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We focus on the high-dimensional linear regression problem, where the algorithmic goal is to efficiently infer an unknown feature vector $\beta^*\in\mathbb{R}^p$ from its linear measurements, using a small number $n$ of samples. Unlike most…

Statistics Theory · Mathematics 2023-09-19 David Gamarnik , Eren C. Kızıldağ , Ilias Zadik

To assess whether a given time series can be modeled by a stochastic process possessing long range correlation one usually applies one of two types of analysis methods: the spectral method and the random walk analysis. The first objective…

Statistical Mechanics · Physics 2009-11-07 Govindan Rangarajan , Mingzhou Ding

With the continued scaling of quantum processors, holistic benchmarks are essential for extensively evaluating device performance. Layer fidelity is a benchmark well-suited to assessing processor performance at scale. Key advantages of this…

Quantum Physics · Physics 2026-02-24 Maria Jose Lozano Palacio , Hasan Nayfeh , Matthew Ware , David C. McKay

For a high-dimensional linear model with a finite number of covariates measured with error, we study statistical inference on the parameters associated with the error-prone covariates, and propose a new corrected decorrelated score test and…

Methodology · Statistics 2020-01-29 Mengyan Li , Runze Li , Yanyuan Ma

We propose a two-stage estimation method of variance components in time series models known as FDSLRMs, whose observations can be described by a linear mixed model (LMM). We based estimating variances, fundamental quantities in a time…

Methodology · Statistics 2020-03-10 Martina Hančová , Gabriela Vozáriková , Andrej Gajdoš , Jozef Hanč

Coherent-state-based phase estimation is a fruitful testbed for the field of precision measurements since coherent states are robust to decoherence when compared with exotic quantum states. The seminal work done by Caves…

Quantum Physics · Physics 2020-01-03 Jian-Dong Zhang , Zi-Jing Zhang , Long-Zhu Cen , Jun-Yan Hu , Yuan Zhao

In this paper, we propose the SPR (sparse phase retrieval) method, which is a new phase retrieval method for coherent x-ray diffraction imaging (CXDI). Conventional phase retrieval methods effectively solve the problem for high…

Data Analysis, Statistics and Probability · Physics 2016-03-29 Shiro Ikeda , Hidetoshi Kono

Inverse Ising inference allows pairwise interactions of complex binary systems to be reconstructed from empirical correlations. Typical estimators used for this inference, such as Pseudo-likelihood maximization (PLM), are biased. Using the…

Disordered Systems and Neural Networks · Physics 2023-07-19 Maximilian Benedikt Kloucek , Thomas Machon , Shogo Kajimura , C. Patrick Royall , Naoki Masuda , Francesco Turci

This paper describes a 561 nm laser heterodyne interferometer that provides time-resolved measurements of line-integrated plasma electron density within the range of 10^15-10^18 cm^(-2). Such plasmas are produced by railguns on the Plasma…

Plasma Physics · Physics 2015-06-03 Elizabeth C. Merritt , Alan G. Lynn , Mark A. Gilmore , Scott C. Hsu

Long-term quantum coherence constitutes one of the main challenges when engineering quantum devices. However, easily accessible means to quantify complex decoherence mechanisms are not readily available, nor are sufficiently stable systems.…

Recently, some mixture algorithms of pointwise and pairwise learning (PPL) have been formulated by employing the hybrid error metric of "pointwise loss + pairwise loss" and have shown empirical effectiveness on feature selection, ranking…

Machine Learning · Computer Science 2023-02-21 Jiahuan Wang , Jun Chen , Hong Chen , Bin Gu , Weifu Li , Xin Tang

This paper considers the computer model calibration problem and provides a general frequentist solution. Under the proposed framework, the data model is semi-parametric with a nonparametric discrepancy function which accounts for any…

Methodology · Statistics 2015-09-14 Raymond K. W. Wong , Curtis B. Storlie , Thomas C. M. Lee

In modern randomized experiments, large-scale data collection increasingly yields rich baseline covariates and auxiliary information from multiple sources. Such information offers opportunities for more precise treatment effect estimation,…

Methodology · Statistics 2026-03-10 Wei Ma , Zeqi Wu , Zheng Zhang

Statistical inference and information processing of high-dimensional data often require efficient and accurate estimation of their second-order statistics. With rapidly changing data, limited processing power and storage at the acquisition…

Information Theory · Computer Science 2015-03-23 Yuxin Chen , Yuejie Chi , Andrea Goldsmith

Estimating the clutter-plus-noise covariance matrix in high-dimensional STAP is challenging in the presence of Internal Clutter Motion (ICM) and a high noise floor. The problem becomes more difficult in low-sample regimes, where the Sample…

Signal Processing · Electrical Eng. & Systems 2025-05-13 Shashwat Jain , Vikram Krishnamurthy , Muralidhar Rangaswamy , Sandeep Gogineni , Bosung Kang , Sean M. O'Rourke

Accurate phase connectivity information is essential for advanced monitoring and control applications in power distribution systems. The existing data-driven approaches for phase identification lack precise physical interpretation and…

Systems and Control · Computer Science 2019-08-23 Wenyu Wang , Nanpeng Yu

A proposed phase-estimation protocol based on measuring the parity of a two-mode squeezed-vacuum state at the output of a Mach-Zehnder interferometer shows that the Cram\'{e}r-Rao sensitivity is sub-Heisenberg [Phys.\ Rev.\ Lett.\ {\bf104},…

Quantum Physics · Physics 2017-05-17 Zixin Huang , Keith R. Motes , Petr M. Anisimov , Jonathan P. Dowling , Dominic W. Berry

We propose a flexible convex relaxation for the phase retrieval problem that operates in the natural domain of the signal. Therefore, we avoid the prohibitive computational cost associated with "lifting" and semidefinite programming (SDP)…

Information Theory · Computer Science 2017-03-17 Sohail Bahmani , Justin Romberg

Determining the phase in one arm of a quantum interferometer is discussed taking into account the three non-ideal aspects in real experiments: non-deterministic state preparation, non-unitary state evolution due to losses during state…

Quantum Physics · Physics 2015-05-20 Thomas B. Bahder

Parameter estimation in linear errors-in-variables models typically requires that the measurement error distribution be known (or estimable from replicate data). A generalized method of moments approach can be used to estimate model…

Methodology · Statistics 2018-12-04 Linh Nghiem , Michael Byrd , Cornelis Potgieter