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Breakthrough system supports over 1,000 qubits, setting a new standard in quantum computing infrastructure

Keysight Technologies, Inc. has delivered the world’s largest commercial quantum control system (QCS) to the National Institute of Advanced Industrial Science and Technology (AIST) in Japan. The system has been integrated into the Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT). This control system is now part of the new evaluation testbed at G-QuAT, which will push the limits of what is possible with quantum computing in terms of both scale and performance.

All quantum computers require a control system to translate from the classical world of code and cables to the quantum world of photons and qubits. As quantum computers grow in size, complexity, and performance, requirements for the control system become much more stringent. Any gap in the control system performance can compromise the capabilities of the quantum computer, so it was important for AIST to select the right partner for this critical component.

Thanks to early investments in scalable architecture, Keysight was able to deliver this control system capable of powering leading-edge quantum computers. Extensive testing demonstrated that rigorous requirements on noise, time alignment, and phase coherence are maintained across the system. This delivery establishes Keysight as the first commercial control system vendor to deliver a system that supports 1,000+ qubits and proves that Keysight’s QCS can meet the scaling challenges of next-generation quantum computers.

Dr. Masahiro Horibe, Deputy Director of G-QuAT, AIST, said: “The 1,000-qubit control system developed here is a groundbreaking device, the world’s first and largest of its kind, realized through Keysight’s exceptional engineering capabilities in response to our advanced technical requirements. The advancement of quantum technology requires not only theoretical progress but also sophisticated engineering to support it. This system has enabled the precise synchronization, control, and readout of complex multi-channel signals, making large-scale qubit operations possible. It is a clear demonstration that engineering is paving the way for the future of quantum technology. We express our deep respect for Keysight’s development capabilities and look forward with great anticipation to further technological innovations.”

Dr. Eric Holland, General Manager, Keysight Quantum Engineer Solutions, said: “Control systems serve a vital role in quantum computing, acting as the bidirectional bridge between the classical and quantum worlds. We are both honored and excited to partner with AIST G-QuAT, providing the hardware and software tools necessary to achieve the critical milestone of a 1,000-qubit quantum computer, a key step toward realizing quantum advantage for practical business applications.”

The post Keysight Installs World’s Largest Commercial Quantum Control System at AIST’s Leading-Edge G-QuAT Center appeared first on ELE Times.

New battery gauges with Dynamic Z-Track algorithm enable precise battery monitoring in applications such as laptops and e-bikes.

Texas Instruments (TI) introduced new single-chip battery fuel gauges with first-of-its-kind adaptive Dynamic Z-Track technology for more efficient, reliable operation in battery-powered devices. Compared to traditional gauging methods, the predictive modeling algorithm in TI’s BQ41Z90 and BQ41Z50 gauges achieve industry-leading state-of-charge and state-of-health accuracy within 1% error, helping extend battery run time by up to 30%.

Why it matters

As users demand more power from electronics, such as laptops, e-bikes and portable medical devices, battery management systems (BMSs) must provide precise, accurate, real-time monitoring. The BQ41Z90 and BQ41Z50 fuel gauges with Dynamic Z-Track technology help engineers design electronic devices with accurate battery capacity readings, even under unpredictable loads. With this increased accuracy, engineers can select a battery size with confidence, eliminating the need for oversized batteries.

“Whether you’re finishing a project on your laptop or riding home on an e-bike, accurate battery capacity estimates and reliability are critical,” said Yevgen Barsukov, TI Fellow and head of BMS algorithm development. “Traditional battery monitoring methods often struggle with accuracy under erratic use conditions, leading to unreliable predictions. However, our new Dynamic Z-Track technology is a predictive battery model that can self-update across dynamic load conditions, like those created by AI applications, ensuring the most accurate run-time prediction. Evolving from 20 years of reactive monitoring, this innovation enables users to experience dependable function, safer operation, and precise tracking of battery age and run time.”

Battery-powered electronics are becoming more complex, making it even more important to use board space efficiently. The BQ41Z90 is the industry’s first highly integrated fuel gauge, monitor and protector for 3-to-16 lithium-ion (Li-ion) battery cells in series. This single-chip solution enables engineers to reduce complexity and save as much as 25% of board space compared to traditional discrete solutions. The BQ41Z50 supports 2-to-4 cells in series.

The post Predictive battery management technology from TI delivers up to 30% longer run time in battery-powered electronics appeared first on ELE Times.

This is a WLED ESP32 project that was a lot of fun. Custom clear acrylic rods sanded all 4 sides for diffusion and diffraction. Strips are Muzata 12vdc 3-led modules per pixel addressable RGB. I’m just running at 25% brightness, these get crazy bright. Seems no video allowed in post, pics are not enough. Visit r/WLED and see cool projects other Redditors did. Some are seriously talented. Every thing is safe and a fuse. Power is through a GFCI outdoor wall outlet, so no zappy. PSU and strip are IP67. Box is 6 x 6 x 4 “ and weather proof. I can control everything over Wifi, and have it turn on at sunset with longitude and latitude. submitted by /u/SirGreybush [link] [comments]

Honestly just wanted to share this! I've done tons and tons of soldering, but have never made a protoboard of any kind. Gave it a shot and damn, came out alright! For those wondering, its a 4 axis stepper board for a lil' robot I'm working on. submitted by /u/Traditional_Low_3786 [link] [comments]

Indie is aiming the stable, narrow-linewidth laser at scalable quantum computing and secure communications applications.

Chris Van de Walle, a distinguished professor in the Materials Department of University of California Santa Barbara (UCSB), has received the 2025 Heinrich Welker Award in recognition of his “development and application of computational methods to elucidate the properties of interfaces, defects, doping, polarization and loss mechanisms in compound semiconductors.”...

Infineon Technologies AG Munich, Germany has launched the CoolSiC MOSFETs 1200V G2 in a top-side-cooled (TSC) Q-DPAK package. Delivering what is said to be optimized thermal performance, system efficiency and power density, the new devices were specifically designed for demanding industrial applications that require high performance and reliability, such as electric vehicle chargers, solar inverters, uninterruptible power supplies, motor drives, and solid-state circuit breakers...

Playing songs on it is very interesting submitted by /u/Impossible_Luck_3839 [link] [comments]

🔵 Велика ймовірність вступити на бюджет до КПІ ім. Ігоря Сікорського! Запрошуємо на бакалаврат на спеціальності, яким надається особлива підтримка! kpi вт, 07/29/2025 - 21:29

Q.ANT's photonic processor has gone live at Leibniz Supercomputing Centre, cutting energy use by up to 90%.

Implementing a simple digital-to-analog converter (DAC) by cascading a single pulse width modulator (PWM) and an analog low-pass filter is nothing new. Nor is applying to a filter the sum of the outputs of a most significant 2N-count PWM and a least significant 2N-count one to get a composite 22N-bit DAC [1][2]. But designing one with simple, adjustment-free topologies and reasonably accurate, repeatable performance characteristics is not trivial. A proposed example is seen in Figure 1. Let’s examine the circuit from the output to the input.

Figure 1 The PWM—driven 16-bit DAC. Capacitors C1, C2, and C3 are NPO/COG ceramic.

Wow the engineering world with your unique design: Design Ideas Submission Guide

Op amp

The OPA383 is a “rail-to-rail” input and output op amp. Typical of such parts, the output doesn’t quite swing to the rails. A close look at the spec reveals that the V+ and V- supplies should be at least ±155 mV beyond the range of output signals, and their difference should be less than 5.5 V.  Input offset voltage is ±5 µV maximum at 25°C, but unfortunately, we are not given limits over temperature. However, a graph of 5 measured units shows limited susceptibility to temperature. Let’s assume three times 5, or a 15 µV maximum over the temperature range.

The bias current is ±76 pA maximum from -40°C to +85°C. I’d like to keep the design’s various independent error contributions under ½ PWM count (in this case, under 2-17 of full-scale). Considering the under 100 kΩ resistance seen by the op amp input, full-scale DAC voltages over 2.0 V would encounter errors less than ½ count due to bias current and offset voltage.

The op amp’s DC gain is a minimum of 118 dB, and its gain-bandwidth (GBW) product is 2.5 MHz typical. In the absence of other information, I’ll assume and work with a minimum GBW of 1 MHz.

PWM filter

The filter consists of U2, Ra, Rb1, Rb2, R1, R2, R3, C1, C2, and C3. It’s important to keep a handle on the tolerances of these passive components to ensure repeatable results. The capacitances of common ceramic types such as Y5V and X7R are very sensitive to temperature and to DC voltage; they are not recommended for use in filters requiring any significant stability. Film and ceramic COG/NPO types are far less sensitive. NPO/COG capacitors and the resistors of the values and tolerances shown in the schematic are available for well under $0.10 in 1000-piece quantities.

The filter shown is a 3rd-order one (evident from the presence of three capacitors). Generally, 3rd-order filters offer a smaller (better) product of settling time and ripple attenuation factor than 2nd-order filters (two capacitors). Design aids for 3rd-order types are rare, so I’ve used one I developed and published in EDN almost 15 years ago [3]. This filter does not rely on the cancellation of large signals of opposing phases, so there is no need for adjustment pots to deal with the lack of zero-tolerance components that would otherwise be required to achieve maximal nulling.

It’s the job of the filter to suppress the AC “ripple” of PWM signals, which are at their worst when the output is 50% of full scale. Minimization of settling time is also of interest. To assess the effects of variations due to component tolerances, Figure 2 and Figure 3 show 100-run Monte Carlo trials of settling times for a zero to full-scale transition and for ripple attenuation.

Figure 2 100 Monte Carlo runs of a transition from 0 to full scale, 0 to 65535 counts. Settling to better than ½ count occurs in less than 2 milliseconds.

Figure 3 100 Monte Carlo runs of ripple, where full scale is 65535 counts. Ripple is less than ½ PWM count peak and 1 count peak-to-peak. PWM frequency is 78 kHz.

Summing network

There are two 8-bit PWMs. To create a 16-bit signal, the contribution of the most significant PWM signal is weighted by a factor very close to 256 times larger than that of the less significant PWM signal. A summing network of Ra and Rb1 + Rb2 accomplishes this. (Note that the remaining filter components have no DC effect on this network.)

Filter drivers (logic Inverters)

The logic inverters shown driving the summing network have finite output resistances, which effectively add to those of Ra and R1b. Unfortunately, logic inverters are not linear devices and are not characterized as such. The best way to determine maximum output resistance from their data sheets is to first identify the specified supply voltage nearest (but less than or equal) to the one intended for use, and then divide the maximum output voltage drop by the specified load current.

It’s best to do this for the high side, as its resistance is typically higher than that of the low side. For instance, if a 3.3-V supply is intended for a Texas Instruments SN74AC04, use the datasheet’s 2.46-V minimum for a 3-V supply drawing 12 mA to arrive at a maximum resistance of 45 Ω. Paralleling five gates will reduce that resistance to an unknown amount below 9 Ω. The amount is unknown because the individual inverters share common resistances on the wafer and in the wafer-to-package bonding wires. And so up to 9 Ω is added to Ra. The up to 45 Ω added to Rb has a comparably negligible effect.

But here we depart from the goal of limiting an error source to a maximum contribution of ½ count—the maximum differential non-linear error is now just under 1 count. Fortunately, even with this error, an increasing series of counts yields a monotonically rising sequence of output voltages. If the performance improvement is worth the cost, you could stay below a ½ count error by doing the following:

• Replacing the inverter with the low-resistance, dual-channel TS5A22362DRCR analog switch
• Replacing the R1a1% part with a 0.05% part
• Replacing the 30.1 kΩ R1b with a 28.7 kΩ 1% resistor in series with a 5% 510-Ω unit.

Driver power supply

Alas, once again, we must abandon the goal of keeping the errors introduced to less than ½ LSb. The TI REF35 IC’s ±0.05% at 25°C rating equates to 33 LSb’s! And even with the benefit of calibration and added hardware to adjust the inverter/analog switch’s supply voltage, the reference’s 12 ppm/°C temperature variations would leave us in the lurch. Once again, we have to eat some error.

In the spirit of continuing to do our best with the cards dealt, the reference’s DC resistance (60 ppm max of 3.3 V (for instance) / 1 mA) is about only 0.2 Ω. This is negligible when met with the DC resistance seen through the summing network of Ra and Rb. Transients from the inverters are a concern, however.

Adequate decoupling of those devices is a must. Additionally, the AC impedance due to the combination of R1, Ra Rb, and C1 of approximately Zsum = 16.5 kΩ appears at the inverter outputs and so also across their supply terminals. Fortunately, these are at frequencies no lower than the PWM frequency (see next section for this value). The capacitors shown keep the impedance at this frequency well below 0.1% of the almost completely resistive Zsum. For practical considerations, the magnitude of this combination is indistinguishable from that of Zsum.

PWM signal source

The PWM signal source is probably a microprocessor. These days, most of them can be clocked at 20 MHz or greater, meaning that they could all source 8-bit PWMs of at least 20 MHz / 256 = 78 kHz. It’s this frequency or higher that the filter was designed for. So why not use microprocessor GPIO PWM outputs as drivers?

First, there’s the usually fairly high GPIO output resistance. Additionally, if you’ve ever looked closely at the voltage of a microprocessor digital output, you might have seen that it’s a few millivolts or even tens of millivolts from ground and the device’s supply. This is because the processor is performing functions in addition to generating a PWM, which draw significant current, producing voltage drops through portions of the IC wafer and its package bonding wires. The SN74AC74 has no such other functions, and any such voltage drops are part of the voltage drop specs discussed earlier.

Modifications

Want lower ripple amplitude? Increase the PWMs’ frequency. Want faster settling time? The resistance looking into Ra and Rb is Rab = 4009 Ω. Reduce R3, R2, and R1—Rab by some factor and/or C1, C2, and C3 by the same or different factor. Increase the PWMs’ frequency by at least the product of the factors. Increase it further to achieve both improvements.

To sum it up

A simple design has been introduced for a PWM-driven 16-bit DAC. Peak ripple is less than ½ LSb and the circuit settles to this level in less than 2 ms. Monte Carlo analyses show that these parameters are met even considering passive component and op amp GBW tolerances. In 1k quantities, the reference is about $1, the op amp is under $0.75, and the filter passives are each under $0.10.

Error sources in various parts of the circuit have been identified and, where possible, limited to no more than ½ LSb. To address other larger errors, suggestions of additional hardware and calibration have been made, but the temperature sensitivity of the voltage reference is a limiting factor.

Christopher Paul has worked in various engineering positions in the communications industry for over 40 years.

Related Content/References

1. Double up on and ease the filtering requirements for PWMs
2. Inherently DC accurate 16-bit PWM TBH DAC
3. Design second- and third-order Sallen-Key filters with one op amp

The post A nice, simple, and reasonably accurate PWM-driven 16-bit DAC appeared first on EDN.

Quantum sensors are devices that can detect motion at the atomic level, as well as in electric and magnetic fields, utilizing principles of quantum mechanics such as superposition, entanglement, and tunneling. These sensors measure physical quantities (time, gravity, acceleration, magnetic fields) by observing quantum phenomena in atoms, ions, or superconducting circuits.

Far more accurate and resilient than traditional sensing tech, quantum sensors are poised to revolutionize defense and aerospace electronics—fields where GPS denial, high-velocity motion, and extreme conditions are common. No longer the stuff of science fiction, quantum sensors represent a near-future inevitability.

Strategic Significance in Defense and Aerospace

Quantum sensors have the potential to significantly outperform current sensing technologies in navigational accuracy, threat detection, and situational awareness. For example, quantum inertial navigation systems (QINS) can be used in submarines, aircraft, and spacecraft to one day operate without GPS systems. This can be a game-changer in electronic warfare scenarios, where jamming the enemy’s GNSS (Global Navigation Satellite System) is a common tactic.

For submarines in particular, quantum magnetometers capable of detecting minute variations in magnetic fields could allow for passive submarine detection or underground mapping—all without active sonar or ground-penetrating radar.

In space, quantum gravimeters could be of great help in providing valuable data or aiding in resource exploration through the mapping of celestial bodies or detecting subterranean anomalies far more precisely than gravimeters of today.

Key Applications Under Development

While not yet deployed for real-world use, several hardware applications are well underway in the development phase and are emerging as front-runners.

• Quantum Clocks

There are already atomic clocks used in satellite navigation that use trapped ions or cold atoms. However, newer designs that aim to miniaturize or ruggedize these systems are also in development. They will be used in mobile platforms like UAVs or autonomous naval systems.

• Quantum Accelerometers and Gyroscopes

Exploiting interferometry to track motion—all without reliance on external signals—these sensors could allow aircraft or missiles traversing through GPS-denied zones to maintain accurate positioning for extended durations.

• Quantum Magnetometers

These tools, employing nitrogen-vacancy (NV) centers in diamond or superconducting quantum interference devices (SQUIDs), have the power to potentially detect magnetic anomalies with unprecedented accuracy. Theoretical applications range from locating stealth submarines to conducting geophysical reconnaissance from orbit.

• Quantum Gravimeters

Able to measure gravity variations at extreme resolutions, they could be used in planetary missions or terrain mapping to reveal subsurface structures or aid in autonomous navigation across unfamiliar environments.

These technologies are at varying stages of maturity. Some, like optical lattice clocks, are now stable and usable in laboratory conditions. Others still face hurdles in miniaturization, environmental shielding, and power efficiency.

However, it may only take a few more years before it begins real-world deployment

Technical and Operational Challenges

While holding great, revolutionary potential, there are still ways to go before quantum sensors become plug-and-play in aircraft, satellites, or even on the battlefield.

One of the main issues hindering real-world deployment is the lack of environmental robustness. Most of the quantum sensors we have now are very sensitive, not only to the parameters they’re designed to measure, but also to thermal fluctuations, electromagnetic interference, and mechanical vibrations.

Many can still only operate under extreme ultracold or vacuum conditions, needing complex laser systems to manipulate quantum states. At best, they currently function only in laboratory settings.

Data integration is also a hindrance. While quantum sensors can produce ultra-precise raw measurements, turning this into actionable data is another conversation. It will require its own technology involving sophisticated signal processing, calibration, and fusion with other sensor modalities. As such, developing AI or edge-processing capabilities tailored for quantum outputs must be developed simultaneously with the sensors themselves.

Finally, quantum tech will introduce new digital vulnerabilities as well, especially given the ultra-precise data these sensors are expected to produce. The need for secure data transmission, therefore, becomes even more critical. New defense-grade encryption and shielding must be developed. And compatibility with simpler apps, such as a VPN app for iPhone, can help ensure access to mission systems in mobile operational contexts.

Ecosystem and Policy Implications

As quantum sensors approach operational readiness, both governments and private companies are investing in the technology. Overall, the US, UK, and EU are reported to have collectively invested $17.7 billion in quantum technologies as of a 2025 OECD report.

For example, DARPA and the U.S. Department of Defense have established dedicated initiatives—like the Quantum Aperture Sensor program—to accelerate prototyping and field trials. As such, we may soon see quantum tech not just in aerospace or defense, but also in civilian and commercial spheres as well.

The Road Ahead

Quantum sensors will not replace classical systems overnight. They will first likely augment them through hybrid, transitional platforms that combine quantum and classical sensing. But they will eventually supersede current tech, becoming foundational for the next-generation aircraft, autonomous naval fleets, and deep-space missions.

It cannot be emphasized enough, however, that development must prioritize safety, reliability, supportive firmware systems, and personnel training for this new technology. Only then can we fully realize the transformative benefits of quantum sensing.

The post Quantum Sensors and Their Impact on Defense and Aerospace Electronics appeared first on ELE Times.

Intelligent power and sensing technology firm onsemi of Scottsdale, AZ, USA says that it is working with NVIDIA of Santa Clara, CA, USA to support the transition to 800V direct current (VDC) power architectures, which is driving significant gains in efficiency, density and sustainability for next-generation AI data centers...

ams OSRAM of Premstaetten, Austria and Munich, Germany has sold its Entertainment and Industry Lamps (ENI) business to Ushio Inc of Tokyo, Japan for €114m (on a cash-and-debt-free basis) as the first divestment under its deleveraging plan. Net deal proceeds will be determined upon final closing accounts at the date of the transaction closing, which is expected by the end of March 2026 (subject to typical closing procedures)...

ams OSRAM of Premstaetten, Austria and Munich, Germany has placed €500m 2029 senior notes to pre-finance OSRAM minority put option exercises and buy back €150m 2027 convertible bonds. The firm has also announces solid preliminary Q2/2025 results...

The Central Processing Unit (CPU) is the heart of any computing device, whether it be a personal laptop, a high-performance gaming rig, or an enterprise-grade server. In the fast-growing digital India, there continues to be growing demand for efficient and powerful CPUs. The right CPU brand is important for gaming, content creation, or commercial use.  Here are the top 10 CPU brands in India that are providing the computer experience in 2025.

1. Intel:

Corporation is based in Santa Clara, California, United States. It is also the most recognizable CPU brand in India and stands for power, stability, and energy efficiency. The Core i3, i5, i7, and i9 series dominate desktops and laptops while the Xeon series powers servers and workstations. Its vast ecosystem of compatible options, integrated graphics, and strong retail presence endear the brand to gamers, students, and professionals alike.AMD (Advanced Micro Devices).

2. AMD:

Headquartered in Santa Clara, California, AMD too is an U.S.-based company. With its Ryzen Series offering better multi-core performance at competitive prices. AMD offers Ryzen 3, 5, 7, and 9 CPUs to suit a wide range of users, from budget conscious individuals to avid gamers and creative professionals. EPYC and Threadripper are excellent for serious work and large enterprises.

3. Apple:

The initiative to enter the CPU market was taken by Apple Inc., based in Cupertino in California, USA, with the designing and manufacturing of custom ARM-based Apple Silicon chips. The concept is very much simple: The processors and chips are exclusive to Apple, thereby allowing the vanquishing of performance barriers on MacBooks, iMacs, and iPads through processors bearing the M1, M2, and M3 names. These processors are not sold as chips to be put into other machines, yet in India, they find usage in the premium productivity and creative segments as they offer unmatched power efficiency and flawless integration with macOS.

4. Qualcomm

An American company headquartered in San Diego, California, Qualcomm is primarily known for mobile chipsets and now has computing in its purview. Snapdragon Compute platforms 8cx and 7c Gen 3 find use in Windows on ARM laptops and provide a very good power-efficient lightweight computing experience for users looking for an always connected kind of computing battery life with good mobile network support.

5. MediaTek

Media Tek is a Taiwanese company headquartered in Hsinchu, in northern Taiwan. Being value for money service providers, they play prominent roles in India’s cheap computing segment. Their Kompanio line powers budget Chromebooks and low-tier laptops, mostly bought by students and some education institutions. MediaTek processors continue to receive appreciation because of their energy.

6. IBM

IBM, with its corporate offices situated in Armonk, New York, USA, rocks the status of a world leader in enterprise computing. Surrounding its Power9 and Power10 processors used in high-end servers and data centers scattered across India, it especially finds great utility within financial institutions and research facilities. Though not seen as a consumer product, IBM CPUs are crucial for backend computing applications and data-intensive applications.

7. VIA Technologies

It is another company based out of Taiwan, and VIA Technologies focuses on embedded and low-power CPU development. The Eden and C7 processors find application in niche industrial settings such as automation, transportation, and edge computing machines. In a more common PC setup, these processors are not used extensively; however, VIA is crucial for India’s developing industrial technology infrastructure.

8. Unisoc

Unisoc is a Chinese semiconductor company, headquartered in Shanghai, China. It provides affordable processors for tablets, cellphones, and educational tools. In India, Unisoc CPUs are often deployed in government-distributed learning devices primarily because of their affordability and consistent performance in basic tasks.

9. Samsung

Samsung, based in Seoul, is the producer for the Exynos family of processors. These processors are mostly used for smartphones, and so are the Exynos 1280 and onwards, which are increasingly being incorporated into ARM-based tablets and hybrid compute devices. Samsung’s push into ARM laptops will bear it in stock for lightweight and budget computing in the Indian market.

10. Rockchip

Rockchip, or Fuzhou Rockchip Electronics Co., Ltd., is the semiconductor company headquartered in Fuzhou, China. The company is mostly into designing low-power ARM-based processors to be used in tablets, smart TVs, and embedded computing solutions. In India, Rockchip processors are found in mass-market Android tablets, OTT boxes, and educational devices simply because of their low cost and fair multimedia capabilities. Examples of smart-classroom-based RK series chips used by the company include RK3328 and RK3566 as well as digital kiosks and lightweight computing environments. Rockchip is yet to lose its presence in the budget digital hardware segment in India.

Comparison:

Brand	Popular Series / Chips	System Design & Number of Cores	Key Technologies & Strengths	Best For
Intel	Core i3–i9, Xeon	x86, up to 24 cores (i9), Hyper-Threading	Intel UHD / Iris Xe Graphics, AI Boost, Thread Director, PCIe 5.0 support	Gamers, professionals, general users
AMD	Ryzen 3–9, Threadripper	x86, up to 96 cores (Threadripper)	Zen 4 architecture, Smart Access Memory, Radeon Graphics, Overclocking	Gamers, creators, multitaskers
Apple	M2, M2 Pro, M3	ARM-based, up to 12 cores	Unified Memory Architecture, Neural Engine, superior power efficiency	Designers, video editors, Mac users
Qualcomm	Snapdragon 8cx Gen 3	ARM, up to 8 cores	5G/4G modem integration, Adreno GPU, NPU, Always-On Connectivity	Lightweight users, mobile computing
MediaTek	Kompanio 1300T, 1380	ARM, 8-core CPUs	Integrated Mali GPU, AI Processing Unit, low power draw	Chromebook users
VIA	Eden X4, C7	x86, dual or quad-core (low power)	Fanless design, long lifecycle, embedded optimization	Industrial PCs, automation systems
Unisoc	T610, T700	ARM, 8-core CPUs	LTE modem, basic GPU, low thermal footprint	Entry-level tablets, digital classrooms
IBM	Power9, Power10	RISC, up to 120 threads	SMT4/8, massive memory bandwidth, enterprise-grade RAS features	Servers, banking, research infrastructure
Samsung	Exynos 1280, 1380	ARM, up to 8 cores	AI Engine, Image Signal Processor, power-efficient fabrication	Tablets, ARM laptops, multimedia systems
Rockchip	RK3328, RK3566	ARM Cortex-A53/A55, quad-core	4K video decoding, GPU for media, affordable SoC design for edge/IoT	Budget tablets, OTT devices

Conclusion:

From mainstream gaming to heavy industrial automation, CPU needs are changing quite dramatically in India, with changes being wrought in innovation and specialization for the market. In terms of performance and brand, Intel and AMD always come to mind first, but new players and niche players like MediaTek, VIA, are steadily making room for themselves.

The post Top 10 CPU Brands in India appeared first on ELE Times.

submitted by /u/rakesh-kumar-phd [link] [comments]

Built on the Arm Cortex-M23 core, the new MCU family delivers precise, low-power motor control with built-in safety and diagnostic features.

Hi all, what is resister R54 rated to? I know that sounds silly, but I’m colourblind and I can’t see what colours are there! Any help would be greatly appreciated :) submitted by /u/Andrew6748942 [link] [comments]

Solid-state transformers (SSTs) that use power electronics and high-frequency components to convert and control electricity are extremely useful for integrating renewable energy sources and energy storage systems into the grid, as well as managing surges and disturbances, reducing the likelihood of blackouts. In April, a major blackout occurred across Spain and Portugal, disrupting power for more than 10 hours and causing economic losses of an estimated $1.6bn...