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Check ",{"type":21,"tag":394,"props":2481,"children":2483},{"className":2482},[],[2484],{"type":26,"value":2485},"backend.configuration().n_qubits",{"type":26,"value":2072},{"type":21,"tag":394,"props":2488,"children":2490},{"className":2489},[],[2491],{"type":26,"value":2492},"backend.configuration().basis_gates",{"type":26,"value":2494}," before transpiling, and let ",{"type":21,"tag":394,"props":2496,"children":2498},{"className":2497},[],[2499],{"type":26,"value":2500},"transpile()",{"type":26,"value":2502}," handle the gate decomposition rather than manually inserting gates the backend doesn't natively support.",{"type":21,"tag":43,"props":2504,"children":2506},{"id":2505},"deprecation-warnings-from-qiskitalgorithms-and-qiskitopflow",[2507,2509,2515,2516],{"type":26,"value":2508},"Deprecation warnings from ",{"type":21,"tag":394,"props":2510,"children":2512},{"className":2511},[],[2513],{"type":26,"value":2514},"qiskit.algorithms",{"type":26,"value":2072},{"type":21,"tag":394,"props":2517,"children":2519},{"className":2518},[],[2520],{"type":26,"value":2521},"qiskit.opflow",{"type":21,"tag":22,"props":2523,"children":2524},{},[2525,2527,2533,2535,2540,2542,2547,2549,2555,2557,2562,2564,2569,2571,2577,2578,2584],{"type":26,"value":2526},"If your console fills with ",{"type":21,"tag":394,"props":2528,"children":2530},{"className":2529},[],[2531],{"type":26,"value":2532},"DeprecationWarning",{"type":26,"value":2534}," on every run, the code is almost always importing from ",{"type":21,"tag":394,"props":2536,"children":2538},{"className":2537},[],[2539],{"type":26,"value":2521},{"type":26,"value":2541}," or the older ",{"type":21,"tag":394,"props":2543,"children":2545},{"className":2544},[],[2546],{"type":26,"value":2514},{"type":26,"value":2548}," module structure, both superseded by the separate ",{"type":21,"tag":394,"props":2550,"children":2552},{"className":2551},[],[2553],{"type":26,"value":2554},"qiskit-algorithms",{"type":26,"value":2556}," package and the primitives-based (",{"type":21,"tag":394,"props":2558,"children":2560},{"className":2559},[],[2561],{"type":26,"value":1464},{"type":26,"value":2563},"\u002F",{"type":21,"tag":394,"props":2565,"children":2567},{"className":2566},[],[2568],{"type":26,"value":1472},{"type":26,"value":2570},") pattern. Warnings aren't fatal, but they're a sign the code is one migration behind, and the underlying functions do eventually get removed. Our ",{"type":21,"tag":34,"props":2572,"children":2574},{"href":2573},"\u002Fblog\u002Fvqe-pennylane-practical-guide",[2575],{"type":26,"value":2576},"VQE walkthrough",{"type":26,"value":2072},{"type":21,"tag":34,"props":2579,"children":2581},{"href":2580},"\u002Fblog\u002Fqaoa-max-cut-tutorial",[2582],{"type":26,"value":2583},"QAOA tutorial",{"type":26,"value":2585}," use the current primitives pattern if you need a working reference to migrate against.",{"type":21,"tag":43,"props":2587,"children":2589},{"id":2588},"jobs-stuck-in-queue-on-the-free-tier",[2590],{"type":26,"value":2591},"Jobs stuck in queue on the free tier",{"type":21,"tag":22,"props":2593,"children":2594},{},[2595,2597,2603,2605,2611,2613,2618],{"type":26,"value":2596},"Not an error message, a silent wait. IBM's free Open Plan queues everyone's jobs on shared hardware, and a job submitted to a busy backend takes real time to return, which looks identical to a hang from the caller's side. Call ",{"type":21,"tag":394,"props":2598,"children":2600},{"className":2599},[],[2601],{"type":26,"value":2602},"service.least_busy(operational=True, simulator=False)",{"type":26,"value":2604}," instead of naming a specific backend, and check ",{"type":21,"tag":394,"props":2606,"children":2608},{"className":2607},[],[2609],{"type":26,"value":2610},"job.status()",{"type":26,"value":2612}," rather than assuming a stuck cell means broken code. Our ",{"type":21,"tag":34,"props":2614,"children":2615},{"href":64},[2616],{"type":26,"value":2617},"free tier guide",{"type":26,"value":2619}," covers what the 10-minute monthly quantum-time limit does and doesn't cover.",{"type":21,"tag":43,"props":2621,"children":2623},{"id":2622},"the-pattern-behind-most-of-these",[2624],{"type":26,"value":2625},"The pattern behind most of these",{"type":21,"tag":22,"props":2627,"children":2628},{},[2629,2631,2637,2638,2643,2644,2650],{"type":26,"value":2630},"Every API-change error above traces back to the equivalent event: Qiskit 1.0 unified what used to be a scattered set of packages (",{"type":21,"tag":394,"props":2632,"children":2634},{"className":2633},[],[2635],{"type":26,"value":2636},"qiskit-terra",{"type":26,"value":582},{"type":21,"tag":394,"props":2639,"children":2641},{"className":2640},[],[2642],{"type":26,"value":1533},{"type":26,"value":582},{"type":21,"tag":394,"props":2645,"children":2647},{"className":2646},[],[2648],{"type":26,"value":2649},"qiskit-ibmq-provider",{"type":26,"value":2651},", and more) into one restructured, versioned package, and retired several legacy paths in the process. If you're hitting an error that isn't listed here and it comes from code copied from an older tutorial, check whether the import path predates that restructuring before assuming your circuit logic is wrong.",{"type":21,"tag":1218,"props":2653,"children":2654},{},[2655],{"type":26,"value":1222},{"title":8,"searchDepth":287,"depth":287,"links":2657},[2658,2659,2661,2663,2665,2667,2669,2671,2672],{"id":1250,"depth":287,"text":1257},{"id":1492,"depth":287,"text":2660},"ImportError or AttributeError on from qiskit import Aer",{"id":1675,"depth":287,"text":2662},"IBMQ.load_account() no longer works",{"id":1972,"depth":287,"text":2664},"ModuleNotFoundError: No module named 'azure.quantum' when submitting to Azure Quantum",{"id":2260,"depth":287,"text":2666},"CircuitError on .measure(): register size mismatch",{"id":2405,"depth":287,"text":2668},"TranspilerError: circuit doesn't match backend",{"id":2505,"depth":287,"text":2670},"Deprecation warnings from qiskit.algorithms and qiskit.opflow",{"id":2588,"depth":287,"text":2591},{"id":2622,"depth":287,"text":2625},"content:blog:common-qiskit-errors-and-fixes.md","blog\u002Fcommon-qiskit-errors-and-fixes.md","blog\u002Fcommon-qiskit-errors-and-fixes",{"_path":2677,"_dir":6,"_draft":7,"_partial":7,"_locale":8,"title":2678,"description":2679,"date":2680,"author":12,"tags":2681,"readingTime":600,"body":2684,"_type":301,"_id":3149,"_source":303,"_file":3150,"_stem":3151,"_extension":306},"\u002Fblog\u002Flogical-qubits-fault-tolerance-explained","Logical Qubits and Fault Tolerance: What the Qubit Count Doesn't Tell You","A physical qubit is hardware. A logical qubit is an error-protected qubit built out of many of them. Understanding the difference is the fastest way to see through quantum computing headlines.","2026-07-18",[2682,15,2683],"Error Correction","QPU",{"type":18,"children":2685,"toc":3139},[2686,2691,2704,2710,2738,2753,2782,2788,2800,2805,2818,2838,2844,2849,2860,2873,2878,2883,2889,2901,2906,2926,2931,2937,2942,2952,2962,2987,2993,2998,3008,3018,3028,3038,3043,3049,3054,3059,3088,3108,3114,3126],{"type":21,"tag":22,"props":2687,"children":2688},{},[2689],{"type":26,"value":2690},"Every few months a press release announces a new record qubit count. Almost none of them tell you the number that decides whether the machine does anything: the error rate.",{"type":21,"tag":22,"props":2692,"children":2693},{},[2694,2696,2702],{"type":26,"value":2695},"This is not a pedantic complaint. The relationship between qubit count and computational power in quantum computing is not merely noisy. It sometimes inverts. Under the right conditions, a machine with more qubits is ",{"type":21,"tag":2697,"props":2698,"children":2699},"em",{},[2700],{"type":26,"value":2701},"worse",{"type":26,"value":2703}," than one with fewer. Understanding why requires one distinction, and once you have it, most quantum computing news becomes far easier to read.",{"type":21,"tag":43,"props":2705,"children":2707},{"id":2706},"two-things-called-qubit",[2708],{"type":26,"value":2709},"Two things called \"qubit\"",{"type":21,"tag":22,"props":2711,"children":2712},{},[2713,2715,2720,2722,2728,2730,2736],{"type":26,"value":2714},"A ",{"type":21,"tag":217,"props":2716,"children":2717},{},[2718],{"type":26,"value":2719},"physical qubit",{"type":26,"value":2721}," is a piece of hardware: a superconducting circuit on a chip, a trapped ion held in an electromagnetic field, a neutral atom in an optical tweezer. It is a real object subject to real physics, which means it drifts, absorbs stray energy, and loses its quantum state on a timescale measured in microseconds to seconds. That decay is ",{"type":21,"tag":34,"props":2723,"children":2725},{"href":2724},"\u002Fglossary\u002Fdecoherence",[2726],{"type":26,"value":2727},"decoherence",{"type":26,"value":2729},", and the ",{"type":21,"tag":34,"props":2731,"children":2733},{"href":2732},"\u002Fglossary\u002Ft1-t2-time",[2734],{"type":26,"value":2735},"T1 and T2 times",{"type":26,"value":2737}," that quantify it are among the few hardware specs worth reading closely.",{"type":21,"tag":22,"props":2739,"children":2740},{},[2741,2742,2751],{"type":26,"value":2714},{"type":21,"tag":217,"props":2743,"children":2744},{},[2745],{"type":21,"tag":34,"props":2746,"children":2748},{"href":2747},"\u002Fglossary\u002Flogical-qubit",[2749],{"type":26,"value":2750},"logical qubit",{"type":26,"value":2752}," is not hardware. It is a qubit's worth of quantum information spread across many physical qubits, arranged so that errors on individual members are detected and undone without ever measuring, and thereby destroying, the encoded state. IonQ describes logical qubits as software-defined, and that framing is a good one: the logical qubit is a construction that hardware supports rather than a thing you point to.",{"type":21,"tag":22,"props":2754,"children":2755},{},[2756,2758,2764,2766,2772,2774,2780],{"type":26,"value":2757},"The technique is ",{"type":21,"tag":34,"props":2759,"children":2761},{"href":2760},"\u002Fglossary\u002Fquantum-error-correction",[2762],{"type":26,"value":2763},"quantum error correction",{"type":26,"value":2765},", and our ",{"type":21,"tag":34,"props":2767,"children":2769},{"href":2768},"\u002Fblog\u002Funderstanding-quantum-error-correction",[2770],{"type":26,"value":2771},"companion post on QEC",{"type":26,"value":2773}," covers the mechanics: parity checks, ",{"type":21,"tag":34,"props":2775,"children":2777},{"href":2776},"\u002Fglossary\u002Fancilla-qubit",[2778],{"type":26,"value":2779},"ancilla qubits",{"type":26,"value":2781},", the surface code lattice. This post is about the accounting: what encoding costs, when it pays off, and what else fault tolerance demands beyond the encoding itself.",{"type":21,"tag":43,"props":2783,"children":2785},{"id":2784},"why-how-many-qubits-is-nearly-meaningless",[2786],{"type":26,"value":2787},"Why \"how many qubits?\" is nearly meaningless",{"type":21,"tag":22,"props":2789,"children":2790},{},[2791,2793,2798],{"type":26,"value":2792},"Here is the uncomfortable arithmetic. If your physical error rate is above the threshold of your error-correcting code, encoding does not help. The extra qubits and the extra gates needed to perform parity checks each introduce errors of their own. Add more of them and you add more noise than you remove. A headline of 1,000 physical qubits with mediocre fidelity is compatible with ",{"type":21,"tag":217,"props":2794,"children":2795},{},[2796],{"type":26,"value":2797},"zero",{"type":26,"value":2799}," logical qubits, not few, zero.",{"type":21,"tag":22,"props":2801,"children":2802},{},[2803],{"type":26,"value":2804},"Meanwhile a smaller, cleaner machine is sometimes strictly more useful. IonQ argues this point aggressively, claiming that a system of 100 physical qubits at 99.99% two-qubit gate fidelity would likely outperform a 10,000-qubit system of lower-quality qubits encoding 100 logical ones: on overhead, gate speed, universality, and energy. That's a vendor making a case for its own architecture and should be read as such, but the underlying logic is sound and widely accepted: quality compounds in a way that quantity does not.",{"type":21,"tag":22,"props":2806,"children":2807},{},[2808,2810,2816],{"type":26,"value":2809},"The compounding is the key mechanism. In a code that corrects one error, roughly speaking, halving the physical error rate quarters the logical error rate. In a code correcting two errors the same improvement gives about an eight-fold gain. IonQ makes this multiplicative argument explicitly, and it explains why hardware teams chase ",{"type":21,"tag":34,"props":2811,"children":2813},{"href":2812},"\u002Fglossary\u002Ffidelity",[2814],{"type":26,"value":2815},"fidelity",{"type":26,"value":2817}," improvements that look small in isolation. A 2x hardware win is a 4x or 8x win after encoding.",{"type":21,"tag":22,"props":2819,"children":2820},{},[2821,2823,2829,2831,2836],{"type":26,"value":2822},"This is also why single-number benchmarks keep failing the field. ",{"type":21,"tag":34,"props":2824,"children":2826},{"href":2825},"\u002Fglossary\u002Fquantum-volume",[2827],{"type":26,"value":2828},"Quantum Volume",{"type":26,"value":2830},", algorithmic qubits, gate counts: each captures a slice and hides the rest. We wrote about that measurement problem ",{"type":21,"tag":34,"props":2832,"children":2833},{"href":264},[2834],{"type":26,"value":2835},"in the context of EO 14413",{"type":26,"value":2837},", and it applies with full force here.",{"type":21,"tag":43,"props":2839,"children":2841},{"id":2840},"the-overhead-is-the-whole-story",[2842],{"type":26,"value":2843},"The overhead is the whole story",{"type":21,"tag":22,"props":2845,"children":2846},{},[2847],{"type":26,"value":2848},"How many physical qubits does one logical qubit cost? The honest answer is that it depends on two numbers you have to state together: your physical error rate and the logical error rate you're targeting.",{"type":21,"tag":22,"props":2850,"children":2851},{},[2852,2858],{"type":21,"tag":34,"props":2853,"children":2855},{"href":2854},"\u002Fresearch\u002Fshor-error-correction-1995",[2856],{"type":26,"value":2857},"Shor's 1995 code",{"type":26,"value":2859},", the first quantum error-correcting code ever written down, used nine physical qubits to protect one logical qubit against an arbitrary single-qubit error. That was a proof that the thing was possible at all. Before it, many physicists believed no-cloning made quantum computing hopeless in principle.",{"type":21,"tag":22,"props":2861,"children":2862},{},[2863,2865,2871],{"type":26,"value":2864},"Nine turned out to be optimistic for practical machines. ",{"type":21,"tag":34,"props":2866,"children":2868},{"href":2867},"\u002Fresearch\u002Fkitaev-anyons-1997",[2869],{"type":26,"value":2870},"Kitaev's 1997 work on anyons",{"type":26,"value":2872}," introduced topological codes, including the surface code, which stores information in global properties of a 2D lattice rather than in any individual site. Its great virtue is that every parity check involves only neighbouring qubits, which maps cleanly onto flat chips, and it tolerates physical error rates around 1%, high enough that real hardware plausibly reaches it.",{"type":21,"tag":22,"props":2874,"children":2875},{},[2876],{"type":26,"value":2877},"The price is scale. Surface code overhead grows with code distance, and realistic estimates for running a cryptographically relevant algorithm land at hundreds to a few thousand physical qubits per logical qubit, with total system requirements often quoted in the millions. Push your physical error rate down and that ratio falls fast. Let it drift up toward threshold and the ratio explodes. Overhead is not a fixed constant of the technology. It is a function of how good your hardware is.",{"type":21,"tag":22,"props":2879,"children":2880},{},[2881],{"type":26,"value":2882},"Newer code families are attacking the ratio directly. IonQ has promoted a bivariate bicycle variant it calls BB5, claiming an idle logical error rate around 5x10⁻⁵ using 50 physical qubits, roughly four times smaller than standard BB codes. Vendor-reported figures like that are worth tracking but not worth treating as settled until independently reproduced.",{"type":21,"tag":43,"props":2884,"children":2886},{"id":2885},"the-threshold-theorem-and-why-2024-mattered",[2887],{"type":26,"value":2888},"The threshold theorem, and why 2024 mattered",{"type":21,"tag":22,"props":2890,"children":2891},{},[2892,2894,2899],{"type":26,"value":2893},"The theoretical foundation under all of this is the ",{"type":21,"tag":217,"props":2895,"children":2896},{},[2897],{"type":26,"value":2898},"threshold theorem",{"type":26,"value":2900},". It says there exists a critical physical error rate. Below it, increasing the size of your code suppresses logical errors exponentially. You build them as small as you like by spending more qubits. Above it, the opposite: bigger codes are worse codes.",{"type":21,"tag":22,"props":2902,"children":2903},{},[2904],{"type":26,"value":2905},"For decades this was a theorem without an experiment. Every roadmap in the industry assumed the crossing was achievable. None had demonstrated it.",{"type":21,"tag":22,"props":2907,"children":2908},{},[2909,2911,2917,2919,2924],{"type":26,"value":2910},"That changed with ",{"type":21,"tag":34,"props":2912,"children":2914},{"href":2913},"\u002Fresearch\u002Fgoogle-below-threshold-2024",[2915],{"type":26,"value":2916},"Google's below-threshold result in 2024",{"type":26,"value":2918},". Running surface codes at distances 3, 5, and 7 on its 105-qubit Willow processor, the team observed each increase in code distance roughly ",{"type":21,"tag":217,"props":2920,"children":2921},{},[2922],{"type":26,"value":2923},"halving",{"type":26,"value":2925}," the logical error rate, the direction fault tolerance requires. Critically, the encoded logical qubit outlived the best individual physical qubit on the chip, which is the concrete test of whether error correction is a net win rather than an expensive way to add noise.",{"type":21,"tag":22,"props":2927,"children":2928},{},[2929],{"type":26,"value":2930},"It's hard to overstate the significance. That experiment converted large-scale quantum computing from an open physics question into a scaling and engineering problem. Engineering problems are hard, but they are a different category of hard.",{"type":21,"tag":43,"props":2932,"children":2934},{"id":2933},"different-hardware-different-arithmetic",[2935],{"type":26,"value":2936},"Different hardware, different arithmetic",{"type":21,"tag":22,"props":2938,"children":2939},{},[2940],{"type":26,"value":2941},"The threshold is not a single universal number. It depends on the code, and which codes are practical depends on your hardware's connectivity. This is where modality differences stop being trivia.",{"type":21,"tag":22,"props":2943,"children":2944},{},[2945,2950],{"type":21,"tag":217,"props":2946,"children":2947},{},[2948],{"type":26,"value":2949},"Superconducting",{"type":26,"value":2951}," processors offer rapid gates (nanoseconds) and mature fabrication, but qubits interact only with their planar neighbours and fidelities are typically lower. That planar constraint is precisely what the surface code was designed around, which is why superconducting roadmaps are built on it.",{"type":21,"tag":22,"props":2953,"children":2954},{},[2955,2960],{"type":21,"tag":217,"props":2956,"children":2957},{},[2958],{"type":26,"value":2959},"Trapped ions",{"type":26,"value":2961}," invert the trade: gates are far slower (microseconds to milliseconds), but fidelities are the highest of any modality and connectivity is effectively all-to-all: any ion in a chain is entangled with any other without a chain of intervening swap operations. IonQ argues this connectivity is a structural advantage for error correction, because codes requiring non-local checks become implementable rather than prohibitively expensive, and it has claimed 99.99% physical two-qubit gate fidelity via its Oxford Ionics acquisition. Again: vendor claim, vendor benchmark conditions.",{"type":21,"tag":22,"props":2963,"children":2964},{},[2965,2967,2972,2973,2978,2980,2985],{"type":26,"value":2966},"Neither is obviously winning. Our ",{"type":21,"tag":34,"props":2968,"children":2969},{"href":272},[2970],{"type":26,"value":2971},"hardware overview",{"type":26,"value":2072},{"type":21,"tag":34,"props":2974,"children":2975},{"href":280},[2976],{"type":26,"value":2977},"modality comparison",{"type":26,"value":2979}," go into the specifics, and the broader ",{"type":21,"tag":34,"props":2981,"children":2982},{"href":36},[2983],{"type":26,"value":2984},"industry landscape",{"type":26,"value":2986}," tracks who is betting on what. The practical takeaway for anyone learning is that connectivity and fidelity, not qubit count, are the specs that determine which error-correction strategies a machine even attempts.",{"type":21,"tag":43,"props":2988,"children":2990},{"id":2989},"encoding-is-necessary-not-sufficient",[2991],{"type":26,"value":2992},"Encoding is necessary, not sufficient",{"type":21,"tag":22,"props":2994,"children":2995},{},[2996],{"type":26,"value":2997},"A subtlety that gets lost in coverage: storing a logical qubit is the easy part of fault tolerance. Computing on one is harder. A genuinely fault-tolerant machine needs all of the following:",{"type":21,"tag":22,"props":2999,"children":3000},{},[3001,3006],{"type":21,"tag":217,"props":3002,"children":3003},{},[3004],{"type":26,"value":3005},"Fault-tolerant gate operations.",{"type":26,"value":3007}," Logical gates must be implemented so that a single physical fault cannot propagate into an uncorrectable logical error. Some gates are cheap in a given code. Others are not.",{"type":21,"tag":22,"props":3009,"children":3010},{},[3011,3016],{"type":21,"tag":217,"props":3012,"children":3013},{},[3014],{"type":26,"value":3015},"Continuous syndrome extraction.",{"type":26,"value":3017}," Parity checks run constantly, in rounds, throughout the computation. The measurement circuits are themselves noisy, so the scheme has to tolerate faults in its own error detection.",{"type":21,"tag":22,"props":3019,"children":3020},{},[3021,3026],{"type":21,"tag":217,"props":3022,"children":3023},{},[3024],{"type":26,"value":3025},"Magic state distillation.",{"type":26,"value":3027}," Surface codes give you Clifford gates relatively cheaply, but Clifford gates alone are classically simulable. Universality needs a non-Clifford gate, typically T, and those are produced by distilling noisy \"magic states\" into clean ones. Distillation factories consume a large fraction of the total qubit budget in realistic architectures.",{"type":21,"tag":22,"props":3029,"children":3030},{},[3031,3036],{"type":21,"tag":217,"props":3032,"children":3033},{},[3034],{"type":26,"value":3035},"Real-time decoding.",{"type":26,"value":3037}," Syndrome data must be interpreted and corrections applied faster than errors accumulate. This is a classical computing problem, running at microsecond latency alongside the QPU, and it's a serious engineering constraint in its own right.",{"type":21,"tag":22,"props":3039,"children":3040},{},[3041],{"type":26,"value":3042},"IonQ's framing here is useful regardless of the vendor context: a logical qubit should be characterised by several attributes together: overhead, idle logical error rate, logical gate fidelity, logical gate speed, and gate-set universality, rather than counted. A logical qubit that is stored but not usefully operated on is not much of a logical qubit.",{"type":21,"tag":43,"props":3044,"children":3046},{"id":3045},"where-the-field-stands",[3047],{"type":26,"value":3048},"Where the field stands",{"type":21,"tag":22,"props":3050,"children":3051},{},[3052],{"type":26,"value":3053},"Honest summary as of mid-2026: logical qubits are real, demonstrated, and few.",{"type":21,"tag":22,"props":3055,"children":3056},{},[3057],{"type":26,"value":3058},"Multiple groups have encoded them. Google has shown error suppression scaling in the right direction. Trapped-ion and neutral-atom teams have run algorithms on minor numbers of encoded qubits. These are genuine milestones, not marketing.",{"type":21,"tag":22,"props":3060,"children":3061},{},[3062,3064,3070,3072,3078,3080,3086],{"type":26,"value":3063},"But useful fault-tolerant computation needs hundreds to thousands of logical qubits executing millions of logical operations, and that means physical qubit counts several orders of magnitude beyond anything running today, with error rates comfortably below threshold across the whole device rather than on the best-behaved corner of a chip. Most working hardware remains firmly in the ",{"type":21,"tag":34,"props":3065,"children":3067},{"href":3066},"\u002Fglossary\u002Fnisq",[3068],{"type":26,"value":3069},"NISQ regime",{"type":26,"value":3071}," that ",{"type":21,"tag":34,"props":3073,"children":3075},{"href":3074},"\u002Fresearch\u002Fpreskill-nisq-2018",[3076],{"type":26,"value":3077},"Preskill named in 2018",{"type":26,"value":3079},", where ",{"type":21,"tag":34,"props":3081,"children":3083},{"href":3082},"\u002Fglossary\u002Ferror-mitigation",[3084],{"type":26,"value":3085},"error mitigation",{"type":26,"value":3087}," (statistical post-processing rather than true correction) is the practical tool.",{"type":21,"tag":22,"props":3089,"children":3090},{},[3091,3093,3098,3100,3106],{"type":26,"value":3092},"None of which means waiting around. The abstractions transfer: circuits, gates, measurement, and noise behave the equivalent way whether you're on a simulator or a fault-tolerant machine a decade out. You begin on ",{"type":21,"tag":34,"props":3094,"children":3095},{"href":821},[3096],{"type":26,"value":3097},"free simulators",{"type":26,"value":3099}," or real QPUs today, and the ",{"type":21,"tag":34,"props":3101,"children":3103},{"href":3102},"\u002Fcourses",[3104],{"type":26,"value":3105},"courses page",{"type":26,"value":3107}," collects structured routes in.",{"type":21,"tag":43,"props":3109,"children":3111},{"id":3110},"the-one-habit-worth-forming",[3112],{"type":26,"value":3113},"The one habit worth forming",{"type":21,"tag":22,"props":3115,"children":3116},{},[3117,3119,3124],{"type":26,"value":3118},"When you following see a qubit-count headline, ask three questions: what is the two-qubit gate fidelity, is it below the relevant threshold, and how many ",{"type":21,"tag":2697,"props":3120,"children":3121},{},[3122],{"type":26,"value":3123},"logical",{"type":26,"value":3125}," qubits does that imply?",{"type":21,"tag":22,"props":3127,"children":3128},{},[3129,3131,3137],{"type":26,"value":3130},"Frequently the answer to the third is zero, and the article won't have mentioned it. Learning to notice that gap is most of what separates informed reading from press-release reading. The ",{"type":21,"tag":34,"props":3132,"children":3134},{"href":3133},"\u002Fglossary",[3135],{"type":26,"value":3136},"glossary",{"type":26,"value":3138}," is a decent place to build the vocabulary for it.",{"title":8,"searchDepth":287,"depth":287,"links":3140},[3141,3142,3143,3144,3145,3146,3147,3148],{"id":2706,"depth":287,"text":2709},{"id":2784,"depth":287,"text":2787},{"id":2840,"depth":287,"text":2843},{"id":2885,"depth":287,"text":2888},{"id":2933,"depth":287,"text":2936},{"id":2989,"depth":287,"text":2992},{"id":3045,"depth":287,"text":3048},{"id":3110,"depth":287,"text":3113},"content:blog:logical-qubits-fault-tolerance-explained.md","blog\u002Flogical-qubits-fault-tolerance-explained.md","blog\u002Flogical-qubits-fault-tolerance-explained",[3153,3231,3289,3349],{"_path":3154,"_dir":6,"_draft":7,"_partial":7,"_locale":8,"title":3155,"description":3156,"date":3157,"author":12,"tags":3158,"readingTime":504,"body":3162,"_type":301,"_id":3228,"_source":303,"_file":3229,"_stem":3230,"_extension":306},"\u002Fblog\u002Fcrypto4a-fips-140-3-level-3-quantum-safe-hsm","Crypto4A Passed FIPS 140-3 Level 3 for a Quantum-Safe HSM","Crypto4A's QASM module passed FIPS 140-3 Level 3, the first quantum-safe HSM to reach the bar, with support for all NIST post-quantum algorithms.","2026-08-21",[3159,3160,3161],"Post-Quantum","Security","Cryptography",{"type":18,"children":3163,"toc":3223},[3164,3169,3175,3180,3186,3191,3212,3218],{"type":21,"tag":22,"props":3165,"children":3166},{},[3167],{"type":26,"value":3168},"Canadian security firm Crypto4A received NIST FIPS 140-3 Level 3 validation for QASM, the cryptographic module inside its QxHSM hardware security module. The certification, announced August 19, 2026, is the first time a quantum-safe HSM reached Level 3 under the updated FIPS 140-3 standard. Level 3 requires physical tamper response, identity-based authentication, and zeroization of keys when the module detects tampering.",{"type":21,"tag":43,"props":3170,"children":3172},{"id":3171},"what-got-validated",[3173],{"type":26,"value":3174},"What got validated",{"type":21,"tag":22,"props":3176,"children":3177},{},[3178],{"type":26,"value":3179},"QASM runs the full set of NIST post-quantum algorithms: ML-KEM (FIPS 203) for key exchange, ML-DSA (FIPS 204) and SLH-DSA (FIPS 205) for signatures, plus stateful hash-based schemes like LMS. Hardware security modules generate, store, and manage the keys behind digital identity, financial transactions, and secure communications. A Level 3 validated module gives those keys a physical root of trust.",{"type":21,"tag":43,"props":3181,"children":3183},{"id":3182},"why-crypto-agility-matters",[3184],{"type":26,"value":3185},"Why crypto agility matters",{"type":21,"tag":22,"props":3187,"children":3188},{},[3189],{"type":26,"value":3190},"Crypto4A pitches the QxHSM and QxVault platforms as crypto-agile. Enterprises and agencies move from legacy RSA and elliptic-curve keys to post-quantum keys without replacing the physical appliance. DigiCert partnered to integrate the validated module into DigiCert ONE for signing, certificate issuance, and public key infrastructure.",{"type":21,"tag":22,"props":3192,"children":3193},{},[3194,3196,3202,3204,3210],{"type":26,"value":3195},"For teams planning a migration, see our ",{"type":21,"tag":34,"props":3197,"children":3199},{"href":3198},"\u002Fblog\u002Fpost-quantum-migration-deadlines",[3200],{"type":26,"value":3201},"post-quantum migration deadlines guide",{"type":26,"value":3203},". For the algorithms themselves, see our ",{"type":21,"tag":34,"props":3205,"children":3207},{"href":3206},"\u002Fblog\u002Fpost-quantum-cryptography-guide",[3208],{"type":26,"value":3209},"post-quantum cryptography guide",{"type":26,"value":3211},".",{"type":21,"tag":43,"props":3213,"children":3215},{"id":3214},"what-remains-unproven",[3216],{"type":26,"value":3217},"What remains unproven",{"type":21,"tag":22,"props":3219,"children":3220},{},[3221],{"type":26,"value":3222},"FIPS 140-3 Level 3 validates a module, not a company's whole product line or its market position. Crypto4A is an Ottawa-based firm led by CEO Bruno Couillard. The announcement is a vendor claim until independent deployments confirm the module in the field. The standard still matters because agencies and critical infrastructure operators face mandatory post-quantum deadlines, and a validated hardware root of trust shortens procurement review.",{"title":8,"searchDepth":287,"depth":287,"links":3224},[3225,3226,3227],{"id":3171,"depth":287,"text":3174},{"id":3182,"depth":287,"text":3185},{"id":3214,"depth":287,"text":3217},"content:blog:crypto4a-fips-140-3-level-3-quantum-safe-hsm.md","blog\u002Fcrypto4a-fips-140-3-level-3-quantum-safe-hsm.md","blog\u002Fcrypto4a-fips-140-3-level-3-quantum-safe-hsm",{"_path":3232,"_dir":6,"_draft":7,"_partial":7,"_locale":8,"title":3233,"description":3234,"date":3157,"author":12,"tags":3235,"readingTime":504,"body":3236,"_type":301,"_id":3286,"_source":303,"_file":3287,"_stem":3288,"_extension":306},"\u002Fblog\u002Fdirac-labs-diamond-navigation-preseed","Dirac Labs Raised $1.8M for Diamond Navigation Sensors","University of Wisconsin-Madison spinout Dirac Labs raised a $1.8 million pre-seed round to build diamond NV-center sensors for GPS-denied navigation.",[14,15],{"type":18,"children":3237,"toc":3281},[3238,3243,3249,3254,3260,3265,3269],{"type":21,"tag":22,"props":3239,"children":3240},{},[3241],{"type":26,"value":3242},"Dirac Labs, a University of Wisconsin-Madison spinout, raised $1.8 million in pre-seed funding to prototype diamond-based quantum navigation sensors. TitletownTech led the round, joined by Automotive Ventures, Riceberg Ventures, quantumEDGE Ventures, gradCapital, and angels Balaji Srinivasan and Jude Gomila.",{"type":21,"tag":43,"props":3244,"children":3246},{"id":3245},"how-the-sensors-work",[3247],{"type":26,"value":3248},"How the sensors work",{"type":21,"tag":22,"props":3250,"children":3251},{},[3252],{"type":26,"value":3253},"The startup's NVD-4 sensor measures local variations in Earth's magnetic field using diamond nitrogen-vacancy (NV) centers. Geomagnetic signatures pass through rock and water, so the system aims to provide positioning underwater, underground, and in GPS-denied regions where radio signals jam or spoof. AI models handle signal processing and sensor fusion, turning weak geomagnetic readings into location fixes.",{"type":21,"tag":43,"props":3255,"children":3257},{"id":3256},"the-market-fit",[3258],{"type":26,"value":3259},"The market fit",{"type":21,"tag":22,"props":3261,"children":3262},{},[3263],{"type":26,"value":3264},"The sensors target a plug-and-play form factor that connects to standard GPS ports on aircraft, submarines, autonomous underwater vehicles, and mining equipment. Dirac Labs says the hardware uses standard CMOS fabrication, which lowers cost and supports volume production. Co-founders CEO Sanket Deshpande and COO Aishwarya Das also secured grants from NOAA, the Indo-US Science and Technology Forum, and other programs.",{"type":21,"tag":43,"props":3266,"children":3267},{"id":3214},[3268],{"type":26,"value":3217},{"type":21,"tag":22,"props":3270,"children":3271},{},[3272,3274,3280],{"type":26,"value":3273},"Pre-seed rounds fund prototypes, not production. The company has no field-tested unit yet, and the unjammable, unspoofable positioning claims are vendor claims until an independent evaluation runs. For a broader look at quantum sensing, see our ",{"type":21,"tag":34,"props":3275,"children":3277},{"href":3276},"\u002Fblog\u002Finfleqtion-colorado-hq-quantum-sensing-minerals-2027",[3278],{"type":26,"value":3279},"Infleqtion Colorado sensing post",{"type":26,"value":3211},{"title":8,"searchDepth":287,"depth":287,"links":3282},[3283,3284,3285],{"id":3245,"depth":287,"text":3248},{"id":3256,"depth":287,"text":3259},{"id":3214,"depth":287,"text":3217},"content:blog:dirac-labs-diamond-navigation-preseed.md","blog\u002Fdirac-labs-diamond-navigation-preseed.md","blog\u002Fdirac-labs-diamond-navigation-preseed",{"_path":3290,"_dir":6,"_draft":7,"_partial":7,"_locale":8,"title":3291,"description":3292,"date":3157,"author":12,"tags":3293,"readingTime":504,"body":3295,"_type":301,"_id":3346,"_source":303,"_file":3347,"_stem":3348,"_extension":306},"\u002Fblog\u002Fquantinuum-albuquerque-integrated-photonics-leda","Quantinuum Got $1.5M to Build an Albuquerque Photonics Hub","Quantinuum received $750,000 from New Mexico and $750,000 from Albuquerque to convert a vacant site into an integrated photonics R&D center.",[14,15,3294],"Trapped-Ion",{"type":18,"children":3296,"toc":3341},[3297,3302,3308,3313,3319,3330,3336],{"type":21,"tag":22,"props":3298,"children":3299},{},[3300],{"type":26,"value":3301},"Quantinuum is expanding in Albuquerque, New Mexico, with a $1.5 million state and city incentive package. The State of New Mexico contributed $750,000 and the City of Albuquerque added $750,000 in Local Economic Development Act (LEDA) funds. Quantinuum will convert a vacant site at 5501 Wilshire into lab and office space for integrated photonics.",{"type":21,"tag":43,"props":3303,"children":3305},{"id":3304},"why-integrated-photonics",[3306],{"type":26,"value":3307},"Why integrated photonics",{"type":21,"tag":22,"props":3309,"children":3310},{},[3311],{"type":26,"value":3312},"Integrated photonics sits at the center of Quantinuum's next-generation trapped-ion machines. Miniaturized, chip-scale photonics guide, modulate, and deliver laser light for qubit state manipulation, addressing, and optical entanglement across multi-zone trapped-ion QPUs. A dedicated facility in New Mexico puts the work near Sandia National Laboratories, Los Alamos National Laboratory, and the University of New Mexico.",{"type":21,"tag":43,"props":3314,"children":3316},{"id":3315},"the-regional-bet",[3317],{"type":26,"value":3318},"The regional bet",{"type":21,"tag":22,"props":3320,"children":3321},{},[3322,3324,3329],{"type":26,"value":3323},"New Mexico has directed more than $450 million toward quantum research, startup infrastructure, and defense partnerships. The Albuquerque hub adds to Quantinuum's headquarters in Broomfield, Colorado and its centers in the US, UK, Germany, Japan, and Singapore. For trapped-ion context, see our ",{"type":21,"tag":34,"props":3325,"children":3326},{"href":131},[3327],{"type":26,"value":3328},"Quantinuum Helios logical qubits post",{"type":26,"value":3211},{"type":21,"tag":43,"props":3331,"children":3333},{"id":3332},"what-the-funding-does-not-buy",[3334],{"type":26,"value":3335},"What the funding does not buy",{"type":21,"tag":22,"props":3337,"children":3338},{},[3339],{"type":26,"value":3340},"This is a facilities and workforce expansion, not a new hardware result. The funding is modest next to the company's research spend, and the value shows only when the photonics work yields a smaller, more scalable trapped-ion system. The near-term signal is regional: a national laboratory ecosystem in New Mexico and a company building photonics capability inside it.",{"title":8,"searchDepth":287,"depth":287,"links":3342},[3343,3344,3345],{"id":3304,"depth":287,"text":3307},{"id":3315,"depth":287,"text":3318},{"id":3332,"depth":287,"text":3335},"content:blog:quantinuum-albuquerque-integrated-photonics-leda.md","blog\u002Fquantinuum-albuquerque-integrated-photonics-leda.md","blog\u002Fquantinuum-albuquerque-integrated-photonics-leda",{"_path":3350,"_dir":6,"_draft":7,"_partial":7,"_locale":8,"title":3351,"description":3352,"date":3157,"author":12,"tags":3353,"readingTime":504,"body":3355,"_type":301,"_id":3415,"_source":303,"_file":3416,"_stem":3417,"_extension":306},"\u002Fblog\u002Fqusquare-benchmark-prefault-tolerant-devices","QuSquare Benchmarks Pre-Fault-Tolerant Quantum Devices","Researchers in Spain published QuSquare, an open-source benchmark with four tests for evaluating today's noisy quantum hardware.",[14,15,3354],"Performance",{"type":18,"children":3356,"toc":3410},[3357,3362,3368,3373,3379,3384,3390],{"type":21,"tag":22,"props":3358,"children":3359},{},[3360],{"type":26,"value":3361},"Researchers at the University of the Basque Country and BCAM published QuSquare, a benchmark suite for evaluating quantum devices before fault tolerance. The paper appeared in Quantum Science and Technology (DOI 10.1088\u002F2058-9565\u002Fae917c) with an open-source implementation.",{"type":21,"tag":43,"props":3363,"children":3365},{"id":3364},"the-problem-the-suite-targets",[3366],{"type":26,"value":3367},"The problem the suite targets",{"type":21,"tag":22,"props":3369,"children":3370},{},[3371],{"type":26,"value":3372},"Hardware vendors publish many different metrics, and results rarely compare across architectures. QuSquare's authors argue misleading performance numbers distort research priorities. The suite builds relevance, reproducibility, fairness, verifiability, and scalability into four tests for fair comparisons across superconducting, trapped-ion, neutral-atom, and photonic systems.",{"type":21,"tag":43,"props":3374,"children":3376},{"id":3375},"the-four-benchmarks",[3377],{"type":26,"value":3378},"The four benchmarks",{"type":21,"tag":22,"props":3380,"children":3381},{},[3382],{"type":26,"value":3383},"The suite runs a Partial Clifford randomized benchmark for gate accuracy, a multipartite entanglement test measuring how well a device builds genuine GHZ states, a transverse-field Ising model simulation for many-body dynamics, and a data re-uploading quantum neural network for classification. The entanglement and QNN tests include adjustable parameters, so a smaller or noisier device still runs a fair version.",{"type":21,"tag":43,"props":3385,"children":3387},{"id":3386},"why-this-matters",[3388],{"type":26,"value":3389},"Why this matters",{"type":21,"tag":22,"props":3391,"children":3392},{},[3393,3395,3401,3402,3408],{"type":26,"value":3394},"QuSquare targets pre-fault-tolerant hardware, the machines available today, rather than hypothetical fault-tolerant systems. For readers running benchmarks themselves, see our ",{"type":21,"tag":34,"props":3396,"children":3398},{"href":3397},"\u002Fblog\u002Frandomized-benchmarking-qiskit-experiments",[3399],{"type":26,"value":3400},"randomized benchmarking guide",{"type":26,"value":2072},{"type":21,"tag":34,"props":3403,"children":3405},{"href":3404},"\u002Fblog\u002Fquantum-volume-benchmarking-tutorial",[3406],{"type":26,"value":3407},"quantum volume tutorial",{"type":26,"value":3409},". The suite is a research tool, not a product, and its value depends on adoption by hardware teams.",{"title":8,"searchDepth":287,"depth":287,"links":3411},[3412,3413,3414],{"id":3364,"depth":287,"text":3367},{"id":3375,"depth":287,"text":3378},{"id":3386,"depth":287,"text":3389},"content:blog:qusquare-benchmark-prefault-tolerant-devices.md","blog\u002Fqusquare-benchmark-prefault-tolerant-devices.md","blog\u002Fqusquare-benchmark-prefault-tolerant-devices",1787493247902]