UPSC Mains Current Affairs for 10 December 2025

Google’s Quantum Echoes Explained: What It Really Means for Q-Day

December 10, 2025

Google’s Quantum Echoes Latest News

Google’s new Quantum Echoes experiment used a 65-qubit quantum processor to study how information moves around inside a quantum system.
Unlike Google’s 2019 Sycamore experiment, which focused on speed, this work was about understanding how quantum bits behave.
Scientists measured out-of-time-order correlators (OTOC) — tiny echoes that reveal how disturbances travel through a network of qubits.
- Basically, scientists gave the system a tiny “poke,” reversed its evolution, and looked for a small “echo” that came back.
- This echo helped them see how quickly information spreads or gets scrambled among qubits.
These insights can help in studying new materials, superconductors, and chemical reactions.
Even though the research is scientifically important, it does not bring us closer to Q-day — the point when quantum computers could break modern encryption. It poses no threat to security systems today.

Q-Day

Q-day is the future moment when a powerful quantum computer can break today’s commonly used encryption systems.
This doesn’t mean data will be exposed instantly — but anything stolen and stored today could be decoded later once such a machine exists.
- This threat is called “harvest now, decrypt later.”

How Are Governments Preparing

Countries are already working on protections.
The U.S. National Institute of Standards and Technology (NIST) has approved new post-quantum cryptography (PQC) methods designed to stay secure even against quantum computers:
- CRYSTALS-Kyber → for encryption
- Dilithium → for digital signatures
These rely on tough mathematical problems that quantum computers are not expected to crack.
Experts believe breaking RSA-2048 — a widely used encryption standard — will require millions of stable (logical) qubits.
- RSA encryption works by multiplying two huge prime numbers.
- Multiplying them is easy. But figuring out the original primes from the final product is extremely hard — so hard that even supercomputers would need billions of years.
At current progress, this may take 5 to 8 years, so Q-day is still a future risk, not an immediate one.

How Quantum Computers Work

Quantum computers use special units called qubits. Unlike normal bits (0 or 1), qubits can be 0 and 1 at the same time (superposition).
They can also be entangled, meaning a change in one instantly affects another, even far away.
Because of this, quantum computers can test many possibilities at once, making them powerful for certain tasks.

Why Quantum Computers Threaten RSA Encryption

RSA encryption is built on the difficulty of breaking a number into its prime factors — something classical computers take billions of years to do.
But quantum computers can use Shor’s algorithm, which turns the factoring challenge into a search for hidden repeating patterns.
The algorithm uses a special mathematical tool called the Quantum Fourier Transform (QFT) to detect these patterns.
If a quantum computer can run this algorithm on a large scale, it could break RSA encryption exponentially faster than classical computers.

The Problem: Today’s Quantum Computers Are Too Small

Breaking a strong key like RSA-2048 requires enormous quantum machines.
A 2019 study by Google researchers estimated that breaking RSA-2048 needs:
- About 20 million physical qubits
- 8 hours of computation
- Perfect error correction
But today’s biggest quantum machines (Google’s Willow, IBM’s Condor) only have a few hundred noisy qubits.

Why We Need Millions of ‘Logical Qubits’

Physical qubits make many errors.
To perform long, accurate calculations, we need logical qubits — stable units created by combining many physical qubits through error correction.
A future, powerful quantum computer would need millions of these logical qubits.
Right now, we aren’t even close to that technology.

Shor’s Algorithm vs. Quantum Echoes: Why They Are Not the Same

Shor’s algorithm is a mathematical tool that could one day break modern encryption by rapidly factoring large numbers — something classical computers struggle to do. Its goal is computational power.
Quantum Echoes, on the other hand, is a physics experiment. It studies how quantum information spreads and comes back like an “echo” inside entangled particles. Its purpose is scientific understanding, not breaking codes.

How Far Are We From Q-Day

Google’s Quantum Echoes experiment does not make that day arrive sooner.
Instead, it marks progress in understanding how quantum systems behave, not in breaking codes.
The experiment shows that quantum processors are getting better at studying complex interactions inside entangled particles. This is a scientific milestone, not a cybersecurity threat.
While quantum machines are slowly advancing, their biggest potential right now is in understanding nature, chemistry, and materials — not cracking RSA.
The real challenge is making sure our digital systems become quantum-safe before quantum computers eventually reach that power.
The technology is evolving, but so must our defences.

Source: TH

Google’s Quantum Echoes FAQs

Q1: What is Google’s Quantum Echoes experiment?

Ans: Quantum Echoes is an experiment using a 65-qubit processor to study how quantum information spreads and refocuses—showing scientific progress in physics, not a step toward breaking encryption.

Q2: Does Quantum Echoes bring Q-Day closer?

Ans: No. The experiment improves understanding of quantum behaviour but does not advance quantum computers toward the scale required to break modern encryption systems.

Q3: What does Q-Day mean in cybersecurity?

Ans: Q-Day refers to the future moment when a powerful quantum computer could break today’s encryption. It is a long-term concern, not an immediate threat.

Q4: How many qubits are needed to break RSA-2048?

Ans: Experts estimate millions of error-corrected logical qubits are required—far beyond today’s few-hundred-qubit machines like Google’s Willow or IBM’s Condor.

Q5: How are governments preparing for Q-Day?

Ans: Countries are adopting post-quantum cryptography. NIST has standardised PQC algorithms like Kyber and Dilithium to secure communications against future quantum attacks.

India–US Rice Trade: Why Trump’s ‘Dumping’ Claim Doesn’t Add Up

December 10, 2025

India–US Rice Trade Latest News

US President Donald Trump recently alleged that India is “dumping” rice in the US and hurting American farmers, vowing to fix the issue with tariffs. However, trade data contradicts this claim.
The US is not a major rice producer and actually exports more rice than it imports. In 2024–25, US production was only 7.05 million tonnes—far below India’s 150 million tonnes—yet the US still exported 3 million tonnes while importing 1.6 million tonnes.
In value terms, the US imported $1.5 billion worth of rice in 2024, mainly from Thailand, while imports from India were much smaller.
The data shows India’s rice exports to the US are limited, and the US is far from being flooded with Indian rice.

India’s Dominance in Global Rice Exports

India remained the world’s leading rice exporter in 2024–25, shipping 198.65 lakh tonnes (19.86 million tonnes) of rice across multiple categories — basmati, parboiled, non-basmati white, broken and other varieties.
In value terms, exports exceeded $12.95 billion, reinforcing India’s position as the top global supplier, controlling around 40% of international rice trade.
Strong monsoons, competitive pricing and the removal of export restrictions on non-basmati rice boosted the sector.
India produced 150 million tonnes of rice in 2024–25, accounting for 28% of global output, with yields increasing from 2.72 t/ha (2014–15) to 3.2 t/ha (2024–25) due to better seeds, agronomy and irrigation.
India currently supplies rice to over 172 countries, and aims to expand exports to 26 additional markets, including the Philippines, Indonesia, the UK, and Mexico, according to APEDA.

U.S. Threatens Tariffs on Indian Rice

Days before U.S. negotiators arrive in New Delhi, President Donald Trump suggested new tariffs on Indian rice, claiming India was “dumping” rice in the U.S.
However, experts say the move appears aimed at pleasing U.S. farmers rather than reflecting genuine trade concerns.

US Rice Imports: Mostly Premium, Not Low-Value Dumping

The US does not import cheap, low-value rice from India or Thailand. Instead, it buys premium aromatic varieties such as Thai Hom Mali, Jasmine, and Indian basmati—priced much higher than US-exported rice.
These imported varieties cost between $690 and $1,125 per tonne, compared to $560–$675 per tonne for typical US export rice.
Since the US exports more rice than it imports, and its imports consist mainly of high-value specialty rice, claims of India “dumping” cheap rice in the American market do not hold.

Impact of Potential New Tariffs on India’s Rice Exports

India is the world’s biggest rice exporter, shipping 22.5–25 million tonnes annually. In comparison, the US is a very small buyer of Indian rice.

US Share in Indian Exports Is Tiny

Basmati exports (2024–25):
- Total: 60.65 lakh tonnes
- To the US: 2.74 lakh tonnes (≈ 4.5%)
Non-basmati exports:
- Total: 141.30 lakh tonnes
- To the US: 0.61 lakh tonnes (≈ 0.4%)
This trend continues in the current fiscal year as well: the US takes only 1–2% of India’s rice shipments.

Bigger Markets Lie Elsewhere

Basmati: West Asia dominates — Saudi Arabia, Iran, Iraq, UAE.
- In the US, basmati sales are controlled by a few Indian companies like LT Foods, whose "Royal" brand holds 55% of the North American market.
Non-basmati: Africa is the main buyer — Benin, Togo, Côte d’Ivoire, Liberia, Senegal, etc.
- The US is almost irrelevant for this category.

Tariff Impact: Minimal to Negligible

Even if Donald Trump imposes new tariffs, the effect on India will be small because:
- The US is not a major rice market for India.
- Indian exporters are not dependent on the US for volumes or revenue.
- Other export items (shrimps, jewellery, garments) would feel tariffs much more than rice.
Experts believe that the proposed tariff would backfire on the US as:
- Tariffs would barely affect India, which has strong global markets. But they would raise rice prices for U.S. households, hurting consumers.
- The threat looks like election-season messaging to American farmers, not a policy shift.

Source: IE | TH | ET

India–US Rice Trade FAQs

Q1: Is India really ‘dumping’ rice in the US?

Ans: No. India sends mainly premium basmati rice to the US, not cheap varieties. Imports are small and do not harm US producers, so “dumping” is inaccurate.

Q2: How important is the US market for India’s rice exports?

Ans: Not very. The US accounts for only about 3% of India’s total rice exports. India exports rice to more than 170 countries, making its markets highly diversified.

Q3: Does India export cheap rice to the US?

Ans: No. The US imports high-value aromatic rice like basmati from India and jasmine from Thailand. These are premium products, not low-priced dumped varieties.

Q4: Would US tariffs hurt India’s rice exporters?

Ans: Only marginally. Since the US is a small buyer and India has strong demand elsewhere, new tariffs would not significantly affect India’s overall rice export earnings.

Q5: Why would new US tariffs impact American consumers more?

Ans: Because the US relies on imports for specialty rice, tariffs would raise retail prices for American households, making rice costlier without reducing India’s export momentum.

One Nation One Licence – India’s Proposed Framework to Balance AI Innovation and Copyright

December 10, 2025

One Nation One Licence Latest News

With the rapid rise of Artificial Intelligence (AI) and Large Language Models (LLMs) like ChatGPT, concerns have intensified over the use of copyrighted content for AI training without consent or remuneration.
Globally, this has triggered litigation, policy debates, and regulatory uncertainty due to intersection of technology, IPR, innovation, and regulation; the role of the State in rate regulation and compulsory licensing.
In this backdrop, a Department for Promotion of Industry and Internal Trade (DPIIT)-led committee has released a working paper proposing a statutory licensing framework to balance AI innovation with copyright protection in India.

Key Proposal - ‘One Nation, One Licence, One Payment’

Mandatory blanket licence for AI training:
- All AI developers must pay royalties for using copyrighted works in AI training.
- No opt-out mechanism for freely available online content.
- Model inspired by compulsory licensing in radio broadcasting under Indian copyright law.
Rejection of voluntary licensing:
- The committee rejects bilateral licensing deals (e.g., OpenAI–Associated Press).
- Reasons are high transaction costs, unequal bargaining power, and marginalisation of small creators and startups.
- Voluntary licensing is seen as favouring big tech and big publishers only.

Institutional Mechanism - CRCAT

A new umbrella non-profit body (Copyright Royalties Collective for AI Training [CRCAT]) to be established under the Copyright Act, 1957.
Functions of the body include collecting royalties from AI companies, distributing proceeds among copyright holders, etc.
Membership: Only organisations (not individuals), one member per class of work.
Coverage can expand gradually to unorganised sectors.

Royalty Determination Framework

Government-appointed rate-setting committee:
- Composition: Senior government officers, legal experts, economic and financial experts, AI and emerging technology experts, AI developers’ and CRCAT representatives.
- Powers: Fix fair, transparent, predictable rates; review rates every three years; decisions subject to judicial review.
Likely pricing model:
- Flat rate preferred initially.
- Royalty as a percentage of gross global revenue earned from commercialised AI systems (excluding taxes).

Retroactive Application of Royalties

Royalties to apply retrospectively: AI developers already using copyrighted works and earning revenue must pay past dues.
Justification:
- Ensures fairness and accountability.
- Not punitive, but corrective to restore balance in the creative ecosystem.

Transparency and Burden of Proof

Data disclosure by AI developers:
- Mandatory submission of a ‘Sufficiently Detailed Summary’ of datasets used.
- Includes:
  - Type of data (text, image, music, audiovisual)
  - Source (social media, publications, libraries, public datasets, proprietary data)
  - Nature of data usage
Distribution of royalties: CRCAT to distribute funds proportionally based on extent of usage, heavily used categories (news, music, audiovisual) receive higher shares.
Legal presumption: In litigation, content owners claim it is presumed valid. Burden shifts to AI developers to disprove misuse or non-payment.

Stakeholder Responses

Supporters (Committee view):
- Ensures non-discriminatory access to training data
- Prevents concentration of royalties among a few big players
- Creates a predictable legal environment for AI development
Opponents:
- NASSCOM:
  - Calls forced royalties a “tax on innovation”
  - Supports opt-out mechanisms for content creators
Creative industry concerns:
- Government-fixed rates are globally unprecedented
- Fear undervaluation of premium content

Challenges in the Proposed Framework and Way Forward

Risk of over-regulation stifling AI innovation: Ensure robust stakeholder consultation.
Administrative complexity in royalty distribution: Fine-tune royalty rates to avoid discouraging AI startups.
Resistance: From both AI firms (cost burden) and content creators (flat-rate concerns). Strong judicial oversight to prevent arbitrariness.
India becoming a global outlier in AI copyright regulation: Harmonisation with global AI governance norms.

Conclusion

India’s proposed mandatory blanket licensing regime for AI training represents a bold and interventionist approach to reconciling innovation with copyright protection.
By institutionalising royalty payments through a statutory mechanism, the Centre aims to ensure equitable compensation for creators while maintaining open access to training data for AI developers.
The success of this model will ultimately depend on rate rationality, transparency, and adaptive governance, making it a critical test case for AI regulation in the Global South.

Source: TH | IE

One Nation One Licence FAQs

Q1: What is the rationale behind India’s proposed “One Nation, One Licence, One Payment” framework for AI training?

Ans: It seeks to balance AI innovation and copyright protection by mandating a statutory blanket licence ensuring equitable compensation to all copyright holders.

Q2: Why has the DPIIT-led committee rejected voluntary licensing agreements between AI developers and content creators?

Ans: Due to high transaction costs, unequal bargaining power, and its tendency to favour large AI firms and major publishers.

Q3: What is the role of the Copyright Royalties Collective for AI Training (CRCAT) in the proposed framework?

Ans: CRCAT will function as a centralised, government-designated body to collect, manage, and proportionally distribute AI training royalties.

Q4: What is the significance of applying royalties retrospectively to AI systems?

Ans: Retroactive royalties aim to ensure fairness and accountability by requiring commercially successful AI developers to compensate creators for past use of copyrighted works.

Q5: How does the proposed Indian model of AI copyright regulation differ from global practices?

Ans: Unlike global voluntary or negotiated models, India proposes government-fixed statutory royalty rates, which may ensure equity but risk over-regulation.

India’s Transport Crisis Reveal Structural Gaps – Explained

December 10, 2025

Transport Crisis Latest News

India recently witnessed two major transport disruptions: severe overcrowding on Bihar-bound trains during October-November, and mass cancellation of Indigo flights in December.
The events raise critical questions on pricing policies, regulatory oversight, monopolies, and the role of the state in ensuring accessible and efficient transport services.

Demand Pressures and the Strain on Public Transport

During Chhath Puja and the Bihar elections, lakhs of migrants attempted to return home, producing a sharp, sudden demand shock for long-distance trains.
With prices kept low for welfare purposes and limited train availability, passengers faced extreme overcrowding, unsafe travel conditions, and inhospitable unreserved compartments.
Economic theory suggests that rising demand should push up prices to equilibrate the market.
However, in essential public services like railways, artificially low prices are a welfare mandate.
The resulting excess demand exposes the underinvestment in public transport infrastructure, rather than a pricing failure.
Why Raising Prices Is Not the Solution
- Critics often argue that low fares create inefficiency. However, the core issue is inadequate supply, not affordability.
- For essential sectors, health, education, and public transport, low pricing is integral to welfare. What is missing is state-led expansion in capacity.

Constraints of a Neo-Liberal Fiscal Framework

Fiscal Limits on Public Investment
- India’s fiscal rules constrain government spending, preventing large-scale expansion of railway capacity.
- Strict deficit targets limit the ability to build additional trains, add new routes, or expand infrastructure.
Impact on Public Welfare
- Thus, the state is forced into a paradox:
- Keeping prices low to maintain welfare,
- But it lacks the fiscal bandwidth to expand services.
This leads to systemic overcrowding, service degradation, and periodic crises.

Private Sector Vulnerabilities: The Indigo Flight Crisis

In December, Indigo, India's dominant private airline, cancelled a large number of flights due to regulatory issues, creating a supply shock. This triggered:
- Stranded passengers
- Sharp spike in airfares across airlines
- Market-wide disruption, despite the issue originating in one firm
This is because Indigo holds a near-monopoly in several sectors of the Indian aviation market.
In a competitive market, one airline’s supply cut would not cause such widespread chaos. The episode underscores the need for regulatory oversight to prevent monopolistic dominance.

Common Structural Thread Between the Crises

At first glance, the train overcrowding and airline cancellations seem unrelated, one arising from public sector limitations, the other from private sector dominance. But both crises stem from a single underlying framework:
Underinvestment in essential public services
- Public transport is priced low for welfare reasons, but cannot expand sufficiently under strict fiscal rules.
Overreliance on deregulated private markets
- Private airlines operate with concentrated market power, enabling fare spikes and system-wide disruption when one firm fails.
Together, these factors reflect the constraints of a neo-liberal policy model, where the state is discouraged from expanding welfare services and private monopolies grow unchecked.
The result is recurring transport crises affecting millions.

Way Forward

The lessons from recent events point to three clear policy needs:
- Expand public investment in railways and essential transport infrastructure.
- Strengthen regulatory oversight of private operators, especially monopolistic entities.
- Reassess fiscal rules to allow higher spending in welfare-critical sectors.
Transport is not just an economic service; it is a public good.
Ensuring reliability, affordability, and resilience requires a balanced model where both state capacity and market behaviour are aligned with public welfare.

Source: TH

Transport Crisis FAQs

Q1: What caused overcrowding in Bihar-bound trains?

Ans: A sudden festive and election-driven surge in passengers overwhelmed limited railway capacity.

Q2: Why didn’t railways raise fares to reduce demand?

Ans: Rail fares are kept low as a welfare measure, making capacity expansion, not price increases, the solution.

Q3: What led to mass Indigo flight cancellations?

Ans: Regulatory non-compliance by Indigo triggered a supply shock and widespread cancellations.

Q4: Why did airfares rise sharply after the cancellations?

Ans: Indigo’s dominant market position allowed fare inflation across the aviation sector.

Q5: What common issue links both crises?

Ans: Both reveal structural weaknesses, underinvestment in public transport and inadequate regulation of private monopolies.