Quantum | Truong Tuan Nghia

PQC vs. QKD: Two Lines of Defense Against Quantum Computers

Mon, 15 Jun 2026 00:00:00 +0000

Facing the threat described in , the security community has developed two defenses that differ in almost every respect: Post-Quantum Cryptography and Quantum Key Distribution. People often treat them as competing options, but they actually solve two different classes of problems.

	PQC	QKD
Layer	Software	Hardware
Security basis	A math problem hard even for quantum computers	Laws of quantum physics
Security level	Computational	Information-theoretic, unconditional
Hardware required	Existing CPUs and GPUs	Single-photon sources, SPAD detectors, dedicated optical infrastructure
Deployment	Available now	Requires building new, more complex infrastructure
Standardized protocols	NIST 2024: CRYSTALS-Kyber, CRYSTALS-Dilithium	BB84, BBM92, CV-QKD

PQC: a software upgrade on infrastructure you already have

Post-Quantum Cryptography is still classical: it runs entirely on ordinary CPUs and GPUs, but it is built around mathematical problems that even a quantum computer has no known efficient way to solve, lattice-based cryptography being the leading example. Its biggest advantage is that it can be deployed right now. No new physical infrastructure is needed, only a software update. In 2024, NIST officially standardized CRYSTALS-Kyber for key exchange and CRYSTALS-Dilithium for digital signatures, marking PQC’s move into practical deployment.

Its weakness sits in the nature of computational security itself: it rests on the assumption that no one has yet found an algorithm to break it, not on an absolute proof. A future mathematical breakthrough or a new quantum algorithm could still weaken PQC, even though nothing of the sort has appeared so far.

QKD: security grounded in physics

QKD takes the opposite approach. Instead of encrypting data with a hard-to-solve algorithm, it uses the quantum state of photons themselves to distribute a key, and its security rests on physical law, specifically the no-cloning theorem and the nature of quantum measurement. That security holds regardless of how much computational power an attacker has, including a quantum computer decades from now. This is information-theoretic security, the strongest form of security that exists in theory.

The trade-off is that QKD needs entirely new physical infrastructure: single-photon sources and detectors, high-precision optics, and, as I discuss in my posts on satellite FSO, extreme sensitivity to channel conditions like atmospheric loss and turbulence. Deploying QKD at scale is far more complex and costly than rolling out a PQC software update.

Not one or the other, but both

The consensus among researchers today is not to pick a side, but to combine both. PQC is well suited to protecting broad, everyday infrastructure right away, things like email and web traffic. QKD is better suited to point-to-point links that demand extremely high, long-term-stable security, such as critical government, defense, and financial systems, or future quantum networks that need to carry actual quantum states rather than just classical key material.

The paper I analyzed for my seminar, , makes exactly this point: it focuses on QKD because its security is grounded in physics, without dismissing PQC’s role. The two are complementary, not mutually exclusive.

Why We Need Quantum-Safe Security Today, Not in 2030

Fri, 12 Jun 2026 00:00:00 +0000

“Powerful quantum computers are still a decade away, why worry now?” I hear this reaction often when the topic of quantum threats to encryption comes up, and it is a fairly dangerous misunderstanding. The timeline below explains why.

From theory to a real threat

The story starts in the 1980s, when Richard Feynman and David Deutsch laid the theoretical groundwork for quantum computation. The original idea was fairly simple: use a quantum system to simulate other quantum systems, a task classical computers handle very inefficiently.

The real turning point came in 1994, with Shor’s algorithm. It proved, at least in theory, that a sufficiently powerful quantum computer could factor large integers in polynomial time, while a classical computer needs exponential time for the same task. This genuinely shook the cryptography community, because RSA’s security, along with many other public-key schemes, rests entirely on integer factorization being computationally hard.

In 2019, Google announced Sycamore, demonstrating what is called quantum supremacy: completing a specific computation far faster than the most powerful classical supercomputer of the time. That computation had no practical use, but it was hardware proof that quantum computing was actually advancing, not just a theoretical exercise. Several industry and academic roadmaps now place 2030 to 2035 as the window in which quantum computers could have enough qubits and enough error correction to run Shor’s algorithm at a scale that breaks widely deployed RSA and ECC keys.

What RSA and AES actually depend on

Nearly all of today’s digital security, from HTTPS and VPNs to online banking and digital signatures, depends on the computational hardness of two problems: factoring large integers for RSA, and the discrete logarithm problem on elliptic curves for ECC. On a classical computer, both problems are practically unsolvable within any useful timeframe. Shor’s algorithm breaks precisely that assumption, not because RSA or ECC are weak, but because the underlying computational model changes entirely.

AES, a symmetric cipher, is far less affected. Grover’s algorithm only speeds up brute-force search by a square root factor, so doubling the key length, using AES-256 instead of AES-128, is enough to compensate. RSA and ECC are where the real vulnerability sits.

Harvest now, decrypt later

This is why the quantum threat is not a distant problem. An attacker with resources, whether a nation-state or a well-funded organization, can harvest and store encrypted data right now, even without being able to read it, and simply wait until a quantum computer capable of decrypting it exists.

This strategy is especially dangerous for data with long-term value: medical records, defense secrets, intellectual property, sensitive financial information. If a piece of data needs to stay protected for the next fifteen or twenty years, waiting until quantum computers actually arrive before taking action is already too late. Data harvested today may already be sitting in an attacker’s hands, waiting for its decryption day.

This is the motivation behind two lines of defense being developed in parallel today: Post-Quantum Cryptography, which upgrades software on infrastructure that already exists, and Quantum Key Distribution, which builds security infrastructure grounded in physical law itself. I break down the differences and the complementary role of each in .

FSO and Non-Terrestrial Networks: The Physical Foundation for a Quantum Internet

Wed, 10 Jun 2026 00:00:00 +0000

Building a quantum internet that spans the globe does not start with choosing an algorithm. It starts with a more basic question: how do you send photons over long distances? Right now, the answer is Free-Space Optics, combined with platforms flying at several different altitudes.

What Free-Space Optics actually is

FSO sends an optical signal, usually a laser, directly through air or vacuum, with no physical waveguide involved. It requires line-of-sight: transmitter and receiver have to see each other, with nothing blocking the path. Compared to fiber, FSO has two properties that matter a great deal for quantum applications. First, the path carries almost no significant thermal noise, unlike fiber, where spontaneous Raman scattering inside the core adds background noise of its own. Second, FSO handles single-photon transmission and detection well, which is a hard requirement for encoding a qubit in a photon’s polarization or phase.

Two characteristic sources of error

The laser beam has to be aimed at the receiver with extreme precision. A misalignment of just a few microradians can send the beam missing the receive aperture entirely, especially over distances of hundreds or thousands of kilometers. With a satellite constantly in motion, precise tracking becomes an engineering problem in its own right, requiring a high-precision Attitude Determination and Control System. This is called pointing error.

The second source comes from the atmosphere itself. Local temperature and pressure fluctuations change the air’s refractive index, producing two effects: beam wandering, where the beam drifts off-target unpredictably over time, and scintillation, where the received signal intensity flickers randomly. Both are commonly modeled with the Gamma-Gamma statistical distribution, the standard used across FSO channel research.

Three non-terrestrial platform layers

A quantum internet in the sky does not rely on a single type of satellite. It combines three altitude layers, each playing a different role.

LEO, at 500 to 600 kilometers, gives wide coverage through Starlink-style constellations, but its fast motion means each overpass offers only a short communication window. HAPS, at 19 to 22 kilometers, flies above the cloud layer, avoiding cloud blockage entirely, experiencing less turbulence, covering a stable footprint of roughly 500 kilometers, and often running on solar power. LAPS, below 5 kilometers, is deployed on demand using drones, suited to last-mile key distribution or temporary operation such as disaster response.

The key insight sits with HAPS: flying above the clouds is a strategic advantage, because it eliminates entirely the largest source of atmospheric loss that a ground-based link has to endure, leaving only the much thinner high-altitude atmosphere to contend with.

The shared constraint: SWaP-C

Whatever the layer, every quantum device deployed on a satellite, a HAPS, or a drone runs into SWaP-C: size, weight, power, and cost. This is not a minor engineering footnote, it is a central design constraint. A single-photon source or detector that performs perfectly well on an optical bench is often far too large, too heavy, or too power-hungry to fit on a small satellite or strap onto a drone.

Two ways of extending the network

When two nodes have no direct physical link, they can still be connected through an intermediate node, by performing a Bell-state measurement there on two separately entangled photon pairs. The result is that the two end nodes become entangled with each other, even though they never interacted directly. This is entanglement swapping, and it extends a quantum network’s reach without classical signal amplification, which is fundamentally incompatible with quantum states under the no-cloning theorem.

Another real-world limit is finite-key effects. A LEO overpass lasts only a few minutes, so the number of detected photons is always finite, not infinite as asymptotic theory assumes. With a finite sample, statistical error in estimating QBER and SKR grows significantly, meaning the achievable key rate is always lower than the theoretical limit. Any serious satellite QKD performance analysis has to account for this rather than relying on idealized formulas.

These ideas form the physical foundation for the problem I am actually working on: modeling the tropical satellite FSO channel for a QKD system, covered in more depth in .

From Qubit to Secret Key Rate: The Foundational Concepts of Quantum You Need

Mon, 08 Jun 2026 00:00:00 +0000

You will run into the same seven concepts again and again across my posts on QKD and satellite quantum communication. I am writing them down once here, as a reference point for everything that follows.

Qubit

A classical bit can only be 0 or 1. A qubit works differently: it can exist in a superposition, written as |ψ⟩ = α|0⟩ + β|1⟩, where α and β are complex probability amplitudes. A qubit only settles into 0 or 1 at the moment of measurement. Before that, it genuinely occupies both states at once in a mathematical sense, not merely “unknown but already decided” the way a coin under your palm would be.

Superposition

Superposition is exactly the linear combination of basis states described above. With n qubits, you can represent a superposition of 2ⁿ states at once, and this is the source of the quantum parallelism that algorithms like Shor’s and Grover’s exploit. One point trips people up often: superposition does not mean 2ⁿ computations for free. Reading out a result is still constrained by measurement, so designing a genuinely useful quantum algorithm is a hard problem in its own right, not a simple consequence of having more states available.

Entanglement

When two qubits are entangled, measuring one instantly determines the state of the other, no matter how far apart they are. This is not faster-than-light communication. There is no way to force a measurement outcome to encode a chosen message, so relativity is never violated. What entanglement produces is a non-local correlation that classical mechanics cannot reproduce, and that correlation underlies protocols like BBM92, as well as future distributed quantum networks.

No-Cloning Theorem

This is a rigorous mathematical result: you cannot create an exact copy of a qubit in an unknown state without destroying the original. Why does this matter for QKD? An eavesdropper, conventionally called Eve, cannot secretly copy a key-carrying photon to analyze later. Any attempt to measure or copy it disturbs the original state, and that disturbance leaves a trace that can be detected.

Quantum Key Distribution

QKD is a protocol that lets two parties, conventionally Alice and Bob, generate a shared encryption key whose security rests on quantum physics rather than computational hardness. The best-known protocol, BB84, works like this: Alice sends photons encoded in randomly chosen polarization bases, Bob measures using his own randomly chosen basis, and the two then publicly compare which bases matched, without revealing any measurement outcomes, keeping only the portion of the key where their choices agree.

Quantum Bit Error Rate

QBER is the error rate in the raw key, estimated by publicly comparing a small sample. Channel noise always produces a nonzero baseline QBER. But if Eve is eavesdropping, her own measurement disturbs the quantum state further, pushing QBER abnormally high. This is QKD’s built-in eavesdropping detector: it requires no extra assumptions about what the attacker is capable of.

Secret Key Rate

After discarding the compromised or erroneous portion of the key, through error correction and privacy amplification, what remains is a genuinely usable secret key. SKR is the rate at which this key is produced, measured in bits per second. It depends directly on channel loss and QBER, making it the single most useful number when judging whether a QKD link, satellite or otherwise, is actually viable.

These seven ideas are enough to follow the rest of what I write here: satellite and FSO infrastructure, PQC versus QKD, and channel modeling for the tropics.

The Quantum Applications Landscape: 5 Groups, and Where Does QKD Fit?

Fri, 05 Jun 2026 00:00:00 +0000

Say “quantum technology” and most people picture a quantum computer. In reality it is an ecosystem of several distinct application groups, each with its own problems, software, and hardware. I put together the five groups below while preparing my seminar on .

Application Group	Representative Software	Representative Hardware
Quantum Security	QKD (BB84), liboqs, CRYSTALS-Kyber/Dilithium	QRNG chips, single-photon detectors, QKD devices
Quantum Communication	NetQASM, QuNetSim, entanglement distribution protocols	Quantum memory nodes, entangled photon sources, QKD satellites (Micius)
Quantum-Inspired	D-Wave Leap, TensorFlow Quantum, simulated annealing/branching solvers	Fujitsu Digital Annealer, Toshiba SBM
QC & Simulation	Qiskit, PennyLane, Q#, QuTiP	Superconducting qubits (IBM/Google), trapped ions (IonQ)
Quantum Sensing	Sensor fusion algorithms, VLBI signal processing	Optical lattice clocks, NV-center magnetometers, atom interferometers

Quantum Security uses quantum principles to protect information: generating truly random numbers with a QRNG, distributing keys with unconditional security through QKD, or running post-quantum cryptography such as CRYSTALS-Kyber on ordinary classical hardware, now a NIST standard as of 2024. Quantum Communication takes a different angle, using quantum principles to transmit quantum information itself, qubits and entangled states, between nodes. This is the foundation for a future Quantum Internet, one built not just to share keys but to support distributed quantum computation.

The remaining two groups on the computing side are a different animal entirely. Quantum-Inspired algorithms borrow ideas from quantum mechanics, annealing and simulated branching among them, but run on specialized classical hardware, with no real qubits involved, and they are still effective at combinatorial optimization. QC & Simulation is where actual quantum computers live, built on superconducting qubits or trapped ions, alongside the SDKs used to program and simulate quantum algorithms on them. Quantum Sensing, meanwhile, exploits the extreme sensitivity of quantum states for precise measurement of magnetic fields, time, or distance, with applications spanning astronomical VLBI to navigation where GPS is unavailable.

So where does QKD actually belong

Here is the interesting part: QKD does not fit neatly into a single group. In terms of purpose, it is a security problem, generating and sharing a key that stays secure. In terms of mechanism, though, it is a communication problem, since it requires faithfully transmitting and measuring qubit states across distance, exactly the infrastructure a Quantum Internet needs regardless of what it is ultimately used for.

This is exactly why my own research, modeling satellite FSO channels for QKD, is both a key-security problem and a building block for satellite quantum communication infrastructure more broadly. Two groups that look separate on paper turn out to share the same physical layer underneath.

Quantum Communication for Satellite Technology: From QKD to the Tropical Weather Problem

Mon, 01 Jun 2026 00:00:00 +0000

Quantum Key Distribution lets two parties share an encryption key whose security is guaranteed by quantum physics, not by computational hardness the way classical schemes like RSA or ECC work. The biggest weakness of terrestrial fiber-based QKD is loss: single photons are absorbed and scattered exponentially with distance, which in practice limits fiber QKD to a few hundred kilometers.

Satellites solve this in a completely different way. Instead of sending photons through hundreds of kilometers of fiber, the signal travels through the near-vacuum of space, where loss is very low, and only experiences meaningful attenuation over a short atmospheric segment near the ground. This is why satellite QKD experiments, China’s Micius mission among them, have already demonstrated key distribution over thousands of kilometers, a range fiber alone simply cannot reach.

What degrades the signal over a free-space channel

Satellite-to-ground QKD links typically rely on Free-Space Optics, sending photons through the air via a narrow, collimated laser beam. Three sources of loss and noise matter most. The first is atmospheric loss, from absorption and scattering by air molecules, aerosols, and especially clouds; thick cloud cover alone can introduce more than 20 to 30 dB of loss, enough to fail a session outright. The second is atmospheric turbulence, refractive-index fluctuations driven by temperature gradients that produce scintillation and beam wander, usually modeled with a Gamma-Gamma distribution. The third is background noise, sunlight or ground light entering the receiver, which directly raises the Quantum Bit Error Rate, the metric that ultimately decides whether a session stays secure enough to extract a key.

A problem specific to tropical ASEAN

Most existing satellite QKD research, whether from China or Europe, has been conducted or simulated in temperate climates, where clear-sky ratios are relatively high and stable across seasons. Tropical ASEAN, Vietnam included, looks quite different. Cloud cover stays high nearly year-round, especially through the rainy season, a challenge similar to what optical remote sensing runs into, something I wrote about in my post on . The gap between wet and dry seasons is sharp, directly shrinking the available window for a satellite session. And tropical humidity and aerosols make atmospheric loss hard to estimate using models calibrated for temperate climates in the first place.

This is precisely the research gap I am working on with the team at PTIT’s Quantum Technology & Applications Lab.

A three-state weather model

Rather than simulating the atmosphere continuously, which is computationally expensive and hard to calibrate against real data, we formalize the satellite FSO channel’s weather into three discrete states. A clear state carries low atmospheric loss and mild turbulence, producing a high and stable SKR. A cloud state introduces moderate to high loss that varies with cloud thickness, dropping SKR sharply, sometimes close to zero. A rain state is the harshest, combining the highest loss with increased turbulence, pushing SKR near zero.

For each state we estimate how often it occurs, using regional climate data, along with its corresponding atmospheric loss, and from there compute an effective Secret Key Rate, the time-averaged secure key rate rather than the instantaneous SKR under ideal conditions that much of the literature still assumes.

From model to a working SIKD system

This weather model feeds into a larger pipeline: a Simultaneous Information and Key Distribution system, transmitting classical data and quantum keys at the same time over the same satellite optical hardware. The pipeline has three stages: channel modeling based on loss per weather state combined with Gamma-Gamma turbulence, QBER estimation from the signal-to-noise ratio and receiver characteristics, and finally QKD performance analysis, computing SKR per scenario along with the probability that a session fails outright.

Early results show a clear gap between dry-season and wet-season performance across the ASEAN region. That points to a practical conclusion: real satellite QKD deployments in the tropics need weather-adaptive routing, choosing ground stations or time windows with a higher chance of clear conditions, rather than assuming a fixed channel the way many existing models still do.

I am now extending this to compare several candidate ground stations across Vietnam and the region, and looking at whether real satellite weather data, rather than historical statistics alone, could enable short-term forecasting of usable communication windows. It is a fairly interesting intersection of the two fields I work across in parallel: Earth observation and quantum communication.

Seminar: Quantum Internet in the Sky (Vision, Challenges, Solutions)

Fri, 15 May 2026 00:00:00 +0000

This is a seminar I prepared for a graduate course at SoICT, Hanoi University of Science and Technology, class CH2025A, analyzing the paper “Quantum Internet in the Sky: Vision, Challenges, Solutions & Future Directions” by Phuc V. Trinh and Shinya Sugiura, published in IEEE Communications Magazine in 2024.

The paper envisions a layered Quantum Internet built on satellites and airborne platforms, HAPS and LAPS, combining Free-Space Optics with Quantum Key Distribution. The topic sits exactly at the intersection of two directions I already work in: satellite QKD and FSO at PTIT, and satellite technology through the Master in Space program at USTH.

Foundational concepts

The paper opens with a set of core concepts. A qubit is the unit of quantum information, existing in superposition until measured. Superposition is a linear combination of basis states, allowing parallel computation across 2ⁿ states at once. Entanglement is a non-local correlation between two qubits, where measuring one instantly determines the other’s state regardless of distance. The No-Cloning Theorem states that an unknown qubit cannot be copied without destroying the original.

These four ideas lead directly to QKD, key distribution using quantum states with unconditional security. Two metrics come with it: QBER, the quantum bit error rate that rises abnormally whenever an eavesdropper is present, and Secret Key Rate, the rate at which a usable secret key is produced after error correction and privacy amplification. I explain each of these in more depth in .

The paper’s infrastructure section introduces a second set of concepts around Free-Space Optics and non-terrestrial networks. FSO transmits an optical signal through air or vacuum and requires line-of-sight. Pointing error is the angular misalignment of the laser beam, measured in microradians. Atmospheric turbulence is the refractive-index fluctuation that causes beam wander and scintillation. Three platform layers, LEO, HAPS, and LAPS, span from 500 kilometers down to below 5 kilometers, and every one of them is bound by SWaP-C: size, weight, power, and cost. Entanglement swapping connects two nodes with no direct physical link through a Bell-state measurement at an intermediate node, while finite-key effects remind us that a short overpass yields only a limited number of photons, pushing statistical error above the asymptotic theoretical limit. I cover this full set of concepts in .

Background and motivation

The paper’s second part asks why this topic is urgent now, rather than a purely academic interest. The timeline runs from Feynman and Deutsch in the 1980s, through Shor’s algorithm in 1994 proving RSA could be broken in polynomial time, to Google’s Sycamore in 2019 demonstrating quantum supremacy. Current roadmaps place 2030 to 2035 as the point where quantum computers may become powerful enough to exploit this in practice. The most pressing motivation, though, is the harvest-now-decrypt-later strategy: an attacker can collect encrypted data today, store it, and decrypt it once the technology matures. I go through this timeline in detail in .

Facing that threat, two lines of defense are being developed in parallel. PQC, post-quantum cryptography, operates at the software layer, relies on computational hardness, and can already be deployed using NIST’s 2024 standards, CRYSTALS-Kyber and Dilithium. QKD sits at the hardware layer, relies on physical law, and reaches information-theoretic security at the cost of needing new infrastructure. The paper focuses on QKD while explicitly stating that PQC and QKD complement rather than replace each other. I compare the two in more detail in .

Finally, the paper explains why FSO is the natural platform for QKD. Compared to RF and terrestrial fiber, FSO carries almost no thermal noise, handles single-photon counting well, and, most importantly, needs no trusted relay, which is fiber-based QKD’s central weakness: a single compromised node can collapse the security of an entire link. A single LEO satellite link can span thousands of kilometers with no intermediate station at all, making true end-to-end quantum security achievable. I lay out this argument fully in .

Why this matters for my research

The paper reinforces the theoretical framework behind what I am actually doing at PTIT: modeling atmospheric loss and turbulence for tropical satellite FSO channels, working toward a SIKD system described in . The paper’s three-layer LEO, HAPS, LAPS framework also suggests a natural extension for the three-state weather model I am developing, particularly the LEO-to-HAPS link, where HAPS flies above the cloud layer and avoids cloud-induced loss entirely, facing only the effects of the lower atmosphere.

Source: Phuc V. Trinh, Shinya Sugiura, “Quantum Internet in the Sky: Vision, Challenges, Solutions & Future Directions,” IEEE Communications Magazine, 2024.