pwc-archive/papers-with-abstracts huggingface dataset:
Interference mitigation with block diagonalization for IRS-aided MU-MIMO communications
Authors: Wilker de O. Feitosa, Igor M. Guerreiro, Fco. Rodrigo P. Cavalcanti, Tarcisio F. Maciel, Maria Clara R. Lobão, Fazal-E-Asim, Behrooz Makki, Gábor Fodor
Date: 2023-06-29 00:00:00

This work investigates interference mitigation techniques in multi-user multiple input multiple output (MU-MIMO) Intelligent Reflecting Surface (IRS)-aided networks, focusing on the base station end. Two methods of precoder design based on block diagonalization are proposed. The first method does not consider the interference caused by the IRS, seeking to mitigate only the multi-user interference. The second method mitigates both the IRS-caused interference and the multi-user interference. A comparison between both methods within an no-IRS MU-MIMO network with strong direct links is provided. The results show that, although in some circumstances IRS interference can be neglected, treating it can improve system capacity and provide higher spectral efficiency
A Unified Framework for Online Data-Driven Predictive Control with Robust Safety Guarantees
Authors: Amin Vahidi-Moghaddam, Kaian Chen, Kaixiang Zhang, Zhaojian Li, Yan Wang, Kai Wu
Date: 2023-06-29 00:00:00
Tasks: Model Predictive Control

Despite great successes, model predictive control (MPC) relies on an accurate dynamical model and requires high onboard computational power, impeding its wider adoption in engineering systems, especially for nonlinear real-time systems with limited computation power. These shortcomings of MPC motivate this work to make such a control framework more practically viable for real-world applications. Specifically, to remove the required accurate dynamical model and reduce the computational cost for nonlinear MPC (NMPC), this paper develops a unified online data-driven predictive control pipeline to efficiently control a system with guaranteed safety without incurring large computational complexity. The new aspect of this idea is learning not only the real system but also the control policy, which results in a reasonable computational cost for the data-driven predictive controllers. More specifically, we first develop a spatial temporal filter (STF)-based concurrent learning scheme to systematically identify system dynamics for general nonlinear systems. We then develop a robust control barrier function (RCBF) for safety guarantees in the presence of model uncertainties and learn the RCBF-based NMPC policy. Furthermore, to mitigate the performance degradation due to the existing model uncertainties, we propose an online policy correction scheme through perturbation analysis and design of an ancillary feedback controller. Finally, extensive simulations on two applications, cart-inverted pendulum and automotive powertrain control, are performed to demonstrate the efficacy of the proposed framework, which shows comparable performance with much lower computational cost in comparison with several benchmark algorithms.
Theoretical Analysis of Heterodyne Rydberg Atomic Receiver Sensitivity Based on Transit Relaxation Effect and Frequency Detuning
Authors: Shanchi Wu, Chen Gong, Shangbin Li, Rui Ni, Jinkang Zhu
Date: 2023-06-30 00:00:00
Tasks: Sensitivity

We conduct a theoretical investigation into the impacts of local microwave electric field frequency detuning, laser frequency detuning, and transit relaxation rate on enhancing heterodyne Rydberg atomic receiver sensitivity. To optimize the output signal amplitude given the input microwave signal, we derive the steady-state solutions of the atomic density matrix. Numerical results show that laser frequency detuning and local microwave electric field frequency detuning can improve the system detection sensitivity, which can help the system achieve extra sensitivity gain. It also shows that the heterodyne Rydberg atomic receiver can detect weak microwave signals continuously over a wide frequency range with the same sensitivity or even more sensitivity than the resonance case. To evaluate the transit relaxation effect, a modified Liouville equation is used. We find that the transition relaxation rate increases the time it takes to reach steady state and decreases the sensitivity of the system detection.
PV Fleet Modeling via Smooth Periodic Gaussian Copula
Authors: Mehmet G. Ogut, Bennet Meyers, Stephen P. Boyd
Date: 2023-06-05 00:00:00
Tasks: Anomaly Detection, Time Series

We present a method for jointly modeling power generation from a fleet of photovoltaic (PV) systems. We propose a white-box method that finds a function that invertibly maps vector time-series data to independent and identically distributed standard normal variables. The proposed method, based on a novel approach for fitting a smooth, periodic copula transform to data, captures many aspects of the data such as diurnal variation in the distribution of power output, dependencies among different PV systems, and dependencies across time. It consists of interpretable steps and is scalable to many systems. The resulting joint probability model of PV fleet output across systems and time can be used to generate synthetic data, impute missing data, perform anomaly detection, and make forecasts. In this paper, we explain the method and demonstrate these applications.
Automated identification and quantification of myocardial inflammatory infiltration in digital histological images to diagnose myocarditis
Authors: Yanyun Liu, Xiumeng Hua, Shouping Zhu, Congrui Wang, Xiao Chen, Yu Shi, Jiangping Song, Weihua Zhou
Date: 2023-07-03 00:00:00
Tasks: Sensitivity, Specificity, whole slide images

This study aims to develop a new computational pathology approach that automates the identification and quantification of myocardial inflammatory infiltration in digital HE-stained images to provide a quantitative histological diagnosis of myocarditis.898 HE-stained whole slide images (WSIs) of myocardium from 154 heart transplant patients diagnosed with myocarditis or dilated cardiomyopathy (DCM) were included in this study. An automated DL-based computational pathology approach was developed to identify nuclei and detect myocardial inflammatory infiltration, enabling the quantification of the lymphocyte nuclear density (LND) on myocardial WSIs. A cutoff value based on the quantification of LND was proposed to determine if the myocardial inflammatory infiltration was present. The performance of our approach was evaluated with a five-fold cross-validation experiment, tested with an internal test set from the myocarditis group, and confirmed by an external test from a double-blind trial group. An LND of 1.02/mm2 could distinguish WSIs with myocarditis from those without. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) in the five-fold cross-validation experiment were 0.899 plus or minus 0.035, 0.971 plus or minus 0.017, 0.728 plus or minus 0.073 and 0.849 plus or minus 0.044, respectively. For the internal test set, the accuracy, sensitivity, specificity, and AUC were 0.887, 0.971, 0.737, and 0.854, respectively. The accuracy, sensitivity, specificity, and AUC for the external test set reached 0.853, 0.846, 0.858, and 0.852, respectively. Our new approach provides accurate and reliable quantification of the LND of myocardial WSIs, facilitating automated quantitative diagnosis of myocarditis with HE-stained images.
Interferometric speckle visibility spectroscopy (iSVS) for measuring decorrelation time and dynamics of moving samples with enhanced signal-to-noise ratio and relaxed reference requirements
Authors: Yu Xi Huang, Simon Mahler, Jerome Mertz, Changhuei Yang
Date: 2023-06-30 00:00:00

Diffusing wave spectroscopy (DWS) is a group of techniques used to measure the dynamics of a scattering medium in a non-invasive manner. DWS methods rely on detecting the speckle light field from the moving scattering media and measuring the speckle decorrelation time to quantify the scattering mediums dynamics. For DWS, the signal-to-noise (SNR) is determined by the ratio between measured decorrelation time to the standard error of the measurement. This SNR is often low in certain applications because of high noise variances and low signal intensity, especially in biological applications with restricted exposure and emission levels. To address this photon-limited signal-to-noise ratio problem, we investigated, theoretically and experimentally, the SNR of an interferometric speckle visibility spectroscopy (iSVS) compared to more traditional DWS methods. We found that iSVS can provide excellent SNR performance through its ability to overcome camera noise. We also proved iSVS system has more relaxed constraints on the reference beam properties than most other interferometric systems. For an iSVS to function properly, we simply require the reference beam to exhibit local temporal stability, while incident angle, reference phase, and intensity uniformity do not need to be constrained. This flexibility can potentially enable more unconventional iSVS implementation schemes.
Expected Shortfall LASSO
Authors: Sander Barendse
Date: 2023-07-03 00:00:00
Tasks: Time Series

We propose an $\ell_1$-penalized estimator for high-dimensional models of Expected Shortfall (ES). The estimator is obtained as the solution to a least-squares problem for an auxiliary dependent variable, which is defined as a transformation of the dependent variable and a pre-estimated tail quantile. Leveraging a sparsity condition, we derive a nonasymptotic bound on the prediction and estimator errors of the ES estimator, accounting for the estimation error in the dependent variable, and provide conditions under which the estimator is consistent. Our estimator is applicable to heavy-tailed time-series data and we find that the amount of parameters in the model may grow with the sample size at a rate that depends on the dependence and heavy-tailedness in the data. In an empirical application, we consider the systemic risk measure CoES and consider a set of regressors that consists of nonlinear transformations of a set of state variables. We find that the nonlinear model outperforms an unpenalized and untransformed benchmark considerably.
The Yule-Frisch-Waugh-Lovell Theorem
Authors: Deepankar Basu
Date: 2023-07-01 00:00:00
Tasks: Econometrics, regression

This paper traces the historical and analytical development of what is known in the econometrics literature as the Frisch-Waugh-Lovell theorem. This theorem demonstrates that the coefficients on any subset of covariates in a multiple regression is equal to the coefficients in a regression of the residualized outcome variable on the residualized subset of covariates, where residualization uses the complement of the subset of covariates of interest. In this paper, I suggest that the theorem should be renamed as the Yule-Frisch-Waugh-Lovell (YFWL) theorem to recognize the pioneering contribution of the statistician G. Udny Yule in its development. Second, I highlight recent work by the statistician, P. Ding, which has extended the YFWL theorem to a comparison of estimated covariance matrices of coefficients from multiple and partial, i.e. residualized regressions. Third, I show that, in cases where Ding's results do not apply, one can still resort to a computational method to conduct statistical inference about coefficients in multiple regressions using information from partial regressions.
Adam Smith's Theory of Value: A Reappraisal of Classical Price Discovery
Authors: Sabiou Inoua, Vernon Smith
Date: 2023-07-01 00:00:00

The relevance of Adam Smith for understanding human morality and sociality is recognized in the growing interest in his work on moral sentiments among scholars of various academic backgrounds. But, paradoxically, Adam Smith's theory of economic value enjoys a less prominent stature today among economists, who, while they view him as the 'father of modern economics', considered him more as having had the right intuitions about a market economy than as having developed the right concepts and the technical tools for studying it. Yet the neoclassical tradition, which replaced the classical school around 1870, failed to provide a satisfactory theory of market price formation. Adam Smith's sketch of market price formation (Ch. VII, Book I, Wealth of Nations), and more generally the classical view of competition as a collective higgling and bargaining process, as this paper argues, offers a helpful foundation on which to build a modern theory of market price formation, despite any shortcomings of the original classical formulation (notably its insistence on long-run, natural value). Also, with hindsight, the experimental market findings established the remarkable stability, efficiency, and robustness of the old view of competition, suggesting a rehabilitation of classical price discovery. This paper reappraises classical price theory as Adam Smith articulated it; we explicate key propositions from his price theory and derive them from a simple model, which is an elementary sketch of the authors' more general theory of competitive market price formation.
Local Eviction Moratoria and the Spread of COVID-19
Authors: Julia Hatamyar, Christopher F. Parmeter
Date: 2023-07-01 00:00:00

At various stages during the initial onset of the COVID-19 pandemic, various US states and local municipalities enacted eviction moratoria. One of the main aims of these moratoria was to slow the spread of COVID-19 infections. We deploy a semiparametric difference-in-differences approach with an event study specification to test whether the lifting of these local moratoria led to an increase in COVID-19 cases and deaths. Our main findings, across a range of specifications, are inconclusive regarding the impact of the moratoria - especially after accounting for the number of actual evictions and conducting the analysis at the county level. We argue that recently developed augmented synthetic control (ASCM) methods are more appropriate in this setting. Our ASCM results also suggest that the lifting of eviction moratoria had little to no impact on COVID-19 cases and deaths. Thus, it seems that eviction moratoria had little to no robust effect on reducing the spread of COVID-19 throwing into question its use as a non-pharmaceutical intervention.
A Comparison of Sequential Ranked-Choice Voting and Single Transferable Vote
Authors: David McCune, Erin Martin, Grant Latina, Kaitlyn Simms
Date: 2023-06-29 00:00:00

The methods of single transferable vote (STV) and sequential ranked-choice voting (RCV) are different methods for electing a set of winners in multiwinner elections. STV is a classical voting method that has been widely used internationally for many years. By contrast, sequential RCV has rarely been used, and only recently has seen an increase in usage as several cities in Utah have adopted the method to elect city council members. We use Monte Carlo simulations and a large database of real-world ranked-choice elections to investigate the behavior of sequential RCV by comparing it to STV. Our general finding is that sequential RCV often produces different winner sets than STV. Furthermore, sequential RCV is best understood as an excellence-based method which will not produce proportional results, often at the expense of minority interests.
Retail Pricing Format and Rigidity of Regular Prices
Authors: Sourav Ray, Avichai Snir, Daniel Levy
Date: 2023-06-29 00:00:00

We study the price rigidity of regular and sale prices, and how it is affected by pricing formats (pricing strategies). We use data from three large Canadian stores with different pricing formats (Every-Day-Low-Price, Hi-Lo, and Hybrid) that are located within a 1 km radius of each other. Our data contains both the actual transaction prices and actual regular prices as displayed on the store shelves. We combine these data with two generated regular price series (filtered prices and reference prices) and study their rigidity. Regular price rigidity varies with store formats because different format stores treat sale prices differently, and consequently define regular prices differently. Correspondingly, the meanings of price cuts and sale prices vary across store formats. To interpret the findings, we consider the store pricing format distribution across the US.
Replication of financial derivatives under extreme market models given marginals
Authors: Tongseok Lim
Date: 2023-07-03 00:00:00

The Black-Scholes-Merton model is a mathematical model for the dynamics of a financial market that includes derivative investment instruments, and its formula provides a theoretical price estimate of European-style options. The model's fundamental idea is to eliminate risk by hedging the option by purchasing and selling the underlying asset in a specific way, that is, to replicate the payoff of the option with a portfolio (which continuously trades the underlying) whose value at each time can be verified. One of the most crucial, yet restrictive, assumptions for this task is that the market follows a geometric Brownian motion, which has been relaxed and generalized in various ways. The concept of robust finance revolves around developing models that account for uncertainties and variations in financial markets. Martingale Optimal Transport, which is an adaptation of the Optimal Transport theory to the robust financial framework, is one of the most prominent directions. In this paper, we consider market models with arbitrarily many underlying assets whose values are observed over arbitrarily many time periods, and demonstrates the existence of a portfolio sub- or super-hedging a general path-dependent derivative security in terms of trading European options and underlyings, as well as the portfolio replicating the derivative payoff when the market model yields the extremal price of the derivative given marginal distributions of the underlyings. In mathematical terms, this paper resolves the question of dual attainment for the multi-period vectorial martingale optimal transport problem.
Order preservation with dummies in the musseum pass problem
Authors: Ricardo Martínez, Joaquín Sánchez-Soriano
Date: 2023-07-02 00:00:00

We study the problem of sharing the revenue obtained by selling museum passes from the axiomatic perspective. In this setting, we propose replacing the usual dummy axiom with a milder requirement: order preservation with dummies. This new axiom formalizes the philosophical idea that even null agents/museums may have the right to receive a minimum allocation in a sharing situation. By replacing dummy with order preservation with dummies, we characterize several families of rules, which are convex combinations of the uniform and Shapley approaches. Our findings generalize several existing results in the literature. Also, we consider a domain of problems that is richer than the domain proposed by Ginsburgh and Zang (2003) in their seminal paper on the museum pass problem.
The Classical Theory of Supply and Demand
Authors: Sabiou Inoua, Vernon Smith
Date: 2023-07-01 00:00:00

This paper introduces and formalizes the classical view on supply and demand, which, we argue, has an integrity independent and distinct from the neoclassical theory. Demand and supply, before the marginal revolution, are defined not by an unobservable criterion such as a utility function, but by an observable monetary variable, the reservation price: the buyer's (maximum) willingness to pay (WTP) value (a potential price) and the seller's (minimum) willingness to accept (WTA) value (a potential price) at the marketplace. Market demand and supply are the cumulative distribution of the buyers' and sellers' reservation prices, respectively. This WTP-WTA classical view of supply and demand formed the means whereby market participants were motivated in experimental economics although experimentalists (trained in neoclassical economics) were not cognizant of their link to the past. On this foundation was erected a vast literature on the rules of trading for a host of institutions, modern and ancient. This paper documents textually this reappraisal of classical economics and then formalizes it mathematically. A follow-up paper will articulate a theory of market price formation rooted in this classical view on supply and demand and in experimental findings on market behavior.
A Classical Model of Speculative Asset Price Dynamics
Authors: Sabiou Inoua, Vernon Smith
Date: 2023-07-01 00:00:00
Tasks: model

In retrospect, the experimental findings on competitive market behavior called for a revival of the old, classical, view of competition as a collective higgling and bargaining process (as opposed to price-taking behaviors) founded on reservation prices (in place of the utility function). In this paper, we specialize the classical methodology to deal with speculation, an important impediment to price stability. The model involves typical features of a field or lab asset market setup and lends itself to an experimental test of its specific predictions; here we use the model to explain three general stylized facts, well established both empirically and experimentally: the excess, fat-tailed, and clustered volatility of speculative asset prices. The fat tails emerge in the model from the amplifying nature of speculation, leading to a random-coefficient autoregressive return process (and power-law tails); the volatility clustering is due to the traders' long memory of news; bubbles are a persistent phenomenon in the model, and, assuming the standard lab present value pattern, the bubble size increases with the proportion of speculators and decreases with the trading horizon.
Unbalanced Growth and Land Overvaluation
Authors: Tomohiro Hirano, Alexis Akira Toda
Date: 2023-07-01 00:00:00

Historical trends suggest the decline in importance of land as a production factor but its continued importance as a store of value. Using an overlapping generations model with land and aggregate uncertainty, we theoretically study the long-run behavior of land prices and identify economic conditions under which land becomes overvalued on the long-run trend relative to the fundamentals defined by the present value of land rents. Unbalanced growth together with the elasticity of substitution between production factors plays a critical role. Around the trend, land prices exhibit recurrent stochastic fluctuations, with expansions and contractions in the size of land overvaluation.
Obvious Manipulations in Matching without and with Contracts
Authors: R. Pablo Arribillaga, E. Pepa Risma
Date: 2023-06-30 00:00:00

This paper explores many-to-one matching models, both with and without contracts, where doctors' preferences are private and hospitals' preferences are public and substitutable. It is known that any stable-dominating mechanism --which is either stable or individually rational and Pareto-dominates (from the doctors' perspective) a stable mechanism--, is susceptible to manipulation by doctors. Our study focuses on \textit{obvious manipulations} and identifies stable-dominating mechanisms that prevent them. Without contracts, we show that more efficient mechanisms are less likely to be obviously manipulable and that any stable-dominating mechanism is not obviously manipulable. However, with contracts, none of these results hold. While we demonstrate that the Doctor-Proposing Deferred Acceptance (DA) Mechanism remains not obviously manipulable, we show that the Hospital-Proposing DA Mechanism and any efficient mechanism that Pareto-dominates the Doctor-Proposing DA Mechanism become (very) obviously manipulable, in the model with contracts.