Tootfinder

Welcome to Computing's weekly roundup of tech news in Asia. This time we look at China’s datacentre glut, a near-zero-carbon facility and a serious cyberattack in Singapore.
https://www.computing.co.uk/news/2025/cloud/china-centralise-cloud…

China tries to centralise cloud computing - Asian Tech Roundup
Welcome to Computing's weekly roundup of tech news in Asia. This time we look at China’s datacentre glut, a near-zero-carbon facility and a serious cyberattack ...

Spatial Regionalization: A Hybrid Quantum Computing Approach
Yunhan Chang, Amr Magdy, Federico M. Spedalieri, Ibrahim Sabek
https://arxiv.org/abs/2506.18799

Spatial Regionalization: A Hybrid Quantum Computing Approach
Quantum computing has shown significant potential to address complex optimization problems; however, its application remains confined to specific problems at limited scales. Spatial regionalization remains largely unexplored in quantum computing due to its complexity and large number of variables. In this paper, we introduce the first hybrid quantum-classical method to spatial regionalization by decomposing the problem into manageable subproblems, leveraging the strengths of both classical and …

Factors Impacting Faculty Adoption of Project-Based Learning in Computing Education: a Survey
Ahmad D. Suleiman, Yiming Tang, Daqing Hou
https://arxiv.org/abs/2507.18039 https:/…

Factors Impacting Faculty Adoption of Project-Based Learning in Computing Education: a Survey
This research full paper investigates the factors influencing computing educators' adoption of project-based learning (PjBL) in software engineering and computing curricula. Recognized as a student-centered pedagogical approach, PjBL has the potential to enhance student motivation, engagement, critical thinking, collaboration, and problem-solving skills. Despite these benefits, faculty adoption remains inconsistent due to challenges such as insufficient institutional support, time constraints, …

Study: only 32 countries, mostly in the Northern Hemisphere, host AI data centers, with the US, China, and the EU controlling 50% of the world's top facilities (New York Times)
https://www.nytimes.com…

A.I. Computing Power Is Splitting the World Into Haves and Have-Nots
As countries race to power artificial intelligence, a yawning gap is opening around the world.

Computing Tree Structures in Anonymous Graphs via Mobile Agents
Prabhat Kumar Chand, Manish Kumar, Anisur Rahaman Molla
https://arxiv.org/abs/2506.19365 ht…

Computing Tree Structures in Anonymous Graphs via Mobile Agents
Minimum Spanning Tree (MST) and Breadth-First Search (BFS) tree constructions are classical problems in distributed computing, traditionally studied in the message-passing model, where static nodes communicate via messages. This paper investigates MST and BFS tree construction in an agent-based network, where mobile agents explore a graph and compute. Each node hosts one agent, and communication occurs when agents meet at a node. We consider $n$ agents initially dispersed (one per node) in an a…

In-Memory Sorting-Searching with Cayley Tree
Subrata Paul, Sukanta Das, Biplab K Sikdar
https://arxiv.org/abs/2506.19379 https://arxi…

In-Memory Sorting-Searching with Cayley Tree
This work proposes a computing model to reduce the workload of CPU. It relies on the data intensive computation in memory, where the data reside, and effectively realizes an in-memory computing (IMC) platform. Each memory word, with additional logic, acts as a tiny processing element which forms the node of a Cayley tree. The Cayley tree in turn defines the framework for solving the data intensive computational problems. It finds the solutions for in-memory searching, computing the max (min) in…

As of today, people in the UK visiting sites likely to host pornographic, self-harm, eating disorder and suicide-related content will have to prove they are over 18.
https://www.computing.co.uk/news/2025/age-verification-comes-into-force-in-t…

Age verification for risky sites comes into force in the UK
As of today, people in the UK visiting sites likely to host pornographic, self-harm, eating disorder and suicide-related content will have to prove they are ...

Neuromorphic Computing: A Theoretical Framework for Time, Space, and Energy Scaling
James B Aimone
https://arxiv.org/abs/2507.17886 https://arxiv.org/pdf/2…

Neuromorphic Computing: A Theoretical Framework for Time, Space, and Energy Scaling
Neuromorphic computing (NMC) is increasingly viewed as a low-power alternative to conventional von Neumann architectures such as central processing units (CPUs) and graphics processing units (GPUs), however the computational value proposition has been difficult to define precisely. Here, we explain how NMC should be seen as general-purpose and programmable even though it differs considerably from a conventional stored-program architecture. We show that the time and space scaling of NMC is equ…

Computing the Stable Reduction of Hyperelliptic Curves in Residue Characteristic 2
Tim Gehrunger
https://arxiv.org/abs/2506.19663 https://

Computing the Stable Reduction of Hyperelliptic Curves in Residue Characteristic 2
Consider a hyperelliptic curve of genus $g$ over a field $K$ of characteristic zero. After extending $K$ we can view it as a marked curve with its $2g+2$ Weierstrass points. We prove some general properties of the stable reduction of this marked curve for a valuation of residue characteristic $2$ and refine an existing algorithm for its computation. We work out explicit examples up to genus $g=30$.

The answer to one of the most universal questions in computing education: "Which Programming Language Should I Teach First?" It's not what you're expecting. At all.
https://parentheticallyspeaking.org/articles/first-language-wrong-question/…

Which Programming Language Should I Teach First?
Parenthetically Speaking: Articles by Shriram Krishnamurthi

Design high-confidence computers using trusted instructional set architecture and emulators
Shuangbao Paul Wang
https://arxiv.org/abs/2506.18780 https://…

Design high-confidence computers using trusted instructional set architecture and emulators
High-confidence computing relies on trusted instructional set architecture, sealed kernels, and secure operating systems. Cloud computing depends on trusted systems for virtualization tasks. Branch predictions and pipelines are essential in improving performance of a CPU/GPU. But Spectre and Meltdown make modern processors vulnerable to be exploited. Disabling the prediction and pipeline is definitely not a good solution. On the other hand, current software patches can only address non-essentia…

Mixed-Mode In-Memory Computing: Towards High-Performance Logic Processing In A Memristive Crossbar Array
Nan Du, Ilia Polian, Christopher Bengel, Kefeng Li, Ziang Chen, Xianyue Zhao, Uwe Huebner, Li-Wei Chen, Feng Liu, Massimiliano Di Ventra, Stephan Menzel, Heidemarie Krueger
https://arxiv.org/abs/2506.19063

Mixed-Mode In-Memory Computing: Towards High-Performance Logic Processing In A Memristive Crossbar Array
In-memory computing is a promising alternative to traditional computer designs, as it helps overcome performance limits caused by the separation of memory and processing units. However, many current approaches struggle with unreliable device behavior, which affects data accuracy and efficiency. In this work, the authors present a new computing method that combines two types of operations,those based on electrical resistance and those based on voltage, within each memory cell. This design improv…

A Novel Coded Computing Approach for Distributed Multi-Task Learning
Minquan Cheng, Yongkang Wang, Lingyu Zhang, Youlong Wu
https://arxiv.org/abs/2507.18025 https://

A Novel Coded Computing Approach for Distributed Multi-Task Learning
Distributed multi-task learning (DMTL) effectively improves model generalization performance through the collaborative training of multiple related models. However, in large-scale learning scenarios, communication bottlenecks severely limit practical system performance. In this paper, we investigate the communication bottleneck within a typical DMTL system that employs non-linear global updates. This system involves distributed workers, assisted by a central server, who collaboratively learn di…

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design
Dong Ben, Hui Feng, Qian Wang
https://arxiv.org/abs/2507.16226

Distilled Large Language Model in Confidential Computing Environment for System-on-Chip Design
Large Language Models (LLMs) are increasingly used in circuit design tasks and have typically undergone multiple rounds of training. Both the trained models and their associated training data are considered confidential intellectual property (IP) and must be protected from exposure. Confidential Computing offers a promising solution to protect data and models through Trusted Execution Environments (TEEs). However, existing TEE implementations are not designed to support the resource-intensive n…

TRMAC: A Time-Reversal-based MAC Protocol for Wireless Networks within Computing Packages
Ama Bandara, Abhijit Das, Fatima Rodriguez-Galan, Eduard Alarcon, Sergi Abadal
https://arxiv.org/abs/2506.19487

TRMAC: A Time-Reversal-based MAC Protocol for Wireless Networks within Computing Packages
As chiplet-based integration and many-core architectures become the norm in high-performance computing, on-chip wireless communication has emerged as a compelling alternative to traditional interconnects. However, scalable Medium Access Control (MAC) remains a fundamental challenge, particularly under dense traffic and limited spectral resources. This paper presents TRMAC, a novel cross-layer MAC protocol that exploits the spatial focusing capability of Time Reversal (TR) to enable multiple par…

Weekend list of critical reading links about the state[1] of Tech, AI[2] hype/finance/politics, mostly long form:
Ed Zitron's The Hater's Guide To The AI Bubble
https://www.wheresyoured.at/the-haters-gui/
How to use computing power faster: on the weird ec…

The Hater's Guide To The AI Bubble
Hey! Before we go any further — if you want to support my work, please sign up for the premium version of Where’s Your Ed At, it’s a $7-a-month (or $70-a-year) paid product where every week you get a premium newsletter, all while supporting my free work too.  Also,

A New Pathway to Integrated Learning and Communication (ILAC): Large AI Model and Hyperdimensional Computing for Communication
Wei Xu, Zhaohui Yang, Derrick Wing Kwan Ng, Robert Schober, H. Vincent Poor, Zhaoyang Zhang, Xiaohu You
https://arxiv.org/abs/2506.18432

A New Pathway to Integrated Learning and Communication (ILAC): Large AI Model and Hyperdimensional Computing for Communication
The rapid evolution of forthcoming sixth-generation (6G) wireless networks necessitates the seamless integration of artificial intelligence (AI) with wireless communications to support emerging intelligent applications that demand both efficient communication and robust learning performance. This dual requirement calls for a unified framework of integrated learning and communication (ILAC), where AI enhances communication through intelligent signal processing and adaptive resource management, w…

Google has unveiled Gemini CLI, an open-source AI agent that allows developers to interact with the Gemini 2.5 LLM from their terminals and integrate its output into their activities.
https://www.computing.co.uk/news/2025/ai/google-unveils-gemini-cli-…

Google unveils Gemini CLI AI tool for coders
Takes on Claude Code and OpenAI Codex CLI.

Lessons from a Big-Bang Integration: Challenges in Edge Computing and Machine Learning
Alessandro Aneggi, Andrea Janes
https://arxiv.org/abs/2507.17270 htt…

Lessons from a Big-Bang Integration: Challenges in Edge Computing and Machine Learning
This experience report analyses a one year project focused on building a distributed real-time analytics system using edge computing and machine learning. The project faced critical setbacks due to a big-bang integration approach, where all components developed by multiple geographically dispersed partners were merged at the final stage. The integration effort resulted in only six minutes of system functionality, far below the expected 40 minutes. Through root cause analysis, the study identifi…

EigenWave: An Optimal O(N) Method for Computing Eigenvalues and Eigenvectors by Time-Filtering the Wave Equation
Daniel Appelo, Jeffrey W. Banks, William D. Henshaw, Ngan Le, Donald W. Schwendeman
https://arxiv.org/abs/2507.18282

EigenWave: An Optimal O(N) Method for Computing Eigenvalues and Eigenvectors by Time-Filtering the Wave Equation
An algorithm named EigenWave is described to compute eigenvalues and eigenvectors of elliptic boundary value problems. The algorithm, based on the recently developed WaveHoltz scheme, solves a related time-dependent wave equation as part of an iteration. At each iteration, the solution to the wave equation is filtered in time. As the iteration progresses, the filtered solution generally contains relatively larger and larger proportions of eigenmodes whose eigenvalues are near a chosen target fr…

Vehicular Cloud Computing: A cost-effective alternative to Edge Computing in 5G networks
Rosario Patan\`e, Nadjib Achir, Andrea Araldo, Lila Boukhatem
https://arxiv.org/abs/2507.15670

Vehicular Cloud Computing: A cost-effective alternative to Edge Computing in 5G networks
Edge Computing (EC) is a computational paradigm that involves deploying resources such as CPUs and GPUs near end-users, enabling low-latency applications like augmented reality and real-time gaming. However, deploying and maintaining a vast network of EC nodes is costly, which can explain its limited deployment today. A new paradigm called Vehicular Cloud Computing (VCC) has emerged and inspired interest among researchers and industry. VCC opportunistically utilizes existing and idle vehicular …

Ink & Switch, on “malleable software”.
https://www.inkandswitch.com/essay/malleable-software/
This is software that can be manipulated by a user. The software itself, not just the document.
I’m reminded of Houyhnhnm Computing (

@… @… Computing became perfectly deterministic, of course.
/s

Linear Layouts Revisited: Stacks, Queues, and Exact Algorithms
Thomas Depian, Simon D. Fink, Robert Ganian, Vaishali Surianarayanan
https://arxiv.org/abs/2508.16319 https://

Linear Layouts Revisited: Stacks, Queues, and Exact Algorithms
In spite of the extensive study of stack and queue layouts, many fundamental questions remain open concerning the complexity-theoretic frontiers for computing stack and queue layouts. A stack (resp. queue) layout places vertices along a line and assigns edges to pages so that no two edges on the same page are crossing (resp. nested). We provide three new algorithms which together substantially expand our understanding of these problems: (1) A fixed-parameter algorithm for computing minimum-pa…

🧲 Scientists find new quantum behavior in unusual superconducting material
https://phys.org/news/2025-08-scientists-quantum-behavior-unusual-superconducting.html

Scientists find new quantum behavior in unusual superconducting material
Researchers at Rice University and collaborating institutions have discovered direct evidence of active flat electronic bands in a kagome superconductor. This breakthrough could pave the way for new methods to design quantum materials—including superconductors, topological insulators and spin-based electronics—that could power future electronics and computing technologies.

ApproxGNN: A Pretrained GNN for Parameter Prediction in Design Space Exploration for Approximate Computing
Ondrej Vlcek, Vojtech Mrazek
https://arxiv.org/abs/2507.16379 https://…

ApproxGNN: A Pretrained GNN for Parameter Prediction in Design Space Exploration for Approximate Computing
Approximate computing offers promising energy efficiency benefits for error-tolerant applications, but discovering optimal approximations requires extensive design space exploration (DSE). Predicting the accuracy of circuits composed of approximate components without performing complete synthesis remains a challenging problem. Current machine learning approaches used to automate this task require retraining for each new circuit configuration, making them computationally expensive and time-consu…

Microsoft has unveiled “Copilot Vision”, a successor to the controversial Recall feature, as part of its expanding suite of AI tools for Copilot PCs – and it's already drawing criticism for its privacy implications.
https://www.computing.co.uk/news/2025/ai/w…

Windows 11’s 'Copilot Vision' watches your screen in real time
Microsoft's latest AI-powered update for Windows 11 is raising eyebrows once again.

Reservoir Computing as a Language Model
Felix K\"oster, Atsushi Uchida
https://arxiv.org/abs/2507.15779 https://arxiv.org/pdf/25…

Reservoir Computing as a Language Model
Large Language Models (LLM) have dominated the science and media landscape duo to their impressive performance on processing large chunks of data and produce human-like levels of text. Nevertheless, their huge energy demand and slow processing still a bottleneck for further increasing quality while also making the models accessible to everyone. To solve this bottleneck, we will investigate how reservoir computing performs on natural text processing, which could enable fast and energy efficient …

Dependability of UAV-Based Networks and Computing Systems: A Survey
Qingyang Zhang, Mohammad Dwipa Furqan, Tasfia Nutzhat, Fumio Machida, Ermeson Andrade
https://arxiv.org/abs/2506.16786

Dependability of UAV-Based Networks and Computing Systems: A Survey
Uncrewed Aerial Vehicle (UAV) computing and networking are becoming a fundamental computation infrastructure for diverse cyber-physical application systems. UAVs can be empowered by AI on edge devices and can communicate with other UAVs and ground stations via wireless communication networks. Dynamic computation demands and heterogeneous computing resources are distributed in the system and need to be controlled to maintain the quality of services and to accomplish critical missions. With the e…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/4]:
- Flexible Coded Distributed Convolution Computing for Enhanced Straggler Resilience and Numerical ...
Shuo Tan, Rui Liu, Xuesong Han, XianLei Long, Kai Wan, Linqi Song, Yong Li

Quantum Software Security Challenges within Shared Quantum Computing Environments
Samuel Ovaskainen, Majid Haghparast, Tommi Mikkonen
https://arxiv.org/abs/2507.17712 https://…

Quantum Software Security Challenges within Shared Quantum Computing Environments
The number of qubits in quantum computers keeps growing, but most quantum programs remain relatively small because of the noisy nature of the underlying quantum hardware. This might lead quantum cloud providers to explore increased hardware utilization, and thus profitability through means such as multi-programming, which would allow the execution of multiple programs in parallel. The adoption of such technology would bring entirely new challenges to the field of quantum software security. This…

It's hard enough to read news articles about quantum computing without it being conflated with other "quantum" research. (e.g. the "quantum compass" being tested as a GPS alternative, isn't quantum computing.)

At Microsoft, we’re advancing quantum computing at every level. With our newly developed family of 4D geometric codes, and our co-designed quantum work with Atom Computing
, we’re getting closer to making large-scale quantum computing a reality. Learn more: https://aka.ms/AQBlogQEC

Microsoft advances quantum error correction with a family of novel four-dimensional codes - Microsoft Azure Quantum Blog
Learn how we're advancing quantum computing by developing 4D error-correction codes that are applicable to many types of qubits.

Brain-inspired interpretable reservoir computing with resonant recurrent neural networks
Mark A. Kramer
https://arxiv.org/abs/2506.17083 https://

Brain-inspired interpretable reservoir computing with resonant recurrent neural networks
Traditional artificial neural networks consist of nodes with non-oscillatory dynamics. Biological neural networks, on the other hand, consist of oscillatory components embedded in an oscillatory environment. Motivated by this feature of biological neurons, we describe a reservoir computing framework with explicit damped, oscillatory node dynamics. We express the oscillatory dynamics using two history dependent terms to connect these dynamics with existing artificial neural network approaches an…

Armada, whose mobile AI data centers for use in remote environments have been used by the US Navy, raised $131M, bringing its total funding to $200M (Cal Biesecker/Defense Daily)
https://www.defensedaily.com/armada-announ

Armada Announces $131 Million Funding Raise To Scale Relocatable Data Center
Armada, a developer and manufacturer of mobile and relocatable data centers that provide computing power to remote and challenged areas, has raised $131

Replaced article(s) found for cs.PL. https://arxiv.org/list/cs.PL/new
[1/1]:
- HPVM-HDC: A Heterogeneous Programming System for Accelerating Hyperdimensional Computing
Arbore, Routh, Noor, Kothari, Yang, Xu, Pinge, Zhou, Rosing, Adve

A "watch your replay videos" reflection assignment on comparing programming without versus with generative AI: learning about programming, critical AI use and limitations, and reflection
Sarah "Magz" Fernandez, Greg L Nelson
https://arxiv.org/abs/2507.17226

A "watch your replay videos" reflection assignment on comparing programming without versus with generative AI: learning about programming, critical AI use and limitations, and reflection
Generative AI is disrupting computing education. Most interventions focus on teaching GenAI use rather than helping students understand how AI changes their programming process. We designed and deployed a novel comparative video reflection assignment adapting the Describe, Examine, then Articulate Learning (DEAL) framework. In an introductory software engineering course, students recorded themselves programming during their team project two times: first without, then with using generative AI. S…

Web Diagrams of Cluster Variables for Grassmannian Gr(4,8)
Wen Ting Zhang, Rui Zhi Tang, Jin Xing Zhao
https://arxiv.org/abs/2507.18432 https://arxiv.org/p…

Web Diagrams of Cluster Variables for Grassmannian Gr(4,8)
Gaetz, Pechenik, Pfannerer, Striker, and Swanson introduced the concept of hourglass plabic graphs and provided a method for computing web diagrams and invariants corresponding to $4\times n$ Young tableaux, while Elkin, Musiker, and Wright applied Lam's method to explicitly compute the webs compatible with cluster variables in Gr(3,n) and their twists, namely, the preimages of the immanant map introduced by Fraser, Lam, and Le. In this paper, we use these two methods to compute both the web di…

Improving the lifetime of aluminum-based superconducting qubits through atomic layer etching and deposition
Neha Mahuli (AWS Center for Quantum Computing, Pasadena, CA, USA), Joaquin Minguzzi (AWS Center for Quantum Computing, Pasadena, CA, USA), Jiansong Gao (AWS Center for Quantum Computing, Pasadena, CA, USA), Rachel Resnick (Google Research), Sandra Diez (National Institute of Standards and Technology), Cosmic Raj (AWS Center for Quantum Computing, Pasadena, CA, USA), Guillaume Mar…

Improving the lifetime of aluminum-based superconducting qubits through atomic layer etching and deposition
We present a dry surface treatment combining atomic layer etching and deposition (ALE and ALD) to mitigate dielectric loss in fully fabricated superconducting quantum devices formed from aluminum thin films on silicon. The treatment, performed as a final processing step prior to device packaging, starts by conformally removing the native metal oxide and fabrication residues from the exposed surfaces through ALE before \textit{in situ} encapsulating the metal surfaces with a thin dielectric laye…

SAFER-D: A Self-Adaptive Security Framework for Distributed Computing Architectures
Marco Stadler, Michael Vierhauser, Michael Riegler, Daniel Waghubinger, Johannes Sametinger
https://arxiv.org/abs/2506.16545

SAFER-D: A Self-Adaptive Security Framework for Distributed Computing Architectures
The rise of the Internet of Things and Cyber-Physical Systems has introduced new challenges on ensuring secure and robust communication. The growing number of connected devices increases network complexity, leading to higher latency and traffic. Distributed computing architectures (DCAs) have gained prominence to address these issues. This shift has significantly expanded the attack surface, requiring additional security measures to protect all components -- from sensors and actuators to edge n…

Micron reports Q3 revenue up 37% YoY to $9.3B, vs. $8.85B est., forecasts Q4 revenue above estimates, and says it's on track for record revenue this fiscal year (Dina Bass/Bloomberg)
https://www.bloomberg.com/news/articles/20

Encrypted-State Quantum Compilation Scheme Based on Quantum Circuit Obfuscation
Chenyi Zhang, Tao Shang, Xueyi Guo
https://arxiv.org/abs/2507.17589 https://

Encrypted-State Quantum Compilation Scheme Based on Quantum Circuit Obfuscation
With the rapid advancement of quantum computing, quantum compilation has become a crucial layer connecting high-level algorithms with physical hardware. In quantum cloud computing, compilation is performed on the cloud side, which exposes user circuits to potential risks such as structural leakage and output predictability. To address these issues, we propose the encrypted-state quantum compilation scheme based on quantum circuit obfuscation (ECQCO), the first secure compilation framework tailo…

No sector has seen greater change than automotive. Packed with intelligent sensors, AI, GPS, cameras and in-car software, today’s vehicles generate and transmit vast volumes of data.
While this helps with seamless connectivity and smarter driving, it also creates serious security, privacy, and compliance risks automotive firms and tech providers can’t afford to ignore.

How connected cars are creating new data protection risks
Seamless connectivity helps with smarter driving, but creates security, privacy and compliance risks vendors can’t afford to ignore, argues Jonathan Armstrong.

Reconfigurable Intelligent Surface-Enabled Green and Secure Offloading for Mobile Edge Computing Networks
Tong-Xing Zheng, Xinji Wang, Xin Chen, Di Mao, Jia Shi, Cunhua Pan, Chongwen Huang, Haiyang Ding, Zan Li
https://arxiv.org/abs/2507.16666

Reconfigurable Intelligent Surface-Enabled Green and Secure Offloading for Mobile Edge Computing Networks
This paper investigates a multi-user uplink mobile edge computing (MEC) network, where the users offload partial tasks securely to an access point under the non-orthogonal multiple access policy with the aid of a reconfigurable intelligent surface (RIS) against a multi-antenna eavesdropper. We formulate a non-convex optimization problem of minimizing the total energy consumption subject to secure offloading requirement, and we build an efficient block coordinate descent framework to iteratively…

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- Distributed Computation with Local Advice
Balliu, Brandt, Kuhn, Nowicki, Olivetti, Rotenberg, Suomela

Two-Timescale Dynamic Service Deployment and Task Scheduling with Spatiotemporal Collaboration in Mobile Edge Networks
Yang Li, Xing Zhang, Yunji Zhao, Wenbo Wang
https://arxiv.org/abs/2508.16293

Two-Timescale Dynamic Service Deployment and Task Scheduling with Spatiotemporal Collaboration in Mobile Edge Networks
Collaborative edge computing addresses the resource constraints of individual edge nodes by enabling resource sharing and task co-processing across multiple nodes. To fully leverage the advantages of collaborative edge computing, joint optimization of service deployment and task scheduling is necessary. Existing optimization methods insufficiently address the collaboration across spatial and temporal dimensions, which hinders their adaptability to the spatiotemporally varying nature of user dem…

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices
Wei Fan, JinYi Yoon, Xiaochang Li, Huajie Shao, Bo Ji
https://arxiv.org/abs/2507.17228

P3SL: Personalized Privacy-Preserving Split Learning on Heterogeneous Edge Devices
Split Learning (SL) is an emerging privacy-preserving machine learning technique that enables resource constrained edge devices to participate in model training by partitioning a model into client-side and server-side sub-models. While SL reduces computational overhead on edge devices, it encounters significant challenges in heterogeneous environments where devices vary in computing resources, communication capabilities, environmental conditions, and privacy requirements. Although recent studie…

Quantum Communication Complexity of L2-Regularized Linear Regression Protocols
Sayaki Matsushita
https://arxiv.org/abs/2508.16141 https://arxiv.org/pdf/250…

Quantum Communication Complexity of L2-Regularized Linear Regression Protocols
Linear regression is fundamental to statistical analysis and machine learning, but its application to large-scale datasets necessitates distributed computing. The problem also arises in quantum computing, where handling extensive data requires distributed approaches. This paper investigates distributed linear regression in the quantum coordinator model. Building upon the distributed quantum least squares protocol developed by Montanaro and Shao, we propose improved and extended quantum protocol…

Crosslisted article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
- Competition and Attraction Improve Model Fusion
Jo\~ao Abrantes, Robert Tjarko Lange, Yujin Tang

Parallel nonlinear neuromorphic computing with temporal encoding
Guangfeng You, Chao Qian, Hongsheng Chen
https://arxiv.org/abs/2506.17261 https://

Parallel nonlinear neuromorphic computing with temporal encoding
The proliferation of deep learning applications has intensified the demand for electronic hardware with low energy consumption and fast computing speed. Neuromorphic photonics have emerged as a viable alternative to directly process high-throughput information at the physical space. However, the simultaneous attainment of high linear and nonlinear expressivity posse a considerable challenge due to the power efficiency and impaired manipulability in conventional nonlinear materials and optoelect…

Designing for Learning with Generative AI is a Wicked Problem: An Illustrative Longitudinal Qualitative Case Series
Clara Scalzer, Saurav Pokhrel, Sara Hunt, Greg L Nelson
https://arxiv.org/abs/2507.17230

Designing for Learning with Generative AI is a Wicked Problem: An Illustrative Longitudinal Qualitative Case Series
Students continue their education when they feel their learning is meaningful and relevant for their future careers. Computing educators now face the challenge of preparing students for careers increasingly shaped by generative AI (GenAI) with the goals of supporting their learning, motivation, ethics, and career development. Our longitudinal qualitative study of students in a GenAI-integrated creative media course shows how this is a "wicked" problem: progress on one goal can then impede progr…

Welcome to Computing's weekly roundup of tech news in Asia. This time we look at the offence taken in China at the US commerce secretary’s statements, Modi’s plans to make India a chip superpower and Accenture’s big Aussie cyber buy.
https://www.computing.co.uk/news/2025/loos…

Loose-lips Lutnick costs Nvidia - Asian Tech Roundup
Welcome to Computing's weekly roundup of tech news in Asia. This time we look at the offence taken in China at the US commerce secretary’s ...

Germany-based Q.ANT, which is developing energy-efficient photonic processors for AI and high-performance computing, raised a €62M Series A (Tamara Djurickovic/Tech.eu)
https://tech.eu/2025/07/17/qant-raises-eur62m-to-transform-the…

Q.ANT raises €62M to transform the future of computing with photonic processing
Germany-based Q.ANT, a pioneer in photonic processing, has secured €62 million Series A financing round to accelerate the commercialisation of its energy-efficient photonic processors for artificial intelligence (AI) and high-performance computing (HPC).  As AI infrastructure scales globally, traditional chip technology (CMOS) reaches its physical limits, performance stagnates, and electricity demand is reaching untenable levels. According to a report by the International Energy Agency (IEA…

Crosslisted article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- Towards Integrated Energy-Communication-Transportation Hub: A Base-Station-Centric Design in 5G a...
Linfeng Shen, Guanzhen Wu, Cong Zhang, Xiaoyi Fan, Jiangchuan Liu

Quantum Machine Learning for Predicting Binding Free Energies in Structure-Based Virtual Screening
Pei-Kun Yang
https://arxiv.org/abs/2507.18425 https://ar…

Quantum Machine Learning for Predicting Binding Free Energies in Structure-Based Virtual Screening
In structure-based virtual screening, it is often necessary to evaluate the binding free energy of protein-ligand complexes by considering not only molecular conformations but also how these structures shift and rotate in space. The number of possible combinations grows rapidly and can become overwhelming. While classical computing has limitations in this context, quantum computing offers a promising alternative due to its inherent parallelism. In this study, we introduce a quantum machine lear…

A Survey of Post-Quantum Cryptography Support in Cryptographic Libraries
Nadeem Ahmed, Lei Zhang, Aryya Gangopadhyay
https://arxiv.org/abs/2508.16078 https://

A Survey of Post-Quantum Cryptography Support in Cryptographic Libraries
The rapid advancement of quantum computing poses a significant threat to modern cryptographic systems, necessitating the transition to Post-Quantum Cryptography (PQC). This study evaluates the support for PQC algorithms within nine widely used open-source cryptographic libraries -- OpenSSL, wolfSSL, BoringSSL, LibreSSL, Bouncy Castle, libsodium, Crypto++, Botan, and MbedTLS -- focusing on their implementation of the NIST-selected PQC finalists: CRYSTALS-Kyber, CRYSTALS-Dilithium, FALCON, and SP…

A review of the legal challenges associated with generative AI training disputes emphasises the need for clarity from the UK government, legislature and courts.
https://www.computing.co.uk/feature/2025/scraping-surface-generative-ai-training-disputes…

Scraping the surface of generative AI training disputes and their legal challenges
A review of the legal challenges associated with generative AI training disputes emphasises the need for clarity from the UK government, legislature and courts.

Challenges and Practices in Quantum Software Testing and Debugging: Insights from Practitioners
Jake Zappin, Trevor Stalnaker, Oscar Chaparro, Denys Poshyvanyk
https://arxiv.org/abs/2506.17306

Challenges and Practices in Quantum Software Testing and Debugging: Insights from Practitioners
Quantum software engineering is an emerging discipline with distinct challenges, particularly in testing and debugging. As quantum computing transitions from theory to implementation, developers face issues not present in classical software development, such as probabilistic execution, limited observability, shallow abstractions, and low awareness of quantum-specific tools. To better understand current practices, we surveyed 26 quantum software developers from academia and industry and conducte…

Replaced article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
- Near-Tight Runtime Guarantees for Many-Objective Evolutionary Algorithms
Simon Wietheger, Benjamin Doerr

Poset-Markov Channels: Capacity via Group Symmetry
Eray Unsal Atay, Eitan Levin, Venkat Chandrasekaran, Victoria Kostina
https://arxiv.org/abs/2506.19305 h…

Poset-Markov Channels: Capacity via Group Symmetry
Computing channel capacity is in general intractable because it is given by the limit of a sequence of optimization problems whose dimensionality grows to infinity. As a result, constant-sized characterizations of feedback or non-feedback capacity are known for only a few classes of channels with memory. This paper introduces poset-causal channels$\unicode{x2014}$a new formalism of a communication channel in which channel inputs and outputs are indexed by the elements of a partially ordered set…

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- A Comparative Analysis of Distributed Linear Solvers under Data Heterogeneity
Boris Velasevic, Rohit Parasnis, Christopher G. Brinton, Navid Azizan

No Scratch Quantum Computing by Reducing Qubit Overhead for Efficient Arithmetics
Omid Faizy, Norbert Wehn, Paul Lukowicz, Maximilian Kiefer-Emmanouilidis
https://arxiv.org/abs/2506.17135

No Scratch Quantum Computing by Reducing Qubit Overhead for Efficient Arithmetics
Quantum arithmetic computation requires a substantial number of scratch qubits to stay reversible. These operations necessitate qubit and gate resources equivalent to those needed for the larger of the input or output registers due to state encoding. Quantum Hamiltonian Computing (QHC) introduces a novel approach by encoding input for logic operations within a single rotating quantum gate. This innovation reduces the required qubit register $ N $ to the size of the output states $ O $, where $ …

Analysis of Post-Quantum Cryptography in User Equipment in 5G and Beyond
Sanzida Hoque, Abdullah Aydeger, Engin Zeydan, Madhusanka Liyanage
https://arxiv.org/abs/2507.17074 http…

Analysis of Post-Quantum Cryptography in User Equipment in 5G and Beyond
The advent of quantum computing threatens the security of classical public-key cryptographic systems, prompting the transition to post-quantum cryptography (PQC). While PQC has been analyzed in theory, its performance in practical wireless communication environments remains underexplored. This paper presents a detailed implementation and performance evaluation of NIST-selected PQC algorithms in user equipment (UE) to UE communications over 5G networks. Using a full 5G emulation stack (Open5GS a…

Replaced article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
- CatCMA with Margin: Stochastic Optimization for Continuous, Integer, and Categorical Variables
Ryoki Hamano, Masahiro Nomura, Shota Saito, Kento Uchida, Shinichi Shirakawa

Snowcap Compute, which is working on building AI computing chips using superconducting tech, raised a $23M seed and says Pat Gelsinger will join its board (Stephen Nellis/Reuters)
https://www.reuters.com/business/snowcap-comp…

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- Picsou: Enabling Replicated State Machines to Communicate Efficiently
Frank, Murray, Tankuranand, Yoo, Xu, Crooks, Gupta, Kapritsos

Validating Terrain Models in Digital Twins for Trustworthy sUAS Operations
Arturo Miguel Russell Bernal, Maureen Petterson, Pedro Antonio Alarcon Granadeno, Michael Murphy, James Mason, Jane Cleland-Huang
https://arxiv.org/abs/2508.16104

Validating Terrain Models in Digital Twins for Trustworthy sUAS Operations
With the increasing deployment of small Unmanned Aircraft Systems (sUAS) in unfamiliar and complex environments, Environmental Digital Twins (EDT) that comprise weather, airspace, and terrain data are critical for safe flight planning and for maintaining appropriate altitudes during search and surveillance operations. With the expansion of sUAS capabilities through edge and cloud computing, accurate EDT are also vital for advanced sUAS capabilities, like geolocation. However, real-world sUAS de…

Welcome to Computing's weekly roundup of tech news in Asia. This time we look at the results of Australia’s age assurance trials, plus signs of regret over US chip bans to China.
https://www.computing.co.uk/news/2025/australia-okays-age-assuran…

Australia okays age assurance tech - Asian Tech Roundup
Welcome to Computing's weekly roundup of tech news in Asia. This time we look at the results of Australia’s age assurance trials, plus signs of ...

Universal Error Correction for Distributed Quantum Computing
Daowen Qiu, Ligang Xiao, Le Luo, Paulo Mateus
https://arxiv.org/abs/2508.15580 https://arxiv.o…

Universal Error Correction for Distributed Quantum Computing
In distributed quantum computing, the final solution of a problem is usually achieved by catenating these partial solutions resulted from different computing nodes, but intolerable errors likely yield in this catenation process. In this paper, we propose a universal error correction scheme to reduce errors and obtain effective solutions. Then, we apply this error correction scheme to designing a distributed phase estimation algorithm that presents a basic tool for studying distributed Shor's al…

PhishingHook: Catching Phishing Ethereum Smart Contracts leveraging EVM Opcodes
Pasquale De Rosa, Simon Queyrut, Y\'erom-David Bromberg, Pascal Felber, Valerio Schiavoni
https://arxiv.org/abs/2506.19480

PhishingHook: Catching Phishing Ethereum Smart Contracts leveraging EVM Opcodes
The Ethereum Virtual Machine (EVM) is a decentralized computing engine. It enables the Ethereum blockchain to execute smart contracts and decentralized applications (dApps). The increasing adoption of Ethereum sparked the rise of phishing activities. Phishing attacks often target users through deceptive means, e.g., fake websites, wallet scams, or malicious smart contracts, aiming to steal sensitive information or funds. A timely detection of phishing activities in the EVM is therefore crucial …

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- FDO Manager: Minimum Viable FAIR Digital Object Implementation
Zoubia, Asundi, Koumpis, Lange, Dogan, Beyan, Boukhers

Replaced article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
- SpiLiFormer: Enhancing Spiking Transformers with Lateral Inhibition
Zeqi Zheng, Yanchen Huang, Yingchao Yu, Zizheng Zhu, Junfeng Tang, Zhaofei Yu, Yaochu Jin

Google has disclosed new figures on the energy consumption of its AI-powered search assistant, Gemini, as debate intensifies over the environmental impact of AI.
https://www.computing.co.uk/news/2025/ai/google-publishes-data-on-energy-use-of-…

Google publishes data on energy use of AI search queries
Google has disclosed new figures on the energy consumption of its AI-powered search assistant, Gemini, as debate intensifies over the environmental impact of AI.

Robust and Efficient Quantum Reservoir Computing with Discrete Time Crystal
Da Zhang, Xin Li, Yibin Guo, Haifeng Yu, Yirong Jin, Zhang-Qi Yin
https://arxiv.org/abs/2508.15230 ht…

Robust and Efficient Quantum Reservoir Computing with Discrete Time Crystal
The rapid development of machine learning and quantum computing has placed quantum machine learning at the forefront of research. However, existing quantum machine learning algorithms based on quantum variational algorithms face challenges in trainability and noise robustness. In order to address these challenges, we introduce a gradient-free, noise-robust quantum reservoir computing algorithm that harnesses discrete time crystal dynamics as a reservoir. We first calibrate the memory, nonlinear…

Securing Swarms: Cross-Domain Adaptation for ROS2-based CPS Anomaly Detection
Julia Boone, Fatemeh Afghah
https://arxiv.org/abs/2508.15865 https://arxiv.or…

Securing Swarms: Cross-Domain Adaptation for ROS2-based CPS Anomaly Detection
Cyber-physical systems (CPS) are being increasingly utilized for critical applications. CPS combines sensing and computing elements, often having multi-layer designs with networking, computational, and physical interfaces, which provide them with enhanced capabilities for a variety of application scenarios. However, the combination of physical and computational elements also makes CPS more vulnerable to attacks compared to network-only systems, and the resulting impacts of CPS attacks can be su…

Replaced article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- Staleness-Centric Optimizations for Parallel Diffusion MoE Inference
Jiajun Luo, Lizhuo Luo, Jianru Xu, Jiajun Song, Rongwei Lu, Chen Tang, Zhi Wang

Colt Technology Services has confirmed that data was stolen in a recent cyberattack that disrupted its operations.
The admission comes as the Warlock ransomware gang begins auctioning what it claims are over a million stolen documents on its dark web site.
https://www.computing.co.uk/news/202…

Colt confirms data theft
Colt Technology Services has confirmed that data was stolen in a recent cyberattack that disrupted its operations.

Spain-based Multiverse Computing, which makes tools to compress LLMs by up to 95% using "quantum-inspired" networks, raised a €189M Series B and has 100 clients (Julie Bort/TechCrunch)
https://techcrunch.com/2025/06/12/mult

Multiverse Computing raises $215M for tech that could radically slim AI costs | TechCrunch
Spanish startup Multiverse Computing announced that it raised an enormous Series B round on the strength of a technology it calls “CompactifAI.”

An Improved ChaCha Algorithm Based on Quantum Random Number
Chao Liu, Shuai Zhao, Chenhao Jia, Gengran Hu, Tingting Cui
https://arxiv.org/abs/2507.18157 https://

An Improved ChaCha Algorithm Based on Quantum Random Number
Due to the merits of high efficiency and strong security against timing and side-channel attacks, ChaCha has been widely applied in real-time communication and data streaming scenarios. However, with the rapid development of AI-assisted cryptanalysis and quantum computing technologies, there are serious challenges to the secure implementation of ChaCha cipher. To further strengthen the security of ChaCha cipher, we propose an improved variant based on quantum random numbers, i.e., Quantum Rando…

Optimizing Compilation for Distributed Quantum Computing via Clustering and Annealing
Ruilin Zhou, Jinglei Cheng, Yuhang Gan, Junyu Liu, Chen Qian
https://arxiv.org/abs/2508.15267

Optimizing Compilation for Distributed Quantum Computing via Clustering and Annealing
Efficiently mapping quantum programs onto Distributed quantum computing (DQC) are challenging, particularly when considering the heterogeneous quantum processing units (QPUs) with different structures. In this paper, we present a comprehensive compilation framework that addresses these challenges with three key insights: exploiting structural patterns within quantum circuits, using clustering for initial qubit placement, and adjusting qubit mapping with annealing algorithms. Experimental result…

[2025-08-25 Mon (UTC), 2 new articles found for cs.DC Distributed, Parallel, and Cluster Computing]
toXiv_bot_toot

Quantum Resource Theories of Anyonic Entanglement
Wenhao Ye, Li You, Cheng-Qian Xu
https://arxiv.org/abs/2506.19735 https://arxiv.org…

Quantum Resource Theories of Anyonic Entanglement
As information carriers for fault-tolerant quantum computing, systems composed of anyons exhibit non-tensor product state spaces due to their distinctive fusion rules, leading to fundamentally different entanglement properties from conventional quantum systems. However, a quantitative characterization of entanglement for general anyonic states remains elusive. In this Letter, within the framework of resource theory, we propose three measures that quantify total entanglement, conventional entang…

Choosing the Right Battery Model for Data Center Simulations
Paul Kilian, Philipp Wiesner, Odej Kao
https://arxiv.org/abs/2506.17739 https://

Choosing the Right Battery Model for Data Center Simulations
As demand for computing resources continues to rise, the increasing cost of electricity and anticipated regulations on carbon emissions are prompting changes in data center power systems. Many providers are now operating compute nodes in microgrids, close to renewable power generators and energy storage, to maintain full control over the cost and origin of consumed electricity. Recently, new co-simulation testbeds have emerged that integrate domain-specific simulators to support research, devel…

Enhanced Image Recognition Using Gaussian Boson Sampling
Si-Qiu Gong, Ming-Cheng Chen, Hua-Liang Liu, Hao Su, Yi-Chao Gu, Hao-Yang Tang, Meng-Hao Jia, Yu-Hao Deng, Qian Wei, Hui Wang, Han-Sen Zhong, Xiao Jiang, Li Li, Nai-Le Liu, Chao-Yang Lu, Jian-Wei Pan
https://arxiv.org/abs/2506.19707

Enhanced Image Recognition Using Gaussian Boson Sampling
Gaussian boson sampling (GBS) has emerged as a promising quantum computing paradigm, demonstrating its potential in various applications. However, most existing works focus on theoretical aspects or simple tasks, with limited exploration of its capabilities in solving real-world practical problems. In this work, we propose a novel GBS-based image recognition scheme inspired by extreme learning machine (ELM) to enhance the performance of perceptron and implement it using our latest GBS device, J…

[2025-06-25 Wed (UTC), 9 new articles found for cs.DC Distributed, Parallel, and Cluster Computing]
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[2025-07-24 Thu (UTC), 8 new articles found for cs.DC Distributed, Parallel, and Cluster Computing]
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Quantum Optimal Control with Geodesic Pulse Engineering
Dylan Lewis, Roeland Wiersema, Sougato Bose
https://arxiv.org/abs/2508.16029 https://arxiv.org/pdf/…

Quantum Optimal Control with Geodesic Pulse Engineering
Designing multi-qubit quantum logic gates with experimental constraints is an important problem in quantum computing. Here, we develop a new quantum optimal control algorithm for finding unitary transformations with constraints on the Hamiltonian. The algorithm, geodesic pulse engineering (GEOPE), uses differential programming and geodesics on the Riemannian manifold of $\textrm{SU}(2^n)$ for $n$ qubits. We demonstrate significant improvements over the widely used gradient-based method, GRAPE, …

Comparing performance of variational quantum algorithm simulations on HPC systems
Marco De Pascale, Tobias Valentin Bauer, Yaknan John Gambo, Mario Hern\'andez Vera, Stefan Huber, Burak Mete, Amit Jamadagni, Amine Bentellis, Marita Oliv, Luigi Iapichino, Jeanette Miriam Lorenz
https://arxiv.org/abs/2507.17614

Comparing performance of variational quantum algorithm simulations on HPC systems
Variational quantum algorithms are of special importance in the research on quantum computing applications because of their applicability to current Noisy Intermediate-Scale Quantum (NISQ) devices. The main building blocks of these algorithms (among them, the definition of the Hamiltonian and of the ansatz, the optimizer) define a relatively large parameter space, making the comparison of results and performance between different approaches and software simulators cumbersome and prone to errors…

[2025-06-24 Tue (UTC), 13 new articles found for cs.DC Distributed, Parallel, and Cluster Computing]
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[2025-07-25 Fri (UTC), 15 new articles found for cs.DC Distributed, Parallel, and Cluster Computing]
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Automated discovery of heralded ballistic graph state generators for fusion-based photonic quantum computation
Gavin S. Hartnett, Dave Kielpinski, Smarak Maity, Pranav S. Mundada, Yuval Baum, Michael R. Hush
https://arxiv.org/abs/2508.16505

Automated discovery of heralded ballistic graph state generators for fusion-based photonic quantum computation
Designing photonic circuits that prepare graph states with high fidelity and success probability is a central challenge in linear optical quantum computing. Existing approaches rely on hand-crafted designs or fusion-based assemblies. In the absence of multiplexing/boosting, both post-selected ballistic circuits and sequential fusion builds exhibit exponentially decreasing single-shot yields, motivating automated discovery of higher-success circuits. We present a general-purpose optimization fra…

Robust Control and Entanglement of Qudits in Neutral Atom Arrays
Amir Burshtein, Shachar Fraenkel, Moshe Goldstein, Ran Finkelstein
https://arxiv.org/abs/2508.16294 https://

Robust Control and Entanglement of Qudits in Neutral Atom Arrays
Quantum devices comprised of elementary components with more than two stable levels - so-called qudits - enrich the accessible Hilbert space, enabling applications ranging from fault-tolerant quantum computing to simulating complex many-body models. While several quantum platforms are built from local elements that are equipped with a rich spectrum of stable energy levels, schemes for the efficient control and entanglement of qudits are scarce. Importantly, no experimental demonstration of mult…

Efficient Routing of Inference Requests across LLM Instances in Cloud-Edge Computing
Shibo Yu, Mohammad Goudarzi, Adel Nadjaran Toosi
https://arxiv.org/abs/2507.15553

Efficient Routing of Inference Requests across LLM Instances in Cloud-Edge Computing
The rising demand for Large Language Model (LLM) inference services has intensified pressure on computational resources, resulting in latency and cost challenges. This paper introduces a novel routing algorithm based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to distribute inference requests across heterogeneous LLM instances in a cloud-edge computing environment. Formulated as a multi-objective optimization problem, the algorithm balances response quality, response time, and i…

Hybrid Classical-Quantum Supercomputing: A demonstration of a multi-user, multi-QPU and multi-GPU environment
Mateusz Slysz, Piotr Rydlichowski, Krzysztof Kurowski, Omar Bacarezza, Esperanza Cuenca Gomez, Zohim Chandani, Bettina Heim, Pradnya Khalate, William R. Clements, James Fletcher
https://arxiv.org/abs/2508.16297

Hybrid Classical-Quantum Supercomputing: A demonstration of a multi-user, multi-QPU and multi-GPU environment
Achieving a practical quantum advantage for near-term applications is widely expected to rely on hybrid classical-quantum algorithms. To deliver this practical advantage to users, high performance computing (HPC) centers need to provide a suitable software and hardware stack that supports algorithms of this type. In this paper, we describe the world's first implementation of a classical-quantum environment in an HPC center that allows multiple users to execute hybrid algorithms on multiple quan…

Harnessing the Full Potential of RRAMs through Scalable and Distributed In-Memory Computing with Integrated Error Correction
Huynh Q. N. Vo, Md Tawsif Rahman Chowdhury, Paritosh Ramanan, Murat Yildirim, Gozde Tutuncuoglu
https://arxiv.org/abs/2508.13298

Harnessing the Full Potential of RRAMs through Scalable and Distributed In-Memory Computing with Integrated Error Correction
Exponential growth in global computing demand is exacerbated due to the higher-energy requirements of conventional architectures, primarily due to energy-intensive data movement. In-memory computing with Resistive Random Access Memory (RRAM) addresses this by co-integrating memory and processing, but faces significant hurdles related to device-level non-idealities and poor scalability for large computing tasks. Here, we introduce \textbf{MELISO+} (In-\textbf{Me}mory \textbf{Li}near \textbf{So}l…

Fault-tolerant quantum computations of vibrational wave functions
Marco Majland, Rasmus Berg Jensen, Patrick Ettenhuber, Irfansha Shaik, Nikolaj Thomas Zinner, Ove Christiansen
https://arxiv.org/abs/2508.16253

Fault-tolerant quantum computations of vibrational wave functions
Quantum computation of vibrational properties of molecules is a promising platform to obtain computational advantages for computational chemistry. However, fault-tolerant quantum computations of vibrational properties remain a relatively unexplored field in quantum computing. In this work, we present different algorithms for efficient encodings of vibrational Hamiltonians using qubitization. Specifically, we investigate different encoding representations, high order tensor decomposition to obta…

Survey of HPC in US Research Institutions
Peng Shu, Junhao Chen, Zhengliang Liu, Huaqin Zhao, Xinliang Li, Tianming Liu
https://arxiv.org/abs/2506.19019 ht…

Survey of HPC in US Research Institutions
The rapid growth of AI, data-intensive science, and digital twin technologies has driven an unprecedented demand for high-performance computing (HPC) across the research ecosystem. While national laboratories and industrial hyperscalers have invested heavily in exascale and GPU-centric architectures, university-operated HPC systems remain comparatively under-resourced. This survey presents a comprehensive assessment of the HPC landscape across U.S. universities, benchmarking their capabilities …

Dynamics of discrete spacetimes with Quantum-enhanced Markov Chain Monte Carlo
Stuart Ferguson, Arad Nasiri, Petros Wallden
https://arxiv.org/abs/2506.19538

Dynamics of discrete spacetimes with Quantum-enhanced Markov Chain Monte Carlo
Quantum algorithms offer the potential for significant computational advantages; however, in many cases, it remains unclear how these advantages can be practically realized. Causal Set Theory is a discrete, Lorentz-invariant approach to quantum gravity which may be well positioned to benefit from quantum computing. In this work, we introduce a quantum algorithm that investigates the dynamics of causal sets by sampling the space of causal sets, improving on classical methods. Our approach builds…

The Quantum Ensemble Variational Optimization Algorithm: Applications to Molecular Inverse Design
Francesco Calcagno, Delmar G. A. Cabral, Ivan Rivalta, Victor S. Batista
https://arxiv.org/abs/2508.15896

The Quantum Ensemble Variational Optimization Algorithm: Applications to Molecular Inverse Design
Designing molecules with optimized properties remains a fundamental challenge due to the intricate relationship between molecular structure and properties. Traditional computational approaches that address the combinatorial number of possible molecular designs become unfeasible as the molecular size increases, suffering from the so-called `curse of dimensionality' problem. Recent advances in quantum computing hardware present new opportunities to address this problem. Here, we introduce the Qua…

The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute
Gilles Buchs, Thomas Beck, Ryan Bennink, Daniel Claudino, Andrea Delgado, Nur Aiman Fadel, Peter Groszkowski, Kathleen Hamilton, Travis Humble, Neeraj Kumar, Ang Li, Phillip Lotshaw, Olli Mukkula, Ryousei Takano, Amit Saxena, In-Saeng Suh, Miwako Tsuji, Roel Van Beeumen, Ugo Varetto, Yan Wang, Kazuya Yamazaki, Mikael P. Johansson

The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute
Quantum computing (QC) has gained significant attention over the past two decades due to its potential for speeding up classically demanding tasks. This transition from an academic focus to a thriving commercial sector is reflected in substantial global investments. While advancements in qubit counts and functionalities continues at a rapid pace, current quantum systems still lack the scalability for practical applications, facing challenges such as too high error rates and limited coherence ti…