Quantum Physics Commons^™

High-Performance Computing In Covariant Loop Quantum Gravity, Pietropaolo Frisoni

Electronic Thesis and Dissertation Repository

This Ph.D. thesis presents a compilation of the scientific papers I published over the last three years during my Ph.D. in loop quantum gravity (LQG). First, we comprehensively introduce spinfoam calculations with a practical pedagogical paper. We highlight LQG's unique features and mathematical formalism and emphasize the computational complexities associated with its calculations. The subsequent articles delve into specific aspects of employing high-performance computing (HPC) in LQG research. We discuss the results obtained by applying numerical methods to studying spinfoams' infrared divergences, or ``bubbles''. This research direction is crucial to define the continuum limit of LQG properly. We investigate the …

Generative Adversarial Game With Tailored Quantum Feature Maps For Enhanced Classification, Anais Sandra Nguemto Guiawa

Doctoral Dissertations

In the burgeoning field of quantum machine learning, the fusion of quantum computing and machine learning methodologies has sparked immense interest, particularly with the emergence of noisy intermediate-scale quantum (NISQ) devices. These devices hold the promise of achieving quantum advantage, but they grapple with limitations like constrained qubit counts, limited connectivity, operational noise, and a restricted set of operations. These challenges necessitate a strategic and deliberate approach to crafting effective quantum machine learning algorithms.

This dissertation revolves around an exploration of these challenges, presenting innovative strategies that tailor quantum algorithms and processes to seamlessly integrate with commercial quantum platforms. A …

Human And Technical Factors In The Adoption Of Quantum Cryptographic Algorithms, Alyssa Pinkston

Mathematical Sciences Technical Reports (MSTR)

The purpose of this research is to understand what factors would cause users to choose quantum key distribution (QKD) over other methods of cryptography. An Advanced Encryption Standard (AES) key can be exchanged through communication using the Rivest, Shamir, Adleman (RSA) cryptographic algorithm, QKD, or post-quantum cryptography (PQC). QKD relies on quantum physics where RSA and PQC use complex mathematics to encrypt data. The BB84 quantum cryptographic protocol involves communication over a quantum channel and a public channel. The quantum channel can be technically attacked by beamsplitting or intercept/resend. QKD, like other forms of cryptography, is vulnerable to social attacks …

Making The Transition To Post-Quantum Cryptography, J. Simon Richard

The Downtown Review

Without intervention, quantum computing could threaten the security of a large portion of our internet in the near future. However, solutions exist. This paper, which is intended for a general audience, provides a wider context for our current state of quantum-preparedness amid the transition from classical cryptosystems to post-quantum cryptosystems—cryptographic algorithms that can resist the attacks of quantum computers. It will also submit a possible way forward inspired by the actions taken around the globe to prevent the millennium (or Y2K) bug.

Applying Hallgren’S Algorithm For Solving Pell’S Equation To Finding The Irrational Slope Of The Launch Of A Billiard Ball, Sangheon Choi

Mathematical Sciences Technical Reports (MSTR)

This thesis is an exploration of Quantum Computing applied to Pell’s equation in an attempt to find solutions to the Billiard Ball Problem. Pell’s equation is a Diophantine equation in the form of x² − ny² = 1, where n is a given positive nonsquare integer, and integer solutions are sought for x and y. We will be applying Hallgren’s algorithm for finding irrational periods in functions, in the context of billiard balls and their movement on a friction-less unit square billiard table. Our central research question has been the following: Given the cutting sequence of the billiard …

Evaluation Of Scalable Quantum And Classical Machine Learning For Particle Tracking Classification In Nuclear Physics, Polykarpos Thomadakis, Emmanuel Billias, Nikos Chrisochoides

The Graduate School Posters

Future particle accelerators will exceed by far the current data size (10¹⁵) per experiment, and high- luminosity program(s) will produce more than 300 times as much data. Classical Machine Learning (ML) likely will benefit from new tools based on quantum computing. Particle track reconstruction is the most computationally intensive process in nuclear physics experiments. A combinatorial approach exhaustively tests track measurements (“hits”), represented as images, to identify those that form an actual particle trajectory, which is then used to reconstruct track parameters necessary for the physics experiment. Quantum Machine Learning (QML) could improve this process in multiple ways, …

Establishing The Legal Framework To Regulate Quantum Computing Technology, Kaya Derose

Catholic University Journal of Law and Technology

No abstract provided.

Quantum Computing For Nuclear Physics, Aikaterini Nikou

2023 REYES Proceedings

Nuclear physics can greatly advance by taking advantage of quantum computing. Quantum computing can play a pivotal role in advancing nuclear physics and can allow for the description of physical situations and problems that are prohibitive to solve using classical computing due to their complexity. Some of the problems whose complexity requires using quantum computing to describe are: interacting quantum many-body and Quantum Field Theory problems such as simulating strongly interacting fields such as Quantum Chromodynamics with physical time evolution, the determination of the shape/phase of a nucleus using the time evolution of an appropriated observable as well as identifying …

Ml-Based Surrogates And Emulators, Tareq Alghamdi, Yaohang Li, Nobuo Sato

College of Sciences Posters

No abstract provided.

Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides

The Graduate School Posters

Edge Detection is one of the computationally intensive modules in image analysis. It is used to find important landmarks by identifying a significant change (or “edge”) between pixels and voxels. We present a hybrid Quantum Edge Detection method by improving three aspects of an existing widely referenced implementation, which for our use cases generates incomprehensible results for the type and size of images we are required to process. Our contributions are in the pre- and post-processing (i.e., classical phase) and a quantum edge detection circuit: (1) we use space- filling curves to eliminate image artifacts introduced by the image decomposition, …

Compiling Quantum Programs, Li-Heng Henry Chang

Senior Projects Spring 2023

This thesis introduces the quantum compilation problem and develops a prototypical compiler. The problem of quantum compiling is, in essence, converting high-level human expressions of quantum programs into low-level hardware executable code. Compilers that target different hardware platforms enable portable code that can be used to benchmark hardware performance, reduce programming work and speed up development. Because quantum systems are subjected to phenomena such as noise, no-cloning and decoherence, the challenge of quantum compiling is tied to the optimization of program runtimes and the lengths of compiled sequences. For near-term intermediate scale quantum (NISQ) computers with limited hardware resources and …

Machine Learning-Based Jet And Event Classification At The Electron-Ion Collider With Applications To Hadron Structure And Spin Physics, Kyle Lee, James Mulligan, Mateusz Płoskoń, Felix Ringer, Feng Yuan

Physics Faculty Publications

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in …

The Mceliece Cryptosystem As A Solution To The Post-Quantum Cryptographic Problem, Isaac Hanna

Senior Honors Theses

The ability to communicate securely across the internet is owing to the security of the RSA cryptosystem, among others. This cryptosystem relies on the difficulty of integer factorization to provide secure communication. Peter Shor’s quantum integer factorization algorithm threatens to upend this. A special case of the hidden subgroup problem, the algorithm provides an exponential speedup in the integer factorization problem, destroying RSA’s security. Robert McEliece’s cryptosystem has been proposed as an alternative. Based upon binary Goppa codes instead of integer factorization, his cryptosystem uses code scrambling and error introduction to hinder decrypting a message without the private key. This …

The Future Between Quantum Computing And Cybersecurity, Daniel Dorazio

Williams Honors College, Honors Research Projects

Quantum computing, a novel branch of technology based on quantum theory, processes information in ways beyond the capabilities of classical computers. Traditional computers use binary digits [bits], but quantum computers use quantum binary digits [qubits] that can exist in multiple states simultaneously. Since developing the first two-qubit quantum computer in 1998, the quantum computing field has experienced rapid growth.

Cryptographic algorithms such as RSA and ECC, essential for internet security, rely on the difficulty of complex math problems that classical computers can’t solve. However, the advancement of quantum technology threatens these encryption systems. Algorithms, such as Shor’s, leverage the power …

Decoherence And Preferred Tensor Product Structures For Systems Of Qubits, Marissa M. Singh

Pitzer Senior Theses

In recent decades, the program of Decoherence has helped clarify how features of the classical world emerge from Quantum Mechanics. According to Decoherence, the interaction between a system and its environment dynamically selects certain system states — the pointer states — that exhibit predictable, classical behavior while their superpositions rapidly decohere. However, most Decoherence studies to date pre-suppose a preferred division of the world into “system” and “environment”, corresponding to a preferred choice of Tensor Product Structure (TPS) on the Hilbert Space of states. A few previous works have suggested that the existence of a well-defined pointer observable may be …