Solve complex materials-science problems with the new Fire Opal quantum-dynamics simulator Quantum computers allow us to directly model the quantum mechanical interactions that govern chemistry and materials, unlike classical simulators, which are forced to rely on approximations that lose precision as the problem grows in complexity. As a result, research scientists are embracing quantum computers as powerful new tools with the potential to accelerate the development of high-performance electric vehicle batteries and energy-efficient industrial catalysts, while opening access to new regimes of energy transfer and materials science that the community has not been able to explore before. This opportunity is impeded by the reality that quantum computers face a real bottleneck—errors which accumulate and cause algorithms to fail. This is an incredibly significant challenge that has placed a limit on how useful quantum computers could be—and it’s exactly what Q-CTRL solves. Delivering on our mission to make quantum technology useful, we recently broke through this barrier thanks to our performance-management software, Fire Opal. In a breakthrough demonstration on the IBM Quantum Platform, Q-CTRL achieved practical quantum advantage in quantum computing, solving a real problem in materials discovery 3,000x faster than the best available alternative classical software. With this demonstration, we have the first real evidence that quantum computers can be used to solve a real problem and deliver a better outcome than the existing conventional alternatives. Learn more about the details in the technical manuscript (updated July 2026) and our technical blog. Roughly one-third of all global supercomputer time is currently consumed by chemistry and materials science simulations. From designing room-temperature superconductors to uncovering carbon-neutral materials, the energy and industrial sectors face massive classical computational bottlenecks. And now quantum computers can help! The challenge Most quantum-dynamics simulations involve understanding how an interacting collection of particles like electrons evolve in time
Jul 20, 2026 · via q-ctrl.com
A new cryptographic breakthrough is reshaping the debate over Bitcoin’s future in the age of quantum computing by offering a potential way to recover some vulnerable coins without exposing private keys. The discussion gained momentum after Binance co-founder Changpeng Zhao (CZ) suggested that Bitcoin’s community could freeze Satoshi Nakamoto’s coins if quantum computers became capable of breaking Bitcoin’s cryptography. The proposal sparked criticism, with opponents arguing that permanently freezing coins would amount to confiscation. The concept already exists in Bitcoin Improvement Proposal (BIP) 361, co-authored by Casa co-founder Jameson Lopp. The proposal would gradually phase out Bitcoin’s legacy signature system, permanently freezing coins that never move. However, critics have long pointed out that such a solution leaves legitimate owners with no way to reclaim their assets. Project Eleven’s newly unveiled proof-of-ownership system aims to solve that problem. Instead of relying on vulnerable private keys, it allows users to prove ownership through the master key generated by modern BIP-32 seed phrases without revealing sensitive information. While quantum computers could eventually derive a private key from an exposed public key, they cannot reverse the one-way process used to generate the master key, making it a secure form of verification. The idea, first introduced by researchers Or Sattath and Shai Wyborski in 2023 as “signature lifting,” has advanced significantly. Lightning Labs CTO Olaoluwa Osuntokun created the first prototype, while Project Eleven’s latest version reportedly completes the verification process in just 243 milliseconds—around 16 times faster than earlier implementations. Despite its promise, the technology has major limitations. It only works with wallets built on the BIP-32 seed phrase standard introduced in 2012. Bitcoin wallets created before then, including those believed to belong to Satoshi Nakamoto, lack a master key and therefore cannot use the recovery method. Research by Sergio Demian Lerner estimates that roughly
Jul 20, 2026 · via tokenpost.com
Optimization problems are everywhere. Whether scheduling deliveries, managing financial portfolios, or analyzing medical images, countless industries rely on the ability to find the best possible solution from an astronomically large number of options. Quantum annealers—a commercially available type of quantum computer made by D-Wave Systems—are purpose-built to tackle exactly these kinds of challenges. But a stubborn obstacle has stood in the way of their broad adoption: qubit errors. When a quantum annealer runs a computation, a small fraction of its quantum bits, or qubits, can collapse into incorrect states. This might sound like a minor inconvenience, but the consequences compound rapidly. The probability of obtaining a correct answer decreases exponentially with the number of qubit errors, meaning that, as problems grow in size, the time required to reach the true optimal solution balloons just as quickly. For large, real-world problems, this makes unassisted quantum annealing—where the machine runs without any error correction or post-processing—impractical. Researchers at CSIRO (Australia’s national science agency) have now developed a technique that cuts through this bottleneck. Their method, called SEMO (spin-error mitigation for optimization), is a post-processing algorithm that identifies and corrects the erroneous spin states left behind after quantum annealing. The work, published in Advanced Physics Research, demonstrates a million-fold improvement in the time required to reach the globally optimal solution for a combinatorial optimization problem. Catching errors after the fact Unlike quantum error correction (QEC), which attempts to protect qubits during computation by encoding each logical qubit across many physical qubits, SEMO operates after the quantum computation is complete. This distinction matters enormously in practice: QEC dramatically reduces the effective number of usable qubits in a system—a significant drawback when quantum hardware already has a limited qubit count. SEMO avoids this penalty entirely by working on the classical post-processing side. The core insight
Jul 20, 2026 · via advancedsciencenews.com
National computing grid to become 'public utility' By Cheng Yu | China Daily | Updated: 2026-07-20 10:06 China has launched a massive, decades-long initiative to unify its domestic computing resources into a single national grid. The goal, unveiled by officials and engineers at the 2026 World Artificial Intelligence Conference in Shanghai on Friday, is to treat processing power as a basic public utility — allowing users to access AI computing as seamlessly as flipping a light switch. According to the National Data Administration, China's intelligent computing capacity surged to 1,882 EFLOPS by the end of March this year, powered by 14.45 million standard server racks. An EFLOP, or exa floating-point operation per second, is a standard measure of computing performance equal to one quintillion calculations per second. To maximize this sprawling footprint, China is deploying a three-stage roadmap designed to strengthen self-reliance, optimizing local networks while funding frontier tech like quantum technology and orbital satellite clusters. Gao Wen, director of Peng Cheng Laboratory and an academician at the Chinese Academy of Engineering, outlined the roadmap at the conference. "The first stage focuses on pooling computing resources nationwide and about 70 percent of that work has already been completed. It means that roughly seven-tenths of China's computing resources have been incorporated into a unified database that is updated in real time," he said. "In the second phase over the next five years, the network is expected to begin coordinating computing tasks among selected participants, initially within companies or between cooperating firms rather than serving the public." He added that the third and final phase would allow computing tasks to move seamlessly across multiple providers without users knowing where the work is being processed. "Achieving that vision could take one or two decades rather than just a few years. But the final
Jul 20, 2026 · via global.chinadaily.com.cn
Andrew Chi-Chih Yao × Gilles Brassard: Two Turing Award Winners Look Back on the Quantum Magic Moment On July 18, at the "Science of Intelligence in the Physical World" themed forum of the 2026 World Artificial Intelligence Conference (WAIC 2026), Prof. Andrew Chi-Chih Yao, 2000 Turing Award laureate and academician of the Chinese Academy of Sciences, engaged in a dialogue with Prof. Gilles Brassard, the 2025 Turing Award laureate. Starting from their respective quantum "magic moments", Yao and Brassard conducted in-depth discussions on how quantum mechanics can infuse new computational paradigms and theoretical depth into artificial intelligence. This marks the second consecutive year that Yao has held a peak dialogue with a Turing Award laureate on the WAIC stage, following his conversation with Geoffrey Hinton last year. In recent years, Yao has continuously promoted the forward-looking layout of quantum artificial intelligence, advocating that "although quantum artificial intelligence is in its initial stage, it is scientifically rich and a direction worthy of promotion". This echoes the research field that Brassard has long dedicated himself to. In 1984, the quantum key distribution method proposed by Brassard and Charles Bennett pioneered the entirely new field of quantum information science. Over the past four decades, quantum information science has continuously expanded its boundaries. From quantum cryptography to quantum computing, and then to quantum artificial intelligence, quantum mechanics is no longer merely a set of theoretical foundations, but has gradually been transformed into a new way of information processing. When classical computing is constrained by the bottlenecks of computing power, energy consumption and data, the parallelism, superposition and entanglement characteristics represented by quantum computing are regarded as a "constant source of vitality" that brings new underlying capabilities to AI. Yao proposed that whether and how quantum information science can bring new computational paradigms to AI
Jul 20, 2026 · via eu.36kr.com
On July 19, 2026, the cryptocurrency world found itself at a crossroads that could redefine the very soul of Bitcoin. A new white paper released by Google’s quantum AI team, in collaboration with researchers from the Ethereum Foundation and Stanford University, has sent shockwaves through the community by warning that quantum computers may be able to break Bitcoin’s cryptographic defenses much sooner than previously believed. For an asset that has prided itself on being censorship-resistant and decentralized since its inception in 2009 by the enigmatic Satoshi Nakamoto, this revelation could not have come at a more precarious time. According to Climatepol, the Google team’s findings have drastically shortened the timeline for a quantum attack—often called Q-Day—by more than twentyfold. Where experts once assumed it would take at least several decades and some 20 million physical qubits to crack Bitcoin’s ECDSA-256 encryption, the new research shows that fewer than 500,000 qubits may suffice. As Google’s lead quantum AI researcher bluntly put it in a recent interview, “The future we predicted is already happening. With advances in quantum error correction and qubit control, blockchain signature algorithms are now extremely vulnerable.” The immediate risk is staggering. Roughly 7 million Bitcoins—worth about $440 billion—are exposed to quantum hacking, including wallets attributed to Satoshi Nakamoto and millions of so-called ‘sleeping wallets’ whose public keys have been revealed. Many of these coins are considered lost or abandoned, as their owners have either misplaced their private keys or, like Satoshi, vanished from the public eye. Even if Bitcoin’s protocol is upgraded to quantum-resistant cryptography, these assets cannot be moved to safer wallets without their owners’ intervention. The specter haunting the Bitcoin ecosystem is clear: Should a quantum-equipped adversary unlock Satoshi’s wallets and dump 7 million Bitcoins onto the market, the resulting hyperinflation and catastrophic collapse of value
Jul 19, 2026 · via evrimagaci.org
Caution warranted over tech threat, investors’ AI exuberance Hong Kong and mainland China have the expertise to prepare for an AI market downturn and the security threat of quantum computers Stock indexes have repeatedly hit new highs despite the ebbs and flows of the AI trade. In China, tech stocks have driven a bull run but consumer stocks lag behind. The Star Market 50 Index, a technology-focused board, jumped more than 50 per cent this year. In contrast, the CSI 300 Index, the benchmark that tracks the largest listed firms on the Shanghai and Shenzhen exchanges, is about 10 per cent below its peak from 2021. Yue is right to caution against investors’ obsession with AI. After all, when an investment bubble bursts, panic inevitably sets in. With external threats such as geopolitical tensions and global inflation compounding existing market risks, the road ahead could become very scary. After all, the current valuations of many tech and AI stocks in China and the United States – the two countries competing for tech dominance – are based more on faith than actual profits. Yue said local banks must prepare adequate capital buffers to protect against a potential AI market downturn. Fortunately, the city’s banking system has always maintained a resilient financial cushion to absorb macroeconomic shocks. Meanwhile, AI and quantum computers have become so powerful that, if they fall into the wrong hands, they could pose a serious threat to financial systems and their data protection. This will be a steep learning curve. The most experienced bankers, regulators, security experts and tech executives must work together to pre-empt such threats. Fortunately, Hong Kong and mainland China do not lack such professionals. It’s a matter of getting the best people together to advance and safeguard the new tech.
Jul 19, 2026 · via scmp.com
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Jul 19, 2026 · via youtube.com
On Saturday morning in Shanghai, a startup that did not exist a year ago walked onto the floor of the World Artificial Intelligence Conference and showed a quantum computer built to slide into an ordinary server rack — no dilution refrigerator, no vibration isolation table, no dedicated quantum facility required. Zhongqi Wuliang (众擎无量), a spinoff from the Chinese Academy of Sciences' Shanghai Institute of Optics and Fine Mechanics, unveiled the Qinghe No. 1 (清河一号) at WAIC 2026, pitching it as the first neutral atom quantum computer engineered specifically for direct data-center deployment in a Pandaily report on the WAIC debut. Whether or not that specific "first" claim stands up — and at least one predecessor system, the Hanyuan-1, came close — the direction the claim points to is real. A pattern has emerged in China's neutral atom quantum computing sector: successive generations of hardware are getting closer to ordinary infrastructure with each release. Three generations in nine months, each physically smaller and thermally simpler than the last, is a cadence that no other national quantum program has matched. The announcement came on day two of WAIC 2026, a conference running July 17–20 at the Shanghai World Expo Exhibition and Convention Center under the theme "AI Partnership for a Brighter Future." The conference has become China's primary showcase for frontier technology announcements, and this year's edition drew over 1,100 exhibitors — more than 300 of them making global product debuts. Why Removing the Refrigerator Changes Everything The engineering barrier that has kept quantum hardware in laboratories for three decades is not primarily about qubits. It is about what surrounds them. Superconducting quantum computers — the dominant commercial architecture used by IBM, Google, and most Western players — require dilution refrigerators to cool their circuits to roughly 15 millikelvin, colder than interstellar
Jul 19, 2026 · via techtimes.com
Artificial intelligence is the latest rage, but quantum mechanics has been around for more than 100 years. Ever since Heisenberg postulated with his matrix, and the wave-particle nature of light that you can’t know position or probability at the same time, we found out that the act of observation actually changes everything. Einstein famously countered with his thought that God does not play dice with the universe. He was relatively wrong. This was another great breakthrough in how we see the universe. Energy and very little matter are not continuous but occurred in interval bursts called quanta. Hence the name. Electrons jump from different, discrete, orbital clouds, giving off signature radiation of both particles and waves that were not predictable or observable. We live our lives in personal quantum intervals, performing in bursts and resting when tired. We rest the uphill ski and leg as we shred, walk, run or cycle. Sisters and sorority girls cycle at the same time. We appreciate the pause in music and the negative space in art. Rivers run in alternating rapid-pool sequences, and waves in the ocean come in on 8-13 second intervals. Water morphs differently when observed. Quantum extrapolations predicted alternative universes with folds in the fabric of the space-time continuum and begged for new mathematics beyond Newtonian calculus to solve for the practical results we desperately wanted. And so we applied it to lasers, transistors and quantum computers, turning the black and white, binary digital world into a technicolor quantum world where we are gods. How cool is that? Quantum computers are not binary but use quantum particles called qubits and photons to solve for an infinite range of solutions almost instantaneously. This may be a great assistance to AI and crypto mining in sensing new phenomena and performing critical matrix operations
Jul 19, 2026 · via parkrecord.com
Russia’s quantum computing effort is organised around a national Quantum Computing Roadmap that the Rosatom state corporation has coordinated since 2020. Rosatom reported total roadmap funding of roughly 24 billion rubles across 2020 to 2024, of which about half came from Rosatom itself, and the programme funds four hardware platforms in parallel: trapped ions, neutral atoms, superconducting circuits, and photonics. This guide profiles the main organisations in that ecosystem, from the Russian Quantum Center at Skolkovo and the Rosatom-coordinated roadmap through the commercial vendors QRate, Scontel, and QApp, the in-house quantum work at Sberbank, and the academic anchors at Lomonosov Moscow State University, the Lebedev Physical Institute, and ITMO University in St Petersburg. Why Russia runs a state-coordinated quantum programme Russia has built one of the larger national quantum-computing programmes outside the United States, China, and the European Union. The work runs under a national Quantum Computing Roadmap that the Rosatom state corporation has coordinated since 2020, and Rosatom reported total roadmap funding of about 24 billion rubles across 2020 to 2024, with roughly half coming from Rosatom itself. Rather than concentrate on one qubit technology, the roadmap funds four hardware platforms at once, and much of the primary research sits with the Russian Quantum Center and its academic partners. In 2024 the programme delivered two 50-qubit prototypes. In September 2024 Rosatom announced a 50-qubit ion-based machine built in a laboratory run jointly by the Russian Quantum Center and the Lebedev Physical Institute, and in December 2024 Lomonosov Moscow State University and the Russian Quantum Center presented Russia’s first 50-qubit prototype based on single neutral rubidium atoms held in optical tweezers. Russian teams had reached a 20-qubit system earlier in 2024, so the move to 50 qubits came ahead of the original roadmap schedule. Published fidelity and coherence figures remain
Jul 18, 2026 · via quantumzeitgeist.com
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Jul 18, 2026 · via instagram.com
When consumer sentiment, inflation signals and housing affordability are all moving in different directions, it can be hard to know which stocks deserve your attention. One approach is to focus on founder led companies where the leaders are deeply tied to the long term outcome of the business. This Founder Led Companies screener does exactly that, filtering for management teams with skin in the game at a time when global growth, energy prices and capital flows are all under close watch. Below, you will see 3 stocks surfaced by this screener. Aritzia (TSX:ATZ) Overview: Aritzia is a Vancouver based fashion retailer that designs and sells a wide range of women’s apparel, activewear and accessories through its own boutiques and online channels across Canada and the United States. Operations: Aritzia generates about CA$4.0b in revenue, primarily from apparel, with around CA$2.5b coming from the United States and CA$1.5b from Canada. Market Cap: CA$16.4b Aritzia provides exposure to a founder led retailer that is scaling in the U.S. while remaining focused on womenswear and a growing digital channel. Recent earnings growth, higher margins and analyst support for further expansion sit alongside a premium P/E, significant use of external funding and recent insider selling, which raise questions about how much optimism is already reflected in the price. For investors, the key consideration is whether the combination of boutique growth, new distribution capacity and higher online engagement can continue to justify that premium without putting pressure on the balance sheet or returns. Aritzia’s premium P/E, recent earnings growth and heavy external funding point to a story that could either accelerate or stall. The real clue sits inside the 4 key rewards and 1 important warning sign Xanadu Quantum Technologies (TSX:XNDU) Overview: Xanadu Quantum Technologies is a Toronto based company that builds photonic quantum computers
Jul 18, 2026 · via simplywall.st
Singapore’s pQCee Raises $3.9M for Post-Quantum Security
pQCee raises $3.9M for post-quantum security.
Singapore-based startup pQCee has closed a $3.9 million seed round led by SGInnovate and Lotus One Investment. The company develops “crypto-agile” solutions—software that allows encryption algorithms to be changed via a cloud patch without hardware replacement. Its products protect against “collect now, decrypt later” attacks, where encrypted data is stored until powerful quantum computers become available. The funds will be used to expand the team and enter the US, European, and Middle Eastern markets; the project has raised a total of $6.7 million.
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Jul 18, 2026 · via forklog.com
Every TLS handshake and every SSH login on the internet today relies on math that a large enough quantum computer could eventually break. That is not a hypothetical for security teams anymore. The National Institute of Standards and Technology finalized its first three post-quantum cryptography standards on August 13, 2024, and the tooling needed to actually deploy them, OpenSSL 3’s provider architecture, the Open Quantum Safe project’s liboqs library, and hybrid key exchange in OpenSSH, has matured enough for production use in 2026. This tutorial walks through a full PQC migration on a real Ubuntu 24.04 server: building the software, generating quantum-safe keys, standing up a hybrid TLS-terminating NGINX proxy, hardening OpenSSH, and verifying every handshake actually negotiates the new algorithms instead of quietly falling back to RSA. By the end you will have a working reverse-proxy stack that speaks both classical and post-quantum cryptography at once, plus the troubleshooting knowledge to fix the handshake failures and build errors that trip up almost everyone on their first attempt. Canadian IT teams have extra reason to move now: the Government of Canada introduced Level 1 of the Canadian Program for Cyber Security Certification in April 2026, and while it does not yet mandate post-quantum algorithms specifically, it signals the direction federal contractors are being pushed. Getting comfortable with PQC before it is contractually required beats scrambling after the fact. This is a hands-on companion to the broader cybersecurity coverage on this site. If you have already hardened your perimeter with an IDS, a SIEM, or a secrets manager, post-quantum cryptography is the next layer down the stack: it protects the actual key exchange and signatures underneath everything else you have built. Don't miss new tech stories on Google Add Tech Insider once in the Google app and our stories appear in
Jul 18, 2026 · via tech-insider.org
The 126th meeting of the Internet Engineering Task Force — the volunteer-driven body whose output shapes every protocol the modern internet runs on — opened Saturday in Vienna and runs through July 24. The Hackathon and Code Sprint are underway this weekend. Full working group sessions begin Monday and continue through Friday afternoon. For engineers who architect multi-agent systems, the most consequential two hours of the week happen Thursday morning. That is when a Birds-of-a-Feather session called agentproto convenes to address a problem that has been building for the past eighteen months: five competing AI agent protocols — Anthropic's Model Context Protocol, Google's Agent2Agent, the Agent Communication Protocol, the Agent Network Protocol, and Cisco's Agntcy Framework — have each staked out overlapping territory without any of them clearing the one bar that makes a protocol truly interoperable across organizational boundaries. That bar is an IETF RFC. The agentproto session is not a product announcement or a panel discussion. It is the formal mechanism by which the IETF decides whether to charter a Working Group. If it does, the resulting standard — likely an RFC two to three years out — would establish the protocol baseline that every vendor shipping inter-domain AI agent infrastructure would eventually need to implement. If the session reveals too much disagreement to proceed, the community returns to the mailing list and the current landscape of competing proprietary-ish standards continues. The IETF has published a full overview of the five scheduled BoFs. This is the decision the Vint Cerf warning pointed toward. Six days before IETF 126 opened, TechTimes published Cerf's retirement argument: that AI agent systems running at machine speed cannot tolerate the semantic ambiguity of natural-language inter-agent communication, and that the industry will be forced — as it was in 1974 — toward formal, unambiguous
Jul 18, 2026 · via techtimes.com
Sixteen years ago, Satoshi Nakamoto answered a doubter on a forum in 2010, and the reply still guides how the network defends its money today. Satoshi Nakamoto Predicted Bitcoin's Hash Defense 16 Years Before Quantum Fears Key Takeaways - Satoshi Nakamoto defended SHA-256 in a July 16, 2010 Bitcointalk forum post. - Google Quantum AI cut its 2026 estimate for breaking Bitcoin’s curve to 500,000 qubits. - Developers have proposed BIP-360 and other ideas in 2026 to prepare quantum-resistant addresses. A Forum Post That Set the Rules On July 16, 2010, a user named bdonlan questioned Bitcoin’s double SHA-256 hashing on the Bitcointalk forum. He asked whether the design weakened security. Satoshi answered directly. Bitcoin’s inventor compared SHA-256 to the jump from 32-bit to 64-bit computing, not a small step up in bit length. Computers ran out of 32-bit address space at 4 gigabytes, he said, but nobody expects to run out of 64-bit space anytime soon. SHA-256 works the same way, and the math gives Bitcoin room to spare. Satoshi also gave the network an exit plan. If SHA-256 ever weakened, developers could soft fork to a new hash function at a set block height. Old and new hashes would run side by side until every node upgraded. Bitcoin’s market capitalization has since grown past a trillion, and the network settles hundreds of billions of dollars in value daily. Every dollar of that activity still depends on the hash function Satoshi defended in a single forum reply sixteen years ago. Why Bitcoin Runs Two Hashes Instead of One Bitcoin’s code hashes data twice: SHA256(SHA256(data)), a method developers call SHA256d. Cryptographers Niels Ferguson and Bruce Schneier recommended the approach to block length extension attacks, a flaw in the Merkle-Damgard structure SHA-2 uses. Miners hash block headers twice to meet the
Jul 18, 2026 · via news.bitcoin.com
Graduate student Seyoon Ragavan led the work alongside senior author Vinod Vaikuntanathan, a computer science professor at MIT. The team published their paper through the IACR Cryptology ePrint Archive and presented it at the CRYPTO 2024 conference. The shadow of Shor’s algorithm The discovery builds directly on Shor’s algorithm, which MIT mathematician Peter Shor introduced three decades ago. Shor proved that a powerful enough quantum computer could crack massive security numbers faster than any regular computer. That finding posed a threat to RSA encryption, the security system developed at MIT in the 1970s. RSA still protects most internet traffic today because a standard computer would need millions of years to guess the secret keys. Why modern encryption is still safe No quantum computer today is powerful enough to actually run Shor’s algorithm for code-breaking. Experts estimate it would take 20 million quantum processing units, called qubits, to do it. The biggest quantum computers built so far have just over 1,100 qubits. Because of this hardware shortfall, modern encryption remains safe for now. In 2023, New York University computer scientist Oded Regev broke that streak. He found a way to cut down the number of steps the computer needs to take, marking the first big improvement since 1994. While Regev’s version was faster, it required a massive amount of quantum memory. Vaikuntanathan heard Regev present his work at a workshop, where Regev ended his talk with a challenge to the room: find a way to shrink that memory problem down. Ragavan and Vaikuntanathan decided to take on the challenge. A Fibonacci shortcut The new MIT system matches Regev’s fast speed but uses a fraction of the qubits, bringing the memory needs back down to Shor’s original levels. Crucially, the new method is also much better at handling the background noise that
Jul 18, 2026 · via futura-sciences.com
What Are qLDPC Codes? The surface code won the first decade of quantum error correction. A sparser, stranger family of codes is now promising the same protection for a tenth of the hardware, and the industry’s biggest roadmap is built on it. The easiest way to understand qLDPC codes is to start with the letters. LDPC stands for low-density parity check, and the low density is the whole idea: every error check touches only a handful of qubits, and every qubit is watched by only a handful of checks, no matter how large the code grows. That sparseness keeps the checking circuitry shallow and the error rate of the checks themselves under control, which is what makes the family practical at all. The reason qLDPC codes have moved from a theorists’ curiosity to the centrepiece of IBM’s fault-tolerance roadmap is arithmetic rather than elegance. The reigning champion of quantum error correction, the surface code, spends thousands of physical qubits to protect a dozen logical ones, and that overhead is the single largest line item in every plan for a useful machine. The best qLDPC codes buy the same protection roughly ten times more cheaply, and when every qubit is an engineering project in its own right, a tenfold saving reshapes what a useful machine costs to build. This guide walks through what the codes are, where they came from, what IBM’s celebrated gross code actually claims, which machines have now run qLDPC codes for real, and the two honest catches, wiring and logic, that decide whether the family takes over. It completes our error-correction series alongside the surface code guide. What qLDPC actually means qLDPC codes are quantum error correction codes that keep every parity check small and every qubit lightly monitored, which lets one block protect many logical qubits
Jul 18, 2026 · via quantumzeitgeist.com
Researchers from the Institute of Mathematical Sciences, QCAR Group, and Pecslab Research in Chennai, India have demonstrated that fermion-to-qubit encodings reveal inherent geometric structures beyond simply replicating energy levels. The work led by Lakshya Nagpal, Nishith Reen, and S. R. Hassan, introduces a framework based on weighted hypergraphs and coupling-space representations built from the Bravyi-Kitaev (BK) and Xia, Bian, Kais (XBK) encodings. Within the BK representation, the team uncovered an exact spectral organization originating from the binary-tree architecture of the encoding, suggesting these encodings impose structure rather than merely translate it. A newly defined geometric observable precisely correlates with interaction strength, allowing quantification of connections between kinetic and interaction hypergraphs. The results establish hypergraph geometry as a new means of understanding these encodings, revealing they function as geometric representations of quantum many-body Hamiltonians. The pursuit of robust quantum computation increasingly relies on translating complex fermionic systems into manageable qubit representations, yet recent work suggests these encodings are far from neutral algorithmic tools. This shifts the focus from the quantum state itself to the structure of the encoding. Applications to models including the Hubbard, spinless-Fermi, and Kitaev models demonstrate that these connectivity- and transport-based geometric descriptions consistently capture structural evolution across diverse many-body systems. The ability to accurately map complex quantum systems onto the architecture of a quantum computer hinges on the fidelity of fermion-to-qubit encodings, but recent work from researchers at the Institute of Mathematical Sciences, QCAR Group, and Pecslab Research in Chennai, India, reveals these encodings possess an inherent geometric structure extending beyond mere computational utility. Researchers are now demonstrating that the Bravyi-Kitaev (BK) encoding isn’t simply a translation tool, but actively structures the quantum system it represents. The team introduces a newly defined geometric observable whose interaction dependence follows a closed analytical form, allowing for quantification of how
Jul 18, 2026 · via quantumzeitgeist.com