Quantum Error Correction: Surface Code & Fault-Tolerant Computing
Quantum error correction news: logical qubits, surface code, fault-tolerant quantum computing, QEC. Error mitigation & suppression.
Quantum error correction (QEC) is the critical enabler for fault-tolerant quantum computing, protecting quantum information from environmental noise through redundant encoding across multiple physical qubits. Recent breakthroughs demonstrated below-threshold error correction where logical qubit error rates fall below physical qubit rates.
The 2D surface code is the leading QEC approach due to high error threshold (~1%), local nearest-neighbor interactions, and compatibility with superconducting chip designs. Recent breakthroughs include Google's Willow demonstrating below-threshold surface code scaling, and IBM's Heavy Hex optimizing qubit connectivity for surface code implementation.
India's Quantum Error Correction Research
India's National Quantum Mission includes quantum error correction in its basic science research component. The Foundation for QC Innovation at IISc Bengaluru addresses error correction as part of its quantum computing development. The Harish-Chandra Research Institute (HRI) and Institute of Mathematical Sciences (IMSc) conduct theoretical research on quantum error correction codes.
The NQM targets developing intermediate-scale quantum computers with 50-1000 physical qubits, requiring error mitigation and eventually error correction to achieve quantum advantage. The mission includes development of indigenous control electronics and error mitigation techniques.
quantum-computingDiraq and imec Demonstrate Eight-Qubit Linear Array Fabricated on 300 mm CMOS Silicon Foundries
Overview of the operation and calibration of an 8-dot device. Quantum engineering pioneer Diraq has announced a validation milestone in silicon-based solid-state quantum architectures with the publication of its peer-reviewed paper, “Eight-Qubit Operation of a 300 mm SiMOS Foundry-Fabricated Device,” in Nature Communications. In direct collaboration with European nanoelectronics hub imec, the research team successfully scaled a linear array of silicon spin qubits from a two-qubit unit cell to an integrated eight-qubit processor. Crucially, the multi-qubit device was manufactured entirely within a commercial, industry-standard 300 mm Silicon Metal-Oxide-Semiconductor (SiMOS) foundry line, demonstrating that highly uniform, qubit-grade quantum dot configurations can be replicated at volume without sacrificing fundamental quantum coherence or gate operational control. [ Diraq - imec 8-Qubit Hardware Matrix ] Fabrication Node ──► imec 300 mm industrial SiMOS production line on isotopically purified 28Si. Array Configuration ──► 8-dot linear chain managed as 4 double quantum dot (DQD) unit cells. Dephasing Time (T2*)──► Ramsey dephasing intervals reaching up to 41 µs (Average ~21 µs). Coherence (T2 Hahn) ──► Hahn-echo coherence times reaching up to 1.31 ms (Average ~0.7 ms). Readout Architecture──► Two-step cascaded charge-sensing to minimize wire count and thermal load. The Architecture of the 8-Dot SiMOS Micro-Array The physical device utilizes electron spins confined within electrostatically defined quantum dots as effective spin-half systems. The layer stack is fabricated on an epitaxially grown silicon substrate isotopically purified to a residual 29Si concentration of only 400 ppm to eliminate ambient nuclear spin dephasing. A triple-layer overlapping polycrystalline silicon gate stack—patterned with a tight 90 nm gate pitch—is used to outline the quantum dots instead of traditional aluminum gates, significantly reducing low-temperature lattice strain at
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quantum-computingQUDORA and QAI Partner to Integrate Trapped-Ion Quantum Computer into South Korean AI Data Center
QUDORA and QAI Partner to Integrate Trapped-Ion Quantum Computer into South Korean AI Data Center European full-stack quantum hardware developer QUDORA Technologies GmbH has signed a Memorandum of Understanding (MoU) with South Korean deep-tech specialist QAI Co., Ltd. to co-deploy trapped-ion quantum processing units (QPUs) inside regional artificial intelligence data centers. Executed on July 9, 2026, the international framework initiates a technical feasibility study to wire QUDORA’s hardware layers directly into operational AI cloud infrastructures managed by QAI in South Korea. The integration track aims to establish a co-processing testbed where machine learning models and optimization subroutines can bounce workloads dynamically between classical hyper-scale graphics processors (GPUs) and low-noise quantum nodes without routing delays. [ QUDORA - QAI Partnership Matrix ] Hardware Modality ──► Integrated full-stack ion-trap QPUs driven by microwave electronics. Qubit Control Layer ──► Laser-free Near Field Quantum Control (NFQC) built on standard CMOS. Facility Infrastructure──► Multi-tenant AI data centers managed locally by QAI (South Korea). Regional Roadmap ──► Using South Korea as a commercial base to penetrate wider APAC markets. The technological alliance pairs QUDORA’s laser-free quantum manipulation framework with QAI’s vertically integrated computing stacks. Unlike traditional trapped-ion architectures that rely on heavy, alignment-sensitive optical laser lines to trigger gate operations, QUDORA utilizes its proprietary Near Field Quantum Control (NFQC) technology. This control scheme uses highly integrated microwave-based electronic circuitry embedded directly into the microfabricated ion-trap processor substrate. By replacing complex external optics with standard CMOS-compatible semiconductor electronics, the architecture drastically reduces fundamental phase noise and environmental drift. This hardware footprint extends raw qubit coherence interva
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quantum-computingQuantum Rings, qBraid Partner to Expand Free Access to Quantum Hardware
Insider Brief PRESS RELEASE — Quantum Rings, a leader in quantum developer tools whose toolchain lets any developer run quantum workloads anywhere, and qBraid (Chicago, Illinois), a leader in quantum-cloud computing, announced a partnership today to make Quantum Rings’ Open Quantum platform available within qBraid Lab. Through this collaboration, tens of thousands of qBraid users […]
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quantum-computing1 Incredible Quantum Computing Stock That Could Make Investors a Fortune - The Motley Fool
Quantum computing may seem like some far-off technology that will never come about, but that's just not the case. There are several companies with early-stage quantum computers that are producing real results for clients, and could easily expand into more mainstream usage as the technology improves and computer size expands. The current timetable for many quantum companies is around 2030, with major market expansion occurring by 2035. McKinsey & Company estimates that the annual quantum computing market could be worth up to $72 billion by 2030, leaving a huge market opportunity available for those who can seize it. One betting favorite is IonQ (IONQ 0.62%), as it's currently the worldwide leader in one of the most critical areas: accuracy. With IonQ holding a world record in this field, it's a favorite to make it to the finish line, and it could make investors a fortune along the way. Image source: Getty Images. IonQ's approach to quantum computing is different than its peers As alluded to above, IonQ holds the world record in 2-qubit gate fidelity, a measurement that ensures the answer is correct after processing through two processing gates. Most companies struggle to reach 99.9% fidelity, but IonQ holds the record at 99.99%. While that's only an extra 0.09%, that is a ton in the quantum computing world. It's the difference between making one error out of every 1,000 operations or one error in every 10,000 operations. IonQ has achieved this by using a unique architecture in its devices. Instead of a supercooling setup like many use, IonQ utilizes trapped-ion technology. This is inherently more accurate, although the trade-off is slower processing speeds. Still, the computing advantage that quantum provides is easily enough to justify these slower speeds. ExpandNYSE: IONQIonQToday's Change(-0.62%) $-0.28Current Price$45.08Key Data Points*:nth-last-child(-n+2)]:border-b-0">Market Cap$17BMarket cap calculated using publicly traded shares outstanding only. Does no
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quantum-computingPan and Colleagues Implement Patch-Based Logical Operations for Surface-Code Processing
A new set of tools for fault-tolerant logical operations brings practical quantum computation closer to reality. Weiping Lin and colleagues from University of Science and Technology of China, Tsinghua University and Zhongguancun Laboratory, have experimentally realised key elements of surface-code logical processing using a 107-qubit superconducting quantum processor. They implemented reusable primitives for manipulating surface-code patches, enabling logical state routing and a full Clifford gate set, a sharp advance beyond storing protected logical memory. The demonstration represents a vital progression in superconducting surface-code experiments, paving the way for more complex quantum algorithms and fault-tolerant computation. Reusable qubit operations enable flexible surface code manipulation A new breakthrough hinged on developing a ‘primitive layer’ of reusable operations for manipulating surface-code patches; this is akin to a mosaic artist mastering a few key tile arrangements that can then be combined to create complex designs. Surface codes are a leading approach to quantum error correction, encoding logical qubits using multiple physical qubits arranged in a two-dimensional lattice. Protecting quantum information requires maintaining the delicate superposition and entanglement of qubits, which are highly susceptible to environmental noise. Surface codes achieve this by distributing the quantum information across the lattice and encoding it in the correlations between qubits. The developed primitive layer allows for dynamic rearrangement of these encoded qubits without destroying the encoded information. Merge, split, expansion, shrinkage, and deformations mediated by domain walls and twist defects allowed for precise reshaping of sections of the qubit grid without disrupting the encoded quantum information. Domain walls represent boundaries between regions with different logical properties, while twist defects introduce controlled changes in the lattice
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quantum-computing1 Incredible Quantum Computing Stock That Could Make Investors a Fortune
Quantum computing may seem like some far-off technology that will never come about, but that's just not the case. There are several companies with early-stage quantum computers that are producing real results for clients, and could easily expand into more mainstream usage as the technology improves and computer size expands. The current timetable for many quantum companies is around 2030, with major market expansion occurring by 2035. McKinsey & Company estimates that the annual quantum computing market could be worth up to $72 billion by 2030, leaving a huge market opportunity available for those who can seize it. One betting favorite is IonQ (IONQ 0.62%), as it's currently the worldwide leader in one of the most critical areas: accuracy. With IonQ holding a world record in this field, it's a favorite to make it to the finish line, and it could make investors a fortune along the way. Image source: Getty Images. IonQ's approach to quantum computing is different than its peers As alluded to above, IonQ holds the world record in 2-qubit gate fidelity, a measurement that ensures the answer is correct after processing through two processing gates. Most companies struggle to reach 99.9% fidelity, but IonQ holds the record at 99.99%. While that's only an extra 0.09%, that is a ton in the quantum computing world. It's the difference between making one error out of every 1,000 operations or one error in every 10,000 operations. IonQ has achieved this by using a unique architecture in its devices. Instead of a supercooling setup like many use, IonQ utilizes trapped-ion technology. This is inherently more accurate, although the trade-off is slower processing speeds. Still, the computing advantage that quantum provides is easily enough to justify these slower speeds. ExpandNYSE: IONQIonQToday's Change(-0.62%) $-0.28Current Price$45.08Key Data Points*:nth-last-child(-n+2)]:border-b-0">Market Cap$17BMarket cap calculated using publicly traded shares outstanding only. Does no
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quantum-computingXanadu Accelerates U.S. Growth with New York State Office - Yahoo Finance
This is a paid press release. Contact the press release distributor directly with any inquiries. Xanadu Accelerates U.S. Growth with New York State Office Xanadu Quantum Technologies Limited Thu, July 9, 2026 at 7:00 AM EDT 7 min read XNDU.TO +1.20% XNDU +1.56% TORONTO, July 09, 2026 (GLOBE NEWSWIRE) -- Xanadu Quantum Technologies Limited ("Xanadu"; NASDAQ/TSX: XNDU), a leading photonic quantum computing company, today announced a significant expansion of its U.S. operations, anchored by its growing presence in Albany, New York. Albany has emerged as a hub for global innovation in quantum computing and advanced semiconductor research, positioning it as an ideal strategic base for Xanadu's U.S. expansion. Xanadu has also scaled up operations across the U.S., with growth in the San Francisco Bay Area as well as a distributed presence across the country spanning 19 states. In total, Xanadu's U.S.-based workforce has grown by more than 5-fold since 2023, and Xanadu anticipates its U.S.-based workforce to increase significantly by the end of this year. "The demand for quantum computing has never been higher and our rapid growth in the United States is a testament to the talent and strategic partnerships we have built across the semiconductor and technology industries to help meet those demands," said Dr. Christian Weedbrook, Founder and Chief Executive Officer of Xanadu. "By co-locating with key partners, we are working to ensure rapid response times and close-knit collaboration across teams. We are not just scaling our footprint; we are accelerating the pace of innovation." This expansion is a direct result of Xanadu's commanding technical progress and industrial partnerships. Xanadu's Aurora system established a foundation for future fault-tolerant quantum systems and demonstrated one of the many distinct advantages of a photonic approach to building quantum hardware: modularity and networkability, allowing for seamless integration into existing classical data centers.
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quantum-computingTiny Vibrations Expand Quantum Memory, ETH Zurich Researchers Find
Researchers at ETH Zurich have, for the first time, combined vibrating memory devices, mechanical resonators, with superconducting qubits, departing from conventional quantum computing approaches. Yiwen Chu and her colleagues are storing information not electromagnetically, but as mechanical vibrations within a quantum chip, significantly increasing the system’s storage capacity; the process resembles the vibrating strings of a guitar producing musical notes. This new architecture intentionally mirrors classical digital computers, separating processing from working memory for greater efficiency. “The interaction between the quantum processor and the quantum memory provides a crucial foundation for establishing quantum computers as a powerful and reliable way to perform computations that are not feasible with conventional computers,” says Yiwen Chu, a professor of Hybrid Quantum Systems. The team demonstrates both fundamental and advanced quantum calculations, providing proof of feasibility and laying the groundwork for a fully programmable quantum computer. Vibrational Memory: Resonators and Quantum Information Storage The ability to densely pack information into a small space remains a critical hurdle in quantum computing, and researchers are now exploring an unexpected avenue: mechanical vibrations. This departure from conventional approaches significantly increases the potential storage capacity within a given volume, offering a pathway toward more scalable quantum processors. The system functions much like a guitar; the resonators, akin to vibrating strings, each produce unique vibrational modes that represent distinct memory slots, with variations within those modes encoding specific information states. Unlike a guitar string governed by classical physics, these quantum vibrations operate under the rules of quantum mechanics, allowing for superposition and entanglement, properties unavailable to traditional computing. The team demonstrates the feasibility of th
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quantum-computingPhysical Error Rates Below Threshold Enable High Accuracy
Achieving arbitrarily high accuracy in quantum computation hinges on maintaining physical error rates below a constant threshold, a principle central to the viability of the technology. However, building fault-tolerant quantum computers introduces significant resource demands; the number of physical qubits needed scales with the square of the code distance ‘d’, while each round of operations grows linearly with ‘d’. Researchers are now proposing a new scheme for general quantum low-density parity-check (qLDPC) codes that lowers these demands, attaining a time overhead of O(da + o(1)) while maintaining constant qubit overhead. This method achieves a smaller time overhead than existing protocols for a broad range of codes, and for good qLDPC codes, further reduces the overhead to O(d1 + o(1)). Quantum Error Correction & Fault-Tolerance Thresholds The viability of scalable quantum computation rests on a delicate balance: maintaining accuracy despite inherent physical errors. According to the fault-tolerance theorem, when the physical error rate is below a constant threshold, arbitrarily high computational accuracy can be achieved by choosing a quantum error correction code with sufficiently large code distance d. However, implementing this error correction introduces resource overheads in terms of both qubit count and computational time. Each logical qubit, the fundamental unit of quantum information, demands multiple physical qubits for encoding and operation, and logical operations require multiple rounds of physical operations. Simultaneously, the time overhead scales as O(d), adding to the complexity. Recent advances focus on minimizing these costs; low-density parity-check (qLDPC) codes, like hypergraph product (HGP) codes, achieve a constant encoding rate. Breakthroughs have even pushed code distance scaling from d = Θ(n1/2) to d = Θ(n) while preserving the constant encoding rate. Two primary strategies exist for operating on these qLDPC codes: concatenated c
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quantum-computingRwth Aachen University Team Proposes Hybrid Color Code Architecture for Fault-Tolerant Computation
Researchers have created a new quantum computer architecture by combining two established methods of protecting quantum information, known as error correction. Quantum error correction is vital because qubits, the fundamental units of quantum information, are exceptionally susceptible to noise and decoherence, leading to computational errors; these codes provide a means of mitigating such errors. This hybrid system uses tetrahedral and H-tetrahedral codes; these codes allow for more operations to be performed without introducing errors than previously possible. Scientists at RWTH Aachen University and Technische Universität Munich have detailed a new approach to building more reliable quantum computers by combining two existing methods of protecting quantum information. The tetrahedral code, a three-dimensional quantum error correcting code, is known for its relatively high threshold for error rates, meaning it can tolerate a significant amount of noise before failing. The H-tetrahedral code is derived from the tetrahedral code via a Hadamard transform, altering its properties and enabling complementary operations. This hybrid architecture utilises tetrahedral and H-tetrahedral codes, allowing for more complex calculations with fewer errors than previously achievable. A key obstacle to creating a complete set of instructions for a quantum computer has been the Eastin-Knill theorem, which acts as a roadblock preventing fully universal operations using only error-resistant methods; think of it like trying to build a road with missing sections. The theorem essentially states that within a single quantum error-correcting code, it is impossible to implement a universal set of transversal gates. Transversal logical gates, where each physical component directly contributes to the result, simplify error correction and are central to this new design. This is because errors during a transversal gate operation are confined to a limited number of physical qubits, simplifying de
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quantum-computingPurdue Finds Unique 2D Phonon Source of Qubit Decoherence
Researchers at Purdue University have pinpointed an origin for spin relaxation in hexagonal boron nitride, identifying the out-of-plane flexural phonon branch, unique to two-dimensional materials, as the primary source of spin relaxation in boron vacancy centers. This finding extends existing theory to a previously unaddressed regime, offering a new microscopic interpretation of observed behavior in two-dimensional quantum defect centers. The Purdue team reports quantitatively reproducing the experimental magnetic field and temperature dependence of T1 (spin-lattice relaxation time) using a microscopic theory applying acoustic mode spin-phonon relaxation, achieving this accuracy without any empirical fitting parameters. These results reveal that relaxation dynamics are driven by a direct one-phonon emission and absorption process resonant with the Zeeman splitting, occurring in the sub-THz regime. A microscopic mechanism governs qubit coherence in hexagonal boron nitride, with sound waves playing the dominant role. The researchers report these findings in their recent work, and this level of predictive accuracy underscores the robustness of their microscopic model. This mechanism, resonant with the Zeeman splitting, builds upon existing treatments focused on low-field regimes. “We show that spin relaxation in the experimentally relevant field and temperature regime is dominated by the ZA phonon branch,” the researchers state. The study’s findings offer vital insights for developing high-field quantum sensing platforms utilizing layered materials, potentially unlocking enhanced performance in nanoscale magnetometry and other applications. The pursuit of robust quantum sensors has increasingly focused on point defects in two-dimensional materials, with the boron vacancy center in hexagonal boron nitride (hBN) emerging as a leading candidate. Realizing the full potential of these sensors requires a detailed understanding of the factors influencing performance, specific
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quantum-computingRISC-V Vector Engine Addresses 128 Qubits With One Instruction
Researchers are forecasting significant advances in quantum control for 2026, centered around a new approach leveraging the RISC-V Vector (RVV) engine. The team reports demonstrating the ability to address 128 qubits with a single instruction, a critical step toward scaling quantum systems beyond current limitations. This vectorized quantum control design also incorporates a hardware-based halt-resume protocol capable of restarting pipeline execution in 80 nanoseconds after a mid-circuit measurement, essential for the rapidly developing field of hybrid quantum-classical algorithms. Comprehensive evaluation using RISC-V toolchains and FPGA prototypes showed a 2.52 times speedup in program execution time compared to baseline designs, suggesting a pathway to overcome the classical control bottleneck hindering quantum processor expansion. Within each circuit family, speedup grows with the number of qubits; for example, performance increased from Bell-4 to Bell-8 by a factor of 52. This progression indicates that larger, more complex quantum algorithms will increasingly benefit from hardware designed to efficiently manage and process a greater number of qubits, moving beyond the limitations of earlier, smaller-scale systems. This capability represents a substantial leap in addressing scalability for quantum systems, moving beyond the sequential control methods that previously limited performance. The ability to operate on a larger qubit space in parallel is critical for realizing the full potential of quantum algorithms, particularly those designed to tackle complex optimization and simulation problems. The hardware-based halt-resume protocol, achieving a restart time of 80 nanoseconds after a mid-circuit measurement, is crucial for enabling rapid iteration in hybrid quantum-classical programs. This speed is essential for minimizing latency and maximizing the efficiency of algorithms that require frequent communication between the quantum processor and classical control
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quantum-computingDiraq Demonstrates Scaled Foundry-Fabricated Silicon-Based Qubit Array Made at imec
Insider Brief PRESS RELEASE — Diraq today announced the publication of “Eight-Qubit Operation of a 300 mm SiMOS Foundry-Fabricated Device” in Nature Communications, marking another decisive step on the company’s roadmap toward utility-scale quantum computers based on silicon. The paper shows that quantum bits (qubits) designed and fabricated by imec using the same industry-standard process […]
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quantum-computingDiraq’s Silicon Qubits Hit 99% Fidelity at 8-Qubit Scale
Diraq reports achieving 99% fidelity while scaling its silicon qubits to an eight-qubit array, a result published in Nature Communications that indicates a viable path toward practical quantum computing. The company fabricated the qubit array using imec’s 300 mm CMOS foundry process, the same technology used for conventional semiconductors, demonstrating that existing manufacturing infrastructure can support quantum chip production. This scaling from two to eight qubits, achieved in under a year, maintains key performance metrics such as coherence and control quality, thereby addressing a major hurdle in quantum computer development. “This is what an industrial pathway to quantum computing looks like,” said Andrew Dzurak, Founder and CEO of Diraq, adding that the company targets scaling to thousands of qubits by 2029 and more than one million qubits by 2031. Innovation Highlights: CMOS-native manufacturing processes, which have been refined over decades by the semiconductor industry, can be used to produce quantum chips that scale reliably. Larger arrays of silicon spin qubits maintain good performance along key metrics (coherence, control quality, architectural scalability for readouts) that was first demonstrated in smaller, two-qubit arrays. This level of performance and manufacturability will scale as array sizes increase, enabling silicon spin qubits to make a commercially useful quantum computer. imec 300mm CMOS Fabrication of Silicon Qubits Diraq’s recent advancements rely on a manufacturing process familiar to the semiconductor industry: imec’s 300mm complementary metal-oxide-semiconductor (CMOS) platform was used to fabricate an eight-qubit array, demonstrating a path toward mass production of quantum processors. Published in Nature Communications, the results reveal that silicon qubits can be scaled using established CMOS techniques without sacrificing performance, a critical challenge for practical quantum computing. This builds on a 2025 demons
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quantum-computingThe Other Direction: How AI Could Become The Operating System For Quantum Computing
WisdomTree5.92K FollowersFollow5ShareSavePlay(18min)CommentsSummaryAI is likely to accelerate quantum computing well before quantum accelerates AI, making today's AI infrastructure providers a compelling way to gain exposure to the theme.NVIDIA's Ising, CUDA-Q and NVQLink suggest the race for quantum leadership will be driven as much by AI infrastructure as by qubit breakthroughs.Rather than betting on hardware winners, investors can gain diversified exposure through the WisdomTree Artificial Intelligence and Innovation Fund and WisdomTree Quantum Computing Fund as AI and quantum technologies increasingly converge. mustafaU/iStock via Getty Images By Christopher Gannatti, CFA and Samuel Rines When NVIDIA (NVDA) announced Ising, a family of AI models designed specifically for quantum calibration and error decoding,1 it was easy to file the newsThis article was written byWisdomTree5.92K FollowersFollowIn 2006, WisdomTree launched with a big idea and an impressive mission — to create a better way to invest. We believed investors shouldn’t have to choose between cost efficiency and performance potential, so we developed the first family of ETFs designed to deliver both. Today, WisdomTree offers a leading product range that offers access to an unparalleled selection of unique and smart exposures.
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quantum-computingPhD proposal in energetic cost of fault-tolerant quantum computing
PhD proposal in energetic cost of fault-tolerant quantum computing Application deadline: Sunday, July 26, 2026Employer web page: https://recrutement.inria.fr/public/classic/en/offres/2026-10236Job type: PhDTags: #PhD #quantum computing #energy #fault-tolerance #quantum error-correction #power #energetics #noise #correlated-noise #scalability #theory #PhDThe MOCQUA team at the Loria laboratory in Nancy (France) is looking for a PhD student in quantum computing theory. More details about the offer and platform to apply is provided in the link The goal will be to analyze how the energy consumption of fault-tolerant quantum computers scales as a function of the size of quantum algorithms, in a regime where the computation is specifically optimized to minimize energy consumption rather than qubits or gates counts. The main objective will be to determine whether better energy scaling than that predicted by the quantum threshold theorems [1,2] can be achieved, following the approaches developed in [3,4]. In practice, the PhD student will mostly focus on fault-tolerant quantum computing theory, and interact with other researchers providing the hardware energetic and noise models. Because such models can introduce correlated noise, this project will indirectly help understanding how to better design fault-tolerant circuits to resist such noise. To design more resource-efficient and noise-resilient fault-tolerant circuits, the PhD might use tools from diagrammatic reasoning for quantum circuits currently developed in the group [5], as well as recent developments in fault-tolerant circuit transformations [6]. =============================================== This project will be supervised by Marco Fellous-Asiani (Starting faculty at INRIA Université de Lorraine; expert in energetics of fault-tolerant quantum computing [3,4]), Simon Perdrix (Research director at INRIA Université de Lorraine; expert in diagrammatic reasoning for quantum circuits [5]), and invo
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quantum-computingLocalized control of large ion crystals in a Penning trap using a spatial light modulator
--> Quantum Physics arXiv:2607.06654 (quant-ph) [Submitted on 7 Jul 2026] Title:Localized control of large ion crystals in a Penning trap using a spatial light modulator Authors:Allison L. Carter, Jennifer F. Lilieholm, Bryce B. Bullock, Kurt Thompson, Diep Nguyen, John J. Bollinger View a PDF of the paper titled Localized control of large ion crystals in a Penning trap using a spatial light modulator, by Allison L. Carter and 5 other authors View PDF HTML (experimental) Abstract:Penning ion traps as quantum platforms have primarily utilized global control and symmetric Dicke states for quantum simulation and sensing experiments. The introduction of local control greatly increases the power of the platform as a quantum simulator but is technically challenging due to the rapid rotation of the ion crystals. Here we use an ultraviolet-compatible spatial light modulator (SLM) to imprint programmable AC Stark shift patterns with different azimuthal symmetries and gradients that co-rotate with the ion crystals, demonstrating localized coherent control of single plane crystals with greater than 100 ions. Comparisons of the measured ion qubit populations with calculations from independent measurements of the applied AC Stark shift patterns show good agreement, validating the technique and providing a path, with a higher format SLM, for parallelizable, coherent individual ion addressing in Penning traps. Comments: Subjects: Quantum Physics (quant-ph); Atomic Physics (physics.atom-ph) Cite as: arXiv:2607.06654 [quant-ph] (or arXiv:2607.06654v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2607.06654 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Allison Carter [view email] [v1] Tue, 7 Jul 2026 17:43:03 UTC (5,481 KB) Full-text links: Access Paper: View a PDF of the paper titled Localized control of large ion crystals in a Penning trap using a spatial light modulator, by Allison L. Carter and 5 othe
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quantum-computingLocalized Thermometry via Dayem Bridges Integrated on Superconducting Qubit Chips
--> Quantum Physics arXiv:2607.06670 (quant-ph) [Submitted on 7 Jul 2026] Title:Localized Thermometry via Dayem Bridges Integrated on Superconducting Qubit Chips Authors:Ella O. Lachman, Dave P. Pappas, Jayss Marshall, Josh Y. Mutus View a PDF of the paper titled Localized Thermometry via Dayem Bridges Integrated on Superconducting Qubit Chips, by Ella O. Lachman and 3 other authors View PDF HTML (experimental) Abstract:Accurate knowledge of the on-chip temperature is essential for understanding and optimizing the performance of superconducting qubits, yet direct thermometry at millikelvin temperatures remains challenging. While qubits themselves are sensitive to the temperature of their environment, other factors may affect the qubits` effective temperature, and using them as thermometers with any accuracy requires specialized measurement protocols and qubit designs, limiting their practicality for routine diagnostics and adding complex infrastructure to any hardware testing apparatus. Here we demonstrate a complementary on-chip thermometry method based on superconducting Dayem bridges that are integrated on the same chip as transmon qubits. By extracting the critical current of the Dayem bridge from I-V measurements, we obtain a local, quantitative measure of the chip temperature without the need for microwave calibration or qubit-specific control sequences. To demonstrate the utility of the Dayem bridges as thermometers, we fabricate them in-situ with qubits on the same chip, calibrate the Dayem bridge critical current as a function of temperature, and characterize its resolution and stability at cryogenic temperatures. We additionally perform simultaneous measurements of the Dayem bridge thermometer and qubit excited-state population, and show agreement over the relevant temperature range, validating the method against established qubit thermometry. Furthermore, we correlate the independently measured chip temperature with qubit energy relaxation and dephasing t
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quantum-computingSpin singlets are useful
--> Quantum Physics arXiv:2607.06672 (quant-ph) [Submitted on 7 Jul 2026] Title:Spin singlets are useful Authors:Silas Hoffman, Edward H. Chen, Matthew Brooks, Stephen Carr, Daniel Volya, Alan Tran, Tyler Keating, Thaddeus D. Ladd, Charles Tahan View a PDF of the paper titled Spin singlets are useful, by Silas Hoffman and 8 other authors View PDF HTML (experimental) Abstract:We evaluate the utility of the spin-zero manifold of an exchange-coupled array of $N$ spins for tasks in quantum computation and quantum simulation. Since pairs of electrons can be readily initialized into a product state of singlets in semiconducting quantum dot arrays, the full spin-zero manifold is available with exchange-only control, providing a Hilbert space of approximate dimension $2^N/(N/2)^{3/2}$, asymptotically close to the $2^N$ dimension of the full spin Hilbert space. Leveraging the spin-zero manifold enables larger computational space in a given array compared to traditional exchange-only control, in which spin arrays are organized into modular units of $n$ spins comprising $N/n$ encoded qubits, limiting to the exponentially smaller Hilbert dimension $2^{N/n}$. Here we focus on benchmarking metrics for this resource utilization by generalizing cross-entropy benchmarking, mirror benchmarking, and out-of-time-ordered correlators to this system. We show that operating in the spin-zero manifold can accelerate the realization of computational quantum advantage applications in semiconductor-based spin qubits. Comments: Subjects: Quantum Physics (quant-ph); Mesoscale and Nanoscale Physics (cond-mat.mes-hall) Cite as: arXiv:2607.06672 [quant-ph] (or arXiv:2607.06672v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2607.06672 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Silas Hoffman [view email] [v1] Tue, 7 Jul 2026 18:00:04 UTC (206 KB) Full-text links: Access Paper: View a PDF of the paper titled Spin single
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quantum-computingSpectral Born machines: classically trainable quantum generative models for discrete data
--> Quantum Physics arXiv:2607.06675 (quant-ph) [Submitted on 7 Jul 2026] Title:Spectral Born machines: classically trainable quantum generative models for discrete data Authors:Austin Huang, William Maxwell, Vasilis Belis, Evan Peters, Jason Pye, Soran Jahangiri, Joseph Bowles View a PDF of the paper titled Spectral Born machines: classically trainable quantum generative models for discrete data, by Austin Huang and 6 other authors View PDF HTML (experimental) Abstract:We present \emph{spectral Born machines}, a class of quantum generative models that results from viewing and generalizing the class of IQP Born machines through the lens of group Fourier analysis. These quantum models exploit the quantum Fourier transform to create an inductive bias that make them naturally suited to learning integer-structured data, while remaining classically hard to sample from in general. Similar to IQP Born machines, spectral Born machines can be trained efficiently at scale on classical hardware via a maximum mean discrepancy loss based on graph spectral analysis, which we make available in a new \emph{tcdq} module of the PennyLane software platform. In numerical experiments, we show how the spectral bias of the model leads to significantly reduced parameter counts compared to unstructured approaches, and demonstrate the scalability of the software by training a 190-qubit model with over 1 million parameters to successfully learn a distribution of 93 nucleotide-long ribosomal RNA. Our results suggest that highly over-parameterized spectral Born machines may be immune to overfitting, even in strongly data-scarce regimes. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2607.06675 [quant-ph] (or arXiv:2607.06675v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2607.06675 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Joseph Bowles [view email] [v1] Tue, 7 Jul 2026 18:00:17 UTC (1,839 KB) Full-text li
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