Quantum Information Communication Technology (QICT)

The Rise of Quantum Information and Communication Technologies

In this scenario, quantum information and communication technologies (QICTs) can be defined as a set of technological components, devices, systems and methods for elaborating, storing and transmitting/sharing quantum information.

This paper focuses on QICT services and applications for quantum communications, specifically in the domain of quantum security, which appear to be more mature today as they rely on systems such as quantum key distribution (QKD) [3].epjquantumtechnology.springeropen.com/articles/10.11…

In particular, QKD is a secure communication method that implements a cryptographic protocol involving components of quantum mechanics. It enables two parties to produce a shared random secret key known only by them, which then can be used to encrypt and decrypt messages. The sender (traditionally referred to as Alice) and the receiver (referred to as Bob) are connected by a quantum communication channel that allows quantum states to be transmitted and an authenticated classical channel for deriving a common secret from the exchanged quantum information.

QKD systems can be divided into two main classes: discrete-variable and continuous-variable.

In the former class, the quantum information is typically encoded into discrete optical modes of a single photon, e.g., polarization or time bin; in this case, single-photon detectors are required for decoding. In the latter class, quantum states are described in an optical domain where the eigenstates are continuous with an infinite dimension, e.g., using Gaussian optical states.

mdpi.com/2624-960X/6/1/3

IEC/ISO JTC 3 Quantum technologies

The scope includes standardization in the field of quantum technologies, including quantum information technologies (quantum computing and quantum simulation), quantum metrology, quantum sources, quantum detectors, quantum communications, and fundamental quantum technologies.

https://www.iso.org/committee/10138914.html

IEC/ISO JTC 3 Quantum technologies Memberships

https://www.iec.ch/dyn/www/f?p=103:29:602724944129129::::FSP_ORG_ID,FSP_LANG_ID:49854,25

European Quantum Communication Infrastructure - EuroQCI

The EuroQCI will be a secure quantum communication infrastructure spanning the whole EU, including its overseas territories.

https://digital-strategy.ec.europa.eu/en/policies/european-quantum-communication-infrastructure-euroqci

PETRUS EuroQCI

A coordination & support action to act as a link between all projects, facilitate collaboration, & identify standardisation needs.

petrus-euroqci.eu

Connecting Europe Facility - CEF Digital

The digital part of the Connecting Europe Facility (CEF Digital) will support & catalyse both public & private investments in digital connectivity infrastructures between 2021 & 2027.

Despite this growing need for connectivity, there still is a significant gap in private & public funding. The Connecting Europe Facility – Digital comes as a response to this gap. Together w/ other funding instruments, including the Recovery & Resilience Facility & the InvestEU, CEF Digital will help support an unprecedented amount of investments devoted to safe, secure, & sustainable high-performance infrastructure.

https://digital-strategy.ec.europa.eu/en/activities/cef-digital

Recovery & Resilience Facility (RRF) Annual Report 2025

W/ €367 billion disbursed, so far, & over 2,700 milestones & targets achieved, the RRF is driving sustainable growth through transformative reforms as well as key projects such as clean vehicle recharging stations, investments in affordable & sustainable housing & high-speed internet connectivity for millions of households. The report stresses the need for EU Member States to fast-track the implementation of their recovery & resilience plans to meet the August 2026 deadline & emphasizes the spillover benefits strengthening the entire EU economy.

https://commission.europa.eu/publications/recovery-and-resilience-facility-annual-report-2025_en

Eagle-1

Eagle-1 will demonstrate the feasibility of quantum key distribution technology within the EU using a satellite-based system. To do so, the system will build on key technologies developed under ESA’s Scylight programme,https://connectivity.esa.int/artes-scylight-work-plan with the aim of validating vital components supplied within the EU.

It will demonstrate and validate quantum key distribution technologies from low Earth orbit to the ground and provide valuable mission data for the development and deployment of the European Quantum Communication Infrastructure (EuroQCI), which will be integrated into the European secure connectivity system. It will allow the EU to prepare for a sovereign, autonomous cross-border quantum secure communications network.

It will initially use an upgraded optical ground terminal from the German Aerospace Centre (DLR) alongside a new optical ground terminal to be developed by a team from the Netherlands. The Eagle-1 platform satellite from Italian company Sitael will carry a quantum-key payload built by Tesat Spacecom of Germany and will be operated by Luxembourg-headquartered SES. Other ESA Member States involved in the project include Austria, Belgium, the Czech Republic, Italy and Switzerland.

The Eagle-1 satellite is due to launch in late 2025 to early 2026 and will then complete three years of in-orbit validation supported by the European Commission.

https://www.esa.int/Applications/Connectivity_and_Secure_Communications/Eagle-1

It begins!! Quantinuum announces the commercial launch of Helios!

Introducing Helios: The Most Accurate Quantum Computer in the World

https://www.quantinuum.com/blog/introducing-helios-the-most-accurate-quantum-computer-in-the-world#

Quantinuum Announces Commercial Launch of Helios — A Quantum Computer With Accuracy to Enable Generative Quantum AI

https://thequantuminsider.com/2025/11/05/quantinuum-announces-commercial-launch-of-helios-a-quantum-computer-with-accuracy-to-enable-generative-quantum-ai/

Our new stack also features a real-time engine that massively improves our capability. With a real-time control system, we are evolving from static, pre-planned circuits to dynamic quantum programs that respond to results on the fly.

We can now, for the first time on a quantum computer, interleave GPU-accelerated classical and quantum computations in a single program.

Our real-time engine also means we have dynamic transport – routing qubits as the moment demands reduces time to solution and diminishes the impact of memory errors.

Programmers can now use our new quantum programming language, Guppy, to write dynamic circuits that were previously impossible. By combining Guppy with our real-time engine, developers can leverage arbitrary control flow driven by quantum measurements, as well as full classical computation—including loops, higher-order functions, early exits, and dynamic qubit allocation.

Far from being mere conveniences, these capabilities are essential stepping stones toward achieving fault-tolerant quantum computing at scale—putting us decisively ahead of the competition.

Fully compatible with industry standards like QIR and tools such as NVIDIA CUDA-Q, Helios bridges classical and quantum computing more seamlessly than ever, making hybrid quantum-classical development simple, natural, and accessible, and establishing Helios as the most programmable, general-purpose quantum computer ever built.

Quantum Guppy

https://www.quantinuum.com/blog/guppy-programming-the-next-generation-of-quantum-computers

Guppy documentation

Quantum-first programming
language, embedded in Python

https://docs.quantinuum.com/guppy/

BioDigital Convergence

PART 17: THE CREATION OF A FEEDBACK CIRCUIT

Remember that energy feedback loop needed for the Human Embedded System?

THE HUMAN EMBEDDED SYSTEM

Soul and Mind As Quantum States of an Embedded Human System

The study explain the possible functions mediated through SOUL, MIND & HUMAN BODY & flow of energy between them as a FEEDBACK CIRCUIT.

BIOPHOTONS

Biophotons are the key in BioDigital Convergence. They will use them to create the feedback circuit, linking a human to a machine.

USING BIOPHOTONS TO CREAT A HUMAN-MACHINE FEEDBACK CIRCUIT

A novel approach to creating a human-machine feedback circuit involves utilizing Ultraweak Photon Emission (UPE), also known as Biophotons, which are naturally emitted by neurons as a byproduct of metabolic processes, particularly those involving reactive oxygen species & ATP production.

These photons correlate with neural activity, oxidative status & Cerebral Energy Metabolism, suggesting a potential informational role in brain function.

The proposed system envisions a Skull-Implantable Photonic Integrated Circuit (PIC) that detects these UPE signals.

The PIC would use an array of optical fibers coupled to waveguides via grating couplers to receive photons, which are then serialized & processed through an optical interferometer to detect Interference Patterns indicative of neural activity.

This allows for the discrimination of emission patterns based on wavelength, with machine learning techniques like principal component analysis (PCA) & Convolutional Neural Networks (CNNs) employed to interpret complex, overlapping patterns in real time.

The feedback circuit could operate in a closed-loop configuration, where the machine interprets the UPE signals to generate commands & the machine can subsequently stimulate the brain with appropriate signals.

This concept is supported by experimental evidence showing that photons can be conducted along neuronal fibers, & that glutamate-induced UPE can be transmitted through axons and neuronal circuits.

https://pmc.ncbi.nlm.nih.gov/articles/PMC10745993/

Furthermore, a theoretical model suggests that axons may act as photonic waveguides, enabling backward propagation of biophotons from post-synaptic to pre-synaptic neurons, which could facilitate a backpropagation-like learning mechanism in the brain.

This mechanism, inspired by stochastic photonic feedback, could allow for information to be relayed across neural networks, potentially enabling adaptive learning processes.

https://www.nature.com/articles/s41598-022-24871-6

The integration of neuromorphic photonic circuits with machine learning offers a promising pathway toward realizing a biologically inspired, energy-efficient human-machine feedback system.

https://www.frontiersin.org/journals/systems-neuroscience/articles/10.3389/fnsys.2025.1597329/full

HUMAN-MACHINE FEEDBACK SYSTEM

A Human-Machine Feedback System is an integrated framework where humans & machines interact through continuous feedback loops to improve performance, decision-making & system outcomes.

HUMAN-MACHINE SYSTEMS (HMS)

These systems are foundational in Human-Machine Systems (HMS), which include a human operator, a machine & an environment, with inputs, outputs, interfaces & feedback mechanisms that allow users to adjust their actions based on system responses.

https://www.capicua.com/blog/human-machine-systems-hms

FEEDBACK LOOPS

The feedback loop is essential for real-time monitoring & control, enabling operators to respond quickly to changing conditions, particularly in industrial settings where HMIs (Human-Machine Interfaces) gather data from controllers like PLCs & present it via visual, interactive screens.

https://blog.airlinehyd.com/human-machine-interface

HUMAN IN THE LOOP

Human-in-the-Loop (HITL) Systems exemplify this approach, where human input is critical for training, monitoring & updating models post-deployment.

https://www.sciencedirect.com/topics/computer-science/human-machine-system

Machine learning techniques for state recognition and auto-tuning in quantum dots

We propose a new paradigm for fully automated experimental initialization through a closed-loop system relying on machine learning and optimization techniques.

We use deep convolutional neural networks to characterize states and charge configurations of semiconductor quantum dot arrays when only measurements of a current−voltage characteristic of transport are available.

https://www.nature.com/articles/s41534-018-0118-7

Transforming energy using quantum dots

Colloidal quantum dots (QDs) have emerged as versatile and efficient scaffolds to absorb light and then manipulate, direct, and convert that energy into other useful forms of energy.

https://pubs.rsc.org/en/content/articlelanding/2020/ee/c9ee03930a

Quantum Dots Are Used To Create Quantum Entanglement Through Entangled Photons

Quantum dots are semiconductor nanostructures that can emit entangled photon pairs, making them a promising candidate for generating entangled photons for quantum communication and computing applications.

These artificial atoms can produce entangled photons on demand, unlike other sources that emit photons at random times.

However, quantum dots often suffer from structural irregularities that can spoil entanglement by causing mismatches in the energies of emitted photon pairs.

To overcome these challenges, researchers have developed methods to tune the internal energy states of quantum dots using a combination of an electric field and mechanical strain.

This tuning can correct asymmetries that usually prevent quantum dots from emitting perfectly entangled photons.

For instance, Daniel Huber and colleagues demonstrated a source of on-demand entangled photon pairs based on GaAs quantum dots, achieving a level of entanglement almost on par with that of parametric-conversion sources.

Moreover, advancements in quantum dot technology have led to the creation of LEDs that can produce entangled photons, potentially enabling their use to encode information in quantum computing.

This technology uses nanotechnology to electrify arrays of pyramid-shaped quantum dots, allowing them to produce entangled photons.

The scalability and precise control over the position of these quantum dot sources are key factors for future quantum technologies.

Quantum dots can also be used in quantum cryptography, where entangled photons from quantum dots have been used to implement quantum key distribution with high fidelity and low error rates.

This demonstrates the viability of quantum dots as light sources for entanglement-based quantum key distribution and quantum networks.

In summary, Quantum Dots Are A Promising Platform For Generating ENTANGLED PHOTONS, with ongoing research addressing the challenges of structural irregularities and aiming to improve the efficiency and reliability of entangled photon generation.

Sources:

Quantum Dots Tuned for Entanglement

https://physics.aps.org/articles/v5/109

Quantum Dots Are Used To Create Quantum Entanglement Through Entangled Photons

Quantum dots are semiconductor nanostructures that can emit entangled photon pairs, making them a promising candidate for generating entangled photons for quantum communication and computing applications.

These artificial atoms can produce entangled photons on demand, unlike other sources that emit photons at random times.

However, quantum dots often suffer from structural irregularities that can spoil entanglement by causing mismatches in the energies of emitted photon pairs.

To overcome these challenges, researchers have developed methods to tune the internal energy states of quantum dots using a combination of an electric field and mechanical strain.

This tuning can correct asymmetries that usually prevent quantum dots from emitting perfectly entangled photons.

For instance, Daniel Huber and colleagues demonstrated a source of on-demand entangled photon pairs based on GaAs quantum dots, achieving a level of entanglement almost on par with that of parametric-conversion sources.

Moreover, advancements in quantum dot technology have led to the creation of LEDs that can produce entangled photons, potentially enabling their use to encode information in quantum computing.

This technology uses nanotechnology to electrify arrays of pyramid-shaped quantum dots, allowing them to produce entangled photons.

The scalability and precise control over the position of these quantum dot sources are key factors for future quantum technologies.

Quantum dots can also be used in quantum cryptography, where entangled photons from quantum dots have been used to implement quantum key distribution with high fidelity and low error rates.

This demonstrates the viability of quantum dots as light sources for entanglement-based quantum key distribution and quantum networks.

In summary, Quantum Dots Are A Promising Platform For Generating ENTANGLED PHOTONS, with ongoing research addressing the challenges of structural irregularities and aiming to improve the efficiency and reliability of entangled photon generation.

Sources:

Quantum Dots Tuned for Entanglement

https://physics.aps.org/articles/v5/109

Observation of the ‘dark exciton’ in CdSe quantum dots

https://link.aps.org/doi/10.1103/PhysRevLett.75.3728

Optical spectroscopy of dark and bright excitons in CdSe nanocrystals in high magnetic fields

https://repository.ubn.ru.nl/bitstream/handle/2066/177408/177408.pdf?sequence=1

Wave function engineering for efficient extraction of up to nineteen electrons from one CdSe/CdS quasi-type II quantum dot

http://pstorage-acs-6854636.s3.amazonaws.com/4185964/ja210312s_si_001.pdf

Dynamic tuning of the bandgap of CdSe quantum dots through redox-active exciton-delocalizing N-heterocyclic carbene ligands

https://par.nsf.gov/servlets/purl/10349811

Ultrafast photoinduced interfacial proton coupled electron transfer from CdSe quantum dots to 4,4-bipyridine

https://www.researchgate.net/profile/Jinquan-Chen-3/publication/288817260_Ultrafast_Photoinduced_Interfacial_Proton_Coupled_Electron_Transfer_from_CdSe_Quantum_Dots_to_44%27-Bipyridine/links/5696f5aa08ae34f3cf1deb19/Ultrafast-Photoinduced-Interfacial-Proton-Coupled-Electron-Transfer-from-CdSe-Quantum-Dots-to-4-4-Bipyridine.pdf

Ultrafast electron transfer from CdSe quantum dots to an [FeFe]-hydrogenase mimic

https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/60c756dc4c89193a40ad48c8/original/ultrafast-electron-transfer-from-cd-se-quantum-dots-to-a-fe-fe-hydrogenase-mimic.pdf

An ultrafast transient absorption study of charge separation and recombination dynamics in CdSe QDs and methyl viologen: Dependence on surface stoichiometry

https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/slct.201800313

Thermally activated delayed photoluminescence from pyrenyl-functionalized CdSe quantum dots

https://par.nsf.gov/servlets/purl/10093439

Electron and hole spin relaxation in CdSe colloidal nanoplatelets

https://pubs.acs.org/doi/10.1021/acs.jpclett.0c03257

Influence of Size and Shape Anisotropy on Optical Properties of CdSe Quantum Dots

https://pubmed.ncbi.nlm.nih.gov/32806736/

Determination of the exciton binding energy in CdSe quantum dots

https://www.osti.gov/servlets/purl/967714-LoakWD/

Excitonic effects in the optical properties of CdSe nanowires

https://arxiv.org/pdf/1002.1562

Relaxation of exciton confinement in CdSe quantum dots by modification with a conjugated dithiocarbamate ligand

https://pubs.acs.org/doi/10.1021/nn1007435

Hydrophilic, hole-delocalizing ligand shell to promote charge transfer from colloidal CdSe quantum dots in water

https://publications.aston.ac.uk/id/eprint/31236/1/2017_JPCC_Ligand_Shell_Promoted_Charge_Transfer_Final_version_of_manuscript.pdf

Direct synthesis of all-inorganic heterostructured CdSe/CdS QDs in aqueous solution for improved photocatalytic hydrogen generation

https://pubs.rsc.org/en/content/articlelanding/2017/ta/c7ta01670k

Rhodamine is in that paper from US naval academy on the Biological Brain Microtubules Interfaced With Semiconductor Qubits.

It's red

Integration of deep learning techniques with biophotonic setups

One of the primary motivations for employing this strategy is the pursuit of higher temporal resolution or increased imaging speed, critical for capturing fine dynamic biological processes.

This article provides an in-depth review of the diverse measurement aspects that researchers intentionally impair in their biophotonic setups, including the point spread function (PSF), signal-to-noise ratio (SNR), sampling density, and pixel resolution.

By deliberately compromising these metrics, researchers aim to not only recuperate them through the application of deep learning networks, but also bolster in return other crucial parameters, such as the field of view (FOV), depth of field (DOF), and space-bandwidth product (SBP).

https://www.nature.com/articles/s41377-024-01544-9?fromPaywallRec=false

They are able to image our heartbeating in 4D!!

They have tested this in a zebrafish!!

Here, we present a deep-learning enhanced light sheet fluorescence microscopy (LSFM) approach that addresses the restoration of rapid volumetric time-lapse imaging with less than 0.03% light exposure and 3.3% acquisition time compared to a typical standard acquisition.

We demonstrate that the convolutional neural network (CNN)-transformer network developed here, namely U-net integrated transformer (UI-Trans), successfully achieves the mitigation of complex noise-scattering-coupled degradation and outperforms state-of-the-art deep learning networks, due to its capability of faithfully learning fine details while comprehending complex global features.

With the fast generation of appropriate training data via flexible switching between confocal line-scanning LSFM (LS-LSFM) and conventional LSFM, this method achieves a three- to five-fold signal-to-noise ratio (SNR) improvement and ~1.8 times contrast improvement in ex vivo zebrafish heart imaging and long-term in vivo 4D (3D morphology + time) imaging of heartbeat dynamics at different developmental stages with ultra-economical acquisitions in terms of light dosage and acquisition time.

https://www.nature.com/articles/s41377-024-01710-z?fromPaywallRec=false

4d in vivo imaging of the heartbeat

Time is the 4th dimension !!!!

Plus the 3d geometries of these nano-heterostructures is the oscillating frequency and that's how they synch frequency and time together 3D morphology + Time = 4D quantum.

IQM launches Halocene, a new quantum computer product line for error correction

IQM Halocene

The new product line is based on an open and modular error correction stack, which will allow end-users to experiment and run different quantum error correction features.

It will start with a 150-qubit system to be delivered by the end of 2026 and extend all the way to 1,000-qubits.

The first release of IQM Halocene will be a 150-qubit quantum computer with advanced error correction functionality. The system will enable users to advance their error correction capabilities, error correction research and to create intellectual property with logical qubits.

In addition, the Halocene product line will allow execution of Noisy Intermediate Scale (NISQ) algorithms and the development of error mitigation techniques.

This release schedule aligns with the company’s ambitious roadmap, which outlines major milestones of quantum error-correction demonstrators and a path to achieve fault-tolerant quantum computing by 2030.

https://meetiqm.com/press-releases/iqm-launches-halocene-a-new-quantum-computer-product-line-for-error-correction/

IMQ Development Roadmap

Technology milestones
(2023 – 2030+)

2025-2026: NISQ

Enhance gate performance, introduce top-tier error reduction (error mitigation and suppression), and deliver NISQ solutions for immediate research applications.

Achieve over 99.94% two-qubit gate fidelities and deploy innovative error-mitigation methods.

2027-2028: QEC Demonstrators

Develop large systems combining QEC and advanced error reduction for early quantum utility in applications like quantum machine learning, simulation, and optimization.

Implement highly efficient QLDPC codes that increase the efficiency compared to surface codes by up to 10 and integrate QEC for both universal quantum computation (i.e. including both Clifford and non-Clifford gates).

2030+: Fault Tolerance

Realize fully QEC-enabled systems with hundreds of high-precision logical qubits, achieving quantum advantage across multiple industries and scale up to 1 Million qubits.

Develop systems with advanced QLDPC codes, novel chip topologies, long-range couplers, and compact packaging for fault-tolerant, large-scale applications.

Enhanced cleanroom facilities will support complex chip fabrication, enabling unique long-range connections and high-performance QEC capabilities.

https://meetiqm.com/technology/roadmap/

Generation of three-dimensional cluster entangled state

https://www.nature.com/articles/s41566-025-01631-2?fromPaywallRec=true

Tket User Guide

https://docs.quantinuum.com/tket/user-guide/manual/manual_backend.html#statevector-and-unitary-simulation-with-tket-backends

All the Emulation of devices is being done on the backend.

Quantinuum's H1 Quantum Processing Unit

A new on-chip cryptographically secure verification protocol for quantum computers was successfully deployed on Quantinuum's H1-1 quantum processor.

"Most of us are theorists working on measurement-based quantum computing and cryptographic protocols that guarantee security and verification. We've had strong theoretical results for years, so naturally, we wanted to see how they perform on real hardware—and the collaboration with Quantinuum offered the perfect opportunity to make that happen."

"We first mapped out the theoretical requirements of our protocol, then tailored it to Quantinuum's H1-1 machine," said Cica. "I was genuinely impressed by the fidelity of their gates and measurements and how easily we could access the device. We pushed it further than we expected—up to 52 nodes—by reusing measured ions from 20 available ions in the trap."

The primary objective of the team's recent efforts was to develop a verification protocol that is cryptographically secure and that is NISQ-friendly, which means that it can be successfully deployed on the quantum computing systems available today.

"This will certainly be relevant for Helios and subsequent generations of our QPUs. As such, it is important for us and our users that we can guarantee a level of trust in the outputs. Verification is a well-established route to doing this, but so far it is a relatively theoretical and abstract field. This collaboration aimed to bridge the gap between theory and hardware to develop a practical verification protocol, bespoke to our machines."

"We took a cryptographic verification protocol that usually requires communication between two devices and made it work entirely on a single chip. The idea is that even if the hardware is noisy or imperfect, it can still verify its own results through built-in tests and randomness."

The team's approach is among the first to enable on-chip verification. This is in stark contrast with other available tools, which require other external systems or two distinct processors to cross-check computations.

"For example, Google's recent Quantum Echoes experiment relied on two separate quantum processors to cross-check results," said Cica. "While this is a powerful consistency test, our method goes a step further: the device verifies itself, without needing a second machine.

"It's a step toward quantum computers that can certify their own results in real-time, using only the technology we already have today."

https://phys.org/news/2025-11-chip-cryptographic-protocol-quantum-results.html

On-Chip Verified Quantum Computation with an Ion-Trap Quantum Processing Unit

Unlike previous cryptographically secure verification protocols, which typically require quantum communication between client and server, our approach is implemented entirely on chip.

This eliminates the need for a quantum capable client, and significantly enhances practicality. We perform tomography to justify the additionally required assumption that the noise is independent of the secret used to prepare the server’s single-qubit states. We quantify the soundness error that may be caused by residual secret dependencies.

We demonstrate our protocol on the 20-qubit Quantinuum H1-1 ion-trap quantum processing unit, using qubit measurements and resets to construct measurement patterns with up to 52 vertices.

To our knowledge, these are the largest verified measurement-based quantum computations performed to date.

Experiments were conducted via Quantinuum Nexus [53] on the Quantinuum H1-1 QPU [54].

https://journals.aps.org/prl/abstract/10.1103/jpms-v3kw

Dude here is how they are emulating the hardware in the cloud!!

Quantinuum Nexus

Quantinuum Nexus is a cloud-based platform that enables users to seamlessly run, review, and collaborate on quantum computing projects.

The platform integrates support for various quantum targets using the TKET quantum programming tools to optimize circuit performance and translation between different targets.

🚨One such target is the Quantinuum machine, H2-1. Each quantum target in nexus is called a BackendConfig and can be CONFIGURED TO ACCESS HARDWARE, EMULATOR OR SIMULATOR!!

Quantinuum Nexus offers different types of jobs that represent a component of your workflow that is running on Nexus-hosted or Quantinuum-hosted emulators.

https://docs.quantinuum.com/nexus/trainings/notebooks/basics/getting_started.html

Quantinuum H1-1

System Model H1 is our first-generation of quantum computers with a single linear architecture and numerous hallmark features that set it apart from other types of quantum computers.

https://www.quantinuum.com/products-solutions/quantinuum-systems/system-model-h1

All the Emulation of devices is being done on the backend

Quantinuum's H1 Quantum Processing Unit

A new on-chip cryptographically secure verification protocol for quantum computers was successfully deployed on Quantinuum's H1-1 quantum processor.

"Most of us are theorists working on measurement-based quantum computing and cryptographic protocols that guarantee security and verification. We've had strong theoretical results for years, so naturally, we wanted to see how they perform on real hardware—and the collaboration with Quantinuum offered the perfect opportunity to make that happen."

"We first mapped out the theoretical requirements of our protocol, then tailored it to Quantinuum's H1-1 machine," said Cica. "I was genuinely impressed by the fidelity of their gates and measurements and how easily we could access the device. We pushed it further than we expected—up to 52 nodes—by reusing measured ions from 20 available ions in the trap."

The primary objective of the team's recent efforts was to develop a verification protocol that is cryptographically secure and that is NISQ-friendly, which means that it can be successfully deployed on the quantum computing systems available today.

"This will certainly be relevant for Helios and subsequent generations of our QPUs. As such, it is important for us and our users that we can guarantee a level of trust in the outputs. Verification is a well-established route to doing this, but so far it is a relatively theoretical and abstract field. This collaboration aimed to bridge the gap between theory and hardware to develop a practical verification protocol, bespoke to our machines."

"We took a cryptographic verification protocol that usually requires communication between two devices and made it work entirely on a single chip. The idea is that even if the hardware is noisy or imperfect, it can still verify its own results through built-in tests and randomness."

The team's approach is among the first to enable on-chip verification. This is in stark contrast with other available tools, which require other external systems or two distinct processors to cross-check computations.

"For example, Google's recent Quantum Echoes experiment relied on two separate quantum processors to cross-check results," said Cica. "While this is a powerful consistency test, our method goes a step further: the device verifies itself, without needing a second machine.

"It's a step toward quantum computers that can certify their own results in real-time, using only the technology we already have today."

https://phys.org/news/2025-11-chip-cryptographic-protocol-quantum-results.html

On-Chip Verified Quantum Computation with an Ion-Trap Quantum Processing Unit

Unlike previous cryptographically secure verification protocols, which typically require quantum communication between client and server, our approach is implemented entirely on chip.

This eliminates the need for a quantum capable client, and significantly enhances practicality. We perform tomography to justify the additionally required assumption that the noise is independent of the secret used to prepare the server’s single-qubit states. We quantify the soundness error that may be caused by residual secret dependencies.

We demonstrate our protocol on the 20-qubit Quantinuum H1-1 ion-trap quantum processing unit, using qubit measurements and resets to construct measurement patterns with up to 52 vertices.

To our knowledge, these are the largest verified measurement-based quantum computations performed to date.

Experiments were conducted via Quantinuum Nexus [53] on the Quantinuum H1-1 QPU [54].

https://journals.aps.org/prl/abstract/10.1103/jpms-v3kw

Dude here is how they are emulating the hardware in the cloud!!

Quantinuum Nexus

Quantinuum Nexus is a cloud-based platform that enables users to seamlessly run, review, and collaborate on quantum computing projects.

The platform integrates support for various quantum targets using the TKET quantum programming tools to optimize circuit performance and translation between different targets.

🚨One such target is the Quantinuum machine, H2-1. Each quantum target in nexus is called a BackendConfig and can be CONFIGURED TO ACCESS HARDWARE, EMULATOR OR SIMULATOR!!

Quantinuum Nexus offers different types of jobs that represent a component of your workflow that is running on Nexus-hosted or Quantinuum-hosted emulators.

https://docs.quantinuum.com/nexus/trainings/notebooks/basics/getting_started.html

Quantinuum H1-1

System Model H1 is our first-generation of quantum computers with a single linear architecture and numerous hallmark features that set it apart from other types of quantum computers.

https://www.quantinuum.com/products-solutions/quantinuum-systems/system-model-h1

Luciferase QDs act as bioluminescent nanotransducers,

Often the choice of BRET source is the bioluminescent protein Renilla luciferase, which catalyzes the oxidation of a substrate, typically coelenterazine, producing an oxidized product in its electronic excited state that, in turn, couples with a proximal fluorophore resulting in a fluorescence emission from the acceptor.

The acceptors pertinent to this discussion are semiconductor quantum dots (QDs), which offer some unrivalled photophysical properties. Amongst other advantages, the QD’s large Stokes shift is particularly advantageous as it allows easy and accurate deconstruction of acceptor signal, which is difficult to attain using organic dyes or fluorescent proteins.

https://pmc.ncbi.nlm.nih.gov/articles/PMC7284562/