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In this paper, we develop a semiparametric sensitivity analysis approach designed to address unmeasured confounding in observational studies with time-to-event outcomes. We target estimation of the marginal distributions of potential…

Methodology · Statistics 2025-11-21 Linda Amoafo , Shiyao Xu , Elizabeth Platz , Daniel Scharfstein

A universal fault-tolerant quantum computer holds the promise to speed up computational problems that are otherwise intractable on classical computers; however, for the next decade or so, our access is restricted to noisy intermediate-scale…

Quantum Physics · Physics 2023-02-22 Archismita Dalal , Amara Katabarwa

Distributed quantum sensing leverages quantum correlations among multiple sensors to enhance the precision of parameter estimation beyond classical limits. Most existing approaches target phase estimation and rely on a shared phase…

Quantum Physics · Physics 2026-02-04 Piotr T. Grochowski , Matteo Fadel , Radim Filip

This paper addresses the problem of unsupervised soft bit error rate (BER) estimation for any communications system, where no prior knowledge either about transmitted information bits, or the transceiver scheme is available. We show that…

Information Theory · Computer Science 2013-09-26 Samir Saoudi , Tarik Ait-Idir , Yukou Mochida

Randomized controlled trials often suffer from interference, a violation of the Stable Unit Treatment Values Assumption (SUTVA) in which a unit's treatment assignment affects the outcomes of its neighbors. This interference causes bias in…

Methodology · Statistics 2025-02-06 Vydhourie Thiyageswaran , Tyler McCormick , Jennifer Brennan

The accurate estimation of quantum observables is a critical task in science. With progress on the hardware, measuring a quantum system will become increasingly demanding, particularly for variational protocols that require extensive…

Cross entropy (XE) measure is a widely used benchmarking to demonstrate quantum computational advantage from sampling problems, such as random circuit sampling using superconducting qubits and boson sampling (BS). We present a heuristic…

Quantum Physics · Physics 2023-07-19 Changhun Oh , Liang Jiang , Bill Fefferman

In this letter we revisit the problem of optimal design of quantum tomographic experiments. In contrast to previous approaches where an optimal set of measurements is decided in advance of the experiment, we allow for measurements to be…

Quantum Physics · Physics 2017-02-28 Ferenc Huszár , Neil M. T. Houlsby

Phase wrapping is a major problem in direction-of-arrival (DOA) estimation using phase-difference observations. For a sensor pair with an inter-sensor spacing greater than half of the wavelength ($\lambda/2$) of the signal, phase wrapping…

Signal Processing · Electrical Eng. & Systems 2021-10-22 Hui Chen , Tarig Ballal , Tareq Y. Al-Naffouri

Accurately inferring the state of a quantum device from the results of measurements is a crucial task in building quantum information processing hardware. The predominant state estimation procedure, maximum likelihood estimation (MLE),…

Quantum Physics · Physics 2010-05-04 Robin Blume-Kohout

This paper studies transfer learning for estimating the mean of random functions based on discretely sampled data, where, in addition to observations from the target distribution, auxiliary samples from similar but distinct source…

Statistics Theory · Mathematics 2024-03-29 T. Tony Cai , Dongwoo Kim , Hongming Pu

The Ramsey sequence is a canonical example of a quantum phase measurement for a spin qubit. In Ramsey measurements, the measurement efficiency can be optimized through careful selection of settings for the phase accumulation time setting,…

Quantum Physics · Physics 2021-10-27 Robert D. McMichael , Sergey Dushenko , Sean M. Blakley

Quantum phase estimation (QPE) is a central algorithmic primitive that estimates eigenvalues of a Hamiltonian up to precision $\epsilon$ in Heisenberg-limited time $T=\Theta(1/\epsilon)$. Standard gate-based implementations of QPE require…

Quantum Physics · Physics 2026-05-22 Alexander Schmidhuber , Seth Lloyd

Error mitigation is essential for extracting reliable results from quantum computations performed on noisy intermediate-scale quantum hardware. Here we introduce Noise-Robust Estimation (NRE), a noise-agnostic framework that suppresses…

We consider sequential hypothesis testing between two quantum states using adaptive and non-adaptive strategies. In this setting, samples of an unknown state are requested sequentially and a decision to either continue or to accept one of…

Quantum Physics · Physics 2023-03-07 Yonglong Li , Vincent Y. F. Tan , Marco Tomamichel

This paper considers cooperative spectrum sensing algorithms for Cognitive Radios which focus on reducing the number of samples to make a reliable detection. We develop an energy efficient detector with low detection delay using…

Information Theory · Computer Science 2013-08-29 Jithin K. Sreedharan , Vinod Sharma

Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an unlabeled target domain supervised by a black-box predictor trained on a source domain. It does not require access to both the source-domain data and the predictor…

Machine Learning · Computer Science 2022-05-31 Jianfei Yang , Xiangyu Peng , Kai Wang , Zheng Zhu , Jiashi Feng , Lihua Xie , Yang You

I consider the role of detection noise in quantum-enhanced metrology in collective spin systems, and derive a fundamental bound for the maximum obtainable sensitivity for a given level of added detection noise. I then present an…

Quantum Physics · Physics 2018-10-31 Simon A. Haine

We consider the challenge of efficiently detecting changes within a network of sensors, where we also need to minimise communication between sensors and the cloud. We propose an online, communication-efficient method to detect such changes.…

Methodology · Statistics 2024-04-11 Ziyang Yang , Idris A. Eckley , Paul Fearnhead

The computational equivalence between approximate counting and sampling is well established for polynomial-time algorithms. The most efficient general reduction from counting to sampling is achieved via simulated annealing, where the…

Data Structures and Algorithms · Computer Science 2026-04-03 David G. Harris , Vladimir Kolmogorov , Hongyang Liu , Yitong Yin , Yiyao Zhang