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High-dimensional entanglement provides unique ways of transcending the limitations of current approaches in quantum information processing, quantum communications based on qubits. The generation of time-frequency qudit states offer…

Secret-key distillation from quantum states and channels is a central task of interest in quantum information theory, as it facilitates private communication over a quantum network. Here, we study the task of secret-key distillation from…

Quantum Physics · Physics 2025-06-16 Vishal Singh , Mark M. Wilde

In this thesis, several new procedures for the generation and manipulation of entangled states in quantum optical systems are introduced. Each is evaluated in terms of realistic models of the imperfect apparatus of any real laboratory…

Quantum Physics · Physics 2007-05-23 Daniel E. Browne

We propose a measurement-based model for fault-tolerant quantum computation that can be realised with one-dimensional cluster states and fusion measurements only; basic resources that are readily available with scalable photonic hardware.…

Quantum Physics · Physics 2023-10-16 Stefano Paesani , Benjamin J. Brown

One-dimensional systems exhibiting a continuous symmetry can host quantum phases of matter with true long-range order only in the presence of sufficiently long-range interactions. In most physical systems, however, the interactions are…

Dataset distillation aims to find a synthetic training set such that training on the synthetic data achieves similar performance to training on real data, with orders of magnitude less computational requirements. Existing methods can be…

Machine Learning · Computer Science 2026-02-09 Hong Ye Tan , Emma Slade

Super-resolution (SR) aims to reconstruct high-resolution (HR) images from their low-resolution (LR) counterparts, often relying on effective downsampling to generate diverse and realistic training pairs. In this work, we propose a…

Image and Video Processing · Electrical Eng. & Systems 2025-03-18 Sohwi Kim , Tae-Kyun Kim

Quantum coherence in a qubit is vulnerable to environmental noise. When long quantum calculation is run on a quantum processor without error correction, the noise often causes fatal errors and messes up the calculation. Here, we propose…

While powerful methods have been developed for high-dimensional hypothesis testing assuming orthogonal parameters, current approaches struggle to generalize to the more common non-orthogonal case. We propose Stable Distillation (SD), a…

Methodology · Statistics 2025-01-10 Ryan Christ , Ira Hall , David Steinsaltz

Entanglement distillation, the process of converting weakly entangled states into maximally entangled ones using Local Operations and Classical Communication (LOCC), is pivotal for robust entanglement-assisted quantum information processing…

Quantum Physics · Physics 2025-12-17 Christopher Popp , Tobias C. Sutter , Beatrix C. Hiesmayr

Large machine-learning training datasets can be distilled into small collections of informative synthetic data samples. These synthetic sets support efficient model learning and reduce the communication cost of data sharing. Thus,…

Machine Learning · Computer Science 2024-08-13 William Holland , Chandra Thapa , Sarah Ali Siddiqui , Wei Shao , Seyit Camtepe

The discrimination of coherent states is a key task in optical communication and quantum key distribution protocols. In this work, we use a photon-number-resolving detector, the transition-edge sensor, to discriminate binary-phase-shifted…

Quantum Physics · Physics 2021-05-18 G. S. Thekkadath , S. Sempere-Llagostera , B. A. Bell , R. B. Patel , M. S. Kim , I. A. Walmsley

We present mean-shift distillation, a novel diffusion distillation technique that provides a provably good proxy for the gradient of the diffusion output distribution. This is derived directly from mean-shift mode seeking on the…

Although diffusion models can generate remarkably high-quality samples, they are intrinsically bottlenecked by their expensive iterative sampling procedure. Consistency models (CMs) have recently emerged as a promising diffusion model…

Recently, diffusion distillation methods have compressed thousand-step teacher diffusion models into one-step student generators while preserving sample quality. Most existing approaches train the student model using a diffusive divergence…

Machine Learning · Computer Science 2025-08-29 Leyang Wang , Mingtian Zhang , Zijing Ou , David Barber

Coherent diffractive imaging (CDI) has been widely applied in the physical and biological sciences using synchrotron radiation, XFELs, high harmonic generation, electrons and optical lasers. One of CDI's important applications is to probe…

Instrumentation and Detectors · Physics 2018-07-04 Yuan Hung Lo , Lingrong Zhao , Marcus Gallagher-Jones , Arjun Rana , Jared Lodico , Weikun Xiao , B. C. Regan , Jianwei Miao

A reliable source of identical (indistinguishable) photons is a prerequisite for exploiting interference effects, which is a necessary component for linear optical based quantum computing, and applications thereof such as Boson sampling.…

Quantum Physics · Physics 2022-11-18 Jeffrey Marshall

We examine the decoherence properties of a quantum open system as modeled by a quantum optical system in the Markov regime. We look for decoherence in both the Environment Induced Superselection (EIS) and Consistent Histories (CH)…

General Relativity and Quantum Cosmology · Physics 2009-10-22 J. Twamley

Decay of a four-level diamond scheme via a cascade is a potential source of entangled photon pairs. A solid-state implementation is the biexciton cascade in a semiconductor quantum dot. While high entanglement fidelities have been…

Computational optical imaging (COI) systems have enabled the acquisition of high-dimensional signals through optical coding elements (OCEs). OCEs encode the high-dimensional signal in one or more snapshots, which are subsequently decoded…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Leon Suarez-Rodriguez , Roman Jacome , Henry Arguello