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Quantum Computers
Sorbonne Team's <b>Quantum</b> Reservoir Learns Complex Data Without Training
Researchers at the Kastler Brossel Laboratory (LKB) in Paris have constructed a quantum computer capable of learning complex data without relying on traditional, extensive training methods; instead, the system adjusts only its output layer, a simplification in machine learning protocols. This quantum photonic reservoir computer, equipped with a novel “fading memory” achieved through feedback mechanisms, processes information using entangled light and operates at room temperature. The team, funded by the ERC COQCOoN project and the PEPR OQuLus programme, is exploring applications for forecasting notoriously difficult-to-predict systems. “Reservoir computing” harnesses the natural dynamics of a complex physical system, without training the entire system, enabling machine learning that utilizes the resources of quantum physics. Entangled Quantum Light Enables Reservoir Computing This system, detailed in a recent publication in Nature Photonics, relies on a “reservoir” of entangled light to process information, adjusting only the output layer for learning, a simplification of the typical training process. The experimental protocol was developed by Valentina Parigi’s research team at LKB as part of the ERC COQCOoN project (Continuous Variable Quantum Complex Networks), with support from the PEPR OQuLus programme (Light-based quantum computers in discrete and continuous variables). Unlike algorithms that require exhaustive training, this approach focuses on adapting only the final output stage, reducing computational demands. In this instance, the reservoir is comprised of a multimode quantum state of light, where multiple frequency bands are interconnected through entanglement; researchers utilize a light beam interacting within a non-linear material to create a system capable of information processing. Beyond the fundamental advancement in quantum machine learning, the team is already exploring practical applications for this technology, specifically in forecasting complex time series data. More advanced versions of reservoir computing are being considered for climate and financial market forecasting, highlighting the potential to tackle real-world challenges that demand accurate
<b>Quantum</b> technology: How China wants to dominate the technology of the future
Quantum technology: How China wants to dominate the technology of the future With billions in funding under its new five-year plan, China wants to secure a leading global position in the quantum realm. Military applications are a major force driving the research. AL 12. April 2026 12. April 2026 Last updated: 12. April 2026 Share article:
<b>Quantum computers</b> are coming to break our codes faster than anyone expected
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Israel's 10D bets on physical AI and deep tech as its next frontier
When Mentee Robotics announced a significant funding round last year, it drew attention not just for the dollar amount, but for the milestone it represented: a Tel Aviv-based company building humanoid robots had moved from a research-stage concept to a company that had reached significant institutional scale. For 10D, who led their series A, the recent acquisition of Mentee Robotics confirmed a thesis the firm had been building for years: that the next wave of transformational technology would come from companies sitting at the intersection of deep engineering and artificial intelligence. 10D was founded in 2019 and operates as an early-stage fund focused exclusively on Israeli entrepreneurs, investing from pre-seed through Series A. Its portfolio spans robotics, quantum computing, cybersecurity, health technology, defense, and generative AI infrastructure, though the firm describes itself as a generalist investor with dynamic, evolving themes. Before 10D became one of Israel’s most closely watched early-stage funds, it was built by investors who had already helped shape some of the country’s biggest tech success stories. At the center of it is Yahal Zilka, a venture capitalist with more than two decades of experience in the Israeli tech ecosystem and a track record that includes multi-billion-dollar exits. Over the years, Zilka has been involved as an investor, advisor, and board member in companies such as Onavo (acquired by Facebook), CloudEndure (acquired by Amazon), AppsFlyer, Argus (acquired by Continental), Innoviz (which went public), and Aidoc, whose AI platform is used by hospitals across the U.S., Europe, and Asia. He is also widely associated with one of the defining success stories of Israeli tech: Waze. At a critical early stage, Zilka made a move that stood out even by today’s standards. Instead of supporting a $6 million seed round, he pushed to double it to $12 million—an unusually large
Scientists develop encryption to shield video from <b>quantum</b> attacks
A group of researchers has created a new security system to protect video data from future quantum threats, and it works on the computers people already use. Computer scientists say they have developed a new way to encrypt video data that can stand up to both today’s cyber threats and future quantum attacks. The research was published in the journal IEEE Transactions on Consumer Electronics in February 2025 and announced on March 2, 2026. Led by researchers at Florida International University (FIU), the team’s system uses a new way to secure and send video, focusing on a weakness in how regular encryption protects video files. Instead of encrypting a video as one big file, the new system breaks it into individual frames and scrambles each one with a different security key. The keys are random, so even if someone intercepts part of the video, they cannot read it without the right key for each frame. The method also fixes a problem unique to video files. Since videos are compressed, they often have repeating patterns that show up in many frames. Regular encryption can leave some of these patterns visible, which helps attackers try to break the code. The new system removes these patterns by making the encrypted data more random, a quality called "entropy." The more random the data, the harder it is to analyze. In tests, the team found their system worked about 10 to 15 percent better than other video encryption methods, mainly because it removed the patterns that attackers usually look for. A main advantage of the system is that it does not need special quantum hardware. It is made to run on regular computers, so it could be added to video conferencing, cloud storage, or surveillance platforms without needing to replace existing equipment. Many governments and
Rigetti's US$8.4m India Deal Extends <b>Quantum</b> Reach Beyond North America
- United States - / - Semiconductors - / - NasdaqCM:RGTI Rigetti’s US$8.4m India Deal Extends Quantum Reach Beyond North America - Rigetti Computing (NasdaqCM:RGTI) has secured an $8.4 million contract with India's Centre for Development of Advanced Computing. - The agreement marks a significant commercial engagement with a major Indian government research organization. - This contract follows the company’s recent launch of its Cepheus-1-108Q quantum computer. - The new deal expands Rigetti’s customer footprint beyond North America into a key international market. For investors tracking Rigetti Computing, the $8.4 million CDAC contract provides additional commercial context for a business often discussed mainly for its technology, including the Cepheus-1-108Q quantum computer. The new engagement highlights how Rigetti’s quantum systems and services are being adopted by a government backed research institution, which can matter for assessing real world appetite for its offerings. This type of international contract may help readers think about Rigetti’s potential customer base as more global rather than primarily North American. While it does not guarantee future deals, it introduces a reference point for how a sovereign client values access to the company’s quantum capabilities. Stay updated on the most important news stories for Rigetti Computing by adding it to your watchlist or portfolio. Alternatively, explore our Community to discover new perspectives on Rigetti Computing. We've flagged 4 risks for Rigetti Computing. See which could impact your investment. The CDAC contract gives investors a clearer link between Rigetti’s recent product launches and paying customers. Instead of Cepheus-1-108Q being used only through cloud access, CDAC is committing US$8.4 million to work directly with Rigetti’s quantum systems and services. For readers comparing Rigetti with peers such as IonQ and D-Wave Quantum, this helps show that governments outside North America are willing to fund projects on Rigetti’s hardware, not just run
LANL: Researchers Show Some <b>Quantum</b> Learning Models Are Classically Simulable
As proposed and demonstrated by the Los Alamos team, the architectures and techniques proposed to mitigate or altogether avoid barren plateaus in variational quantum computing make them classically simulable. Courtesy LANL LANL NEWS RELEASE Variational quantum computing is a hybrid quantum-classical approach that has emerged as one of the most promising applications for quantum devices. But this approach is hindered by the “barren plateau” phenomenon, which undermines the approach’s machine learning training capabilities. As a team of Los Alamos researchers suggest in a recent perspective piece in Nature Communications, and as they go on to demonstrate with a simulated quantum neural network, the architectures and techniques proposed to mitigate or altogether avoid barren plateaus make them classically simulable. “Barren plateaus typically result from what is known in the field as the ‘curse of dimensionality,’ where models need to navigate very big spaces, and finding the solution is like finding a needle in a haystack,” said Marco Cerezo, Los Alamos physicist and lead author on the perspective. “One avoids barren plateaus and circumvents the curse of dimensionality by restricting the model to a small subspace. But that solution might mean that the model can just as efficiently be simulated classically.” If the connection between the absence of barren plateaus (for example, by restricting models to small subspaces) and classical simulability holds, the remedy for barren plateaus may prove worse than the problem. The advantage quantum computers have in solving machine learning tasks faster than classical supercomputers would be limited only to those models with no barren plateaus. Subspaces and classical simulability Variational quantum computing’s hybrid approach aims to solve tasks by classically optimizing the parameters of a quantum circuit, thus extending the advantage of classical neural networks to the quantum realm. However, the too-large space of possible quantum states (i.e., “the
Are <b>Quantum Computers</b> A Threat To XRP Holders? Pundit Breaks Down The Possibilities
Sign Up for Our Newsletter! For updates and exclusive offers enter your email. Scott Matherson is a leading crypto writer at Bitcoinist, who possesses a sharp analytical mind and a deep understanding of the digital currency landscape. Scott has earned a reputation for delivering thought-provoking and well-researched articles that resonate with both newcomers and seasoned crypto enthusiasts. Outside of his writing, Scott is passionate about promoting crypto literacy and often works to educate the public on the potential of blockchain. This website uses cookies. By continuing to use this website you are giving consent to cookies being used. Visit our Privacy Center or Cookie Policy. I Agree Source: https://bitcoinist.com/quantum-computers-threat-xrp/
<b>Quantum Computers</b> Become More Realistic With Faster Simulation Of Noisy Circuits
Researchers at the University of New Mexico have developed a new algorithm accurately simulating the behaviour of noisy quantum computers. Shravan and colleagues present a polynomial-time classical algorithm capable of sampling output distributions from instantaneous quantum polynomial (IQP) circuits affected by amplitude-damping noise. The algorithm addresses a key gap in the field, as most existing simulation techniques rely on specific types of noise or inherent randomness, whereas this one functions effectively with non-unital noise and without requiring randomness. Efficient simulation of these circuits, generated by arbitrary local gates with sufficient depth, is a vital step towards validating quantum computations and developing strong error mitigation strategies for near-term quantum devices. Polynomial time simulation of amplitude-damped instantaneous quantum polynomial circuits overcomes existing limitations Circuits previously requiring a depth exceeding Ω(log(n)) for classical simulation are now efficiently sampled in polynomial time. The breakthrough applies to amplitude-damped instantaneous quantum polynomial (IQP) circuits, a class specifically designed to challenge classical computers and benchmark quantum supremacy. These circuits are constructed using Clifford gates and a non-Clifford gate, typically a Hadamard gate applied to a specific qubit, creating a computational basis state that is difficult for classical computers to represent efficiently. Previous methods struggled with circuits beyond this logarithmic depth or relied on specific noise conditions, such as unital noise where the trace of the noise operator is preserved, meaning the overall probability remains constant. Researchers have developed a classical algorithm capable of simulating quantum circuits previously considered beyond reach, utilising arbitrary ‘l-local diagonal gates’, meaning gates acting on a limited number of qubits at a time. Diagonal gates, in this context, represent operations that preserve the diagonal elements of the density matrix, simplifying the simulation process. This expands the scope of verifiable quantum computation and offers a new tool for developing error mitigation techniques, enabling the
Symmetry-Based Qubits Unlock Simpler, Faster <b>Quantum Computer</b> Components
A new pathway towards practical photonic quantum computing has been identified by harnessing the symmetry of photons. David S. Simon and colleagues at Boston University report a deterministic linear-optical computing method employing symmetry-based qubits. Their research reveals Grover four-ports can function as compact controlled-NOT gates without post-selection or ancilla measurements, a key advancement as these techniques typically hinder scalability. This approach enables the creation of flexible optical devices capable of implementing a range of quantum gates, including the complex Fredkin and Toffoli gates, paving the way for more efficient and resource-conscious quantum processors. Photon symmetry defines qubit states and enables direct interactions Encoding qubits, the basic units of quantum information, into a photon’s symmetry proved central to this development. Traditionally, qubits are defined by properties like the polarisation or phase of a photon, representing the ‘0’ and ‘1’ states. However, this research introduces a nonstandard qubit definition based on spatial symmetry. A qubit is now defined by how its properties behave under reflection, specifically whether a state is symmetric or antisymmetric, rather than simply its presence or absence. This means a photon’s wave function exhibits either even symmetry (unchanged by reflection) or odd symmetry (inverted by reflection), forming the basis for the qubit’s ‘0’ and ‘1’ states. Grover four-ports, a specific arrangement of beam splitters, then exploit this principle, directing photons based on their symmetry much like a railway switch directs trains. These ports are designed to couple the photon’s symmetry to its direction of travel; a photon in a symmetric state will exit through a different port than one in an antisymmetric state, creating interactions between qubits without needing extra photons or complex measurements. This technique aims for deterministic operation, contrasting with previous approaches like the KLM method, which require increasing resources and often yield probabilistic results. The KLM
Deep Learning Models Validate Encryption, Distinguishing Ciphertexts With High Accuracy
A new methodology employing deep neural networks models and empirically tests the security of key encapsulation mechanisms (KEMs), hybrid constructions, and cascade encryption schemes. Simon Calderon and colleagues at Linköping University apply this deep learning framework to public-key encryption schemes including ML-KEM, BIKE, and HQC, as well as combinations with classical algorithms like RSA and AES. The methodology offers a flexible approach to data-driven validation. The research confirms these algorithms and combinations currently exhibit no key vulnerabilities under the tested conditions, aligning with established theoretical security guarantees and offering a vital new set of tools for practical cryptographic analysis. Deep learning sharply enhances empirical validation of post-quantum cryptographic An 80% reduction in ciphertext distinguishing accuracy for HQC.pke resulted from employing a deep learning approach, exceeding the previously achievable 20% error rate and resolving a key limitation in validating post-quantum cryptography. This improvement enables empirical testing of complex hybrid encryption schemes, previously impossible with methods reliant on theoretical guarantees alone. Traditional analysis struggled to assess combinations of new and established cryptographic techniques, hindering comprehensive security evaluations. Deep learning sharply enhances empirical validation of post-quantum cryptography by providing a more robust method for assessing these complex systems. The deep learning framework models the IND-CPA game, a standardised security test, as a binary classification task, allowing for data-driven validation of implementations and compositions. Further validation of these findings came from applying the framework to cascade symmetric encryption, testing combinations of AES-CTR, AES-CBC, AES-ECB, ChaCha20, and DES-ECB; this demonstrated the flexible nature of the approach beyond post-quantum algorithms. This adaptive testing method complements analytical security analysis, offering a flexible tool for assessing the security of evolving cryptographic systems and their combinations. Statistical analysis, utilising two-sided binomial hypothesis testing, confirmed that no tested algorithm or combination achieved a statistically significant advantage over random guessing, aligning
Physicists unlock way to measure <b>quantum</b> entanglement inside real-world materials
Physicists unlock way to measure quantum entanglement inside real-world materials By decoding neutron data, scientists can now put a number on entanglement inside complex materials. Scientists have always wondered whether ordinary materials are also secretly held together by quantum connections. Until now, there seems to be no way to answer this question. However, recently, a team of researchers has demonstrated a technique that can directly detect entanglement inside solids. So instead of guessing or relying purely on theory, scientists can now directly measure how entangled a material is—an essential step for designing better quantum devices. Moreover, according to the researchers, their technique works even when there is no perfect theoretical model of the material, and the sample is not pure (which is often the case in real-world materials). “We’ve found that it works 100 percent,” Allen Scheie, one of the researchers and a condensed matter physicist at Los Alamos National Laboratory in New Mexico, said. Turning neutron echoes into a map of entanglement The problem scientists faced wasn’t a lack of theory but a lack of tools. Traditional methods like Bell tests can confirm entanglement between a few particles, but they break down when dealing with the trillions of interacting particles inside a solid. Materials are messy, complex, and often imperfect, making it extremely difficult to tell whether entanglement is present, let alone measure how much of it exists. The researchers tackled this by refining neutron scattering, a technique that has been around since the 1950s. In simple terms, they fired neutrons at a material and observed how those neutrons bounced off. These scattered neutrons carry subtle fingerprints of what’s happening inside a material—how atoms are arranged and how their quantum properties behave. However, the real breakthrough came from combining this old tool with a newer concept called quantum Fisher
Exploring fundamentals of <b>quantum computing</b> and career pathways in the field
“From the age of the internet to artificial intelligence, we are now marching towards to the age of quantum. The future is certainly quantum,” said Maheswari R., Principal, Rajalakshmi Institute of Technology, Chennai, at The Hindu EducationPlus Career Counselling Fair 2026. Ms. Maheswari introduced students and parents to the fundamentals of quantum computing, the difference between classical bits and quantum bits (qubits). She elaborated on concepts such as quantum entanglement and interference, comparisons between traditional and quantum computers. Published - April 12, 2026 01:13 am IST
Is Ripple (XRP) <b>Quantum</b>-Safe? A Top XRPL Validator Just Published a Full Audit
Quantum computing has become one of the biggest concerns in crypto after Google revealed that future machines could crack the encryption most blockchains rely on—and do it with less power than anyone expected. Bitcoin is the most exposed, with up to 35% of its supply sitting in old wallets that can’t be protected without moving the funds. XRP (CRYPTO: XRP) holders have been asking the same question: Is my XRP at risk too? An XRPL validator just audited the entire XRP Ledger to find out. Only 0.03% of XRP’s supply is directly exposed through dormant accounts—far less than Bitcoin’s estimated 35%. The XRP Ledger also has built-in tools like key rotation that most blockchains don’t offer. But the live network still runs on the same encryption that quantum computers could eventually break, and the upgrades being tested on XRPL’s developer network haven’t reached the main chain yet. How Much XRP Is Exposed to Quantum Risk? When you make a transaction on any blockchain, your public key gets revealed to the network. A quantum computer powerful enough to run the right algorithm could work backwards from that public key to figure out your private key, and once it has that, it can drain your wallet. If you’ve never made a transaction, your public key has never been exposed, and a quantum attacker has nothing to work with. Vet, a well-known XRPL validator, ran a full check across the XRP Ledger on April 7 and found that around 300,000 accounts have never sent a single transaction. Those accounts are quantum-safe right now because their public keys don’t exist anywhere on the network. Vet found only two dormant large-holder accounts with exposed keys, and the total XRP in those accounts works out to roughly 0.03% of the supply. The 0.03% figure has been
Q-Day: The <b>Quantum</b> Threat That Could Unravel Bitcoin's Security
Quantum computing is advancing faster than Bitcoin’s defenses, and the cryptographic bedrock beneath the world’s most valuable digital asset may have a ticking clock on it. Call it Q-Day: the hypothetical moment when a quantum computer becomes powerful enough to crack the elliptic curve cryptography that protects Bitcoin wallets and authorizes transactions. It sounds like science fiction, but in early 2026 the conversation has moved firmly into engineering departments and central bank risk committees. The question is no longer whether quantum machines will get there, but when, and whether the crypto industry will be ready. Bitcoin’s security rests on a problem that classical computers find practically impossible to reverse: deriving a private key from a public key. The math underpinning this, specifically the Elliptic Curve Digital Signature Algorithm, would take a conventional computer billions of years to break by brute force. A sufficiently advanced quantum computer running Shor’s algorithm could theoretically do it in hours. That is the core of the threat, and it is why the National Institute of Standards and Technology finalized its first set of post-quantum cryptographic standards in 2024, a quiet signal that governments are treating this as a near-term infrastructure problem rather than an academic curiosity. The attack scenario most experts flag is not some dramatic heist of coins sitting in cold storage. The real vulnerability window opens when someone broadcasts a Bitcoin transaction. In that moment, the public key is exposed on the network before the transaction is confirmed, typically for around ten minutes. A quantum adversary with enough processing power could extract the private key during that window and sign a competing transaction, effectively stealing the funds mid-flight. Wallets that have never broadcast a transaction, and whose public keys therefore remain hidden, are considered safer for now. How far away is the actual
Best <b>Quantum Computing</b> Stocks To Watch Today - April 11th
IonQ, D-Wave Quantum, Quantum Computing, and Horizon Quantum Computing Pte. are the five Quantum Computing stocks to watch today, according to MarketBeat's stock screener tool. "Quantum computing stocks" are shares of companies that develop, manufacture, or commercialize quantum computing hardware, software, algorithms, supporting components, or related services, including specialist startups, established tech firms, and ETFs focused on the field. For investors, these stocks offer exposure to an emerging, high‑risk/high‑reward technology whose valuations are often driven more by R&D progress, partnerships, and long‑term potential than by current revenue or profits. These companies had the highest dollar trading volume of any Quantum Computing stocks within the last several days. IonQ (IONQ) IonQ, Inc. engages in the development of general-purpose quantum computing systems in the United States. It sells access to quantum computers of various qubit capacities. The company makes access to its quantum computers through cloud platforms, such as Amazon Web Services (AWS) Amazon Braket, Microsoft's Azure Quantum, and Google's Cloud Marketplace, as well as through its cloud service. Read Our Latest Research Report on IONQ D-Wave Quantum (QBTS) D-Wave Quantum Inc. develops and delivers quantum computing systems, software, and services worldwide. The company offers Advantage, a fifth-generation quantum computer; Ocean, a suite of open-source python tools; and Leap, a cloud-based service that provides real-time access to a live quantum computer, as well as access to Advantage, hybrid solvers, the Ocean software development kit, live code, demos, learning resources, and a vibrant developer community. Read Our Latest Research Report on QBTS Quantum Computing (QUBT) Quantum Computing Inc., an integrated photonics company, offers accessible and affordable quantum machines. The company offers Dirac systems are portable, low power, and room temperature qubit and qudit entropy quantum computers (EQC); reservoir computing; remote sensing; and single photon imaging. It also provides Quantum random number generator (uQRNG),
GTRI Supports Initiative to Assess <b>Quantum Computing</b> Efforts | Business News This Week
Quantum computers may one day enable revolutionary advances in fluid dynamics, drug discovery, development of better agricultural fertilizers, improved materials design and other technical areas that are beyond the capabilities of today’s conventional computers. To reach those goals, companies from around the world are pursuing a variety of approaches aimed at developing large-scale, fault-tolerant quantum computers. The approaches of over a dozen quantum computing companies are now being evaluated through the Quantum Benchmarking Initiative (QBI), a project of the U.S. Defense Advanced Research Projects Agency (DARPA). According to the agency, QBI “aims to rigorously verify and validate whether any quantum computing approach can achieve utility-scale operation – meaning its computational value exceeds its cost – by the year 2033.” Supporting the effort, a 40-person interdisciplinary research team from the Georgia Tech Research Institute (GTRI) has joined the test and evaluation component of QBI, providing unbiased subject-matter experts to work with 13 other research organizations in evaluating the R&D plans of participating quantum computer companies. Through this collaboration, the GTRI team is working with more than 400 other thirted-party experts on the project.
Milestone on the Way to Creating Antihydrogen in Mainz: New Dual-Frequency Paul Trap Tested
A new type of radiofrequency trap can capture particles with extremely different requirements and could theoretically hold both types of particles at the same time. Researchers in the group of Professor Dr. Dmitry Budker from the PRISMA++ Cluster of Excellence at Johannes Gutenberg University Mainz (JGU) and the Helmholtz Institute Mainz were able to trap calcium ions or electrons in the same apparatus. The team's findings, published in Physical Review A, show the potential of this technology for synthesizing antihydrogen. "Radiofrequency traps, also called Paul traps, have long been used by physicists to trap specific particles," Dr. Hendrik Bekker explained. "However, they are usually limited to a single frequency." This means that only one type of particle can be captured at a time in a typical Paul trap. In order to synthesize antihydrogen, however, two types of particles – antiprotons and positrons – would need to be trapped together at the same time. Due to their low mass, positrons require GHz-frequency fields for stable confinement, while antiprotons are typically trapped with MHz-frequency fields. For their current study, the researchers used electrons and heavy calcium ions (40Ca+) as more readily available stand-ins for antiprotons and positrons. Catching Two Birds in the Same Cage In order to trap the calcium ions and electrons, the dual-frequency Paul-trap, which is being developed in collaboration with Professor Dr. Ferdinand Schmidt-Kaler from JGU as well as the group of Professor Dr. Hartmut Häffner at UC Berkeley, has to generate both GHz and MHz frequency fields. Hendrik Bekker and PhD candidate students Vladimir Mikhailovski and Natalija Rajeshri Sheth generate these fields by layering three printed circuit boards (PCB) and separating them with ceramic spacers. The central board is equipped with what is known as a coplanar waveguide resonator which generates the GHz frequency field to trap electrons.
New paper highlights '<b>Quantum</b>-safe Bitcoin' - Focus turns on XRP instead
New paper highlights ‘Quantum-safe Bitcoin’ – Focus turns on XRP instead Bitcoin’s attempt to stay quantum-safe comes with a key limitation, prompting market attention toward other networks. If there’s one theme shaping the 2026 cycle so far, it’s that networks are starting to prioritize security. A week ago, Solana [SOL] ran a quantum-resistance test to evaluate whether the network could withstand quantum-related attacks. The key takeaway was a significant trade-off: about a 90% drop in speed in exchange for stronger security guarantees. Notably, other networks are now starting to follow suit. In the past two days, two major quantum-related updates came out for Bitcoin [BTC]. One prototype allows users to recover funds if quantum computers ever break current signature schemes. Now, a proposal by Avihu Levy suggests that Bitcoin transactions could be made quantum-safe without requiring changes to the core protocol. Interestingly, the latter has become the main focus among crypto enthusiasts. Levy released a whitepaper highlighting how Bitcoin transactions could become quantum-resistant without requiring a soft fork. That said, it doesn’t come without trade-offs. Notably, Bitcoin can be made quantum-safe today without a protocol upgrade, though each transaction could cost around $75 to $150 in GPU compute. Put simply, this means users would pay more in computing power and cost in exchange for stronger security without changing Bitcoin’s base protocol. In short, security for networks won’t come without trade-offs. First, Solana proved it with a 90% reduction in speed, and now Bitcoin with higher transaction costs. In this context, does this setup give a potential edge to networks that can better balance security with efficiency without pushing either cost or speed too far? Bitcoin’s quantum debate shifting attention toward XRP One clear signal from recent moves is that quantum threats are shifting from hype to a real concern. Why