Events & Promotions
|
|
GMAT Club Daily Prep
Thank you for using the timer - this advanced tool can estimate your performance and suggest more practice questions. We have subscribed you to Daily Prep Questions via email.
Customized
for You
Track
Your Progress
Practice
Pays
Not interested in getting valuable practice questions and articles delivered to your email? No problem, unsubscribe here.
May 0111:00 AM PDT
-12:00 PM PDT
Free- full-length test + 15 concept videos + 150+ short videos + study plan!
May 0312:30 AM EDT
-01:30 AM EDT
Learn how Kamakshi achieved a GMAT 675 with an impressive 96th %ile in Data Insights. Discover the unique methods and exam strategies that helped her excel in DI along with other sections for a balanced and high score.
24 Aug 2025, 21:46
Kudos
Bookmarks
The design of public transportation systems in large metropolitan areas illustrates how complex networks balance accessibility, cost, and speed. In highly populated cities such as New York and Tokyo, subway lines average 8–10 stations per mile, whereas newer, automobile-oriented cities like Phoenix may feature fewer than four. Yet the growth in station count is sub-linear: when a city’s population doubles, the number of stops typically rises by only about 60 percent. Transit planners therefore concentrate new stations in dense commercial corridors, where ridership and fare revenue justify the expense, while leaving outlying zones with wider stop spacing. The resulting pattern creates a network that expands with population but avoids the financial and scheduling penalties of building a perfectly uniform grid.
A comparable trade-off shapes biological neural networks. Across mammals, total neuron count increases with brain volume, but the average number of synaptic connections per neuron declines in larger brains. A mouse neuron might link to thousands of partners, whereas an elephant neuron connects to only a few hundred. This phenomenon, termed neural scaling, limits both the metabolic cost of maintaining long-range axons and the signal-propagation delays that would arise if every additional neuron established the same density of links. Computational studies show that such tapered connectivity lets big brains support greater absolute processing power without incurring an exponential rise in wiring length and energy demand.
Systems scientist Deborah Gordon argues that the two cases exemplify a universal principle of network optimization. Whether engineers map subway routes or neurons self-organize during development, each system must weigh the benefits of dense connectivity—short travel times, rapid information flow—against constraints of energy, space, and time. These trade-offs yield scaling laws that echo across domains: the most efficient large networks are neither maximally connected nor minimally built but instead occupy a mathematically predictable middle ground of “just-enough” links.
According to the passage, the sub-linear relationship between population size and subway-station count most directly implies that
A. cities with larger populations tend to have fewer subway stations per resident than smaller cities.
B. station density remains constant regardless of a city’s population growth.
C. the total length of a subway network is independent of the number of stations it contains.
D. planners in smaller cities deliberately avoid building stations in their most crowded corridors.
E. line extensions in rapidly growing cities are constructed primarily in low-demand peripheral zones.
A comparable trade-off shapes biological neural networks. Across mammals, total neuron count increases with brain volume, but the average number of synaptic connections per neuron declines in larger brains. A mouse neuron might link to thousands of partners, whereas an elephant neuron connects to only a few hundred. This phenomenon, termed neural scaling, limits both the metabolic cost of maintaining long-range axons and the signal-propagation delays that would arise if every additional neuron established the same density of links. Computational studies show that such tapered connectivity lets big brains support greater absolute processing power without incurring an exponential rise in wiring length and energy demand.
Systems scientist Deborah Gordon argues that the two cases exemplify a universal principle of network optimization. Whether engineers map subway routes or neurons self-organize during development, each system must weigh the benefits of dense connectivity—short travel times, rapid information flow—against constraints of energy, space, and time. These trade-offs yield scaling laws that echo across domains: the most efficient large networks are neither maximally connected nor minimally built but instead occupy a mathematically predictable middle ground of “just-enough” links.
According to the passage, the sub-linear relationship between population size and subway-station count most directly implies that
A. cities with larger populations tend to have fewer subway stations per resident than smaller cities.
B. station density remains constant regardless of a city’s population growth.
C. the total length of a subway network is independent of the number of stations it contains.
D. planners in smaller cities deliberately avoid building stations in their most crowded corridors.
E. line extensions in rapidly growing cities are constructed primarily in low-demand peripheral zones.
24 Aug 2025, 21:46
Kudos
Bookmarks
Official Solution:
The design of public transportation systems in large metropolitan areas illustrates how complex networks balance accessibility, cost, and speed. In highly populated cities such as New York and Tokyo, subway lines average 8–10 stations per mile, whereas newer, automobile-oriented cities like Phoenix may feature fewer than four. Yet the growth in station count is sub-linear: when a city’s population doubles, the number of stops typically rises by only about 60 percent. Transit planners therefore concentrate new stations in dense commercial corridors, where ridership and fare revenue justify the expense, while leaving outlying zones with wider stop spacing. The resulting pattern creates a network that expands with population but avoids the financial and scheduling penalties of building a perfectly uniform grid.
A comparable trade-off shapes biological neural networks. Across mammals, total neuron count increases with brain volume, but the average number of synaptic connections per neuron declines in larger brains. A mouse neuron might link to thousands of partners, whereas an elephant neuron connects to only a few hundred. This phenomenon, termed neural scaling, limits both the metabolic cost of maintaining long-range axons and the signal-propagation delays that would arise if every additional neuron established the same density of links. Computational studies show that such tapered connectivity lets big brains support greater absolute processing power without incurring an exponential rise in wiring length and energy demand.
Systems scientist Deborah Gordon argues that the two cases exemplify a universal principle of network optimization. Whether engineers map subway routes or neurons self-organize during development, each system must weigh the benefits of dense connectivity—short travel times, rapid information flow—against constraints of energy, space, and time. These trade-offs yield scaling laws that echo across domains: the most efficient large networks are neither maximally connected nor minimally built but instead occupy a mathematically predictable middle ground of “just-enough” links.
According to the passage, the sub-linear relationship between population size and subway-station count most directly implies that
A. cities with larger populations tend to have fewer subway stations per resident than smaller cities.
B. station density remains constant regardless of a city’s population growth.
C. the total length of a subway network is independent of the number of stations it contains.
D. planners in smaller cities deliberately avoid building stations in their most crowded corridors.
E. line extensions in rapidly growing cities are constructed primarily in low-demand peripheral zones.
(A) Correct Answer: The passage states that when a city’s population doubles, the number of stations rises by only about 60 percent, so stations grow more slowly than population. This means there are fewer stations per resident in a larger city, matching option A.
(B) Incorrect: If station density remained constant, station count would rise in direct proportion to population, which the passage explicitly rejects.
(C) Incorrect: The passage discusses station density relative to population, not the relationship between track length and station count.
(D) Incorrect: The text says smaller, automobile-oriented cities already have wider stop spacing; it does not claim their planners “avoid” dense corridors.
(E) Incorrect: The passage states that new stations concentrate in high-demand areas, not primarily in low-demand outskirts.
Answer: A
The design of public transportation systems in large metropolitan areas illustrates how complex networks balance accessibility, cost, and speed. In highly populated cities such as New York and Tokyo, subway lines average 8–10 stations per mile, whereas newer, automobile-oriented cities like Phoenix may feature fewer than four. Yet the growth in station count is sub-linear: when a city’s population doubles, the number of stops typically rises by only about 60 percent. Transit planners therefore concentrate new stations in dense commercial corridors, where ridership and fare revenue justify the expense, while leaving outlying zones with wider stop spacing. The resulting pattern creates a network that expands with population but avoids the financial and scheduling penalties of building a perfectly uniform grid.
A comparable trade-off shapes biological neural networks. Across mammals, total neuron count increases with brain volume, but the average number of synaptic connections per neuron declines in larger brains. A mouse neuron might link to thousands of partners, whereas an elephant neuron connects to only a few hundred. This phenomenon, termed neural scaling, limits both the metabolic cost of maintaining long-range axons and the signal-propagation delays that would arise if every additional neuron established the same density of links. Computational studies show that such tapered connectivity lets big brains support greater absolute processing power without incurring an exponential rise in wiring length and energy demand.
Systems scientist Deborah Gordon argues that the two cases exemplify a universal principle of network optimization. Whether engineers map subway routes or neurons self-organize during development, each system must weigh the benefits of dense connectivity—short travel times, rapid information flow—against constraints of energy, space, and time. These trade-offs yield scaling laws that echo across domains: the most efficient large networks are neither maximally connected nor minimally built but instead occupy a mathematically predictable middle ground of “just-enough” links.
According to the passage, the sub-linear relationship between population size and subway-station count most directly implies that
A. cities with larger populations tend to have fewer subway stations per resident than smaller cities.
B. station density remains constant regardless of a city’s population growth.
C. the total length of a subway network is independent of the number of stations it contains.
D. planners in smaller cities deliberately avoid building stations in their most crowded corridors.
E. line extensions in rapidly growing cities are constructed primarily in low-demand peripheral zones.
(A) Correct Answer: The passage states that when a city’s population doubles, the number of stations rises by only about 60 percent, so stations grow more slowly than population. This means there are fewer stations per resident in a larger city, matching option A.
(B) Incorrect: If station density remained constant, station count would rise in direct proportion to population, which the passage explicitly rejects.
(C) Incorrect: The passage discusses station density relative to population, not the relationship between track length and station count.
(D) Incorrect: The text says smaller, automobile-oriented cities already have wider stop spacing; it does not claim their planners “avoid” dense corridors.
(E) Incorrect: The passage states that new stations concentrate in high-demand areas, not primarily in low-demand outskirts.
Answer: A
30 Aug 2025, 08:45
Kudos
Bookmarks
I don’t quite agree with the solution. Larger cities(size) and more populated cities are different as per my undertanding. it was never mentioned anywhere in the 1st para of any relationship between city size(area) and station count.
Though,in the 2nd para there was a mention with brain size and neuron, but that doesn't qualify to be this question's answer.
What am I missing here, please correct me..
Though,in the 2nd para there was a mention with brain size and neuron, but that doesn't qualify to be this question's answer.
What am I missing here, please correct me..
