher ADD. It is analytically shown that both procedures control the FDR under a specified tolerated level and are also scalable in the sense that they attain an ADD that does not increase asymptotically with the number of sensors. In addition, it is demonstrated that the proposed detection procedures are useful for trading off between reduced ADD and reduced average number of observations drawn until discovery. Numerical simulations are conducted for validating the analytical results and for demonstrating the properties of the proposed procedures., Comment: 13 pages, 10 figures

For nonlinear supervised learning models, assessing the importance of predictor variables or their interactions is not straightforward because it can vary in the domain of the variables. Importance can be assessed locally with sensitivity analysis using general methods that rely on the model's predictions or their derivatives. In this work, we extend derivative based sensitivity analysis to a Bayesian setting by differentiating the R\'enyi divergence of a model's predictive distribution. By utilising the predictive distribution instead of a point prediction, the model uncertainty is taken into account in a principled way. Our empirical results on simulated and real data sets demonstrate accurate and reliable identification of important variables and interaction effects compared to alternative methods.

Adaptive importance sampling is a class of techniques for finding good proposal distributions for importance sampling. Often the proposal distributions are standard probability distributions whose parameters are adapted based on the mismatch between the current proposal and a target distribution. In this work, we present an implicit adaptive importance sampling method that applies to complicated distributions which are not available in closed form. The method iteratively matches the moments of a set of Monte Carlo draws to weighted moments based on importance weights. We apply the method to Bayesian leave-one-out cross-validation and show that it performs better than many existing parametric adaptive importance sampling methods while being computationally inexpensive., Comment: Major revision: More comparisons to adaptive importance sampling with parametric distributions

This work considers properties of the logarithm of the Neumann-to-Dirichlet boundary map for the conductivity equation in a Lipschitz domain. It is shown that the mapping from the (logarithm of) the conductivity, i.e. the (logarithm of) the coefficient in the divergence term of the studied elliptic partial differential equation, to the logarithm of the Neumann-to-Dirichlet map is continuously Fr\'echet differentiable between natural topologies. Moreover, for any essentially bounded perturbation of the conductivity, the Fr\'echet derivative defines a bounded linear operator on the space of square integrable functions living on the domain boundary, although the logarithm of the Neumann-to-Dirichlet map itself is unbounded in that topology. In particular, it follows from the fundamental theorem of calculus that the difference between the logarithms of any two Neumann-to-Dirichlet maps is always bounded on the space of square integrable functions. All aforementioned results also hold if the Neumann-to-Dirichlet boundary map is replaced by its inverse, i.e. the Dirichlet-to-Neumann map., Comment: 20 pages

Background: Treatment verification with PET imaging in charged particle therapy is conventionally done by comparing measurements of spatial distributions with Monte Carlo (MC) predictions. However, decay curves can provide additional independent information about the treatment and the irradiated tissue. Most studies performed so far focus on long time intervals. Here we investigate the reliability of MC predictions of space and time (decay rate) profiles shortly after irradiation, and we show how the decay rates can give an indication about the elements of which the phantom is made up. Methods and Materials: Various phantoms were irradiated in clinical and near-clinical conditions at the Cyclotron Centre of the Bronowice proton therapy centre. PET data were acquired with a planar 16x16 cm$^2$ PET system. MC simulations of particle interactions and photon propagation in the phantoms were performed using the FLUKA code. The analysis included a comparison between experimental data and MC simulations of space and time profiles, as well as a fitting procedure to obtain the various isotope contributions in the phantoms. Results and conclusions: There was a good agreement between data and MC predictions in 1-dimensional space and decay rate distributions. The fractions of $^{11}$C, $^{15}$O and $^{10}$C that were obtained by fitting the decay rates with multiple simple exponentials generally agreed well with the MC expectations. We found a small excess of $^{10}$C in data compared to what was predicted in MC, which was clear especially in the PE phantom., Comment: 9 pages, 5 figures, 1 table. Proceedings of the 20th International Workshop on Radiation Imaging Detectors (iWorid2018), 24-28 June 2018, Sundsvall, Sweden

Variable selection for Gaussian process models is often done using automatic relevance determination, which uses the inverse length-scale parameter of each input variable as a proxy for variable relevance. This implicitly determined relevance has several drawbacks that prevent the selection of optimal input variables in terms of predictive performance. To improve on this, we propose two novel variable selection methods for Gaussian process models that utilize the predictions of a full model in the vicinity of the training points and thereby rank the variables based on their predictive relevance. Our empirical results on synthetic and real world data sets demonstrate improved variable selection compared to automatic relevance determination in terms of variability and predictive performance., Comment: Minor changes to text, additions to supplementary material

Aligning sequencing reads on graph representations of genomes is an important ingredient of pan-genomics. Such approaches typically find a set of local anchors that indicate plausible matches between substrings of a read to subpaths of the graph. These anchor matches are then combined to form a (semi-local) alignment of the complete read on a subpath. Co-linear chaining is an algorithmically rigorous approach to combine the anchors. It is a well-known approach for the case of two sequences as inputs. Here we extend the approach so that one of the inputs can be a directed acyclic graph (DAGs), e.g. a splicing graph in transcriptomics or a variant graph in pan-genomics. This extension to DAGs turns out to have a tight connection to the minimum path cover problem, asking for a minimum-cardinality set of paths that cover all the nodes of a DAG. We study the case when the size $k$ of a minimum path cover is small, which is often the case in practice. First, we propose an algorithm for finding a minimum path cover of a DAG $(V,E)$ in $O(k|E|\log|V|)$ time, improving all known time-bounds when $k$ is small and the DAG is not too dense. Second, we introduce a general technique for extending dynamic programming (DP) algorithms from sequences to DAGs. This is enabled by our minimum path cover algorithm, and works by mimicking the DP algorithm for sequences on each path of the minimum path cover. This technique generally produces algorithms that are slower than their counterparts on sequences only by a factor $k$. Our technique can be applied, for example, to the classical longest increasing subsequence and longest common subsequence problems, extended to labeled DAGs. Finally, we apply this technique to the co-linear chaining problem. We also implemented the new co-linear chaining approach. Experiments on splicing graphs show that the new method is efficient also in practice.

We present a theory of the superfluid weight in multiband attractive Hubbard models within the Bardeen-Cooper-Schrieffer (BCS) mean field framework. We show how to separate the geometric contribution to the superfluid weight from the conventional one, and that the geometric contribution is associated with the interband matrix elements of the current operator. Our theory can be applied to systems with or without time reversal symmetry. In both cases the geometric superfluid weight can be related to the quantum metric of the corresponding noninteracting systems. This leads to a lower bound on the superfluid weight given by the absolute value of the Berry curvature. We apply our theory to the attractive Kane-Mele-Hubbard and Haldane-Hubbard models, which can be realized in ultracold atom gases. Quantitative comparisons are made to state of the art dynamical mean-field theory and exact diagonalization results., Comment: Updated version, 17 pages, 10 figures

We give explicit and asymptotic lower bounds for the quantity $|e^{s/t}-M/N|$ by studying a generalized continued fraction expansion of $e^{s/t}$. In cases $|s|\geq 3$ we improve existing results by extracting a large common factor from the numerators and the denominators of the convergents of that generalized continued fraction.

Graphene nanoribbons are prone to in-plane bending even when supported on flat substrates. However, the amount of bending that ribbons can stably withstand remains poorly known. Here, by using molecular dynamics simulations, we study the stability limits of 0.5-1.9 nm wide armchair and zigzag graphene nanoribbons subject to bending. We observe that the limits for maximum stable curvatures are below ~10 deg/nm, in case the bending is externally forced and the limit is caused by buckling instability. Furthermore, it turns out that the limits for maximum stable curvatures are also below ~10 deg/nm, in case the bending is not forced and the limit arises only from the corrugated potential energy landscape due to the substrate. Both of the stability limits lower rapidly when ribbons widen. These results agree with recent experiments and can be understood by means of transparent elasticity models., Comment: 6 pages, 4 figures

Using dynamical mean-field theory and exact diagonalization we study the phase diagram of the repulsive Haldane-Hubbard model, varying the interaction strength and the sublattice potential difference. In addition to the quantum Hall phase with Chern number $C=2$ and the band insulator with $C=0$ present already in the noninteracting model, the system also exhibits a $C=0$ Mott insulating phase, and a $C=1$ quantum Hall phase. We explain the latter phase by a spontaneous symmetry breaking where one of the spin-components is in the Hall state and the other in the band insulating state., Comment: Updated version, 6 pages, 4 figures

We implement the Lanczos algorithm on an Intel Xeon Phi coprocessor and compare its performance to a multi-core Intel Xeon CPU and an NVIDIA graphics processor. The Xeon and the Xeon Phi are parallelized with OpenMP and the graphics processor is programmed with CUDA. The performance is evaluated by measuring the execution time of a single step in the Lanczos algorithm. We study two quantum lattice models with different particle numbers, and conclude that for small systems, the multi-core CPU is the fastest platform, while for large systems, the graphics processor is the clear winner, reaching speedups of up to 7.6 compared to the CPU. The Xeon Phi outperforms the CPU with sufficiently large particle number, reaching a speedup of 2.5.

Peeling, shearing, and sliding are important mechanical phenomena in van der Waals solids. However, theoretically they have been studied mostly using minimal periodic cells and in the context of accurate quantum simulations. Here, we investigate the peeling of large-scale multilayer graphene stacks with varying thicknesses, stackings, and peeling directions by using classical molecular dynamics simulations with a registry-dependent interlayer potential. Simulations show that, while at large scale the peeling proceeds smoothly, at small scale the registry shifts and sliding patterns of the layers are unexpectedly intricate and depend both on the initial stacking and on the peeling direction. These observations indicate that peeling and concomitant kink formations may well transform stacking order and thereby profoundly influence the electronic structures of such multilayer solids., Comment: 7 pages, 9 figures

The discovery of graphene some ten years ago was the first proof of a free-standing two-dimensional (2D) solid phase. Here, using quantum molecular dynamics simulations of nanoscale gold patches suspended in graphene pores, we predict the existence of an atomically thin, free-standing 2D liquid phase. The liquid phase, enabled by the exceptional planar stability of gold due to relativistic effects, demonstrates extreme fluxionality of metal nanostructures and opens possibilities for a variety of nanoscale phenomena., Comment: 9 pages, 4 figures (incl. Supplementary Information, 5 pages and 5 figures) Nanoscale (2015)

We study how the asymptotic irrationality exponent of a given generalized continued fraction \[ \K_{n=1}^\infty \frac{a_n}{b_n}\,,\quad a_n, b_n\in \mathbb{Z}^+, \] behaves as a function of growth properties of partial coefficient sequences $(a_n)$ and $(b_n)$.

We study the toplogical checkerboard lattice model around the $\nu=\frac{1}{3}$ fractional quantum Hall phase using numerical exact diagonalization without Landau level projections. We add local perturbations, modified hoppings and on-site potentials, and observe phase transitions from the fractional quantum Hall phase to metallic and insulating phases when the strength and number of impurities is increased. In addition to evaluating the energy spectrum, we identify the phase diagrams by computing the topological Chern number of the many-body ground state manifold, and we show how the ground states lose their correlations due to the impurities by evaluating the spectrum of the one-body reduced density matrix. Our results show that the phase transition from the fractional quantum Hall phase to the metallic phase occurs for both impurity hoppings and potentials. Strong impurity hoppings cause a further transition into the insulating state, regardless of the sign of the hopping, when their density is high enough. In contrast, the same happens only for attractive potentials. Furthermore, the mixing to the higher band in a two-band model, generally denoted as Landau level mixing, is measured concluding that the lowest Landau level projection works well even with remarkably strong interactions and in the presence of impurities.

Investigating topological effects in materials requires often the modeling of material systems as a whole. Such modeling restricts system sizes, and makes it hard to extract systematic trends. Here, we investigate the effect of M\"obius topology in the electronic structures of armchair graphene nanoribbons. Using density-functional tight-binding method and minimum-cell simulations through revised periodic boundary conditions, we extract electronic trends merely by changing cells' symmetry operations and respective quantum number samplings. It turns out that for a minimum cell calculation, once geometric and magnetic contributions are ignored, the effect of the global topology is unexpectedly short-ranged., Comment: 7 pages, 5 figures

In double quantum dot singlet-triplet qubits, the exchange interaction is used in both quantum gate operation and the measurement of the state of the qubit. The exchange can be controlled electronically by applying gate voltage pulses. We simulate the exchange induced charge state transitions in one and two singlet-triplet qubit systems using the exact diagonalization method. We find that fast detuning pulses may result in leakage between different singlet charge states. The leakage could cause measurement errors and hinder quantum gate operation for example in the case of the two-qubit Coulomb gate.

The correlated motion of a positron surrounded by electrons is a fundamental many-body problem. We approach this by modeling the momentum density of annihilating electron-positron pairs using the framework of reduced density matrices, natural orbitals and natural geminals (electron-positron pair wave functions) of the quantum theory of many-particle systems. We find that an expression based on the natural geminals provides an exact, unique and compact expression for the momentum density. The natural geminals can be used to define and determine enhancement factors for enhancement models going beyond the independent-particle model for a better understanding of results of positron annihilation experiments., Comment: Resubmitted to Physical Review B (Rapid Communications) on 19 December 2013

We implement, optimize, and validate the linear-scaling Kubo-Greenwood quantum transport simulation on graphics processing units by examining resonant scattering in graphene. We consider two practical representations of the Kubo-Greenwood formula: a Green-Kubo formula based on the velocity auto-correlation and an Einstein formula based on the mean square displacement. The code is fully implemented on graphics processing units with a speedup factor of up to 16 (using double-precision) relative to our CPU implementation. We compare the kernel polynomial method and the Fourier transform method for the approximation of the Dirac delta function and conclude that the former is more efficient. In the ballistic regime, the Einstein formula can produce the correct quantized conductance of one-dimensional graphene nanoribbons except for an overshoot near the band edges. In the diffusive regime, the Green-Kubo and the Einstein formalisms are demonstrated to be equivalent. A comparison of the length-dependence of the conductance in the localization regime obtained by the Einstein formula with that obtained by the non-equilibrium Green's function method reveals the challenges in defining the length in the Kubo-Greenwood formalism at the strongly localized regime., Comment: 15 pages, 8 figures

We present a highly flexible computational scheme for studying correlated electrons confined by an arbitrary external potential in two-dimensional semiconductor quantum dots. The method starts by a Lagrange mesh calculation for the single-particle states, followed by the calculation of the Coulomb interaction matrix elements between these, and combining both in the exact diagonalization of the many-body Hamiltonian. We apply the method in simulation of double quantum dot singlet-triplet qubits. We simulate the full quantum control and dynamics of one singlet-triplet qubit. We also use our method to provide an exact diagonalization based first-principles model for studying two singlet-triplet qubits and their capacitative coupling via the long-distance Coulomb interaction., Comment: 14 pages, 12 figures

In this paper, we develop a highly efficient molecular dynamics code fully implemented on graphics processing units for thermal conductivity calculations using the Green-Kubo formula. We compare two different schemes for force evaluation, a previously used thread-scheme where a single thread is used for one particle and each thread calculates the total force for the corresponding particle, and a new block-scheme where a whole block is used for one particle and each thread in the block calculates one or several pair forces between the particle associated with the given block and its neighbor particle(s) associated with the given thread. For both schemes, two different classical potentials, namely, the Lennard-Jones potential and the rigid-ion potential are implemented. While the thread-scheme performs a little better for relatively large systems, the block-scheme performs much better for relatively small systems. The relative performance of the block-scheme over the thread-scheme also increases with the increasing of the cutoff radius. We validate the implementation by calculating lattice thermal conductivities of solid argon and lead telluride.

The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various different algorithms. In this review, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics, and on quantum simulations for electronic structure calculations using the density functional theory, wave function techniques, and quantum field theory., Comment: Proceedings of the 11th International Conference, PARA 2012, Helsinki, Finland, June 10-13, 2012

We solve the Hubbard model with the exact diagonalization method on a graphics processing unit (GPU). We benchmark our GPU program against a sequential CPU code by using the Lanczos algorithm to solve the ground state energy in two cases: a one-dimensional ring and a two-dimensional square lattice. In the one-dimensional case, we obtain speedups of over 100 and 60 in single and double precision arithmetic, respectively. In the two-dimensional case, the corresponding speedups are over 110 and 70.

We study effective models of chiral fields and Polyakov loop expected to describe the dynamics responsible for the phase structure of two-flavor QCD at finite temperature and density. We consider chiral sector described either using linear sigma model or Nambu-Jona-Lasinio model and study the phase diagram and determine the location of the critical point as a function of the explicit chiral symmetry breaking (i.e. the bare quark mass $m_q$). We also discuss the possible emergence of the quarkyonic phase in this model., Comment: 10 pages, 6 figures

A local algorithm is a distributed algorithm where each node must operate solely based on the information that was available at system startup within a constant-size neighbourhood of the node. We study the applicability of local algorithms to max-min LPs where the objective is to maximise $\min_k \sum_v c_{kv} x_v$ subject to $\sum_v a_{iv} x_v \le 1$ for each $i$ and $x_v \ge 0$ for each $v$. Here $c_{kv} \ge 0$, $a_{iv} \ge 0$, and the support sets $V_i = \{v : a_{iv} > 0 \}$, $V_k = \{v : c_{kv}>0 \}$, $I_v = \{i : a_{iv} > 0 \}$ and $K_v = \{k : c_{kv} > 0 \}$ have bounded size. In the distributed setting, each agent $v$ is responsible for choosing the value of $x_v$, and the communication network is a hypergraph $\mathcal{H}$ where the sets $V_k$ and $V_i$ constitute the hyperedges. We present inapproximability results for a wide range of structural assumptions; for example, even if $|V_i|$ and $|V_k|$ are bounded by some constants larger than 2, there is no local approximation scheme. To contrast the negative results, we present a local approximation algorithm which achieves good approximation ratios if we can bound the relative growth of the vertex neighbourhoods in $\mathcal{H}$., Comment: 16 pages, 2 figures

In this thesis, we develop path integral localization methods that are familiar from topological field theory: the integral over the infinite dimensional integration domain depends only on local data around some finite dimensional subdomain. We introduce a new localization principle that unifies BRST localization, the non-Abelian localization principle and the conformal generalization of the Duistermaat-Heckman integration formula. In addition, it is studied if one can possibly derive a generalized Selberg's trace formula on locally homogeneous manifolds using localization techniques. However, a definite answer is obtained only in the Lie group case (we complete the work of R. Picken) in which it is an application of the Duistermaat-Heckman integration formula. Also a new derivation of DeWitt's term is reported. Furthermore, connections between evolution operators of integrable models and localization methods are studied. A derivative expansion localization is presented and it is conjectured to apply also to integrable models, for example the Toda lattice. Moreover, a pedagogical introduction to the localization techniques is given, as well as a list of selected references that might be useful for a beginning graduate student in mathematical physics or for a mathematician who would like to study the physical point of view to topological field theory and string theory., Comment: 40 pages, uses antero.sty that is included, Ph.D. thesis, Uppsala University

We introduce a new localization principle which is a generalized canonical transformation. It unifies BRST localization, the non-abelian localization principle and a special case of the conformal Duistermaat-Heckman integration formula of Paniak, Semenoff and Szabo. The heat kernel on compact Lie groups is localized in two ways. First using a non-abelian generalization of the derivative expansion localization of Palo and Niemi and secondly using the BRST localization principle and a configuration space path integral. In addition we present some new formulas on homogeneous spaces which might be useful in a possible localization of Selberg's trace formula on locally homogeneous spaces., Comment: 30 pages LaTeX, 1 figure; published version

We study the partition function of N=1 supersymmetric De Rham quantum mechanics on a Riemannian manifold, with a nontrivial chemical potential $\mu$ for the fermions. General arguments suggest that when $\mu \to \infty$ we should get the partition function of a free point particle. We investigate this limit by exact evaluation of the fermionic path integral. In even dimensions we find the De Witt term with a definite numerical factor. However, in odd dimensions our result is pestered by a quantum mechanical anomaly and the numerical factor in the De Witt term remains ambiquous., Comment: 10 pages, standard Latex run twice (3 figures that run under stadard Latex)

Coherent states for a general Lie superalgebra are defined following the method originally proposed by Perelomov. Algebraic and geometrical properties of the systems of states thus obtained are examined, with particular attention to the possibility of defining a K\"ahler structure over the states supermanifold and to the connection between this supermanifold and the coadjoint orbits of the dynamical supergroup. The theory is then applied to some compact forms of contragradient Lie superalgebras., Comment: 42 pages

This article introduces the central ideas of G. H. von Wright's cultural philosophy concerning the techno-scientific form of life. Georg Henrik von Wright (1916-2003) was best known for his achievements in the field of modal logic and for his association with Ludwig Wittgenstein. However, his work also included a critical analysis of science and technology. von Wright was concerned about ecological problems, human alienation, and the breakdown of traditional value systems. He analyzed the historical roots of modern techno-science. According to him, understanding the conceptual framework of modern natural science can help us in facing the problems produced by the powerful use of technology. As the most troubling feature of techno-science, he considered its manipulative approach toward reality.