Tootfinder

On Google's New Backup-and-Sync, and G-Drive: Reviews (2017) - An efficient and simple backup scheme that works for me, that does not carry a big price tag nor carbon footprint. - https://www.earth.org.uk/note-on-backup-energy-efficiency.html

On Googles New Backup-and-Sync, and G-Drive: Reviews (2017)
An efficient and simple backup scheme that works for me, that does not carry a big price tag nor carbon footprint.

psi: Plant Photosystem I excitation energy transfer network (2020)
Weighted directed network of the light-harvesting Photosystem Ι (PSI) of the plant Pisum sativum. The nodes represent chromophores with different identities (i.e. chlorophyll a, chlorophyll b, β-carotene and derivates, lutein, violaxanthin), while edges represent FRET transfer between chromophores. The link directionality connecting nodes in the PSI network depends on the energy levels of the connected chromophores. The…

Racing to Idle: Energy Efficiency of Matrix Multiplication on Heterogeneous CPU and GPU Architectures
Mufakir Qamar Ansari (Department of Electrical Engineering and Computer Science, The University of Toledo, Toledo, OH, USA), Mudabir Qamar Ansari (Department of School of Accounting and Information Systems, Lamar University, Beaumont, TX, USA)
https://

Racing to Idle: Energy Efficiency of Matrix Multiplication on Heterogeneous CPU and GPU Architectures
The paradigm shift towards multi-core and heterogeneous computing, driven by the fundamental power and thermal limits of single-core processors, has established energy efficiency as a first-class design constraint in high-performance computing (HPC). Heterogeneous systems, integrating traditional multi-core CPUs with specialized accelerators like discrete (dGPU) and integrated (iGPU) graphics processing units, offer a compelling path to navigating the trade-offs between performance and power. H…

On Office Comfort and Energy Efficiency - Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars -

On Office Comfort and Energy Efficiency
Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars

Embodied Intelligence for Sustainable Flight: A Soaring Robot with Active Morphological Control
Ghadeer Elmkaiel, Syn Schmitt, Michael Muehlebach
https://arxiv.org/abs/2508.19684

Embodied Intelligence for Sustainable Flight: A Soaring Robot with Active Morphological Control
Achieving both agile maneuverability and high energy efficiency in aerial robots, particularly in dynamic wind environments, remains challenging. Conventional thruster-powered systems offer agility but suffer from high energy consumption, while fixed-wing designs are efficient but lack hovering and maneuvering capabilities. We present Floaty, a shape-changing robot that overcomes these limitations by passively soaring, harnessing wind energy through intelligent morphological control inspired by…

A Framework for Energy Management Modelling in Hubs for Circularity
Tobias L{\o}vebakke Nielsen, Daniela Guericke, Alessio Trivella, Devrim Murat Yazan
https://arxiv.org/abs/2508.19765

A Framework for Energy Management Modelling in Hubs for Circularity
The concept Hubs for Circularity (H4C) represents integrated systems that combine efficient use of clean energy and circular economy to enhance resource efficiency within a region. H4C benefit from the geographical proximity of different industries within industrial zones and the surrounding urban and rural areas, allowing them to share resources, technology, and infrastructure. They reduce the use of virgin resources through Industrial Symbiosis (IS), where one company uses waste of another co…

Big Data Energy Systems: A Survey of Practices and Associated Challenges
Lunodzo J. Mwinuka, Massimo Cafaro, Lucas Pereira, Hugo Morais
https://arxiv.org/abs/2507.19154 https://…

Big Data Energy Systems: A Survey of Practices and Associated Challenges
Energy systems generate vast amounts of data in extremely short time intervals, creating challenges for efficient data management. Traditional data management methods often struggle with scalability and accessibility, limiting their usefulness. More advanced solutions, such as NoSQL databases and cloud-based platforms, have been adopted to address these issues. Still, even these advanced solutions can encounter bottlenecks, which can impact the efficiency of data storage, retrieval, and analysi…

Tu(r)ning AI Green: Exploring Energy Efficiency Cascading with Orthogonal Optimizations
Saurabhsingh Rajput, Mootez Saad, Tushar Sharma
https://arxiv.org/abs/2506.18289

Tu(r)ning AI Green: Exploring Energy Efficiency Cascading with Orthogonal Optimizations
AI's exponential growth intensifies computational demands and energy challenges. While practitioners employ various optimization techniques, that we refer as "knobs" in this paper, to tune model efficiency, these are typically afterthoughts and reactive ad-hoc changes applied in isolation without understanding their combinatorial effects on energy efficiency. This paper emphasizes on treating energy efficiency as the first-class citizen and as a fundamental design consideration for a compute-in…

Fundamental limitations of thermoradiative energy conversion
Maxime Giteau, Michela F. Picardi, Georgia T. Papadakis
https://arxiv.org/abs/2507.19864 https://

Fundamental limitations of thermoradiative energy conversion
Understanding the fundamental limits of various energy conversion approaches is essential for assessing their efficiency and power output. In this work, we derive general performance bounds for thermoradiative heat engines that exchange heat radiatively with a cold sink, establishing power-versus-efficiency thermodynamic bounds for several configurations. We find that the performance of these engines is always bounded by that of radiative engines, which harness the thermal radiation emitted by …

AxOSyn: An Open-source Framework for Synthesizing Novel Approximate Arithmetic Operators
Siva Satyendra Sahoo, Salim Ullah, Akash Kumar
https://arxiv.org/abs/2507.20007 https://…

AxOSyn: An Open-source Framework for Synthesizing Novel Approximate Arithmetic Operators
Edge AI deployments are becoming increasingly complex, necessitating energy-efficient solutions for resource-constrained embedded systems. Approximate computing, which allows for controlled inaccuracies in computations, is emerging as a promising approach for improving power and energy efficiency. Among the key techniques in approximate computing are approximate arithmetic opera- tors (AxOs), which enable application-specific optimizations beyond traditional computer arithmetic hardware reducti…

Ultrafast photocurrent detection reveals that device efficiency is dominated by ultrafast exciton dissociation not exciton diffusion
Zachary M. Faitz, Chris J. Blackwell, Dasol Im, Abitha Dhavamani, Michael Arnold, Martin T. Zanni
https://arxiv.org/abs/2506.21402

Ultrafast photocurrent detection reveals that device efficiency is dominated by ultrafast exciton dissociation not exciton diffusion
Excitons diffusing to a charge-separating interface is a necessary step to convert energy into current in next-generation photovoltaics. In this report, made possible by a new ultrafast spectrometer design, we compare exciton dynamics measured using both photoabsorption- and photocurrent-detected transient and 2D spectroscopies. For a device with semiconducting carbon nanotubes as the exciton transport material, we find that photoabsorption detection greatly overestimates the importance of long…

MNN-AECS: Energy Optimization for LLM Decoding on Mobile Devices via Adaptive Core Selection
Zhengxiang Huang, Chaoyue Niu, Zhaode Wang, Jiarui Xue, Hanming Zhang, Yugang Wang, Zewei Xin, Xiaotang Jiang, Chengfei Lv, Fan Wu, Guihai Chen
https://arxiv.org/abs/2506.19884

MNN-AECS: Energy Optimization for LLM Decoding on Mobile Devices via Adaptive Core Selection
As the demand for on-device Large Language Model (LLM) inference grows, energy efficiency has become a major concern, especially for battery-limited mobile devices. Our analysis shows that the memory-bound LLM decode phase dominates energy use, and yet most existing works focus on accelerating the prefill phase, neglecting energy concerns. We introduce Adaptive Energy-Centric Core Selection (AECS) and integrate it into MNN to create the energy-efficient version, MNN-AECS, the first engine-level…

High-Efficiency Tunable Microwave Photon Detector Based on a Semiconductor Double Quantum Dot Coupled to a Superconducting High-Impedance Cavity
Fabian Oppliger, Wonjin Jang, Aldo Tarascio, Franco De Palma, Christian Reichl, Werner Wegscheider, Ville F. Maisi, Dominik Zumb\"uhl, Pasquale Scarlino
https://arxiv.org/abs/2506.…

High-Efficiency Tunable Microwave Photon Detector Based on a Semiconductor Double Quantum Dot Coupled to a Superconducting High-Impedance Cavity
High-efficiency single-photon detection in the microwave domain is a key enabling technology for quantum sensing, communication, and information processing. However, the extremely low energy of microwave photons (~μeV) presents a fundamental challenge, preventing direct photon-to-charge conversion as achieved in optical systems using semiconductors. Semiconductor quantum dot (QD) charge qubits offer a compelling solution due to their highly tunable energy levels in the microwave regime, enabli…

Digitalization improves energy efficiency https://www.sciencedirect.com/science/article/pii/S014098832500516X @…

Enhancing Energy and Spectral Efficiency in IoT-Cellular Networks via Active SIM-Equipped LEO Satellites
Rahman Saadat Yeganeh, Hamid Behroozi, Mohammad Javad Omidi, Mohammad Robat Mili, Eduard A. Jorswieck, Symeon Chatzinotas
https://arxiv.org/abs/2508.17149

Enhancing Energy and Spectral Efficiency in IoT-Cellular Networks via Active SIM-Equipped LEO Satellites
This paper investigates a low Earth orbit (LEO) satellite communication system enhanced by an active stacked intelligent metasurface (ASIM), mounted on the backplate of the satellite solar panels to efficiently utilize limited onboard space and reduce the main satellite power amplifier requirements. The system serves multiple ground users via rate-splitting multiple access (RSMA) and IoT devices through a symbiotic radio network. Multi-layer sequential processing in the ASIM improves effective …

psi: Plant Photosystem I excitation energy transfer network (2020)
Weighted directed network of the light-harvesting Photosystem Ι (PSI) of the plant Pisum sativum. The nodes represent chromophores with different identities (i.e. chlorophyll a, chlorophyll b, β-carotene and derivates, lutein, violaxanthin), while edges represent FRET transfer between chromophores. The link directionality connecting nodes in the PSI network depends on the energy levels of the connected chromophores. The…

Tri-Hybrid Beamforming for Radiation-Center Reconfigurable Antenna Array: Spectral Efficiency and Energy Efficiency
Yinchen Li, Chenhao Qi, Shiwen Mao, Octavia A. Dobre
https://arxiv.org/abs/2508.15924

Tri-Hybrid Beamforming for Radiation-Center Reconfigurable Antenna Array: Spectral Efficiency and Energy Efficiency
In this paper, we propose a tri-hybrid beamforming (THBF) architecture based on the radiation-center (RC) reconfigurable antenna array (RCRAA), including the digital beamforming, analog beamforming, and electromagnetic (EM) beamforming, where the EM beamformer design is modeled as RC selection. Aiming at spectral efficiency (SE) maximization subject to the hardware and power consumption constraints, we propose a tri-loop alternating optimization (TLAO) scheme for the THBF design, where the digi…

Dependability Theory-based Statistical QoS Provisioning of Fluid Antenna Systems
Irfan Muhammad, Priyadarshi Mukherjee, Wee Kiat New, Hirley Alves, Ioannis Krikidis, Kai-Kit Wong
https://arxiv.org/abs/2507.19984

Dependability Theory-based Statistical QoS Provisioning of Fluid Antenna Systems
Fluid antenna systems (FAS) have recently emerged as a promising technology for next-generation wireless networks, offering real-time spatial reconfiguration to enhance reliability, throughput, and energy efficiency. Nevertheless, existing studies often overlook the temporal dynamics of channel fading and their implications for mission-critical operations. In this paper, we propose a dependability-theoretic framework for statistical quality-of-service (QoS) provisioning of FAS under finite bloc…

Does anyone have data on the efficiency of energy harvesting HVAC systems?
Scenario:
* Area A generates X kW of waste heat at a pretty constant rate year round which is currently dumped outside by a heat pump and lost
* Area B, close by, is air conditioned in the summer and heated in the winter by a second, isolated, heat pump. During the winter, it uses an average of Y kW to do this.
If I wanted to dump the waste heat from area A into area B to heat it, what kind of en…

Energy-Efficient Precoding for Dense VCSEL-Based OWC Systems Under a Cooperative Broadcast Model
Hossein Safi, Asim Ihsan, Hossien B. Eldeeb, Bastien Bechadergue, Iman Tavakkolnia, Harald Haas
https://arxiv.org/abs/2508.18871

Energy-Efficient Precoding for Dense VCSEL-Based OWC Systems Under a Cooperative Broadcast Model
As 6G and beyond aim for sustainable, high-capacity wireless connectivity, optical wireless communication (OWC) has emerged as a compelling solution.Recent advances in vertical-cavity surface-emitting laser (VCSEL) arrays have significantly enhanced OWC performance, enabling high-speed, low-power data transmission. However, dense VCSEL deployments introduce challenges related to interference and energy efficiency (EE). This paper proposes a scalable precoding framework for EE maximization in fu…

Energy minimisation using overlapping tensor-product free-knot B-splines
Alexandre Magueresse, Santiago Badia
https://arxiv.org/abs/2508.17705 https://arxi…

Energy minimisation using overlapping tensor-product free-knot B-splines
Accurately solving PDEs with localised features requires refined meshes that adapt to the solution. Traditional numerical methods, such as finite elements, are linear in nature and often ineffective for such problems, as the mesh is not tailored to the solution. Adaptive strategies, such as $h$- and $p$-refinement, improve efficiency by sequentially refining the mesh based on a posteriori error estimates. However, these methods are geometrically rigid -- limited to specific refinement rules -- …

Non-ideal subthreshold swing in aligned carbon nanotube transistors due to variable occupancy discrete charge traps
Saurabh S. Sawant, Teo Lara, Francois Leonard, Zhi Yao, Andrew Nonaka
https://arxiv.org/abs/2507.18646

Non-ideal subthreshold swing in aligned carbon nanotube transistors due to variable occupancy discrete charge traps
Carbon nanotube transistors have been experimentally demonstrated to reach performance comparable and even surpassing that of silicon transistors. Further improvement requires addressing non-idealities arising from device fabrication that impact performance and reproducibility. One performance metric that determines energy efficiency is the subthreshold swing which is often observed to be 3-4 times larger than the ideal thermal limit. In this work, we present simulations indicating that a discr…

Topological dark energy from spacetime foam: A challenge for $\Lambda$CDM
Fotios K. Anagnostopoulos, Stylianos A. Tsilioukas, Emmanuel N. Saridakis
https://arxiv.org/abs/2507.18389

Topological dark energy from spacetime foam: A challenge for $Λ$CDM
Using only the standard considerations of spacetime foam and the Euclidean Quantum Gravity techniques known long ago, we result to a model of Topological Dark Energy (TDE) that outperforms the standard $Λ$CDM paradigm with regard to data fitting efficiency. Specifically, it is known that at the foam level, topologically non-trivial solutions such as instantons appear. In the particular case of Einstein-Gauss-Bonnet gravity, we obtain an effective dynamical dark energy term proportional to the …

TLGLock: A New Approach in Logic Locking Using Key-Driven Charge Recycling in Threshold Logic Gates
Abdullah Sahruri, Martin Margala
https://arxiv.org/abs/2508.17809 https://

TLGLock: A New Approach in Logic Locking Using Key-Driven Charge Recycling in Threshold Logic Gates
Logic locking remains one of the most promising defenses against hardware piracy, yet current approaches often face challenges in scalability and design overhead. In this paper, we present TLGLock, a new design paradigm that leverages the structural expressiveness of Threshold Logic Gates (TLGs) and the energy efficiency of charge recycling to enforce key-dependent functionality at the gate level. By embedding the key into the gate's weighted logic and utilizing dynamic charge sharing, TLGLock …

Comparing energy consumption and accuracy in text classification inference
Johannes Zschache, Tilman Hartwig
https://arxiv.org/abs/2508.14170 https://arxiv…

Comparing energy consumption and accuracy in text classification inference
The increasing deployment of large language models (LLMs) in natural language processing (NLP) tasks raises concerns about energy efficiency and sustainability. While prior research has largely focused on energy consumption during model training, the inference phase has received comparatively less attention. This study systematically evaluates the trade-offs between model accuracy and energy consumption in text classification inference across various model architectures and hardware configurati…

Convergence and divergence in energy efficiency in developing countries https://www.sciencedirect.com/science/article/pii/S0140988325005225 @…

TaiBai: A fully programmable brain-inspired processor with topology-aware efficiency
Qianpeng Li, Yu Song, Xin Liu, Wenna Song, Boshi Zhao, Zhichao Wang, Aoxin Chen, Tielin Zhang, Liang Chen
https://arxiv.org/abs/2508.18961

TaiBai: A fully programmable brain-inspired processor with topology-aware efficiency
Brain-inspired computing has emerged as a promising paradigm to overcome the energy-efficiency limitations of conventional intelligent systems by emulating the brain's partitioned architecture and event-driven sparse computation. However, existing brain-inspired chips often suffer from rigid network topology constraints and limited neuronal programmability, hindering their adaptability. To address these challenges, we present TaiBai, an event-driven, programmable many-core brain-inspired proces…

Approximating CCCV charging using SOC-dependent tapered charging power constraints in long-term microgrid planning
Hassan Zahid Butt, Xingpeng Li
https://arxiv.org/abs/2507.18853

Approximating CCCV charging using SOC-dependent tapered charging power constraints in long-term microgrid planning
Traditional long-term microgrid planning models assume constant power charging for battery energy storage systems (BESS), overlooking efficiency losses that occur toward the end of charge due to rising internal resistance. While this issue can be mitigated at the cell level using constant current-constant voltage (CCCV) charging, it is impractical at the pack level in large-scale systems. However, battery management systems and inverter controls can emulate this effect by tapering charging powe…

Vision encoders should be image size agnostic and task driven
Nedyalko Prisadnikov, Danda Pani Paudel, Yuqian Fu, Luc Van Gool
https://arxiv.org/abs/2508.16317 https://

Vision encoders should be image size agnostic and task driven
This position paper argues that the next generation of vision encoders should be image size agnostic and task driven. The source of our inspiration is biological. Not a structural aspect of biological vision, but a behavioral trait -- efficiency. We focus on a couple of ways in which vision in nature is efficient, but modern vision encoders not. We -- humans and animals -- deal with vast quantities of visual data, and need to be smart where we focus our limited energy -- it depends on the task.…

How to Increase Energy Efficiency with a Single Linux Command
Alborz Jelvani, Richard P Martin, Santosh Nagarakatte
https://arxiv.org/abs/2506.16046 https:…

How to Increase Energy Efficiency with a Single Linux Command
Processors with dynamic power management provide a variety of settings to control energy efficiency. However, tuning these settings does not achieve optimal energy savings. We highlight how existing power capping mechanisms can address these limitations without requiring any changes to current power governors. We validate this approach using system measurements across a month-long data acquisition campaign from SPEC CPU 2017 benchmarks on a server-class system equipped with dual Intel Xeon Scal…

psi: Plant Photosystem I excitation energy transfer network (2020)
Weighted directed network of the light-harvesting Photosystem Ι (PSI) of the plant Pisum sativum. The nodes represent chromophores with different identities (i.e. chlorophyll a, chlorophyll b, β-carotene and derivates, lutein, violaxanthin), while edges represent FRET transfer between chromophores. The link directionality connecting nodes in the PSI network depends on the energy levels of the connected chromophores. The…

Cost-benefit analysis of an AI-driven operational digital platform for integrated electric mobility, renewable energy, and grid management
Arega Getaneh Abate, Xiaobing Zhang, Xiufeng Liu, Dogan Keles
https://arxiv.org/abs/2506.20631

Cost-benefit analysis of an AI-driven operational digital platform for integrated electric mobility, renewable energy, and grid management
Integrating electric mobility (electric vehicles (EVs), electric trucks (ETs)) and renewable energy sources (RES) with the power grid is paramount for achieving decarbonization, efficiency, and stability. Given the rapid growth of decentralized technologies and their critical role in decarbonization, two critical challenges emerge: first, the development of a digital platform for operational coordination; and second, rigorous research into their cost-benefit profile. This paper addresses this b…

Interesting French government analysis on alternatives to diesel trucks. Battery-electric superior to alternatives on many points (energy efficiency, CO2 reduction, local value creation in production 100% French energy). Upfront TCO costs still higher.
https://www.

On Office Comfort and Energy Efficiency - Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars -

On Office Comfort and Energy Efficiency
Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars

Near-Field Energy Harvesting Using XL-MIMO Over Non-Stationary Channels
Muhammad Zeeshan Mumtaz, Mohammadali Mohammadi, Hien Quoc Ngo, Michail Matthaiou
https://arxiv.org/abs/2506.20067

Near-Field Energy Harvesting Using XL-MIMO Over Non-Stationary Channels
This paper explores the maximization of the harvested power efficiency (HPE) in a modular extremely large multiple-input multiple-output (XL-MIMO) system, which supports energy harvesting (EH) for near-field users. These users are located in spatially distinct visibility regions (VRs) with non-stationary channel characteristics. We propose to determine which sub-arrays are switched on or off as well the power control coefficients at the sub-arrays to maximize the HPE. The design can be processe…

Robust Energy-Efficient DRL-Based Optimization in UAV-Mounted RIS Systems with Jitter
Mahmoud M. Salim, Khaled M. Rabie, Ali H. Muqaibel
https://arxiv.org/abs/2506.17971

Robust Energy-Efficient DRL-Based Optimization in UAV-Mounted RIS Systems with Jitter
In this letter, we propose an energy-efficient design for an unmanned aerial vehicle (UAV)-mounted reconfigurable intelligent surface (RIS) communication system with nonlinear energy harvesting (EH) and UAV jitter. A joint optimization problem is formulated to maximize the EH efficiency of the UAV-mounted RIS by controlling the user powers, RIS phase shifts, and time-switching factor, subject to quality of service and practical EH constraints. The problem is nonconvex and time-coupled due to UA…

On the rank-reduced relativistic coupled cluster method
Alexander V. Oleynichenko, Artem S. Rumiantsev, Andrei Zaitsevskii, Ephraim Eliav
https://arxiv.org/abs/2506.21133

On the rank-reduced relativistic coupled cluster method
An efficiency of the Tucker decomposition of amplitude tensors within the single-reference relativistic coupled cluster method with single and double excitations (RCCSD) was studied in a series of benchmark calculations for (AuCl)$_n$ chains, Au$_n$ clusters, and the cluster model of solid YbCl$_2$. The 1 kJ/mol level of accuracy for correlation energy estimates of moderate-size systems and typical reaction energies can be achieved with relatively high compression rates of amplitude tensors via…

How Viable are Energy Savings in Smart Homes? A Call to Embrace Rebound Effects in Sustainable HCI
Christina Bremer, Harshit Gujral, Michelle Lin, Lily Hinkers, Christoph Becker, Vlad C. Coroam\u{a}
https://arxiv.org/abs/2506.14653

How Viable are Energy Savings in Smart Homes? A Call to Embrace Rebound Effects in Sustainable HCI
As part of global climate action, digital technologies are seen as a key enabler of energy efficiency savings. A popular application domain for this work is smart homes. There is a risk, however, that these efficiency gains result in rebound effects, which reduce or even overcompensate the savings. Rebound effects are well-established in economics, but it is less clear whether they also inform smart energy research in other disciplines. In this paper, we ask: to what extent have rebound effects…

Controlling energy delivery with bistable nanostructures
Andreas Ehrmann, Carl P. Goodrich
https://arxiv.org/abs/2506.14266 https://a…

Controlling energy delivery with bistable nanostructures
Countless biological processes are fueled by energy-rich molecules like ATP and GTP that supply energy with extreme efficiency. However, designing similar energy-delivery schemes from the bottom up, essential for the development of powered nanostructures and other {\it de novo} machinery, presents a significant challenge: how can an energy-rich structure be stable in solution yet still deliver this energy at precisely the right time? In this paper, we present a purely physical mechanism that so…

LoRaIN: A Constructive Interference-Assisted Reliable and Energy-Efficient LoRa Indoor Network
Mahbubur Rahman, Abusayeed Saifullah
https://arxiv.org/abs/2506.16409

LoRaIN: A Constructive Interference-Assisted Reliable and Energy-Efficient LoRa Indoor Network
LoRa is a promising communication technology for enabling the next-generation indoor Internet of Things applications. Very few studies, however, have analyzed its performance indoors. Besides, these indoor studies investigate mostly the RSSI and SNR of the received packets at the gateway, which, as we show, may not unfold the poor performance of LoRa and its MAC protocol, LoRaWAN, indoors in terms of reliability and energy-efficiency. In this paper, we extensively evaluate the performance of Lo…

On the Role of Color Temperature and Color Rendering Index of White-Light LEDs on the Theoretical Efficiency Limit of Indoor Photovoltaics
Aditi Sharma, Alexander A. Guaman, Jason A. R\"ohr
https://arxiv.org/abs/2506.20811

On the Role of Color Temperature and Color Rendering Index of White-Light LEDs on the Theoretical Efficiency Limit of Indoor Photovoltaics
As the Internet of Things (IoT) continues to grow, the demand for sustainable indoor power sources is increasing. Indoor photovoltaics (IPVs), which are currently in development, present a renewable solution but need to be designed to match specific light sources. While previous studies have emphasized the role of white-light LED color temperature (CT) in determining IPV efficiency and optimum bandgap energy, the role of color rendering index (CRI) remains less understood. In this study, we emp…

Toward Sustainable Vertical Farming: Impacts of Environmental Factors and Energy Mix on Performance and Costs
Francesco Ceccanti, Aldo Bischi, Umberto Desideri, Andrea Baccioli
https://arxiv.org/abs/2507.18419

Toward Sustainable Vertical Farming: Impacts of Environmental Factors and Energy Mix on Performance and Costs
The increasing interest in vertical farming arises from its ability to ensure consistent, high-quality, and pest-free vegetable production while supporting synergies with energy systems and urban development. Accordingly, standardized design and operation guidelines are essential to improve energy efficiency and lower costs. This study analyzes the production performance and energy consumption of a vertical farming system, assessing its efficiency, sustainability, and economic viability. A tota…

Bridding OT and PaaS in Edge-to-Cloud Continuum
Carlos J Barrios (LIG, UIS, CITI), Yves Denneulin (LIG, Grenoble INP)
https://arxiv.org/abs/2506.21072 http…

Bridding OT and PaaS in Edge-to-Cloud Continuum
The Operational Technology Platform as a Service (OTPaaS) initiative provides a structured framework for the efficient management and storage of data. It ensures excellent response times while improving security, reliability, data and technology sovereignty, robustness, and energy efficiency, which are crucial for industrial transformation and data sovereignty. This paper illustrates successful deployment, adaptable application management, and various integration components catering to Edge and…

MEDEA: A Design-Time Multi-Objective Manager for Energy-Efficient DNN Inference on Heterogeneous Ultra-Low Power Platforms
Hossein Taji, Jos\'e Miranda, Miguel Pe\'on-Quir\'os, David Atienza
https://arxiv.org/abs/2506.19067

MEDEA: A Design-Time Multi-Objective Manager for Energy-Efficient DNN Inference on Heterogeneous Ultra-Low Power Platforms
The growing demand for on-device AI necessitates energy-efficient execution of DNN based applications on resource-constrained ultra-low power (ULP) platforms. Heterogeneous architectures, combining specialized processing elements (PEs), have emerged as a key solution for achieving the required performance and energy efficiency. However, optimizing energy while executing applications on these platforms requires efficiently managing platform resources like PEs, power features, and memory footprin…

Jet Reconstruction with Mamba Networks in Collider Events
Jinmian Li, Peng Li, Bingwei Long, Rao Zhang
https://arxiv.org/abs/2506.18336 https://

Jet Reconstruction with Mamba Networks in Collider Events
We introduce a novel end-to-end framework for jet reconstruction in high-energy collider events, leveraging the efficiency and long-range modeling capabilities of the Mamba architecture. Our model unifies instance segmentation, classification, and kinematic regression into a single multi-task learning system, enabling a sophisticated multi-level reconstruction that simultaneously identifies primary heavy jets ($t$, $H$, $W/Z$) and their constituent sub-jets. To facilitate supervised learning fo…

psi: Plant Photosystem I excitation energy transfer network (2020)
Weighted directed network of the light-harvesting Photosystem Ι (PSI) of the plant Pisum sativum. The nodes represent chromophores with different identities (i.e. chlorophyll a, chlorophyll b, β-carotene and derivates, lutein, violaxanthin), while edges represent FRET transfer between chromophores. The link directionality connecting nodes in the PSI network depends on the energy levels of the connected chromophores. The…

A water Cherenkov detector prototype for future high-energy tau-neutrino experiment
Monong Yu, Yiren Chen, Lei Wang, Shiping Zhao, Xingyu Li, Qiang Yuan, Yi Zhang, Guang Yang
https://arxiv.org/abs/2508.14743

A water Cherenkov detector prototype for future high-energy tau-neutrino experiment
The detection of high-energy tau neutrinos remains a critical challenge in neutrino astronomy, limited by inadequate angular resolution and sensitivity in current detectors like IceCube and KM3NeT. We present a modular water Cherenkov detector prototype optimized for tau-neutrino-induced extensive air showers (EAS) in the 1-100 PeV range, leveraging canyon terrain for natural cosmic-ray shielding. Laboratory validation demonstrates this prototype design has high detection efficiency (>99%) and …

SYCL for Energy-Efficient Numerical Astrophysics: the case of DPEcho
Salvatore Cielo, Alexander P\"oppl, Ivan Pribec
https://arxiv.org/abs/2508.14117 https://

SYCL for Energy-Efficient Numerical Astrophysics: the case of DPEcho
Energy awareness and efficiency policies are gaining more attention, over pure performance (time-to-solution) Key Performance Indicators (KPIs) when comparing the possibilities offered by accelerated systems. But in a field such as numerical astrophysics, which is struggling with code refactorings for GPUs, viable porting paths have to be shown before first. After summarizing the status and recurring problems of astrophysical code accelerations, we highlight how the field would benefit from por…

Energy Efficiency in Robotics Software: A Systematic Literature Review (2020-2024)
Aryan Gupta
https://arxiv.org/abs/2508.12170 https://arxiv.org/pdf/2508.…

Energy Efficiency in Robotics Software: A Systematic Literature Review (2020-2024)
This study presents a systematic literature review of software-level approaches to energy efficiency in robotics published from 2020 through 2024, updating and extending pre-2020 evidence. An automated-but-audited pipeline combined Google Scholar seeding, backward/forward snowballing, and large-language-model (LLM) assistance for screening and data extraction, with ~10% human audits at each automated step and consensus-with-tie-breaks for full-text decisions. The final corpus comprises 79 peer-…

Emerging Paradigms in the Energy Sector: Forecasting and System Control Optimisation
Dariush Pourkeramati, Gareth Wadge, Rachel Hassall, Charlotte Mitchell, Anish Khadka, Shiwang Jaiswal, Andrew Duncan, Rossella Arcucci
https://arxiv.org/abs/2507.12373

Emerging Paradigms in the Energy Sector: Forecasting and System Control Optimisation
The energy sector is experiencing rapid transformation due to increasing renewable energy integration, decentralisation of power systems, and a heightened focus on efficiency and sustainability. With energy demand becoming increasingly dynamic and generation sources more variable, advanced forecasting and optimisation strategies are crucial for maintaining grid stability, cost-effectiveness, and environmental sustainability. This paper explores emerging paradigms in energy forecasting and manag…

On Office Comfort and Energy Efficiency - Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars -

On Office Comfort and Energy Efficiency
Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars

Adaptively Robust LLM Inference Optimization under Prediction Uncertainty
Zixi Chen, Yinyu Ye, Zijie Zhou
https://arxiv.org/abs/2508.14544 https://arxiv.or…

Adaptively Robust LLM Inference Optimization under Prediction Uncertainty
We study the problem of optimizing Large Language Model (LLM) inference scheduling to minimize total latency. LLM inference is an online and multi-task service process and also heavily energy consuming by which a pre-trained LLM processes input requests and generates output tokens sequentially. Therefore, it is vital to improve its scheduling efficiency and reduce the power consumption while a great amount of prompt requests are arriving. A key challenge in LLM inference scheduling is that whil…

Efficiency of turbulence
A Lopez (SPEC - UMR3680), A Barral (SPEC - UMR3680), G Costa (SPEC - UMR3680), Q Pikeroen (SPEC - UMR3680), V Shukla (SPEC - UMR3680), B\'ereng\`ere Dubrulle (SPEC - UMR3680)
https://arxiv.org/abs/2508.05686

Efficiency of turbulence
We consider the efficiency of turbulence, a dimensionless parameter that characterises the fraction of the input energy stored into a turbulent flow field. We first show that the inverse of the efficiency provides an upper bound for the dimensionless energy injection in a turbulent flow. We analyse the efficiency of turbulence for different flows using numerical and experimental data. Our analysis suggests that efficiency is bounded from above, and, in some cases, saturates following a power la…

Design and optimization of a novel leaf-shape antenna for RF energy transfer
Junbin Zhong, Mingtong Chen, Zhengbao Yang
https://arxiv.org/abs/2507.18630 https://

Design and optimization of a novel leaf-shape antenna for RF energy transfer
In this research, the design and optimization of a novel leaf-shaped antenna inspired by natural leaf structures for radio frequency energy transfer is presented. The objectives of this study are to develop a bio-inspired antenna, optimize its performance through impedance matching for the 915 MHz frequency band, and evaluate its efficiency in capturing RF energy. The design process involves selecting an appropriate leaf shape, modeling the antenna using AutoCAD and HFSS software, and fabricati…

Crosslisted article(s) found for hep-th. https://arxiv.org/list/hep-th/new
[1/1]:
- Relativistic Quantum Thermal Machine: Harnessing Relativistic Effects to Surpass Carnot Efficiency
Tanmoy Pandit, Pritam Chattopadhyay, Kaustav Chatterjee, Varinder Singh

On Energy-Efficient Passive Beamforming Design of RIS-Assisted CoMP-NOMA Networks
Muhammad Umer, Muhammad Ahmed Mohsin, Aamir Mahmood, Haejoon Jung, Haris Pervaiz, Mikael Gidlund, Syed Ali Hassan
https://arxiv.org/abs/2506.17189

On Energy-Efficient Passive Beamforming Design of RIS-Assisted CoMP-NOMA Networks
This paper investigates the synergistic potential of reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) to enhance the energy efficiency and performance of next-generation wireless networks. We delve into the design of energy-efficient passive beamforming (PBF) strategies within RIS-assisted coordinated multi-point (CoMP)-NOMA networks. Two distinct RIS configurations, namely, enhancement-only PBF (EO) and enhancement & cancellation PBF (EC), are proposed and an…

Replaced article(s) found for cs.PF. https://arxiv.org/list/cs.PF/new
[1/1]:
- Power-Capping Metric Evaluation for Improving Energy Efficiency in HPC Applications
Patrou, Wang, Elwasif, Eisenbach, Miller, Godoy, Hernandez

Multistage Robust Optimization for Time-Decoupled Power Flexibility Aggregation with Energy Storage
Rui Xie, Yue Chen
https://arxiv.org/abs/2508.14477 https://

Multistage Robust Optimization for Time-Decoupled Power Flexibility Aggregation with Energy Storage
To mitigate global climate change, distributed energy resources (DERs), such as distributed generators, flexible loads, and energy storage systems (ESSs), have witnessed rapid growth in power distribution systems. When properly managed, these DERs can provide significant flexibility to power systems, enhancing both reliability and economic efficiency. Due to their relatively small scale, DERs are typically managed by the distribution system operator (DSO), who interacts with the transmission sy…

On the efficiency of a posteriori error estimators for parabolic partial differential equations in the energy norm
Iain Smears
https://arxiv.org/abs/2507.13188

On the efficiency of a posteriori error estimators for parabolic partial differential equations in the energy norm
For the model problem of the heat equation discretized by an implicit Euler method in time and a conforming finite element method in space, we prove the efficiency of a posteriori error estimators with respect to the energy norm of the error, when considering the numerical solution as the average between the usual continuous piecewise affine-in-time and piecewise constant-in-time reconstructions. This illustrates how the efficiency of the estimators is not only possibly dependent on the choice …

Scalable Fairness Shaping with LLM-Guided Multi-Agent Reinforcement Learning for Peer-to-Peer Electricity Markets
Shrenik Jadhav, Birva Sevak, Srijita Das, Akhtar Hussain, Wencong Su, Van-Hai Bui
https://arxiv.org/abs/2508.18610

Scalable Fairness Shaping with LLM-Guided Multi-Agent Reinforcement Learning for Peer-to-Peer Electricity Markets
Peer-to-peer (P2P) energy trading is becoming central to modern distribution systems as rooftop PV and home energy management systems become pervasive, yet most existing market and reinforcement learning designs emphasize efficiency or private profit and offer little real-time guidance to ensure equitable outcomes under uncertainty. To address this gap, a fairness-aware multiagent reinforcement learning framework, FairMarket-RL, is proposed in which a large language model (LLM) critic shapes bi…

On Office Comfort and Energy Efficiency - Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars -

On Office Comfort and Energy Efficiency
Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars

Game-Theoretic and Reinforcement Learning-Based Cluster Head Selection for Energy-Efficient Wireless Sensor Network
Mehrshad Eskandarpour, Saba Pirahmadian, Parham Soltani, Hossein Soleimani
https://arxiv.org/abs/2508.12707

Game-Theoretic and Reinforcement Learning-Based Cluster Head Selection for Energy-Efficient Wireless Sensor Network
Energy in Wireless Sensor Networks (WSNs) is critical to network lifetime and data delivery. However, the primary impediment to the durability and dependability of these sensor nodes is their short battery life. Currently, power-saving algorithms such as clustering and routing algorithms have improved energy efficiency in standard protocols. This paper proposes a clustering-based routing approach for creating an adaptive, energy-efficient mechanism. Our system employs a multi-step clustering st…

Extracting energy from plunging region of a Kerr-Taub-NUT black hole by magnetic reconnection
Zhengwei Cheng, Songbai Chen, Jiliang Jing
https://arxiv.org/abs/2507.11859

Extracting energy from plunging region of a Kerr-Taub-NUT black hole by magnetic reconnection
We have studied the energy extraction from a Kerr-Taub-NUT black hole via magnetic reconnections occurring in the plunging region. Our results show that the gravitomagnetic charge suppresses the energy extraction process through magnetic reconnection and reduces the corresponding extraction efficiency, which is opposite to those of the black hole spin and the magnetization parameter. Finally, we treat the energy extraction process through magnetic reconnection as a mechanism to revisit the prob…

Building an Open CGRA Ecosystem for Agile Innovation
Rohan Juneja, Pranav Dangi, Thilini Kaushalya Bandara, Zhaoying Li, Dhananjaya Wijerathne, Li-Shiuan Peh, Tulika Mitra
https://arxiv.org/abs/2508.19090

Building an Open CGRA Ecosystem for Agile Innovation
Modern computing workloads, particularly in AI and edge applications, demand hardware-software co-design to meet aggressive performance and energy targets. Such co-design benefits from open and agile platforms that replace closed, vertically integrated development with modular, community-driven ecosystems. Coarse-Grained Reconfigurable Architectures (CGRAs), with their unique balance of flexibility and efficiency are particularly well-suited for this paradigm. When built on open-source hardware…

Efficient many-jet event generation with Flow Matching
Enrico Bothmann, Timo Jan{\ss}en, Max Knobbe, Bernhard Schmitzer, Fabian Sinz
https://arxiv.org/abs/2506.18987

Efficient many-jet event generation with Flow Matching
We apply for the first time the Flow Matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the random numbers used to generate the momenta and helicities of the scattering matrix elements as implemented in the portable partonic event generator Pepper, we find substantial efficiency improvements in the studied processes. We focus our study on the highest final-state multiplicities in Drell--Yan and top--antitop…

Backscattering-Based Security in Wireless Power Transfer Applied to Battery-Free BLE Sensors
Taki Eddine Djidjekh (INSA Toulouse, LAAS-MINC), Ga\"el Loubet (LAAS-MINC, INSA Toulouse), Alexandru Takacs (LAAS-MINC, UT)
https://arxiv.org/abs/2507.13042

Backscattering-Based Security in Wireless Power Transfer Applied to Battery-Free BLE Sensors
The integration of security and energy efficiency in Internet of Things systems remains a critical challenge, particularly for battery-free and resource-constrained devices. This paper explores the scalability and protocol-agnostic nature of a backscattering-based security mechanism by integrating it into Bluetooth Low Energy battery-free Wireless Sensor Network. The proposed approach leverages the Wireless Power Transfer link, traditionally used for energy harvesting, to generate additional id…

Energy Efficiency Maximization for Movable Antenna Communication Systems
Jingze Ding, Zijian Zhou, Lipeng Zhu, Yuping Zhao, Bingli Jiao, Rui Zhang
https://arxiv.org/abs/2506.07129

Energy Efficiency Maximization for Movable Antenna Communication Systems
This paper investigates energy efficiency maximization for movable antenna (MA)-aided multi-user uplink communication systems by considering the time delay and energy consumption incurred by practical antenna movement. We first examine the special case with a single user and propose an optimization algorithm based on the one-dimensional (1D) exhaustive search to maximize the user's energy efficiency. Moreover, we derive an upper bound on the energy efficiency and analyze the conditions required…

Sb2S3 and GaAs Absorber Layer-based Quantum Dot Solar Cells with Cadmium Telluride-based HTL: A Comparative Study
Sayak Banerjee (Department of Physics, Indian Institute of Technology, Jodhpur, Rajasthan, India-342037, Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Jodhpur, Rajasthan, India), Anupam Chetia (Department of Physics, Indian Institute of Technology, Jodhpur, Rajasthan, India-342037), Satyajit Sahu (Department of Physics, Indian Instit…

Sb2S3 and GaAs Absorber Layer-based Quantum Dot Solar Cells with Cadmium Telluride-based HTL: A Comparative Study
Quantum dot solar cells (QDSC) are widely acknowledged to be one of the best solar energy harvesting devices in the present world. Absorber layer is a core component of a QDSC with a strong influence on its operational efficiency. Hence, we choose to undertake a comparative study of two QDSC having different QD absorber layers: Sb2S3 and GaAs with the motive to identify the better absorber layer material. The numerical analysis has been carried out using SCAPS-1D (Solar Cell Capacitance Simulat…

Joint Active and Passive Beamforming for Energy-Efficient STARS with Quantization and Element Selection in ISAC Systems
Li-Hsiang Shen, Yi-Hsuan Chiu
https://arxiv.org/abs/2507.16210

Joint Active and Passive Beamforming for Energy-Efficient STARS with Quantization and Element Selection in ISAC Systems
This paper investigates a simultaneously transmitting and reflecting reconfigurable intelligent surface (STARS)-aided integrated sensing and communication (ISAC) systems in support of full-space energy-efficient data transmissions and target sensing. We formulate an energy efficiency (EE) maximization problem jointly optimizing dual-functional radar-communication (DFRC)-empowered base station (BS) ISAC beamforming and STARS configurations of amplitudes, phase-shifts, quantization levels as well…

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
Humza Ashraf, Syed Muhammad Danish, Aris Leivadeas, Yazan Otoum, Zeeshan Sattar
https://arxiv.org/abs/2508.08332

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
Large Language Models (LLMs) are widely used for code generation. However, commercial models like ChatGPT require significant computing power, which leads to high energy use and carbon emissions. This has raised concerns about their environmental impact. In this study, we evaluate open-source Small Language Models (SLMs) trained explicitly for code generation and compare their performance and energy efficiency against large LLMs and efficient human-written Python code. The goal is to investigat…

Refining Motion for Peak Performance: Identifying Optimal Gait Parameters for Energy-Efficient Quadrupedal Bounding
Yasser G. Alqaham, Jing Cheng, Zhenyu Gan
https://arxiv.org/abs/2507.12751

Refining Motion for Peak Performance: Identifying Optimal Gait Parameters for Energy-Efficient Quadrupedal Bounding
Energy efficiency is a critical factor in the performance and autonomy of quadrupedal robots. While previous research has focused on mechanical design and actuation improvements, the impact of gait parameters on energetics has been less explored. In this paper, we hypothesize that gait parameters, specifically duty factor, phase shift, and stride duration, are key determinants of energy consumption in quadrupedal locomotion. To test this hypothesis, we modeled the Unitree A1 quadrupedal robot a…

A new data-driven energy-stable Evolve-Filter-Relax model for turbulent flow simulation
Anna Ivagnes, Toby van Gastelen, Syver D{\o}ving Agdestein, Benjamin Sanderse, Giovanni Stabile, Gianluigi Rozza
https://arxiv.org/abs/2507.17423

A new data-driven energy-stable Evolve-Filter-Relax model for turbulent flow simulation
We present a novel approach to define the filter and relax steps in the evolve-filter-relax (EFR) framework for simulating turbulent flows. The EFR main advantages are its ease of implementation and computational efficiency. However, as it only contains two parameters (one for the filter step and one for the relax step) its flexibility is rather limited. In this work, we propose a data-driven approach in which the optimal filter is found based on DNS data in the frequency domain. The optimizati…

Programmable electro-optic frequency comb empowers integrated parallel convolution processing
Jinze He, Junzhe Qiang, Yiying Dong, Jingyi Wang, Tian Dong, Gongcheng Yue, Rongjin Zhuang, Mingze Lv, Siyuan Yu, Zhongjin Lin, Xinlun Cai, Yuanmu Yang, Guanhao Wu, Yang Li
https://arxiv.org/abs/2506.18310…

Programmable electro-optic frequency comb empowers integrated parallel convolution processing
Integrated photonic convolution processors make optical neural networks (ONNs) a transformative solution for artificial intelligence applications such as machine vision. To enhance the parallelism, throughput, and energy efficiency of ONNs, wavelength multiplexing is widely applied. However, it often encounters the challenges of low compactness, limited scalability, and high weight reconstruction latency. Here, we proposed and demonstrated an integrated photonic processing unit with a parallel …

FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture
Somayeh Sobati-M
https://arxiv.org/abs/2507.16668 https://arxiv.org/pdf/2…

FOGNITE: Federated Learning-Enhanced Fog-Cloud Architecture
Modern smart grids demand fast, intelligent, and energy-aware computing at the edge to manage real time fluctuations and ensure reliable operation. This paper introduces FOGNITE Fog-based Grid In intelligence with Neural Integration and Twin based Execution a next-generation fog cloud framework designed to enhance autonomy, resilience, and efficiency in distributed energy systems. FOGNITE combines three core components: federated learning, reinforcement learning, and digital twin validation. Ea…

On Office Comfort and Energy Efficiency - Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars -

On Office Comfort and Energy Efficiency
Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars

Multi-dimensional evaluation on a rural integrated energy system including solar, wind, biomass and geothermal energy
Ruonan Lia, Chang Wena, Mingyu Yan, Congcong Wu, Ahmed Lotfy Elrefai, Xiaotong Zhang, Sahban Wael Saeed Alnaser
https://arxiv.org/abs/2506.15398

Multi-dimensional evaluation on a rural integrated energy system including solar, wind, biomass and geothermal energy
This study focuses on the novel municipal-scale rural integrated energy system (RIES), which encompasses energy supply and application. By constructing a seven-dimensional evaluation system including energy efficiency, energy supply, low-carbon sustainability, environmental impact, energy economy, social benefits, and integrated energy system development, this research combines the improved analytic hierarchy process (IAHP) and entropy weight method (EWM) by sum of squares of deviations to bala…

On the Trade-Off Between Sum-Rate and Energy Efficiency through the Convergence of HAPS and Active RIS Technologies
Bilal Karaman, Ilhan Basturk, Ferdi Kara, Metin Ozturk, Sezai Taskin, Halil Yanikomeroglu
https://arxiv.org/abs/2507.13889

On the Trade-Off Between Sum-Rate and Energy Efficiency through the Convergence of HAPS and Active RIS Technologies
This paper investigates the integration of active reconfigurable intelligent surfaces (RIS) relay with high-altitude platform stations (HAPS) to enhance non-terrestrial network (NTN) performance in next-generation wireless systems. While prior studies focused on passive RIS architectures, the severe path loss and double fading in long-distance HAPS links make active RIS a more suitable alternative due to its inherent signal amplification capabilities. We formulate a sum-rate maximization proble…

H2EAL: Hybrid-Bonding Architecture with Hybrid Sparse Attention for Efficient Long-Context LLM Inference
Zizhuo Fu, Xiaotian Guo, Wenxuan Zeng, Shuzhang Zhong, Yadong Zhang, Peiyu Chen, Runsheng Wang, Le Ye, Meng Li
https://arxiv.org/abs/2508.16653

H2EAL: Hybrid-Bonding Architecture with Hybrid Sparse Attention for Efficient Long-Context LLM Inference
Large language models (LLMs) have demonstrated remarkable proficiency in a wide range of natural language processing applications. However, the high energy and latency overhead induced by the KV cache limits the edge deployment, especially for long contexts. Emerging hybrid bonding (HB) technology has been proposed as a promising alternative to conventional near-memory processing (NMP) architectures, offering improved bandwidth efficiency and lower power consumption while exhibiting characteris…

A Collusion-Resistance Privacy-Preserving Smart Metering Protocol for Operational Utility
Farid Zaredar, Morteza Amini
https://arxiv.org/abs/2508.14744 https://

A Collusion-Resistance Privacy-Preserving Smart Metering Protocol for Operational Utility
Modern grids have adopted advanced metering infrastructure (AMI) to facilitate bidirectional communication between smart meters and control centers. This enables smart meters to report consumption values at predefined intervals to utility providers for purposes including demand balancing, load forecasting, dynamic billing, and operational efficiency. Compared to traditional power grids, smart grids offer advantages such as enhanced reliability, improved energy efficiency, and increased security…

Energy Efficiency Optimization for Movable Antenna-Aided Communication Systems
Jingze Ding, Zijian Zhou, Yuping Zhao, Bingli Jiao
https://arxiv.org/abs/2508.05033 https://

Energy Efficiency Optimization for Movable Antenna-Aided Communication Systems
This paper investigates the energy efficiency optimization for movable antenna (MA) systems by considering the time delay and energy consumption introduced by MA movement. We first derive the upper bound on energy efficiency for a single-user downlink communication system, where the user is equipped with a single MA. Then, the energy efficiency maximization problem is formulated to optimize the MA position, and an efficient algorithm based on successive convex approximation is proposed to solve…

psi: Plant Photosystem I excitation energy transfer network (2020)
Weighted directed network of the light-harvesting Photosystem Ι (PSI) of the plant Pisum sativum. The nodes represent chromophores with different identities (i.e. chlorophyll a, chlorophyll b, β-carotene and derivates, lutein, violaxanthin), while edges represent FRET transfer between chromophores. The link directionality connecting nodes in the PSI network depends on the energy levels of the connected chromophores. The…

Hybrid Single-Pulse and Sawyer-Tower Method for Accurate Transistor Loss Separation in High-Frequency High-Efficiency Power Converters
Xiaoyang Tian, Mowei Lu, Florin Udrea, Stephan Goetz
https://arxiv.org/abs/2506.18635

Hybrid Single-Pulse and Sawyer-Tower Method for Accurate Transistor Loss Separation in High-Frequency High-Efficiency Power Converters
Accurate measurement of transistor parasitic capacitance and its associated energy losses is critical for evaluating device performance, particularly in high-frequency and high-efficiency power conversion systems. This paper proposes a hybrid single-pulse and Sawyer-Tower test method to analyse switching characteristics of field-effect transistors (FET), which not only eliminates overlap losses but also mitigates the effects of current backflow observed in traditional double-pulse testing. Thro…

On Office Comfort and Energy Efficiency - Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars -

On Office Comfort and Energy Efficiency
Sweating or shivering 9 to 5 at work? Small business or home office? Get comfy, save money, cut carbon! #office #frugal #thermostatWars

Secrecy Energy Efficiency Maximization in RIS-Aided Networks: Active or Nearly-Passive RIS?
Robert Kuku Fotock, Agbotiname Lucky Imoize, Alessio Zappone, Marco Di Renzo, Roberto Garello
https://arxiv.org/abs/2507.07241

Secrecy Energy Efficiency Maximization in RIS-Aided Networks: Active or Nearly-Passive RIS?
This work addresses the problem of secrecy energy efficiency (SEE) maximization in RIS-aided wireless networks. The use of active and nearly-passive RISs are compared and their trade-off in terms of SEE is analyzed. Considering both perfect and statistical channel state information, two SEE maximization algorithms are developed to optimize the transmit powers of the mobile users, the RIS reflection coefficients, and the base station receive filters. Numerical results quantify the trade-off betw…

Towards High-Efficiency Solar Cells: Insights into AsNCa 3 Antiperovskite as Active Layer
M. Irfan, B. D. Aparicio-Huacarpuma, C. M. de Oliveira Bastos, M. J. Piotrowski, C. R. C. R\^ego, D. Guedes-Sobrinho, R. Besse, A. M. Almeida Silva, Alexandre C. Dias, L. A. Ribeiro Jr
https://arxiv.org/abs/2506.15403

Towards High-Efficiency Solar Cells: Insights into AsNCa 3 Antiperovskite as Active Layer
Advances in photovoltaic technology are a viable route to contribute to cleaner and more sustainable energy solutions, placing perovskite-based materials among the best candidates for solar energy conversion. However, some challenges must be addressed to enhance their performance and stability. Herein, we report an investigation of the AsNCa3 antiperovskite system for its potential in photovoltaic devices. We consider eight distinct crystalline phases, their structural parameters, dynamical sta…

Near-Field SWIPT Using XL-MIMO: Power Allocation and Subarray Activation
Muhammad Zeeshan Mumtaz, Mohammadali Mohammadi, Hien Quoc Ngo, Michail Matthaiou
https://arxiv.org/abs/2506.20050

Near-Field SWIPT Using XL-MIMO: Power Allocation and Subarray Activation
This paper investigates the simultaneous wireless information and power transfer (SWIPT) capability of a modular extremely large multiple-input multiple-output (XL-MIMO) system, in the context of power consumption (PC) efficiency. The network users are divided into two functional categories: information decoding (ID) users and energy harvesting (EH) users. Non-stationary near-field channels are considered whilst the users are located in spatially distinct visibility regions (VRs). We formulate …

Lookup Table-based Multiplication-free All-digital DNN Accelerator Featuring Self-Synchronous Pipeline Accumulation
Hiroto Tagata, Takashi Sato, Hiromitsu Awano
https://arxiv.org/abs/2506.16800

Lookup Table-based Multiplication-free All-digital DNN Accelerator Featuring Self-Synchronous Pipeline Accumulation
Deep neural networks (DNNs) have been widely applied in our society, yet reducing power consumption due to large-scale matrix computations remains a critical challenge. MADDNESS is a known approach to improving energy efficiency by substituting matrix multiplication with table lookup operations. Previous research has employed large analog computing circuits to convert inputs into LUT addresses, which presents challenges to area efficiency and computational accuracy. This paper proposes a novel …

Towards Sustainable Computing: Exploring Energy Consumption Efficiency of Alternative Configurations and Workloads in an Open Source Messaging System
Maria Voreakou, George Kousiouris, Mara Nikolaidou
https://arxiv.org/abs/2506.10693

Towards Sustainable Computing: Exploring Energy Consumption Efficiency of Alternative Configurations and Workloads in an Open Source Messaging System
Energy consumption in current large scale computing infrastructures is becoming a critical issue, especially with the growing demand for centralized systems such as cloud environments. With the advancement of microservice architectures and the Internet of Things, messaging systems have become an integral and mainstream part of modern computing infrastructures, carrying out significant workload in a majority of applications. In this paper, we describe an experimental process to explore energy-ba…

RL-Driven Semantic Compression Model Selection and Resource Allocation in Semantic Communication Systems
Xinyi Lin, Peizheng Li, Adnan Aijaz
https://arxiv.org/abs/2506.18660

RL-Driven Semantic Compression Model Selection and Resource Allocation in Semantic Communication Systems
Semantic communication (SemCom) is an emerging paradigm that leverages semantic-level understanding to improve communication efficiency, particularly in resource-constrained scenarios. However, existing SemCom systems often overlook diverse computational and communication capabilities and requirements among different users. Motivated by the need to adaptively balance semantic accuracy, latency, and energy consumption, this paper presents a reinforcement learning (RL)-driven framework for semant…

Energy Efficiency Optimization of Finite Block Length STAR-RIS-aided MU-MIMO Broadcast Channels
Mohammad Soleymani, Ignacio Santamaria, Eduard Jorswieck, Robert Schober, Lajos Hanzo
https://arxiv.org/abs/2506.11594

Energy Efficiency Optimization of Finite Block Length STAR-RIS-aided MU-MIMO Broadcast Channels
Energy-efficient designs are proposed for multi-user (MU) multiple-input multiple-output (MIMO) broadcast channels (BC), assisted by simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RIS) operating at finite block length (FBL). In particular, we maximize the sum energy efficiency (EE), showing that STAR-RIS can substantially enhance it. Our findings demonstrate that the gains of employing STAR-RIS increase when the codeword length and the maximum tolerable b…

Federated Learning within Global Energy Budget over Heterogeneous Edge Accelerators
Roopkatha Banerjee, Tejus Chandrashekar, Ananth Eswar, Yogesh Simmhan
https://arxiv.org/abs/2506.10413

Federated Learning within Global Energy Budget over Heterogeneous Edge Accelerators
Federated Learning (FL) enables collaborative model training across distributed clients while preserving data privacy. However, optimizing both energy efficiency and model accuracy remains a challenge, given device and data heterogeneity. Further, sustainable AI through a global energy budget for FL has not been explored. We propose a novel optimization problem for client selection in FL that maximizes the model accuracy within an overall energy limit and reduces training time. We solve this wi…

psi: Plant Photosystem I excitation energy transfer network (2020)
Weighted directed network of the light-harvesting Photosystem Ι (PSI) of the plant Pisum sativum. The nodes represent chromophores with different identities (i.e. chlorophyll a, chlorophyll b, β-carotene and derivates, lutein, violaxanthin), while edges represent FRET transfer between chromophores. The link directionality connecting nodes in the PSI network depends on the energy levels of the connected chromophores. The…

Joint Power Allocation and Reflecting-Element Activation for Energy Efficiency Maximization in IRS-Aided Communications Under CSI Uncertainty
Christos N. Efrem, Ioannis Krikidis
https://arxiv.org/abs/2507.11413

Joint Power Allocation and Reflecting-Element Activation for Energy Efficiency Maximization in IRS-Aided Communications Under CSI Uncertainty
We study the joint power allocation and reflecting element (RE) activation to maximize the energy efficiency (EE) in communication systems assisted by an intelligent reflecting surface (IRS), taking into account imperfections in channel state information (CSI). The robust optimization problem is mixed integer, i.e., the optimization variables are continuous (transmit power) and discrete (binary states of REs). In order to solve this challenging problem we develop two algorithms. The first one i…

ECLIP: Energy-efficient and Practical Co-Location of ML Inference on Spatially Partitioned GPUs
Ryan Quach, Yidi Wang, Ali Jahanshahi, Daniel Wong, Hyoseung Kim
https://arxiv.org/abs/2506.12598

ECLIP: Energy-efficient and Practical Co-Location of ML Inference on Spatially Partitioned GPUs
As AI inference becomes mainstream, research has begun to focus on improving the energy consumption of inference servers. Inference kernels commonly underutilize a GPU's compute resources and waste power from idling components. To improve utilization and energy efficiency, multiple models can co-locate and share the GPU. However, typical GPU spatial partitioning techniques often experience significant overheads when reconfiguring spatial partitions, which can waste additional energy through rep…

Optimizing Solar Energy Production in the USA: Time-Series Analysis Using AI for Smart Energy Management
Istiaq Ahmed, Md Asif Ul Hoq Khan, MD Zahedul Islam, Md Sakibul Hasan, Tanaya Jakir, Arat Hossain, Joynal Abed, Muhammad Hasanuzzaman, Sadia Sharmeen Shatyi, Kazi Nehal Hasnain
https://arxiv.org/abs/2506.23368

Optimizing Solar Energy Production in the USA: Time-Series Analysis Using AI for Smart Energy Management
As the US rapidly moves towards cleaner energy sources, solar energy is fast becoming the pillar of its renewable energy mix. Even while solar energy is increasingly being used, its variability is a key hindrance to grid stability, storage efficiency, and system stability overall. Solar energy has emerged as one of the fastest-growing renewable energy sources in the United States, adding noticeably to the country's energy mix. Retrospectively, the necessity of inserting the sun's energy into th…

Exploiting Convexity of Neural Networks in Dynamic Operating Envelope Optimization for Distributed Energy Resources
Hongyi Li, Liming Liu, Yunyi Li, Zhaoyu Wang
https://arxiv.org/abs/2508.13090

Exploiting Convexity of Neural Networks in Dynamic Operating Envelope Optimization for Distributed Energy Resources
The increasing penetration of distributed energy resources (DERs) brings opportunities and challenges to the operation of distribution systems. To ensure network integrity, dynamic operating envelopes (DOEs) are issued by utilities to DERs as their time-varying export/import power limits. Due to the non-convex nature of power flow equations, the optimization of DOEs faces a dilemma of solution accuracy and computation efficiency. To bridge this gap, in this paper, we facilitate DOE optimization…

Energy efficiency of DMAs vs. conventional MIMO: a sensitivity analysis
Pablo Ram\'irez-Espinosa, David Morales-Jim\'enez, Beatriz Soret
https://arxiv.org/abs/2506.09181

Energy efficiency of DMAs vs. conventional MIMO: a sensitivity analysis
Motivated by the stringent and challenging need for `greener communications' in increasingly power-hungry 5G networks, this paper presents a detailed energy efficiency analysis for three different multi-antenna architectures, namely fully-digital arrays, hybrid arrays, and dynamic metasurface antennas (DMAs). By leveraging a circuital model, which captures mutual coupling, insertion losses, propagation through the waveguides in DMAs and other electromagnetic phenomena, we design a transmit Wien…

A Data-driven Predictive Control Architecture for Train Thermal Energy Management
Ahmed Aboudonia, Johannes Estermann, Keith Moffat, Manfred Morari, John Lygeros
https://arxiv.org/abs/2506.09187

A Data-driven Predictive Control Architecture for Train Thermal Energy Management
We aim to improve the energy efficiency of train climate control architectures, with a focus on a specific class of regional trains operating throughout Switzerland, especially in Zurich and Geneva. Heating, Ventilation, and Air Conditioning (HVAC) systems represent the second largest energy consumer in these trains after traction. The current architecture comprises a high-level rule-based controller and a low-level tracking controller. To improve train energy efficiency, we propose adding a mi…

MD-OFDM: An Energy-Efficient and Low-PAPR MIMO-OFDM Variant for Resource-Constrained Applications
Rahul Gulia
https://arxiv.org/abs/2507.13623 https://

MD-OFDM: An Energy-Efficient and Low-PAPR MIMO-OFDM Variant for Resource-Constrained Applications
Orthogonal Frequency Division Multiplexing (OFDM) combined with Multiple-Input Multiple-Output (MIMO) techniques forms the backbone of modern wireless communication systems. While offering high spectral efficiency and robustness, conventional MIMO-OFDM, especially with complex equalizers like Minimum Mean Square Error (MMSE), suffers from high Peak-to-Average Power Ratio (PAPR) and significant power consumption due to multiple active Radio Frequency (RF) chains. This paper proposes and mathemat…